Handbook in Monte Carlo simulation: applications in financial engineering, risk management, and economics

Description

Part I Overview and Motivation -- 1 Introduction to Monte Carlo Methods -- 2 Numerical Integration Methods -- Part II Input Analysis: Modeling and Estimation -- 3 Stochastic Modeling in Finance and Economics -- 4 Estimation and Fitting -- Part III Sampling and Path Generation -- 5 Random Variate Generation -- 6 Sample Path Generation for Continuous-Time Models -- Part IV Output Analysis and Efficiency Improvement -- 7 Output Analysis -- 8 Variance Reduction Methods -- 9 Low-Discrepancy Sequences -- Part V Miscellaneous Applications.;10 Optimization -- 11 Option Pricing -- 12 Sensitivity Estimation -- 13 Risk Measurement and Management -- 14 Markov Chain Monte Carlo and Bayesian Statistics. Part I Overview and Motivation -- 1 Introduction to Monte Carlo Methods -- 2 Numerical Integration Methods -- Part II Input Analysis: Modeling and Estimation -- 3 Stochastic Modeling in Finance and Economics -- 4 Estimation and Fitting -- Part III Sampling and Path Generation -- 5 Random Variate Generation -- 6 Sample Path Generation for Continuous-Time Models -- Part IV Output Analysis and Efficiency Improvement -- 7 Output Analysis -- 8 Variance Reduction Methods -- 9 Low-Discrepancy Sequences -- Part V Miscellaneous Applications. 10 Optimization -- 11 Option Pricing -- 12 Sensitivity Estimation -- 13 Risk Measurement and Management -- 14 Markov Chain Monte Carlo and Bayesian Statistics.