Non-Linear Time Series Models in Empirical Finance
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Non-Linear Time Series Models in Empirical Finance by Philip Hans Franses
Book DescriptionAlthough 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.
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Book DetailsISBN: 9780521779654
(247mm x 174mm x 16mm)
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 27-Jul-2000
Country of Publication: United Kingdom
Books By Author Philip Hans Franses
Expert Adjustments of Model Forecasts, Hardback (October 2014)
Brings together current theoretical insights and new empirical results to examine expert adjustment of model forecasts from an econometric perspective.
Time Series Models for Business and Economic Forecasting, Hardback (April 2014)
Taking a practical approach, this updated and classroom-tested textbook prepares students to create effective forecasting models for business and economics.
Quantitative Models in Marketing Research, Paperback (June 2010)
This 2001 book presents important and practically relevant quantitative models used for marketing research.
Periodic Time Series Models, Hardback (March 2004)» View all books by Philip Hans Franses
In this modern study of the use of periodic models in the description and forecasting of economic data the authors investigate such areas as seasonal time series, periodic time series models, periodic integration and periodic cointegration.
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