Summary

Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment of today's financial markets, daily prices and models based upon low frequency price series data do not provide the level of accuracy required by traders and a growing number of risk managers. To improve results, more and more researchers and practitioners are turning to high frequency data. Nonlinear Modelling of High Frequency Financial Time Series presents the latest developments and views of leading international researchers and market practitioners, in modelling high frequency data in finance. Combining both nonlinear modelling and intraday data for financial markets, the editors provide a fascinating foray into this extremely popular discipline. This book evolves around four major themes. The first introductory section focuses on high frequency financial data. The second part examines the exact nature of the time series considered: several linearity tests are presented and applied and their modelling implications assessed. The third and fourth parts are dedicated to modelling and forecasting these financial time series.

Author Biography

CHRISTIAN L. DUNIS is Girobank Professor of Banking and Finance at Liverpool Business School, and Director of its Centre for International Banking, Economics and Finance. He is also a consultant to asset management firms, a Visiting Professor of International Finance at Venice International University and an Official Reviewer attached to the European Commission for the evaluation of applications to finance of emerging software technologies. He is an Editor of the European Journal of Finance, and has widely published in the field of financial markets analysis and forecasting. He has organised the Forecasting Financial Markets Conference since 1994.

List of Contributors

vii

(4)

About the Contributors

(8)

Series Preface

xix

(2)

Preface

xxi

Part I High Frequency Models in Finance: Motivations and Theoretical Issues

(48)

1 Modelling with High Frequency Data: A Growing Interest for Financial Economists and Fund Managers

(20)

Michael Gavridis

2 High Frequency Foreign Exchange Rates: Price Behavior Analysis and `True Price' Models

(26)

John Moody

Lizhong Wu

Part II Detecting Nonlinearities in High Frequency Data: Empirical Tests and Modelling Implications

(76)

3 Testing Linearity with Information-Theoretic Statistics and the Bootstrap

(18)

F.M. Aparicio Acosta

4 Testing for Linearity: A Frequency Domain Approach

(18)

Jerome Drunat

Gilles Dufrenot

Laurent Mathieu

5 Stochastic or Chaotic Dynamics in High Frequency Financial Data

(22)

Dominique Guegan

Ludovic Mercier

6 F-consistency, De-volatilization and Normalization of High Frequency Financial Data

109

(16)

Bin Zhou

Part III Parametric Models for Nonlinear Financial Time Series

125

(98)

7 High Frequency Financial Time Series Data: Some Stylized Facts and Models of Stochastic Volatility

127

(34)

Eric Ghysels

Christian Gourieroux

Joanna Jasiak

8 Modelling Short-term Volatility with GARCH and HARCH Models

161

(16)

Michel M. Dacorogna

Ulrich A. Muller

Richard B. Olsen

Olivier V. Pictet

9 High Frequency Switching Regimes: A Continuous-time Threshold Process

177

(24)

Roberto Dacco

Steve Satchell

10 Modelling Burst Phenomena: Bilinear and Autoregressive Exponential Models

201

(22)

Jerome Drunat

Gilles Dufrenot

Laurent Mathieu

Part IV Non-parametric Models for Nonlinear Financial Time Series

223

(70)

11 Application of Neural Networks to Forecast High Frequency Data: Foreign Exchange

225

(22)

Peter J. Bolland

Jerome T. Connor

A-Paul N. Refenes

12 An Application of Genetic Algorithms to High Frequency Trading Models: A Case Study

247

(32)

Christian Dunis

Michael Gavridis

Andrew Harris

Swee Leong

Poomjai Nacaskul

13 High Frequency Exchange Rate Forecasting by the Nearest Neighbours Method

279

(14)

Herve Alexandre

Isabelle Girerd-Potin

Ollivier Taramasco

Index

293

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