Investing Whiplash: Looking for Closure with Apple and Amazon!

In September, I took a look, in a series of posts, at two companies that had crested the trillion dollar market cap mark, Apple and Amazon, and concluded that series with a post where I argued that both companies were over valued. I also mentioned that I was selling short on both stocks, Amazon for the first time in 22 years of tracking the company, and Apple at a limit price of $230. Two months later, both stocks have taken serious hits in the market, down almost 25% apiece, and one of my short sales has been covered and the other is still looking profitable. It is always nice to have happy endings to my investment stories, but rather than use this as vindication of my valuation or timing skills, I will argue that I just got lucky in terms of timing. That said, given how much these stocks have dropped over the last two months, it is an opportunity to not just revisit my valuations and investment judgments, but also to draw some general lessons about intrinsic valuation and pricing.

My September Valuations: A Look Back

In September, I valued Apple and Amazon and arrived at a value per share of roughly $200 for Apple and $1255 for Amazon, well below their prevailing stock prices of $220 (Apple) and $1950 (Amazon). I was also open about the fact that my valuations reflected my stories for the companies, and that my assumptions were open for debate. In fact, I estimated value distributions for both companies and noted that not only did I face more uncertainty in my Amazon valuation, but also that there was a significant probability in both companies that my assessment (that the stocks were over valued) was wrong. I summarized my results in a table that I reproduce below:

Apple Valuation & Amazon Valuation in September 2018

I did follow through on my judgments, albeit with some trepidation, selling short on Amazon at the prevailing market price (about $1950) and putting in a limit short sell at $230, which was fulfilled on October 3, as the stock opened above $230. With both stocks, I also put in open orders to cover my short sales at the 60th percentile of my value distributions, i.e., $205 at Apple and $1412 at Amazon, not expecting either to happen in the near term. (Why 60%? Read on...) Over the years, I have learned that investment stories and theses, no matter how well thought out and reasoned, don't always have happy endings, but this one did, and at a speed which I did not expect:

My Apple short sale which was initiated on October 3 was closed out on November 5 at $205, while Amazon got tantalizingly close to my trigger price for covering of $1412 (with a low of $1420 on November 20), before rebounding. 

Intrinsic Value Lessons

Every investment, whether it is a winner or a loser, carries investment lessons, and here are mine from my AAPL/AMZN experiences, at least so far:

1. Auto pilot rules to fight behavioral minefields: If you are wondering why I put in limit orders on both my Apple short sale and my covering trades on both stocks, it is because I know my weaknesses and left to my own biases, the havoc that they can wreak on my investment actions. I have never hidden the fact that I love Apple as a company and I was worried that if I did not put in my limit short sell order at $230, and the stock rose to that level, I would find a way to justify not doing it. For the limit buys to cover my short sales, I used the 60th percentile of the value distribution, because my trigger for buying a stock is that it be at least at the 40th percentile of its value distribution and to be consistent, my trigger for selling is set at the 60th percentile. It is my version of margin of safety, with the caveat being that for stocks like Amazon, where uncertainty abounds, this rule can translate into a much bigger percentage price difference than for a stock like Apple, where there is less uncertainty. (The price difference between the 60th and 90th percentile for Apple was just over 10%, whereas the price difference between those same percentiles was 35% for Amazon, in September 2018.)
2. Intrinsic value changes over time: Among some value investors, there is a misplaced belief that intrinsic value is a timeless constant, and that it is the market that is subject to wild swings, driven by changes in mood and momentum. That is not true, since not only do the determinants of value (cash flows, growth and risk) change over time, but so does the price of risk (default spreads, equity risk premiums) in the market. The former occurs every time a company has a financial disclosure, which is one reason that I revalue companies just after earnings reports, or a major news story (acquisition, divestiture, new CEO),  and the latter is driven by macro forces. That sounds abstract, but I can use Apple and Amazon to illustrate my point. Since my September valuations for both companies occurred after their most recent earnings reports, there have been no new financial disclosures from either company. There have been a few news stories and we can argue about their consequentiality for future cash flows and growth, but the big change has been in the market. Since September 21, the date of my valuation, equity markets have been in turmoil, with the S&P 500 dropping about 5.5% (through November 30) and the US 10-year treasury bond rate have dropped slightly from 3.07%  to 3.01%, over the same period. If you are wondering why this should affect terminal value, it is worth remembering that the price of risk (risk premium) is set by the market, and the mechanism it has for adjusting this price is the level of stock prices, with a higher equity risk premium leading to lower stock prices. In my post at the end of a turbulent October, I traced the change in equity risk premiums, by day, through October and noted that equity risk premiums at the end of the month were up about 0.38% from the start of the month and almost 0.72% higher than they were at the start of September 2018. In contrast, November saw less change in the ERP, with the ERP adjusting to 5.68% at the end of the month.
   
