Friday, January 13, 2017

January 2017 Data Update 2: The Resilience of US Equities!

If asked to list the biggest threats to US equities at the start of 2016, most people would have pointed to the Federal Reserve’s imminent retreat from quantitative easing and the possibility of a slowdown in China spilling into lower global growth. Those fears contributed to a very bad start to 2016 for US stock markets, and as stocks dropped by about 5% in January, those who have warned us about a bubble looked prescient. But the stock market, as is its wont, surprised us again. Not only did US equities come back from those setbacks but it weathered other crises during the year, including the decision by UK voters to exit the EU in June and by US voters to elect Donald Trump as president in November to end the year with healthy gains. As we enter a year with potentially big changes to the US tax code and trade policy looming, it is time to take stock of where we are and where we might be going in the next year.

Stocks and Bonds: Looking Back
The best place to see  how the year unfolded for stocks is to trace out how the S&P 500 (large cap stocks), the S&P 600 (for small cap stocks) and US ten-year treasury bond rate did on a month by month basis through 2016.
Monthly returns, using month-end values
To convert the index values into returns each month, I first computed price changes for the indices each month (and cumulatively over the year) and added the dividends for the year to estimate annual returns of 11.74% for the S&P 500 and 26.46% for the S&P 600; it was a very good year for small cap stocks and a good one for large cap stocks.  I converted the treasury bond rates into bond price changes each month and cumulatively (for a 10-year constant maturity bond) over the year and added the coupon at the start of the year to get a return of 0.58% for the year; the rise in interest rates cause bond prices to drop by 1.68% during the year.

To put these returns in perspective, I added the S&P 500 and treasury bond return for 2016 to my historical data series which goes back to 1928 and computed both simple and compounded (geometric) annual averages in both for the entire period and compared them to a annualized 3-month treasury bill return (which you can think of as the return for holding cash).
Download spreadsheet with historical data

This table (or some variant of it) is used by practitioners to get the equity risk premium for US markets, by subtracting the average return on treasuries (bills or bonds) from the average return on stocks over a historical time period. Using my estimates, I get the following values for the historical equity risk premium for the US market.
Download spreadsheet with historical data
Note that the equity risk premium varies widely, from 2.3% to 7.96%,  depending on how long a time period you use, how you  compute averages (simple or compounded) and whether you use treasury bills or bonds as your measure of a risk free investment. Adding a statistical note of caution, each of these estimated premiums comes with a standard error, reported in red numbers below the estimated number. Thus, if you decide to use 6.24%, the difference between the arithmetic average returns on stocks and bonds from 1928-2016, as your historical risk premium, that number comes with a standard error of 2.26%. That would mean that your true equity risk premium, with 95% confidence, could be anywhere from 1.72% to 10.76% (plus and minus two standard errors).

Stocks: Looking forward
Looking at the past may give us comfort but investing is always about the future. I have been a long-time skeptic of historical risk premiums for two reasons.  First, as noted in the table above, they are noisy (have high standard errors). Second, they assume mean reversion, i.e., that US equity markets will revert back to what they have historically delivered as returns and that is an increasingly tenuous assumption. It is for this reason that I compute a forward-looking estimate of the equity risk premium for the US, using the S&P 500 Index as my measure of US stocks. Specifically, I estimate expected cash flows from dividends and buybacks from holding the S&P 500 for the next five years, using the trailing 12-month cash flow as my starting point and an expected growth rate in earnings as my proxy for cash flow growth and use these estimates, in conjunction with the index level on January 1, 2017, to compute an internal rate of return (a discount rate that will make the present value of the expected cash flows on the index equal to the traded level of the index).
Given the level of the index (2038.83 on January 1, 2017) and expected cash flows, I estimate an expected return on 8.14% for stocks and netting out the T.Bond rate of 2.45% on January 1, 2017, yields an implied ERP for the index of 5.69%. That number is down from the 6.12% that I estimated at the start of 2016 but is still well above the historical average (from 1960-2016) for this implied ERP of about 4.11%.

There is one troubling feature to the trailing 12 month cash flows on the S&P 500 that gives me pause. As was the case last year, the cash flows returned by S&P 500 companies represented more than 100% of earnings during the trailing 12 months, an unsustainable pace even in a mature market. I recomputed the ERP on the assumption that the cash payout ratio will decrease over time to sustainable levels, i.e., levels that would allow for enough reinvestment given the growth rate. The results are shown below:
The implied ERP for the index, with payout adjusting to about 82.3% of earnings in year 5, is 4.50%, still higher than historic norms but with a much slimmer buffer for safety. Looking at the next year, though, the potential for tax law changes will roil estimates. Not only are many analysts expecting significant increases in earnings next year of 12-15%, as they expect corporate tax rates to get lowered (at least in the aggregate) but there may also be a return of some of the trapped cash ($2 trillion or higher) back to the US, if that portion of the law is modified. Either change will relieve the pressure on cash flows and make it less likely that you will see dramatic cuts in stock buybacks or dividends.

Interest Rates: What lies ahead?
With bonds, I will take a different tack. I believe that, rather than waiting on the Fed, the path for interest rates this year will be determined by the path of the economy, with higher real growth and/or higher inflation pushing up rates. Updating a figure that I have used before, where I compare the T.Bond rate to an intrinsic interest rate (computed by adding expected inflation to expected real growth), you do see the beginning of a gap between the two at the end of 2016:
Entering 2017, the ten-year treasury bond at 2.45% is well below the intrinsic risk free of 3.60%, obtained by adding the inflation rate to real GDP growth through much of 2016. It is entirely possible that the economy will revert back to its post-2008 sluggishness or that there will be other shocks to the global economic system that will cause inflation and real growth to recede and interest rates to stay low, but for the moment at least, it looks like interest rates are their journey back to a new normal. If I were advising the Fed, my suggestion is for them is to act quickly on rates (perhaps as early as the next meeting) in order to preserve the fiction that it is they who are setting rates, rather than following them.

