Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics

Abstract

The book illustrates the application of Monte Carlo methods in financial engineering and economics. The book is organized into five parts: introduction and motivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysis and variance reduction; and applications ranging from option pricing and risk management to optimization. Advanced topics like stochastic differential equations, low-discrepancy sequences, stochastic optimization, numerical methods for stochastic dynamic programming, risk measures, and Markov chain Monte Carlo methods are illustrated with practical applications and working R code is provided

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