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Behavioral Finance Economics 437.

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Presentation on theme: "Behavioral Finance Economics 437."— Presentation transcript:

1 Behavioral Finance Economics 437

2 Data in Fama and French 1962 -1989 data
Book Value (leverage and price/earnings) at previous year end Returns starting on July 1 of the following year (also use the market equity as of July 1 for size, but use market equity at previous year end for B/M calculation) Calculate monthly returns Each month the cross-section of returns is regressed on explanatory variables. Prior research used “portfolio betas”; F-F use individual stocks Sort stocks into “size deciles” Sort each size decile into 10 portfolios based on beta Calculate equal weighted monthly returns on the portfolios for the next 12 months (from July to June).

3 Results on Beta Portfolios in size deciles (without breaking them into 10 beta portfolios) show a relationship between beta and return Large size means lower beta and lower returns When size deciles are subdivided into beta ranked decile portfolios Larger size firms have lower returns “no relation between average return and beta”

4 Results on Book/Market
What is book to market Book is firm net worth reported on 10-Ks Market is: shares outstanding times price Book/market is positively related to returns Size still matters but B/M is much more important B/M swamps leverage and E/P Leverage: book or market leverage? January “slopes” twice slopes of other months Overall largest decile book to market beats smallest decile book to market by 1.53 % per month

5 Significance of F-F Provided a simple rule for investing success
Seems to contradict Semi-Strong EMH Made “respectable’ earlier work that provided simple, but successful investment rules DeBondt and Thaler, for example

6 DeBondt-Thaler 1984 “Over-Reaction” Hypothesis Suggests that:
After a period of “over-reaction,” markets “revert” back and go the other way. Stocks that have done well in the past, do poorly in the future Stocks that done poorly in the past, do well in the future Their article is designed to test whether or not “mean reversion” is true.

7 Data NYSE data Begin with three year lookback in Dec 1932
Jan 1926 through December 1982 Monthly return data Begin with three year lookback in Dec 1932 Monthly data from Jan 1930 through Dec 1932 36 months or three years data Form portfolios of L(osers) and W(inners) Then see how they do for the next three years

8 DeBondt and Thaler: “Does the Stock Market Overreact” (1985)
L – three year loses W – three year winners Question: How do the W’s do in the next three years? How do the L’s do in the next three years? Other things worth noting Almost all of the impact is in January When the W portfolios are formed, they have very high P/E ratios, the L portfolios have low P/E ratios at the time of formation

9 DeBondt-Thaler conclusions
Definite evidence of mean reversion (a form of serial correlation): L portfolios consistently outperform W portfolios 19.6 % better than the market after end of 3 years W portfolios consistently underperform the market 5 % less than the market after end of 3 years

10 Interesting facts Most of the excess returns are in January
Loser effect more pronounced: Losers earned 19.6 % more than the market Winners earn 5.0 % less than the market Loser portfolio minus Winner portfolio return = 24.6 %!!!!! Most of the return difference is during 2nd and 3rd year Larger loses become larger winners; larger winners become larger losers

11 The End


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