PE, CAPE and Bond PE Ratios
I am not a fan of PE crystal ball gazing but I know that there are many who make their market judgments based on PE ratios. Updating a graph that I last used when I posted on CAPE last year to reflect the numbers at the start of the 2017, here is what the updated PE ratios look like for the S&P 500:
Spreadsheet with data
While current PE ratios, in all their variants, are not at 1999 levels, they have clearly climbed back to 2007 levels and are well above historical averages. Scary, right? This will inevitably lead to the warnings about markets overheating and a coming crash, just as it has for much of the last five years. While one of these years, that predicted crash will come, you may want to look at stock PE ratios relative to the PE ratio on a treasury bond today, another comparison that I made in my CAPE post;
Spreadsheet with data
It is true that stocks look expensive today (at 27 times earnings) but they start to look much better when you compare them to bonds (at 40 times earnings). If you are concerned that bond rates will climb this year to reflect higher inflation/real growth, you may be forced to take another look at how you are pricing stocks at that time. There is one final divergence that needs explaining. In the last section, I noted that implied equity risk premiums on the US market look reasonable or even high relative to historical norms (a sign that the market is not over valued) but in this section, I have pointed to PE ratios being higher than historical norms (a sign of stock prices overheating). How do you reconcile the two findings? The answer lies in this final graph:
Spreadsheet with data
While PE ratios have risen over the last five or six years by almost 35-40%, the ratio of price to cash returned to stockholders (in the form of dividends and buybacks) has barely budged for the last five years. Here again, you should heed the warnings in the last section, where I noted that US companies are returning almost 107% of their earnings as cash to stockholders, unsustainable in the long term. If companies abruptly pull back on stock buybacks, the delicate balance that has allowed for the long bull market will be threatened.

The Closing
In summary,  the primary threats to stocks at the start of 2017, whether you look at implied equity risk premiums or PE ratios, come from two sources. The first is that interest rates will rise quickly, without a concurrent increase in earnings, and the second is that companies will  scale back the cash they return to stockholders to get back to a sustainable payout. Is there a reasonable probability that these events could occur? Of course, and if they both do, it will be a bad year for stocks. However, there is almost equal likelihood that as interest rates rise, earnings will rise even more (partly because of higher inflation/growth and partly because of cuts in corporate taxes) and that companies are able to sustain or even augment cash returned to stockholders. If this scenario unfolds, it will be a very good year for stocks. I will predict that you will be hearing from absolutists on both sides of this argument, one side preaching gloom and doom and the other predicting a market surge. I am in awe of the conviction that each side has in its market-timing judgment, but I am afraid that my market crystal ball is much too cloudy for me to make strong market predictions. So, I will do what I have always done, invest in individual stocks that I find to be priced right and accept that I have little or no control over the market.

YouTube Video

  1. Historical Returns on Stocks, T.Bond and T.Bills from 1928 to 2016
  2. Implied Equity Risk Premium - January 2017 (Calculation Spreadsheet)
  3. Historical Implied Equity Risk Premiums - 1960 to 2016 
  4. T.Bond Rate - Actual versus Implied from 1954-2016
  5. PE, CAPE, Shiller PE and Bond PE from 1954-2016

Thursday, January 12, 2017

Almost time for class: My Line Up for the Spring Semester!

If you have been reading my blog for awhile, you should be familiar with the routine at the start of every semester. If I am teaching that semester, I list the classes that I will be teaching, describe them briefly and offer ways in which you can follow the classes online, if you are so inclined. This semester is shaping up to be a busy one, with an MBA Corporate Finance class leading the list, followed by an undergraduate Valuation class and closing with a new online valuation certificate class that will be offered by the Stern School of Business.

Corporate Finance
The most important class that I teach is corporate finance, not valuation. Put simply, this class (or at least the version that I subscribe to) is about the first financial principles that govern how to run a business, small or large, private or public and in any market. That sounds like an ambitious agenda but it makes for a fascinating class, where we break down everything that a business does into three categories: investing, financing and dividend decisions. At the risk of summarizing the entire class into a single picture, these are the questions that corporate finance tries to answer:

For a business to be successful, it has to find a singular objective and then make investment, financing and dividend decisions that advance that objective. We start the class by debating what that objective should be and then move into the investment principle, first looking at how best to estimate the hurdle rates (the threshold for a good investment) in a business and then then at measuring the returns on prospective or actual investments. We follow up by discussing whether there is a right mix of debt and equity to use in funding a business as well as the right type of financing (long term or short term, floating or fixed, straight or convertible, currency) for that business. We finish with a discussion of how much cash should be returned to investors in a business in the form of dividends or buybacks, why a business may prefer one form of cash return over another and how much cash (balance) is too much cash. We end the class by bringing all of these principles together in the value of a business, setting up for my next class (Valuation).

The first session will be on January 30, 2017, and we will meet every Monday and Wednesday from 10.30-12 until May 8. While you have to be enrolled in the class as a Stern MBA to attend the class physically, you are welcome to follow the class online in one of three forums. In each of these forums, I will post recorded webcasts of the lectures late on Mondays and Wednesdays, with links lecture notes and other material. I will also post the quizzes and exams that I will be giving in class online, with grading templates that you can use to grade yourself.
  1. My website: The primary platform for my class is on the webpage for the class on my website. A one-page listing of the webcasts and other materials can be found at this link. You can watch the streaming videos or download them and also the slides and other links for each class. You can indulge your voyeuristic instincts by reading the emails I send to the class at this link.
  2. Apple iTunes U: If you prefer a more polished and device-friendly platform and you own an Apple device (iPhone or iPad), you should download the iTunes U app from the store and once you have it installed, try entering the code " EXC-JJS-XEA", and the class should show up on your shelf. (If it does not, try this link instead.) As I post the lectures and other material on the site, you should get a notification (if you want) about the posting. If you have an Android device, you have to download the Tunesviewer app to be able to access iTunes U classes. 
  3. YouTube: If you want a more minimalist set up, with limited demands on broadband, you can use YouTube and check out the playlist for the class. Again, as classes get posted, you should see them show on the playlist.
This is a class that I teach almost every semester to the MBAs and this semester, I will be teaching it to undergraduates. That said, I teach exactly the same class to both and this class follows the same structure as my MBA classes. It is a class about attaching a number to an asset or business and we will look at both intrinsic valuation and pricing of both public and private firms. 

