Non-Linear Time Series Models in Empirical Finance

Philip Hans Franses

ISBN 10: 0521770416 / ISBN 13: 9780521770415

Published by Cambridge University Press, 2000

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are more appropriate for forecasting and accurately describing returns and volatility. The enormous number of non-linear time series models appropriate for modeling and forecasting economic time series models makes choosing the best model for a particular application daunting. This classroom-tested advanced undergraduate and graduate textbook, first published in 2000, provides a rigorous treatment of recently developed non-linear models, including regime-switching and artificial neural networks. The focus is on the potential applicability for describing and forecasting financial asset returns and their associated volatility. The models are analysed in detail and are not treated as 'black boxes'. Illustrated using a wide range of financial data, drawn from sources including the financial markets of Tokyo, London and Frankfurt.

Seller Inventory # 9780521770415

Bibliographic Details

• Title: Non-Linear Time Series Models in Empirical Finance
• Publisher: Cambridge University Press
• Publication Date: 2000
• Language: English
• ISBN 10: 0521770416
• ISBN 13: 9780521770415
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 21D millimeters 260 millimeters width by 183 millimeters height by 21 millimeters depth
• Weight: 759 grams

About this title

Synopsis

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.