   Plugging in the higher equity risk premium and the slightly lower risk free rate into my Apple valuation, leaving the rest of my inputs unchanged, yields a value of $197 for the company, about 1.5% less than my $200 estimate on September 21. With Amazon, the effect is slightly larger, with the value per share dropping from $1255 per share to $1212, about 3.5%. Those changes may seem trivial but if the market correction had been larger and the treasury rate had changed more, the value effect would have been larger.
3. But price changes even more: If the fact that value changes over time, even in the absence of company-specific information, makes you uncomfortable, keep in mind that the market price usually changes even more. In the case of Apple and Amazon, this is illustrated in the graph below, where I compare value to price on September 21 and November 30 for both companies:
   
   In just over two months, Apple's value has declined from $201 to $196, but the stock price has dropped from $220 to $179, shifting it from being overvalued by 9.54% to undervalued by 9.14%. Amazon has become less over valued over time, with the percentage over valuation dropping from  55.38% to 39.44%. I have watched Apple's value dance with its price for  much of this decade and the graph below provides the highlights:
   
   From my perspective, the story for Apple has remained largely the same for the last eight years, a slow-growth, cash machine that gets the bulk of its profits from one product: the iPhone. However, at regular intervals, usually around a new iPhone model, the market becomes either giddily optimistic about it becoming a growth company (and pushes up the price) or overly pessimistic about the end of the iPhone cash franchise (and pushes the price down too much). In the face of this market  bipolarity, this is my fourth round of holding Apple in the last seven years, and I have a feeling that it will not be the last one.
4. Act with no regrets:  I did cover my short sale, by buying back Apple at $205, but the stock continued to slide, dropping below $175 early last week. I almost covered my Amazon position at $1412, but since the price dropped only as low as $1420, my limit buy was not triggered, and the stock price is back up to almost $1700. Am I regretful that I closed too early with Apple and did not close out early enough with Amazon? I am not, because if there is one thing I have learned in my years as an investor, it is that you have stay true to your investment philosophy, even if it means that you leave profits on the table sometimes, and lose money at other times. I have faith in value, and that faith requires me to act consistently. I will continue to value Amazon at regular intervals, and it is entirely possible that I missed my moment to sell, but if so, it is a price that I am willing to pay.
5. And flexible time horizons: A contrast that is often drawn between investors and traders is that to be an investor, you need to have a long time horizon, whereas traders operate with windows measured in months, weeks, days or even hours. In fact, one widely quoted precept in value investing is that you should buy good companies and hold them forever. Buy and hold is not a bad strategy, since it minimizes transactions costs, taxes and impulsive actions, but I hope that my Apple analysis leads you to at least question its wisdom. My short sale on Apple was predicated on value, but it lasted only a month and four days, before being unwound. In fact, early last week, I bought Apple at $175, because I believe that it under valued today, giving me a serious case of investing whiplash. I am willing to wait a long time for Apple's price to adjust to value, but I am not required to do so. If the price adjusts quickly to value and then moves upwards, I have to be willing to sell, even if that is only a few weeks from today. In my version of value investing, investors have to be ready to hold for long periods, but also be willing to close out positions sooner, either because their theses have been vindicated (by the market price moving towards value) or because their theses have broken down (in which case they need to revisit their valuations).