Since I provided a much longer introduction when I wrote about my Fall 2016 class, you can read it full at this link. The first session for this class will be January 23, and as with the corporate finance class, you can follow the class online, in one of three ways:
  1. My website: The primary platform for my class is on the webpage for the class on my website. A one-page listing of the webcasts and other materials can be found at this link
  2. Apple iTunes U: If you download the iTunes U app from the store to your Apple device, you can enter the code "FHS-KWW-FPK" for the class. If you prefer a direct link, try this one.
  3. YouTube: You can use YouTube and check out the playlist for the class. As classes get posted, you should see them show on the playlist.
Valuation Certificate
These postings, listing upcoming classes and offering them online, have been a ritual of mine for more than 20 years and one common query I get is whether I can offer certification. My answer, hitherto, has been no, not only because I have no way of testing or grading what you do or providing feedback. This semester, the Stern School of Business has decided to offer an online version of my class as Valuation certification class, with the following features:
  1. Lectures: The class is built around twenty eight lecture sessions, each of which is about 12-20 minutes long. These sessions were recorded in a studio and should much more professional than the online videos that I make and more watchable than my full-length classes.
  2. Timing: The class is scheduled to begin on January 30 and go through mid-May, requiring that you watch about two sessions a week. Each session will come with self-test assessment, practice problems, additional readings and other material to supplement learnings.
  3. Synchronous sessions: Every two weeks, I will use WebEx for a live Q&A session, where you can ask questions about the four sessions from the prior two weeks.
  4. Discussion Boards: If you are enrolled in the class, you will be able to participate in discussion boards organized by valuation topics, posting comments, questions or other links. A teaching assistant will monitor the boards and add to the discussion, if needed.
  5. Quizzes and Exams: Just as in my regular classes, there will quizzes and exams. You will be able to take these exams online and I will grade them. 
  6. Valuation Project: As in my regular class, each person in the certificate program will be both valuing and pricing a company and I will provide mid-semester feedback on the valuation and a final grade assessment at the end of the semester.
There is bad news and good news with this new offering. The first piece of bad news is that it is not free and you have to decide, for yourself, whether the price charged ($425) is worth the experience (and the certificate). The second is that this is Stern's first try at this type of offering; it will have a few hiccups and the number of students will be capped at fifty. If you are interested, you can find out more about the certificate program at this link and even if you are unable to participate or get into the class this semester, it will be offered again to a larger audience, later in the year. The good news, if you decide to be part of the program is that I will treat you like I treat my regular in-class students. I am not sure that even this is good news, since you will hear from me about once every day and you will be sick and tired of me by May 12.

YouTube Video: Valuation Certificate Class Preview

  1. Corporate Finance (MBA):  (a) My website (b) Apple iTunes U (c) YouTube Playlist
  2. Valuation (Undergraduate):  (a) My website (b) Apple iTunes U (c) YouTube Playlist
  3. Stern Valuation Certificate: Stern entry webpage

Wednesday, January 11, 2017

Narrative and Numbers: How a number cruncher learned to tell stories!

When I taught my first valuation class in 1986 at New York University, I taught it with numbers, with barely a mention of stories. It was only with the passage of time that I realized that my valuations were becoming number-crunching exercises, with little holding them together other than historical data and equations. Worse, I had no faith in my own valuations, recognizing how easily I could move my final value by changing a number here and a number there. It was then that I realized that I needed a story to connect the numbers and that I was not comfortable with story telling, and that realization led me to start working on my narrative skills. While I am still a novice at it, I think that I have become a little better at story telling than I used to be and it is this journey that is at the core of my newest book, Narrative and Numbers: The Value of Stories in Business.

Story versus Numbers
What comes more naturally to you, story telling or number crunching? That is the question that I start every valuation class that I teach and my reasons are simple. In a world where we are encouraged to make choices early and specialize, we unsurprisingly play to our strengths and ignore our weaknesses. I see a world increasingly divided between number crunchers, who have abandoned common sense and intuition in pursuit of data analytics and complex models and story tellers, whose soaring narratives are unbounded by reality. Each side is suspicious of the other, the story tellers convinced that numbers are being used to intimidate them and the number crunchers secure in their belief that they are being told fairy tales. It is a pity, since there is not only much that each can learn from the other, but you need skills in investing and valuation. I think of valuation as a bridge between stories and numbers, where every story becomes a number in the valuation and every number in a valuation has a story behind it.

When I introduce this picture in my first class, my students are skeptical, as they should be, viewing it as an abstraction, but I try to make it real, the only way I can, which is by applying it on real companies. I start every valuation that I do in class with a story and try to connect my numbers to that story and I try to be open about how much I struggle to come up with stories for some companies and have much my story has to change to reflect new facts or data with others. I push my students to work on their weaker sides when they do valuations, trying  asking story tellers to pay more heed to the numbers and beseeching number crunchers to work on their stories. Seeking a larger audience, I have not only posted many times on the process but almost every valuation that I have posted on this blog has been as much about the story that I am telling about the company as it is about the numbers. In fact, having written and talked often about the topic, I thought it made sense to bring it all together in a book, Narrative and Numbers, published by Columbia University Press, and available at bookstores near you now (and on Amazon in both physical and Kindle versions). (Update: The hardcover is not available yet outside the United States, but should be accessible in about 4-6 weeks. The Kindle version is available everywhere.)

From Story to Value: The Sequence
So, how does a story become a valuation? This book is built around a sequence that has worked for me, in five steps, starting with a story, putting the story through a reality check, converting the story into a valuation and then leaving the feedback loop open (where you listen to those who disagree with you the most and try to improve your story).
There is no rocket science in any of these steps and I am sure that this is not the only pathway to converting narrative to value. These steps have worked for me and I use four companies as my lead players to illustrate the process.
  1. Uber, the ride-sharing phenomenon: I start with the story that I told about Uber in June 2014, and the resulting value, and how that story evolved over the next 15 months as I learned more about the company and its market/competition changed.
  2. Amazon, the Field of Dreams Company: Amazon is a story stock that seems to defy the numbers laws and I use it to illustrate how the value for Amazon can vary as a function of the story you tell about it.
  3. Alibaba, the China story: The China big market story has been used to justify the valuations of many companies, but Alibaba is one case where the use of that story is actually merited. In my story, Alibaba continues to dominate the growing Chinese online retail market and my value reflects that, but I also look at how that value will change if Alibaba can replicate its success globally (Alibaba, the Global Story).
  4. Ferrari, the Exclusive Club: I value Ferrari as an exclusive club, leading into its IPO, and explore how that value will change if you assume that it will follow a different business model.
In the later chapters, I bring in other familiar names (at least to those who read my blog), Vale to illustrate how macroeconomic factors affect stories and Yahoo! to examine the effect of the corporate life cycle. In the final part of the book, I turn the focus on management and look at how the story telling skills of top managers can make a significant difference in how a young company is perceived and valued by the market and how that skill set has to shift as the company ages.

Personal, Applied and Live!
This is my tenth book and I have never had more fun writing a book. There are three aspects to this book that I hope come through:
  1. It is a personal book: If you read the book, you will notice that rather than use the formal "we" or "you" through much of the book, I talk about "I" and "my". Before you decide that this is a sign of an ego run wild, I did this because this book is about my journey from an unquestioning trust in numbers to an increasing focus on stories in valuation and my stories about the companies that I value in this book. I don't expect you to buy into my stories. In fact, I hope that you disagree with me and tell your own stories and that this book will help you convert those stories into valuations. 
  2. It is applied: One common theme across all my books is that I believe that financial tools are best illustrated with real companies in real time. That is the reason that I not only chose real companies as my illustrative examples, but companies that many of you will have strong views (positive or negative) about. 
  3. It is live:  The most exciting part of this book, for me, is that is is never going to be complete. The companies that I use in the book are dynamic entities and I am sure that the stories that I have told about them will change, shift and perhaps even break over time. Rather than dread these upcoming changes, I view them as opportunities for me to revisit my stories and valuations and to update them. You will see these updates on this blog but you will also be able to find them at the website for the book, where I also have pulled together YouTube videos and other material relevant to the book.
I am usually too embarrassed to ask people to buy my books, since many of them are obscenely over priced, one reason that I don't require them even for students in my classes. I feel no such qualms about this book, since it is (I think) priced reasonably and I hope it offers good value for the money. I hope that you will read the book and that that you enjoy it, and if you can learn something that helps you improve your valuation skills, I will view that as icing on the cake. Drawing on one of the themes in the book, where I argue that the key to keep the feedback loop open, I would also like to hear from those of you who don't like the book and what I can do better! I'll try!

