Value Investing and Modern Finance Theory

Transcription

1 Value Investing and Modern Finance Theory Author: Matthew DePaola, Chief Investment Officer

2 Table of Contents Section 1: Introduction.1 Section 2: Origins of the Value Approach.3 Section 3: Origins of Modern Finance..10 Section 4: Value Investing and MFT Section 5: Conclusion..20

3 1. INTRODUCTION On May 17, 1984, Columbia University held a symposium in celebration of the 50 th anniversary of former professors Benjamin Graham and David Dodd s book Security Analysis. During the event professor Michael Jensen, then at the University of Rochester, was invited to provide a defense of the then (and still) reigning investment theory in academic finance, known as the efficient market hypothesis (EMH). The EMH states that all available information is incorporated into a stock s price, making it nearly impossible to generate superior long-term investment results. Proponents of the EMH, including Jensen, recognize that a few investors have beaten the market but attribute this success to random chance. During his speech, Jensen suggested that the same outcome could be achieved during a random exercise, such as coin flipping: If I survey a field of untalented analysts all of whom are doing nothing but flipping coins, I expect to see some who have tossed two heads in a row and even some who have tossed ten heads in a row (Lowenstein 2008, 317). Warren Buffett, then and now the most famous Graham and Dodd disciple, provided the rebuttal to Jensen s argument. Buffett suggested that if a coin flipping contest were held among the roughly 225 million people in the U.S. (roughly the U.S. population in the early 1980 s), after 20 days 215 people would be left who had each day accurately predicted the 1

4 outcome of the coin toss. These winners would likely claim to have superior ability, while some business school professor will probably be rude enough to bring up the fact that if 225 million orangutans had engaged in a similar exercise, the results would be much the same 215 egotistical orangutans with 20 straight winning flips (Buffett 1984, 5). But, Buffett supposed, what if 40 of the orangutans came from the same zoo? Surely, no honest statistician would dismiss this as random chance. In the case of successful investors, I think you will find that a disproportionate number of successful coin-flippers in the investment world came from a very small intellectual village that could be called Graham-and- Doddsville. A concentration of winners that simply cannot be explained by chance can be traced to this particular intellectual village (Buffett 1984, 6). Buffett recognized that while few investors had achieved long-term success, a disproportionate number of them were disciples of Benjamin Graham and David Dodd and their investment philosophy known as value investing. In this paper, we ll attempt to broaden the description of value investing from merely an investment style, identified by a stock s statistical characteristics (P/E ratios, for example), to a comprehensive investment philosophy. 2

5 2. ORIGINS OF THE VALUE APPROACH 2.1. Benjamin Graham s Early Career Benjamin Graham graduated from Columbia University in 1914 and accepted a position with investment firm Newberger, Henderson & Loeb. He eventually became the firm s statistician (then the term for investment analyst) and made partner in 1923 (Morris 2015, 165). His responsibilities mostly involved studying bonds. It was during these years that Graham learned to analyze financial statements and identify a company s assets and earnings. Graham applied his craft at a time before uniform disclosure rules existed at the national level. Companies did provide minimal financial information as promotional material to attract investors or to comply with exchange requirements, but this information was generally not used to analyze common stocks. Graham was unique in identifying that financial statement analysis could be used to generate conservative profits in stocks. In 1915, the Guggenheim Exploration Company proposed to liquidate its assets and distribute the proceeds to shareholders. Graham noticed that the company owned interests in several NYSE listed mining companies, whose value, along with Guggenheim s other assets, represented $76.23 per Guggenheim share. The quoted price for Guggenheim s shares at that time were $ Thus, Graham reasoned, by shorting (selling borrowed shares) the stocks of the listed mining companies and 3

