by David Dreman
48. Roni Michaely, Richard H. Thaler, and Kent Womack, “Price Reactions to Dividend Initiations and Omissions: Overreaction or Drift?” NBER working paper series no. 4778 (Cambridge: National Bureau of Economic Research, 1994).
49. Victor Bernard and Jacob Thomas, “Evidence That Stock Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings,” Journal of Accounting and Economics 13 (1990): 305–340; Victor Bernard and Jacob Thomas, “Post-Earnings-Announcement Drift: Delayed Price Response or Risk Premium?” Journal of Accounting Research 27(S) (1989): 1–36; George Foster, Chris Olsen, and Terry Shevlin, “Earnings Releases, Anomalies, and the Behavior of Security Returns,” Accounting Review 59 (1984): 574–603; Ray Ball and Philip Brown, “An Empirical Evaluation of Accounting Income Numbers.”
50. Jeffery Abarbanell and Victor Bernard, “Tests of Analysts’ Overreaction/Underreaction to Earnings Information as an Explanation for Anomalous Stock Price Behavior,” Journal of Finance 47 (1992): 1181–1206.
51. See, e.g., Tables 11-1 and 12-1.
52. Robert J. Shiller, “Do Stock Prices Move Too Much to Be Justified by Subsequent Changes in Dividends?” American Economic Review 71 (1981): 421–436.
53. Ibid., pp. 432–433.
54. Edward M. Saunders, Jr., “Testing the Efficient Market Hypothesis Without Assumptions,” Journal of Portfolio Management (Summer 1994): 28.
55. Karl R. Popper, The Logic of Scientific Discovery (New York: Basic Books, 1959).
56. David N. Dreman, Psychology and the Stock Market (New York: AMACOM, 1977), p. 221.
57. Alfred W. Stonier and Douglas C. Hague, A Textbook of Economic Theory (London: Longmans, Green, 1953), p. 2.
58. Krugman, “How Did Economists Get It So Wrong?”
59. Joseph Stiglitz, “Information and the Change in the Paradigm in Economics,” Nobel Prize lecture, December 8, 2001, pp. 519–520.
60. Tim Icano, “How Did Economists Fail Us So Badly?” The Wall Street Journal, November 30, 2010.
61. John Cassidy, “The Decline of Economics,” The New Yorker, December 2, 1996, pp. 50–60.
62. Ibid.
63. Ibid.
64. Thomas S. Kuhn, The Structure of Scientific Revolutions (Chicago: University of Chicago Press, 1970).
65. Ibid., p. 23.
66. Ibid., p. 52.
CHAPTER 7: WALL STREET’S ADDICTION TO FORECASTING
1. Woody Guthrie, “Pretty Boy Floyd,” Dust Bowl Ballads, 1939, RCA.
2. P. J. Hoffman, P. Slovic, and L. G. Rorer, “An Analysis of Variance Model for the Assessment of Configural Cue Utilization in Clinical Judgment,” Psychological Bulletin 69 (1968): 338–349.
3. These can combine into fifteen possible two-way interactions, twenty possible three-way interactions, fifteen possible four-way interactions, six possible five-way interactions, and one six-way interaction.
4. L. G. Rorer, P. J. Hoffman, B. D. Dickman, and P. Slovic, “Configural Judgments Revealed,” in Proceedings of the 75th Annual Convention of the American Psychological Association 2 (Washington, D.C.: American Psychological Association, 1967), pp. 195–196.
5. Lewis Goldberg, “Simple Models or Simple Processes? Some Research on Clinical Judgments,” American Psychologist 23 (1968): 338–349.
6. Paul Slovic, “Analyzing the Expert Judge: A Descriptive Study of a Stockbroker’s Decision Processes,” Journal of Applied Psychology 53 (August 1969): 225–263; P. Slovic, D. Fleissner, and W. S. Bauman, “Analyzing the Use of Information in Investment Decision Making: A Methodological Proposal,” Journal of Business 45, No. 2 (1972): 283–301.
7. Goldberg, “Simple Models or Simple Processes?”
8. Paul Slovic, “Behavioral Problems Adhering to a Decision Policy,” IGRF Speech, May 1973.
9. Dale Griffin and Amos Tversky, “The Weighing of Evidence and the Determinants of Confidence,” Cognitive Psychology 24 (1992): 411–435; S. Lichtenstein and B. Fischhoff, “Do Those Who Know More Also Know More About How Much They Know? The Calibration of Probability Judgments,” Organizational Behavior and Human Performance 20 (1977): 159–183.
10. W. Wagenaar and G. Keren, “Does the Expert Know? The Reliability of Predictions and Confidence Ratings of Experts,” in Intelligent Decision Support in Process Environments, ed. E. Hollnagel, G. Maneini, and D. Woods (Berlin: Springer, 1986), pp. 87–107.
