The pricing kernel puzzle: survey and outlook

Cuesdeanu, Horatio; Jackwerth, Jens Carsten

doi:10.1007/s10436-017-0317-9

Cited by 51 publications

(20 citation statements)

References 188 publications

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“…Finally, the (discounted) ratio of the risk-neutral divided by the subjective density delivers the pricing kernel. Jackwerth (2004) and Cuesdeanu and Jackwerth (2016) survey the literature and details the different approaches, which tend to confirm the pricing kernel puzzle using slightly different methods and data sets. More recently, Christoffersen, Heston, and Jacobs (2013) and Beare and Schmidt (2014) confirm the pricing kernel puzzle yet again in the data.…”

Section: Introductionmentioning

confidence: 99%

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The pricing kernel puzzle in forward looking data

Cuesdeanu

Jackwerth

2017

Rev Deriv Res

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The pricing kernel puzzle concerns the locally increasing empirical pricing kernel, which is inconsistent with a risk-averse representative investor in a single period, single state variable setting. Some recent papers worry that the puzzle is caused simply by the mismatch of backward looking subjective and forward looking risk-neutral distributions of index returns. By using a novel test and forward looking information only, we generally confirm the existence of a u-shaped pricing kernel puzzle in the S&P 500 options data. The evidence is weaker for tests against an alternative with a risk-neutral investor and for longer horizons.

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Section: Introductionmentioning

confidence: 99%

“…We refer to such models in Section 4.2. For a more comprehensive view on the solutions to the pricing kernel puzzle, see Cuesdeanu and Jackwerth (2016).…”

Section: Introductionmentioning

confidence: 99%

The pricing kernel puzzle in forward looking data

Cuesdeanu

Jackwerth

2017

Rev Deriv Res

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“…The pricing kernel puzzle (see Cuesdeanu and Jackwerth (2018) for a review) is the empirical nding that the pricing kernel or stochastic discount factor is not monotonically decreasing in the market return, but rather increases at the right tail of the distribution, generating a U-shape (e.g., Bakshi et al (2010), Sichert (2018)). Here we show that the Sentiment CAPM predicts a U-shaped pricing kernel and generates the novel prediction that the pricing kernel should have a more pronounced U shape in high sentiment periods.…”

Section: Sentiment and The Pricing Kernel Puzzlementioning

confidence: 99%

An Empirical Study of the Sentiment Capital Asset Pricing Model

Ghazi

Schneider

2020

SSRN Journal

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What is market sentiment? This paper takes a new approach to this question and derives a formula for market sentiment as a function of the risk-free rate, the price/dividend ratio, and the conditional stock market volatility. The formula is derived from a representative agent with a prospect theory probability weighting function. We estimate the model and nd that our sentiment measure correlates positively with the leading sentiment indexes. The model matches the equity premium while generating a low and stable risk-free rate with low risk aversion. We also apply the model to explain other anomalies for the aggregate stock market.

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“…A full exposition of this subject is beyond the scope of this paper. Cuesdano and Jackwerth (2017) provide an excellent and comprehensive review.…”

Section: Figure 1 Goes About Herementioning

confidence: 99%

Risk-Neutral Densities: A Review

Figlewski

2018

Annu. Rev. Financ. Econ.

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Trading in options with a wide range of exercise prices and a single maturity allows a researcher to extract the market's risk-neutral density (RND) over the underlying price at expiration. The RND contains investors’ beliefs about the true probabilities blended with their risk preferences, both of which are of great interest to academics and practitioners alike. With a particular focus on US equity options, I review the historical development of this powerful concept, practical details of fitting an RND to options market prices, and the many ways in which investigators have tried to distill true expectations and risk premia from observed RNDs. I briefly discuss areas of active current research including the pricing kernel puzzle and the volatility surface, and offer thoughts on what has been learned about RNDs so far and fruitful directions for future research.

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The pricing kernel puzzle: survey and outlook

Cited by 51 publications

References 188 publications

The pricing kernel puzzle in forward looking data

The pricing kernel puzzle in forward looking data

An Empirical Study of the Sentiment Capital Asset Pricing Model

Risk-Neutral Densities: A Review

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