A Smoothed Perturbation Analysis of Parisian Options

In this technical note we provide a smoothed perturbation analysis (SPA) estimator of the sensitivity of a discrete time Parisian option with respect to the barrier level. The analysis put forward is of interest in a broader context than that of exotic options as we provide an SPA analysis for a problem where the critical event for the SPA estimator is based on an entire sample path, which is a novelty in the literature. Numerical examples illustrate the performance of the estimator.

[1]  Vu,et al.  European Options Sensitivities via Monte Carlo Techniques , 2013 .

[2]  E. Benhamou Optimal Malliavin Weighting Function for the Computation of the Greeks , 2003 .

[3]  Pierre-Louis Lions,et al.  Applications of Malliavin calculus to Monte Carlo methods in finance , 1999, Finance Stochastics.

[4]  Michael Schr oder,et al.  Brownian excursions an Parisian barrier options: a note , 2002 .

[5]  Pricing Parisians and barriers by hitting time simulation , 2008 .

[6]  B. Heidergott,et al.  A Smoothed Perturbation Analysis Approach to Parisian Options , 2013 .

[7]  L. Jeff Hong,et al.  Estimating Quantile Sensitivities , 2009, Oper. Res..

[8]  Céline Labart,et al.  Pricing Double Barrier Parisian Options Using Laplace Transforms , 2009 .

[9]  Yuh-Dauh Lyuu,et al.  Unbiased and efficient Greeks of financial options , 2011, Finance Stochastics.

[10]  P. Glasserman,et al.  Estimating security price derivatives using simulation , 1996 .

[11]  Michael Schröder Brownian excursions and Parisian barrier options: a note , 2002 .

[12]  P. Boyle,et al.  Monte Carlo methods for pricing discrete Parisian options , 2009 .

[13]  Michael C. Fu,et al.  Conditional Monte Carlo , 1997 .

[14]  M. Fu What you should know about simulation and derivatives , 2008 .

[15]  Jian-Qiang Hu,et al.  Conditional Monte Carlo: Gradient Estimation and Optimization Applications , 2012 .

[16]  Pierre-Louis Lions,et al.  Applications of Malliavin calculus to Monte-Carlo methods in finance. II , 2001, Finance Stochastics.

[17]  Michael A. Zazanis,et al.  Convergence Rates of Finite-Difference Sensitivity Estimates for Stochastic Systems , 1993, Oper. Res..

[18]  Paul Glasserman,et al.  Monte Carlo Methods in Financial Engineering , 2003 .

[19]  L. Jeff Hong,et al.  Kernel Estimation of the Greeks for Options with Discontinuous Payoffs , 2011, Oper. Res..