Probability Weighting Meets Heavy Tails: An Econometric Framework for Behavioral Asset Pricing
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912721302192128 |
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| author | Deep, Akash Rachev, Svetlozar T. Fabozzi, Frank J. |
| author_facet | Deep, Akash Rachev, Svetlozar T. Fabozzi, Frank J. |
| contents | We develop an econometric framework integrating heavy-tailed Student's $t$ distributions with behavioral probability weighting while preserving infinite divisibility. Using 432{,}752 observations across 86 assets (2004--2024), we demonstrate Student's $t$ specifications outperform Gaussian models in 88.4\% of cases. Bounded probability-weighting transformations preserve mathematical properties required for dynamic pricing. Gaussian models underestimate 99\% Value-at-Risk by 19.7\% versus 3.2\% for our specification. Joint estimation procedures identify tail and behavioral parameters with established asymptotic properties. Results provide robust inference for asset-pricing applications where heavy tails and behavioral distortions coexist. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_16563 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Probability Weighting Meets Heavy Tails: An Econometric Framework for Behavioral Asset Pricing Deep, Akash Rachev, Svetlozar T. Fabozzi, Frank J. Mathematical Finance 91G70, 91G10, 62P05 We develop an econometric framework integrating heavy-tailed Student's $t$ distributions with behavioral probability weighting while preserving infinite divisibility. Using 432{,}752 observations across 86 assets (2004--2024), we demonstrate Student's $t$ specifications outperform Gaussian models in 88.4\% of cases. Bounded probability-weighting transformations preserve mathematical properties required for dynamic pricing. Gaussian models underestimate 99\% Value-at-Risk by 19.7\% versus 3.2\% for our specification. Joint estimation procedures identify tail and behavioral parameters with established asymptotic properties. Results provide robust inference for asset-pricing applications where heavy tails and behavioral distortions coexist. |
| title | Probability Weighting Meets Heavy Tails: An Econometric Framework for Behavioral Asset Pricing |
| topic | Mathematical Finance 91G70, 91G10, 62P05 |
| url | https://arxiv.org/abs/2511.16563 |