A Do-it-yourself (DIY) Valuation of Tesla: Of Investment Regrets and Disagreements!

I was hoping to move on from Tesla to my data update posts, but my last post on Tesla drew some attention, in good and bad ways, partly because of its timing. Right after I sold my shares for $640, last week (January 30), the stock took off, climbing to more than $900/share in the matter of days. As always, there were people on both sides of the great Tesla divide commenting on my valuation, with bears accusing me of wearing rose-colored glasses and making unrealistically optimistic assumptions, and bulls pointing to inputs that they felt under estimated the company’s potential. I wish that I had been clearer in my writing that the numbers that I was using did not represent “the” valuation of Tesla but that this was “my” valuation of the company, and that I not only expect disagreement, but I think it is part and parcel of a healthy market. Rather than leave that view as an abstraction, I thought I would revisit the valuation and present it in a different format, one in which you can choose your story for Tesla and estimate the value for yourself.

The Key Levers of Value

In my earlier post, I valued Tesla and presented my valuation in a picture, where I connected the story that I was telling about the company to my estimated value per share of roughly $427 per share:

Download spreadsheet

If you find the numbers off putting or overwhelming, the value is determined by four key levers:

1. The Growth Lever: The revenue growth rate controls how much and how quickly the firm will be able to grow its revenues from autos, software, solar panels and anything else that you believe the company will be selling. Rather than focus on the growth rate, I would suggest looking at the estimated revenues in 2030 (ten years out). In my Tesla story (valuation), I have estimated revenues of $125 billion in 2030, a five-fold increase over the 2019 revenues.
2. The Profitability Lever: The target (pre-tax) operating margin determines how profitable you think the company will be, once its growth days start to scale down. Since these are operating margins, not gross or net margins, they are after all operating expenses (cost of goods sold, SG&A etc.) but before any financial expenses (interest expenses). In keeping with my view that R&D is really a capital expense, I capitalize R&D, which improves Tesla’s profitability, and target an operating margin of 12% by 2025.
3. The Investment Efficiency Lever: To grow, companies have to invest in production capacity and the sales to invested capital drives how efficiently investment is done, with higher sales to capital ratios reflecting more efficiency. With Tesla, I assume that every dollar of investment (in new factories, technology and new R&D) in the first 5 years generates $3 in revenues, as it utilizes excess capacity in the early years, and that this efficiency drops back by a third, as capacity constraints hit.
4. The Risk lever: There are two inputs in this valuation that incorporate risk. The first is the cost of capital that I start the valuation with, a reflection of risk as seen through the eyes of a diversified investor in the company. The second is the likelihood of failure (or distress), where the company has to liquidate assets and lose the additional value that it could have generated as a going concern. With Tesla, I set this cost of capital at 7% and assume that given its marginal profitability and significant debt load, the chance of failure is 10%.

The value per share of $427 comes out of these assumptions and is driving my investment decisions. Since this is my story and valuation, I expect and welcome disagreement on any and all of these inputs. After all, I don’t have a crystal ball to forecast the future or a monopoly on the right estimates

A DIY Valuation of Tesla

In the rest of this post, rather than force my story on your, I would like you to make your choices on the growth, profitability, investment and risk dimensions future for Tesla, and just in case you need some help, I will offer data perspective, on each of those choices. 

The Growth Lever

To make your judgment on how much revenue Tesla will have in a decade, it may help to take a look at the overall auto business. In 2019, the collective revenues of all publicly traded auto companies in the world was about $2.46 trillion and the the compounded average growth rate in those revenues over the last decade has been about 3.5%:

Source data: S&P Capital IQ

Put simply, this is a big market, but the overall market is in slow growth. To provide some perspective on what the bigger auto companies generate in revenues, I have listed the 20 largest auto companies, in terms of revenues in the table below:

Source data: S&P Capital IQ

Tesla does make the list, coming in at the very bottom of the list, and its compounded annual growth rate between 2010 and 2019 stands out, partly the base revenues for the company, in 2010, were tiny. Since one of the Tesla stories told by optimistic is that it is a tech company, It may help in your estimation to see what large tech companies look like, and to make this assessment, I decided to focus on the giants on top of the tech heap in the FAANG stocks, with Microsoft thrown in for full measure:

Note that while the tech companies are substantially more profitable than the auto companies, in terms of margins and dollar operating income, their revenues tend to be more muted, reflecting the pricing of their products and services. Apple, the largest market cap company in the world, had revenues of $ 260 billion in 2019, and Microsoft, the largest software company in the world, by far, had revenues of $129 billion, and both companies lagged Toyota and Volkswagen, on total revenues.

