Nonlinear time series models in empirical finance / / Philip Hans Franses, Dick van Dijk [[electronic resource]]

• Record Nr.: UNINA9910823240103321
• Autore: Franses Philip Hans <1963->
• Pubbl/distr/stampa: Cambridge : , : Cambridge University Press, , 2000
• ISBN: 1-107-11898-0; 1-280-15463-2; 0-511-11827-9; 0-511-15217-5; 0-511-32333-6; 0-511-75406-X; 0-511-04932-3
• Descrizione fisica: 1 online resource (xvi, 280 pages) : digital, PDF file(s)
• Disciplina: 332/.01/5118
• Soggetti: Finance - Mathematical models; Time-series analysis
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Title from publisher's bibliographic system (viewed on 05 Oct 2015).
• Nota di bibliografia: Includes bibliographical references (p. 254-271) and index.
• Nota di contenuto: Cover; Half-title; Title; Copyright; Dedication; Contents; Figures; Tables; Preface; 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 Conclusions; Bibliography; Author index; Subject index
• Sommario/riassunto: 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.