Simulation Techniques in Financial Risk Management

Informationen zum Autor Ngai Hang Chan, PhD, is Choh-Min Li Chair Professor of Statistics of the Department of Statistics at The Chinese University of Hong Kong. An elected Fellow of the Institute of Mathematical Statistics and the American Statistical Association, Professor Chan is also the co-editor and associate editor of 8 journals and author of Time Series: Applications to Finance with R and S-Plus, Second Edition and Handbook of Financial Risk Management: Simulations and Case Studies, both also published by Wiley. His research interests include statistical finance, risk management, time series, econometrics, and stochastic modeling.Hoi-Ying Wong, PhD, is Professor in the Risk Management Science Program of the Department of Statistics at The Chinese University of Hong Kong. Professor Wong is also associate editor of one journal and the author of Handbook of Financial Risk Management: Simulations and Case Studies, also published by Wiley. His research interests include derivatives pricing, interest rate modeling, financial risk management, and statistical finance. Klappentext Praise for the First Edition"...a nice, self-contained introduction to simulation and computational techniques in finance..."- Mathematical ReviewsSimulation Techniques in Financial Risk Management, Second Edition takes a unique approach to the field of simulations by focusing on techniques necessary in the fields of finance and risk management. Thoroughly updated, the new edition expands on several key topics in these areas and presents many of the recent innovations in simulations and risk management, such as advanced option pricing models beyond the Black-Scholes paradigm, interest rate models, MCMC methods including stochastic volatility models simulations, model assets and model-free properties, jump diffusion, and state space modeling. The Second Edition features also features:* Updates to primary software used throughout the book, Microsoft Office(r) Excel(r) VBA* New topical coverage on multiple assets, model-free properties, and related models* More than 300 exercises at the end of each chapter, with select answers in the appendix, to help readers apply new concepts and test their understanding* Extensive use of examples to illustrate how to use simulation techniques in risk management* Practical case studies, such as the pricing of exotic options; simulations of Greeks in hedging; and the use of Bayesian ideas to assess the impact of jumps, so readers can reproduce the results of the studies* A related website with additional solutions to problems in the text, and Excel VBA and S-Plus computer code for many of the examples within the bookSimulation Techniques in Financial Risk Management, Second Edition is an invaluable resource for risk managers in the financial and actuarial industries as well as a useful reference for readers interested in learning how to better gauge risk and make more informed decisions. The book is also an excellent textbook for upper-undergraduate and graduate-level courses in simulation and risk management.Ngai Hang Chan, PhD, is Choh-Min Li Chair Professor of Statistics of the Department of Statistics at The Chinese University of Hong Kong. An elected Fellow of the Institute of Mathematical Statistics and the American Statistical Association, Professor Chan is also the co-editor and associate editor of 8 journals and author of Time Series: Applications to Finance with R and S-Plus, Second Edition and Handbook of Financial Risk Management: Simulations and Case Studies, both also published by Wiley. His research interests include statistical finance, risk management, time series, econometrics, and stochastic modeling.Hoi-Ying Wong, PhD, is Professor in the Risk Management Science Program of the Department of Statistics at The Chinese University of Hong Kong. Professor Wong is also associate editor of one journal and the author of Handbook of Financial Risk Management: Simulati...