With this background, I think that you have the ammunition you need to make your own revenue judgments for Tesla in a decade, differentiating your story from mine, where revenues in 2030 for Tesla are roughly $125 billion. So, with no further ado, here are your choices (pick one):

Download spreadsheet

Since Tesla’s revenue stream includes not just autos but also software, batteries and solar panels, your story may augment revenues to reflect these, but remember that these streams cannot deliver the same revenue heft as selling cars, though they may be more profitable. In addition, be cautious about growth rates, since it is almost impossible to grasp the compounding effect, without looking at the dollar values. For instance, there are some who take Elon Musk at his word that he plans to grow Tesla at 50%-100% a year; applying a 50% growth rate to Tesla's revenues would give it $470 billion in revenues, which would make it second only to Walmart on a global basis. With 100% growth, Tesla's revenues would be around $4 trillion in 2030, and if you can find a way to get there, good luck to you!

The Profitability Lever

To make your judgment on operating profitability, take a look at both the largest auto company tables and the one for FAANG stocks in the last section. There is not a single large auto company with double digit margins, and across all auto companies listed publicly, the profit picture is even more bleak:

Source: S&P Capital IQ

The picture is brighter for the FAANG stocks, where the aggregate operating margin across all five stocks is 19.87%, well above auto industry averages. That margin, though, is delivered on smaller revenues and with business models where production costs are a smaller fraction of selling prices. The marginal cost of producing an extra unit for Microsoft is close to zero on both its Office and Cloud business, and even for Apple, which derives a large chunk of its revenues from the iPhone, the cost of making the iPhone is about about 40% of the price it charges. 

This information should provide a basis for you to make a choice on a target operating margin for Tesla in the future, keeping in mind that its current operating margin is miniscule and barely positive. 

Download spreadsheet

As you make this choice, it is important that you tie it back to your earlier growth story. While Tesla sales of software/tech will have higher margins, it the auto sales that are responsible for the bulking up of revenues over time. Thus, if your argument is that Tesla will become predominantly a soft services company, you can give it higher margins, but your revenue expectations may have to be reduced. If you buy the argument of some that the costs of manufacturing will continue to drop (by about 15%), as production increases (doubles), you may think you have the basis for exploding margins, but the flaws in this argument should be obvious. First, there has to be a floor on cost savings or Volkswagen, which sells close to 10 million a year right now, should be making cars for close to nothing and generating margins of closer to 100% on the marginal car it sells (and it does not). Second, even if there are revolutionary changes in technology that allow the costs of production to decrease, unless you can show that Tesla and Tesla alone can reap these benefits, you have a business that will see the prices drop, as costs drop. Put simply, if Wright's law applies to all competitors, you and I will be able to buy electric cars at $3000/car and none of the manufacturers will be making sky high margins.

The Investment Efficiency Lever

The investment efficiency lever is one of the trickiest to navigate. Again, the place to start is with automobile companies, and the table below presents the distribution of sales to invested capital across all auto firms, at the start of 2020.

Looking across global auto companies, the median company generates $1.37 in sales for every dollar of capital invested, and at the 75th percentile, the more capital-efficient auto companies generate $2.42 in revenues for every dollar of capital invested. In fact, my estimate of $3 in revenues for every dollar of capital invested reflects an optimistic view of Tesla’s capacity to bring technological innovation to its production processes, and reduce the capital needed to fund those processes. Since Tesla, in 2019, generates $1.32 in revenue for every dollar of capital invested, my estimate is more aspirational than based on observable efficiencies, right now. Tesla bulls will counter with the tech company story, and to help the estimation process, I estimated the sales to invested capital at tech firms generally, just software firms and finally at just the FAANG stocks. None of these groups had sales to invested capital that were higher than my estimate. With that data to provide perspective, it is time to make your own judgment on investment efficiency:

Download spreadsheet

This choice will drive not only how much Tesla will have to reinvest to grow, but the extent to which it will be dependent on external capital for that growth.

The Risk Lever

The first component in the risk lever is the cost of capital, and to provide a sense of what costs of capital look like around the world at the start of 2020, let me start with a cost of capital distribution for all publicly traded companies:

Download spreadsheet

Note that the median cost of capital across all firms globally is 7.58%, and that 50% of all publicly traded firms have costs of capital that fall between 6.27% and 8.71%. It is true that costs of capital vary across different industries, and while you can get the entire list on my website, the median cost of capital for auto firms is 6.94% and for tech firms, it is 8.86%. While I used 7% as my cost of capital, you may disagree and here are your choices:

Download spreadsheet

The other component of risk is failure, where the company faces the risk of having its life truncated, either because it runs out of cash or because of debt payments coming due. While the rise in stock price has reduced its vulnerability for the moment, those who see more losses in the future and continued borrowing to fund investment may attach a higher probability of default than the 10% that I use, whereas those who believe Elon’s claims that Tesla has entered an era of positive earnings and cash flows, may decide that Tesla has no risk of failure any more:

The Valuation

I have created a front end for my Tesla valuation spreadsheet that allows the choices you made to drive the valuation. Running through the different combinations for the four variables, I have too many to list individually, but consider a subset in this table:

Download spreadsheet

Broadly speaking, there are four broad stories that I have valued here:

