Alpha, the Capital Markets, and the Efficient Markets Hypothesis (Chapter 6) Adapted from Portfolio Construction, Management, & Protection, 4e, Robert A. Strong Copyright ©2006 by South-Western, a division of Thomson Business & Economics. All rights reserved.

No matter how many winners you’ve got, if you either leverage too much or do anything that gives you the chance of having a zero in there, it’ll all turn into pumpkins and mice. Warren Buffett

Outline Introduction Alpha and Portfolio Management Role of the Capital Markets Efficient Market Hypothesis Anomalies

What is “alpha”? Alpha = the amount by which the market is beaten, after adjusting for risk What is alpha for the market as a whole? Alpha for market as a whole is zero So, on average, portfolios are ON the SML Provides conceptual value of CAPM Regardless of whether market is efficient, it is still a zero-sum game Burden of active manager In order to win (i.e., beat the market), someone else has to lose Key question = what is special about you (and about your knowledge) that will allow you to be the one that wins?

Generating alpha Are there ways to consistently generate alpha? See portfolio manager performance example:

Portfolio Manager’s Performance: Past Three Years Previous Three Years: S&P 500 Fund Manager Compound Annual Return -4.98% -22.01% Total Return -14.20% -52.56%

Portfolio Manager’s Performance: Past Four Years Previous Four Years: S&P 500 Fund Manager Compound Annual Return 0.50% -14.19% Total Return 2.02% -45.77%

Portfolio Manager’s Performance: Past Five Years Previous Five Years: S&P 500 Fund Manager Compound Annual Return 3.17% -0.54% Total Return 16.91% -2.67%

Portfolio Manager’s Performance: Past Six Years Previous Six Years: S&P 500 Fund Manager No. of Down Years 2 of 6 4 of 6 Compound Annual Return 3.29% -1.66% Total Return 21.47% -9.58%

Generating alpha Would you have invested with this manager? Who is this manager with this horrible record? Warren Buffett, of course!!! Portfolio = investment in Berkshire-Hathaway, over the period of 1970 – 1975 Note: while stock price lagged market substantially, book value per share grew faster than market each year except 1975; this is a metric with which Buffett is more concerned

Generating alpha As we have seen previously in discussing the EMH, value stocks tend to outperform growth stocks Concomitantly, Warren Buffett has the best investment record in history, becoming the 2nd richest man in the world in the process However, as we have just now seen, although value wins on average, over the long run, it does not win perfectly consistently! Instead, the markets tend to cycle, with different styles of investment performing well at different times

Book to Market as a Predictor of Return: Value (positive a) tends to outperform Growth (negative a) 0% 5% 10% 15% 20% 25% Annualized Rate of Return Value Growth 10 9 8 7 6 5 4 3 2 1 High Book/Market Low Book/Market

Rolling Annualized Average 5-year Difference Between the Returns to Value and Growth Composites: The Market cycles between Value and Growth, But Value Wins on Average 50% 40% 30% 20% Relative Difference 10% 0% 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 -10% -20% Year

Empirical Regularities: Sources of alpha Three categories that tend to outperform over the long run: Value stocks vs. Growth stocks Size: Small caps tend to outperform large caps Momentum: stocks with momentum (earnings or price) tend to beat stocks without momentum However, the payoffs to all of these tend to cycle! A typical portfolio manager, being judged on a quarter-by-quarter basis, would have been fired long before if he had the same record as Buffett for 1970 – 1975! (In fact, he fired himself during this period!) None of these beats the market perfectly consistently A typical portfolio manager would need to try to cycle along with the market, in order to keep from ever lagging too far behind it

Empirical Regularities: Sources of alpha Beating the market consistently would require some sort of rotation strategy in order to profit from the type of securities that are performing well in the given type of market But - combination of “fat tails” and “volatility clustering” (discussed previously) can cause problems! Best performance for a given style is likely to follow closely on the heels of its worst performance, and much of the movement for the style is likely to come in a relatively short burst (thus, if you miss it, it’s gone) E.g.: 40% of the stock market gains for the entire decade of the 1980’s occurred during a mere 10 trading days ! So efforts to cycle with the market and keep from falling too far behind it also make it much more difficult to beat the market!

