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Anchoring-Adjusted Option Pricing Models

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  • Hammad Siddiqi

Abstract

Relying on a useful starting point and attempting to adjust it appropriately is a robust human decision-making heuristic. Evidence suggests that underlying stock volatility is such a starting point, which is scaled up to estimate call option volatility. The author adjusts the Black-Scholes, Heston, and Bates models for reliance on this starting point. The adjustment mechanism captures several option-return puzzles. The adjusted Black-Scholes generates implied-volatility skew. The adjusted Heston stochastic-volatility model matches the same data better, does so at more plausible parameter values, and generates a steep short-term skew. Furthermore, 2 novel predictions are empirically tested and strongly supported in the data.

Suggested Citation

  • Hammad Siddiqi, 2019. "Anchoring-Adjusted Option Pricing Models," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(2), pages 139-153, April.
    • Handle: RePEc:taf:hbhfxx:v:20:y:2019:i:2:p:139-153
    DOI: 10.1080/15427560.2018.1492922
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    Cited by:

    1. Siddiqi, Hammad, 2022. "Asset Pricing in the Resource-Constrained Brain," MPRA Paper 120526, University Library of Munich, Germany, revised 05 Feb 2024.

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