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Are Markets Rational? Part 1 Adapted from Haugen, Ch. 15: “The Wrong 20-Yard Line”

Are Markets Rational? Part 1 Adapted from Haugen, Ch. 15: “The Wrong 20-Yard Line”. References. Reilly & Brown, Ch. 7 – “Efficient Capital Markets” Haugen, Ch. 15 – “The Wrong 20-Yard Line” Mauboussin ( www.capatcolumbia.com ) – “Shift Happens”

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Are Markets Rational? Part 1 Adapted from Haugen, Ch. 15: “The Wrong 20-Yard Line”

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  1. Are Markets Rational?Part 1Adapted from Haugen, Ch. 15: “The Wrong 20-Yard Line”

  2. References • Reilly & Brown, Ch. 7 – “Efficient Capital Markets” • Haugen, Ch. 15 – “The Wrong 20-Yard Line” • Mauboussin (www.capatcolumbia.com) – “Shift Happens” • Hagstrom, Ch. 8 – “The Market as a Complex Adaptive System” • Rubinstein (Financial Analysts Journal, 2001) – “Rational Markets: Yes or No? The Affirmative Case” • Fortune (3 Dec. 2002) – “Is the Market Rational?”

  3. Forms Of EMT • Weak Form • Prices reflect all historical information • Price changes follow a random walk • “Tests of Return Predictability” • Technical Analysis • Semi-Strong Form • Prices reflect all public information • “Event Studies” • Fundamental Analysis • Strong Form • Prices reflect all public and private information • “Tests for Private Information” • Insider Trading

  4. Weak Form EMH • Supported by: • Studies on Autocorrelation • Tests of Filter Rules • Contradicted by: • Seasonality • January Effect • Day-of-the-Week Effect • Long-term overreaction/reversal patterns

  5. Semi-Strong Form EMH • Supported by: • Most Event Studies • Contradicted by: • Various Accounting Anomalies • Size Effect • M/B Effect • Neglected Firm Effect

  6. Summary on Semi-Strong Form EMH • 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 seems 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

  7. Strong Form EMH • Supported by: • Under-performance of most fund managers • Most are beaten by the market averages • Contradicted by: • Returns following insider purchases • Value Line effect • Consistent outperformance of some fund managers • Notably, Warren Buffett and the “Superinvestors of Graham-and-Doddsville”

  8. Fund Managers • Trained professionals, working full time at investment management • If any investor can achieve above-average returns, it should be this group • If any non-insider can obtain inside information, it would be this group, due to the extensive management interviews that they conduct • But, Peter Lynch criticism: • “have blinders on” • Also …

  9. Fund Managers • Quote from “Wall Street:” • “Do you want to know why fund managers can’t beat the S&P 500? Because fund managers are sheep … and sheep get slaughtered.” • Problems Fund Managers Face: • Administrative expenses and trading costs • Agency problems that contribute to poor performance • Compensation structure that encourages “sheep-like” behavior

  10. Tests and Results of EMH • Many results tend to support EMH • Event studies • Performance of most fund managers • But many other results tend to contradict EMH • Performance of Buffett • Numerous anomalies & long-run overreaction/reversals • So, are markets efficient (or rational) or not? • Need to examine whether markets can be beaten, after adjusting for risk • But, how should you model and measure risk? CAPM? APT?

  11. Tests and Results of EMH • Tests face a joint hypothesis problem • Results are dependent on both of two factors: • 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? • So, are the markets efficient or rational? • Ultimately, can never answer definitively • Mauboussin’s view (“Shift Happens”): stock market as a chaotic or complex adaptive system • Haugen’s view follows …

  12. Haugen’s Trilogy • “The New Finance” • “Beast on Wall Street” • “The Inefficient Stock Market”

  13. “The New Finance” • Focuses on the market’s major systematic error: • Fails to appreciate the strength of competitive forces in a market economy • Over-estimates the length of the “short run” • Over-reacts to records of success and failure for individual companies • Drives the prices of successful companies too high • Drives the prices of unsuccessful companies too low • So: • Successful firms tend to experience negative earnings surprises down the road • Unsuccessful firms tend to benefit from positive earnings surprises

  14. Changing Investor Opinion as to the Length of the Short Run • Prior to 1924 • Stock valuation based on current normalized earnings. • 1925 • E. L. Smith advises stock valuation based on future growth - New Era Theory. • Growth stocks start to take off, followed by Crash of ’29 • Leads to development of Graham & Dodd approach • 1934 • Graham and Dodd dispute New Era Theory’s views on growth and valuation. • Lessons learned until Go-go years of ’60’s • 1960’s • Growth stock investing makes comeback.

