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Behavioral Finance

Behavioral Finance. Economics 437. Q-Group Conference, Apr 2-4. “Bubbling with Excitement” by Terrance Odean (U Cal Berkeley) Odean was the first to find the “disposition effect” in actual data of investors

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Behavioral Finance

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  1. Behavioral Finance Economics 437

  2. Q-Group Conference, Apr 2-4 • “Bubbling with Excitement” by Terrance Odean (U Cal Berkeley) • Odean was the first to find the “disposition effect” in actual data of investors • Experiment conducted with 9 students: Each given money and stock, 15 periods, dividend each period is either 0, 8, 28, 60) each with ¼ probability every period. Expected value of the asset is $ 24 per period. At the beginning 15 times $ 24, then declining to t time 24 (where t is the number of periods remaining) • Tells the story of Red Hat • IPO in Aug 1999 at $ 14 …. Traded later in the day at 52 • By Dec, 1999 traded at 142 ($ 20 billion market cap) • By Summer, 2000 traded at 20, by Jan 2002 traded at 2 • Then three different situations • Exciting 5 min film with happy ending • Boring 5 min history film • Exciting 5 min film from horror movie

  3. Result $ 360

  4. “New Research in Behavioral Finance” by Nicholar Barberis (Yale) • Investors “overweigth” recent experience (Barberis refers to this as “representativeness”…. • Probability weighting • From DeBondt-Thaler-Tversky • Overweights unlikely events • Values “positive skewness” • Three predictions • Investors value “positive skewness” • Mutual fund flows predict momentum in stocks • Realization utility (“neural experiments at Cal Tech)

  5. “What is ‘risk neutral’ Volatility” by Stephen Figlewski (NYU) • Liquidity • How do you define it? • How do you “measure it” in real life • Is it priced? • Fit a treasury curve…look at deviations from the yield curve

  6. Illiquidity During a crisis….more observations Far away from the best fit Maturity

  7. Fitting the treasury yield curve During normal times…very good fit Maturity

  8. Definition of Market Efficiency (Shiller) where

  9. Implications of EMH (“Market Efficiency”) • Stock prices should not be “serially correlated” • There should no “mean reversion” • There should be no “earnings momentum” • Or “stock price momentum” • Or “delayed reaction to news” • In general, no predictability of prices

  10. Definition of absence of serial correlation Let pt-1, pt-2, pt-3, etc. be a series of past prices Now, think about, pt E[ pt | info, pt-1, pt-2, pt-3, etc.] = E[ pt | info] Then, no serial correlation

  11. DeBondt and Thaler: “Does the Stock Market Overreact” (1985) • W – three year loses • L – 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

  12. 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

  13. The End

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