Description
Book SynopsisThis text focuses on the issue of non-linear modelling of high frequency financial data. Non-linearity refers to situations in which there is a high degree of apparent randomness to the way in which a particular financial measure, price, interest rate, or exchange rate moves with time.
Table of ContentsHIGH FREQUENCY MODELS IN FINANCE: MOTIVATIONS AND THEORETICAL ISSUES.
Modelling with High Frequency Data: A Growing Interest for Financial Economists and Fund Managers (M. Gavridis).
High Frequency Foreign Exchange Rates: Price Behavior Analysis and 'True Price' Models (J. Moody & L. Wu).
DETECTING NONLINEARITIES IN HIGH FREQUENCY DATA: EMPIRICAL TESTS AND MODELLING IMPLICATIONS.
Testing Linearity with Information-Theoretic Statistics and the Bootstrap (F. Acosta).
Testing for Linearity: A Frequency Domain Approach (J. Drunat, et al.).
Stochastic or Chaotic Dynamics in High Frequency Financial Data (D. Guégan & L. Mercier).
F-consistency, De-volatization and Normalization of High Frequency Financial Data (B. Zhou).
PARAMETRIC MODELS FOR NONLINEAR FINANCIAL TIME SERIES.
High Frequency Financial Time Series Data: Some Stylized Facts and Models of Stochastic Volatility (E. Ghysels, et al.).
Modelling Short-term Volatility with GARCH and HARCH Models (M. Dacorogna, et al.).
High Frequency Switching Regimes: A Continuous-time Threshold Process (R. Dacco' & S. Satchell).
Modelling Burst Phenomena: Bilinear and Autoregressive Exponential Models (J. Drunat, et al.).
NON-PARAMETRIC MODELS FOR NONLINEAR FINANCIAL TIME SERIES.
Application of Neural Networks to Forecast High Frequency Data: Foreign Exchange (P. Bolland, et al.).
An Application of Genetic Algorithms to High Frequency Trading Models: A Case Study (C. Dunis, et al.).
High Frequency Exchange Rate Forecasting by the Nearest Neighbours Method (H. Alexandre, et al.).
Index.