YouTube Video

Book Links

Monday, January 9, 2017

January 2017 Data Update 1: The Promise and Perils of "Big Data"!

Each year, for the last 25 years, I have spent the first week playing Moneyball, with financial data. I gather accounting and market data on all publicly traded companies, listed globally, and then try to extract whatever lessons that I can from the data, to use in investing, corporate finance and valuation for the rest of the year. I report the data, classified by industry group and by country, on my website, in the hope that others might find it useful. While, like last year, I will be summarizing what I see in the data in a series of posts over the rest of January, I decided to use this one to both provide some perspective and cautionary notes not only on my data but on numbers, in general.

The Number Cruncher's Delusions
In an earlier post on narrative and numbers, I confessed that I am more naturally a number cruncher than a story teller and that I have learned through experience that focusing entirely on the numbers can lead you astray in valuation and investing. In fact, as you read my posts on what the numbers look like at the start of 2017, it is also worth noting that I am, like all number crunchers, susceptible to three delusions about data:
  1. Numbers are precise: I say, only half jokingly, that when a number cruncher is in doubt, his or her reaction is to add more decimals, in the hope that making a number look more precise will make it so. The truth is that numbers are only as precise as the process that delivers them and in business, that makes them imprecise. Thus, when you peruse the returns on capital or costs of capital that I will be estimating and reporting for both companies and industry groups, please do recognize that the former is an accounting number, where discretionary choices on expensing and depreciation can translate into big changes in returns on capital, and the latter is market number, making it not only a moving target (as interest rates and risk premiums change) but also a function of my estimation choices as well as estimation error in estimating risk premiums and risk parameters. 
  2. Numbers are objective: One of the resentments that number crunchers have about story tellers is that the latter indulge in flights of fancy and are unashamed about bringing their biases into their stories and through them into pricing and investing. The problem, though, is that numbers can be just as biased as stories, with the caveat that it is easier to hide biases with numbers. To give one example, one of the datasets that I will be updating has tax rates paid by US companies in 2016 and I provide three measures of effective tax rates, ranging from a simple average of effective tax rates across all companies in a sector, yielding the lowest values, to a weighted average effective tax rate that is computed only across money-making firms, which yields much higher values. If you are dead-set on making a case that US companies don't pay their fair share in taxes, you will report only the first number and not mention the rest, whereas if you want to show that US companies pay their fair share and more in taxes, you will go with the latter. It is for this reason that I will not claim to be unbiased (since no one is) but I will try to provide multiple measures of widely used variables and leave it to you to decide which one best fits your preconceptions. 
  3. Numbers put you in control: It is human nature to try to be in control and numbers serve us well, in that pursuit. As in other aspects of life, we seem to think that attaching a number to a volatile or uncontrollable variable brings it under control. So, at the risk of stating the obvious, let me say that measuring your return on invested capital is not going to turn bad projects into good ones, just as estimating your interest coverage ratio is not going to make it easier for you to make your interest payments. 
Don't get me wrong! I remain, at heart, a number cruncher but I have a more complicated, and healthier, relationship with data than I used to have. My faith in data has been tempered by my experiences with data, and especially so with the ease with which I have seen it bent to reflect the agenda of the user. I trust numbers, but only after I verify them, and I hope that you will do the same with the data that you find on my site.

A Big Data Skeptic
It is my experience with data that make me skeptical about two of the hottest concepts in business, big data and data analytics, at least as a basis for making money. It is true that companies are collecting more data than ever before on almost every aspect of our lives, with the intent of using that data to make more money off us. In a capitalist society, I remain doubtful that big data will be monetized, for three reasons.
  1. Data is not information: Not all data is created equal. Data that is based on what you do is worth a lot more than what you say will do; a tweet that you are bullish on Apple, Twitter or the entire market is less useful data than a record of you buying Apple, Twitter or the entire market. This is a point worth remembering as the rush is on to incorporate social media data (from Twitter and Facebook) with financial data to create super data bases. In addition, as we collect and store more data, it is worth noting that data is not information. In fact, if data analytics does its job, converting data to information will remain its focus, rather than generating neat looking graphs and obscure statistics. 
  2. If everyone has it (data), no one has it: For data to have value, you have to some degree of exclusivity in access to that data or a proprietary edge on processing that data. It is one of the reasons that investors have been unable, for the most part, to convert increased access to financial data into investing profits.
  3. Not all data is actionable: , To convert that data to profits, you need to be able to find a way to monetize whatever data edge you have acquired. For companies that offer products and services, this will take the form of modifying existing products/services or coming up with new products/services to what you have learned from the data.
As you look at these three factors, it is easy to see why Netflix and Amazon have become illustrative examples for the benefits of big data. They get to observe us (as consumers) in action, Amazon watching what we buy and Netflix observing what we watch on our devices, and that information is not only proprietary but can be used to not only modify product offerings but to also nudge us to act in ways that will be beneficial to the companies. By the same token, you can also see why using big data as an investing advantage will, at best, provide a transitory advantage, and why I feel no qualms about sharing my data. 

