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In , I described the wild ride that the price of risk took in 2020, with equity risk premiums and default spreads initially sky rocketing, as the virus led to global economic shutdowns, and then just as abruptly dropping back to pre-crisis levels over the course of the year. As stock and bond markets went through these gyrations, it should come as no surprise that the same forces were playing out in other markets as well. In this post, I will take a look at these other markets, starting with a way of dividing investments into assets, commodities, currencies and collectibles that I find useful in thinking about what I can (and cannot) do in those markets, and then reviewing how these markets performed during 2020. As I do this, there is no way that I can evade discussing Bitcoin and other crypto assets, which continued to draw disproportionate (relative to their actual standing in markets) attention during the year, and talking about what 2020 taught us about them.

Investments: Classifications and Consequences

In , focused on bitcoin, I argued that all investments can be categorized into one of four groups, assets, commodities, currencies and collectibles, and the differences across these group are central to understanding why pricing is different from value, and what sets investing apart from trading.

The Divide: Assets, Commodities,ÌýCurrencies and Collectibles

If you define an investment as anything that you can buy and hold, with the intent of making money, every investment has to fall into at least one of these groupings:

Assets: An asset has expected cash flows that can either be contractually set (as they are with loans or bonds), residual (as is the case with an equity investment in a business or shares in a publicly traded company) or even conditional on an event occurring (options and warrants).ÌýCommodities: A commodity derives its value from being an input into a process to produce a item (product or service) that consumers need or want. Thus, agricultural products like wheat and soybeans are commodities, as are industrial commodities like iron ore and copper, and energy-linked commodities like oil and natural gas.ÌýCurrencies: A currency serves three functions. It is a measure of value (used to tell you how much a product or service costs), a medium of exchange (facilitating the buying and selling of products and services) and a store of value (allowing people to save to meet future needs). While we tend to think of fiat currencies like this Euro, the US dollar or the Indian rupee, the use of currency pre-dates governments, and human beings have used everything from to Ìýas currency.Collectibles: A collectible's pricing comes from the perception that it has value, driven by tastes (artwork) and/or scarcity (rare items). There are a range of items that fall into this grouping from fine art to sports memorabilia to precious metals.While most investments fall into one of these buckets, there are some that can span two or more, and you have to decide which one dominates. Take gold, for instance, whose ductility and malleability makes it a prized commodity to jewelers and electronics makers, but whose scarcity and indestructibility (almost) make it even more attractive as a currency or a collectible, With bitcoin, even its most ardent promoters seem to be divided on whether the end game is to create a currency or a collectible, a debate that we will revisit at the end of this post.
Price versus ValueThe classification of investments is key to understanding a second divide, one that I have repeatedly returned to in my posts, between value and price.
If the value of an investment is a function of its cashflows and the risk in those cash flows, it follows that only assets can be valued. ThoughÌýÌýcommodities can sometimes Ìýbe roughly valued with macro estimates of demand and supply, they are far more likely to be priced.ÌýCurrencies and collectible can only be priced, and the determinants of their pricing will vary:Commodity Pricing: With commodities, the pricing will be determined by two factors. The first is the demand for and supply of the commodity, given its usage, with shocks to either causing price to change. Thus, it should come as no surprise that the oil embargo in the 1970s caused oil prices to surge and resulted in higher prices for orange juice. The second is storability, with storage costs ranging from minimal with some commodities Ìýto prohibitive for others. In general, storable commodities provide buyers with the option of buying when prices are low, and storing the commodity, and for that reason, futures prices of storable commodities are tied to spot prices and storage costs.Currency Pricing: Currencies are priced against each other, with the prices taking the form of "exchange rates". In the long term, that pricing will be a function of how good a currency is as a medium of exchange and a store of value, with better performing currencies gaining at the expense of worse performing ones. On the first dimension (medium of exchange) currencies that are freely exchangeable (or even usable) anywhere in the world (like the US dollar, the Euro and the Yen) will be priced higher than currencies that do not have that reach (like the Indian rupee or the Peruvian Sul). On the second (store of value), it is inflation that separates good from bad currencies, with currencies with low inflation (like the Swiss franc) gaining at the expense of currencies with higher inflation (like the Zambian kwacha).ÌýCollectible Pricing: Most collectibles are pure plays on demand and supply, with no fundamentals driving the price, other than scarcityÌýand desirability, real or perceived. Paintings by Picasso, Monet or Van Gogh are bought and sold for millions, because there are collectors and art lovers who see them as special works of art, and their supply is limited. Adding to the allure (and pricing) of collectibles is their longevity, reflected in their continuous hold on investor consciousness. It should come as no surprise that gold's, because it brings together all three characteristics; it's scarcity comes from nature, its desirability comes from in many forms and it has been .I capture these differences in the table below:In short, assets can be both priced and value, commodities can be roughly valued but are mostly priced and currencies and collectibles can only be priced.
Investing versus TradingThe essence of investing is assessing value, and buying assets that trade at prices below that value, and selling assets that trade at more. Trading is far simpler and less pretentious, where successful trading requires one thing and one thing only, buying at a low price and selling at a higher one. If you agree with those definitions, it then follows that you can invest only in assets (stocks, bonds, businesses, rental properties) and that you can only trade commodities, currencies and collectibles. ÌýDrawing on a table that I have used in prior posts (and I apologize for reusing it), here is my contrast between investing and trading:
Note that I am not passing judgment on either, since your end game is to make money, whether you are an investor or a trader, and the fact that you made money following the precepts of value investing and did fundamental analysis does not make you better or more worthy than your neighbor who made the same amount of money, buying and selling based upon price and volume indicators.

Commodities

With that lengthly lead in, let's look at what 2020 brought as surprises to the commodity market. As the virus caused a global economic shut down, there were severe disruptions to the demand for some commodities, as usage decreased, and to the supply of others, as production facilities and supply chains broke down. During the course of 2020, I kept track continuously of two commodities, copper and oil, both economically sensitive, and widely traded.Ìý

Note that the ups and downs of oil and copper not only follow the same time pattern, but closely resemble what stocks were doing over the same periods, but the changes are more exaggerated (up and down) with oil than with copper. Both oil and copper dropped during the peak crisis weeks (February 14 through March 23, 2020), but while copper not only recouped its losses and was up almost 26% over the course of the year, oil remains more than 20% below the start-of-the-year numbers. Note also the odd phenomenon on April 20, where West Texas crude prices dropped below zero, as traders panicked about running out of storage space for oil in the US.

Expanding more broadly and looking at a basket of commodities, we can trace out the same effects. In the graph below, I look at three commodity indices, the S&P World Commodity Index (WCI), which is a production-weighted index of commodity futures, the S&P GSCI Index, an investable version that includes the most liquid commodity futures, and the S&P GSCI Agricultural Index, a weighted average of agricultural commodity futures.

The broad commodity indices (WCI and GSCI) saw significant drops between February 14 and March 23, and recoveries in the months after, mirroring the oil and copper price movements. Agricultural commodity futures were far less affected by the crisis, with only a small drop during the crisis weeks, and delivered the best overall performance for the year.

Currencies

In a year during which financial markets had wild swings, and commodity prices followed, it should come as no surprise that currency markets also went through turbulence. In the graph below, I look at the movements of a select set of currencies over 2020, all scaled to the US dollar to allow for comparability:

The dollar strengthened against all of the currencies between February 14 and March 23, but over the course of the year, it depreciated against the Euro, Yen and the Yuan, was mostly flat against the British pound and Indian rupee and gained significantly against the Brazilian Real. Looking at the US dollar’s movements more broadly, Ìýyou can see the effects of 2020 by looking at the Us Ìýmovement relative to developed market and emerging market currencies in the graph below:

In the crisis weeks (2/14 to 3/23), the US dollar gained against other currencies, but more so against emerging market currencies than developed markets ones. In the months afterwards, it gave back those gains to end the year flat against emerging market currencies and down about 5.5% against developed market currencies.

Collectibles

During crises, collectibles often see increased demand, as fear about the future and a loss of faith in institutions (central banks, governments) leads people to see refuge in investments that they believe will outlast the crisis. Given the history of gold and silver as crisis assets, I start by looking at gold and silver prices in 2020;

Both gold and silver had strong years, with gold up 24.17% and silver up 46.77% during the year, but gold played the role of crisis asset better, with its price dropping only 5.19% in the crisis weeks from February 14 to March 23, beating out almost every other asset class in performance during the period. Silver dropped by 29.34% during that same period, but while its subsequent rise more than made up for that drop, on the narrow measure of crisis asset, it did not perform as well as gold.

The year (2020) had mixed effects on other collectible markets. Fine art, for itself, built around in-person auctions of expensive art works saw sales plummet in the early months of 2020, as shutdowns kicked in, but saw a towards the end of the year. Notwithstanding this development, overall sales of art dropped in 2020, and transactions decreased, especially in the highest-priced segments.Ìý

Cryptos

It would be impossible to complete this post without talking about bitcoin, which as it has for much of the decade, continued to dominate discussions of markets and investments. Looking at this graph of bitcoin since its inception, you can see its meteoric rise:

There are clearly many who have been enriched during this rise, and quite a few who have lost their shirts, but any discussion of bitcoin evokes more passion than reason. There are some who believe so intensely in bitcoin that any critique or viewpoint that is contrary to theirs evokes an almost hysterical overreaction. On the other hand, there are others who view bitcoin as speculation run amok, with the end game destined to be painful. At the risk of provoking both sides, I want to start with a fundamental question of whether bitcoin is an asset, a commodity, a currency or a collectible. Even among its strongest supporters, there seems to be no consensus, with the biggest split being between those who argue that it will become a dominant currency, replacing fiat currencies in some markets, and supplementing them in others, and those who claim that it is a gold-like collectible, deriving its pricing from crises and loss of faith in fiat currencies. You could argue that this divide has existed from its creation in 2008, both in terminology (you mine for bitcoin, just as you do for gold) and in its design (an absolute limit on its numbers, creating scarcity). There are even some who believe that the block chain technology that is at the heart of bitcoin can make it a commodity, with the price rising, as block chains find their place in different parts of the economy. Here is my personal take:

Bitcoin is not an asset. I know that you can create securities denominated in bitcoin that have contractual or residual Ìýcash flows, but if you do so, it is not bitcoin that is the asset, but the underlying contractual claim. Put simply, when you buy a dollar or euro denominated bond, it is the bond that is the asset, not the currency of denomination.Bitcoin is not a commodity. It is true that block chains are finding their way into different segments of the economy and that the demand for block chains may grow exponentially, but bitcoin does not have a proprietary claim to block chain technology. In fact, you can utilize block chains with fiat currencies or other crypto currencies, and many do. There are some cryptos, like ethereum, that are , and with those crypto currencies, there is a commodity argument that can be made.Bitcoin is a currency, but it is not a very good one (at least at the moment): Every year, since its inception, we have been told that Bitcoin is on the verge of a breakthrough, where sellers of products and services will accept it as payment for goods and services, but twelve years after its creation, Ìýits acceptance remains narrow and limited. There are simple reasons why it has not acquired wider acceptance. First, if the essence of a currency is that you want transactions to occur quickly and at low cost, bitcoin is inefficient, with transactions times and costs remaining high. Second, the wild volatility that makes it such a desirable target for speculative trading makes both buyers and sellers more reluctant to use it in transactions, the former because they are afraid that they will miss out on a price run up and the latter because they may be accepting it, just before a price drop. Third, a currency with an absolute limit in numbers is one that is destined for deflation in steady state, in economies with real growth. I know that stories about the Silk Road have enshrined the mythology of bitcoin being the currency of choice for illegal activities, but a currency designed purely for evasion (of crime and taxes) is destined to be a niche currency that will be under assault from governments and law enforcement.Bitcoin is a collectible, but with a question mark on longevity: I have described Bitcoin as millennial gold, and you could argue that, at least for some young people, holding bitcoin resonates more than holding gold. They may be right in their choice, but there are two issues that they need to confront. The first is that while bitcoin’s allure is that it has limits on Ìýquantity, that assumes that it has no substitutes. If other cryptos can operate as substitutes, even imperfect ones, there is no limit on quantity, since you can keep creating new variants. The second is whether the desirability of bitcoin will endure, since much of that desirability right now is built on its past price performance. In other words, if traders move on from bitcoin to some other speculative investment, and bitcoin prices stagnate or drop, will traders continue to hold it? In Bitcoin's favor, it has been able to make it through prior downturns, and not only survive but come back stronger, but the question still remains.Looking at how Bitcoin did in 2020 can give us insight into its future. In the graph below, I look at Bitcoin and Ethereum prices through the year:Yahoo! FinanceBoth Bitcoin and Ethereum delivered spellbinding returns in 2020, with Bitcoin up more than 300% and Ethereum up 469%. It may seem odd to take issue with either investment after a year like this one, but there are two components to the year's performance that should give pause to proponents. The first is that during the crisis weeks (2/14 - 3/23) and the months afterwards (3/23 - 9/1), Bitcoin and Ethereum both behaved more like very risky stocks than crisis assets, undercutting the argument that investors will gravitate to them during crises. The second is that there were no significant developments that I know off, during the last few months of 2020, that advanced the cause of Bitcoin as a currency or Ethereum as a commodity, which leaves us with momentum as the dominant variable explaining the price run up.Ìý
Does that mean that we are headed for a correction in one or both of these cryptos? Not necessarily, since momentum is a dominant force, and while momentum can and will break, the catalysts for that to happen are not obvious in either Bitcoin or Ethereum, precisely because they are unformed. Since the end game (currency or collectible) is still being hashed out, there are no markers against which progress is being measured, and thus, no disappointments or surprises that will lead to a reassessment. Put simply, if you don't know where Bitcoin is going, how would you know if it is getting there? Let me suggest that this confusion serves the interests of bitcoin traders, keeping its prices volatile, but it comes at the expense of bitcoin’s long term potential as a currency or collectible, which require more stability.Ìý

The Investment Lessons

Every investing class starts with a discourse on diversification, an age-old lesson of not putting your eggs in one basket, and spreading your bets. In the last few decades, a combination of modern portfolio theory and data access has quantified this search for stability into a search for uncorrelated investments. When I was learning investments, admittedly a lifetime ago, I was told to expand my stock holdings to foreign markets and real estate, because their movements were driven by different forces than my domestic stockholdings. That was sensible advice, but as we (collectively as investors) piled into foreign stock funds and securitized real estate, we created an unwanted, but predictable consequence. The correlations across markets rose, reducing the benefits of diversification, and particularly so, during periods of crisis. The co-movement of markets during the 2008 crisis has been well chronicled, and I was curious about how 2020 played out across markets, and to capture the co-movement, I computed correlations using daily returns in 2020, across markets:

If you are rusty on statistics, this table can look intimidating, but it is a fairly easy one to read. To see the story behind the numbers, remember that a correlation of one reflects perfect co-movement, plus one, if in the same direction, and minus one, if in opposite directions, and a number close to zero indicates that there is no co-movement. Here is what I see:

Equities moved together across markets, with correlations of 0.89 between US large cap and small cap, 0.70 between US large cap and European equities and 0.60 between US large cap and emerging market equities. Put simply, having a globally diversified stock portfolio would have helped you only marginally on the diversification front, during 2020.The US dollar moved inversely with equities, gaining strength when stocks were weak and losing strength when they were strong, and the movements were greater against emerging economy currencies ((-0.54)Ìýthan against developed economy currencies (-0.17). That may have offset some or much of the diversification benefits of holding emerging market stocks.Treasury bondÌýprices moved inversely with stock prices, at least during 2020. ÌýThat can be seen in the negative correlations between the S&P 500 and 3-month T.Bills (-.06) and 10-year T.Bonds (-0.48). In other words, on days in 2020, when interest rates rose (fell) strongly, causing T.Bond prices to drop (rise), stock prices were more likely to go up (down). (I computed daily returns on treasury bonds, including the price change effect of interest rates changing.)With corporate bonds, the relationship with stock prices was positive, with lower-grade and high yield bonds moving much more with stocks (S&P 500 correlation with CCC & lower rated bonds was 0.60), than higher grade bondsÌý(S&P 500 correlation with CCC & lower rated bonds was 0.47).ÌýIn 2020, at least, commodity prices moved with stock prices, with the correlations being strongly positive not just for oil and copper, but with the broader commodity index.The S&P real estate index moved strongly with stocks, but a caveat is in order, since this index measures securitized real estate. Most of real estate is still held in private hands, and the prices on real estate can deviate from securitized real estate prices. The Case-Shiller index measures actual transactions, but it is not updated daily, and thus does not lend itself to this table.Gold and silver provided partial hedges against financial assets (stocks and bonds), but the correlation was not negative, as it was in the 1970s. During 2020, gold and silver both posted positive correlations with the S&P 500, 0.17 for the former and 0.24 for the latter.Cryptos moved more with stocks than gold, with bitcoin exhibiting a correlation of 0.43 with the S&P 500 and ethereum correlated 0.45 against the same index. Interesting the correlation between cryptos and gold is low; the correlation is 0.10 between bitcoin and gold and 0.12 between ethereum and gold.I know that this is all from one year, and that these correlations are unstable, but it is crisis years like 2008 and 2020 that we should be looking at, to make judgments about the relationship between investments and risk. The bottom line is that diversification today is a lot more difficult than it was a few decades ago, and staying with the old playbook of hold more foreign stocks and some real estate will no longer do the trick.Ìý
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Data Updates for 2021

In , I described the wild ride that the price of risk took in 2020, with equity risk premiums and default spreads initially sky rocketing, as the virus led to global economic shutdowns, and then just as abruptly dropping back to pre-crisis levels over the course of the year. As stock and bond markets went through these gyrations, it should come as no surprise that the same forces were playing out in other markets as well. In this post, I will take a look at these other markets, starting with a way of dividing investments into assets, commodities, currencies and collectibles that I find useful in thinking about what I can (and cannot) do in those markets, and then reviewing how these markets performed during 2020. As I do this, there is no way that I can evade discussing Bitcoin and other crypto assets, which continued to draw disproportionate (relative to their actual standing in markets) attention during the year, and talking about what 2020 taught us about them.

Investments: Classifications and Consequences

In , focused on bitcoin, I argued that all investments can be categorized into one of four groups, assets, commodities, currencies and collectibles, and the differences across these group are central to understanding why pricing is different from value, and what sets investing apart from trading.

