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Parameter Estimation Risk in Asset Pricing and Risk Management: A Bayesian Approach

Tunaru, Radu, Zheng, Teng (2017) Parameter Estimation Risk in Asset Pricing and Risk Management: A Bayesian Approach. International Review of Financial Analysis, 53 . pp. 80-93. ISSN 1057-5219. (doi:10.1016/j.irfa.2017.08.004) (KAR id:62961)

Abstract

Parameter estimation risk is non-trivial in both asset pricing and risk management. We adopt a Bayesian estimation paradigm supported by the Markov Chain Monte Carlo inferential techniques to incorporate parameter estimation risk in financial modelling. In option pricing activities, we find that the Merton’s Jump-Diffusion (MJD) model outperforms the Black-Scholes (BS) model both in-sample and out-of-sample. In addition, the construction of Bayesian posterior option price distributions under the two well-known models offers a robust view to the influence of parameter estimation risk on option prices as well as other quantities of interest in finance such as probabilities of default. We derive a VaR-type parameter estimation risk measure for option pricing and we show that parameter estimation risk can bring significant impact to Greeks’ hedging activities. Regarding the computation of default probabilities, we find that the impact of parameter estimation risk increases with gearing level, and could alter important risk management decisions.

Item Type: Article
DOI/Identification number: 10.1016/j.irfa.2017.08.004
Uncontrolled keywords: Parameter estimation risk; Bayesian option pricing; Greeks; Probability of default JEL classification G13; G17; G32; C53
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Radu Tunaru
Date Deposited: 29 Aug 2017 08:18 UTC
Last Modified: 09 Dec 2022 09:03 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/62961 (The current URI for this page, for reference purposes)

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