Bottom Line

As investors, we are often quick to claim credit for our successes and equally quick to blame others for our failures, and I am no exception. While I am sorely tempted to view what has happened at Apple and Amazon as vindication of my value judgments, I know better. I got lucky in terms of timing, catching a market correction and one targeted at tech stocks, and I am inclined to believe that  is the main reason why my Apple and Amazon positions have made me money in the last two months. With Amazon, in particular, there is little that has happened in the last two months that would represent the catalysts that I saw in my initial analysis, since it was government actions and regulatory pushback that I saw as the likely triggers for a correction. With Apple, I do have a longer history and a better basis for believing that this is market bipolarity at play, with the stock price over shooting its value, after good news, and over correcting after bad news, but nothing that has happened  to the company in the last two month would explain the correction. Needless to say, I will bank my profits, even if they are entirely fortuitous, but I will not delude myself into chalking this up to my investing skills. It is better to be lucky than good!

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Blog Posts

1. Apple and Amazon at a Trillion $: A Follow-up on Uncertainty and Catalysts (September 2018)
2. An October Surprise: Making Sense of Market Mayhem (October 2018)

Amazon and Apple at a Trillion $: A Follow-up on Uncertainty and Catalysts!

In my last post, I looked at Apple and Amazon, as their market caps exceeded a trillion dollars, tracing the journey that they took over the last two decades to get to that threshold and valuing them  given their current standing. While you can check out the stories that I told and the details of my valuation in that post, I valued Apple at $200, about 9% less than the market price, and Amazon at abut $1255, about 35% lower than its market price. I concluded the post with a teaser, promising to come back with my decisions on whether I would sell my existing Apple shareholding and/or sell short on Amazon, after reviewing two loose ends. The first is to lay bare the uncertainties inherent in both valuations, to see if there is something in those uncertainties that I can use to make a better decision. The second is to evaluate whether there are catalysts that will convert the gap that I see between value and price into actual profits.

Facing up to Uncertainty

One of the recurrent themes in this blog is that we (as human beings) are not good at dealing with uncertainty. We avoid, evade and deny its existence, and in the process end up making unhealthy choices. When valuing companies, uncertainty is a given, a feature and not a bug, and traditional valuation models often give it short shrift. In fact, looking at my valuations of Apple and Amazon, you can see that the only place that I explicitly deal with uncertainty is in the discount rate, and even that process is rendered opaque, because I use betas and equity risk premiums to get to my final numbers. My cash flows reflect my expectations, and even in my moments of greatest hubris, I don't believe that I know, with precision, what will happen to Apple's revenue growth over time or how Amazon's operating margin will evolve in the future. So, why bother? In investing, you have no choice but to make your best estimates and value companies, knowing fully well that you will be wrong, no matter how much information you have and how good your models are. 

That said, it is puzzling that we still stick with point estimates (single numbers for revenue growth and operating margins) in conventional valuation, when we have the tools to bring in uncertainty  into our valuation judgments. While our statistics classes in college are a distant (and often painful) memory for most of us, there are statistical tools that can help us. While these tools may have been impractical even a decade ago, they are now more accessible, and when coupled with the richer data that we now have, we have the pieces in place to go beyond single value judgments. It is with this objective in mind that I recently updated a paper that I have on using probabilistic and statistical techniques to enrich valuation online, and you can get the paper by going to this link. Consider it a companion to another paper that I wrote a while back, dealing more expansively with uncertainty and healthy ways of dealing with it in investing and valuation.

Summarizing the probabilistic techniques that may help in valuation, I suggest three: (1) Scenario Analysis, for valuing companies that may have different valuations depending upon specific and usually discrete scenarios unfolding (for example a change in regulatory regimes for a bank or telecommunications company), (2) Decision Trees, for valuing companies that face sequential risk, i.e., you have to get through one phase of risk to arrive at the next one, as is the case with young drug companies that have new drugs in the regulatory pipeline and (3) Monte Carlo Simulations, the most general technique that can accommodate continuous and even correlated risks that you face in valuation, as is the case when you forecast revenue growth and operating margins for Apple and Amazon, in pursuit of their values.

Simulated Values: Apple and Amazon
Before delving into the simulations for Apple and Amazon, it is important that we set up the structure of the simulations first by first deciding what variables to build distributions around. While you may be tempted by the power of the tool to make every input (from risk free rates to terminal growth rates) into a distribution, my suggestion is that you focus on the variables that not only matter the most, but where you feel most uncertain. With Apple, the three inputs that I will build distributions around are revenue growth, operating margins and cost of capital. With Amazon, I will add a fourth variable to the mix, in the sales to invested capital, measuring how efficiently Amazon can deliver its revenue growth.