The Divide: Assets, Commodities,ÌýCurrencies and Collectibles

If you define an investment as anything that you can buy and hold, with the intent of making money, every investment has to fall into at least one of these groupings:

Assets: An asset has expected cash flows that can either be contractually set (as they are with loans or bonds), residual (as is the case with an equity investment in a business or shares in a publicly traded company) or even conditional on an event occurring (options and warrants).ÌýCommodities: A commodity derives its value from being an input into a process to produce a item (product or service) that consumers need or want. Thus, agricultural products like wheat and soybeans are commodities, as are industrial commodities like iron ore and copper, and energy-linked commodities like oil and natural gas.ÌýCurrencies: A currency serves three functions. It is a measure of value (used to tell you how much a product or service costs), a medium of exchange (facilitating the buying and selling of products and services) and a store of value (allowing people to save to meet future needs). While we tend to think of fiat currencies like this Euro, the US dollar or the Indian rupee, the use of currency pre-dates governments, and human beings have used everything from to Ìýas currency.Collectibles: A collectible's pricing comes from the perception that it has value, driven by tastes (artwork) and/or scarcity (rare items). There are a range of items that fall into this grouping from fine art to sports memorabilia to precious metals.While most investments fall into one of these buckets, there are some that can span two or more, and you have to decide which one dominates. Take gold, for instance, whose ductility and malleability makes it a prized commodity to jewelers and electronics makers, but whose scarcity and indestructibility (almost) make it even more attractive as a currency or a collectible, With bitcoin, even its most ardent promoters seem to be divided on whether the end game is to create a currency or a collectible, a debate that we will revisit at the end of this post.
Price versus ValueThe classification of investments is key to understanding a second divide, one that I have repeatedly returned to in my posts, between value and price.
If the value of an investment is a function of its cashflows and the risk in those cash flows, it follows that only assets can be valued. ThoughÌýÌýcommodities can sometimes Ìýbe roughly valued with macro estimates of demand and supply, they are far more likely to be priced.ÌýCurrencies and collectible can only be priced, and the determinants of their pricing will vary:Commodity Pricing: With commodities, the pricing will be determined by two factors. The first is the demand for and supply of the commodity, given its usage, with shocks to either causing price to change. Thus, it should come as no surprise that the oil embargo in the 1970s caused oil prices to surge and resulted in higher prices for orange juice. The second is storability, with storage costs ranging from minimal with some commodities Ìýto prohibitive for others. In general, storable commodities provide buyers with the option of buying when prices are low, and storing the commodity, and for that reason, futures prices of storable commodities are tied to spot prices and storage costs.Currency Pricing: Currencies are priced against each other, with the prices taking the form of "exchange rates". In the long term, that pricing will be a function of how good a currency is as a medium of exchange and a store of value, with better performing currencies gaining at the expense of worse performing ones. On the first dimension (medium of exchange) currencies that are freely exchangeable (or even usable) anywhere in the world (like the US dollar, the Euro and the Yen) will be priced higher than currencies that do not have that reach (like the Indian rupee or the Peruvian Sul). On the second (store of value), it is inflation that separates good from bad currencies, with currencies with low inflation (like the Swiss franc) gaining at the expense of currencies with higher inflation (like the Zambian kwacha).ÌýCollectible Pricing: Most collectibles are pure plays on demand and supply, with no fundamentals driving the price, other than scarcityÌýand desirability, real or perceived. Paintings by Picasso, Monet or Van Gogh are bought and sold for millions, because there are collectors and art lovers who see them as special works of art, and their supply is limited. Adding to the allure (and pricing) of collectibles is their longevity, reflected in their continuous hold on investor consciousness. It should come as no surprise that gold's, because it brings together all three characteristics; it's scarcity comes from nature, its desirability comes from in many forms and it has been .I capture these differences in the table below:In short, assets can be both priced and value, commodities can be roughly valued but are mostly priced and currencies and collectibles can only be priced.
Investing versus TradingThe essence of investing is assessing value, and buying assets that trade at prices below that value, and selling assets that trade at more. Trading is far simpler and less pretentious, where successful trading requires one thing and one thing only, buying at a low price and selling at a higher one. If you agree with those definitions, it then follows that you can invest only in assets (stocks, bonds, businesses, rental properties) and that you can only trade commodities, currencies and collectibles. ÌýDrawing on a table that I have used in prior posts (and I apologize for reusing it), here is my contrast between investing and trading:
Note that I am not passing judgment on either, since your end game is to make money, whether you are an investor or a trader, and the fact that you made money following the precepts of value investing and did fundamental analysis does not make you better or more worthy than your neighbor who made the same amount of money, buying and selling based upon price and volume indicators.

Commodities

With that lengthly lead in, let's look at what 2020 brought as surprises to the commodity market. As the virus caused a global economic shut down, there were severe disruptions to the demand for some commodities, as usage decreased, and to the supply of others, as production facilities and supply chains broke down. During the course of 2020, I kept track continuously of two commodities, copper and oil, both economically sensitive, and widely traded.Ìý

Note that the ups and downs of oil and copper not only follow the same time pattern, but closely resemble what stocks were doing over the same periods, but the changes are more exaggerated (up and down) with oil than with copper. Both oil and copper dropped during the peak crisis weeks (February 14 through March 23, 2020), but while copper not only recouped its losses and was up almost 26% over the course of the year, oil remains more than 20% below the start-of-the-year numbers. Note also the odd phenomenon on April 20, where West Texas crude prices dropped below zero, as traders panicked about running out of storage space for oil in the US.

Expanding more broadly and looking at a basket of commodities, we can trace out the same effects. In the graph below, I look at three commodity indices, the S&P World Commodity Index (WCI), which is a production-weighted index of commodity futures, the S&P GSCI Index, an investable version that includes the most liquid commodity futures, and the S&P GSCI Agricultural Index, a weighted average of agricultural commodity futures.

The broad commodity indices (WCI and GSCI) saw significant drops between February 14 and March 23, and recoveries in the months after, mirroring the oil and copper price movements. Agricultural commodity futures were far less affected by the crisis, with only a small drop during the crisis weeks, and delivered the best overall performance for the year.

Currencies

In a year during which financial markets had wild swings, and commodity prices followed, it should come as no surprise that currency markets also went through turbulence. In the graph below, I look at the movements of a select set of currencies over 2020, all scaled to the US dollar to allow for comparability:

The dollar strengthened against all of the currencies between February 14 and March 23, but over the course of the year, it depreciated against the Euro, Yen and the Yuan, was mostly flat against the British pound and Indian rupee and gained significantly against the Brazilian Real. Looking at the US dollar’s movements more broadly, Ìýyou can see the effects of 2020 by looking at the Us Ìýmovement relative to developed market and emerging market currencies in the graph below:

In the crisis weeks (2/14 to 3/23), the US dollar gained against other currencies, but more so against emerging market currencies than developed markets ones. In the months afterwards, it gave back those gains to end the year flat against emerging market currencies and down about 5.5% against developed market currencies.

Collectibles

During crises, collectibles often see increased demand, as fear about the future and a loss of faith in institutions (central banks, governments) leads people to see refuge in investments that they believe will outlast the crisis. Given the history of gold and silver as crisis assets, I start by looking at gold and silver prices in 2020;

Both gold and silver had strong years, with gold up 24.17% and silver up 46.77% during the year, but gold played the role of crisis asset better, with its price dropping only 5.19% in the crisis weeks from February 14 to March 23, beating out almost every other asset class in performance during the period. Silver dropped by 29.34% during that same period, but while its subsequent rise more than made up for that drop, on the narrow measure of crisis asset, it did not perform as well as gold.

The year (2020) had mixed effects on other collectible markets. Fine art, for itself, built around in-person auctions of expensive art works saw sales plummet in the early months of 2020, as shutdowns kicked in, but saw a towards the end of the year. Notwithstanding this development, overall sales of art dropped in 2020, and transactions decreased, especially in the highest-priced segments.Ìý

Cryptos

It would be impossible to complete this post without talking about bitcoin, which as it has for much of the decade, continued to dominate discussions of markets and investments. Looking at this graph of bitcoin since its inception, you can see its meteoric rise:

There are clearly many who have been enriched during this rise, and quite a few who have lost their shirts, but any discussion of bitcoin evokes more passion than reason. There are some who believe so intensely in bitcoin that any critique or viewpoint that is contrary to theirs evokes an almost hysterical overreaction. On the other hand, there are others who view bitcoin as speculation run amok, with the end game destined to be painful. At the risk of provoking both sides, I want to start with a fundamental question of whether bitcoin is an asset, a commodity, a currency or a collectible. Even among its strongest supporters, there seems to be no consensus, with the biggest split being between those who argue that it will become a dominant currency, replacing fiat currencies in some markets, and supplementing them in others, and those who claim that it is a gold-like collectible, deriving its pricing from crises and loss of faith in fiat currencies. You could argue that this divide has existed from its creation in 2008, both in terminology (you mine for bitcoin, just as you do for gold) and in its design (an absolute limit on its numbers, creating scarcity). There are even some who believe that the block chain technology that is at the heart of bitcoin can make it a commodity, with the price rising, as block chains find their place in different parts of the economy. Here is my personal take:

Bitcoin is not an asset. I know that you can create securities denominated in bitcoin that have contractual or residual Ìýcash flows, but if you do so, it is not bitcoin that is the asset, but the underlying contractual claim. Put simply, when you buy a dollar or euro denominated bond, it is the bond that is the asset, not the currency of denomination.Bitcoin is not a commodity. It is true that block chains are finding their way into different segments of the economy and that the demand for block chains may grow exponentially, but bitcoin does not have a proprietary claim to block chain technology. In fact, you can utilize block chains with fiat currencies or other crypto currencies, and many do. There are some cryptos, like ethereum, that are , and with those crypto currencies, there is a commodity argument that can be made.Bitcoin is a currency, but it is not a very good one (at least at the moment): Every year, since its inception, we have been told that Bitcoin is on the verge of a breakthrough, where sellers of products and services will accept it as payment for goods and services, but twelve years after its creation, Ìýits acceptance remains narrow and limited. There are simple reasons why it has not acquired wider acceptance. First, if the essence of a currency is that you want transactions to occur quickly and at low cost, bitcoin is inefficient, with transactions times and costs remaining high. Second, the wild volatility that makes it such a desirable target for speculative trading makes both buyers and sellers more reluctant to use it in transactions, the former because they are afraid that they will miss out on a price run up and the latter because they may be accepting it, just before a price drop. Third, a currency with an absolute limit in numbers is one that is destined for deflation in steady state, in economies with real growth. I know that stories about the Silk Road have enshrined the mythology of bitcoin being the currency of choice for illegal activities, but a currency designed purely for evasion (of crime and taxes) is destined to be a niche currency that will be under assault from governments and law enforcement.Bitcoin is a collectible, but with a question mark on longevity: I have described Bitcoin as millennial gold, and you could argue that, at least for some young people, holding bitcoin resonates more than holding gold. They may be right in their choice, but there are two issues that they need to confront. The first is that while bitcoin’s allure is that it has limits on Ìýquantity, that assumes that it has no substitutes. If other cryptos can operate as substitutes, even imperfect ones, there is no limit on quantity, since you can keep creating new variants. The second is whether the desirability of bitcoin will endure, since much of that desirability right now is built on its past price performance. In other words, if traders move on from bitcoin to some other speculative investment, and bitcoin prices stagnate or drop, will traders continue to hold it? In Bitcoin's favor, it has been able to make it through prior downturns, and not only survive but come back stronger, but the question still remains.Looking at how Bitcoin did in 2020 can give us insight into its future. In the graph below, I look at Bitcoin and Ethereum prices through the year:Yahoo! FinanceBoth Bitcoin and Ethereum delivered spellbinding returns in 2020, with Bitcoin up more than 300% and Ethereum up 469%. It may seem odd to take issue with either investment after a year like this one, but there are two components to the year's performance that should give pause to proponents. The first is that during the crisis weeks (2/14 - 3/23) and the months afterwards (3/23 - 9/1), Bitcoin and Ethereum both behaved more like very risky stocks than crisis assets, undercutting the argument that investors will gravitate to them during crises. The second is that there were no significant developments that I know off, during the last few months of 2020, that advanced the cause of Bitcoin as a currency or Ethereum as a commodity, which leaves us with momentum as the dominant variable explaining the price run up.Ìý
Does that mean that we are headed for a correction in one or both of these cryptos? Not necessarily, since momentum is a dominant force, and while momentum can and will break, the catalysts for that to happen are not obvious in either Bitcoin or Ethereum, precisely because they are unformed. Since the end game (currency or collectible) is still being hashed out, there are no markers against which progress is being measured, and thus, no disappointments or surprises that will lead to a reassessment. Put simply, if you don't know where Bitcoin is going, how would you know if it is getting there? Let me suggest that this confusion serves the interests of bitcoin traders, keeping its prices volatile, but it comes at the expense of bitcoin’s long term potential as a currency or collectible, which require more stability.Ìý

The Investment Lessons

Every investing class starts with a discourse on diversification, an age-old lesson of not putting your eggs in one basket, and spreading your bets. In the last few decades, a combination of modern portfolio theory and data access has quantified this search for stability into a search for uncorrelated investments. When I was learning investments, admittedly a lifetime ago, I was told to expand my stock holdings to foreign markets and real estate, because their movements were driven by different forces than my domestic stockholdings. That was sensible advice, but as we (collectively as investors) piled into foreign stock funds and securitized real estate, we created an unwanted, but predictable consequence. The correlations across markets rose, reducing the benefits of diversification, and particularly so, during periods of crisis. The co-movement of markets during the 2008 crisis has been well chronicled, and I was curious about how 2020 played out across markets, and to capture the co-movement, I computed correlations using daily returns in 2020, across markets:

If you are rusty on statistics, this table can look intimidating, but it is a fairly easy one to read. To see the story behind the numbers, remember that a correlation of one reflects perfect co-movement, plus one, if in the same direction, and minus one, if in opposite directions, and a number close to zero indicates that there is no co-movement. Here is what I see:

Equities moved together across markets, with correlations of 0.89 between US large cap and small cap, 0.70 between US large cap and European equities and 0.60 between US large cap and emerging market equities. Put simply, having a globally diversified stock portfolio would have helped you only marginally on the diversification front, during 2020.The US dollar moved inversely with equities, gaining strength when stocks were weak and losing strength when they were strong, and the movements were greater against emerging economy currencies ((-0.54)Ìýthan against developed economy currencies (-0.17). That may have offset some or much of the diversification benefits of holding emerging market stocks.Treasury bondÌýprices moved inversely with stock prices, at least during 2020. ÌýThat can be seen in the negative correlations between the S&P 500 and 3-month T.Bills (-.06) and 10-year T.Bonds (-0.48). In other words, on days in 2020, when interest rates rose (fell) strongly, causing T.Bond prices to drop (rise), stock prices were more likely to go up (down). (I computed daily returns on treasury bonds, including the price change effect of interest rates changing.)With corporate bonds, the relationship with stock prices was positive, with lower-grade and high yield bonds moving much more with stocks (S&P 500 correlation with CCC & lower rated bonds was 0.60), than higher grade bondsÌý(S&P 500 correlation with CCC & lower rated bonds was 0.47).ÌýIn 2020, at least, commodity prices moved with stock prices, with the correlations being strongly positive not just for oil and copper, but with the broader commodity index.The S&P real estate index moved strongly with stocks, but a caveat is in order, since this index measures securitized real estate. Most of real estate is still held in private hands, and the prices on real estate can deviate from securitized real estate prices. The Case-Shiller index measures actual transactions, but it is not updated daily, and thus does not lend itself to this table.Gold and silver provided partial hedges against financial assets (stocks and bonds), but the correlation was not negative, as it was in the 1970s. During 2020, gold and silver both posted positive correlations with the S&P 500, 0.17 for the former and 0.24 for the latter.Cryptos moved more with stocks than gold, with bitcoin exhibiting a correlation of 0.43 with the S&P 500 and ethereum correlated 0.45 against the same index. Interesting the correlation between cryptos and gold is low; the correlation is 0.10 between bitcoin and gold and 0.12 between ethereum and gold.I know that this is all from one year, and that these correlations are unstable, but it is crisis years like 2008 and 2020 that we should be looking at, to make judgments about the relationship between investments and risk. The bottom line is that diversification today is a lot more difficult than it was a few decades ago, and staying with the old playbook of hold more foreign stocks and some real estate will no longer do the trick.Ìý
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Spreadsheets

Data Updates for 2021

Investors are constantly in search of a single metric that will tell them whether a market is under or over valued, and consequently whether they should buying or selling holdings in that market. With equities, the metric that has been in use the longest is the PE ratio, modified in recent years to the CAPE, where earnings are normalized (by averaging over time) and sometimes adjusted for inflation. That metric, though, has been signaling that stocks are over valued for most of the last decade, a ten-year period when stocks delivered blockbuster returns. The failures of the signal have been variously attributed to low interest rates, accounting mis-measurement of earnings (especially at tech companies), and by some, to animal spirits. ÌýIn this post, I offer an alternative, albeit a more complicated, metric that I believe offers not only a more comprehensive measure of pricing, but also operates as a barometer of the ups and downs in the market.

The Price of Risk

The price of risk is what investors demand as a premium, an extra return over and above what they can make on a guaranteed investment (risk free), to invest in a risky asset. Note that this price is set by demand and supply and will reflect everything that investors collectively believe, hope for, and fear.

Does the price of risk have to be positive? The answer depends on whether human beings are risk averse or not. If they are, the price of risk will be reflected in a positive premium, and the level of the premium will increase, as investors become more risk averse. If, on the other hand, investors are risk neutral, the price of risk will be zero, and investors will buy risky business, stocks and other investments, and settle for the risk free rate as the expected return.