1. The Big Auto Story: If your story is that Tesla will emerge from its growth period as one of the largest auto companies in the world (revenues of $100- $300 billion in year 10), with top-tier auto company margins (7.42%), investment efficiency (2.42) and cost of capital (6.94%), the value per share ranges from $106/share (with BMW like revenues) to $227/share (with Daimler-like revenues) to $333/share (with VW/Toyota like revenues).
2. The Techy Auto Company Story: An alternate story is that Tesla is an auto/software/services company with tech company characteristics, giving it higher margins (10.25%) and a higher cost of capital (8.86%). With this story, the value per share ranges from $111/share (with BMW like revenues) to $212/share (with Daimler-like revenues) to $298/share (with VW/Toyota like revenues). Put simply, the higher risk nullifies the benefits of higher profitability.
3. The FAANGy Auto Company: In this variant of the tech story, Tesla not only develops a tech twist, but becomes as successful as the most successful tech companies (I use the FAANG stocks + Microsoft).  In this story, the margins approach 18.97% and with a tech cost of capital, the value per share ranges from $459/share (with BMW like revenues) to $855/share (with Daimler-like revenues) to $2,106/share (with VW/Toyota like revenues).
4. The Make-your-best Company: In this variant, I give Tesla the best possible outcomes on each variable, revenues like VW/Toyota, margins like pure software companies (21.24%), a sales to capital ratio that is higher than any of the sector averages (4.00) and a cost of capital of an auto company (6.94%), and arrive at a value per share of $2106.

For some of you, the fact that there is a value here that justifies whatever your Tesla status is right now (long, short or just watching) should not be the end of your analysis. Each of these stories may be possible, but the tests you have to run, and I will prejudge your conclusions, is whether they are plausible. With each story, there are key questions that need answering:

• With the big auto stories, the key question will be whether Tesla can climb to the very top of the heap in terms of revenues, generally reserved for mass market companies, while earning operating margins that are usually reserved for smaller luxury auto companies?
• With the techy auto stories, the key question becomes whether a company that derives the bulk of its revenues from selling cars be profitable and reinvest like a tech company? 
• With the FAANGy stories, the investment question becomes whether you should up front for a company on the expectation that it will be an exceptional company. It very well might make it to the top of the heap, but if it does not, you are set up for disappointment.
• With the MYB story, you are approaching the most dangerous place in valuation, where you pick and choose each assumption, without considering the ones you have already made. Put simply, is it even possible to build a company that generates revenues like Toyota, earns margins like Microsoft and invests more efficiently than any manufacturing company in history has ever done, while still preserving the low cost of capital of an auto company?

Conclusion

In the week since I sold Tesla at $640, the stock has gone on a wild ride, rising above $900 in two trading days. Not surprisingly, quite a few of you have asked me whether I have any regrets about selling too early. You may not believe me, but I don't. I made my decision to buy, based on my story and valuation for Tesla, and my decision to sell, for the same reason, because I am an investor who believes in value, and acting on it. If I abandon that philosophy to play the momentum game, a game that I am not good at and don’t really play well, I may make a bit more money, but at what cost?   On a different note, I have to confess that one reason that I write about Tesla reluctantly is the vitriol that seems to be part of any discussion of the stock. In a world where we face unbridgeable divides on politics, religion and culture, do we need to add investing to the mix?  If you stayed with your Tesla investment, I wish you the best, and I hope that you are holding on for the right reasons, either because you believe that its value is much higher or because you are playing the pricing game. If you sold short and lost money, I get no joy out of your losses and no inclination to do a celebratory dance. For the moment, you may have lost, but having watched this stock for as long as I have, that can change in a minute. As far as I am concerned, Tesla is a fascinating company, but it is just an investment, not a matter of life or death, and definitely not worth losing sleep, and friends, over.

YouTube Video


Spreadsheet

1. A Do-it-Yourself Valuation of Tesla

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An Ode to Luck: Revisiting my Tesla Valuation

When investing, I am often my own biggest adversary, handicapped by the preconceptions and priors that I bring into analysis and decision making, and no company epitomizes the dangers of bias more than Tesla. It is a company where there is no middle ground, with the optimists believing that there is no limit to its potential and the pessimists convinced that it is a time bomb, destined to implode. I have tried, without much luck, to navigate the middle ground in my valuations of the company and have been found wanting by both sides. For much of Tesla’s life, I have pointed to its promise but argued that it was too richly priced to be a good investment, and during that period, Tesla bulls accused me of working for the short sellers. They did not believe me when I argued that you could like a company for its vision and potential, and not like it as an investment. When I bought Tesla in June 2019, arguing that the price had dropped enough (to $180) to make it a good investment, they became my allies, but that decision led to a backlash from Tesla bears, who labeled me a traitor for abandoning my position, again not accepting my argument that at the right price, I would buy any company. I would love to chalk it to my expert timing, but luck was on my side, the momentum shifted right after I bought, and the stock has not stopped rising since. When Tesla’s earnings reported its earnings yesterday (January 29th), the stock was trading at $581, before jumping to $650 in after-market trading. It is time to revisit my valuation and reassess my holding!

