Article2008

What you should know about simulation and derivatives

61 citations0/0 files storedNaval Research Logistics (NRL)

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Simulation Techniques and Applications Stochastic processes and financial applications Modeling and Simulation Systems

Abstract

Abstract Derivatives (or gradients) are important for both sensitivity analysis and optimization, and in simulation models, these can often be estimated efficiently using various methods other than brute‐force finite differences. This article briefly summarizes the main approaches and discusses areas in which the approaches can most fruitfully be applied: queueing, inventory, and finance. In finance, the focus is on derivatives of another sort. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008

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References

2003Monte Carlo Methods in Financial Engineering 1990Options, Futures, and Other Derivative Securities.2002Feature Article: Optimization for simulation: Theory vs. Practice 1991Gradient Estimation via Perturbation Analysis 1999Applications of Malliavin calculus to Monte Carlo methods in finance 1996Estimating Security Price Derivatives Using Simulation 1995Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization by the Score Function Method 1994Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization by the Score Function Method

Cited by

2010Optimization via Simulation Over Discrete Decision Variables 2013Simulation Optimization: A Review on Theory and Applications

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