Note that nothing that I have said so far is premised on modern portfolio theory, or any academic view of risk premiums. It is true that economists have researched risk aversion for centuries and concluded that investors are collectively risk averse, and that the level of risk aversion varies across age groups, income levels and time. Some have developed models that try to measure what a fair risk premium should be, but to arrive at their conclusions, they have make assumptions about investor utility functions that are often unobservable and untestable. I have no desire to make this a lengthy treatise about the "right" risk premium, but will instead start with two assertions:

Risk premiums can be estimated: You can back out the risk premiums that investors are demanding from the prices that they pay for risky assets. Put simply, if you can observe the price that an investor pays for a risky asset, and are willing to estimate the expected cash flows on that asset, you can estimate the expected return on that asset and net out the risk free asset to arrive at a risk premium. It is true that you can make mistakes on your expected cash flows, but your output should reflect an estimate, albeit a noisy one, of what investors are demanding as a premium.Risk premiums can and will change over time: Risk premiums are driven by risk aversion, and risk aversion itself can change over time. In fact, greed and fear, two big drivers of market prices, also affect risk aversion, with investors becoming more risk averse and charging higher premiums, when the fear factor becomes dominant.ÌýWhen risk premiums change, prices will move: As risk premiums change, the prices that investors are willing to pay for risky assets will also change, with the two moving in opposite directions. Intuitively, if you want to earn a higher risk premium on an investment, holding cash flows fixed, you will pay less for that investment today.TheÌýPrice of Risk: Bond Market

All bonds, including those with guaranteed coupons, are risky, if you define risk as prices being volatile, since as interest rates changes, bond prices will change as well. Most bonds, though, are exposed to a second risk, which is that the bond issuer can default on coupon payments, making returns and prices even more uncertain. This is why corporate bonds are riskier than sovereign bonds, and sovereign bonds issued by shakier governments are riskier than sovereign bonds issued by governments that are unlikely to default.Ìý

Bond Default Spread

If you accept the proposition that a bond with default risk is riskier than an otherwise equivalent bond (same coupon and maturity) issued by a default-free entity, the price of risk in the bond market can be measured by looking at the differences in yields between the two bonds. Thus, if a 10-year corporate bond has a yield of 3.00% and a 10-year government bond, in the same currency and with no default risk, has a yield of 1.00%, the difference is termed the default spread and becomes a measure of the price of risk in the bond market.Ìý

At the risk of belaboring the details, it is not the yield that we should be comparing, but the yield to maturity, which is the internal rate of return on the bond, given how it is priced:

To compute the default spread over a 10-year period for a specific corporate bond (or loan), you would compute the yields to maturity on the ten-year corporate and treasury bonds and take the difference. Note that even this comparison is an approximation, but it yields a close enough value to work, and that it yields a default spread for a specific maturity. You could compute default spreads for other maturities, and compute the price of risk over 1-year, 2-year, 3-year periods and so on.Ìý

Corporate Default Spreads: Current and Look Back at 2020

Corporate bonds are traded, and as a consequence, and you can use traded prices to estimate default spreads in the market. In the chart below, I compare default spreads at the start of 2021 with the default spreads at the start of 2020:

Source: BofA ML Spreads on Federal Reserve (FRED)

At first sight, it looks like an uneventful year, with spreads in 2021 mildly higher than spreads in 2020, but that comparison is deceptive, since default spreads went on a roller-coaster ride during 2020:

Source: BofA ML Spreads on Federal Reserve (FRED)While spreads started 2020 in serene fashion, the COVID-driven market crisis caused them to widen dramatically between February 14 and March 20, with the spreads almost tripling for lower rated bonds. Given the worries about default and a full-fledged market meltdown, that was not surprising, but what is surprising is how quickly the fear factor faded and spreads returned almost to pre-crisis levels.

Measuring against the past

Are default spreads today too low? There are two ways to answer that question. One is to look at their movement over time, and compare current spreads to historic norms.Ìý

Source: BofA ML Spreads on Federal Reserve (FRED)

The default spreads at the end of 2020 are at the low end of the historical spectrum, and the contrast with the 2008 crisis is stark, since default spread surged in the last quarter of 2008 and did not come back down to pre-crisis levels until almost two years later. The other is to look at corporate defaults over time to see if markets are building in enough of a buffer against future defaults.Ìý

Sources: S&P and Moody's
Default rates increased in 2020, with spillover effects expected into 2021, but the corporate bond default spreads do not seem to reflect this. One explanation is that the bond market beliefs that the worst of the crisis is over and that default rates will return quickly to pre-COVID levels. The other is the corporate bond market is under estimating both the risk and the consequences of default.

TheÌýPrice of Risk: Equities

Equities are riskier than bonds (or at least most bonds), and it stands to reason that there is a price of risk bearing in the equity markets. While that price has a name, i.e., the equity risk premium, it is more difficult to observe and estimate than the default spread in bond markets. In this section, I will present both the standard approach to estimating the equity risk premium and my preferred way of doing so, with a rationale for why.

Estimation Approaches

Why is it so difficult to estimate an equity risk premium? The simple reason is that unlike a bond, which comes with specified coupons, the cash flows that you receive when you buy stocks are neither pre-specified nor guaranteed. It is true that some companies pay dividends, and that these dividends are sticky, but it is also true that companies are under no contractual obligation to continue paying those same dividends. This difficulty in observing the equity risk premium leads many to look backwards, when asked to estimate the equity risk premium. Put simply they look at a long time period in the past (50 years or even 100 years) and look at the premium that stocks earned over a risk free investment (treasury bills or bonds); that historical risk premium then gets used as a measure of the current equity risk premium. On my website, I update this historical risk premium every year, and the graph below reflects my January 2021 findings:

Looking over a 92-year time period (1928-2020), for instance, stocks earned an geometric average return of 9.79%, giving them a premium of 4.84% over the 4.95% that you would have earned, investing in treasury bonds. If you buy into this measure of equity risk premiums, consider its limitations. First, it is backward looking and built on the presumption that the future will look like the past. Second, even if you trust mean reversion, note that the estimated premium is not a fact but an estimate, with a wide range around it. Specifically, the estimate of 4.84% for the equity risk premium from 1928 to 2020 comes with a standard error of 2.1%; the true ERP, with this error, could fall anywhere from 0.64% to 9.04%. Third, this premium is static and does not reflect market crises and investor fears; thus, the historical risk premium on February 14, 2020 would have very similar to the historical risk premium on March 20, 2020.

The alternative approach to estimating equity risk premiums is revolutionary and it borrows from the yield to maturity approach that we used to estimate bond default spreads. Consider replacing the bond price with the level of stock prices today (say, with the S&P 500 index) and coupons with expected cash flows on stocks (from dividends and buybacks), and solve for an internal rate of return:

Implied Equity Risk Premium: In General

The internal rate of return is the expected return on stocks, and netting out the risk free rate today will yield an implied equity risk premium. In the picture below, I use this process to estimate an equity risk premium of 4.72% Ìýfor the S&P 500 on January 1, 2021:

It is true that my estimates of earnings and cash flows in the future are driving my premium, and that the premium will be lower (higher) if I have under (over) estimated those numbers. This approach to estimating equity risk premiums is forward-looking and dynamic, changing as the market price changes. In the graph below, I report implied equity risk premiums that I computed, by day, during 2020, in an effort to gauge how the crisis was playing out and keep my sanity.

As with the bond default spread, the implied equity risk premium was extraordinarily volatile in 2020, peaking at 7.75% on March 20, before falling back to pre-crisis levels by the end of the year.

Market Gauge?

As we are engulfed by talk of market bubbles and corrections, it is worth nothing that any question about the overall market can really be reframed as a question about the implied equity risk premium. If you believe that the current implied equity risk premium is too low, you are in effect also saying that stocks are overvalued, just as a judgment that the equity risk premium is too high is equivalent to arguing that stocks are undervalued. So, at 4.72%, is the equity risk premium too low and is the market in a bubble? One way to pass judgment is to compare the current premium to implied equity risk premiums in the past:

On this comparison, stocks don't look significantly over valued, since the current premium is higher than the long term average (4.21%), though if you compare it to the equity risk premium in the last decade (5.53%), it looks low, and that stocks are over valued by about 15%. There is a caveat, though, which is that this risk premium is being earned on a risk free rate that is historically low. Consider this alternative graph, where I look at the expected return on stocks (risk free rate plus implied equity risk premium) over the same time period:

For much of this century, the expected return on stocks has hovered around 8%, but the expected return at the start of 2021 is only 5.65%, well below the expected returns in prior periods.

A Market Assessment

I know that you are probably incredibly confused, and I am afraid that I cannot clear up all of that confusion, but this framework lends itself to valuing the entire market. To do this, you have to be willing to make estimates of:

Earnings on the index: You cannot value a market based upon last year's earnings (though many do so). Investing is about the future, and uncomfortable as it may make you feel, you have to make estimates for the future. With an index like the S&P 500, you can outsource these estimates at least for the near years, by looking at consensus forecasts from analysts tracking the index.Cash returned, relative to earnings: Since it is cash returned to stockholders that drives value, you also have to make judgments on what percent of earnings will be returned to stockholders, either in dividends or buybacks. To this, you can look to history, but recognize that it is also a function of the confidence that companies have about the future, with more confidence leading to higher cash being returned.Risk free rates over time: While it is generally not a good idea to play interest rate forecaster, we are in unusual times, with rates close to all time lows. In addition, your views on future growth in the economy are intertwined with what will happen to risk free rates, with stronger economic growth putting more upward pressure on rates.An acceptable ERP: As I noted in the last section, equity risk premiums have been volatile over time, and particularly so in years in 2020. The equity risk premium, added to the risk free rate, will determine what you need stock returns to be, to break even on a risk-adjusted basis.

It is only fair that I go first. In the picture below, I make my best judgments on each of these dimensions, using consensus estimates of earnings in 2021 and 2022 to get started, but then slowing growth in earnings to match the growth rate in the economy, which I approximate with the risk free rate. On the risk free rate, I assume that rates will rise over time to 2%, and that 5% is a fair ERP, given history. My valuation is below:

Based upon my inputs, the S&P 500 is over valued by about 12%, certainly not bubble territory, but still richly priced. You may (and should) disagree with my assumptions, and I welcome you to download the spreadsheet and change the inputs. Ultimately though, the judgment you make on the market will be a joint effect of your views on the economy and interest rates in the next few years. The table below summarizes the interplay between economic growth and interest rate assumptions, and the effects on the index value:

As you can see,Ìýthere areÌýfar more badÌýpossibleÌýoutcomes than good ones, and the only scenario where stocks have significant room to rise is the Goldilocks market, where rates stay low (at close to 1%), while the economy comes back strongly. I know that the possibility of additional economic stimulus may improve the odds for the economy, but can they do so without affecting rates? To buy into that scenario, you have to belief that the Fed has theÌýpower to keep rates low, no matter what happens to the economy, and I don't share that faith.Ìý

As many of you who have read my blog posts know, I am a reluctant market timer, but ultimately we all time markets, implicitly or explicitly, the formerÌýwooing up in how much of your portfolio is in cash and the latter in more overt acts of either protection orÌýbets onÌýmarket directions. Going into 2021, I have far more cash in my portfolio than I usually do, and for the first time in a long, long time, I have bought partial protection against a market drop, using derivatives. It is insurance, and like all insurance, my best case scenario is that I never need to use it, but it reflects my wariness about what comes next. I am not and don't want to be in the business of doling out investment advice,Ìýand I think that the healthiest pathway for you is to make your ownÌýjudgments on interest rates,Ìýearnings growth and acceptable risk premiums, and follow thatÌýwith consistent actions.Ìý

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Spreadsheets

Data Updates for 2021

Data Update 2 for 2021: The Price of Risk!

As we approach the turn of the calendar year, I have my own set of rituals that prepare me for the new year. Last week, was my data week, where I download and analyze data on all publicly traded companies, listed anywhere in the world, and I will post extensively on what the numbers look like after a most tumultuous year. I also start thinking about my passion, which is teaching, the spring semester to come, and the classes that I will be teaching, repeating a process that I have gone through every year since 1984, my first year as a teacher. And as always, I invite you come along for the ride.Ìý

What I teach...

For a class to resonate and be remembered, it has to be more than a collection of topics, and with each of my classes there is a core narrative that animates and connects the class sessions. If you were to ask me what that narrative was for each of my classes, here is how I would respond.

Corporate Finance: Corporate finance is the development of the first financial principles that govern how to run a business. It is that mission that makes corporate finance the ultimate big picture class, one that everyone (entrepreneurs, investors, analysts, business observers) should take. If it looks like I am over reaching, I start my corporate finance class with the simple proposition that any decision that involves money is a corporate finance decision, and by that definition everything that businesses do falls under its umbrella. To make this operational, I build my class around my big picture of corporate finance:
I tie every session and every topic within each session to this big picture, and while I am willing to and often do abandon models and theories, I am loath to compromise on first principles. Thus, you and I can disagree about whether beta is a good measure of risk, but not on the principle that no matter what definition of risk you ultimately choose, riskier investments need higher hurdles than safer investments. I end the class with a corporate finance version of valuation, where I tie inputs into value (cash flows, growth and risk) to investment, financing and dividend decisions.ÌýValuation: It is unfortunate, but for most people, the vision that comes to mind when I say that I teach valuation is excel spreadsheets and high profile company names. Don't get me wrong! I find Excel to be a solid tool in my arsenal, but I am not only old enough to have valued companies with a ledger sheet and calculator but also wary of letting a tool drive my valuations. If you do take this class, you should recognize that I will almost never open and work with an excel spreadsheet in class (though I do have supplemental YouTube videos on using them in analysis) and my interest is in valuing just about anything, not just large public companies.
In fact, there are three key themes that I emphasize through this class.ÌýPrice versus Value: The first is that we need to draw a contrast between valuing an investment and pricing it; the former is driven by fundamentals (cash flows, growth and risk) and the latter by demand and supply (with mood, momentum and liquidity often dominating fundamentals). While intrinsic valuation models try to assess value, pricing is built upon what others are willing to pay for similar investments; in the context of stocks, using a PE ratio and a peer group to attach a number to company is a pricing, not a valuation.ÌýValue = Story + Numbers: The second is that a good valuation is a bridge between stories and numbers, where every number that you use in a valuation, whether it be expected growth, margin or discount rate, has to be built around a story about the company, and every story you tell about a company (its amazing management, its superior platform or loyal employees) has to show up in a number. I will confess that, as a natural number cruncher, it too me a while to learn this lesson, and I try to pass on how I moved up (and continue to try to do better) the learning curve.Face up to uncertainty, rather than avoid or deny it: Uncertainty is a feature of investing/ business, not a bug. One of my biggest issues with old-time value investing is that it viewed and continues to view uncertainty as something to be avoided as much as possible, and takes the view that you cannot value investments, where there is too much uncertainty. That view has led value investors to focus on mostly mature companies and kept them out of the game of investing in young and growing businesses. I take the point of view that uncertainty should not stop you from valuing companies, that your value estimates will have more error in them, but since the market also faces the same uncertainty, your best bargains may be in the midst of uncertainty. It is for that reason that I spend large portions of this class valuing difficult-to-value companies, in what I call the dark side of valuation.Investment Philosophies: ÌýIf my classes were children, this class would be my neglected one, since I have never taught it in person at NYU, but it is a class that was born out of an observation. There are only a few investors who have consistently beaten the market over time, and many of them are legendary, but people within this small group are extraordinarily diverse in terms of how they think about markets and investing. That tells me three things. The first and obvious one is that there are no easy ways to beat the market, and anyone who claims to have found one is either lying or heading for a letdown. The second is that the notion that there is only one pathway to investment nirvana is hubris, and that there must be different philosophies that can be successful. The third is that since many of these successful investors have been widely followed, just copying what they do must not work, or we would observe far more imitation Buffets and Simons, Ìýwho are successful. In this class, I try (and that is all I can do) to provide a full menu of investment philosophies, starting with technical analysis/charting, moving on to value and growth investing (in both public and private forms), and then on trading on public or private information. I close by looking at bookends of the philosophies by looking at arbitrage, where investors chase (and sometimes catch) the dream of guaranteed profits and indexing, where investors come to an acceptance that stock picking does not work.
With each philosophy, I look at strategies that emerge, the historical backing for whether these strategies work and end by looking at the make up that you would need as an investor to be able to succeed with that philosophy. By the end of the class, my objective is not to sell you on the best philosophy but to provide you with a framework where you can find the philosophy that best fits you.I also offer online classes in basic finance (present value, risk models and measures) and accounting (or at least my version of it) as background to my main classes. If you are at all interested in taking any of these classes, and are wondering about sequence, I modified the flow chart that I used in my September 2020 post to lead you through your choices:

Please recognize that this is just a very rough flow chart, and that you may find pathways through it that meet your needs better.
The Delivery ChoicesIf you decide to take a class or two, there are three platforms that you can pick from, and which one is best for you will depend both on your preferences and objectives:

1. Stern NYU classes: The first, and the one with the deepest roots, are the classes that I teach at the Stern School of Business at NYU to both MBAs and undergraduates. I normally teach these classes, in person, every spring, starting late January/early February and ending early in May. ÌýThis spring, I will be teaching three classes, a corporate finance class for MBAs and two identical valuation classes, one to MBAs and one to undergraduates, but with the virus still raging out of control, I will be teaching the classes on Zoom. The class times for the coming semester are below:Ìý

Corporate Finance: Mondays & Wednesdays, 12.30 pm - 1.50 pm (New York time)Valuation (MBA): Mondays & Wednesdays, 2.00 pm - 3.20 pm (New York time)Valuation (Undergraduate): Mondays & Wednesdays, 3.30 pm - 4.45 pm (New York time)

All three classes start on February 1, 2021 and end on May 10, 2021. To sit on the live classes, you have to be a Stern student enrolled in the class, but I plan to record the classes and you can watch those recordings either on my website or on YouTube (where each class will have its own playlist), and access supplementary material (slides, post-class tests).Ìý2. My (free) online classes: The biggest challenge with following the NYU classes online is that they are not designed as online classes. The lectures are 75-80 minutes long, an eternity for an online experience, where time is measured in seconds, not minutes. I have created 12-15 minute versions of each session, preserving almost 80% of the content in the longer classes, and these online classes are also available on my website or on YouTube. If you do decide to take these classes, there are no hoops to jump through and no cost involved, but there is no credit for classes taken or certification.Ìý3. NYU certificate classes: If it is important to you that you get more structure, more touch and certification, there is a third option. NYU Stern has certificate versions of the online classes on their website. While the content of the free online and certificate classes are almost identical, you get more polished versions of the recorded sessions, once-every-two-weeks live zoom sessions where you can ask me questions and certificate at the end of the class, if you pass the exams/quizzes and complete the project requirements. The cost, though, is definitely not zero, and if you get sticker shock when you check what NYU charges, please remember that I have no control over or negotiation with you on this price. Ìý