6 simultaneously purchasing stock in Guggenheim, an investor could make a nearly risk-free profit ( arbitrage ) of $7.35 per share (Kahn and Milne 1977, 4-5). Graham came to specialize in these arbitrage opportunities, and in 1923 Graham left Newberger, Henderson & Loeb to start his own investment firm. The common view on wall street in the early 1920 s was that an investor was interested in stable income while a speculator was interested in forecasting price movements. Thus, investors bought bonds while speculators bought stocks. The prevailing view, in other words, was that stocks could never be thought of as an investment. Graham disagreed, and he invested profitably in common stocks through the 1920 s. Edgar Lawrence Smith s Common Stocks as Long Term Investments, which had shown statistically that stocks had outperformed bonds overtime, became a widely-read book on Wall Street (Fox 2009, 22). By the late 1920 s, Smith s book had become, according to Warren Buffett, the intellectual underpinning of the 1929 stock-market mania (quoted in Schroeder 2009, 20). Graham, looking back, felt that Smith s analysis was taking market participants to an illogical conclusion: In using past performance of common stocks as the reason for paying prices 20 to 40 times their earnings, the new-era exponents were starting with a sound premise and twisting it into a woefully unsound conclusion (Graham and Dodd 1934, 313). 4

7 Unfortunately, Graham was not spared by the 1929 market crash. Graham, who by then had closed his first firm and began a partnership with Jerome Newman, had borrowed heavily to leverage his arbitrage profits proved the worst year for Graham, with his operation down a full -50%, vs. -29% for the Dow Jones Industrials (Kahn and Milne 1977, 18). Presumably, Graham would have dissolved the firm, save for a $75,000 capital infusion from a relative of Jerome Newman (Lowenstein 2008, 38). However, that stocks were in such disfavor in the 1930 s played to Graham s analytical method. In 1932, Graham wrote a series of articles for Forbes magazine titled Is American Business Worth More Dead Than Alive? in which he identified that over 40 percent of NYSE listed stocks were selling below net working capital (Kahn and Milne 1977, 21) Security Analysis and The Intelligent Investor In 1928, Ben Graham began teaching a night course in Security Analysis at Columbia University. Graham s ultimate motivation was to write a book on the subject, and teaching allowed him to organize his thoughts and test his ideas on a live audience. Attending Graham s class was Columbia faculty member David Dodd, who was tasked with transcribing Graham s lectures. Working from these notes, the professors would author their classic text, Security Analysis (Lowe 1994, 81). 5

8 The first edition of Security Analysis was published in 1934 and by the late 1970 s the book had become the basic text for the teaching and practice of two generations of security analysts (Kahn and Milne 1977, 21). To Graham, a stock was not categorically risky. Graham advocated that the price relative to the earnings and assets of the underlying business was the key to separating a sound investment from a risky speculation. Just as stocks were considered risky after the crash, before the crash the opposite was true: The new-era doctrine that good stocks (or blue chips ) were sound investments regardless of how high the price paid for them was at bottom only a means of rationalizing under the title of investment the well-nigh universal capitulation to the gambling fever (Graham 1934, 11). Graham advocated that the investor be well advised to devote his attention to the field of undervalued securities issues, whether bonds or stocks, which are selling well below the levels apparently justified by a careful analysis of the relevant facts (Graham 1934, 13). To Graham, a stock had a price (market quotation) and an underlying value and these two figures were distinct. A stock could be a sound investment if the underlying value, as carefully and conservatively calculated, was significantly higher than the stock s price. A bargain purchase was central to the process. Graham recognized that markets could occasionally create bargains for behavioral reasons: the market is not a weighing machine, on which the value of each issue is recorded by an exact and impersonal mechanism, in accordance with its specific qualities. Rather should we say that the market is a voting 6