Capital Market Theory Capital market theory springs from the notion that: People like return People do not like risk Dispersion around expected return is a reasonable measure of risk

Role of the Capital Markets Definition Economic Function Continuous Pricing Function Fair Price Function

Definition Capital markets trade securities with lives of more than one year Examples of capital markets New York Stock Exchange (NYSE) American Stock Exchange (AMEX) Chicago Board of Trade Chicago Board Options Exchange (CBOE)

Economic Function The economic function of capital markets facilitates the transfer of money from savers to borrowers e.g., mortgages, Treasury bonds, corporate stocks and bonds

Continuous Pricing Function The continuous pricing function of capital markets means prices are available moment by moment Continuous prices are an advantage to investors Investors are less confident in their ability to get a quick quotation for securities that do not trade often

Fair Price Function The fair price function of capital markets means that an investor can trust the financial system The function removes the fear of buying or selling at an unreasonable price The more participants and the more formal the marketplace, the greater the likelihood that the buyer is getting a fair price

Efficient Market Hypothesis Definition Types of Efficiency Forms of Efficiency Weak Form Semi-Strong Form Strong Form Semi-Efficient Market Hypothesis Security Prices and Random Walks

Definition The efficient market hypothesis (EMH) is the theory supporting the notion that market prices are in fact fair Under the EMH, security prices fully and fairly (i.e., without bias) reflect all available information about the security Since the 1960’s, the EMH has been perhaps the most important paradigm in finance Whether markets are efficient has been extensively researched and remains controversial

Types of Efficiency Operational efficiency measures how well things function in terms of speed of execution and accuracy It is a function of the number of orders that are lost or filled incorrectly It is a function of the elapsed time between the receipt of an order and its execution

Types of Efficiency (cont’d) Informational efficiency is a measure of how quickly and accurately the market reacts to new information This is the type of efficiency with which the EMH is concerned The market is informationally very efficient Security prices adjust rapidly and fairly accurately to new information However, as we’ve already seen, the market is still not completely efficient

Forms of Market Efficiency Eugene Fama’s original formulation of the Efficient Market Hypothesis established three forms of market efficiency, based on the level of information reflected in security prices: Weak form = prices reflect all past market level (price and volume) information Semi-strong form = prices also reflect all publicly available fundamental company and economic information Strong form = prices also reflect all privately held information that would affect the value of the company and its securities

Weak Form Definition Charting Runs Test

Definition The weak form of the EMH states that it is impossible to predict future stock prices by analyzing prices from the past The current price is a fair one that considers any information contained in the past price data Charting techniques are of no use in predicting stock prices

Definition (cont’d) Example Which stock is a better buy? Stock A Current Stock Price Stock B

Definition (cont’d) Example (cont’d) Solution: According to the weak form of the EMH, neither stock is a better buy, since the current price already reflects all past information.

Charting People who study charts are technical analysts or chartists Chartists look for patterns in a sequence of stock prices Many chartists have a behavioral element

Runs Test A runs test is a nonparametric statistical technique to test the likelihood that a series of price movements occurred by chance A run is an uninterrupted sequence of the same observation A runs test calculates the number of ways an observed number of runs could occur given the relative number of different observations and the probability of this number These tests have provided evidence in favor of weak form efficiency

Conducting A Runs Test

Semi-Strong Form The semi-strong form of the EMH states that security prices fully reflect all publicly available information e.g., past stock prices, economic reports, brokerage firm recommendations, investment advisory letters, etc.

Semi-Strong Form (cont’d) Academic research supports the semi-strong form of the EMH by investigating various corporate announcements, such as: Stock splits Cash dividends Stock dividends Examined through “event studies” This means investors are seldom going to beat the market by analyzing public news

Semi-Strong Form (cont’d) Market seems to do a relatively good job at adjusting a stock’s valuation for certain types of new information Determining how much the new info. will change the stock’s value and then adjusting the price by an equivalent amount This is what event studies examine But it does seem to have problems developing an overall valuation for a stock in the first place E.g., What is the correct value for IBM as a whole is a very difficult question to answer, but how much IBM’s value should change if it is awarded a specific new contract is much easier to determine

Semi-Strong Form (cont’d) Burton Malkiel points out that two-thirds of professionally managed portfolios are consistently beaten by a low-cost index fund Suggests that securities are accurately priced and that in the long run returns will be consistent with the level of systematic risk taken Supports semi-strong form of the EMH Also would suggest that portfolio managers do not possess any private information that is not already reflected in security prices Supports the strong form of the EMH

Strong Form The strong form of the EMH states that security prices fully reflect all relevant public and private information This would mean even corporate insiders cannot make abnormal profits by using inside information about their company Inside information is information not available to the general public

Semi-Efficient Market Hypothesis The semi-efficient market hypothesis (SEMH) states that the market prices some stocks more efficiently than others Less well-known companies are less efficiently priced The market may be tiered A security pecking order may exist Lynch prefers stocks that “the analysts don’t follow … and the institutions don’t own …” See the Small Firm and Neglected Firm Effects discussed later

Security Prices and Random Walks The unexpected portion of news follows a random walk News arrives randomly and security prices adjust to the arrival of the news We cannot forecast specifics of the news very accurately

Anomalies Definition Low PE Effect Low-Priced Stocks Small Firm and Neglected Firm Effect Market Overreaction Value Line Enigma January Effect

Anomalies (cont’d) Day-of-the-Week Effect Turn-of-the Calendar Effect Persistence of Technical Analysis Behavioral Finance Joint Hypothesis Problem Chaos Theory