The links to all of these classes are at the end of this post.
COVID Lessons

When I start my teaching in early February, it will be my 58th semester teaching valuation and my 36th teaching corporate finance. Have I changed the way that I teach these classes over the last 36 years? Of course, but with two caveats. The first is the first principles or big pictures that you see for the classes are almost identical to those that I taught my very first semester, which should not surprise you, since that is what makes them first principles. The second is that the changes in content in most semesters has been incremental, building largely on the material from the previous one, with more timely data and a few augmentations. That said, since I believe that you should be able to value companies in the real world , each crisis that I have lived and taught through has left its imprint on classes, sometimes altering ways in which I approach estimating and sometimes altering the way I think about fundamentals. The dot com boom of the 1990s forced me to expand my valuation tools and models to cover younger companies, often with lots of potential and very little historical data. I am open about the fact that I learned to value young company through my struggles in valuing Amazon in 1998 and 1999. The dot com bust crystallized my views on the contrast between valuing and pricing an asset, and how behavioral finance can explain why the two diverge and what causes eventual convergence. The 2008 market crisis taught me that globalization had grayed the once bright lines between developed and emerged markets and the capacity for failures at some companies to spill over into other companies and sometimes the entire market. The last decade, with it influx of user based companies and technology platforms forced me to think seriously about how to value a user, subscriber or rider and extrapolate from there to company value. During 2020, as I watched companies and investors struggle with the after shocks of the economic shut down created by COVID, I wrote a series of fourteen posts (linked below) on what I was learning, unlearning and relearning about corporate finance and valuation. Unlike some market watchers, who have been quick to label the market as crazy, speculative or a bubble, I believe that the movements in market value across companies, regions and sectors have implications for how businesses should be run as well how investors price these companies: table.tableizer-table { font-size: 12px; border: 1px solid #CCC; font-family: Arial, Helvetica, sans-serif; } .tableizer-table td { padding: 4px; margin: 3px; border: 1px solid #CCC; } .tableizer-table th { background-color: #104E8B; color: #FFF; font-weight: bold; }

COVID lessonBasisCorporate FinanceValuationInvestment Philosophies The price of risk is dynamic and volatileBoth equity risk premiums & default spreads went on a wild ride in 2020Companies need hurdles rates (costs of equity & capital that change to reflect market levels.Discount rates in intrinsic valaution have to change to reflect current market conditions, and can be expected to change over time.Investors need to reassess their expected returns to reflect risk free rates & current ERP & default spreads. Flexibility is an asset (and has value)Young firms with low capital intensity and more variable cost structures did much better during the crisis than their more capital intensive, high fixed cost counterparts.When investing, companies have to explicitly incorporate flexiblity into decision making, sometimes taking lower NPV, more flexible projects over high NPV, less flexible investments.Value has to incorporate the value of flexibility, explicitly through the use option pricing models or implicitly, when comparing pricing multiples across companies.Investment strategies that create concentrations in manufacturing and captial intensive companies need to be balanced with firms that have more flexible cost structures. Debt can handcuff even large, established companies & put them at risk.In the early days of the crisis, established firms like Boeing found themselves in the crosshairs, partly because of their heavy debt loads.The assessment of how much to borrow has to factor in distress costs much more explicitly, and more value should be attached to keeping a safety buffer.Since it is very difficult, if not impossible, to incorporate failure risk in a DCF, more effort should be put into estimating the probability of failure and its consequences.Strategies that concentrate investments in companies with high failure risk (start ups and indebted firms) have to compensate by holding more cash or buying protection against market shocks.In my valuation class, I will bring in some of the valuations that I did, both of the market (S&P 500) and individual companies during the crisis to illustrate how story telling was key to getting past the near-term uncertainty created by the shut down. In my investment philosophies class, I plan to talk about how the crisis shook my faith and what I had to do to find serenity.Ìý

YouTube Video

Class Links

Corporate Finance MBA class (Spring 2021): and Valuation MBA class (Spring 2021): Ìý and Valuation Undergraduate class (Spring 2021): Ìý and Foundations of Finance Online class (Free):Ìý and Accounting Online class (Free):Ìý and Corporate Finance Online class (Free): and Valuation Online (Free):Ìý: and Investment Philosophies Online class (Free):Ìý: and NYU Corporate Finance Certificate class (Definitely not free & offered only in fall 2021) (Definitely not free) (Definitely not free)

Viral Market Update Posts

I spent the first week of 2021 in the same way that I have spent the first week of every year since 1995, collecting data on publicly traded companies and analyzing how they navigated the cross currents of the prior year, both in operating and market value terms. I knew that this year would be more challenging than most other years, for two reasons. The first was that the shut down of the global economy, initiated by the spreading of COVID early last year, had significant effects on the operations of Ìýcompanies in different sectors, and across the world. The second was that, starting mid-year in 2020, equity markets and the real economy moved in different directions, with the former rising on the expectations a post-virus future, and the latter languishing, as most of the world continued to operate with significant constraints. In this post, I will start with a rationalization of why I do this data analysis every year, follow up with a description (geographic and sector) of the overall universe of companies that are in my analysis, list out the variables that I estimate and report, and conclude with a short caveat about 2020 data.

Data: A Pragmatist View

We live in the age of data worship, where investors, analysts and businesses all seem to have bought into the idea that big data has answers for every question and that collecting the data (or paying for it) will create positive payoffs. I am a skeptic and I have noted that to make money on big data, two conditions have to be met:

If everyone has it, no one does: I believe that if everyone has a resource or easy access to that resource, it is difficult to make money off that resource. Applying that concept to data, the most valuable data is unique and exclusively available to its owner, and the further away you get from exclusivity, the less valuable data becomes.ÌýData is not dollars:ÌýData is valuable only if it can be converted into a product or service, or improvements thereof, allowing a company to capture higher earnings and cash flows from those actions. Data that is interesting but that cannot be easily monetized through products or services is not as valuable.All of the data that I use in my data analysis is in the public domain, and while I am lucky enough to have access to large (and expensive) databases like Bloomberg and S&P, there are tens of thousands of investors who have similar access. Put simply, I possess no exclusivity here, and staying consistent with my thesis, I don't expect to expect to make money by investing based upon this data. So, why bother? I believe that there are four purposes that are served:Gain perspective: One of the challenges of being a business or an investor is developing and maintaining perspective, i.e., a big picture view of what comprises normal, high or low. Consider, for instance, an investor who picks stocks based upon price to book ratios, who finds a stock trading at a price to book ratio of 1.5. To make a judgment on whether that stock is cheap or expensive, she would need to know what the distribution of price to book ratios is for companies in the sector that the company operates in, and perhaps in the market in which it is traded.ÌýClear tunnel vision: Investors are creatures of habit, staying in their preferred markets, and often within those markets, in their favored sectors. Equity research analysts are even more focused on handfuls of companies in their assigned industries. So what? By focusing so much attention on a small subset of companies, you risk developing tunnel vision, especially when doing peer group comparisons. Thus, an analyst who follows young technology companies may decide that paying ten times revenues for a company is a bargain, if all of the companies that he tracks trade at multiples greater than ten times revenues. Nothing is lost, and a great deal is gained, by stepping back from your corner of the market and looking at how stocks are priced across industries and markets.Expose BS: I know that everyone is entitled to their opinions, but they are not entitled to their facts. I am tired of market experts and analysts who make assertions, often based upon anecdotal evidence and plainly untrue, to advance a thesis or agenda. Are US companies more levered than they were a decade ago? Do US companies pay less in taxes than companies in other parts of the world? Are companies that buy back stocks more financially fragile than companies that do not? These are questions that beg to be addressed with data, not emotions or opinions. (I know.. I know... You would like those answers now, but stay tuned to the rest of my data updates and the data will speak for itself.)Challenge rules of thumb and conventional wisdom: Investing has always had rules of thumb on how and when to invest, ranging from using historical PE or CAPE ratios to decide if markets are over valued, to simplistic rules (eg. buy stocks that trade at less than book value or trade at PEG ratios less than one) for individual stocks. It is very likely that these rules of thumb were developed from data and observation, but at a different point in time. As markets and companies have moved on, many of them no longer work, but investors continue to use them. To illustrate, consider a practice in valuation, where analysts are trained to add a small cap premium to discount rates for smaller companies, on the intuition that they are riskier than larger companies. The small cap premium was uncovered in the the early 1980s, when researchers found that small cap stocks in the US earned significantly higher returns than large cap stocks, based upon data from 1926 to 1980. In the decades since, the small cap premium has disappeared in returns, but inertia and laziness have kept the practice of adding small cap premium alive.In closing, I also want to dispense with the notion that data is objective and that numbers-focused people have no bias. If you have a bias or a preconception, it is amazing how quickly you can bend the data to reflect that bias or preconception. As an exercise, take a look at my paid by US companies in 2021. From past experience, I predict that numbers in this table will be quoted by journalists, economists and even politicians, with very different agendas, but the tax rate measure (since I report several different measures) that they quote will reflect their biases. Put simply, if you find my data quoted elsewhere, I would suggest that you visit the source and make your own judgments.
The SampleThe focus in markets is often on subsets of firms, usually with good reason. In general, larger firms (especially in market value terms) get more attention that smaller ones, because their movements in their value are more consequential for more investors Also, publicly traded firms generally garner more attention than privately owned businesses, partly because they are larger, but also because there are is more information disclosed and investment opportunity with the former. Finally, fair or not, companies in developed and more liquid markets are in the spotlight Ìýmore than their counterparts in emerging markets. That said, focusing on just large or developed market companies can create biased samples and skew assessments about market and operating performance. It is to avoid this that I started by looking at all publicly traded companies that were traded on January 1, 2021, and arrived at a sample of 46,579 firms, spread across 136 countries.ÌýWhile the universe of companies is diverse, with approximately half of all firms from emerging markets, it is more concentrated in market capitalization, with the US accounting for 40% of global market capitalization at the start of the year. Using the S&P categorization of global companies into sectors, the data universe looks as follows:It should come as no surprise, especially given their performance over the last year, that the technology sector is the largest in terms of market capitalization. While some of the companies in this data trace their existence back decades, there is a healthy proportion of younger companies, many in emerging markets and new industries.Ìý
Finally, it is worth noting that, notwithstanding the travails of last year, the number of firms in the data universe increased from 44,394 firms at the start of 2020 to 46,579 firms, a 4.9% increase over the year, as new listings outnumbered companies that defaulted during the course of the year.Ìý
If there is a hole in my sample, it is the absence of privately owned businesses. One reason is that these businesses are not only not required to publicly disclose their financial details in most parts of the world, but often follow more malleable accounting standards, making the data less reliable and comparable. The other is that even in those parts of the world, where private company information is available, the data is limited and market price data is missing (since the companies are not traded). That said, it does mean that any broad conclusions (about profitability and revenues) that emerge from my data apply to public companies, and it may be dangerous to extrapolate to private businesses, especially in a year like 2020 where private businesses could have been affected more adversely by COVID shutdowns than public companies.
The DataAs more data has become publicly available, and access to the data becomes easier, the challenge that we face in investing and valuation is that we often have too much data, and information overload is a clear and present danger. In this section, I will list the data that I estimate and report, as well as explain how I consolidate company-level data into more usable group statistics.Ìý
General DetailsWhile there are advantages to looking across all firms, small and large, listed anywhere in the world, there are challenges that come from casting such a wide net. I have tried my best to keep them from overwhelming the analysis, and in the interests of openness, here are some of the details:Currency: One of the challenges of dealing with a global sample is that you are working with accounting and market numbers quoted in multiple currencies, and since you cannot aggregate or average across them, I will employ two techniques. First, all value numbers (like market capitalization, debt or revenues) that I aggregate or average will be converted into US dollars to ensure currency consistency. Second, most of the numbers that I report will be ratios, where the currencies are no longer an issue; a PE ratio for a Turkish company, with market cap and earnings denominated in Turkish Lira, can be compared to the PE ratio for a US company, with market cap and earnings denominated in US $. It is true that the Turkish company will face more risk because of its location, but that is an issue separate from currency.Missing Data: Information disclosure requirements vary across the world, and there are some data items that are available for some companies or some markets, and not for others. Rather than remove all firms with missing data, which will eliminate a large portion of my sample, I keep the firms in the sample and report only the variable/metric that is affected by the missing item as "NA". For instance, I have always computed the present value of lease commitments in future years and treated that value as debt, a practice that IFRS and GAAP have adopted in 2019, but that computation requires explicit disclosures of lease commitments in future years. That is standard practice in the United States, but not in many emerging markets, but rather than not do the computation for all companies or remove all companies with missing lease commitments, I compute lease debt for those companies that report commitments and report it as zero for those companies that do not, an imperfect solution but the least imperfect of the many choices.Accounting Differences: In addition to disclosure differences, there are also accounting differences in revenue recognition, expensing rules, depreciation methods and other details across markets. I work with the publicly available data, recognizing that net income for a Japanese company may be measured differently than earnings for an Indian company, and accept that this may skew the results. However, it is worth noting that accounting rules around the world have converged over the last four decades, and they share a lot more in common than they have as differences.Source Reliability and Errors: I obtain my raw data from S&P, Bloomberg and others, and I am grateful that I can do that, because I could never hand collect and input data on 40,000+ companies. They, in turn, obtain the data from computerized databases in different markets that collect public filings, and at every stage in this process, there is the possibility of errors. I do run some simple error checks to eliminate obvious mistakes, but I am sure that there are others that I miss. My defense is that, unless the mistake is on a very large scale, the impact it has on my group statistics is small, simply because of my sample size. In addition, there is also the possibility of accounting fraud in some companies, and there is little or nothing that can be done about them.I am not trying to pass the buck or evade responsibility for any mistakes that persist but if you do find odd looking values for some variables that I report, especially for small samples, take them with a grain of salt.
Macro DataI do not report much macroeconomic data for two reasons. The first is that I do not have a macro focus, and my interests in macro variables occur only in the context of corporate finance or valuation issues. The second is that there are great (and free) sources for macro economic data, ranging from the to the and I don’t see the point of replicating something that they already do well. The macro variables that I track on my site relate to the price of risk, a key input into valuation, in both equity and debt markets:US Equity Risk Premiums: The equity risk premium is the price of risk in equity markets. In my view, it is the most comprehensive measure (much more so than PE ratios or other pricing multiples) of how stocks are being priced, with a higher (lower) equity risk premium correlating with lower (higher) stock prices. The conventional approach to measuring this premium is looking at past returns on stocks and treasuries (or something close to riskfree) and measuring the difference in historical returns and I report the updated levels (through 2020) for . I have argued that this approach is both backward looking and static, and have computed and reported forward-looking and dynamic equity risk premiums, based upon current stock price levels and expected future cash flows; you can find both the .ÌýCountry Risk Premiums: In a world where both investing and business is globalized, we need equity risk premiums for markets around the world, not only to value companies listed in those markets, but also to value companies that have operations in those countries. I will not delve into the details here, but I use the same approach that I have used for the last 30 years to estimate the additional risk premiums that I would charge for investing in other markets to get .ÌýBond Default Spreads: The bond default spread is the price of risk in corporate bond (lending) markets, and as with the equity risk premium, higher (lower) spreads go with lower (higher) corporate bond prices. In the where I compute historical equity risk premiums, I report historical returns on corporate bonds in two ratings classes (Moody’s Aaa and Baa ratings). I also report on bonds in different ratings classes and the current riskfree rate.I am not an interest rate prognosticator, but since today’s low rate environment seems to have made everyone a forecaster of interest rates, I do compute and compare it to current levels in this dataset.
Micro DataThe focus of my data collection is understanding how companies are operating and how investors are pricing them. That said, you will not find individual company data on my site for two reasons. The first is that I bear a responsibility (ethical and legal) to my raw data providers to not undercut their businesses by giving away that data for free. The second is that you don’t need my site or any public site to get data on an individual company; if you want to get data on a company, there is no better way to do it than go to the source, which is the company’s annual or quarterly filings. To understand and use the data, here are some specifics that you may (or may not) find useful:Industry: Data can be consolidated by geography, industry or company size, and I use all three, to some extent or the other. My primary consolidation is by industry and I break down my sample of 46,579 firms into 94 industry groupings. To make this classification, I start with the industry classifications that are in my raw data, but create my own industry groups, again to prevent stepping on the toes of my data providers. I know that this description is opaque, but the best way to understand my industry groups is to go , where I report the companies that I include in each industry.ÌýGeography: There is one dataset where I look at companies broken down by country, and I report a number of different statistics for 136 countries. I would caution you to take this data with a grain of salt, since there are only a handful of listings in some country. I do report much more data for a broader geographical classification, where I classify firms into six broad geographical groupings: Note that while emerging markets is a very large and diverse group, I do report statistics for India and China, two of the bigger components, separately.Averaging: I hope it does not sound patronizing, but I want to explain how I compute group values (averages), Ìýbecause it is not as obvious as it sounds. To illustrate why, consider the challenge of computing the . You could compute the PE ratio for each company in the group and take a simple average, but that approach has two problems. First, it weights small firms as much as large firms, and outliers can cause the average to take on outlandish values. Second, it eliminates firms that have negative earnings (and thus have no PE ratios) from the sample, potentially creating biased samples. Using a weighted average PE ratio can counter the first problem and using a median can reduce the outlier effect, but neither approach can deal with the second problem (of sample bias). For most of my industry averaging, I use an aggregation approach, where I compute ratios using aggregated values; to compute the PE ratio for chemical companies, I add up the market capitalizations of all chemical companies and divide that number by the aggregate net income of all chemical companies (including money losers). This ensures that (a) all companies are counted, (b) the computed number is weighted since larger companies contribute more to the aggregate and (c) the risk of outliers is reduced, since it is less likely to occur in a large sample than for an individual firm.Current data: The focus of this data update is to report on how companies did in 2020, rather than to provide historical time series. Since I am updating the data in early January 2021, and the complete numbers for 2020 will not be available until March or April at the earliest, I will be using the trailing twelve month numbers for operating variables (like revenues and operating income) to compute ratios. For accounting numbers, that will effectively be the twelve months through September 30, 2020, that will be captured in the data. This practice of focusing on current data can cause the computed numbers to be volatile, but I going back in time (more than 20 years in the US, less for other parts of the world) at this link.VariablesI confess that I have a primary constituency when I think of the variables that I would like to estimate, and that (selfishly) is me. Since my interests lie in corporate finance and valuation, the statistics that I compute are numbers that I will find useful when doing a corporate financial analysis or valuation of a company. Since I compute and report on dozens of variables, the best way of summarizing what you will in the following picture:Ìý
With each variable, I report the industry averages by geography. With cost of capital, for instance, I report the cost of capital by industry for the US at this link, and by geography: Europe, Emerging Markets (China and India), Australia, NZ & Canada, Japan & Global).
COVID EffectsI would normally not belabor the fact that my data is focused on the most recent year, but 2020 was an unusual year. Starting in February and extending for most of the rest of the year, the economic shutdown created turmoil in both financial markets an the real economy. While markets, for the most part, have recovered strongly, large segments of the real economy have not. Consequently, there are a couple of considerations if you use this year’s numbers:
COVID effects: To capture how COVID has played out in different sectors and geographies, I computed the changes in aggregate market capitalization during 2020 broken down by sub periods (1/1/20 - 2/14, 2/14- 3/20, 3/20 - 9/1 and 9/1 - 12/31/20), reflecting the ups and downs in the overall market. I also looked at the change in revenues and operating income over the last twelve months (October 2019 - September 2020) compared to revenues in the year prior (October 2018 - September 2019). Since the worst effects of the crises were in the second and third quarters of 2020, this comparison should provide insight into how much damage was wrought by the viral shutdown. Just as a preview of how consequential the year was for stock prices, take a look at the median percentage change in market capitalization in the table below:
I will come write more extensively about the COVID effects in a future post, but you can see the , ands you can also download the data for other geographies here: , ( and ), , & .Operating metrics: My computations for operating margins and accounting returns (returns on equity and capital) reflect the COVID effect on earnings in 2020, and not surprisingly, you will see that their values are much lower for the most damaged sectors (restaurants, airlines) than in prior years. If you are comparing across companies in these sectors, that may not be an issue, but if you are valuing companies and want to find a target value for margins or accounting returns, you will be better served using my archived values for these variables from 2019.Pricing metrics: I compute and report a range of pricing multiples from PE ratios to Enterprise Value (EV) to sales ratios, but as with the operating metrics, COVID has left its imprint on the numbers this year. As market capitalizations have quickly retraced their losses, but operating variables have not, the multiples reflect that disconnect. They are either not meaningful in some sectors, which are reporting aggregated losses, or at elevated levels in others (where the collective earnings are down significantly, but market values are not). Again, while this should not be an issue with cross company comparisons, there are two cautionary notes. The first is that investors who come in with strong preconceptions of what comprises cheap or expensive in pricing ratio terms or historic norms will find that everything looks exorbitantly priced. The other is that you will lose large segments of your peer groups if you stick with multiples like PE ratios for comparisons, since so many companies will be money losing.Access and Use of DataI know that the numbers (in terms of companies and variables) makes this data update sound like daunting work, but I will make a confession. I enjoy the process, even including the messy details, and it prepares me for the year to come. In fact, the time that this aggregated data saves me through the year, when I value and analyze companies, represents a huge multiple of the time I spend putting it together. Put simply, if you are tempted to anoint me for sainthood for sharing my data, you are overreaching because I would do it anyway, and sharing it costs nothing, while potentially benefiting you. If you decide to use the data, here are some things that I hope you will consider:Data access:ÌýThe data is accessible on my website, if you click on data. The data for 2020 is available under current data, and data from previous years under archived data. If you do click on current data, you will see the data classified into groupings based upon how I see the world (corporate governance, risk, investment returns, debt, dividends and pricing). You can see the data online for US companies by clicking on the links next to the data item, but I would strongly recommend that you download the excel spreadsheets that contain the data instead. Not only will this let you access data for other geographical regions, but each excel spreadsheet includes descriptions of the variables reported in that dataset and many include short YouTube videos explaining the data.Data Use:ÌýI know that those who download my data use it in many different contexts. If you use it at their jobs as corporate finance or equity analysts, I am glad to take some of that burden off you, and I hope that you find more enjoyable uses for the time you save. If you use my data to buttress an argument or debunk someone else’s, I wish you the best, as long as you don’t make it personal. If you use is it to back your case in legal settings, go ahead, but please do not involve me formally. I believe that courts are a graveyard for good valuation practices and while I do not begrudge you, I have no interest in playing that game.Data Questions: If you have a question about how a variable is computed, please check the website first, since the question has probably been answered already, but if you cannot find that answer, you know how to find me, and I will try to address your issues. As I mentioned earlier, the excel spreadsheets that contain the data include the descriptions of how I compute the variables.Suggestions and Complaints: Before you send off angry or impassioned emails to my team, about my data, you should know that this team has only one member and it is me. I am not a full time data service, and I cannot provide customized data solutions. If you find a mistake in a computation or a typo, please do let me know, and I will fix the error, perhaps not as quickly as you would like me to, but I will.In sum, I hope you find the data that I provide useful. In the next month, I will add about a dozen posts on what I see in the data, but I will do so with the recognition that change is the only constant and that assuming that things always revert back to historic norms is not an investment philosophy.
YouTube Video