11. Stewart Oskamp, “Overconfidence in Case Study Judgments,” Journal of Consulting Psychology 29 (1965): 261, 265.
12. L. B. Lusted, A Study of the Efficacy of Diagnostic Radiology Procedures: Final Report on Diagnostic Efficacy (Chicago: Efficacy Study Committee of the American College of Radiology, 1977).
13. J. B. Kidd, “The Utilization of Subjective Probabilities in Production Planning,” Acta Psychologica 34 (1970): 338–347.
14. M. Neal and M. Bazerman, Cognition and Rationality in Negotiation (New York: Free Press, 1990).
15. C. A. S. Stael von Holstein, “Probabilistic Forecasting: An Experiment Related to the Stock Market,” Organizational Behavior and Human Performance 8 (1972): 139–158.
16. S. Lichtenstein, B. Fischhoff, and L. Phillips, “Calibration of Probabilities: The State of the Art to 1980,” in Judgment Under Uncertainty: Heuristics and Biases, ed. D. Kahneman, P. Slovic, and A. Tversky (Cambridge, England: Cambridge University Press, 1982).
17. G. Keren, “Facing Uncertainty in the Game of Bridge: A Calibration Study,” Organizational Behavior and Human Decision Processes 39 (1987): 98–114; D. Hausch, W. Ziemba, and M. Rubenstein, “Efficiency of the Market for Racetrack Betting,” Management Sciences 27 (1981): 1435–1452.
18. J. Frank Yates, Judgment and Decision Making (Englewood Cliffs, N.J.: Prentice-Hall, 1990).
19. Wall Street Transcript 45, No. 13 (September 23, 1974).
20. Herbert Simon, Models of Man: Social and Rational (New York: Wiley, 1970).
21. The belief that all paranoid patients accentuate certain characteristics in their drawings belongs in the category of psychologists’ old wives’ tales.
22. L. Chapman and J. P. Chapman, “Genesis of Popular but Erroneous Psychodiagnostic Observations,” Journal of Abnormal Psychology (1967): 193–204; L. Chapman and J. P. Chapman, “Illusory Correlations as an Obstacle to the Use of Valid Psychodiagnostic Signs,” Journal of Abnormal Psychology (1974): 271–280.
23. Amos Tversky, “The Psychology of Decision Making,” in Behavioral Finance and Decision Theory in Investment Management, ed. A. Wood, ICFA Continuing Education Series (Stanford, Calif.: Stanford University Press, 1995), pp. 2–6.
24. Ibid.
25. Ibid., p. 6.
26. Ibid.
27. Jennifer Francis and Donna Philbrick, “Analysts’ Decisions as Products of a Multi-Task Environment,” Journal of Accounting Research 31 (Autumn 1993): 216–230.
28. A Ph.D. in astrophysics who worked for the Dreman Foundation.
29. For details, please see David N. Dreman, The New Contrarian Investment Strategy (New York: Random House, 1982), app. I, pp. 303–307.
30. “Vanderheiden Choices Top Other Pickers,” The Wall Street Journal, January 3, 1994, p. R34; John R. Dorfman, “‘Value’ Still Has Value, Says This Quartet of Stock Pickers,” The Wall Street Journal, January 4, 1993, p. R8; John R. Dorfman, “Cyclicals Could Be the Right Way to Ride to New Highs in 1992,” The Wall Street Journal, January 2, 1992, p. R24; John R. Dorfman, “New Year’s Stock Advice in an Icy Economy: Insulate,” The Wall Street Journal, January 2, 1991, p. R22; John R. Dorfman, “The Sweet Smell of Success Might Be One of Caution,” The Wall Street Journal, January 2, 1990, p. R6; John R. Dorfman, “Champion Stock-Picker Is Facing 3 Challengers for Title,” The Wall Street Journal, January 3, 1989, p. R6; John R. Dorfman, “Four Investment Advisors Share Their Favorite Stock Picks for 1988,” The Wall Street Journal, January 4, 1988, p. 6B; John R. Dorfman, “Stock Pickers Nominate Big Gainers for 1987,” The Wall Street Journal, January 2, 1987, p. 4B; Rhonda L. Rundle, “Stock Pickers Make T
heir Picks Public, Betting on Low Inflation, Falling Rates,” The Wall Street Journal, January 2, 1986, p. R4.
31. Just as the theory holds that even professionals cannot outdo the market over time, it also holds that they cannot do substantially worse. After all, it is their very decision making that keeps prices at the proper level in the first place. The surveys, however, give us a different picture from the one assumed by the theorists. The massive underperformance in both up and down markets indicates that their most crucial assumption is inconsistent with a significant body of evidence. The hypothesis is made of straw.
CHAPTER 8: HOW BIG A LONG SHOT WILL YOU PLAY?