Data Details
If you choose to use any of my data, it behooves me to take you through the process by which I collect and analyze the data and offer some cautionary notes along the way. 
  1. Raw Data: The first step in the process is collecting the raw data and I am deeply thankful to the data services that allow me to do this. I use S&P Capital IQ, Bloomberg and a host of specialized services (Moody's, PRS etc.). For company-specific data, the only criteria that I use for including a company is that it has to have a non-zero market capitalization, yielding a total of 42678 firms on January 1, 2017. The data collected is as of January 1, 2017, with market data (stock prices, market capitalization and interest rates) being as of that data but accounting data reflecting the most recent twelve months (which would be through September 30, 2016 for calendar year companies). 
  2. Classification: I classify these companies first by geographic group into five groups - the United States, Japan, Developed Europe (including the EU and Switzerland), Emerging Markets (including Eastern Europe, Asia, Africa and Latin America) and Australia/New Zealand/Canada, a somewhat arbitrary grouping that I am stuck with because of history.
    I also classify firms into 96 industry groups, built loosely on raw service industrial grouping and SIC codes. The number of firms in each industry group, broken down further by geographic grouping, can be found at this link and you can find the companies in each industry grouping at this link.
  3. Key numbers: I generally don't report much macroeconomic data (interest rates, inflation, GDP growth etc.), since there are much better sources for the data, with my favorite remaining FRED (the Federal Reserve data site in St. Louis). I update equity risk premiums not only for the US but for much of the world at the start of every year and will update them again in July 2017. Using the company data, I report on dozens of metrics at the industry group and geographic levels on profitability, cost of capital, relative risk and valuation ratios and you can find the entire listing here.
  4. Computational details: One of the lessons that I have learned from wrestling with the data is that computing even simple statistics requires making choices, which, in turn, can be affected by your biases. Just to provide an example, to compute the PE ratio for US steel companies, I can take a simple average of the PE ratios of companies but that will not only weight tiny companies and very large companies equally but will also eliminate any companies that have negative earnings from my sample (causing bias in my estimates). To eliminate this problem, for most of the industry average statistics, I aggregate values across companies and then compute ratios. With the PE ratio for US steel companies, for instance, I aggregate the net income of all steel companies (including money-losing companies) and the market capitalizations for the same companies and then divide the former by the latter to get the PE ratio. Think of these averages then as weighted averages of all companies in each industry group, perhaps explaining why my numbers may be different from those reported by other services. 
  5. Reporting: I have wrestled with how best to report this data, so that you can find what you are looking for easily. I have not found the perfect template, but here is how you will find the data. For the current data (from January 2017), go to this link. You will see the data classified into risk, profitability, capital structure and dividend policy measures, reflecting my corporate finance focus, and then into pricing groups (earnings multiples, book value multiples and revenue multiples). I also keep archived data from prior years (going back to 1999) at this link. Unfortunately, since I have had to switch raw data providers multiple times in the last 20 years, the data is not perfectly comparable over time, as both industry groupings and data measures change over time. 
  6. Usage: There are two ways you can get the data. For the US data, I have html versions that you can see on your browser. For all of the data, I have excel spreadsheets that you can download for the data. I would strongly encourage you to use the latter rather than the former, since you can then manipulate and work with the data. If you have questions about any of the variables and how exactly I define them, try this link, where I summarize my computational details
In Closing
I am a one-man operation and I am sure that there are datasets that I have not updated or where you find missing pieces. If you find any of these, please let me know, and I will try to fix them. I also don't see myself as a raw data provider, especially on a real-time basis and on individual companies. So, I don't plan to update this data over the course of the year, partly because industry averages should not have dramatic changes over a few months and partly because I have other stuff that I would rather do.

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Data Links
  1. Current Data on my website
  2. Archived Data on my website
Data 2017 Posts
  1. Data Update 1: The Promise and Perils of Big Data
  2. Data Update 2: US Stocks at the start of 2017
  3. Data Update 3: Of Interest Rates and Currencies - January 2017
  4. Data Update 4: Country Risk and Pricing, January 2017
  5. Data Update 5: Death and Taxes in January 2017- Changes Coming?
  6. Data Update 6: The Cost of Capital in January 2017
  7. Data Update 7: Profitability, Excess Returns and Corporate Governance- January 2017
  8. Data Update 8: The Debt Trade off in January 2017
  9. Data Update 9: Dividends and Buybacks in 2017
  10. Data Update 10: A Pricing Update in January 2017

Wednesday, December 28, 2016

Active Investing: Seeking the Elusive Edge!

In my last post, I pointed to the shift towards passive investing that has accelerated over the last decade and argued that much of that shift can be explained by the sub-par performance of active investors. I ended the post on a contradictory note by explaining why I remained an active investor, though the reasons I gave were more personal than professional. I was taken to task on two fronts. The first was that I should have spent less time describing the problem (poor performance of active investors) and more time diagnosing the problem (the reasons for that poor performance). The second was that my rationale for being an active investor, i.e., that I enjoyed investing enough that I would be okay not earning excess returns, could never be used if I sought to manage other people's money and that a defense of active investing would have to be based on something more substantial. Both are fair critiques and I hope to address them in this post.