Data Updates for 2021Data Update 1: A (Data) Look Back at a Most Forgettable Year!

On Monday, November 16, Airbnb filed it’s preliminary prospectus with the SEC, starting the clock on its long awaited initial public offering. On the same day, rising COVID cases caused more shut downs and restrictions around the world, creating a clear disconnect. Why would a company that derives its value from short term rentals by people who travel want to go public, when a out-of-control virus is causing its business to shut down? In this post, I will argue that there are good reasons for Airbnb's IPO timing, and make my first attempt at valuing this latest entrant into public markets.

Setting the Table

As with any valuation, the first step in valuing Airbnb is trying to understand its history and its business model, including how it has navigated the economic consequences of the COVID. In this section, I will start with a Ìýbrief history of the company, move on to reviewing its financials leading into 2020, and then look at how it has performed in 2020. I will end the section by looking at information disclosed in the recent prospectus filing that provides insights into the company’s journey to its initial public offering.

Timeline of Airbnb

Airbnb's roots go back to 2007, when during an industrial design conference in San Francisco, Brian Chesky and Joe Gebbia realized that there were opportunities for homeowners to rent their homes to visitors, and created a company called AirBed & Breakfast. Joined in 2008, by Nathan Blecharczyk, a Harvard graduate and technical architect, AirbedandBreakfast.com was born and later renamed Airbnb. In subsequent years, the company grew, with multiple rounds of funding from venture capital. Along the way, investors in the company rapidly escalated their pricing of the company from $1 billion in 2011 to $10 billion in 2014 to more than $30 billion in 2016. The time line below captures some (but not all) of the highlights in Airbnb’s history:

While the company has been able to hit new milestones of growth each year, there are two challenges that it has faced along the way, that need to be incorporated into any valuation you attach to the company today.ÌýLegal Challenges: The company has faced multiple challenges from cities that feel that its business model violates local zoning laws and regulations, and evades taxes. While you can attribute some of this pushback to hotel company lobbying and the inertia of the status quo, there is no doubt that Airbnb, like Uber, pushes regulatory and legal limits, taking action first and asking for permission later. While Airbnb has found a way to co-exist with laws in different cities, the restrictions they face vary widely across the world, with some locations (like New York) imposing much more stringent rules than others.Acquisitions: As the number of hosts and guests on Airbnb have climbed over the years, the company has invested in building a more robust platform for its rentals. While some of that money has been spent on internal improvements, much of it has been spent acquiring more than two dozen companies, most of them small, technology businesses.Ìý

Business Model

Airbnb's primary business model connects hosts who own houses and apartments with guests who want to rent them for short term stays, while providing a secure and easy-to-use platform for search, reservations, communications and payments. That said, though, it is worth peeking under the hood to see how this business model plays out as revenues and earnings. In the picture below, I look at the Airbnb business model, both in its original form (which still holds for hosts renting their own houses or apartments) and professional hosts (who own multiple units or even operate small hotels), a model it introduced recently and is still transitioning into:

In both versions of the model, Airbnb's revenues come from fees collected on rentals, with both the host and the guest paying in the individual host version, but only the host paying in the professional host version. In 2016, Airbnb extended the model, allowing hosts to to their guests, for a fee, with Airbnb keeping 20% of the payment. While the concept was heavily promoted, it has been slow to take off, with only $10 million in sales in 2017, but Airbnb has not given up, hiring Catherine Powell, a Disney theme park executive in 2020, to revamp the business.

The Financials, leading into 2020

The proof of a business is in the numbers, and Airbnb, in addition to posting impressive numbers on hosts, listings and guest nights, has also seen financial results from that growth. In the graph below, I look at gross bookings (the total amount spent by guests on their rentals), revenues to Airbnb from these booking (in dollar values and as a percent of gross bookings) and operating profitability, in dollar and percentage terms:

Source: Airbnb Prospectus (November 16, 2020)

Taking a closer look at the numbers, here are some preliminary features that stand out:

Growth is high, but the rate is declining: It may seem churlish too take issue with a company that has grown its revenues more than five fold over a five-year period, but as the company's base gets bigger, its growth rate, not surprisingly, is also declining. By the start of 2020, Airbnb had already become one of the largest players in its market of vacation and travel rentals, a sign of success, but also a crimp on future growth.Airbnb's revenue share has stayed stable: As gross bookings have increased, Airbnb's share of these bookings has remained stable, ranging from 12-13% of overall revenues. Note that the shift to the new business model for professional hosts (where Airbnb keeps 14% of the transaction revenue) is relatively recent, and it will take some time for that change to play out in the numbers. In addition, growth in the experiences business will also push this metric upwards, since Airbnb keeps a 20% share of those revenues.The company is edging towards profitability: To Airbnb's credit, it is closer to profitability than many of its high profile sharing-economy predecessors (such as Uber and Lyft) and the fact that it was able to report positive operating profits, albeit fleetingly in 2018, without playing the adjusted earnings game (where companies add back stock based compensation and other items to their bottom line to claim fictional profitability) puts them ahead of the pack.

In summary, coming into 2020, Airbnb was delivering a combination of growth driven by disruption and a pathway to profitability that made them a prime candidate for a public offering.

The COVID effect

I don’t think anyone expected 2020 to be the year that it was, and even in hindsight, it has been full of unwelcome surprises for individuals and businesses. While there were news stories about the virus for the first few weeks of 2020, they centered either on China or passengers on cruise ships that had been exposed to the virus. Once the virus made its presence felt elsewhere, in February and March, countries responded with partial and full economic shut downs that hurt all businesses. The travel business was particularly exposed, as people curtailed flying and traveling to distant destinations, and Airbnb was hurt badly in 2020, as can be seen in the graphs below:

Source: Airbnb Prospectus

The graph to the left looks at the effect of COVID on gross bookings and cancellations (in millions of nights), with the net bookings representing the difference. Note that cancellations exceeded bookings in March and April, at the height of the global shutdown, but have come back surprisingly well in the months after. In the graph to the right, you can see the effects on the financials, in a comparison of first nine months of 2019 to the first nine months of 2020, with gross bookings dropping 39% and operating losses almost tripling over the period.

The Prospectus Revelations

If Airbnb had broached the idea of a public offering in March and April, where the numbers were not just dire but potential catastrophic, it is likely that they would have been laughed out of the market. There are two factors that may have led Airbnb to reassess their prospects and file for a public offering now.Ìý

It’s relative: ÌýThe first is that it was not just Airbnb that felt the pain from the economic shut down. As we will see in the next section, the hotel and travel booking businesses were damaged even more than Airbnb, because of their large asset bases and debt levels. In relative terms, Airbnb might emerge from the COVID crisis, than going into it.ÌýRebound:The second is that business returned stronger than most had anticipated in 2020, with third quarter numbers coming in above expectations, and markets rebounded even more strongly with stocks recouping all of their early losses. When Airbnb filed its prospectus with the SEC on November 16, I don't think that there were many who were surprised at the timing.ÌýWhile Airbnb's general financial performance has been mostly public for the last few years, the prospectus provides more detail as well as guidance on governance and the terms of the offering.

Pathway to Profitability: Digging through Airbnb's financials over the last five years, and breaking down the expenses, here is what we see:Source: Airbnb Prospectus (Nov 16)
Note that, at least through the most recent years, there is little evidence of economies of scale, since the direct operating costs have stayed at between 40-42% of revenues and the other costs have, for the most part, been rising. In 2019, the company also reported a substantial restructuring charge that presumably was one-time and extraordinary, but that item bears watching, since it has become a convenient vehicle for companies to hide ongoing operating expenses.Use of Proceeds: While the details are still being worked out, it is rumored that Airbnb is looking to raise about $3 billion in proceeds on the offering date, and that while some of the proceeds will be used to retire existing debt, most of it will be held by the company to cover future investment needs.Share classes: In keeping with the practices of tech companies that have gone public in recent years, Airbnb has shares with different voting rights: class A shares with one voting right per share, class B shares with 20 voting rights per share, and class C & class H shares with no voting rights per share. Not surprisingly, the class B shares will be held by founders and other insiders, allowing them control of the company, even if they own well below 50% of all shares outstanding. It is the class A shares that will be available to shareholders who buy on the offering day, and will remain the most liquid of the share classes thereafter. It is not clear why there are class C shares, other than to give founders, who already have control, even more control in future years, if they feel threatened.ÌýAn ESG twist: It should come as no surprise that in an age where companies are valued on their "goodness", Airbnb is signaling it's intent to be socially responsible, with Brian Chesky making explicit the corporate values for the company, including "having an infinite time horizon" and "serving all of our customers". In addition, the proceeds from the non-voting class H shares , though it is not clear whether the primary intent is to give hosts a stake in the company’s success, or to help them out during periods of need.ÌýI remain skeptical about ESG, but will hold off on passing judgment on whether this is just a public relations ploy.

The Hospitality Business

To value Airbnb, we need to start with an assessment of the market that it is targeting and then understand the competition that the company faces. In this section, I will start with a look at the market size and then examine the hotel and booking companies that comprise its competition.

The Market (TAM)

There are two ways in which I can describe Airbnb's total addressable market. One is to look the hotel business globally, which generated in excess of $600 billion in revenues in 2019, with the following characteristics:

The hotel business is large, but its growth has slowed over the last five years, and it remains concentrated, with the top five hotel chains accounting for a larger and larger portion of the overall market every year since 2014. While the US remains the largest market, geographically, Asia is the center of growth, with China leading the way.Ìý
There are some who believe that the conventional hotel market understates the potential market for a sharing economy company like Airbnb, since it can increase the supply of rental units without major new investment, and perhaps induce new entrants into the business. After all, the ride sharing companies have doubled or even tripled the size of the car service business in the last decade, using this template. It should come as no surprise that Airbnb believes that its total addressable market is much bigger than the hotel business. In 2011, in its infancy as a company, Airbnb estimated that its total addressable market at the 1.9 billion trips that were booked in 2010, and its share of that market at 10.6 million trips, as can be seen in this graph from the company in an early VC pitch:
In its prospectus, driven partially by its past success, and partly by the need to justify a large market cap, Airbnb has expanded its estimate of market potential to $3.4 trillion, as evidenced in this excerpt from the prospectus:

We have a substantial market opportunity in the growing travel market and experience economy. We estimate our serviceable addressable market (“SAM�) today to be $1.5 trillion, including $1.2 trillion for short-term stays and $239 billion for experiences. We estimate our total addressable market (“TAM�) to be $3.4 trillion, including $1.8 trillion for short-term stays, $210 billion for long-term stays, and $1.4 trillion for experiences.

In my view, Airbnb's targetable market falls somewhere in the middle, clearly higher than just the hotel business of $600 billion, but below Airbnb's upper end estimate of $2 trillion for this business. That is because there are parts of the world, where the Airbnb model will be less successful than it has been in the United States, either because of consumer behavior or regulatory restrictions. Given how much trouble Airbnb has had in the experiences business, I think Airbnb’s estimate of $1.4 trillion for that business is more fictional than even aspirational.

The Players

To make a judgment on Airbnb's future, we need to understand two peer groups. The first is the hotel business, since it is the business that is most at risk of being disrupted by the Airbnb model. The other is the online travel booking business, where there are large players like Expedia and Booking.com which have, at least for segments of their business, made their money by acting, like Airbnb, as intermediaries or brokers connecting guests with hospitality offerers.Ìý

1. The Hotel Business

The hotel business is both large and diverse, composed of hotels that range the spectrum from luxury to budget. To get a measure of the business, I have listed the 25 largest publicly traded hotel companies (in market capitalization) in the world below, with Marriott topping the list, with revenues of about $21 billion in 2019:

The conventional hotel business is an asset-heavy business, with a significant real estate component to its value, and while some hotel companies have stayed with that model, others have moved on to a more capital-light model, where the real estate is owned by a separate entity (both in terms of ownership and control) and the hotel companies operates primarily as an operator. Marriot, for instance, follows the latter model, with the Marriott REIT owning the real estate, and Marriott collecting operating revenues from running the hotels. In addition, the global economic shutdown precipitated by COVID has wreaked havoc on hotel company revenues and profits, with revenues down about a third (in annualized terms) in the last 12 months, relative to 2019.Ìý

2. The Travel Booking Business

While the hotel business is the one being disrupted the most by Airbnb, it is the travel booking business that is closest to the Airbnb business model. That business is also dominated by large players, with Expedia and Booking.com being the biggest. In the table below, I look at the revenues and operating income at these companies in 2019 and the last 12 months:

While Expedia and Booking.com both generate revenues from operating as middlemen between travelers and hospitality providers, just like Airbnb does, there are two key differences:

Other businesses: Both Expedia and Booking.com also operate in other businesses that drive revenues and margins. First, they generate revenues by buying blocks of hotel rooms at a discount from hotels, and then reselling them at a higher price, in what they call the "merchant" business. Second, they also derive revenues from online advertising by hotels and travel providers. Expedia gets a much larger share (47%) of its revenues from the merchant business than Booking.com (25%), which may explain its lower margins.Status Quo vs Disruption: Both Expedia and Booking.com were designed to make money off the status quo in the hospitality business, and derived all of their revenues until recently from existing hotels and airlines. In reaction to Airbnb's success, both companies have tried to expand into the home and apartment rental businesses, but these listings still represent a small fraction of overall revenues.