Tesla in June 2019: A Story Stock loses its story!

It was in June 2019 just over seven months ago, when the sky was full of dark clouds for Tesla, as a collection of wounds, some internal and others external had pushed the stock price down more than 40% in a few months, that I took a look at the company and valued it at just over $190 per share:

Download spreadsheet

In arriving at this value, I told a story of a company that would grow to deliver $100 billion in revenues in a decade, while also earning a 10% pre-tax operating margin. One concern that I had at the time was that the debt load for the company, in conjunction with operating losses and a loss of access to new capital, would expose the company to a risk of default; I estimated a 20% probability that Tesla would not survive.  At the time that I wrote the post, I posted a limit order to buy the stock at a $180 stock price, and when it executed a short while later,  some of you pointed out that I was not giving myself much margin of safety. I argued that the distribution of Tesla value outcomes gave me a much larger chance of upside than downside. At the time of the investment, I also described the company as a corporate teenager, with lots of potential but a frustrating practice of risking it all for distractions.

A Story Update, through January 2020

When I bought Tesla, I had no indication that it had hit bottom. In fact, given how strongly momentum and mood had shifted against the stock, I expected to lose money first, before any recovery would kick in, and I certainly did not expect a swift return on my investment. The market, of course, had its own plans for Tesla and the stock’s performance since the time I bought it is in the graph below:

One of my concerns, as an investor, is that I can sometimes mistake dumb luck for skill, but in this case, I  am operating under illusions. The timing on this investment was pure luck, but I am not complaining. What happened to cause the turnaround. There were three factors that fed into the upward spiral in the stock price:

1. Return to growth: In the middle of 2019, Tesla’s growth seemed to have run out of steam and there were some who believed that its best days were behind it. In the two quarters since, Tesla has shown signs of growth, albeit not at the breakneck pace that you saw it grow, earlier in its life.
2. Operating improvements: One of Tesla’s weaknesses has been an inability to deliver on time and maintain anything resembling an efficient supply chain. In the second half of 2019, Tesla seemed to be paying attention to its weakest link, focusing on producing and delivering cars, without drama, and even running ahead of schedule on new capacity that it was adding in Shanghai.
3. Radio Silence: I know that this will sound petty to Musk fans, but Elon Musk has always been a mixed blessing for the company. While his vision has been central to building the company, he has also made it a practice of creating diversions that take people’s attention away from the story line. He has also had a history of pre-empting operating decisions with rash missives (pricing the Tesla 3 at $35,000 and producing 5,000 cars/week) that led to operating and credibility problems for the company. Musk has been quieter and more focused of late, and the last six months have been blessedly free of distractions, allowing investors to focus on the Tesla story.

In earlier posts, I have drawn a distinction between the value of a stock and its price, noting that traders play the pricing game (trying to gauge momentum and shifts) and investors play the value game, where they invest based upon value, hoping for price convergence. While price and value are driven by different factors, in the case of Tesla, there is a feedback effect from price to value because of (a) its high debt obligations and (b) its need for more capital to fund its growth. As stock prices rise, the debt obligation becomes less onerous for two reasons. First, some of it is convertible debt, at high enough stock prices, it gets converted to equity. Second, Tesla’s capacity to raise new equity at high stock prices gives it a fall back that it can use, if it chooses to pay down debt. By the same token, the number of shares that Tesla will need to issue to cover its funding needs, as it grows, will decrease as the stock price rises, reducing their dilution effect on value.

Valuing Tesla in January 2020

There have been three earnings reports from Tesla since my June 2019 report, and the table below shows how the base year numbers have shifted, as a consequence:

Tesla Quarterly Reports & Earnings Call on January 29, 2020

The base revenues have increased by about 9%, and operating margins continued to get less negative (turning positive in the last quarter of the year), as long-promised economies of scale finally manifested themselves. In the table below, I highlight the changes that I have made in key inputs relating to growth, profitability and reinvestment. 

Download spreadsheet

Specifically, here is what I changed:

• Higher end revenues: My revenue growth rate, while only marginally higher than the growth rate I used in June 2019, delivers revenues of just above $125 billion in 2030, about 25% higher than the end revenues that I forecast a year ago. Since this will require that Tesla sell more than 2 million cars in 2030, I am not making this assumption lightly.
• Higher margins: My target pre-tax operating margin has also been pushed up from 10% to 12%, reflecting the improvements in margins that the company has already delivered and an expectation that the company will continue to work on a more efficient production model than conventional automakers. 
• More efficient reinvestment: My reinvestment assumptions for the long term resemble those that I made in June, with every dollar in invested capital delivering $2 in revenues, as the company adds capacity. In the near term, though, I assume less reinvestment, assuming $3 in revenues for every new dollar of capital invested, since Tesla contends in its January 2020 earnings call to have capacity online to produce 640,000 cars, enough to cover growth for the next year or two.

