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Jun 18

Simulation-Based Estimation of Contingent-Claims Prices

Posted by abiao at 10:56 | Code » Matlab | Comments(0) | Reads(8534)
Please allow me to share an interesting paper I came across this morning, Simulation-Based Estimation of Contingent-Claims Prices, the main point of this paper is to use Monte Carlo simulation, along with Maximum likelihood estimation (MLE), to reduce the biases caused by MLE method alone,
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.
This paper proposes a simulation-based method. When it is used in connection with ML, it can improve the finite-sample performance of the ML estimator while maintaining its good asymptotic properties. The method is implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond and bond option pricing
model. It is especially favored when the bias in ML is large due to strong persistence in the data or strong nonlinearity in pricing functions. Monte Carlo studies show that the proposed procedures achieve bias reductions over ML estimation in pricing contingent claims when ML is biased. The bias reductions are sometimes accompanied by reductions in variance. Empirical applications to U.S. 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.

Download the paper and accompanying matlab code at http://www.mysmu.edu/faculty/yujun/research.html

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