Models play a crucial role in financial markets and an understanding and appreciation of how to model financial data is key to any finance practitioner's skill set. This book provides a treatment of model development. As well as numerous real-world examples to illustrate concepts in an accessible manner, the accompanying CD will allow the reader to implement the examples themselves and adapt them for their own purposes. This is a reference for those involved in model selection and development. Table of Contents Preface Acknowledgments PART I: VOLATILITY AND CORRELATION ANALYSIS Understanding Volatility and Correlation Implied Volatility and Correlation Moving Average Models GARCH Models Forecasting Volatility and Correlation PART II: MODELLING THE MARKET RISK OF PORTFOLIOS Principal Component Analysis Covariance Matrices Risk Measurement in Factor Models Value-At-Risk Modelling Non-Normal Returns PART III: STATISTICAL MODELS FOR FINANCIAL MARKETS Time Series Models Cointegration Forecasting High-Frequency Data Technical Appendix Linear Regression Statistical Inference Residual Analysis Data Problems Prediction Maximum Likelihood Methods. References. Tables Index