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Price and Earnings Momentum: An Explanation Using Return Decomposition

Price and Earnings Momentum: An Explanation Using Return Decomposition. Qinghao Mao K.C. John Wei Hong Kong University of Science and Technology NTUICF Dec 2010. Outline. Introduction Hypotheses Empirical Tests Summary. Motivation.

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Price and Earnings Momentum: An Explanation Using Return Decomposition

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  1. Price and Earnings Momentum: An Explanation Using Return Decomposition Qinghao Mao K.C. John Wei Hong Kong University of Science and Technology NTUICF Dec 2010

  2. Outline • Introduction • Hypotheses • Empirical Tests • Summary

  3. Motivation • Explain sources of momentum profits by distinguishing rational and behavioral explanations. • Do past winners appear to be riskier than past losers? • Do return innovations differ systematically across momentum portfolios? • How does price momentum differ from earnings momentum? • Return decomposition quantifies return innovations due to expected price change, cash flow news and discount rate news.

  4. Momentum Strategies • Price and Earnings Momentum • Price momentum: Jegadeesh and Titman (93), (01) • Earnings momentum: Ball and Brown (68), Bernard and Thomas (90) • Comparison: Chan, Jegadeesh and Lakonishok (96), Chordia and Shivakuma (06) • Explanations • Rational: Berk, Green and Naik (99), Johnson (02) • Behavioral: Daniel, Hirshleifer and Subrahmanyam (98), Barberis, Shleifer and Vishny (98)

  5. Return Decomposition • VAR approach • Campbell and Shiller (98), Campbell (91) • Accounting valuation models • Chen and Zhao (09), (10) VAR is subject to the predictability of state variables and sensitive to which state variables are chosen. Valuation models directly apply analyst earnings forecasts to quantify cash flow news. The current approach has been used to correct the traditional wisdom on what drives stock price movements.

  6. Example • A stock is expected to be liquidated with payoff of 2.42 in two periods and r=10%. • After one period, the expected payoff drops to 2.30 and r=15%.

  7. Expected return (ex ante return): cost of equity • Return innovations: due to earnings news or discount rate news

  8. Hypotheses • Conrad and Kaul (98): the expected return component post-formation is positive while DRret and CFret are zero. • Johnson (02): the expected return component post formation is positive, pre-formation CFret is positive and DRret is negative. • The behavioral models (DHS(98), BSV(98), Hong and Stein(99)): the CFret post-formation is positive.

  9. Results Preview

  10. The Sample • Sample period 1985-2008 • I/B/E/S EPS forecasts and long term growth rate forecasts • CRSP monthly stock return file • Compustat • On average, 1687 firms per year

  11. Return decomposition • Stock price is a function of earnings per share, growth rate, book equity value and discount rate. • We use four accounting valuation models to compute implied discount rates each month. • Then we calculate Eret, CFret, DRret respectively applying the cashflow inputs, discount rate inputs to the valuation models. • Four accounting valuation models are used, for example Claus and Thomas (01):

  12. Return Components

  13. Momentum Profits

  14. Momentum Profits

  15. Characteristics at portfolio formation • The discount rate at the formation time. • The contribution from return components to the pre formation returns. • The difference between price and earnings momentum.

  16. CharacteristicsPrice momentum portfolios • Price momentum: • Winners experience higher CFret and DRret in the pre holding period. • Winners have lower discount rate.

  17. CharacteristicsEarnings momentum portfolios • Earnings momentum: • Winners experience higher CFret but not DRret pre formation. • Winners have lower discount rate.

  18. Long term reversal

  19. Calendar time properties • Time series variations in momentum profits could depend on, for example, market state, investor sentiment. • We look at return components and explore why momentum profits vary over time. • CFret, DRret, Eret.

  20. Calendar time properties • Time Series price movements are dominated by DRret. • Positive cross sectional return spreads are coming from positive spreads in Cfret.

  21. Momentum and information uncertainty • Information uncertainty is related to the degree of behavioral biases. • Momentum is more pronounced: Zhang (06). • More underreactions and price anchoring would cause higher spreads in cashflow returns and discount rate returns. • Information uncertainty measures: firm age, operating cash flow volatility, stock return volatility.

  22. Price momentum and information uncertainty

  23. Conclusion In this paper, we test rational and behavioral explanations for price and earnings momentum applying a unified framework using return decomposition. We find: • Momentum profits are mainly contributed by the persistent cash flow return component. • Earnings momentum does not display long term reversal and it does not sort on past discount rate return. Overall, the results support the behavioral explanation that the market incorporates cash flow information too slowly which drives momentum profits.

  24. Thank you.

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