The Valuation

To value Airbnb, I will follow a familiar script, at least for me. I will start by telling my Airbnb story, based upon the market it is in and its competition, current and potential, and then use this story as a launching pad for my valuation of the company. I will complete the valuation by looking at its sensitivity to key value drivers and bring in uncertainty into the equation.

Story and Numbers

I believe that Airbnb will continue to grow, while finding a pathway to profitability. Airbnb's growth in gross bookings will come not only from disrupting and taking market share from the hotel business, bad news for conventional hotel companies and travel providers who serves them, but also from continued expansion of non-conventional hospitality providers (home and apartment owners). As it grows, Airbnb's share of those gross bookings is likely to plateau at close to current levels, but its operating margins will continue to improve towards travel booking industry levels, as product development, marketing and G&A costs decrease, not in dollar terms, but as a percent of revenues. While Airbnb is enthusiastic about the experiences business, it is likely to remain a tangential business, contributing only marginally to revenues and profitability. Since Airbnb has a light debt load and is closer to profitability than most of the sharing-economy companies that have gone public in recent years, I will assume that their risk will approach that of the travel business, and that the risk of failure is low. In terms of inputs, this story translates into the following:

The COVID After-effects: The comeback from COVID will be slow in 2021, with Airbnb seeing revenues return, albeit to less than 2019 levels, while continuing to lose money (with operating margins of -10%).Growth in Gross Bookings: In 2019, Airbnb’s gross bookings grew 29.25%, lower than the growth rate in prior years, reflecting its increasing scale. After its recovery from COVID in 2021, gross bookings will continue to grow at a compounded annual growth rate of 25% between 2022 and 2025, and growth will drop down over the following years. In 2031, I expect Airbnb’s gross bookings to climb above $150 billion, about 60% higher than Booking.com’s gross bookings in 2019 and 40% higher than Expedia's gross bookings in that year.Revenues as percent of Bookings: Over the next decade, revenues as a percent of gross bookings will increase only mildly from current levels (12%-13) to 14%, sustained by the new host model for professional hosts and the supplemental benefits from Experiences business.ÌýTarget Operating Margin: This will be a key component of Airbnb’s story, and I will assume that the operating margins will improve over the next decade to 25%, lower than Booking.com’s 2019 operating margin of 35.48%, but higher than the margins for Expedia or the hotel business.Sales to Invested Capital: While Airbnb has a capital-light model, it’s platform requires new investments in either product development and acquisitions. In 2020, Airbnb's sales to invested capital was 1.82, but the invested capital was negative in the prior year, making it unreliable, and ÌýBooking.com had a sales to invested capital of 1.91 in 2019. I assume that Airbnb will be able to generate $2.00 of revenues per dollar of invested capital in the next decade.Cost of Capital & Failure Risk: For the cost of capital, I will assume that Airbnb’s cost of capital will be 6.50%, close to the cost of capital of hotel companies, to start the valuation, but over time, it will rise to 7.23%, reflecting an expected increase in the treasury bond rate from current levels to 2% in 2031. While Airbnb has flirted with profitability and has little debt, it still remains a young, money losing company, and I will assume a 10% chance of failure.Share Count: Getting the share count for a company on the verge of going public is always tricky, as preferred shares get converted to common shares, options and warrants are outstanding and additional shares are issued on the offering date. For Airbnb, there is the added complication of a 2 for 1 stock split which occurred only a few weeks prior to the offering. For the moment, therefore, the share count is still a number that is in progress, but the next update on the prospectus should provide more clarity. (Right after I posted this, Airbnb updated their prospectus to reflect a more accurate share count. The value per share should now be closer to the right value)With these inputs, my valuation of Airbnb is captured in the picture below:

The value that I derive for Airbnb, with my story and inputs, is about $36 billion, with $3 billion in expected proceeds from the IPO augmenting the value and netting out the value of options outstanding. The per share value based upon the latest share count is about $48/share.
Value Drivers and Dealing with UncertaintyThere are two key drivers of Airbnb’s value. The first is the growth rate in gross bookings and the resulting expected dollar value in 2031, with value increasing with expected gross bookings. The other is the target operating margin, in 2031, with higher margins translating into higher value. In the table below, I list out the value of equity in Airbnb for variants of gross booking growth and operating margins:

Rather than view this table as anything goes, I would use it to make break even assessments, given what Airbnb trades at. For instance, if the market capitalization of Airbnb today is $60 billion, you would need it to deliver gross billings of $200 billion in 2031, with an operating margin of close to 35%. There is ample room for disagreement on Airbnb’s value, since there are plausible combinations of revenue growth and margins that deliver very different equity values. To more explicitly capture the effect of this uncertainty, I replace my point estimates of gross bookings growth, target margin and cost of capital with distributions, run simulations and capture the consequences in a value distribution:

In short, there is nothing sacrosanct about my value judgment for Airbnb and if you disagree with me, even strongly, I understand your point of view. In fact, it is these differences that allow for buyers and sellers to co-exist in the market.

Previewing the IPO

While we can debate what Airbnb’s value truly is, an IPO is a pricing game. Put simply, rather than operate under the delusion that it is value that drive decisions, it is healthier to recognize that bankers price IPOs, not value them, for the offering, that much of the trading on the offering day and the weeks thereafter is driven by traders, trying to gauge mood and momentum. In this section, I will look at the contours of this pricing game for Airbnb, and implications for investors who may be more concerned about value.
An IPO is a Pricing Game
To price an IPO, traders look at two places for guidance. The first is the VC pricing of the company in the rounds leading into the public offering. The second is the market pricing of publicly traded companies in the peer groups, companies that investors will compare the company to, in setting prices.Ìý

1. Venture Capital Pricing: ÌýAs mentioned earlier, Airbnb has raised more than two dozen rounds of venture capital over its lifetime, and has been reprised multiple times. In the graph below, I look at the trend lines in Airbnb’s pricing, based upon VC assessments:

The pricing attached to Airbnb climbed dramatically in the first few years, reaching $31 billion in 2016, but then settled into a period of stagnation. In April 2020, at the height of the COVID crisis, the company raised more capital from VC investors, who reduced its pricing to $26 billion.Ìý

2. Peer Group Pricing: To price Airbnb, relative to publicly traded companies, I have computed pricing multiples for hotel and booking companies in the table below:

Applying any of these multiples to Airbnb’s current operating metrics (revenues, EBITDA or net income) will yield valuations that are too low, because the company is still growing and finessing its business model. To get a more realistic pricing, I apply the multiples to Airbnb’s expected values for these metrics in 2025, and then discounting the future values back to today.

In summary, these numbers yield a much higher pricing for Airbnb’s equity, if it is priced similarly to Booking.com, and a much lower pricing, if Expedia is used asÌýthe comparable.

Investment Judgments

In the coming weeks, Airbnb will update its prospectus to reflect more details on its IPO, and bankers will set an offering price per share, based primarily on the feedback that they get from potential investors to different ÌýI may be jumping the gun here, but given how well the market has treated capital-light and technology companies this year, I would not be surprised if the market attaches a pricing of all above my estimated value for Airbnb's equity. As a market participant, you have three ways of participating in the Airbnb sweepstakes:

Get in on the offering: Given the propensity of bankers to under price offerings, and given how the market has been behaving in the last few months, you can try to get a share of the shares at the offering price. This game gets easier to play if you are on the preferred client list at Morgan Stanley or Goldman Sachs, and are allowed access to the offering, but much more difficult, if you are not. Even if you do get in on the offering, there is no guaranteed payoff, because bankers do sometimes over price IPOs, as they did a few times in 2019.Play the trading game:ÌýIn the trading game, value is a minor factor, at best, in whether you succeed. Your success will depend upon gauging the market mood and momentum on Airbnb and getting ahead of it and paying attention to what I call incremental information, small news stories that may have little or even no effect on value but can be consequential for momentum.ÌýBe an investor: If you areÌýtruly a value investor, you should not beÌýruling out Airbnb just because it is money-losing or a young company facing multiple uncertainties. Instead, you should value AirbnbÌýyourself, and drawÌýup decision rules well ahead ofÌýthe offering. Since I have my estimated Ìývalue for Airbnb at $36 billion, I will go first, using the valuation results, by decile, that come from my simulation:Ìý

If equity is priced at <$28 billion (20% percentile): A bargainIf equity is priced between $28 & $33 (40th percentile) billion: A solid buyIf equity is priced between $33 (40th percentile) & $38 billion (60thpercentile): A fair valueIf equity is priced between $38 (60th percentile) & $44 billion (80thpercentile): Too richly pricedIf equity is priced > $44 billion: Over valued

As I have argued in prior posts, it is not my preference to sell short on stocks like Airbnb, even if I believe the they are significantly over priced, given how much more powerful momentum is than any fundamentals in driving stock prices.

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Raw Data

Spreadsheets

Over the last eight months, I have written a series of posts on the market and how it has adapted and adjusted to COVID. The very first of these posts, on February 26, 2020, was about two weeks into the meltdown and it is indicative of how little we knew about the virus then, and what effects it would have on the economy and the market. More than seven months later, there is still much that we still do not know about COVID, as it continues to wreak havoc on global economies and businesses. In this post, I intend to wrap up this series with a final post, reviewing how value has been reallocated across companies during the months, and providing an updated valuation of the S&P 500. Given that much of Europe is going into lockdown, and that there is no vaccine in sight, this may seem premature, but I have a feeling that there will be other uncertainties that will vie for market attention over the coming weeks, especially as the US election results play out in legal and legislative arenas.Ìý

A Market Overview

For those of you who have read my prior posts on COVID's market effects, I will follow a familiar script. I will start by noting that this crisis has played out in markets in three acts, captured in the graph below where I look at the S&P 500 and the NASDAQ, since the start of this year:

The year began auspiciously for US equities, as stocks built on positive performance in 2019 (when it was up more than 30%) and continued to rise. In fact, on February 14, US equities were are at all time highs, when news of the virus encroaching into Europe and then rapidly expanding across the world caused stocks to go into a tailspin that lasted just over five weeks. On March 23, 2020, amidst talk of doomsday for stocks, momentum shifted, with some credit to the Fed, and stocks went on a run that extended through the end of August, recovering almost all of the ground lost during the meltdown. In September and October, stocks were choppy with more bad days than good, as investors recalibrated. While the graph is US-centric, this was a global crisis, and equities around the global moved through the same three phases, as you can see in the table below, where I look at selected equity indices from around the world:

Note that the pattern Ìýis very similar, across indices, with steep drops in the first phase (2/14-3/20), followed by steep increases in the following months (3/20-9/1) before settling down in the last two months (9/1-11/1). As equities went on a turbulent ride, other asset classes were also affected, with US treasuries benefiting from a flight to safety in the first five weeks:US treasury yields dropped across all maturity classes between February 14 and March 20, with short term rates dropping close to zero and 10-year T.Bond rates dropping fro 1.7% to 0.7%. I know it is fashionable now to attribute all things related to interest rates to the Fed's actions, but the bulk of the decline in treasury rates occurred before the Fed finally acted in mid-March, and it is surprising how little movement there has been in treasury rates in the months since. Though treasury yields have stayed at their mid-March levels, the rise and fall of the fear factor in the equity markets also played out in the corporate bonds, in the form of movements in corporate default spreads:
When stocks were melting down between February 14 and March 20, corporate bond spreads were also widening dramatically, but those spreads have fallen back almost to pre-crisis levels for the higher ratings, and mostly recovered even for the lower ratings.Ìý
Looking at oil and copper, two economically sensitive commodities, you see reflections of the turbulence that affected equities and corporate bond markets:
Both oil and copper prices dropped significantly between February 14 and March 20, with oil showing a much larger decline (down more than 50%) than copper (about 15%), but both commodities have recovered, with copper now up almost 17% from pre-crisis levels. Oil, in spite of its comeback in the last few months, is still down more than 30% from pre-crisis levels. Finally, I look at gold and bitcoin, an odd pair, but both touted by their advocates as crisis assets:While bitcoin is now up more than gold over the period, gold has performed better as a crisis asset, holding its own when equities were melting down between February 14 and March 20. In contrast, the crypto currencies (Bitcoin and Ethereum) have behaved like very risky equities, going down more than equities, when stocks were going down, and rising more, when they rose.
Equity Markets: A Wealth TransferThe quick recovery in equity markets has led some to believe that the market has ignored the crisis, but that is not true. While equity values have recovered globally, there has been a significant shift in value across regions, sectors and company types. While I have talked about this value reallocation in previous posts, I will update the numbers and provide a summary of what the data is showing as of November 1. First, this crisis has played out very differently in different parts of the world, as you can see below, where I break down the market capitalizations of all publicly traded companies, by region, on February 14, 2020 and on November 1, 2020, with a table showing the percentage changes over the period:
The markets that are showing the most residual damage are Africa, Eastern Europe & Russia and Latin America. While the easy explanation is that they are all emerging markets, note that Asia has emerged not just unscathed, but as one of the best performing regions of the world. Among the developed markets, the UK is the worst performer, perhaps dragged down by the continued uncertainty of how Brexit will play out. A better explanation would be that these are regions heavily dependent on natural resource and infrastructure businesses, and as we will see in the next section, those have been adversely affected by this crisis. In addition, since these returns are in US dollars, currency movements add to the effect, with depreciating (appreciating) currencies, against the dollar, worsening (improving) returns. Building on the theme that damage has varied across sections, I break down aggregate market cap by sectors, on February 14 and November 20, in the graph below (also with percent changes over the period:
Again, the shift in value is clear and decisive, with consumer discretionary, technology and health care gaining at the expense of energy, real estate, utilities and financials. Put simply, capital light businesses have gained at the expense of capital intensive ones, and breaking down sectors into finer industry detail, emphasizes this shift, with the ten best and worst performing industries below:
In an earlier post, I connected this value shift across industries to corporate life cycles, noting that younger, higher growth companies have gained value at the expense of older, more mature businesses, as can be seen in the tables below, where I break down the value change across companies, first by age, and then by expected revenue growth rate, into deciles:Download Ìý&
The youngest companies have gained value over this crisis, whereas the oldest companies have lost value, and high growth companies have benefited at the expense of low growth firms. As this shift has occurred, it is not surprising that the stocks most favored by value investors (low PE/PBV, high dividends) have underperformed the stocks that are most favored by growth investors. I capture this in the table below, where I first look at value changes across companies, first classified across PE ratios and then across dividend yields:DownloadÌýÌý&ÌýValue investors have also warned us over the last decade about two trends in corporate behavior, an increase in debt loads at some companies and a surge in stock buybacks. To evaluate whether those warnings were justified, I looked at companies classified by debt load (net debt to EBITDA) into deciles and computed value changes between February 14 and November 1.
On this front, I think that the message is clear that the more indebted a company, the more exposed it was to damage during this crisis. On the buyback front, the results are a little murkier. In the graph below, I look at value changes for four groups of companies, (1) those that returned no cash at all in 2019 (no dividends or buybacks), (2) those that paid only dividends, (3) those that returned cash in the form of buybacks and (4) those that did both:

There is a muddled message in this graph. While companies that returned no cash to their shareholders in 2019 fared better overall than companies that returned cash (either in dividends or in buybacks) in 2019, companies that returned cash only in the form of buybacks recovered faster and more completely the companies that paid only dividends. Companies that both paid dividends and bought back stock did worst of all. If flexibility is key to surviving a crisis, it is possible that this crisis will make companies more reluctant to return cash, in general, and when they do, it is also more likely that you will see that cash returned in the form of buybacks than dividends, since the former are easily retracted but the latter are sticky.
Finally, no post on US equities is complete without a mention of the FANGAM stocks, a topic that I focused on in my last post. Updating the numbers through November 1, here is how these six companies have performed over the crisis, relative to the rest of the market:Download data

As you can see, the FANGAM stocks have added $1.25 trillion in aggregate market cap since February 14, while all other US equities have shed $1.32 trillion over that period. If the market has almost fully recovered from its early swoon, the credit has to go almost entirely to these six companies.
The Resilient Risk Capital ThesisThe best way to summarize how this crisis has affected companies is to summarize the value transfer from what would be consider "risk on" categories (young, high growth, high PE, low or no dividends and high debt) to "risk off" categories (old, low growth, low PE, high dividends and low debt), looking at the top and bottom deciles of each grouping:
Note that in almost every category, other than debt, the "risk on" group gained value at the expense of the "risk off" group. One explanation that I offered in my post from a Ìýfew weeks ago was that, unlike prior crises, risk capital (defined as capital invested in the highest risk assets, such as venture capital and investments in below investment grade bonds) has stayed in the game, as can be seen in the behavior of VC fund flows and issuances of high yield bonds (updated to include the third quarter of 2020):
In fact, it is this resilience of risk capital that explains why the equity risk premium for the S&P 500, which soared in the first five weeks of this crisis, has reverted back to pre-crisis levels:
Put simply, markets, for better or worse, seem to be sending the message that the fear factor of the crisis has passed, though earnings and cash flows will need to be tweaked.
Market Assessment: Predictive Mechanism or Animal SpiritsAs markets have risen over the last few months, there has been a fair amount of hand wringing about animal spirits and irrational exuberance driving markets higher. Some of this concern has come from the clear disconnect between stocks going up and economic malaise, but I noted that this is neither unusual nor unexpected, using this graph of stock returns and real GDP growth, by quarter:

Looking at the quarterly data over the last 60 years, there has been little to no relationship between stock returns in a quarter and the GDP change in that quarter, and if there is one, it is mildly negative, i.e., stocks are Ìýslightly more likely to go up (down) in a quarter when GDP is down (up). While that may surprise some people, it is entirely understandable, when you recognize that stock markets are predictive mechanisms, and that is borne out by the data, with stock returns becoming positively correlated with GDP growth in future quarters. Note that while the correlation increases as you look three or four quarters ahead, it flattens out at about 0.26 indicating that markets are noisy predictors; they are wrong as often as they are right, but given a choice between trusting markets and going with market gurus, I will take the former every single time.
There is a debate to be had about whether markets have over adjusted to the possibility of a vaccine and the economy reopening, and to address that question, I decided to value the S&P 500 again; I did value it on June 1, 2020 and found it to be close to fairly valued. I revisited my assumptions, updating my estimates of earnings for the index in the near years (2020, 2021 and 2022), where the bulk of the damage from this crisis will be done.
Note that in the intervening five months, since my last valuation, analysts tracking the index have become more optimistic about earnings in 2020 and 2021. The resulting valuation reflects these improved estimates:

Based upon my inputs, I arrive at a value for the index of just over 3100, which would make stocks mildly over valued. I also followed up with a simulation of this valuation, based upon distributions for my key inputs, and the results are below:


The simulation reinforces the findings in the base case valuation. You could make a case that stocks are over valued, and that case will be built on the premise that the economic damage from this crisis will be much greater and long lasting that analysts believe. However, if your argument is that markets have gone crazy and that nothing explains stock prices, you may want to evaluate that view, and consider at least the possibility that your world view (about how the economy will recover and the virus will play out) is wildly at odds with the market consensus. That leaves open the unpleasant possibility that it is you that is being irrational and wrong, not the market.
Crisis as Crucible: Lessons learned, unlearned and relearnedEvery crisis is a crucible, exposing what we don't know and putting our faith to the test. This one has been no different, and while I will not tell you that I have enjoyed it, I have learned some lessons from it.Respect markets, even if you disagree with them: Markets are not all knowing and they are definitely not efficient, but they are extraordinary platforms for conveying a consensus view of the future. While you and I may disagree with the market view, and markets can be wrong, it behooves us all to at least try and understand the message that it delivers.Time to move on: For many managers and investors, the COVID crisis is a reminder, sometimes in painful terms, that we are now well into the 21st century and continuing to use tools, techniques and metrics that were developed and tested on 20th century data is a recipe for disaster. That was the underlying message in my posts on value investing from last month.Importance of Flexibility: If you look across what companies that have done well during this crisis share in common, it is flexibility, with companies that can adapt quickly to new circumstances improving their odds of winning. In the same vein, it seems self defeating for companies to borrow too much or lock themselves into paying large dividends, since both reduce their capacity to respond quickly to changed circumstances.All in all, it has been an interesting roller coaster ride over these last few months, and I am glad that you were able to join me for at least some of the ride. It is definitely not over, but I have a feeling it is time for me to move on. There are other attractions at this fair!
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If you have had the endurance to make your way through my first two posts on value investing, I compliment you on your staying power, but I am sure that, if you are a value investor, you have found my take on it to be unduly negative. In this, my third post, I want to explain why value investing is in trouble and point to ways in which it can be reinvented, to gain new life. I am sure that many of you will disagree both with my diagnosis and my solutions, but I welcome your points of view.