Apple: A September 2018 Simulation
I build around my core story for Apple, which is that it will be a slow growth, cash machine, deriving the bulk of its revenues, profits and value from the iPhone, but allow for uncertainty in each of my key inputs:

1. Revenue growth: While my expected growth rate stays 3%, I allow for a range of growth rates from no growth (flat revenues) , if the iPhone's higher prices cost it signifiant market share) to 6% growth, which would require that Apple find a new growth source, perhaps from services or a new product.
2. Operating Margin: In my story, I assumed that operating margin would decline to 25% (from  the current 30%) over the next five years. While I still feel that this is the best estimate, I allow for the possibility that competition will be stronger than expected (with margins dropping to 20%), at one end, and that Apple will be able to use its brand name to keep margins at 30%, at the other. 
3. Cost of capital: My base case cost of capital is 8.20%, reflecting Apple's mix of businesses, but allowing for errors in my sector risk measures and changes in business mix, I build a distribution centered around 8.20% but with a small standard error (0.40%).  

Since I want to stay market neutral, taking no stand on either the level of interest rates or overall stock prices, I am leaving the ten-year bond rate and equity risk premium untouched. The results of the simulation are below:

Valuation & Simulation Output

Note that the median, mean and base case valuations are all bunched up at $200 and that the range in value, using the 10th and 90th percentiles, is tight ($176 to $229).

Amazon: A September 2018 Simulation
Moving from Apple to Amazon, my uncertainties multiply partly because my story is of a company that will move into any business where it believes its disruptive platform can deliver results, and there are very few businesses that are immune. Consequently, every input into the valuation is much more volatile, but I will focus on four:

1. Revenue Growth: I used an expected growth rate for Amazon of 15% a year for the next 5 years, tapering down to lower levels in the future, to push revenues to $626 billion, ten years from now. While that is an ambitious target, Amazon has proved itself capable of beating sky high expectations before and it is plausible that the growth rate could be as high as 25% (which would translate to revenues of $1.13 trillion, ten years out). There is also the possibility that regulators and anti-trust enforcers may step in and restrain Amazon's growth plans, which could cause the growth rate to drop significantly to 5% (resulting in revenues of $330 billion in year 10).
2. Operating Margin: While Amazon's margins have been on a slow, but steady, climb in the last few years, much of that improvement has come from the cloud services business, and the future course of margins will depend not only on how well Amazon can bring logistics costs under control but also on what new businesses it targets. I will stay with my base cash assumption of a target operating margin of 12.5%, but allow for the possibility that Amazon's margins will stay stagnant (close to today's margins of about 7%), at one extreme, and that there might be a new, very profitable business that Amazon can enter, pushing up the margins above 18%, at the other.
3. Sales to Invested Capital: Currently, Amazon is an efficient utilizer of capital, generating $5.95 in revenues for every dollar of capital invested. While this will remain my base case, there may be future businesses that Amazon is targeting that may be more or less capital intensive than its current ones, leading to a significant range (3.95 for the more capital intensive - 7.95 to the less  capital intensive).
4. Cost of Capital: I will stick with my base case cost of capital of 7.97%, with the possibility that that it could drop as Amazon's older businesses become profitable (but not by much, since the current cost of capital is close to the median for global companies) as well as the very real chance that it could go up significantly, if Amazon targets risky businesses in emerging markets for its growth.

Valuation & Simulation Output

The median value across the simulations is $1242, close to the base case valuation of $1,255. The range on value, using the 10th and 90th percentiles is $705 - $2,152, much wider than the range for Apple.

Lessons from Apple and Amazon Simulations
Simulations yield pretty pictures and if that is all you get out of them, it is time and energy wasted. There are lessons that we can eke out of the Apple and Amazon simulations that may help us in making more informed judgments:

1. This is not about getting better estimates of value: If you are running simulations because you think they will give you more precise or better estimates of value than point estimate valuations, you will be disappointed. Since my input distributions are centered around my base case assumptions, and they should be, the median values across 100,000 simulations are close to my base case valuations for both Apple and Amazon.
2. If it is a risk proxy, it is a very noisy and dangerous one: It is true that the spread of the distributions provides a measure of estimation uncertainty that you bring into your valuation. Using the Apple and Amazon simulations to illustrate, I face far greater uncertainty with my Amazon story than with my Apple story, and you can see it reflected in a larger range of value for the former. You may be puzzled that my cost of capital is lower for Amazon than for Apple, but that reflects the fact that much of the uncertainty that I face with Amazon is company-specific and should be buffered by other stocks in my portfolio. As a diversified investor, the variance in simulated values is a poor proxy for risk. However, if you are an investor who prefers concentrated portfolios, you can use the variance in simulated value as a measure of risk. 
3. There can be no one margin of safety for all companies: I have written about the margin of safety before, often with skepticism, and one of my critiques has been with the way it is used in practice, where it is set at a fixed number for all companies. Thus, you will find value investors who use a margin of safety of 15% or 20% for all stocks, and the Apple and Amazon simulations show the danger in this practice. A 15% margin of safety for Apple may be too large, given how tightly values are distributed for the company, whereas the same 15% margin of safety may be too small for Amazon, with its wider band of values.
4. Tails matter: Symmetry or the lack of it in distributions may seem like an inside statistics topic, but with simulated values, it has investment consequences. You can see that Apple's value distribution is  much more symmetric than Amazon's distribution, with the latter having a significant positive skew, reflecting a greater likelihood of big positive surprises in value, than negative ones. With companies with exposure to large and potentially catastrophic news stories (a large lawsuit or debt covenants), you can have value distributions that are negatively skewed.  In general, positive skewed distributions are better for (long) investors than negatively skewed ones, and the reverse is true for investors who are shorting a company.

I ran the simulations after my base case valuations suggested that Apple and Amazon were over valued, to see how they might affect my decision on whether to sell short on either company. The results are mixed.

• While the simulations confirm my over valuations (no surprise there), with both companies, the current stock price is well within the realm of possibilities. While my base case valuation suggested that Apple was far less over valued (10%) than Amazon (55%), there is roughly a 15-20% chance that both companies are under valued, not over valued.
• In addition, with Amazon, there is the added risk, if you are selling short, given the long positive tail on the distribution, that if I am wrong, the price I will pay will be much greater than if I am wrong with Apple.

The bottom line is that while Amazon seemed like a much better short selling target, after my base case valuations, because it was far more over valued than Apple, the simulations that I did on the two companies even out the scales, at least marginally. Apple is more over valued, but the probability of making money, assuming my valuations are on target is about the same with both stocks, and the downside of being wrong is far greater with Amazon than with Apple.

Value and Price: The Search for Catalysts
In the post that initiated this series, I looked at why crossing a trillion-dollar threshold may matter to investors, using the contrast between the value process and the pricing process. In effect, I argued that there can be a gap between value and price, and that even if you are right about your value judgment, you will make money only if the gap between the two closes:

Investment success thus rides not only on the quality of your value judgment, and how much faith you have in it, but on whether there are catalysts that can cause the gap to change. With companies, these catalysts can take different forms:

1. Earnings reports: In their earnings reports, in addition to the proverbial bottom line (earnings per share), companies provide information about operating details (growth, margins, capital invested). To the extent that the pricing reflects unrealistic expectations about the future, information that highlights this in an earnings report may cause investors to reassess price. 
2. Corporate news: News stories about a company's plans to expand, acquire or divest businesses  or to update or introduce new products can reset the pricing game and change the gap.
3. Management Change/Behavior: A change in the ranks of top management or a managerial misjudgment that is made public can cause investors to hit the pause button, and this is especially true for companies that are bound to a single personality (usually a powerful founder/CEO) or derive their value from a key person. 
4. Macro/ Government: A change in the macro environment or the regulatory overlay for a company can also cause a reassessment of the gap.

With all of these catalysts, there may be value effects (because the cash flows, growth and risk) as well, and it should also be noted that when the gap changes, it may not always close. In fact, these catalysts can sometime make a gap bigger, by feeding into pricing momentum.

As an investor, I look for catalysts when I invest, but I am even more intent on finding them, when I sell short than when I am long a stock. The reason for that divergence is that I am in far greater control of my time horizon, when I buy a stock, since, as long as I stay disciplined and retain faith in my value, only liquidity needs can cause me to sell. When I sell short, my time horizon is far less under my control, exposing me to timing risk. Put different, I can bet on a company being over valued, be right on my thesis, but still lose money on a short sale, because I am forced to close out my position, in the absence of a catalyst.

