Non-Linear Time Series Models in Empirical Finance [Paperback]

This 2000 volume reviews non-linear time series models, and their applications to financial markets.The most up to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed non-linear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. Uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.The most up to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed non-linear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. Uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.This is the most up-to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed nonlinear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. It uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.1. Introduction; 2. Some concepts in time series analysis; 3. Regime-switching models for returns; 4. Regime-switching models for volatility; 5. Artificial neural networks for returns; 6. Conclusion.