If you are surprised about the lower cost of capital in January 2020, that drop has little to do with Tesla and more to do with changes in the market. First, the US treasury bond rate has dropped to 1.75% from 2.26% in June 2019, creating a lower base for both the costs of equity and debt for the company. Second, while Tesla’s bond rating has not improved dramatically, default spreads on bonds have dropped over the course of the year. Finally, the price feedback effect has silenced talk about imminent default, but I understand that a momentum shift and a lower stock price can rekindle it, and I have halved the probability of default. With this more upbeat story, the value that I get per share for Tesla is $427, and the details are shown below:

Download spreadsheet

If your criticism of this valuation is that I am letting the good times in the stock feed into my intrinsic value estimate, I am guilty as charged, but I have never been able to completely ignore what markets are doing, when doing intrinsic value. To see how each assumption that I have altered feeds into the value, I broke down the value change into constituent pieces.

The biggest increase in value comes from increasing the margin, accounting for a little bit more than half of the value change, followed by higher revenue growth and then by lower costs of capital. Note that the firm’s debt load magnifies the effects of changes in the value of operating assets on equity value, and the options that had dropped in value with the stock price in June 2019, are reasserting their role as a drain on value. If there is a lesson that I would take away from this table, it is that the key debate that we should be having on Tesla is not about whether it can grow. Given the size of the auto market, and the shift towards electric cars, the growth is both possible and plausible. It is about the margins that Tesla can command, once it becomes a mature company, which in turn requires an assessment of what the auto market will look like a decade from now. If you believe that an electric car is an automobile first, and electric next, it will be difficult to reach and sustain double-digit operating margins, if you are not a niche auto company. If, in contrast, your view is that the electric car market will be viewed as an electronic or tech product, you may be able to justify higher margins.

What now?

In the interests of transparency, I should start with a confession. I went into this valuation wanting to hold on to Tesla for a little while longer, partly because it has done so well for me (and it tough to let winners go, when they are still winning) but mostly because at a 7-month holding period, selling it now will expose me to a fairly hefty tax liability; short-term capital gains (less than a one-year holding period) are taxed at my ordinary tax rate and long term capital gains (greater than a year holding period) are taxed at a 20% lower rate. This desire to derive a higher value for Tesla (to justify continuing to hold it) may be driving the optimism in my assumptions in the last section, but even with those optimistic assumptions, my value per share of $427 was well below the closing price of $581 at the end of trading and even further below the $650 that Tesla was trading at after the earnings release. Could tweaking the assumptions give me a value higher than the price? Of course! I could raise my end year revenues to $200 billion ( plausible in a market this size) and give Tesla an 18% operating margin (perhaps by calling it a tech company) and arrive at a value of $ 1,168 per share, but that to me is pushing the limits of possibility, and one reason why I hold back on simple what-if analyses. A Monte Carlo simulation allows for a more complete assessment of uncertainty and in the table below, I vary four key assumptions (revenue growth, target margin, reinvestment efficiency and cost of capital) to arrive at a value distribution for Tesla:

Simulation Results

At the price of $650/share, post-earnings report, Tesla is close to the 90th percentile of my value distribution. While it possible that Tesla could be worth more than $650, it is neither plausible nor probable, at least based on my assumptions.

A Post Script

Holding on to the hope that I could defer my sale of Tesla until June (to qualify for long term capital gains), I looked at buying puts to protect my capital gains, but that pathway is an expensive one at Tesla, given how much volatility is priced into the options. Reluctantly, I  sold my Tesla holdings at $640 this morning, and as with my buy order in June, I don’t expect immediate or even near-term gratification. The momentum is strong, and the mood is delirious, implying that Tesla’s stock price could continue to go up. That said, I am not tempted to stay longer, though, because I came to play the investing game, not the trading game, and gauging momentum is not a skill set that I possess. I will miss the excitement of having Tesla in my portfolio, but I have a feeling that this is more a separation than a permanent parting, and that at the right price, Tesla will return to my portfolio in the future. 

YouTube Video

Spreadsheets

1. My Valuation of Tesla in June 2019
2. My Valuation of Tesla in January 2020
3. Tesla Simulation (Crystal Ball)

Posts on Tesla

1. Twists and Turns in the Tesla Story (June 2018)
2. Tesla's Travails: Curfew for a Corporate Teenager (June 2019)

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Data Update 2 for 2020: Retrospective on a Disruptive Decade

My data updates usually look at the data for the most recent year and what I learn from them, but 2020 also marks the end of a decade. In this post, I look back at markets over the period, a testing period for many active investors, and particularly so for value investors, who found that even as financial assets posted solid returns, what they thought were tried and true approaches to "beating the market" seemed to lose their power. In addition, trust in mean reversion, i.e., that things would go back to historic norms was shaken as interest rates remained low for much of the period and PE ratios rose above historical averages and continued to rise, rather than fall back. 

