Price and Earnings Momentum: An Explanation Using Return Decomposition

Qinghao MaoK.C. John Wei

Hong Kong University of Science and TechnologyNTUICF Dec 2010

Outline

• Introduction

• Hypotheses

• Empirical Tests

• Summary

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.

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)

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.

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%.

2

1.22

2

2.21.2

2

2.2

2

2

2%151

3.21.2

%101

3.22.2

%101

42.22

%)101(

42.22

DRretCFretEretR

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

news

1

1111

1

111

1

1

1

11

1

1*

)1,,(),,(

),,(),,(

),,(),,(

)1,,(),,(

t

tttt

t

tttt

t

tttt

t

tttt

t

ttt

P

tdrcfftdrcffEret

P

tdrcfftdrcffDRret

P

tdrcfftdrcffCFret

P

tdrcfftdrcff

P

PPR

EretDRretCFretR

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.

Results Preview

-5 -4 -3 -2 -1 0 1 2 3 4 5 6

-10

-5

0

5

10

15

20

Price momentum

retCFretDRretEret

month

ret

-5 -4 -3 -2 -1 0 1 2 3 4 5 6

-3

-2

-1

0

1

2

3

4

5

Earnings momentum

retCFretDRretEret

month

ret

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

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):

545

5

1

1*

)1()(

)1()(

)1( ctltct

lttctt

ii

ct

itctittt RgR

gBRFEPS

R

BRFEPSBP

Return Components

N Mean Std dev Max p99 Median p1 Min

CFret 449175 -0.008 0.150 0.900 0.509 0.000 -0.570 -0.900

DRret 449175 0.011 0.192 0.900 0.647 0.003 -0.540 -0.900

Eret 449175 0.009 0.003 0.049 0.017 0.008 0.003 0.000

Ret 449175 0.012 0.135 1.514 0.415 0.009 -0.349 -0.930

CFret DRret Eret Ret

CFret 1.000 -0.756 0.034 0.086

(std) 0.000 0.006 0.003 0.003

DRret -0.756 1.000 -0.162 0.569

(std) 0.006 0.000 0.005 0.007

Eret 0.034 -0.162 1.000 -0.184

(std) 0.003 0.005 0.000 0.006

Ret 0.086 0.569 -0.184 1.000

(std) 0.003 0.007 0.006 0.000

Summary statistics for CFret, DRret, Eret and total returns (Ret )

Correlations between CFret, DRret, Eret and Ret

Momentum Profits

Panel A:Price momentumRet CFret DRret Eret

D1(lowest) 0.74 -3.65 3.43 0.96D2 0.94 -2.14 2.18 0.91D3 1.01 -1.49 1.62 0.88D4 1.08 -1.05 1.27 0.86D5 1.11 -0.70 0.96 0.85D6 1.08 -0.46 0.70 0.84D7 1.03 -0.23 0.43 0.83D8 1.13 0.03 0.27 0.82D9 1.19 0.36 0.01 0.82D10(highest) 1.59 1.25 -0.48 0.82D10-D1 0.85 4.90 -3.90 -0.15t-statistic (2.85) (27.15) (-11.77) (-6.43)

Momentum Profits

Panel B:Earnings momentumRet CFret DRret Eret

D1(lowest) 0.79 -1.75 1.65 0.89D2 0.89 -1.49 1.51 0.88D3 1.02 -1.26 1.41 0.87D4 1.02 -1.09 1.24 0.87D5 1.14 -0.79 1.07 0.86D6 1.15 -0.61 0.91 0.86D7 1.18 -0.41 0.74 0.85D8 1.20 -0.44 0.80 0.84D9 1.23 -0.23 0.63 0.83D10(highest) 1.21 0.02 0.39 0.81D10-D1 0.42 1.77 -1.27 -0.08t-statistic (2.99) (16.02) (-6.93) (-8.86)

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.

CharacteristicsPrice momentum portfolios

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

Panel A-Price momentum

momr Ret CFret DRret Eret R Gr SUE

1 -7.19 -4.33 -3.84 0.98 0.13 0.20 -1.06

2 -3.17 -2.27 -1.81 0.91 0.12 0.17 -0.29

3 -1.47 -1.47 -0.88 0.88 0.11 0.16 -0.05

4 -0.25 -1.01 -0.10 0.86 0.11 0.15 0.13

5 0.80 -0.71 0.66 0.85 0.11 0.15 0.31

6 1.76 -0.38 1.30 0.84 0.11 0.15 0.48

7 2.78 -0.05 2.00 0.83 0.10 0.15 0.56

8 3.97 0.29 2.85 0.83 0.10 0.16 0.66

9 5.70 0.80 4.08 0.82 0.10 0.17 0.80

10 10.05 2.08 7.15 0.82 0.10 0.20 0.97

10-1 17.24 6.41 10.99 -0.16 -0.03 0.00 2.04

t (28.66) (31.56) (20.87) (-12.22) (-13.75) (0.43) (23.11)

