Non-Linear Time Series Models in Empirical Finance
eBook - PDF

Non-Linear Time Series Models in Empirical Finance

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Non-Linear Time Series Models in Empirical Finance

About this book

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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Yes, you can access Non-Linear Time Series Models in Empirical Finance by Philip Hans Franses,Dick van Dijk in PDF and/or ePUB format, as well as other popular books in Volkswirtschaftslehre & Ökonometrie. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-title
  3. Title
  4. Copyright
  5. Dedication
  6. Contents
  7. Figures
  8. Tables
  9. Preface
  10. 1 Introduction
  11. 2 Some concepts in time series analysis
  12. 3 Regime-switching models for returns
  13. 4 Regime-switching models for volatility
  14. 5 Artificial neural networks for returns
  15. 6 Conclusions
  16. Bibliography
  17. Author index
  18. Subject index