9 machine, whereon countless individuals register choices which are the product partly of reason and partly of emotion (Graham 1934, 23). In 1949, The Intelligent Investor was published. Whereas Security Analysis was written as a textbook for investment professionals, The Intelligent Investor was written for a more general audience. Warren Buffett, in a forward to the fourth edition, advises the reader to pay particular attention to chapters 8 and 20 (Graham [1973] 2003, ix) Graham s View of Stock Market Prices In chapter 8 of The Intelligent Investor, Graham presents a view of market prices which is in contrast with the view of market prices in MFT. Graham relates his views through his famous Mr. Market analogy (Graham [1973] 2003, ). Graham asks the reader to imagine owning a small interest in a private company. One of your partners is named Mr. Market, and every day he offers you a price at which he will purchase your shares or sell you his. Mostly Mr. Market will quote a price which is sensible considering the business s fundamentals. However, Mr. Market is subject to wild mood swings and can on occasional quote you a wildly pessimistic or wildly optimistic price. It is up to you to take advantage of Mr. Market s volatile temperament by buying when he offers you an absurdly low price and selling when he offers you a very high price. 7

10 To Graham, the market was there to serve rather than guide the investor. As Graham stated: Price fluctuations have only one significant meaning for the true investor. They provide him with an opportunity to buy wisely when prices fall sharply and to sell wisely when they advance a great deal. At other times he will do better if he forgets about the stock market and pays attention to. the operating results of his companies (Graham [1973] 2003, 205). This is a view of stock markets which is in significant contrast to the view of markets held by MFT proponents Margin-of-Safety The second of Graham s major insights in The Intelligent Investor has been the cornerstone of the philosophy followed by many successful investment practitioners. That concept is the margin of safety. The margin of safety is the difference between the stock s underlying value and the stock s price. As Graham explained, the margin of safety was a favorable difference between price on the one hand and indicated or appraised value on the other. That difference is the safety margin. It is available for absorbing the effect of miscalculations or worse than average luck (Graham [1973] 2003, ). Graham wrote considerably on the need to differentiate between the terms investment and speculation. Graham, writing in the early 1930 s, recognized that no authoritative definition existed for the term investment. He thus offered the following definition: An investment 8

11 operation is one which, upon thorough analysis, promises safety of principal and a satisfactory return. Operations not meeting these requirements are speculative (Graham and Dodd 1934, 54). In The Intelligent Investor, Graham proposed the margin of safety concept be used to further his definition of investment: To have a true investment there must be present a true margin of safety. And a true margin of safety is one that can be demonstrated by figures, by persuasive reasoning, and by reference to a body of actual experience (Graham [1973] 2003, 520). 9

12 3. ORIGINS OF MODERN FINANCE Security Analysis in its various editions remained part of academic finance curriculums for several decades after its initial publication. As the late Robert Huagen, a prominent EMH critic, remembered: When I entered the university in 1960, I was taught old finance. My textbooks were Benjamin Graham and David Dodd s Security Analysis and a corporate finance book by Arthur Stone Dewing, The Financial Policy of Corporations (Haugen 2010, 6). Today, few undergraduate or graduate level finance students have more than a passing understanding of Graham s methods. By the early 1970 s Graham and Dodd s Security Analysis had been supplanted by academic ideas collectively referred to as modern finance theory (MFT). While an in-depth study of MFT is beyond the scope of this paper, we will examine a few key ideas below Harry Markowitz and Modern Portfolio Theory In 1950, a young PhD student at the University of Chicago named Harry Markowitz was contemplating what to write for his doctoral dissertation. While waiting outside of a professor s office, Markowitz conversed with a stockbroker who suggested that Markowitz base his paper on the stock market (Fox 2009, 53). From this serendipitous meeting emerged the birth of academic finance. 10