The Roots of the Active Investing Malaise
There is no denying the facts. Active investing has a problem not only because it collectively under performs passive investing (which is a mathematical given) but also because the drag on returns (from transactions costs costs and management fees) seems to be getting worse over time.  Even those few strands of active investing that historically have outperformed the market have come under siege in the last decade. While there are many reasons that you can point to for this phenomenon, here are some that I would highlight:
  1. A "Flatter" Investment Word: The investment world is getting flatter, as the differences across active investors rapidly dissipate. From information to processing models to trading platforms, professionals at the active investing game (including mutual funds and hedge funds) and individual investors are on a much more even playing field than ever before. As an individual investor, I have access to much of the information that an analyst working at Merrill Lynch or Fidelity has, whether it be financial statements or market rumors. I am not naive enough to believe that, SEC rules against selective information disclosure notwithstanding,  there are no channels for analysts to get "inside" information but much of that information is either too biased or too noisy to be useful. I have almost as much processing power on my personal computer as these analysts do on theirs and can perhaps even put it to better use. In fact, the only area where institutions (or at least some of them) may have an advantage over me is in being able to access information on trading data in real time and investing instantaneously and in large quantities on that information, leading to breast beating about the unfairness of it all. If history is any guide, the returns to these strategies fade quickly, as other large players with just as much trading power are drawn into the game. In fact, while much ink was spilt on flash trading and how it has put those who cannot partake at a disadvantage, it is worth noting that the returns to flash trading, while lucrative at first, have faded, while attracting smaller players into the game. In summary, if the edge that institutional active investors have had over individual active investors was rooted in information and processing power, it has almost disappeared in the United States and has eroded in much of the rest of the world.
  2. No Core Philosophy: There is an old saying that if you don't stand for something, you will fall for anything, and it applies to much of active investing. Successful investing starts with an investment philosophy, a set of core beliefs about market behavior that give birth to investment strategies. Too many active investors, when asked to characterize their investment philosophies, will describe themselves as "value investors" (the most mushy of all investment descriptions, since it can mean almost anything you want it to mean), "just like Warren Buffett" (a give away of lack of authenticity) or "investors in low PE stocks" (confusing an investment strategy with a philosophy). The absence of a core philosophy has two predictable consequences: (a) a lack of consistency, where active investors veer from one strategy to another, often drawn to whatever strategy worked best during the last time period and (b) me-tooism, as they chase momentum stocks to keep up with the rest. The evidence for both can be seen in the graph below, which looks at the percentages of funds in each style group who remain in that group three and five years later and finds that about half of all US funds change styles within the next five years.
    Source: SPIVA
  3. Bloated Cost Structures: If there is a core lesson that comes from looking at the performance of active investors, it is that the larger the drag on returns from the costs of being active, the more difficult it is to beat passive counterparts. One component of these costs is trading costs, and the absence of a core investment philosophy, referenced above, leads to more trading/turnover, as fund managers undo entire portfolios and redo them to match their latest active investing avatars. Another is the overhead cost of maintaining an active investing infrastructure that was built for a different market in a different era. The third cost is that of active management fees, set at levels that are not justified by either the services provided or by the returns delivered by that management team. Active money managers are feeling the pressure to cut costs, as can be seen in expense ratios declining over time, and the fund flows away from active money managers has been greatest at highest cost funds. I can only speak for myself but there is not one active investor (nope, not even him, and not even if he was forty years younger) in the world that I have enough reverence for that I would pay 2% (or even .5%) of my portfolio and 20% (or 5%) of my excess returns every year, no matter what his or her track record may be. To those who would counter that this is the price you have to pay for smart money, my response is that the smart money does not stay smart for very long, as evidenced by how quickly hedge fund returns have come back to earth. 
  4. Career Protection: Active money managers are human and it should come as no surprise  that they act in ways that increase their compensation and reduce their chances of losing their jobs. First, to the extent that their income is a function of assets under management (AUM), it is very difficult, if not impossible, to fight the urge to scale up a strategy to accommodate new inflows, even if it is not scaleable. Second, if you are a money manager running an established fund, it is far less risky (from a career perspective) to adopt a strategy of sustained, low-level mediocrity than one that tries to beat the market by substantial amounts, with the always present chance that you could end up failing badly. In institutional investing, this has led some of the largest funds to quasi-index, where their holdings deviate only mildly from the index, with predictable results: these funds deliver returns that match the index, prior to transactions costs, and systematically under perform true index funds, after transactions costs, but not by enough for managers to be fired. Third, at the other end of the spectrum, if you are a small, active money manager trying to make a name for yourself, you will naturally be drawn to high-risk, high-payoff strategies, even if they are bad bets on an expected value basis. In effect, you are treating investing as a lottery, where if you win, more money will flow into your funds and if you do not, it is other people's money anyway.
There are macroeconomic factors that may also explain why active investing has had more trouble  in the last decade, but it is not low interest rates or central banks that are the culprits. It is that the global economy is going through a structural shift, where the old order (with a clear line of demarcation between developed & emerging markets) is being replaced with a new one (with new power centers and shifting risks), upending historical relationships and patterns. Given how much of active money management is built on mean reversion and lessons learned by poring over US market data from the last century, it should come as no surprise that the payoff to screening stocks (for low PE ratios or high dividend yield) or following rigid investing rules (whether they be centered on CAPE or interest rates) has declined.  In all of this discussion, I have focused on the faults of active institutional investors, be they hedge funds or mutual funds, but I believe that their clients bear just as much responsibility for the state of affairs. They (clients) let greed override good sense (knowing that those past returns are too good to be true, but not asking questions), claim to be long term (while demanding to see positive performance every three months), complain about quasi indexing (while using tracking error to make sure that deviations from the index get punished) and refuse to take responsibility for their own financial affairs (blaming their financial advisors for all that goes bad). In effect, clients get the active money managers they deserve.

A Pathway to Active Investing Success
If you accept even some of my explanation of why active investing is failing, at least collectively, there is a kernel of good news in that description. Specifically, the pathway to being a successful active investor lies in exploiting the weakness of the active investment community, especially large institutional investors. Here are my ingredients for active investing success, though I will add the necessary caveat that having all these ingredients will not guarantee an investment payoff.
  1. Have a core investment philosophy: In my book on investment philosophies, I argued that there is no best investment philosophy that fits all investors. The best investment philosophy for you is the one that best fits you as an investor, in sync not only with your views about markets but with your personal makeup (in terms of patience, liquidity needs and skill sets). Thus, if you have a long time horizon, believe that value is grounded in fundamentals and  that markets under estimate the value of assets in place, old-time value investing may very well be your best choice. In contrast, if your time horizon is short, believe that momentum, not value, drives stock prices, your investment philosophy may be built around technical analysis, centered on gauging price momentum and shifts in it.
  2. Balance faith with feedback: In a post on Valeant, I argued that investing requires balancing faith with feedback, faith in your core market beliefs with enough of an acceptance that you can be wrong on the details, to allow for feedback that can modify your investing decisions. In practice, walking this tightrope is exceedingly difficult to do, as many investors sacrifice one at the expense of the other. At one extreme, you have investors whose faith is so absolute that there is no room for feedback and positions once taken can never be reversed. At the other extreme, you have investors who  have no faith and whose decisions change constantly, as they observe market prices.   
  3. Find your investing edge: It has always been my contention that you have to bring something uncommon to the investment table to be able to take something away. Drawing on the language of competitive advantages and moats, what sets you apart does not have to be unique but it does have to be scarce and not easily replicable. That is why I am unmoved by talk of big data in investing and the coming onslaught of successful quant strategies, unless that big data comes with exclusivity (you and only you can exploit it). Here are four potential edges (and I am sure that there others that I might be missing): (a) In sync with client(s): I was not being facetious when I argued that one of my big advantages as an investor is that I invest my own money and hence have a freedom that most active institutional investors cannot have. If you are managing other peoples money, this suggests that your most consequential decision will be the screening your clients, turning money away from those who are not suited to your investment philosophy (b) Sell Liquidity: To be able to sell liquidity to investors seeking it, especially in the midst of a crisis, is perhaps one of investing's few remaining solid bets. That is possible, though, only if you, as an investor, value liquidity less than the rest of the market, a function of both your financial security.  (c) Tax Play: Investor price assets to generate after-tax returns and that effectively implies that assets that generate high-tax income (dividends, for instance) will be priced lower than assets that generate low-tax or no-tax income. If you are an investor with a different tax profile, paying either no or low taxes, you will be able to capture some of the return differential. Before you dismiss this as impossible or illegal, recognize that there is a portion of each of our portfolios, perhaps in IRAs or pension funds, where we are taxed differently and may be able to use it to our advantage. (d) Big Picture Perspective: As we become a world of specialists, each engrossed in his or her corner of the investment universe, there is an opening for "big picture" investors, those who can see the forest for the trees and retain perspective by looking across markets and across time. 
If you are considering actively investing your money, you should be clear about what your own investment philosophy is, and why you hold on to it, and identify the scarce resource that you are bringing to the investment table. If you are considering paying someone else to actively manage your money, my suggestion is that while you should consider that person's track record, it is even more critical that you examine whether that track record is grounded in a consistent investment philosophy and backed up by a sustainable edge. 
There is much that I still do not know about investing but here are the lessons that I learn, unlearn and relearn every day. First, an investment cannot be a sure-bet and risky at the same time, and you can count me among the skeptical when presented with the next easy way of beating the market. Second, when I believe that I own the high ground in any investment debate, it is a sure sign that I have let hubris get the better of me and that my arguments are far weaker than I think they are. Third, much as I hate to be wrong on my investment choices,  I learn more when I concede that "I am wrong" than when I contend that "I am right".  For now, I will continue to invest actively, holding true to my investment philosophy centered on intrinsic value, while nurturing the small edges that I have over institutional investors. 