  15. But … • Successful growth stock investing requires some degree of persistence in earnings growth, • while the speed of mean-reversion in earnings growth appears to be quite fast. • If, in general, it is faster than the market expects, cheap (expensive) stocks should tend to grow faster (slower) than expected. • If this happens, cheap stocks should tend to out-perform expensive stocks.

  16. The Relative Performance of Portfolios Equally-weighted in the Cheap and Expensive Quartiles • The difference in cumulative return of value stocks relative to growth stocks is measured over rolling 5-year periods. • The relative performance appears to cycle over time. • Cheap (value) stocks out-perform more often than not.

  17. Rolling Annualized Average 5-year Difference Between the Returns to Value and Growth Composites 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 1997 1993 1994 1996 1992 1995 -10% -20% Year

  18. 14% 12% January Prior Losers 10% Feb. - Dec. Average Monthly 8% Return 6% 4% 2% 0% 1 Prior Winners 2 3 4 5 6 7 8 9 10 11 12 13 Rank based on Previous 5-year Return 14 15 16 17 18 19 20 Seasonal Returns to Value and Growth Portfolios

  19. What has Over-estimation of the Length of the Short Run Done to Risk and Return? • Cheap (expensive) stocks tend to have surprisingly high (low) realized returns • Cheap (expensive) stocks tend to have low (high) volatility, because little (much) is expected of them • Investors may expect higher returns from expensive stocks but they may be repeatedly surprised by disappointing earnings reports • Thus, the relationship between risk and return appears to be upside-down

  20. How Long Have Risk and Return Been Up-side Down? • If it’s caused by an over-estimation of the short run, it should begin with the renaissance of growth stock investing at the end of the 1950’s. • What has been the relative performance between the low-volatility stock portfolio and the market index over time?

  21. Cumulative Difference 25% 15% 5% -5% -15% -25% -35% 1928 1938 1948 1958 1968 1978 1988 Cumulative Difference in Return Between Low Volatility Portfolio and S&P 500

  22. The Relationship Between the Perceived and True Growth Horizon and Average Growth Rates • Define the growth horizon (or growth duration, see Ch. 20) as the length of time a typical stock takes to mean-revert to the average rate of earnings growth. • The evidence indicates that the perceived horizon is longer than the true horizon.

  23. The Relationship Between the Perceived and True Growth Horizon and Average Growth Rates • The true horizon tends to be relatively constant, but investor perceptions may change. • If investors perceive that relative differences in growth will persist for longer periods, growth stocks may out-perform. • Changes in the perceived horizon may create a cycle in growth/value performance.

  24. Rolling Annualized Average 5-year Difference Between the Returns to Value and Growth Composites 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 1997 1993 1994 1996 1992 1995 -10% -20% Year

  25. “Beast on Wall Street” • 2nd book in trilogy • Focuses on stock volatility • Three components of volatility

  26. Three Components of Stock Volatility • Event-driven volatility • Error-driven volatility • Price-driven volatility

  27. High-wire Act at the Financial Circus The wireThe economy The aerialists Different stocks Movements in Movements in balance bars stock prices

  28. Components of the Movements in the Balance Bars • Event-driven The best moves in the bars humanly possible • Error-driven Over- and under-reactions to shocks in the wire • Price-driven Aerialists interacting with each other

  29. The Types of Volatility Contrasted • Event-driven and error-driven volatility are caused by investors [over]reacting to specific information that could be expected to affect stock values • Price-driven volatility, on the other hand, works in the opposite direction – it is caused by investors reacting to what is happening in the stock market itself • i.e., there is a reassessment of stock valuations solely as a consequence of changes in stock prices … • rather than stock prices changing as a consequence of changes in stock valuations that are being driven by outside information • This is similar to Keynes’ and Graham’s views

  30. “We have reached the third degree where we devote our intelligence to anticipating what average opinion expects the average opinion to be.” • Keynes • “For stock speculation is largely a matter of A trying to decide what B, C, and D are likely to think – with B, C, and D trying to do the same.” • Graham and Dodd

  31. Synthesis The results of many old studies, when considered together, point to startling new conclusions.

  32. Contentions • Price-driven volatility is the largest of the three components. • Price-driven volatility is explosive. • Price-driven volatility is an important drag on long-run economic growth. • Explosions in Price-driven volatility create disruptions in economic activity. • For example. the Great Crash of 1929 helped cause the Great Depression.

  33. Mysteries of the Stock Market • Too much stock volatility (Shiller, American Economic Review, 1981)

  34. 34 30 26 22 30 P/E 18 14 10 6 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 Year Market Price and Perfect Forecast Price: Constant Discount Rates Pt / Et30 PFt / Et30

  35. Mysteries of the Stock Market • Too much stock volatility • Volatility too unstable (Haugen, Talmor, and Torous, Journal of Finance, 1991)

  36. Volatility Shifts Over 8-week Trading Periods • HTT find (with 99% confidence) 402 cases where volatility becomes significantly larger or smaller between the first and second 4-week blocks.