1. It was a great year, and a very good decade, for equities, and a very good year for bonds!

While investing should always be forward-looking, there is a benefit to pausing and looking backwards. If you had US stocks in your portfolio, 2019 was a very good year. The S&P 500 started the year at 2506.85 and ended the year at 3230.78, an increase of 28.88%, and with dividends added, the return for the year was 31.22%. To get a sense of how this year measures up against other good years, I compared it to the annual returns from 1927 to 2019 in this graph:

Download spreadsheet with annual market data

Over the 92 years that are in this historical assessment, 2019 ranked as the sixteenth best year and second only to 2013 (annual return of 32.15%) in this century. While stocks have garnered the bulk of the attention for having a good year, bonds were not slackers in the returns game. In 2019, the ten-year US treasury bond returned 9.64% and ten-year Baa corporate bonds weighing in with a 15.33% return. That may surprise some, given how low interest rates have been, but the bulk of these returns came from price appreciation, as the US treasury bond rate declined from 2.69% to 1.92%, and the corporate bonds also benefited from a decline in default spreads (the price of risk in the bond market) during the year. The year also capped off a decade of gains for stocks, with the S&P almost tripling from 1115.10 on January 1, 2010 to 3230.78 on January 1, 2020, and with dividends included and reinvested, the cumulated return for the decade is 252.96%. To put these returns in perspective, I have compared this cumulated return to the eight full decades that I have data for in the table below, in conjunction with the cumulated returns for treasury and corporate bonds over each decade:

Download spreadsheet with annual market data

While 2010-19 represented a bounce back for stocks from a dismal 2000-09 time period, with the 2008 crisis ravaging returns, it falls behind three other decades of even higher returns (1950-59, 1980-89 and 1990-1999). It was a middling decade for both treasury and corporate bonds, with cumulated returns running ahead of the three decades spanning 1940 to 1969 but falling behind the other decades, in terms of returns delivered. Treasury bills delivered their worst decade of returns, since the 1940s, with the cumulated return amounting to 5.25%. I don’t want to overanalyze historical data, but there are interesting nuggets of information in the data:

a. Historical Risk Premium: The US historical data has been used by many analysts in corporate finance and valuation as the basis for computing historical risk premiums and in the table below, I compute the risk premiums that investors would have earned in this market, investing in stocks as opposed to treasury bills and bonds, over different time periods, and with different averaging approaches:

Download spreadsheet with annual market data

If you go with the geometric average premium from 1927-2019 as your predictor for the equity risk premium in 2020, US stocks should earn about 4.83% more than US treasury bonds for the year:

Expected return on stocks in 2020 = T.Bond Rate + Historical ERP 

= 1.92% + 4.83% = 6.75%

Since a portion of this return will come from dividends, the expected price appreciation in stocks is the difference:

Expected price appreciation on stocks = Expected Return - Dividend yield 

= 6.75%- 1.82% = 4.93%

I am not a fan of historical premiums, not only because they represent almost an almost slavish faith in mean reversion but also because they are noisy; the standard errors in the historical premiums are highlighted in red and you can see that even with 92 years of data, the standard error in the risk premium is 2.20% and that with 10 or 20 years of data, the risk premium estimate is drowned out by estimation error.

b. Asset Allocation: The fact that stocks have beaten treasury and corporate bonds by wide margins over the entire history is often the sales pitch used to push investors to allocate more of their savings to stocks, with the argument being that stocks always win in the long term. The data should yield cautionary notes:

• First, in three decades out of the nine in the table, stocks under-performed treasury bonds and treasury bills, and if your response is that ten years is not a long enough time period, you may want to check the actuarial tables. 
• Second, there is a selection bias in our use of the US markets for computing the historical premium. Looking across the globe, the US was one of the most successful equity markets of the last century and using it may be skewing our results upwards. Put bluntly, if you had invested in the Nikkei at the height of its climb in the 1980s, you would still be struggling to get back the money you lost, when the Japanese markets collapsed.

c. Market Timing: It is human nature to try to time markets, and some investors make it the central focus of their investment philosophies. I will not try to litigate the good sense of doing so in this post, but the historical return data gives us a sense of both the upside and the downside of doing so. In terms of pluses, an investor who was able to avoid the doomed decades (when stocks earned less than T.Bills and T.Bonds) would be comfortably ahead of an investor who did not, if he or she stayed fully invested in the remaining decades. In terms of minuses, if the market timing investor failed to stay invested in stocks in the good decades, the opportunity costs would quickly overwhelm the benefits. Between 2010 and 2019, there were many investors who believed that a correction was around the corner, driven by their perception that interest rates were being kept artificially low by central banks and that they would revert to historic norms quickly. When that reversion did not occur, these investors paid a hefty price in returns foregone. All of the historical returns that I have reported in this section are nominal, and to the extent that you are interested in real returns, you may want to download the historical data from my website and check out the results. (Hint: Not much changes)

