One-Factor Asset Pricing

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One-Factor Asset Pricing

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One-Factor Asset Pricing with Stefanos Delikouras (University of Miami) Alex Kostakis Manchester June 2017, WFA (Whistler) Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 1 / 28

Presentation Outline Motivation and Related Literature Generalized Disappointment Aversion SDF Asset Pricing Tests Disappointment Events Robustness Checks Conclusions Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 2 / 28

Motivation Long tradition in asset pricing linking premia to consumption risk C-CAPM: aggregate consumption growth should be a suffi cient statistic for expected returns (Breeden, 1979) Main implication: Risk Premium γcov (r i,t+1, c t+1 ) However, aggregate consumption growth has proved too smooth to generate the empirical equity premium (Mehra and Prescott, 1985) explain the cross-section of equity premia implied Risk Aversion coeffi cient implausibly high (Rabin, 2000) Recent attempts to engineer a more volatile SDF via alternative definitions of consumption risk (Parker and Julliard, 2005, Yogo, 2006, Jagannathan and Wang, 2007, Savov, 2011) have had limited success Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 3 / 28

Motivation Empirical asset pricing literature dominated by multi-factor models since Fama and French (1993) Fishing license: Merton s ICAPM and Ross s APT Factors are typically return-generated and a-theoretical Unsettled debate whether factors proxy macro risks or capture anomalies Proliferation of factors and factor models (3-factor FF, 4-factor FFC, 4-factor HXZ, 5-factor FF...) Serious data mining concerns (Harvey et al., 2016) Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 4 / 28

This Paper Propose a single-factor, consumption-based asset pricing model to explain the cross-section of equity returns Sole factor is an indicator of consumption growth being less than its certainty equivalent, derived from GDA preferences Intuitive interpretation of "bad times" and consumption risk Very good and robust empirical fit for various portfolio sorts and frequencies, comparable to Fama-French multi-factor models Plausible Disappointment Aversion coeffi cients Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 5 / 28

Disappointment Aversion Model is based on Disappointment Aversion preferences (Gul, 1991) Axiomatic framework, but relaxing the independence axiom of EU Asymmetric treatment of losses vs gains à la Kahneman and Tversky (1979) & Benartzi and Thaler (1995) kink in the utility function But reference point is endogenously defined (certainty equivalent of lottery) rather than imposed ad hoc Can resolve Allais paradox and explain Samuelson s famous gamble Investor exhibits first-order risk aversion (Segal and Spivak, 1990) unlike the traditional second-order risk aversion framework Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 6 / 28

Generalized Disappointment Aversion Functional form for GDA preferences (Routledge and Zin, 2010): u(µ(p)) = x i X p (x i ) u (x i ) θ x i δµ(p) p (x i ) (u (δµ(p)) u (x i )) where µ(p) is the certainty equivalent for lottery p, θ is the DA coeffi cient, and δ is the multiplier of µ(p) Interpretation: Investor imposes a penalty proportional to θ on lottery outcomes below the disappointment threshold Can be combined with separable or non-separable utility functions Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 7 / 28

Related Studies with (G)DA Preferences Portfolio Choice: Ang, Bekaert and Liu (2005) Khanapure (2012) Dahlquist, Faragó and Tédongap (2017) Equity premium: Epstein and Zin (2001) Routledge and Zin (2010) Bonomo, Garcia, Meddahi and Tédongap (2011) Dolmas (2014) Cross-sectional asset pricing: Ostrovnaya, Routledge and Zin (2006) Faragó and Tédongap (2017) Delikouras (2017) Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 8 / 28

Routledge and Zin (2010) SDF Starting point: GDA intertemporal SDF of Routledge and Zin (2010) Mt+1 GDA = Epstein-Zin terms {}}{ [ ] α ρ [ ( ) ρ 1 Ct+1 β C t }{{} C-CAPM V t+1 µ t (V t+1 ) ] 1 + θ1{v t+1 δµ t } 1 + θδ α E t [1{V t+1 δµ t }] }{{} Disappointment Aversion correction µ t (V t+1 ) : Certainty Equivalent of Lifetime Utility V t+1 α : Risk Aversion coeffi cient, 1/(1 ρ) : EIS, δ : multiplier of µ t θ : Disappointment Aversion coeffi cient (overweigh losses) 1{V t+1 δµ t } : Indicator of disappointment events Nested preferences: θ = 0 Epstein-Zin preferences θ = 0 & α = ρ Power utility preferences Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 9 / 28

GDA-I SDF 1 Homoscedastic AR(1) consumption growth with normal shocks 2 Disappointment Aversion only (α = ρ = 1) Derive GDA-I SDF for excess returns: { conditional mean }} { st dev {}} { t+1 θ1{ c t+1 µ c (1 φ c ) + φ c c t + d 2 }{{ 1 φ 2 c σ c } } certainty equivalent M GDA I Threshold for disappointment event depends on deviation from expected consumption growth controlled by d 2 Consumption growth covariance risk is not priced GDA-I is an indicator function of consumption growth being less than its certainty equivalent bi-modal SDF Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 10 / 28

Comparison with Popular SDFs C-CAPM SDF: CAPM SDF: NBER SDF: M C CAPM t+1 γ c t+1 M CAPM t+1 b m R x m,t+1 M NBER t+1 λ1{> 4 NBER recession months in a year} Fama-French 3-factor SDF: M FF 3 t+1 b mr x m,t+1 b SMB R SMB,t+1 b HML R HML,t+1 Fama-French 5-factor SDF: M FF 5 t+1 b mr x m,t+1 b SMB R SMB,t+1 b HML R HML,t+1 b RMW R RMW,t+1 b CMA R CMA,t+1 Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 11 / 28