CharacteristicsEarnings momentum portfolios

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

Panel B-Earnings momentum

momr Ret CFret DRret Eret R Gr SUE

1 -1.00 -2.88 0.98 0.90 0.11 0.16 -4.75

2 -0.14 -2.21 1.18 0.89 0.11 0.15 -0.97

3 0.35 -1.70 1.17 0.88 0.11 0.15 -0.38

4 0.92 -1.07 1.12 0.87 0.11 0.15 -0.07

5 1.50 -0.42 1.06 0.86 0.11 0.16 0.13

6 1.85 -0.16 1.16 0.86 0.11 0.16 0.36

7 2.12 0.12 1.15 0.85 0.11 0.17 0.68

8 2.32 0.31 1.17 0.84 0.11 0.17 1.16

9 2.51 0.51 1.18 0.83 0.10 0.18 1.94

10 2.88 0.97 1.11 0.80 0.10 0.19 4.48

10-1 3.88 3.85 0.14 -0.10 -0.01 0.03 9.22

t (25.62) (30.61) (0.81) (-14.75) (-14.07) (15.28) (36.29)

Long term reversal

Panel A-Price momentum

Strategy/D10-D1 Ret t-statistic CFret t-statistic DRret t-statistic Eret t-statistic

Momentum1-6 0.85 (2.85) 4.90 (27.15) -3.90 (-11.77) -0.15 (-6.43)

Momentum7-12 0.28 (1.18) 1.65 (12.06) -1.30 (-5.03) -0.07 (-3.80)

Momentum13-18 -0.69 (-3.17) -0.15 (-1.03) -0.51 (-2.07) -0.03 (-2.53)

Momentum19-24 0.07 (0.34) -0.14 (-1.01) 0.23 (0.96) -0.03 (-2.22)

Momentum25-36 -0.23 (-1.52) -0.26 (-2.96) 0.07 (0.38) -0.03 (-2.28)

Panel B-Earnings momentum

Strategy/D10-D1 Ret t-statistic CFret t-statistic DRret t-statistic Eret t-statistic

Momentum6-6 0.42 (2.99) 1.77 (16.02) -1.27 (-6.93) -0.08 (-8.86)

Momentum7-12 0.14 (1.07) 0.54 (5.28) -0.34 (-1.99) -0.06 (-7.45)

Momentum13-18 0.12 (0.87) 0.38 (3.83) -0.20 (-1.18) -0.05 (-7.82)

Momentum19-24 -0.02 (-0.19) 0.12 (1.30) -0.09 (-0.67) -0.05 (-7.23)

Momentum25-36 -0.13 (-1.16) -0.13 (-1.31) 0.05 (0.32) -0.05 (-7.44)

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.

Calendar time properties

1985 1990 1995 2000 2005

-10

-8

-6

-4

-2

0

2

4

6

8

10

Price momentum profits

retCFretDRretEret

year

ret

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

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.

Price momentum and information uncertainty

Uncertainty M1 M2 M3 M4 M5 M5-M1 t-statistic

U1 Ret 1.15 1.14 1.06 0.96 1.04 -0.11 (-0.73)

U2 0.98 1.06 1.08 1.09 1.22 0.24 (1.36)

U3 0.90 0.93 1.11 1.14 1.52 0.62 (2.73)

U4 0.82 0.91 1.19 1.22 1.62 0.80 (2.89)

U5 0.52 0.77 0.97 1.20 1.68 1.16 (3.83)

U5-U1 -0.63 -0.37 -0.09 0.24 0.64 1.28 (4.79)

t-statistic (-1.52) (-0.91) (-0.24) (0.64) (1.63) (4.79)

U1 CFret -1.11 -0.55 -0.25 -0.08 0.41 1.52 (12.65)

U2 -1.79 -0.95 -0.45 0.02 0.69 2.48 (17.74)

U3 -2.53 -1.35 -0.70 -0.06 0.95 3.48 (20.25)

U4 -3.20 -1.80 -0.80 -0.08 1.15 4.35 (22.60)

U5 -4.26 -2.51 -1.52 -0.52 1.01 5.26 (22.67)

U5-U1 -3.14 -1.96 -1.26 -0.45 0.60 3.74 (15.34)

t-statistic (-16.63) (-13.97) (-9.60) (-3.20) (3.55) (15.34)

U1 DRret 1.43 0.88 0.52 0.26 -0.14 -1.58 (-7.57)

U2 1.89 1.16 0.69 0.26 -0.27 -2.15 (-9.89)

U3 2.52 1.39 0.95 0.36 -0.24 -2.76 (-10.00)

U4 3.07 1.80 1.11 0.44 -0.35 -3.42 (-10.66)

U5 3.77 2.33 1.57 0.84 -0.18 -3.95 (-10.95)

U5-U1 2.34 1.45 1.05 0.58 -0.04 -2.38 (-6.90)

t-statistic (5.47) (3.44) (2.76) (1.56) (-0.09) (-6.90)

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.

Thank you.