Value Investing: Has it lost its way?

I have never made the pilgrimage to the Berkshire Hathaway meetings, but I did visit Omaha, around the time of the annual meeting, a few years ago, to talk to some of the true believers who had made the trek. I do not think that I will be invited back again, because I argued in harsh terms that value investing had lost its way at three levels.

It has become rigid: In the decades since Ben Graham published Security Analysis, value investing has developed rules for investing that have no give to them. Some of these rules reflect value investing history (screens for current and quick ratios), Ìýsome are a throwback in time, and some just seem curmudgeonly. For instance, Ìývalue investing has been steadfast in its view that companies that do not have significant tangible assets, relative to their market value, and that view has kept many value investors out of technology stocks for most of the last three decades. Similarly, value investing's focus on dividends has caused adherents to concentrate their holdings in utilities, financial service companies and older consumer product companies, as younger companies have shifted away to returning cash in buybacks.ÌýIt has become ritualistic: The rituals of value investing are well established, from the annual trek to Omaha, to the claim that your investment education is incomplete unless you have read Ben Graham's Intelligent Investor and Security Analysis to an almost unquestioning belief that anything said by Warren Buffett or Charlie Munger has to be right.ÌýIts has become righteous: While investors of all stripes believe that their "investing ways" will yield payoffs, some value investors seem to feel entitled to high returns because they have followed all of the rules and rituals. In fact, they view investors who deviate from the script as shallow speculators, but are convinced that they will fail in the "long term".

Put simply, value investing, at least as practiced by some of its advocates, has evolved into a religion, rather than a philosophy, viewing other ways of investing as not just misguided, but wrong and deserving of punishment.Ìý

A New Paradigm for Value Investing

For value investing to rediscover its roots and reclaim its effectiveness, I believe that it has to change in fundamental ways. As I list some of these changes, they may sound heretical, especially if you have spent decades in the value investing trenches.Ìý

Be clearerÌýabout the distinction between value and price:ÌýWhile value and price are often used interchangeably by some market commentators, they are the results of very different processes and require different tools to assess and forecast.
Value is a function of cash flows, growth and risk, and any intrinsic valuation model that does not explicitly forecast cash flows or adjust for risk is lacking core elements. Price is determined by demand and supply, and moved by mood and momentum, and you price an asset by looking at how the market is pricing comparable or similar assets. I am surprised that so many value investors seem to view discounted cash flow valuation as a speculative exercise, and instead pin their analysis on comparing comparing on pricing multiples (PE, Price to book etc.). After all, there should be no disagreement that the value of a business comes from its future cash flows, and the uncertainty you feel about those cash flows, and as I see it, all that discounted cash flow valuation does is bring these into the fold:

It is true that you are forecasting future cash flows and trying to adjust for risk in intrinsic valuation, and that both exercises expose you to error, but I don't see how using a pricing ratio or a short cut makes that error or uncertainty go away.ÌýRather than avoid uncertainty, face up to it: Many value investors view uncertainty as "bad" and "something to be avoided", and it is this perspective that has led them away from investing in growth companies, where you have to grapple with forecasting the future and towards investing in mature companies with tangible assets. The truth is that uncertainty is a feature of investing, not a bug, and that it always exists, even with the most mature, established companies, albeit in smaller doses.
While it is true that there is less uncertainty, when valuing more mature companies in stable markets, you are more likely to find those mistakes in companies where the uncertainty is greatest about the future, either because they are young or distressed, or because the macroeconomic environment is challenging. In fact, uncertainty underlies almost every part of intrinsic value, whether it be from micro to macro sources:
To deal with that uncertainty, value investors need to expand their tool boxes to .ÌýMargin of safety is not a substitute risk measure:ÌýI know that value investors view traditional risk and return models with disdain, but there is nothing in intrinsic value that requires swearing allegiance to betas and modern portfolio theory. In fact, if you don't like betas, intrinsic valuation is flexible enough to allow you to , whether they be based upon earnings, debt or accounting ratios.
For those value investors who argue that the margin of safety is a better proxy for risk, it is worth emphasizing that the margin of safety comes into play only after you have valued a company, and to value a company, you need a measure of risk. When used, the margin of safety creates trade offs, where you avoid one type of investment mistake for another:
As to whether having a large MOS is a net plus or minus depends in large part on whether value investors can afford to be picky. One simply measure that the margin of safety has been set too high is a portfolio that is disproportionately in cash, an indication that you have set your standards so high that too few equities pass through.ÌýDon't take accounting numbers at face value: It is undeniable that value investing has an accounting focus, with earnings and book value playing a central role in investing strategies. There is good reason to trust those numbers less now than in decades past, for a few reasons. One is that companies have become much more aggressive in playing accounting games, using pro forma income statements to skew the numbers in their favor. The second is that as the center of gravity in the economy has shifted away from manufacturing companies to technology and service companies, accounting has struggled to keep up. In fact, it is clear that the accounting treatment of R&D has resulted in the understatement of book values of technology and pharmaceutical companies.ÌýYou can pick stocks, and be diversified, at the same time: While not all value investors make this contention, a surprisingly large number seem to view concentrated portfolios as a hallmark of good value investing, arguing that spreading your bets across too many stocks will dilute your upside. The choice of whether you want to pick good stocks or be diversified is a false one, since there is no reason you cannot do both. After all, you have thousands of publicly traded stocks to pick from, and all that diversification requires is that rather than put your money in the very best stock or the five best stocks, you should hold the best thirty or forty stocks. My reasoning for diversification is built on the presumption that any investment, no matter how well researched and backed up, comes with uncertainty about the payoff, either because you missed a key element when valuing the investment or because the market may not correct its mistakes. In a post from a few years ago, I presented the choice between concentration and diversification in terms of those two uncertainties, i.e., about value and the price/value gap closing:

I think that value investors are on shaky ground assuming that doing your homework and focusing on mature companies yield precise valuations, and on even shakier ground, when assuming that markets correct these mistakes in a timely fashion. In a market, where even the most mature of companies are finding their businesses disrupted and market momentum is augmented by passive trading, having a concentrated portfolio is foolhardy.Don't feel entitled to be rewarded for your virtue: Investing is not a morality play, and there are no virtuous ways of making money. The distinction between investing and speculating is not only a fine one, but very much in the eyes of the beholder. To hold any investing philosophy as better than the rest is a sign of hubris and an invitation for markets to take you down. If you are a value investor, that is your choice, but it should not preclude you from treating other investors with respect and borrowing tools to enhance your returns. I will argue that respecting other investors and considering their investment philosophies with respect can allow value investors to borrow components from other philosophies to augment their returns.ÌýMoving ForwardInvestors, when asked to pick an investment philosophy, gravitate towards value investing, drawn by both its way of thinking about markets and its history of success in markets. While that dominance was unquestioned for much of the twentieth century, when low PE/PBV stocks earned significantly higher returns than high PE/PBV stocks, the last decade has shaken the faith of even diehard value investors. While some in this group see this as a passing phase or the result of central banking overreach, I believe that value investing has lost its edge, partly because of its dependence on measures and metrics that have become less meaningful over time and partly because the global economy has changed, with ripple effects on markets. To rediscover itself, value investing needs to get over its discomfort with uncertainty and be more willing to define value broadly, to include not just countable and physical assets in place but also investments in intangible and growth assets.
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Blog Posts on Value Investing (2020)Value Investing II: A Lost Decade

In the last post, I noted the strong backing for value investing for much of the last century, where a combination of investing success stories and numbers that back those stories allowed it to acquire its lead position among investment philosophies. In this post, I plan to look at the underbelly of value investing, by first going back to the "good old days" for value investing, and probing the numbers more closely to see if even in those days, there were red lights that were being ignored. I will follow up by looking at the last decade (2010-2019), a period where value investing lost its sheen and even long time value investors started questioning its standing, and then extend this discussion to 2020, as COVID has caused further damage. I will close by looking at the explanations for this lost decade, not so much as a post-mortem, but to get a measure of what value investors may need to do, going forward.

The Dark Side of the Good Old Days

For value investors, nostalgic for the good old days, when the dominance of value investing was unquestioned, I think it is worth pointing out that the good old days were never that good, and that even in those days, there were legitimate questions about the payoff to value investing that remained unanswered or ignored.

Revisiting the Value Premium

For some value investors, the graph from , showing that low price to book stocks have outperformed high price to book stocks by more than 5% a year, going back to 1927 in the US, is all the proof they need to conclude that value investing has won the investing game, but even that rosy history has warts that are worth examining. In the graph below, I look at the year-to-year movements in the value premium, i.e. the difference between the annual returns on the lowest and highest deciles of price to book ratios:

Source:Ìý

While it is true that low price to book stocks earned higher annual returns than high price to book stocks over the entire time period, note that there is significant variation over time, and that the high price to book stocks delivered higher returns in 44 of the 93 years of data. In fact, one of the pitches that growth investors made, with some success, during the glory days of value investing was that you could still succeed as a growth investor, if you had the capacity to time the value/growth cycle. In particular, looking back at the data on value versus growth and correlating with other variables, there are two fundamentals that seem to be correlated with whether value or growth investing emerges the winner.Ìý

The first is earnings growth, with growth investing beating value investing when earnings growth rates are low, perhaps because growth becomes a scarcer and a bigger driver of value.ÌýThe other is the slope of the yield curve, i.e., the difference between short term and long term rates, with flatter and downward sloping yield curves associates with growth outperforming and upward sloping yield curves with value outperforming.

In short, the fact that value stocks, at least based upon the price to book proxy, delivered higher returns than growth stocks, again using that proxy, obscures the reality that there were periods of time even in the twentieth century, where the latter won out.

Payoff to Active Value Investing

Investing in low PE or low PBV stocks would not be considered true value investing, by most of its adherents. In fact, most value investors would argue that the while you may start with these stocks, the real payoff to value investing comes in from the additional analysis that you do, whether it be in bringing in other quantitative screens (following up on Ben Graham) and qualitative ones (good management, moats). If we call this active value investing, the true test of value investing then becomes whether following value investing precepts and practices and picking stocks generates returns that exceed the returns on a value index fund, created by investing in low price to book or low PE stocks. Defined thus, the evidence that value investing works has always been weaker than just looking at the top lines, though the strength of the evidence varies depending upon the strand of value investing examined.

Screening for Value: Since Ben Graham provided the architecture for screening for cheap stocks, it should be no surprise that some of the early research looked at whether Graham's screens worked in delivering returns. Henry Oppenheimer examined the returns on stocks, picked using the Graham screens, between 1970 and 1983, and found that they delivered average annual returns of 29.4% a year, as opposed to 11.5% of the index. There are other studies that do come to the same conclusion, looking at screening over the period, but they all suffer from two fundamental problems. The first is that one of the value screens that invariably gets used is low PE and low PBV, and we already know that these stocks delivered significantly higher returns than the rest of the market for much of the last century, and it is unclear from these studies whether all of the additional screens (Graham has a dozen or more) add much to returns. The second is that the ultimate test of a philosophy is not in whether its strategies work on paper, but in whether the investors who use those strategies make money on actual portfolios. There is many a slip between the cup and the lip, when it comes to converting paper strategies to practical ones, and finding investors who have consistently succeeded at beating the market, using screening, is difficult to do.ÌýContrarian Value: The early evidence on contrarian investing came from looking at loser stocks, i.e., stocks that have gone down the most over a prior period, and chronicling the returns you would earn if you bought these stocks. One of the earliest studies, from the mid 1980s, presented this eye-catching graph, backing up the thesis that loser stocks are investment winners:Source:Ìý,Ìý
Loser stocks, defined as the stocks that have gone down the most in the last year, deliver almost 45% more in returns than winner stocks, defined as stocks that have gone up the most in the last year. ÌýBefore you jump out and start buying loser stocks, research in subsequent years pointed to two flaws. The first was that many of the loser stocks in the study traded at less than a dollar, and once transactions costs were factored in, the payoff to buying these stocks shrunk significantly. The second came in a different study, which made a case for buying winner stocks with this graph:Source:Ìý
Note that winner stocks continue to win, in both time periods examined, in the first twelve months after the portfolios are created, though those excess returns fade in the months thereafter. Put simply, if you invest in loser stocks and lose your nerve or your faith, and sell too soon, your loser stock strategy will not pay off.Activist Value: Of all of the different strands of value investing, the one that seems to offer the most promise is activist investing, since it is a club that only those with substantial resources can join, with the promise of bringing change to companies. The early results looked promising, as activist hedge funds seemed to offer a greater chance of beating the market than other investing approaches:Source:Ìý
In the 1995-2007 time period, activist value investors outstripped both hedge funds and the S&P 500, delivering super-sized returns Those numbers, though, are starting to come under strain, as activist investing has widened it search and perhaps lost its focus in the last decade:ÌýSource:
In the last decade, the bloom has come off the activist investing rose, as returns from it have dropped off to the point that activist investors, at least in the aggregate, are underperforming the market. The only saving grace is that activist investing is a skewed game, where the winners win really big, and many of the losers drop out.Indexed Value: Many value investors will blanch at the idea of letting indexed value investors into this group, but there can be no denying the fact that funds have flowed into tilted index funds, with many of the tilts reflecting historical value factors (low price to book, small cap, low volatility). The sales pitch for these funds is more often that you can not only get a higher return, because of your factor tilts, but also Ìýa bigger bang (return) for your risk (standard deviation) rather than a higher return per se (higher ratios of returns to standard deviation). The jury is still out, and my personal view is that titled index funds are an oxymoron, and that these funds should be categorized as minimalist value funds, where you try to minimize your activity, so as to lower your costs.Ìý

The most telling statistics on the failure of value investing come from looking at the performance of mutual fund managers who claim to be its adherents. While the earliest studies of mutual funds looked at them as a group, and concluded that they collectively under performed the market, later studies have looked at mutual funds, grouped by category (small cap vs large cap, value vs growth) to see if fund managers in any of these groupings performed better than managers in other groupings. None of these studies have found any evidence that value fund managers are more likely to beat their index counterparts than their growth fund counterparts. It is telling that value investors, when asked to defend their capacity to add value to investing, almost never reference that research, partly because there is little that they can point to as supportive evidence, but instead fall back on Warren Buffett, as their justification for value investing. As I noted in my last post, there is no doubt about Buffett's success over the decades, but as the man turned ninety this year, it is worth asking whether the continued use of his name is more a sign of weakness in value investing, rather than of strength.

Wandering in the wilderness? Value Investing inÌýthe last decade

Looking at my analysis of value investing over the last century, you can accuse me of perhaps nitpicking an overall record of success, but the last decade has, in my view, tested value investing in ways that we have never seen before. To see how much of an outlier this period (2010-2019) has been, take a look at the returns to low and high PBV stocks, by decade:

Source:

While it is true that the dot-com boom allowed growth stocks to beat out value stocks in the 1990s, the difference was small and bunched up in the last few years of that decade. In the 2010-2019 time period, in the battle between value and growth, it was no contest with growth winning by a substantial amount and in seven of the ten years.

To make things worse, active value investors, at least those that run mutual funds, found ways to underperform even these badly performing indices. Rather than use risk and return models or academic research to back up this proposition, and open up the debate about portfolio theories, I will draw on a much more simplistic but perhaps more effective comparison. One of S&P's most informative measures is SPIVA, where S&P compares the returns of fund managers in different groupings to indices that reflect that grouping (value index for value funds, growth index for growth funds etc.) and reports on the percentage of managers in each grouping that beat the index. Listed below are the SPIVA measures for 2005-2019 for value managers in all different market cap classes (large, mid-sized, small):

Risk Adjusted SPIVA Scorecard (2019)

Put simply, most value fund managers have had trouble beating the value indices, net of fees. Even gross of fees, the percentages of fund managers beating their indices stays well above 50%.