Data Sample period: 1933-2012 BEA consumption of services and non-durables Normalized by population and PCE price index NBER recession periods K. French s online data library 6 & 25 & 100 Size/BM portfolios 25 Size/OP & 25 Size/INV portfolios (post 64) 10 LTR portfolios 10 E/P portfolios (post 53) Fama-French factors Corporate bond and equity index option portfolios Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 12 / 28

Estimation Need to specify consumption growth moments to identify disappointment events and test GDA-I model Fit the empirical consumption growth moments jointly with Euler equations for excess portfolio returns for each cross-section via GMM: E[ c t ] µ c E[ ct 2 ] µ 2 c σ2 c E[ c t c t 1 ] µ 2 c φ c σ2 c E [ (R i,t R 1y,t ) ( 1 E [ M GDA I t ] + M GDA I t = 0 )] Weighting matrix ensures consumption growth moments matching Competing asset pricing models estimated via GMM using identity weighting matrix Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 13 / 28

Annual 25 Size/BM Portfolios: Estimates Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 14 / 28

Annual 25 Size/BM Portfolios: Estimates Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 15 / 28

Annual 25 Size/BM Portfolios: Estimates Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 16 / 28

Annual 25 Size/BM Portfolios: Fit 0.25 a) GDA I 0.25 b) CCAPM 0.25 c) FF3 sdf 0.25 d) NBER sdf sample risk premia 0.2 0.15 0.1 0.05 0.2 0.15 0.1 0.05 0.2 0.15 0.1 0.05 0.2 0.15 0.1 0.05 0 0 0.1 0.2 fitted risk premia 0 0 0.1 0.2 fitted risk premia 0 0 0.1 0.2 fitted risk premia 0 0 0.1 0.2 fitted risk premia Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 17 / 28

consumption growth Disappointment Years {1937, 46, 48, 56, 73, 79-80, 90, 99, 2007-08, 2011-12} 7% 6% 4% 4% 3% 2% 1% 0-1% 1940 1950 1960 1970 1980 1990 2000 2010 log-consumption growth GDA-I threshold Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 18 / 28

Disappointment Years Characteristics Full Sample Disappointment Yrs Non Disappointment Yrs Market Premium 9.16% 3.05% 11.52% SMB Premium 2.12% 5.68% 3.63% HML Premium 9.02% 4.23% 9.95% S&P 500 Daily St. Dev. 15.43% 19.22% 14.70% Term spread 1.62% 0.99% 1.74% Real Consumption growth 2.21% 0.07% 2.65% Earnings growth 11.23% 3.20% 12.78% Net Equity Expansion 1.52% 0.77% 1.66% cay 0.00% 0.16% 0.03% Change in unemployment, t+1 0.06% 0.97% 0.10% Δ% in Consumer Confidence 0.16% 7.49% 1.80% Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 19 / 28

Monthly 25 Size/BM Portfolios: Estimates Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 20 / 28

Monthly 25 Size/BM Portfolios: Estimates Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 21 / 28

Monthly 25 Size/BM Portfolios: Estimates Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 22 / 28

Monthly 25 Size/BM Portfolios: Fit 0.02 a) GDA I sdf 0.02 b) CCAPM 0.02 c) FF3 sdf 0.02 d) NBER sdf sample risk premia 0.015 0.01 0.005 0.015 0.01 0.005 0.015 0.01 0.005 0.015 0.01 0.005 0 0 0.01 0.02 fitted risk premia 0 0 0.01 0.02 fitted risk premia 0 0 0.01 0.02 fitted risk premia 0 0 0.01 0.02 fitted risk premia Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 23 / 28

Why does GDA-I SDF work? GDA-I SDF implies that an asset s premium should be a linear function of its losses during disappointment events The standard asset pricing equation yields for GDA-I SDF: E[R i,t R f,t ] = Cov (R i,t R f,t, M t ) E[R i,t R f,t ] = θe[1 t] 1 θe[1 t ] E[(R i,t R f,t ) 1 t = 1] GDA-I SDF successfully aligns portfolio premia with their disappointment betas Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 24 / 28

sample premia Premia & Disappointment Betas: 25 Size/BM Portfolios 0.3 R 2 = 0.901 0.25 0.2 0.15 0.1 0.05-0.45-0.4-0.35-0.3-0.25-0.2-0.15-0.1 betas with the GDA-I factor Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 25 / 28

Robustness Checks GDA-I SDF performs very well with: 1 Other equity cross-sections (Size/OP, Size/INV, LTR, E/P, Joint) 2 Great Depression, pre-crisis & post-wwii periods 3 Recursive estimation of disappointment events 4 Value-weighted portfolios 5 Quarterly data 6 Two-stage GMM estimation 7 Other asset classes (corporate bond & equity index option portfolios) Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 26 / 28

Further Robustness Checks 1 Weak Identification? Disappointment betas are statistically significant and exhibit substantial cross-sectional dispersion 2 Sensitivity to Disappointment Threshold? Explanatory power remains strong even if we use d 2 = d 2 ± std error( d 2 ) to determine new disappointment threshold & events 3 Spurious Explanatory Power? 1m placebo indicators confirm that the success of GDA-I SDF is not spuriously driven by its functional form Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 27 / 28

Conclusions Propose a simple SDF to explain the cross-section of equity returns GDA-I SDF consists of an indicator function of consumption growth being less than its certainty equivalent Founded on (G)DA preferences of Gul & Routledge and Zin Yields very good empirical fit and plausible DA coeffi cients for various cross-sections Question the ability of second-order risk aversion (smooth utility functions) to explain the cross-section of equity returns Support consumption-based asset pricing but highlight the importance of downside consumption risk Alex Kostakis (Manchester) One-Factor Asset Pricing June 2017, WFA (Whistler) 28 / 28