Simulation-based Estimation of Contingent-claims Prices

Peter Phillips and Jun Yu

No 1596, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: A new methodology is proposed to estimate theoretical prices of financial contingent-claims whose values are dependent on some other underlying financial assets. In the literature the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but is not necessarily the best method in finite samples. The present paper proposes instead a simulation-based method that improves the finite sample performance of the ML estimator while maintaining its good asymptotic properties. The methods are implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond pricing model, but have wider applicability. Monte Carlo studies show that the proposed procedures achieve bias reductions over ML estimation in pricing contingent claims. The bias reductions are sometimes accompanied by reductions in variance, leading to significant overall gains in mean squared estimation error. Empirical applications to US treasury bills highlight the differences between the bond prices implied by the simulation-based approach and those delivered by ML. Some consequences for the statistical testing of contingent-claim pricing models are discussed.

Keywords: Bias reduction; Bond pricing; Indirect inference; Option pricing; Simulation-based estimation (search for similar items in EconPapers)
JEL-codes: C15 G12 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2007-01
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-sea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Simulation-Based Estimation of Contingent-Claims Prices (2009)
Working Paper: Simulation-based Estimation of Contingent-claims Prices (2008)
Working Paper: Simulation-based Estimation of Contingent Claims Prices
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