Going through the list of catalysts with Apple and Amazon, with both stocks approaching all-time highs, there is no obvious pricing trigger than I can point to, though my technical analyst friends will undoubtedly point to indicators that I did not even know existed. On the earnings front, the earnings reports for both companies are so heavily scripted to expectations that it would take a big surprise to reset stories, and I don't see that happening. In fact, I will predict that Amazon's earnings reports will continue to deliver double digit revenue growth and improving margins for the next few quarters, and investors will react positively, even though the growth may not be high enough or the margin improvement substantial enough to justify the market pricing. On the corporate news front, Apple's smart phone business model, with the pressure it puts on the company every year or two to reinvent itself, with the latest and the best, coupled with its big announcement events, creates catalyst moments. Looking back at Apple's ups and downs over the last few years, the triggers for substantial up and down movements on the stock have been new iPhone models doing better or worse than expected. In contrast, Amazon is remarkably low key in new product introductions, preferring to slip in under the radar. Both companies have well regarded and established CEOs, and neither company is personality-driven, making it unlikely that you will see management changes triggering big price changes. Finally, on the macro front, both companies face potential catalyst moments. For Apple, it is the possibility of a trade war with China, a huge market for its products and devices, and for Amazon, it is talk of regulatory restrictions and anti-trust actions that can constrain the company.  Since I cannot filibuster my way to a non-decision, I decided to compare my Apple and Amazon numbers/analysis, side by side:

I sold my Apple shares at $220, at the start of trading on Friday (9/21), but while I have not sold short any more shares. I have put in a limit (short) sell, if the price hits $230 (roughly my 90th percentile of value) in the near future. With Amazon, I sold short at $1950 at the start of trading on Friday (9/21).  the first time in twenty years that I have sold short on the company, and one reason that I am pulling the trigger is because I believe that the pushback from regulators and anti-trust enforcers will slow the company down in ways that no competitor ever could. I am doing so, with open eyes, since I believe that Amazon is in one of the best run companies in the world, adept at setting market expectations and beating them, and with a track record of taking short sellers to the graveyard. Time will tell, and I am sure that some of you reading this post will let me know, if my bet goes awry, but I don't plan to lose any sleep over this. 

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Trillion Dollar Posts

1. Trillion Dollar Toppers: Market Drivers, Pricing Triggers and Catalysts
2. Amazon and Apple at a Trillion $: Looking back and Looking forward
3. Amazon and Apple at a Trillion $: A Follow up on Uncertainty and Catalysts!

Spreadsheets

1. Apple valuation and simulation results
2. Amazon valuation and simulation results

(I use Crystal Ball, an add-on to Excel, for my simulations. If you don't have that extension (available only on the PC version), you cannot recreate my simulations, but you can download the program for a trial run on the Oracle website)

Papers/Reading

1. Facing up to Uncertainty: Using Probabilistic Approaches in Valuation
2. Living with Noise: Investing and Valuation in the Face of Uncertainty

A Tale of Two Markets: Politics and Investing!

"It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct to Heaven, we were all going direct the other way.” That Charles Dickens opening to The Tale of Two Cities is an apt description of financial markets today. While disagreement among market participants has always been a feature of markets, seldom has there been such a divide between those who believe that we are on the verge of a massive correction and those who equally vehemently feel that this is the cusp of a new bull market, and between those who see unprecedented economic and policy uncertainty and market indicators that suggest the exact opposite. Is one side right and the other wrong? Is it possible that both sides are right? Or that both sides are wrong?

The Divergence

The investor divide is visible, and sometimes dramatically so, in almost every aspect of markets, from risk indicators to fund flows to consumer behavior.

1. Risk on? Risk off?

Do we live in risky or safe times? It depends on who you ask and what indicator to look at. Over the last two decades, the VIX (Volatility Index) has become a proxy for how much risk investors see in  equity markets and the graph below captures the movement of the index (and a similarly constructed index for European stocks) over much of that period:

VIX: S&P 500, Euro VIX: Euro Stoxx 50

Last year, the volatility measures in both the US and Europe not only took Brexit and the Trump election in stride but they have, in the months since the US presidential elections, continued their downward move, ending May 2017 at close to historic lows.