Even legendary value investors lost their mojo during the decade, and even Warren Buffett's stock picking delivered average returns. He abandoned long standing practices, such as and , for good and bad reasons. The best indicator of how the market has also lowered the value it attaches to his stock picking is in a number that has the Buffett imprimatur, the ratio of price to book at Berkshire in the last few years:

Since Berkshire's assets are primarily in publicly traded companies, and these investments have been marked to market for all of this period, one way to look at a portion of the premium that investors are paying over book value is to consider it to be the stock picker premium. Since some of the premium can also be explained by its presence in the insurance business, I compared the price to book for Berkshire to that of general insurance companies listed and traded in the United States. At the start of 2010, Berkshire traded at a price to book ratio of 1.54, well above the US insurance company industry average of 1.10. Ten years later, at the start of 2020, the price to book ratio for Berkshire had dropped to 1.27, below the average of 1.47 for US insurance companies. The loss of the Buffett premium may seem puzzling to those who track news stories about the man, since he is still not only treated as an investing deity, but viewed as the person behind every Berkshire Hathaway decision, from its investment in Apple in 2017 to its more recent one in the Snowflake IPO. My reading is that markets are less sentimental and more realistic in assessing both the quality of his investments (that he is now closer to the average investor than he has ever been) and the fact that at his age, it is unlikely that he is the lead decision-maker at Berkshire anymore.Ìý

The COVID shock

For much of the decade, value investors argued that their underperformance was a passing phase, driven by the success of growth and momentum and aided and abetted by the Fed, and that it value investing would come back with a vengeance in a crisis. The viral shock delivered by the Corona Virus early this year seemed to offer an opportunity for value investing, with its emphasis on safety and earnings, to shine.Ìý

In the first few weeks, there were some in the value investing camp who argued that following old time value investing precepts and investing in stocks with low PE and Price to book ratios and high dividends would help buffer investors from downside risk. While the logic may have been appealing, the results have not, as can be seen in this table, where I look at stocks classified based upon their PE ratios and Price to Book ratios on February 14, 2020 (at the start of the crisis), and examining the changes in the aggregate market capitalization in the six months following:

The numbers speak for themselves. Low PE and low PBV stocks have lost value during this crisis, just as high PE and PBV stocks have gained in value. Breaking companies down based upon dividend yields, and looking at market capitalization changes yields the following:

The results are perverse, at least from a value investing perspective, since the stocks that have done best in this crisis are non-dividend paying, high PE stocks, and the stocks that have done worst during the crisis have been high dividend paying, low PE stock.Ìý

The Explanations

The attempt to explain what happened to value investing in the last decade (and during COVID) is not just about explaining the past, since the rationale you provide will inform whether you will continue to adhere to old time value investing rules, modify them to reflect new realities or abandon them in search of new ones. In particular, there are four explanations that I have heard from value investors for what were wrong during the last decade, and I will list them in their order of consequence for value investing practices, from most benign to most consequential.

This is a passing phase!Diagnosis: Even in its glory days, during the last century, there were extended periods (like the 1990s) when low PE and low PBV stocks underperformed, relative to high PE and high PBV stocks. Once those periods passed, they regained their rightful place at the top of the investing heap. The last decade was one of those aberrations, and as with previous aberrations, it too shall pass!Prescription: Be patient. With time, value investing will deliver superior returns.The Fed did it!Diagnosis: Starting with the 2008 crisis and stretching into the last decade, central banks around the world have become much more active players in markets. With quantitative easing, the Fed and other central banks have contributed not only to keeping interest rates lower (than they should be, given fundamentals) but also provided protection for risk taking at the expense of conservative investing.ÌýPrescription: Central banks cannot keep interest rates low in perpetuity, and even they do not have the resource to bail out risk takers forever. Eventually, the process will blow up, causing currencies to lose value, government budgets to implode and inflation and interest rates to rise. When that happens, value investors will find themselves less hurt than other investors.The Investment World has become flatter!Diagnosis: When Ben Graham listed his screens for finding good investments in 1949, running those screens required data and tools that most investors did not have access to, or the endurance to run. All of the data came from poring over annual reports, often using very different accounting standards, the ratios had to be computed with slide rules or on paper, and the sorting of companies was done by hand. Even into the 1980s, access to data and powerful analytical tools was restricted to professional money managers and thus remained a competitive advantage. As data has become easier to get, accounting more standardized and analytical tools more accessible, there is very little competitive advantage to computing ratios (PE, PBV, debt ratio etc.) from financial statements and running screens to find cheap stocks.ÌýPrescription: To find a competitive edge, value investors have to become creative in finding new screens that are either qualitative or go beyond the financial statements or in finding new ways of processing publicly accessible data to find undervalued stocks.ÌýThe global economy has changed!Diagnosis: At the risk of sounding cliched, the shift in economic power to more globalized companies, built on technology and immense user platforms, has made many old time value investing nostrums useless. ÌýPrescription: Value investing has to adapt to the new economy, with less of a balance sheet focus and more flexibility in how you assess value. Put simply, investors may have to leave their preferred habitat (mature companies with physical assets bases) in the corporate life cycle to find value.From listening to value investors across the spectrum, there does not seem to be a consensus yet on what ails it, but the evolution in thinking has been clear. As the years of under performance have stretched on, there are fewer value investors who believe that this is a passing phase and that all that is needed is patience. There are many value investors who still blame the Fed (and other central banks) for their underperformance, and while I agree with them that central banks have sometimes over reached and skewed markets, I also think that this belief has become a convenient excuse for not looking at the very real problems at the heart of value investing. Especially after the COVID experience, there are at least some value investors who are willing to consider the possibility that it is time to change the way we practice value investing. In my next post, I will look at some of these changes.
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Blog Posts on Value Investing (2020)Value Investing II: A Lost Decade

One of the classes that I teach is on investment philosophies, where I begin by describing an investment philosophy as a set of beliefs about how markets work (and sometimes don't) which lead to investment strategies designed to take advantage of market mistakes. Unlike some, I don't believe that there is a Ìýsingle "best" philosophy, since the best investment philosophy for you is the one that best fits you as a person. It is for that reason that I try to keep my personal biases and choices out, perhaps imperfectly, of the investment philosophies, and use the class to describe the spectrum of investment philosophies that investors have used, and some have succeeded with, over time. I start with technical analysis and charting, move on to value investing, then on to growth investing, and end with information trading and arbitrage. The most common pushback that I get is from old-time value investors, arguing that there is no debate, since value investing is the only guaranteed way of winning over the long term. Embedded in this statement are a multitude of questions that deserve to be answered:

What is value investing and what do you need to do to be called a value investor?Where does this certitude that value investing is the "winningest" philosophy come from? Is it deserved?How long is the long term, and why is it guaranteed that value investing wins?I will argue over the course of the next few posts that the answers to these questions are not only more nuanced than many true believers posit them to be, but also that changes in economies and markets are undercutting key components of the value investing case. In this post, I will focus on defining value investing and on the roots of its allure.

What is value investing?

Given how widely data services tracking mutual funds and active investing seem to be able . how quickly prognosticators are able to pass judgment on value investing's and and how much academics have been able to in the last few decades, you would think that there is consensus now on what comprises value investing, and how to define it. But you would be wrong! The definition of value investing varies widely even among value investors, and the differences are not often deep and difficult to bridge.

In this section, I will start by providing three variants on value investing that I have seen used in practice, and then go on to explore a way to find commonalities.

Lazy Value Investing: Let's start with the easiest and most simplistic definition, and the one that many data services and academics continue to use, simply because it is quantifiable and convenient, and that is to base whether you are a value or growth investor on whether the stocks you buy trade at low or high multiples of earnings or book value. Put simply, if you consistently invest in stocks that trade at low PE and low price to book ratios, you are a value investor, and if you do not, you are not one.ÌýCerebral Value Investing: If you use the lazy definition of value investing as just buying low PE and low PBV stocks with a group of Omaha-bound value investors, you will get pushback from them. They will point to value investing writing, starting with Graham and buffered by Buffett's annual letters to shareholders, that good value investing starts by looking at cheapness (PE and PBV) but also includes other criteria such as good management, solid moats or competitive advantages and other qualitative factors.ÌýBig Data Value Investing: Closely related to cerebral value investing in philosophy, but differing in its roots is a third and more recent branch of value investing, where investors start with the conventional measures of cheapness (low PE and low PBV) but also look for additional criteria that has separated good investments from bad ones. Those criteria are found by poring over the data and looking at historical returns, a path made more accessible by access to huge databases and powerful statistical tools.In my book on value investing, I take a different twist to value investing, arguing that value investors can be broadly classified into four groups, depending on how they approach finding bargains:Passive Value Investing: In passive value investing, you screen for the best stocks using criteria that you believe will improve your odds. Once you buy these stocks, you are asked to be patient, and in some cases, to just buy and hold, and that your patience will pay off as higher returns and a more solid portfolio. To see this approach play out, at least in the early days of value investing, take a look at these screens for good stocks that Ben Graham listed out in 1939 in his classic book on the intelligent investor. These screens have evolved in the years since, in two ways. The first is with the introduction of more qualitative screens, like "good" management, where notwithstanding attempts to measure goodness, there will be disagreements. The second is to use increased access to data, Ìýboth from the company and about it, to both test existing screens and to add to them.ÌýContrarian Value Investing: In contrarian value investing, you focus your investing energies on companies that have seen steep drops in stock prices, with the belief that markets tend to overreact to news, and that corrections will occur, to deliver higher returns, across the portfolio. Within this approach, access to data has allowed for refinements that, at least on paper, deliver higher and more sustained returns.ÌýActivist Value Investing: In activist value investing, you target companies that are not only cheap but badly run, and then expend resources (and you need a considerable amount of those) to push for change, either in management practices or in personnel. The payoff to activist value investing comes from activist investors being the catalysts for both price change in the near term, as markets react to their appearance, and to changes in how the company is run, in the long term.Minimalist Value Investing: There is a fourth approach to value investing that perhaps belongs more within passive investing, but for the moment, I will set it apart. In the last decade or two, we have seen the rise of titled index funds and ETFs, where you start with an index fund or ETF, and tilt the fund/ETF by overweighting value stocks (high PE/PBV, for instance) and underweighting non-value stocks.At this stage, if you are completely confused about what a value investor is, I don't blame you, but there is a more general approach to framing value investing that encompasses all these approaches, and allows you to differentiate it from its most direct competitor, which is growth investing. That approach draws on a structure that I have used repeatedly in my writing and teaching, which is the use of a financial (as opposed to an accounting) balance sheet to describe companies:
Put simply, the contrast between value and growth investing is not that one cares about value and the other does not, but in what part of the company the "value error" lies. Value investors believe that their tools and data are better suited to finding mistakes in valuing assets in place, and that belief leads them to focus in on more mature companies, that derive the bulk of their value from existing investments. Growth investors, on the other hand, accept that valuing growth is more difficult and more imprecise, but argue that it is precisely because of these difficulties that growth assets are more likely to be mis-valued.

IsÌývalueÌýinvesting the winningest philosophy?

While it is not uncommon for investors of all stripes to Ìýexpress confidence that their approach to investing is the best one, it is my experience that value investors express not just confidence, but an almost unquestioning belief, that their approach to investing will win in the end. To see where this confidence comes from, it is worth tracing out the history of value investing over the last century, where two strands, one grounded in stories and practice and the other in numbers and academic, connected to give it a strength that no other philosophy can match.

The Story Strand

When stock markets were in their infancy, investors faced two problems. The first was that there were almost no information disclosure requirements, and investors had to work with whatever information they had on companies, or on rumors and stories. The second was that investors, more using to pricing bonds than stocks, drew on bond pricing methods to evaluate stocks, giving rise to the practice of paying dividends (as replacements for coupons). That is not to suggest that there were not investors who were ahead of the game, and the first stories about value investing come out of the damage of the Great Depression, where a few investors like found a way to preserve and even grow their wealth. However, it was Ben Graham, a young associate of Baruch, who laid the foundations for modern value investing, by formalizing his approach to buying stocks and investing in 1934 inÌý, a book that reflected his definition of an investment as "one which thorough analysis, promises safety of principal and adequate return". In 1938, John Burr Williams wrote , introducing the notion of present value and discounted cash flow valuation. Graham's subsequent book,Ìý, where he elaborated his more developed philosophy of value investing and developed a list of screens, built around observable values, for finding under valued stocks.

While Graham was a successful investor, putting many of his writings into practice, I would argue that Graham's greater contribution to value investing came as a teacher at Columbia University. While many of his students have acquired legendary status, one of them, Warren Buffett has come to embody value investing. Buffett started an investment partnership, which he dissolved (famously) in 1969, arguing that given a choice between bending his investment philosophy and finding investments and not investing, he would choose the latter. These words, in , more than any others have cemented his status in value investing: "I just don't see anything available that gives any reasonable hope of delivering such a good year and I have no desire to grope around, hoping to "get lucky" with other people's money. ÌýHe did allow his partners a chance to receive shares in a struggling textile maker, Berkshire Hathaway, and the rest, as they say, is history, as Berkshire Hathaway morphed into an insurance company, with an embedded closed end mutual fund, investing in both public and some private businesses, run by Buffett. While Buffett has been generous in his praise for Graham, his approach to value investing has been different, insofar as he has been more willing to bring in qualitative factors (management quality, competitive advantages) and to be more active (taking a role in how the companies he has invested in are run) than Graham was. If you had invested in Berkshire Hathaway in 1965 or soon after, and had continued to hold through today, you would be incredibly wealthy:

Source:ÌýÌý(with a Sept 2020 update)

The numbers speak for themselves and you don't need measures of statistical significance to conclude that these are not just unusually good, but cannot be explained away as luck or chance. Not only did Berkshire Hathaway deliver a compounded annual return that was double that of the S&P 500, it did so with consistency, outperforming the index in 37 out of 55 years. It is true that the returns have looked a lot more ordinary in the last two decades, and we will come back to examine those years in the next post.

Along the way, Buffett has proved to be an extraordinary spokesperson for value investing, not only by delivering mind-blowing returns, but also because of his capacity to explain value investing in homespun, catchy . In 1978, he was joined by Charlie Munger, whose aphorisms about investing have been just as effective at getting investor attention, and were captured well . There have been others who have worn the value investing mantle successfully, and I don't mean to discount them, but it is difficult to overstate how much of value investing as we know it has been built around Graham and Buffett. The Buffett legend has been burnished not just with flourishes like the 1969 partnership letter but by the stories of the companies that he picked along the way. Even novice value investors will have heard the in 1963, after its stock price collapsed following a disastrous loan to scandalous salad oil company, and quickly doubled his investment.Ìý

The Numbers Strand

If all that value investing had for it were the stories of great value investors and their exploits, it would not have the punch that it does today, without the help of a numbers strand, ironically delivered by the very academics that value investors hold in low esteem. To understand this contribution, we need to go back to the 1960s, when finance as we know it, developed as a discipline, built around strong beliefs that markets are, for the most part, efficient. In fact, the capital asset pricing model, despised by value investors, also was developed in 1964, and for much of the next 15 years, financial researchers worked hard trying to test the model. To their disappointment, the model not only revealed clear weaknesses, but it consistently misestimated returns for classes of stock. In 1981, Rolf Banz published a, showing that smaller companies (in terms of market capitalization) delivered much higher returns, after adjusting for risk with the CAPM, than larger companies. Over the rest of the 1980s, researchers continued to find other company characteristics that seemed to be systematically related to "excess" returns, Ìýeven though theory suggested that they should not. (It is interesting that in the early days, these systematic irregularities were called anomalies and non inefficiencies, suggesting that it was not markets that were mispricing these stocks but researchers who were erroneously measuring risk.)

In 1992, Fama and French pulled all of these company characteristics together in a study, where they reversed the research order. Rather than ask whether betas, company size or profitability were affecting returns, they started with the returns on stocks and backed into the characteristics that were strongest in explaining differences across companies. Their conclusion was that two variables, market capitalization (size) and book to market ratios explained the bulk of the variation in stock returns from 1963 to 1990, and that the other variables were either subsumed by these or played only a marginal role in explaining differences. For value investors, long attuned to book value as a key metric, this research was vindication of decades of work. In fact, the relationship between returns over time and price to book ratios still takes pride of place in any sales pitch for value investing, and on the Fama-French factors, allowing me to provide you with an updated version of the link between returns and price to book ratios:

Source: Ken French

That study has not only been replicated multiple times with US stocks, and there is evidence that if you back in time, low price to book stocks earn premium returns in much of the rest of the world. Dimson, Marsh and Staunton, in their , note that the value premium (the premium earned by low price to book stocks, relative to the market) has been positive in 16 of the 24 countries that they have returns for more than a century and amounted to an annual excess return of 1.8%, on a global basis.

While value investors are quick to point to these academic studies as backing for value investing, they are slower to acknowledge the fact that among researchers, there is a clear bifurcation in what they see as the reasons for these value premium:

It is a proxy for missed risk: In their 1992 paper, Fama and French argued that companies that trade at low price to book ratios are more likely to be distressed and that our risk and return models were not doing an adequate job of capturing that risk. They and others who have advanced the same type of argument would argue that rather than be a stamp of approval for value Ìýinvesting, these studies indicate risks that may not show up in near term returns or in traditional risk and return models, but eventually will manifest themselves and cleanse the excess returns. Put simply, in their world, value investors will look like they are beating the market, until these unseen risks show up and mark down their portfolios.It is a sign of market inefficiency: During the 1980s, as behavioral finance became more popular, academics also became more willing to accept and even welcome the notion that markets make systematic mistakes and that investors less susceptible to these behavioral quirks could take advantage of these mistakes. For these researchers, the findings that low price to book stocks were being priced to earn higher returns gave rise to theories of how investor irrationalities could explain these returns.ÌýIt is the latter group that reinforces the opinion that value investors have that they are better than the rest of the market and that the excess returns that they earned were a reward for their patience and careful research. i.e., being the grown-ups in a world filled with juvenile and impulsive traders.

The End Result

When valuing companies, I talk about how value is a bridge between stories and numbers, and how the very best and most valuable companies represent an uncommon mix of strong stories backed up by strong numbers. In the realm of investment philosophies, value investing has had that unique mix work in its favor, with stories of value investors and their winning stocks backed up by numbers on how well value investing does, relative to other philosophies. It is therefore no surprise that many investors, when asked to describe their investment philosophies, describe themselves as value investors, not just because of its winning track record, but also because of its intellectual and academic backing.Ìý

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