13 At the University of Chicago, Markowitz had studied a then-new mathematical application called linear programming. This method is a means of finding optimum (maximum or minimum) relationships among variables. Markowitz realized that this application was well suited to the field of investment as investors were always seeking to maximize gains while minimizing risk. Markowitz determined to concentrate his efforts on two timeless questions facing investors: (1) the tradeoff between risk and reward and (2) how to use diversification to minimize a portfolio s risk. To systematize the problem, Markowitz had to have a measure for an asset s risk. For risk, Markowitz used the standard deviation, a statistical measure of dispersion, of past returns. Because Markowitz was concerned with the risk and return tradeoff of a portfolio, and not just an individual asset, he added a third input: covariance. The covariance is a measure of the returns between two assets. This third element was Markowitz s unique insight. By constructing a portfolio of assets whose returns had low or negative correlation, the standard deviation of the portfolio would be lower than the average standard deviations of the individual assets. Thus, Markowitz showed how to diversify to obtain reduction in portfolio volatility. His work, however, was also considered as a mathematical proof for the 11

14 importance of portfolio diversification. Markowitz s findings were published in 1952 in the Journal of Finance under the title Portfolio Selection 1. For the average investment professional in the 1950 s, applying Markowitz s method was a nearly impossible task (Bernstein 2005, 57). The method worked best when applied to a wide universe of financial securities, but the correlations among each combination had to be calculated. The use of Markowitz s portfolio optimization methods, not coincidentally, increased with the rise of enhanced and affordable computing power. Today, even most personal computers are equipped with basic optimization software. And most financial planners and other advisers rely heavily on optimization programs to set portfolio allocations for clients William Sharpe and Beta Shortly after producing his landmark paper, Markowitz accepted a position doing linear programming for the RAND Corporation (Fox 2009, 55). At RAND, Markowitz was introduced to a young staffer and UCLA doctoral student named William Sharpe. At Markowitz s behest, Sharpe focused his dissertation research on making Markowitz s insights regarding portfolio 1 Markowitz was innovative not only in his insight, but also in taking up the subject at all. In the early 1950 s, the stock market was not a popular subject for academic research. 12

15 optimization more practical. UCLA had given Markowitz permission to serve as Sharpe s thesis adviser, despite Markowitz having no affiliation with the University. Sharpe set out to simplify Markowitz s work by seeking a common statistical relationship among stocks. Sharpe s PhD dissertation was published in the journal Management Science in 1963 (Fox 2009, 86). In the paper, Sharpe created a simplified model in which a stock s return would be determined by several random factors and some measure of this common relationship. Sharpe referred to this as the diagonal model, and the common factor may be the level of the stock market as a whole, the Gross National Product, some price index or any other factor thought to be the most important single influence on the returns from securities (Sharpe 1963, 281). To Sharpe, the key driver of a security s returns was the security s correlation with this common factor. The common factor which seemed to have the most explanatory value was the market itself. Sharpe represented this correlation with the symbol, B, which would later be referred to as beta. Sharpe recognized that the price of an asset should be such as to compensate the investor for the asset s risk. To Sharpe, an asset s risk had two components. The first component of an asset s risk was the correlation between an asset s returns and the returns of the market 13

16 itself. The second component of an asset s risk was the risk which was specific to the individual asset. Sharpe referred to the first component of risk as systematic risk and the second form as unsystematic risk (Sharpe 1964, 439). For the sake of his analysis, Sharpe assumed that all investors followed Markowitz s model of portfolio diversification, thus diversifying away any specific risk. According to Sharpe: Since all other types can be avoided by diversification, only the responsiveness of an asset s rate of return to the level of economic activity is relevant in assessing its risk (Sharpe 1964, 442). The proposition would prove alluring to academics and finance professionals: a stock s risk could be measured by a single statistic, B The Efficient Market Hypothesis The third major idea of academic finance which we will consider is the efficient market hypothesis (EMH). This idea is also the most controversial and perhaps widely subscribed to idea in finance. The EMH is especially controversial for any practitioners of active stock selection. The EMH evolved from the work of several economists regarding the predictability of securities prices. The real birth of the EMH, however, may lie in an obscure doctoral dissertation written in 1900 by a French mathematician named Louis Bachelier. While searching through the libraries of Cambridge, Massachusetts, famed MIT economist Paul 14