Lest you believe that this drop in volatility is restricted to stocks, you see similar patterns in other measures of risk including treasury yield volatility (shown in the graph) and in corporate bond volatility. This volatility swoon is also not restricted to the US, since measures of global volatility have also leveled off or decreased over the last few months. In fact, the volatility in currency movements has also dropped close to all-time lows. 

In sum, the market seems to be signaling a period of unusual stability. That is at odds with what we are reading about economic policies, where there is talk of major changes to the US tax code and trade policies, signaling a period of high volatility for global economies. The economic policy uncertainty index, is an index constructed by looking at news stories, CBO lists of temporary tax code provisions and disagreement among economic forecasters, has been sending a very different signal to the market than the market volatility indices:

In the months since the election, the indices have spiked multiple times, breaking through records set during the 2008 crisis. In short, we are either on the cusp of unprecedented stability (at least as measured with the market volatility indices) or explosive change (according to the economic policy indices).

2. Funds in? Funds out?

The ultimate measure of how comfortable investors feel about risk is whether they are putting money into stocks or taking them out and fund flows have historically been a good measure of that comfort. Put simply, if investors are wary and risk averse about an asset class or market, you should expect to see money flow out of that market and if they are sanguine, you should see money flow in. In the graph below, we look at fund flows into equity, bond and commodity funds, by month, from the start of 2016 to the April 2017:

Source: Investment Company Institute

More money has flowed into both equity and bond funds, on a monthly basis, since November 2016 than in the first ten months of 2016.  While the fund flow picture is consistent with the drop in volatility that you see across the market-based risk measures, there are discordant notes here as well. First, and perhaps least surprisingly, the perennial market bears have become even more bearish, with concerns about macroeconomic risk augmenting their long-standing concerns about stocks trading at high PE ratios. Second, there are big name investors who are cautioning that a market correction is around the corner, with Jeff Gundlach being the latest to argue that it is time to sell the S&P 500 and buy emerging market stocks. Finally, there is some evidence that money is leaving US stocks, with the Wall Street Journal reporting that money going into US stocks is at a 9-year low, while inflows into European stocks hit a five-year high.

3. Corporate and Business Behavior

Ultimately, risk does not come from market perceptions or newsletters but is reflected in consumer spending and business investment. On these dimensions as well, there is enough ammunition for both sides to see what they want to see. With consumer confidence, the trend lines are clear cut, with consumers becoming increasingly confident about both their current and future prospects:

That confidence, though, is not carrying through into consumer spending, where the numbers indicate more uncertainty about the future:

While consumer spending has increased since November, the rate of change has not accelerated from growth in prior years. You can see similar divergences between confidence and spending numbers at the business level, with business confidence up strongly since November 2016 but business investment not showing any significant acceleration.  In short, both consumers and businesses seem to be feeling better about future prospects but they don't seem willing to back up that confidence with spending.

The Diagnostics
So, how do we go about explaining these stark differences between different indicators? Has risk gone up or has it gone down in the last few months? Is money coming into stocks or is it leaving stocks? Why, if consumers and businesses are feeling better about the future, are they not spending and investing more? There are four possible explanations and they are not mutually exclusive. In fact, I believe that all four contribute to the dichotomy.

1. Markets have become inured to crises: The last decade has been one filled with crises, in different regions and with different origins, with each one described as the one that is going to tip markets into collapse. Each time, after the debris has cleared, markets have emerged resilient and sometimes stronger than they went in. It is possible that investors have learned to take these market shocks in stride. Like the boy who cried wolf, it is possible that market pundits are viewed by investors as prone to hysteria, and are being ignored.
2. Disagreement about economic policy changes/effects: It is also possible that economic pundits and investors are parting ways on both the likelihood of economic policy shocks and/or the consequences. On economic policy changes, the skepticism on the part of investors can be explained by the fact that governments across the globe seem to be more interested in talking about making big changes than they are in making those changes. On the effects of changes, the logic that policy uncertainty leads to economic uncertainty which, in turn, causes market uncertainty is being put to the test as governments and central banks are discovering that policy changes, on everything from interest rates to tax rates, are having a much smaller impact on both economic growth and investor behavior than they used to, perhaps because of globalization. 
3. Macro to Micro Risk: One of the residual effects of the 2008 crisis was an increase in correlation across stocks, with the proportion of risk attributable to market risk in individual stocks rising, relative to firm-specific risk, with that effect persisting into 2016.  Since November 2016, the correlation across stocks has dropped, as investors try to assess how new policies on taxes and infrastructure will help or hurt individual stocks.and this may explain the drop in the VIX, even as individual stocks are perhaps getting riskier.
4. Politics first, analysis later: It is no secret that we live in partisan times, where almost every news story is viewed through political lens. Why should financial markets be immune from political partisanship? I have seen no research to back this up, but my very limited sampling of investor views (on politics and markets) indicates a convergence of the two in recent months. Put simply, Trump supporters are more likely to be bullish on stocks and confident about the future of the economy, and Trump opponents are more likely to be bearish about both stocks and the economy. Both sides see what they want to see in news stories and data releases and ignore that which does not advance their theses.

