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- Product code: 9383
- ISBN: 0471974641,
ISBN13: 9780471974642,
332 pages, hardback
Published by John Wiley & Sons on 1998
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Description of Nonlinear Modelling of High Frequency Financial Time Series |
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.
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Contents of Nonlinear Modelling of High Frequency Financial Time Series |
Part I High Frequency Models in Finance: Motivations and Theoretical Issues
Modelling with High Frequency Data: A Growing Interest for Financial Economists and Fund Managers
High Frequency Foreign Exchange Rates: Price Behavior Analysis and 'True Price' Models
Part II Detecting Non-Linearities in High Frequency Data: Empirical Tests and Modelling Implications
Testing Linearity with Information-Theoretic Statistics and the Bootstrap
Testing for Linearity: A Frequency Domain Approach
Stochastic or Chaotic Dynamics in High Frequency Financial Data
F-consistency, Devolatilization and Normalization of High Frequency Financial Data
Part III Parametric Models for Nonlinear Financial Time Series
High Frequency Financial Time Series Data: Some Stylized Facts and Models of Stochastic Volatility
Modelling Short-Term Volatility with GARCH and HARCH Models
High Frequency Switching Regimes: A Continuous-time Threshold Process
Modelling Burst Phenomena: Bilinear and Autoregressive Exponential Models
Part IV Non-parametric Models for Nonlinear Financial Time Series
Application of Neural Networks to Forecast High Frequency Data: Foreign Exchange
An Application of Genetic Algorithms to High Frequency Trading Models: A Case Study
High Frequency Exchange Rate Forecasting by the Nearest Neighbours Method.
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