1. Ben White, “On Wall Street, Stock Doublespeak; Public, Private Talk at Odds, Papers Show,” The Washington Post, April 30, 2003, p. E01.
2. Gretchen Morgenson, “Bullish Analyst of Tech Stocks Quits Salomon,” The New York Times, August 16, 2002.
3. “The Superstar Analysts,” Financial World, November 1980, p. 16.
4. Ibid.
5. Ibid.
6. David Dreman, “Cloudy Crystal Balls,” Forbes, Vol. 154, Issue 8, October 10, 1994, p. 154; David Dreman, “Chronically Cloudy Crystal Balls,” Forbes, Vol. 152, Issue 8, October 11, 1993, p. 178; David Dreman, “Flawed Forecasts,” Forbes, Vol. 148, Issue 13, December 9, 1991, p. 342; David Dreman, “Hard to Forecast,” Barron’s, March 3, 1980, p. 9; David Dreman, “Tricky Forecasts,” Barron’s, July 24, 1978, pp. 4–5, 16, 18; David Dreman, “The Value of Financial Forecasting: A Contrarian’s Approach,” speech at Fortieth Annual Meeting of the American Financial Association, December 29, 1981. In June 1996, the study was updated again in collaboration with Eric Lufkin, formerly of the Dreman Foundation.
7. David Dreman and Michael Berry, “Analyst Forecasting Errors and Their Implications for Security Analysis,” Financial Analysts Journal 51 (May–June 1995): 30–41.
8. The average of the forecasts of the analysts covering the company. Studies have shown that these estimates are reasonably closely bunched.
9. Before the early 1980s, the database used the forecasts of analysts in the Value Line Investment Survey, which normally were very close to consensus forecasts.
10. We used the database of Abel/Noser Corporation, which contains estimates from the leading forecast services: Value Line prior to 1981, Zacks Investment Research beginning in 1981, and I/B/E/S beginning in 1984. The utilized portion of the database includes 500,000 individual estimates. Eric Lufkin, formerly of the Dreman Foundation, updated the findings for the 1991–1996 period using Abel/Noser Corporation data through 1993Q3 and I/B/E/S estimates thereafter. Thomson First Call provided the data for 1997–2010.
11. The four separate error metrics:
SURPE =(Actual earnings – Forecast) / |Actual earnings|
SURPF =(Actual earnings – Forecast) / |Forecast|
SURP8 =(Actual earnings – Forecast) / Standard deviation of actual earnings, eight quarters trailing
SURPC7 =(Actual earnings – Forecast) / Standard deviation of change in actual earnings, seven quarters trailing.
All the results in the book are for SURPE: forecast error divided by actual earnings.
12. With signs removed. We recorded a total of 189,158 surprises in expansions (104,538 positive and 69,411 negative) and 36,901 surprises in recessions (19,477 positive and 14,941 negative). Note that positive surprises outnumbered negative surprises in both expansions and recessions. Surprises of zero, although not true surprises, have been retained in calculations of all surprises, because they count in assessing analysts’ overall accuracy.
13. Dov Fried and Dan Givoly, “Financial Analysts’ Forecasts of Earnings: A Better Surrogate for Market Expectations,” Journal of Accounting and Economics 4 (1982): 85–107; Patricia C. O’Brien, “Analysts’ Forecasts as Earnings Expectations,” Journal of Accounting and Economics 10 (1988): 53–83; K. C. Butler and L. H. Lang, “The Forecast Accuracy of Individual Analysts: Evidence of Systematic Optimism and Pessimism,” Journal of Accounting Research 29 (1991): 150–156; M. R. Clayman and R. A. Schwartz, “Falling in Love Again: Analysts’ Estimates and Reality,” Financial Analysts Journal (September–October 1994): 66–68; A. Ali, A. Klein, and J. Rosenfeld, “Analysts’ Use of Information About Permanent and Transitory Earnings Components in Forecasting Annual EPS,” Accounting Review 87 (1992): 183–198; L. Brown, “Analysts’ Forecasting Errors and Their Implications for Security Analysis: An Alternative Perspective,” Financial Analysts Journal (January–February 1996): 40–47.
14. J. G. Cragg and B. Malkiel, “The Consensus and Accuracy of Some Predictions of the Growth of Corporate Earnings,” Journal of Finance 23 (March 1968): 67–84.
15. Ibid. You may recall the Meehl studies of clinical psychologists, where it was shown that simple mechanical techniques performed as well as or better than the complex analytical diagnoses in twenty separate studies of trained psychologists. In fact, mechanical prediction formulas have been suggested in a number of fields, primarily psychology, as a direct result of these problems, and they will be a part of the strategies proposed in the following chapters.
16. I. M. D. Little, “Higgledy Piggledy Growth,” Bulletin of the Oxford University Institute of Economics and Statistics (November 1962): 31.
