Cumulative Prospect Theory, Option Returns, and the Variance Premium

Baele, Lieven; Driessen, Joost; Ebert, Sebastian; Londoño, Juan M.; Spalt, Oliver G.

doi:10.1093/rfs/hhy127

Cited by 54 publications

(40 citation statements)

References 83 publications

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“…For example, Shefrin (2008) finds that the pricing kernel has a U-shape when agents have heterogeneous risk tolerance. Baele, Driessen, Ebert, Londono, and Spalt (2018) observe that pricing kernels under the cumulative prospect theory (CPT) are U-shaped. a specific weighting function -in this case, Prelec's -then an analytical examination of the signs becomes possible.…”

Section: B Risk Premiumsmentioning

confidence: 99%

Beta and Coskewness Pricing: Perspective from Probability Weighting

Shi¹,

Cui²,

Zhou³

2020

Preprint

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The security market line is often flat or downward-sloping. We hypothesize that probability weighting plays a role and that one ought to differentiate between periods in which agents overweight extreme events and those in which they underweight them. Overweighting inflates the probability of extremely bad events and demands greater compensation for beta risk. Underweighting has the opposite effect. Overall, these two effects offset each other, resulting in a flat or slightly negative return--beta relationship. Similarly, overweighting the tails enhances the negative relationship between return and coskewness, whereas underweighting reduces it. We support our theory through an extensive empirical study.

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Section: B Risk Premiumsmentioning

confidence: 99%

Beta and Coskewness Pricing: Perspective from Probability Weighting

Shi¹,

Cui²,

Zhou³

2020

Preprint

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“…is a dummy that takes the value of 1 when the one-monthahead return is above (below) a reference level r ref . Following the convention in the literature (see Feunou, Jahan-Parvar, and Okou (2017), Kilic and Shaliastovich (2018), and Baele, Driessen, Ebert, Londono, and Spalt (2018)), we define downside (upside) stock return variances conditional on the stock price at maturity being below (above) the current stock price (r ref = 0).…”

Section: Definitionsmentioning

confidence: 99%

Variance Risk Premium Components and International Stock Return Predictability

Londoño

2019

Int. finance discuss. pap.

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In this paper, we document and explain the distinct behaviors of U.S. downside and upside variance risk premiums (DVP and UVP, respectively) and their international stock return predictability patterns. DVP, the compensation for bearing downside variance risk, is positive, highly correlated with the total variance premium, and countercyclical, whereas UVP is, on average, borderline positive and procyclical with large negative spikes around episodes of market turmoil. We then provide robust evidence that decomposing VP into its downside and upside components significantly improves domestic and international stock return predictability. DVP is a robust predictor at four to six months and exhibits a hump-shaped pattern, whereas UVP performs the best at very short horizons. These stylized facts highlight the importance of acknowledging asymmetry in equity risk premiums. Hence, in the second part of the paper, we rationalize the economic sources of DVP and UVP in an international dynamic asset pricing model featuring asymmetric and time-varying risk aversion and economic uncertainty in a partially integrated world economy. We show that DVP is mostly driven by the upside movements of risk aversion, whereas UVP loads significantly and negatively on downside economic uncertainty. Moreover, we find that DVP (UVP) transmits to international markets mostly through financial integration (real economic integration).

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“…Barberis and Huang (2008) show that, in a financial market where investors evaluate risk according to prospect theory, probability weighting leads to the prediction that the skewness will be priced. This idea has been used to explain low average returns of IPO stocks (Green and Hwang (2012)), the apparent overpricing of out-of-the-money options and the variance premium (Polkovnichenko and Zhao (2013), Baele et al (2017)), the lack of diversification in household portfolios (Polkovnichenko (2005)) and many other puzzles. On an aggregate scale, De Giorgi and Legg (2012) show that probability weighting is useful in generating a large equity premium -and can do so independently of loss aversion (Benartzi and Thaler (1995)).…”

Section: Introductionmentioning

confidence: 99%