Articlediamond2005

Monte Carlo Simulation with Asymptotic Method

40 citations0/0 files storedJOURNAL OF THE JAPAN STATISTICAL SOCIETY

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Stochastic processes and financial applications Simulation Techniques and Applications Markov Chains and Monte Carlo Methods

Abstract

We shall propose a new computational scheme with the asymptotic method to achieve variance reduction of Monte Carlo simulation for numerical analysis particularly for finance. We not only provide general scheme of our method, but also show its effectiveness through numerical examples such as computing optimal portfolio and pricing an average option. Finally, we show mathematical validity of our method.

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References

1983Stochastic Differential Equations and Diffusion Processes 2003Monte Carlo Methods in Financial Engineering 1992Bond Pricing and the Term Structure of Interest Rates: A New Methodology for Contingent Claims Valuation 1990A pricing method for options based on average asset values 1996The law of the Euler scheme for stochastic differential equations 2003A Monte Carlo Method for Optimal Portfolios 1991A generalized clark representation formula, with application to optimal portfolios 1991Malliavin calculus for processes with jumps

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2012Approximations for Asian options in local volatility models 2009Computation in an Asymptotic Expansion Method 2011Pricing barrier and average options in a stochastic volatility environment.2012Pricing Multi-Asset Cross Currency Options 2010Pricing average options on commodities 2015Asymptotic Expansion Approach in Finance

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