List of contents

List of Figures xiList of Tables xiiiPreface xv1 Preliminaries of VBA 11.1 Introduction 11.2 Basis Excel VBA 11.2.1 Developer Mode and Security Level 21.2.2 Visual Basic Editor 21.2.3 The Macro Recorder 51.2.4 Setting Up a Command Button 61.3 VBA Programming Fundamentals 81.3.1 Declaration of Variables 81.3.2 Types of Variables 81.3.3 Declaration of Multivariable 91.3.4 Declaration of Constants 91.3.5 Operators 91.3.6 User-Defined Data Types 101.3.7 Arrays and Matrices 111.3.8 Data Input and Output 121.3.9 Conditional Statements 121.3.10 Loops 131.3.11 Sub Procedures and Function Procedures 151.3.12 VBA's Built-In Functions 182 Basic Properties of Futures and Options 192.1 Introduction 192.1.1 Arbitrage and Hedging 192.1.2 Forward Contracts 202.1.3 Futures Contracts 232.2 Options 262.3 Exercises 313 Introduction to Simulation 353.1 Questions 353.2 Simulation 353.3 Examples 363.3.1 Quadrature 363.3.2 Monte Carlo 373.4 Stochastic Simulations 383.5 Exercises 404 Brownian Motions and Itô's Rule 414.1 Introduction 414.2 Wiener and Itô's Processes 414.3 Stock Price 464.4 Itô's Formula 474.5 Exercises 545 Black-Scholes Model and Option Pricing 575.1 Introduction 575.2 One Period Binomial Model 585.3 The Black-Scholes-Merton Equation 615.4 Black-Scholes Formula 675.5 Exercises 726 Generating Random Variables 756.1 Introduction 756.2 Random Numbers 756.3 Discrete Random Variables 766.4 Acceptance-Rejection Method 786.5 Continuous Random Variables 796.5.1 Inverse Transform 806.5.2 The Rejection Method 816.5.3 Multivariate Normal 836.6 Exercises 877 Standard Simulations in Risk Management 897.1 Introduction 897.2 Scenario Analysis 897.2.1 Value at Risk 917.2.2 Heavy-Tailed Distribution 927.2.3 Case Study: VaR of Dow Jones 947.3 Standard Monte Carlo 967.3.1 Mean, Variance, and Interval Estimation 977.3.2 Simulating Option Prices 997.3.3 Simulating Option Delta 1027.4 Exercises 1047.5 Appendix 1058 Variance Reduction Techniques 1078.1 Introduction 1078.2 Antithetic Variables 1078.3 Stratified Sampling 1128.4 Control Variates 1208.5 Importance Sampling 1258.6 Exercises 1319 Path Dependent Options 1339.1 Introduction 1339.2 Barrier Option 1339.3 Lookback Option 1359.4 Asian Option 1369.5 American Option 1389.5.1 Simulation: Least Squares Approach 1389.5.2 Analyzing the Least Squares Approach 1419.5.3 American Style Path Dependent Options 1449.6 Greek Letters 1459.7 Exercises 14810 Multiasset Options 15110.1 Introduction 15110.2 Simulating European Multiasset Options 15210.3 Case Study: On Estimating Basket Options 15310.4 Dimension Reduction 15510.5 Exercises 15811 Interest Rate Models 16111.1 Introduction 16111.2 Discount Factor and Bond Prices 16111.3 Stochastic Interest Rate Models and Their Simulations 16511.4 Hull-White Model 16711.5 Fixed Income Derivatives Pricing 17111.6 Exercises 17412 Markov Chain Monte Carlo Methods 17712.1 Introduction 17712.2 Bayesian Inference 17712.3 Simulating Posteriors 17912.4 Markov Chain Monte Carlo 18012.4.1 Gibbs Sampling 18012.4.2 Case Study: The Effect of Jumps on Dow Jones 18312.5 Metropolis-Hastings Algorithm 18812.6 Exercises 196References 199Index 203

Product details

• Authors: Ngai Han Chan, Ngai Hang Chan, Ngai Hang Wong Chan, Hoi Ying Wong, Hoi-Ying Wong
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 24.04.2015
• EAN: 9781118735817
• ISBN: 978-1-118-73581-7
• No. of pages: 232
• Series: Statistics in Practice; Statistics in Practice
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > General, dictionaries; Statistik, Risikomanagement, Statistics, Financial Engineering, Finance & Investments, Finanz- u. Anlagewesen, Finanztechnik, Statistik in den Ingenieurwissenschaften, Engineering Statistics, Statistics for Finance, Business & Economics, Finanz- u. Wirtschaftsstatistik