Simulation-Based Estimation of Contingent-Claims Prices

31 Pages Posted: 2 Jan 2007

See all articles by Peter C. B. Phillips

Peter C. B. Phillips

University of Auckland Business School; Yale University - Cowles Foundation; Singapore Management University - School of Economics

Jun Yu

Singapore Management University - School of Economics; Singapore Management University - Lee Kong Chian School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: January 2007

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

JEL Classification: C15, G12

Suggested Citation

Phillips, Peter C. B. and Yu, Jun, Simulation-Based Estimation of Contingent-Claims Prices (January 2007). Cowles Foundation Discussion Paper No. 1596, Available at SSRN: https://ssrn.com/abstract=954569

Peter C. B. Phillips (Contact Author)

University of Auckland Business School ( email )

12 Grafton Rd
Private Bag 92019
Auckland, 1010
New Zealand
+64 9 373 7599 x7596 (Phone)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States
203-432-3695 (Phone)
203-432-5429 (Fax)

Singapore Management University - School of Economics

90 Stamford Road
178903
Singapore

Jun Yu

Singapore Management University - School of Economics ( email )

90 Stamford Road
178903
Singapore
+6568280858 (Phone)
+6568280833 (Fax)

HOME PAGE: http://www.mysmu.edu/faculty/yujun/

Singapore Management University - Lee Kong Chian School of Business ( email )

469 Bukit Timah Road
Singapore 912409
Singapore

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
167
Abstract Views
1,129
Rank
325,589
PlumX Metrics