Wednesday, December 14, 2016

Active Investing: Rest in Peace or Resurgent Force?

I was a doctoral student at UCLA, in 1983 and 1984, when I was assigned to be research assistant to  Professor Eugene Fama, who wisely abandoned the University of Chicago during the cold winters for the beaches and tennis courts of Southern California. Professor Fama won the Nobel Prize for Economics in 2013, primarily for laying the foundations for efficient markets in this paper and refining them in his work in the decades after. The debate between passive and active investing that he and others at the University of Chicago initiated has been part of the landscape for more than four decades, with passionate advocates on both sides, but even the most ardent promoters of active investing have to admit that passive investing is winning the battle. In fact, the mutual fund industry seems to have realized that they face an existential threat not just to their growth but to their very existence and many of them are responding by cutting fees and offering passive investment choices.

Passive Investing is winning!
When Jack Bogle started the Vanguard 500 Index fund in 1975, I am sure that even he could not have foreseen how successful it would become in changing the way we invest. Not only have index funds become an increasing part of the landscape, but exchange traded funds have also added to the passive investing mix and index-based investing has expanded well beyond the S&P 500 to cover almost every traded asset market in the world. Today, you can put together a portfolio composed of index funds and ETFs to create any market exposure that you want in stocks, bonds or commodities. The growth of passive investing can be seen in the graph below, where I plot the proportion of the US equity market held by passive investors (in the form of ETFs and index funds) and active investors from 2005 to 2016:
Source: Morningstar
In 2016, passive investing accounted for approximately 40% of all institutional money in the equity market, more than doubling its share since 2005. Since 2008, the flight away from active investing has accelerated and the fund flows to active and passive investing during the last decade tell the story.
The question is no longer whether passive investing is growing but how quickly and at what expense to active investing. The answer will have profound consequences not only for our investment choices going forward, but also for the many employed, from portfolio managers to sales people to financial advisors, in the active investing business. 

Aided and Abetted by Active Investing
To understand the shift to passive investing and why it has accelerated in recent years, we have to look no further than the investment reports that millions of investors get each year from their brokerage houses or financial advisors, chronicling the damage done to their portfolios during the course of the year by frenetic activity. Put bluntly, investors are more aware than ever before that they are often paying active money managers to lose money for them and that they now have the option to do something about this disservice.

1. Collectively, active investing cannot beat passive investing (ever)!
Before you attack me for being a dyed-in-the-wool efficient marketer, there is a simple mathematical reason why this statement has to be true. During 2015, for instance, about 40% of institutional money in equities was invested in index funds and ETFs and about 60% in active investing of all types. The money invested in index funds and ETFs will track the index, with a very small percentage (about 0.11%) going to cover the minimal transactions costs. Thus, active money managers have to start off with the recognition that they collectively cannot beat the index and that their costs (transactions and management fees) will have to come out of the index returns. Not surprisingly, therefore, active investors will collectively generate less than the index during every period and more than half of them will usually underperform the index.  To back up the first statement, here are the median returns for all actively managed funds, relative to passive index funds for various time periods ending in 2015:
Source: S&P (SPIVA)
The median active equity fund manager underperformed the index by about 1.21% a year between 2006 and 2015 and by far larger amounts over one-year (-2.92%), three year (-2.78%) and five year (-2.90%). Thus, it should come as no surprise that well over half of all active fund managers have been outperformed by the index over different time periods:
Note that in this graph, active fund managers in equity, bond and real estate all under perform their passive counterparts, suggesting that poor performance is not restricted just to equity markets.

If active money managers cannot beat the market, by construct, how do you explain the few studies  that claims to find that they do? There are three possibilities. The first is that they look at subsets of active investors (perhaps hedge funds or professional money managers) rather than all active investors and find that these subsets win, at the expense of other subsets of active investors. The second is that they compare the returns generated by mutual funds to the return on a stock index during the period, a comparison that will yield the not-surprising result that active money managers, who tend to hold some of their portfolios in cash, earn higher returns than the index in down markets, entirely because of their cash holdings. You can perhaps use this as evidence that mutual fund managers are good at market timing, but only if they can generate excess returns over long periods. The third is that these studies are comparing returns earned by active investors to a market index that might not reflect the investment choices made by the investors. Thus, comparing small cap active investors to the S&P 500 or global investors to the MSCI may reveal more about the limitations of the index than it does about active investing. 

2. No sub-group of active investors seems to be able to beat the market
The standard defense that most active investors would offer to the critique that they collectively underperform the market is that the collective includes a lot of sub-standard active investors. I have spent a lifetime talking to active investors who contend that the group (hedge funds, value investors, Buffett followers) that they belong to is not part of the collective and that it is the other, less enlightened groups that are responsible for the sorry state of active investing. In fact, they are quick to point to evidence often unearthed by academics looking at past data that stocks with specific characteristics (low PE, low Price to book, high dividend yield or price/earnings momentum) have beaten the market (by generating returns higher than what you would expect on a risk-adjusted basis). Even if you conclude that these findings are right, and they are debatable, you cannot use them to defend active investing, since you can create passive investing vehicles (index funds of just low PE stocks or PBV stocks) that will deliver those excess returns at minimal costs. The question then becomes whether active investing with any investment style beats a passive counterpart with the same style. SPIVA, S&P’s excellent data service for chronicling the successes and failures of active investing, looks at the excess returns and the percent of active investors who fail to beat the index, broken down by style sub-group. 
Source: S&P (SPIVA)
Note that not only is there not a single sub-group that has been able to beat the index for that group but also that the magnitude of under performance is staggering. It is true that these are the results for US equity fund managers, but just in case you are holding out hope that active money management is better at delivering results in other markets, the following table that looks at the percent of active managers who fail to beat indices in their markets should cast doubt on that claim:
Source: S&P (SPIVA)
There are glimmers of hope in the one-year returns in Europe and Japan and in the emerging markets, but there is not a single geography where active money managers have beaten the index over the last five years.