2. A Low Interest Rate Decade

If there was a defining characteristic for the decade, it was that interest rates, both in the US and globally, dropped to levels not seen in decades. You can see this in the path of the US 10-year treasury bond rate in the graph below:

Download historical treasury rates, by year

Since the drop in rates occurred after the 2008 crisis, and in the aftermath of concerted actions by central banks to bolster weak economies, it has become conventional wisdom that it is central banks that have kept rates artificially low, and that the ending of quantitative easing would cause rates to revert back to historical averages. As many of you who have been reading my posts know, I don't believe that central banks have the power to keep long term market-set rates low, if the fundamentals don't support low rates. In fact, one of my favorite graphs is one where I compare the 10-year treasury bond rate each year to the sum of the inflation rate and real GDP growth rate that year (intrinsic riskfree rate):

Download historical treasury rates, by year

As you can see, the main reason why rates have dropped in the US and Europe has been fundamental. As inflation has declined (and become deflation in some parts of the world) and real GDP growth has been anemic, intrinsic and actual risk free rates have dropped. To the extent that the difference between the two is a measure of central banking actions, it is true that the Fed’s actions kept actual rates lower than intrinsic rates more in the last decade than in prior years, but it is also true that even in the absence of central banking intervention, rates would not have reverted back to historical norms. 

3. It was a tech decade, and FAANG stocks stole the show!

While it was a good decade for stocks,  the gains varied across sectors. Using the S&P 500 again as the indicator, you can see the shift in value over the decade by looking at how the different sectors evolved over the decade, as a percent of the S&P 500:

The most striking shift is in the energy sector, which dropped from 11.51% of the index to 4.60%, in market capitalization terms. Some of this drop is clearly due to the decline in oil prices during the decade, but some of it can be attributed to a general loss of faith in the future of fossil fuel and conventional energy companies. The biggest sector through the entire decade was technology but its increase in percentage terms seems modest at first sight, rising from 19.76% in 2009 to 21.97% in 2019, but that is because two of the biggest names in the sector, Google and Facebook, were moved to the communication services sector; if they had been left in technology, its share of the index would have risen to more than 30%. In fact, five companies (Facebook, Amazon, Apple, Netflix and Google), representing the FAANG stocks, had a very good decade, with their collective market capitalization increasing by $3.4 trillion over the ten years:

Put in perspective, the FAANG stocks accounted for 22% of the increase in market capitalization of the S&P 500, and any portfolio that did not include any of these stocks for the entire decade would have had a tough time keeping up with the market, let alone beating it. (This is an approximation, since not all five FAANG stocks were part of the S&P 500 for the entire decade, with Facebook entering after its IPO in 2012 and Netflix being added to the index in 2014).

4. Mean Reversion or Structural Shift

One of the perils of being in a market like the US, where rich historical data is available and easily accessible is that analysts and academics have pored over the data and not surprisingly found patterns that have very quickly become part of investment lore. Thus, we have been told that value beats growth, at least over long periods, and that small cap stocks earn a premium, and have converted these findings into investing strategies and valuation practices. While it is dangerous to use a decade’s results to abandon a long history, the last decade offered sobering counters to old investing nostrums.

a. Value versus Growth

The basis for the belief that value beats growth is both intuitive and empirical. The intuitive argument is that value stocks are priced cheaper and hence need to do less to beat expectations and the empirical argument is that stocks that are classified as value stocks, defined as low price to book and low price to book stocks, have historically done better than growth stocks, defined as those trading at high price to book and high price earnings ratios. Looking at the annual returns on the lowest and highest PBV stocks in the United States, going back to 1927:

Raw Data from Ken French

The lowest price to book stocks have historically earned 5.22% more than the highest price to book stocks, if you look at 1927-2019. Broken down by decades, though, you can see that the assumption that value beats growth is not as easily justified:

Raw Data from Ken French

While there are some, especially in the old-time value crowd, that view the last decade as an aberration, the slide in the value premium has been occurring over a much longer period, suggesting that there are fundamental factors at play that are eating away at the premium. If you are a believer in value, as I am, there is a consolation prize here. Assuming that low PE stocks and low PBV stocks are good value is the laziest form of value investing, and it is perhaps not surprising that in a world where ETFs and index funds can be created to take advantage of these screens, there is no payoff to lazy value investing. I believe that good value investing requires creativity and out-of-the-box thinking, as well as a willingness to live with uncertainty, and even then, the payoff 

b. The Elusive Small Cap Premium

Another accepted part of empirical wisdom about stocks not only in the US, but also globally, is that small cap stocks deliver higher returns, after adjusting for risk using conventional risk and return models, than large cap stocks. 

