Items related to Non-Linear Time Series Models in Empirical Finance
Synopsis
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.
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Book Description
An accessible guide to one of the fastest growing areas in financial analysis by one of Europes's leading teaching and researching teams, first published in 2000. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of non-linear models, including regime-switching and artificial neural networks.
"About this title" may belong to another edition of this title.
- PublisherCambridge University Press
- Publication date2000
- ISBN 10 0521770416
- ISBN 13 9780521770415
- BindingHardcover
- LanguageEnglish
- Number of pages298
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Nonlinear Time Series Models in Empirical Finance
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Non-Linear Time Series Models in Empirical Finance (Hardcover)
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ISBN 10: 0521770416
ISBN 13: 9780521770415
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Hardcover. Condition: new. Hardcover. 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. A guide to one of the fastest growing areas in financial analysis by one of Europe's leading teaching and researching teams. This textbook provides a treatment of non-linear models, including regime-switching and artificial neural networks. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521770415
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Non-Linear Time Series Models in Empirical Finance
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ISBN 13: 9780521770415
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Nonlinear Time Series Models in Empirical Finance
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Non-Linear Time Series Models in Empirical Finance
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. An accessible guide to one of the fastest growing areas in financial analysis by one of Europes s leading teaching and researching teams, first published in 2000. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treat. Seller Inventory # 446946501
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Non-Linear Time Series Models in Empirical Finance
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Non-Linear Time Series Models in Empirical Finance (Hardcover)
Published by
Cambridge University Press, Cambridge, 2000
ISBN 10: 0521770416
ISBN 13: 9780521770415
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Hardcover. Condition: new. Hardcover. 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. A guide to one of the fastest growing areas in financial analysis by one of Europe's leading teaching and researching teams. This textbook provides a treatment of non-linear models, including regime-switching and artificial neural networks. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780521770415
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