3. Consistent winners are rare
The third and final line of defense for active investors is that while they collectively underperform and that underperformance stretches across sub-groups, there is a subset of consistent winners who have found the magic ingredient for investment success. That last hope is dashed, though, when you look at the numbers. If there is consistent performance, you should see continuity in performance, with highly ranked funds staying highly ranked and poor performers staying poor. To see if that is the case, I looked at how portfolio managers ranked by quartile in one period did in the following three years:

Note that the numbers in the table, when you look at all US equity funds, suggest very little continuity in the process. In fact, the only number that is different from 25% (albeit only marginally significant on a statistical basis) is that transition from the first to the fourth quartile, with a higher incidence of movement across these two quartiles than any other two. That should not be surprising since managers who adopt the riskiest strategies will spend their time bouncing between the top and the bottom quartiles.

As your final defense of active investing, you may roll out a few legendary names, with Warren Buffett, Peter Lynch and the latest superstar manager in the news leading the list, but recognize that this is more an admission of the weakness of your argument than of its strength. In fact, successful though these investors have been, it becomes impossible to separate how much of their success has come from their investment philosophies, the periods of time when they operated and perhaps even luck. Again, drawing on the data, here is what Morningstar reports on the returns generated by their top mutual fund performer each year in the subsequent two years:
While the numbers in 2000 and 2001 look good, the years since have not been kind to super performers who return to earth quickly in the subsequent years. We could try to explain the failure of active investing to deliver consistent returns over time with lots of reasons, starting with the investment world getting flatter, as more investors have access to data and models but I will leave that for another post. Suffice to say, no matter what the reasons, active investing, as structured today, is an awful business, with little to show for all the resources that are poured into it. In fact, given how much value is destroyed in this business, the surprise is not that passive investing has encroached on its territory but that active investing stays standing as a viable business. 

The What next?
Since it is no longer debatable that passive investing is winning the battle for investor money, and for good reasons, the question then becomes what the consequences will be. The immediate effects are predictable and painful for active money managers. 
  1. The active investing business will shrink: The fees charged for active money management will continue to decline, as they try to hold on to their remaining customers, generally older and more set in their ways. Notwithstanding these fee cuts, active money managers will continue to lose market share to ETFs and index funds as it becomes easier and easier to trade these options. The business will collectively be less profitable and hire fewer people as analysts, portfolio managers and support staff. If the last few decades are any indication, there will be periods where active money management will look like it is mounting a comeback but those will be intermittent. 
  2. More disruption is coming: In a post on disruption, I noted that the businesses that are most ripe for disruption are ones where the business is big (in terms of dollars spent), the value added is small relative to the costs of running the business and where everyone involved (businesses and customers) is unhappy with the status quo. That description fits the active money management like a glove and it should come as no surprise that the next wave of disruption is coming from fintech companies that see opportunity in almost every facet of active money management, from financial advisory services to trading to portfolio management.
While active investing has contributed to its own downfall, there is a dark side to the growth of passive investing and many in the active money management community have been quick to point to some of these. 
  1. Corporate Governance: As ETFs and index funds increasing dominate the investment landscape, the question of who will bear the burden of corporate governance at companies has risen to the surface. After all, passive investors have no incentive to challenge incumbent management at individual companies nor the capacity to do so, given their vast number of holdings. As evidence, the critics of passive investors point to the fact that Vanguard and Blackrock vote with management more than 90% of the time. I would be more sympathetic to this argument if the big active mutual fund families had been shareholder advocates in the first place, but their track record of voting with management has historically been just as bad as that of the passive investors. 
  2. Information Efficiency: To the extent that active investors collect and process information, trying to find market mistakes, they play a role in keeping prices informative. This is the point that was being made, perhaps not artfully, by the Bernstein piece on how passive investing is worse than Marxism and will lead us to serfdom. I wish that they had fully digested the Grossman and Stiglitz paper that they quote, because the paper plays out this process to its logical limit. In summary, it concludes that if everyone believes that markets are efficient and invests accordingly (in index funds), markets would cease to be efficient because no one would be collecting information. Depressing, right? But Grossman and Stiglitz also used the key word (Impossibility) in the title, since as they noted, the process is self-correcting. If passive investing does grow to the point where prices are not informationally efficient, the payoff to active investing will rise to attract more of it. Rather than the Bataan death march to an arid information-free market monopolized by passive investing, what I see is a market where  active investing will ebb and flow over time.
  3. Product Markets: There are some who argue that the growth of passive investing is reducing product market competition, increasing prices for customers, and they give two reasons. The first is that passive investors steer their money to the largest market cap companies and as a consequence, these companies can only get bigger. The second is that when two or more large companies in a sector are owned mostly by the same passive investors (say Blackrock and Vanguard), it is suggested that they are more likely to collude to maximize the collective profits to the owners. As evidence, they point to studies of the banking and airline businesses, which seem to find a correlation between passive investing and higher prices for consumers. I am not persuaded or even convinced about either of these effects, since having a lot of passive investors does not seem to provide protection against the rapid meltdown of value that you still sometimes observe at large market cap companies and most management teams that I interact with are blissfully unaware of which institutional investors hold their shares.
The rise of passive investing is an existential threat to active investing but it is also an opportunity for the profession to look inward and think about the practices that have brought it into crisis. I think that a long over-due shakeup is coming to the active investing business but that there will be a subset of active investors who will come out of this shakeup as winners. As to what will make them winners, I have to hold off until another post.

Making it personal
Should you be an active investor or are you better off putting your money in index funds? The answer will depend on not only what you bring to the investment table in the resources but also on your personal make-up. I have long argued that there is no one investment philosophy that works for all investors but there is one that is just right for you, as an investor. In keeping with this philosophy of personalized investing, I think it behooves each of us, no matter how limited our investment experience, to try to address this question. To start this process, I will make the case for why I am an active investor, though I don’t think any you will or should care. I will begin by listing all the reasons that I will not give for investing actively. Since I use public information in financial statements and databases, my information is no better than anyone else’s. While my ego would like to push me towards believing that I can value companies better than others, that is a delusion that I gave up on a long time ago and it is one reason that I have always shared my valuation models with anyone who wants to use them. There is no secret ingredient or special sauce in them and anyone with a minimal modeling capacity, basic valuation knowledge and common sense can build similar models. 

So, why do I invest actively? First, I am lucky enough to be investing my own money, giving me a client who I understand and know. It is one of the strongest advantages that I have over a portfolio manager who manages other people’s money. Second, I have often described investing as an act of faith, faith in my capacity to value companies and faith that market prices will adjust to that value. I would like to believe that I have that faith, though it is constantly tested by adverse market movements. That said, I am not righteous, expecting to be rewarded for doing my homework or trusting in value. In fact, I have made peace with the possibility that at the end of my investing life, I could look back at the returns that I have made over my active investing lifetime and conclude that I could have done as well or better, investing in index funds. If that happens, I will not view the time that I spend analyzing and picking stocks as wasted since I have gained so much joy from the process. In short, if you don’t like markets and don’t enjoy the process of investing, my advice is that you put your money in index funds and spend your time on things that you truly enjoy doing!

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