17 Samuelson discovered a copy of Bachelier s dissertation, Théorie de la spéculation (Theory of speculation) (Fox 2009, 65). Bachelier s work was a mathematical analysis of security prices on the Paris Bourse. Through dense mathematical application, Bachelier demonstrated that securities prices fluctuate randomly. In 1934, a statistician at Stanford University named Holbrook Working produced a study of the behavior of commodity prices. The study showed that while seemingly nonrandom patterns occur in commodity prices, commodity price changes occurred in an entirely random sequence (Bernstein 2005, 95). Working s statistical methodology was later applied to a study of stock prices by University of Chicago professor Harry Roberts. Roberts s paper, published in the Journal of Finance in 1959, was particularly aimed at debunking the chart reading services which were popular at the time. And Roberts did seem to make a compelling case. According to economist and author Peter Bernstein, Roberts suggests that just about all of the classical patterns of technical analysis could be generated by chance artificially by a suitable roulette wheel or random-number table (Bernstein 2005, 101). And while Paul Samuelson continued work on stock price behavior and was considered an expert on the subject, he never published these findings in a major academic journal. The conclusions of these (and other) academic studies, i.e., that securities prices were random and thus could not be predicted, later became known as the random walk hypothesis. 15

18 Eugene Fama of the University of Chicago expanded the work done by Roberts and others into a more comprehensive theory of asset prices, which he called the efficient markets model. To Fama, a market is efficient when prices fully reflect available information (Fama 1970, 383). As an undergraduate at Tufts University, Fama worked for a stock market newsletter run by a professor. Fama s job was to analyze stock charts to find profitable trading strategies. Fama noticed, however, that once he identified a pattern it would disappear. In other words, the market was good at competing away any excess profits on a trading strategy. It was this experience that inspired Fama to study asset prices (Fox 2009, 96). At Harry Robert s suggestion, Fama s efficient markets model, later referred to as the efficient market hypothesis (EMH), recognized three degrees of market efficiency: weak form, semi-strong form, and strong form. The weak form was a reformulation of the random walk hypothesis, i.e., that past price patterns cannot be used to predict future price patterns. The semi-strong form suggested that all public information was fully reflected in stock prices. The strong-form of the EMH suggested that both public and private information was fully reflected in stock prices. 16

19 4. VALUE INVESTING AND MFT A full analysis of the EMH is beyond the scope of this paper. It is enough to recognize that the Graham and Dodd philosophy of buying bargains and patiently waiting has attracted a new generation of practitioners, many of whom have produced impressive results. And these investors, while recognizing that markets are highly competitive, are largely opposed to the idea of perfectly efficient markets. As one highly-regarded value investor has said, There is simply no question that investors applying disciplined analysis can identify inefficiently priced securities, buy and sell accordingly, and achieve superior returns. Specifically, by finding securities whose prices depart appreciably from underlying value, investors can frequently achieve above-average returns while taking below-average risks (Klarman 1991,98). Value investing practitioners also disagree with the notion that investment risk can be captured in a single statistical figure. Graham advocated that investors analytically treat stocks as if they were purchasing the entire business: Investment is most intelligent when it is most businesslike (Graham [1973] 2003, 523). The MFT proponents, in contrast, advocate that investors ignore all idiosyncratic risks of business ownership, as they can be diversified away, and focus only on systematic risk as measured by a company s beta. Even Eugene Fama, in collaboration with Kenneth French, conducted a study in which they 17

