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Non-Linear Time Series Models in Empirical Finance - Philip Hans Franses

Non-Linear Time Series Models in Empirical Finance

Hardcover Published: 4th September 2000
ISBN: 9780521770415
Number Of Pages: 298

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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 - the most up to-date and accessible guide available - 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.

Introduction
Some concepts in time series analysis
Regime-switching models for returns
Regime-switching models for volatility
Artificial neural networks for returns
Conclusion
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780521770415
ISBN-10: 0521770416
Audience: Tertiary; University or College
Format: Hardcover
Language: English
Number Of Pages: 298
Published: 4th September 2000
Publisher: CAMBRIDGE UNIV PR
Country of Publication: GB
Dimensions (cm): 25.4 x 17.78  x 1.75
Weight (kg): 0.74

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