17. I. M. D. Little and A. C. Rayner, Higgledy Piggledy Growth Again (Oxford: Basil Blackwell, 1966).
18. See, e.g., Joseph Murray, Jr., “Relative Growth in Earnings per Share—Past and Future,” Financial Analysts Journal 22 (November–December 1966): 73–76.
19. Richard A. Brealey, An Introduction to Risk and Return from Common Stocks (Cambridge, Mass.: MIT Press, 1968).
20. François Degeorge, Jayendu Patel, and Richard Zeckhauser, “Earnings Management to Exceed Thresholds,” Journal of Business 72, no. 1 (January 1999): 1–33.
21. John Dorfman, “Analysts Devote More Time to Selling as Firms Keep Scorecard on Performance,” The Wall Street Journal, October 29, 1991, p. C1.
22. Ibid. See also Amitabh Dugar and Siva Nathan, “Analysts’ Research Reports: Caveat Emptor,” Journal of Investing 5 (Winter 1996): 13–22.
23. Michael Siconolfi, “Incredible Buys: Many Companies Press Analysts to Steer Clear of Negative Ratings,” The Wall Street Journal, July 19, 1995, p. A1.
24. Ibid., p. 3; Debbie Gallant, “The Hazards of Negative Research Reports,” Institutional Investor (July 1990): 73–80.
25. Siconolfi, “Incredible Buys.”
26. E. S. Browning, “Please Don’t Talk to the Bearish Analyst,” The Wall Street Journal, May 2, 1995, p. C1.
27. Dugar and Nathan, “Analysts’ Research Reports.”
28. Siconolfi, “Incredible Buys.”
29. Ibid.
30. D. Kahneman and A. Tversky, “On the Psychology of Prediction,” Psychological Review 80 (1973): 237–251.
31. D. Kahneman and D. Lovallo, “Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking,” Management Science 39 (January 1993): 1–16.
32. E. Merrow, K. Phillips, and C. Myers, Understanding Cost Growth and Performance Shortfalls in Pioneer Process Plants (Santa Barbara, Calif.: Rand Corporation, 1981).
33. J. Arnold, “Assessing Capital Risk: You Can’t Be Too Conservative,” Harvard Business Review 64 (1986): 113–121.
CHAPTER 9: NASTY SURPRISES AND NEUROECONOMICS
1. For greater detail, see David Dreman, “Don’t Count on Those Earnings Forecasts,” Forbes, Vol. 161, Issue 2, January 26, 1998, p. 110; David Dreman and Michael Berry, “Overreaction, Underreaction, and the Low-P/E Effect,” Financial Analysts Journal 51 (July–August 1995): 21–30; David Dreman, “Nasty Surprises,” Forbes, July 19, 1993, p. 246.
2. We formed the portfolios at the beginning of the first quarter and measured earnings surprises thereafter.
3. Compustat, provided by Standard & Poor’s, is one of the largest stock databases available, giving price, earnings, and other information on more than 34,000 stocks. The studies reported here use the largest 1
,500 companies in the Compustat database traded on the NYSE, AMEX, and NASDAQ exchanges, as measured by the total market value of all shares outstanding at the beginning of each calendar year. (This sample is referred to here as the Compustat 1500.) We use the Compustat database for all price and accounting information.
4. To control for negative earnings, we delete companies with no earnings or negative earnings. We also delete P/E multiples above 45 (over 75 from 1997 on), to control for stocks with nominal earnings as a result of poor quarters. In doing so, we also unfortunately lose some of the most highly favored issues.
5. Ibbotson® SBBI®, 2011 Classic Yearbook: Market Results for Stocks, Bonds, Bills and Inflation, 1926–2010.
6. Jennifer Francis and Donna Philbrick, “Analysts’ Decisions as Products of a Multi-Task Environment,” Journal of Accounting Research 31 (Autumn 1993): 216–230.
7. The T-statistics show that the probability that these results are just chance is less than 1 in 1,000, often much less.
8. Jeffery Abarbanell and Victor Bernard, “Tests of Analysts’ Overreaction/Underreaction to Earnings Information as an Explanation for Anomalous Stock Price Behavior,” Journal of Finance 47 (July 1992): 1181–1208; V. Bernard and J. K. Thomas, “Evidence That Stock Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings,” Journal of Accounting and Economics 13 (1990): 305–340.
9. Eric Lufkin and I came up with findings similar to those of Abarbanell and Bernard. We also discovered that after the surprise quarter, stocks in the high-, low-, and middle-P/E groups (with positive surprises in that quarter) outperformed those stocks in the same groups without positive surprises for the next three quarters. (The same was true for price-to-book-value and price-to-cash-flow measures.) This seems to be caused by additional positive surprises, if the initial surprise was positive—or negative surprises, if the initial surprise was negative—in the three succeeding quarters, again indicating that analysts’ forecasts do not adjust quickly to changing conditions.