Definition A financial anomaly refers to unexplained results that deviate from those expected under finance theory Especially those related to the efficient market hypothesis

Low PE Effect Stocks with low PE ratios provide higher returns than stocks with higher PEs And similarly for high P/B (hence lower Book/Market) stocks Supported by several academic studies Conflicts directly with the CAPM, since study returns were risk-adjusted (Basu) Related to both semi-strong form and weak form efficiency

Low-Priced Stocks Stocks with a “low” stock price earn higher returns than stocks with a “high” stock price There is an optimum trading range

Small Firm and Neglected Firm Effects Small Firm Effect Neglected Firm Effect

Small Firm Effect Investing in firms with low market capitalization will provide superior risk-adjusted returns Supported by academic studies Implies that portfolio managers should give small firms particular attention

Neglected Firm Effect Security analysts do not pay as much attention to firms that are unlikely portfolio candidates Implies that neglected firms may offer superior risk-adjusted returns

Market Overreaction The tendency for the market to overreact to extreme news Investors may be able to predict systematic price reversals Results because people often rely too heavily on recent data at the expense of the more extensive set of prior data

The Value Line Enigma Value Line (VL) publishes financial information on about 1,700 stocks The report includes a timing rank from 1 down to 5 Firms ranked 1 substantially outperform the market Firms ranked 5 substantially underperform the market Victor Niederhoffer refers to Value Line’s ratings as “the periodic table of investing”

The Value Line Enigma Changes in rankings result in a fast price adjustment Some contend that the Value Line effect is merely the unexpected earnings anomaly due to changes in rankings from unexpected earnings Nonetheless, Value Line’s successful record is evidence in support of the existence of superior analysts who apparently possess private information

January Effect Stock returns are inexplicably high in January Small firms do better than large firms early in the year Especially pronounced for the first five trading days in January

January Effect (cont’d) Possible explanations: Tax-loss trading late in December (Branch) The risk of small stocks is higher early in the year (Rogalski and Tinic)

January Returns by Type of Firm Average January return Average January return minus average monthly return in rest of year Average January return after adjusting for systematic risk S&P 500 Companies Highly Researched 2.48% 1.63% -1.44% Moderately Researched 4.95% 4.19% 1.69% Neglected 7.62% 6.87% 5.03% Non-S&P 500 Companies Neglected 11.32% 10.72% 7.71% Source: Avner Arbel, “Generic Stocks: The Key to Market Anomalies,” Journal of Portfolio Management, Summer 1985, 4–13.

Day-of-the-Week Effect Mondays are historically bad days for the stock market Wednesday and Fridays are consistently good Tuesdays and Thursdays are a mixed bag

Day-of-the-Week Effect (cont’d) Should not occur in an efficient market Once a profitable trading opportunity is identified, it should disappear The day-of-the-week effect continues to persist However – there are confounding effects between the levels and the volatilities of returns across different days

Turn-of-the-Calendar Effect The bulk of the return comes from the last trading day of the month and the first few days of the following month For the rest of the month, the ups and downs approximately cancel out

Persistence of Technical Analysis Technical analysis refers to any technique in which past security prices or other publicly available information are employed to predict future prices Studies show the markets are efficient in the weak form Literature based on technical techniques continues to appear but should be useless

Behavioral Finance Concerned with the analysis of various psychological traits of individuals and how these traits affect the manner in which they act as investors, analysts, and portfolio managers Growth companies will usually not be growth stocks due to the overconfidence of analysts regarding future growth rates and valuations Notion of “herd mentality” of analysts in stock recommendations or quarterly earnings estimates is confirmed

Chaos Theory Chaos theory refers to instances in which apparently random behavior is systematic or even deterministic under Mauboussin’s theory of the market as a complex adaptive system, then we would expect to see chaotic dynamics Econophysics refers to the application of physics principles in the analysis of stock market behavior e.g., an investment strategy based on studies of turbulence in wind tunnels Includes use of multifractal models

Are Markets Rational? This question always faces a joint hypothesis problem: Tests of EMH are always dual tests of both market efficiency and the specific asset-pricing model assumed Market efficiency Is the stock’s price equal to its true value? Asset pricing model used (CAPM, APT, etc.) What is the stock’s true value? Never known for sure “The question of value presupposes an answer to the question, of value to whom, and for what?” – Ayn Rand E.g., the value of Apple stock would be different to Steve Jobs than to any other investor

Are Markets Rational? Related issue – what is information? “Information is that which causes changes” – Claude Shannon (father of information theory) So, if something causes the markets to move, then by definition, it must be information, and vice versa From this perspective, the market is neither efficient nor inefficient, it just is So, are the markets efficient or rational? Ultimately, difficult to answer categorically Key question is not whether or not the markets are efficient – this is a side issue – but how investors should act, given how the markets work