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This summary delves into the scheduling and grading issues in the upcoming Behavioral Finance course with Prof. Burton, focusing on the critical concepts of earnings and price momentum. Key studies by Ball-Brown and Jegadeesh-Titman are analyzed, discussing how the market tends to underreact to earnings surprises and the implications for investment strategies. Moreover, the course highlights the performance of winner and loser portfolios, emphasizing the superiority of earnings momentum over price momentum in driving investment outcomes. A multi-factor model is proposed for optimizing portfolio strategies.
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Behavioral Finance Economics 437
Scheduling Issues • Next two weeks, Prof Burton is not traveling • Grading review (of 2nd mid-term): Monroe Basement, 3:30 – 6:30 on Tuesday, April 22nd
Earnings or Price? Momentum • Earning Earnings or Price? • “Under-reaction” • Ball-Brown • Price Earnings or Price? • Jegadeesh-Titman
Ball & Brown 1986 • Market “underreacts” to earnings surprises • Article generally ignored until Jagdeesh-Titman • Time span suggests that Ball-Brown effect may be the same thing as Jagdeesh-Titman
Jegadeesh and Titman (1993) • Relative strength strategies, sometimes called “Earnings or Price?” strategies • Find past winners and and past losers (using 3 to 12 month holding periods) generate gains (winners gain; losers lose) • Construct W portfolio and L portfolio • W-L (using 6 month periods) earns more than 12 % better than market portfolio • Longer term portfolios do best in next 12 months • Interpretation in “event time” • Doesn’t work in January
Chan, Jegadeesh, Lakonishok 1996 • Is it earnings? Is it price? • They 7.7 percent six month gap between winner portfolios and loser portfolios using price momentum. • Conclusion (page 1709): “ In general, the price momentum effect tends to be stronger and longer-lived than the earnings momentum effect.”
Chordia-Shivakumar, 2006 • Is it “pricing momentum” or “earnings momentum” that drives the “under-reaction” phenomenon? • Conclude the earnings momentum is the key factor. • Price momentum variables are a “noisy proxy” for earnings momentum
Haugen-Baker, 1996 • Great summary of the literature • A Grand Synthesis • Use multi-factor model to create a “generalized” value portfolio • Incorporate J-T effects • 20 percent outperformance for H-B synthesis • Data used from five countries: France, Germany, Japan, UK, US
Hanna-Ready, 2005 • Dispute H-B results due to monthly turnover (40 percent) in HB rebalancing (causes high transaction costs) • Conclude that six month rebalancing of F-F portfolios is best • Most of H-B results come from J-T. J-T results fall if transaction costs considered • Cannot explain why F-F does so well
What about January? • Total returns over decades come mostly in January • F-F, D-T, J-T results all peculiar in January • Two January effects • The above impact • January as a predictor of the yearly results