  37. Realization of Risk Premiums Following the Price-level Adjustments • Following the price-adjustments to volatility changes, subsequent stock returns are, on average, 460 basis points higher following volatility increases. (The higher required returns are apparently realized.) • Interestingly, only 10% of the shifts have an associated cause traceable in the media.

  38. Mysteries of the Stock Market • Too much stock volatility • Volatility too unstable • Unconnected market (Cutler, Poterba, and Summers, Journal of Portfolio Management, 1989)

  39. Percentage Changes in Stock Prices on 49 Historic Days Examples: Pearl Harbor Attacked -4.37% Roosevelt Dies 1.07% Bay of Pigs .47% John Kennedy Assassinated -2.81% Robert Kennedy Assassinated -.49% Chernobyl -1.06%

  40. Percentage Changes in Stock Prices on Historic Days • Average absolute return over 49 historic days 1.46% • Average absolute return over all other days .56%(standard deviation: .82%)

  41. “Events” Associated with the Five Largest One-day Percentage Changes in Stock Prices Worry over dollar (10/19/87) -20.47% Deficit talks in Wash. (10/21/87)9.10% Fear of deficit (10/26/87)-8.28% No reason for decline (09/03/46)-6.73% Roll-back of steel prices (05/28/62)-6.68%

  42. Haugen vs. Mauboussin • Note that the previous observation is consistent with Mauboussin’s hypothesis of the financial markets as a complex adaptive system • Nonlinearity causes stock price movements to bear little relation to specific definable causes

  43. “The Inefficient Stock Market” • 3rd book in Haugen’s trilogy • Focuses on expected return factor models • Attempt, in part, to exploit error-driven volatility • Positive payoff to cheapness results from market’s overreaction to success and failure • Positive payoff to intermediate term momentum results from the market’s underreaction to positive and negative earnings surprises in individual earnings reports • Also exploit the distortions in the structure of stock prices brought about by price-driven volatility

  44. It’s Tough to Beat the Market • It the market is so inefficient, why isn’t beating it “like taking candy from a baby?” • Two reasons: • Many professional investors are victims of their own agency problems • More importantly, a gale of unpredictable price-driven volatility stands between investors and the “candy”

  45. It’s Tough to Beat the Market • Professional investors are victims of agency problems • Easier to make a “story” for growth stocks than for value stocks • Worry about “benchmark risk” rather than total risk • Portfolio managers need to keep up with market on a fairly steady basis or risk losing their jobs • Gale of unpredictable price-driven volatility stands between investors and consistent profits • Price-driven volatility is unpredictable, increasing the element of chance in stock returns • Even after maximizing predictability of stock returns, only 10% of differences in monthly stock returns can be explained by model • Overvalued growth stocks can always go up even more before finally “coming down to earth”

  46. The Wrong 20-Yard Line • Spectrum of market efficiency equivalent to positions on a football field • At one end zone, perfectly efficient markets • At other end, completely inefficient markets

  47. The Wrong 20-Yard Line Near efficient markets end zone (the left end zone): • All volatility is event-driven • Models based on rational economic behavior do a good job of explaining and predicting market pricing • No under- or over-valued stocks, so no role for active investment • No inefficiencies for active managers to exploit • Fact that fund managers tend to underperform the market taken as evidence that markets are efficient

  48. The Wrong 20-Yard Line Near the other endzone (the right end zone): • All volatility is price-driven • Market pays no attention whatsoever to fundamentals • Market, in the short-term, is in a state of complete and unpredictable chaos

  49. The Wrong 20-Yard Line As we move from the left to the right end zone: • Models based on rational economic behavior begin to lose power • As you cross midfield, behavioral models begin to dominate • Note: under these models, markets have biased reactions to real economic events, but they do still react to real economic events • As you move to the extreme right, even behavioral models lose power, and the market reacts only to its own events (at least in the short run) • Aerialists pay no attention to the wire whatsoever

  50. The Wrong 20-Yard Line Active managers would perform best when the market is near the 60-yard line: • Too close to the efficient markets end zone, and there are no inefficiencies for the active managers to exploit • Too close to the inefficient markets end zone, and unpredictable, price-driven volatility begins to dominate, making it nearly as impossible for active managers to beat the market as at the right end zone • Best way to do well in this case would be by buying future dividend streams at relatively cheap prices, cf., Warren Buffett • Lack of clear success by active managers indicates only that we are near one of the end zones, not which one we are near

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