Raw Data from Ken French

Looking at the data from 1927 to 2019, it looks conclusively like small market cap stocks have earned substantially higher returns than larger cap stocks; relative to the overall market, small cap stocks have delivered about 4-4.5% higher returns, and conventional adjustments for risk don't dent this number significantly. Not only has this led some to put their faith in small cap investing but it has also led analysts to add a small cap premium to costs of equity, when valuing small companies. I have not only never used a small cap premium, when valuing companies, but I am skeptical about its existence, and wrote a post on why a few years ago. Again, updating the data by decades, here is what I see:

Raw Data from Ken French

As with the value premium, the size premium had a rough decade between 2010 and 2019, dropping close to zero, on a value weighted basis, and turning significantly negative, when returns are computed on a equally weighted basis. Again, the trend is longer term, as there has been little or no evidence of a small cap premium since 1980, in contrast to the dramatic premiums in prior decades. If you are investing in small cap stocks, expecting a premium, you will be disappointed, and if you are still adding small cap premiums to your discount rates, when valuing companies, you are about four decades behind the times.

5. New buzzwords were born

Every decade has its buzzwords, words that not only become the focus for companies but are also money makers for consultants, and the last decade was no exception. At the risk of being accused of missing a few, there were two that stood out to me. The first was big data, driven partly by more extensive collection of information, especially online, and partly by tools that allowed this data to be accessed and analyzed. The other was crowd wisdom, where expert opinions were replaced by crowd judgments on a wide range of applications, from restaurant reviews to new (crypto) currencies.

a. Big Data

Earlier in this post, I looked at the surge in value of the FAANG stocks, and how they contributed to shaping the market over the last decade. One common element that all five companies shared was that they were not only reaching tens of millions of users, but that they were also collecting information on these users, and then using that information to improve existing products/services and add new ones. Other companies, seeking to emulate their success, tried their hand at “big data”, and it became a calling card for start-ups and young firms during the decade. While I agree that Netflix and Amazon, in particular, have turned big data into a weapon against competition, and Facebook’s entire advertising business is built on using personal data to focus advertising, I personally believe that like all buzz words, big data has been over sold. In particular, I noted, in a post from 2018 ,that for big data to create value,

1. The data has to be exclusive: For data to be valuable, there has to be some exclusivity. Put simply, if everyone has it, no one has an advantage. Thus, the fact that you, as a business, can trace my location has little value when two dozen other applications and services on my iPhone are doing exactly the same thing. 
2. The data has to be actionable: For value conversion to occur, the data that has been collected has to be usable in modifying and adapting the products and services you offer as a business. 

Using these two-part test, you can see why Amazon and Netflix are standouts when it comes to big data, since the data they collect is exclusive (Netflix on your viewing habits/tastes and Amazon on your retail behavior) and is then used to tailor their offerings (Netflix with its original content investments and offerings and Amazon with its product nudging). Using the same two-part test, you can also see why the claims of big data payoffs at MoviePass and Bird Scooters makers never made sense.

b. Crowd Wisdom

One consequence of the 2008 crisis was a loss in faith in both institutional authorities (central banks, governments, regulators) but also in experts, most of whom had been hopelessly wrong in the lead up to the crisis. It is therefore not surprising that you saw a move towards trusting crowds on answers to big questions right after the crisis. It is no coincidence that Satoshi Nakamoto (whoever he might be) posted the paper laying out the architecture of Bitcoin in November 2008, a proposal for a digital currency without a central bank or regulatory overlay, where transactions would be crowd-checked (by miners). While Bitcoin has been more successful as a speculative game than as a currency during the last decade, the block chains that it introduced have now found their way into a much wider range of businesses, threatening to replace institutional oversight (from banks, stock exchanges and other established entities) with cheaper alternatives. The crowd concept has expanded into almost every aspect of our lives, with Yelp ratings replacing restaurant reviewers in our choices of where to eat, Rotten Tomatoes supplanting movie critics in deciding what to watch and betting markets replacing polls in predicting election outcomes. I share the distrust of experts that many others have, but I also wary of crowd wisdom. After all, financial markets have been laboratories for observing how crowds behave for centuries, and we have found that while crowds are often much better at gauging the right answers than market gurus and experts, they are also prone to herding and collective bad choices. For those who have become too trusting of crowds, my recommendation is that they read “The Madness of Crowds”, an old manuscript that is still timely.

The decade to come

It has been said that those who forget the past are destined to relive it, and that is one reason why we pore over historical track records, hoping to get insight for the future. But it has also been said that army generals who prepare too intensely to fight the last war will lose the next one, suggesting that reading too much into history can be dangerous. To me the biggest lesson of the last decade is to keep an open mind and to not take conventional wisdom as a given. I don’t know what the next decade will bring us, but I can guarantee you that it will not look like the last one or any of the prior ones, So, strap on your seat belts and get ready! It’s going to be a wild ride!

YouTube Video


Data Links

1. Stocks, Bonds and Bills: 1928-2019
2. Intrinsic and Actual Risk free Rates: 1954-2019
3. Ken French Data on Value and Size Effects

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