20 concluded that beta was a weak explanation for returns over their sample period (Fama and French 1992, 464). The concept of beta, however, continues to be taught in universities and used by investment practitioners. As noted earlier, MFT continues to dominate the teaching of finance. Thus, few finance students at the undergraduate or graduate levels are exposed to Graham and Dodd s teachings. We should recognize, however, that numerous academic studies had emerged in the 1980 s and 1990 s which had at least partially discredited the EMH 2. It is interesting to note that the 2013 Nobel Prize in Economic Sciences was shared (with Lars Peter Hansen) by Eugene Fama and Robert Shiller. This is notable because, while Fama is the father of the EMH, Shiller is most recognized for his work in behavioral finance, a discipline which stands in contrast with the EMH. Academic finance has at least become a bit more balanced. Still, many university courses titled Security Analysis prioritize the portfolio approach to stock selection, in which stocks are primarily chosen based on their diversification benefits to a portfolio, and not on whether they are undervalued. Graham and Dodd remain underrepresented in academia 3. 2 See Tweedy, Brown Company s booklet What Has Worked in Investing (2009) for a discussion of many of these academic papers. 3 To its credit, Columbia University has selectively restored Graham and Dodd s teachings under the leadership of professor Bruce Greenwald and a few adjunct professors. Several other universities have also begun offering select value investing courses. However, these courses are the exception to MFT s predominance. 18

21 The EMH remains the most widely accepted market theory among finance academics. The persistent faith in the EMH seems to lie in the general inability of fund managers to beat their respective benchmarks. As professor Burton Malkiel, a leading proponent of the EMH has stated: For me, the most convincing tests of market efficiency are direct tests of the ability of professional fund managers to outperform the market as a whole (Malkiel 2011, 291). And fund managers have not disappointed the EMH proponents. According to the Standard & Poor s (S&P) Indices versus Active (SPIVA ) report, 88.3% of mutual funds lagged their respective S&P index over the five-year period ending 12/31/

22 5. CONCLUSION In response to the pervasive-underperformance EMH argument, value practitioners may point out that few professional investors follow a true value investing philosophy. The mutual fund industry has embraced a definition of value as an investment style characterized by the selection of stocks based on low P/E ratios and other similar metrics. But this definition of value investing does not fully capture Graham s underlying philosophy, nor does it describe the methods of most true value investing practitioners. Bill Ruane, the late founder of the Sequa Fund, once suggested that value investors account for approximately 5% of professionally managed money (Lowenstein 2008,36). Similarly, fund manager Jean Marie Eveillard stated in a speech given at Columbia University in 2005 that maybe 5 percent of professional money managers are true value investors (Nocera 2005). Anyone who has followed this small-subset of professional money managers understands that their collective superior long-term performance is more than chance. As Buffett concluded in his 1984 speech, Ships will sail around the world but the Flat Earth Society will flourish. There will continue to be wide discrepancies between price and value in the marketplace, and those who read their Graham & Dodd will continue to prosper (Buffett 1984, 15). 20

23 Tortuga Capital, LLC is an independent investment adviser located in Fort Myers, Florida. To learn more about our services, please visit or us at Disclaimer Tortuga Capital LLC is a registered investment adviser. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and unless otherwise stated, are not guaranteed. Be sure to first consult with a qualified financial adviser and/or tax professional before implementing any strategy discussed herein. Registration does not imply that such person has been sponsored, recommended, or approved by the state or any agency or officer of the state or by the United States or any agency or officer of the United States. 21

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25 Lowe, Janet Benjamin Graham on Value Investing: Lessons from the Dean of Wall Street. U.S.: Dearborn Financial Publishing. Lowenstein, Louis The Investor s Dilemma: How Mutual Funds Are Betraying Your Trust and What to Do About It. Hoboken: Wiley. Lowenstein, Roger Buffett: The Making of an American Capitalist. New York: Random House. Malkiel, Burton G A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing. New York: W.W. Norton & Company. Morris, Edward Wall Streeters: The Creators and Corruptors of American Finance. New York: Columbia University Press. Nocera, Joe The Heresy That Made Them Rich. The New York Times, October 29. Schroeder, Alice The Snowball: Warren Buffett and the Business of Life. New York: Bantam Books. Sharpe, William F A Simplified Model for Portfolio Analysis Management Science 9 (2): Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk The Journal of Finance 19 (3): Standard & Poor s SPIVA Report. Accessed August 05, The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel

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