So, who is right here? I think that both sides have reasonable cases to make and both have their blind spots. On crisis weariness, it is true that market watchers have been guilty of hyping every crisis over the last decade, but it is also true that not all crises are benign and that one of them may very well be the next "big one". On economic policy changes and effects, I am inclined to side with those who feel that the powers of governments and central banks to guide economies is overstated but I also know that both entities can cause serious damage, if they pursue ill-thought through policies. On the political front, I won't tip my hand on my political affiliations but I believe that viewing economics and markets through political lens can be deadly for my portfolio. 

My Sanity Check:  Equity Risk Premiums
As you can see, it is easy to talk yourself on to the cliff or off the cliff but after all the talking is done, it remains just that, talk. So, I will fall back on a calculation that lets the numbers do the talking (rather than my biases) and that is my computation of the implied equity risk premium for US stocks. On June 1, 2017, as I have at the start of every month since September 2008 and every year going back to 1990, I backed out the rate of return that investors can expect to make on the S&P 500, given where it was trading at on that day (2411.8) and expected cash flows from dividends and buybacks on the index in the future (estimated from the cash flows in the most recent twelve months and consensus estimates of earnings growth over the next five years in earnings). Given the index level and cash flows on June 1, 2017, the expected annual return on stocks (the IRR of the cash flows) is 7.50%. Netting out the 10-year treasury bond rate (2.21%) on June 1 yields an implied equity risk premium of 5.29%.

Download spreadsheet

To put this in perspective, I have graphed out the implied equity risk premiums for the S&P 500, by year, going back to 1960.

Download historical data

To the extent that the equity risk premium is higher than median values over values over the 1960-2017 time period, you should feel comforted, but the market's weakest links are visible in this graphs as well. Much of the expansion in equity risk premiums in the last decade has been sustained by two forces.

1. Low interest rates: If the US treasury bond rate was at its 2007 level of 4.5%, the implied equity risk premium on June 1, 2017, would have been 3%, dangerously close to all time lows. 
2. High cash return: US companies have been returning immense amounts of cash in the form of buybacks over the last decade and it is the surge in the collective cash flow that pushes premiums up. As earnings at S&P 500 companies flattened and dropped in 2015 and 2016, you can argue that the current rate of cash return is not just unsustainable but also incompatible with the infrastructure-investment driven growth stories told by some market bulls.

The first half of 2017 delivered some good news and some bad news on this front. The good news is that notwithstanding rumors of Fed tightening, treasury bond rates dropped from 2.45% on January 1, 2017 to 2.21% on June 1, 2017, and S&P 500 companies reported much stronger earnings for the first quarter, up almost 17% from the first quarter of 2016. The bad news is that it seems a near certainty that Fed will hike the Fed Funds rate soon (though its impact on longer term rates is debatable) and that there is preliminary evidence that companies have slowed the pace of stock buybacks.  The bottom line, and this may disappoint those of you who were expecting a decisive market timing forecast, is that stocks are richly priced, relative to history, but not relative to alternative investments today. Paraphrasing Dickens, we could be on the verge of a sharp surge in stock prices or a sharp correction, entering an extended bull market or on the brink of a bear market, at the cusp of an economic boom or on the precipice of a bust. I will leave it to others who are much better than me at market timing to make these calls and continue to muddle along with my stock picking.

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Attachments

1. Implied Equity Risk Premium for S&P 500 - June 2017
2. Historical ERP for S&P 500: 1961-2017