The Impact of Misalignment of Beliefs on the Estimation of the Pricing Kernel

Barone‐Adesi, Giovanni; Fusari, Nicola; Sala, Carlo; Mira, Antonietta

doi:10.2139/ssrn.2720180

Cited by 3 publications

(2 citation statements)

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“…">The traditional method to compute the SDF compares a backward‐looking forecast with a forward‐looking RND, questioning whether the pricing kernel puzzle could be caused by misaligned expectations (see Brown & Jackwerth, 2012; Beare, 2011; Beare & Schmidt, 2016; Carr & Wu, 2003; Grith et al, 2017; Yatchew & Härdle, 2006). While several papers address this information mismatch (see Cuesdeanu & Jackwerth, 2018a; Linn et al, 2018; Sala et al, 2016), we are the first to estimate the real‐world pricing kernel, including both risk‐preferences and behavioral effects, in a consistent forward‐looking framework. Previous studies indirectly attribute to sentiment all deviations between a traditional kernel and the empirical SDF.…”

Section: Introductionmentioning

confidence: 99%

Estimating real‐world probabilities: A forward‐looking behavioral framework

Crisóstomo

2021

Journal of Futures Markets

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We show that disentangling sentiment-induced biases from fundamental expectations significantly improves the accuracy and consistency of probabilistic forecasts. Using data from 1994 to 2017, we analyze 15 stochastic models and risk-preference combinations and in all possible cases a simple behavioral transformation delivers substantial forecast gains. Our results are robust across different evaluation methods, risk-preference hypotheses, and sentiment calibrations, demonstrating that behavioral effects can be effectively used to forecast asset prices. We also implement a trading strategy that shows how behavioral biases can be exploited to generate trading profits. Further analyses confirm that our real-world densities outperform forecasts recalibrated to avoid past mistakes and improve predictive models where risk aversion is dynamically estimated from option prices.

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Section: Introductionmentioning

confidence: 99%

Estimating real‐world probabilities: A forward‐looking behavioral framework

Crisóstomo

2021

Journal of Futures Markets

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“… See Brown and Jackwerth (2012),Beare and Schmidt (2016),Beare (2011),Carr and Wu (2003),Grith, Härdle and Krätschmer (2017), andYatchew and Härdle (2006).4 SeeLinn et al (2018), andSala et al (2016). 5 SeeBliss and Panigirtzoglou (2004),Liu et al (2007),Kang and Kim (2006) andAlonso et al (2009).…”

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confidence: 99%