Nonlinear modelling of high frequency financial time series
In the competitive and risky environment of todays 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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A Frequency Domain Approach
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algorithm analysis applied approach arbitrage attractor autocorrelation autoregressive average behaviour bid-ask Bilinear bilinear models bispectrum Bollerslev coefficients components computed correlation Dacorogna data set de-volatilization defined DEM/FRF DEM/JPY deviation dimension distribution Dunis dynamics Econometrics Economic empirical equation error estimate exchange rates Figure financial time series Foreign Exchange Market Foreign Exchange Rates frequency exchange rates function Gaussian Ghysels HARCH heteroscedasticity high frequency data high frequency exchange High Frequency Financial Hurst exponent in-sample interval intraday Jasiak Kalman filter kurtosis linearity test Lyapunov exponent market activity matrix measure method methodology model parameters momentum model Neural Networks nonlinear Nonlinear Modelling normal null hypothesis observation noise Olsen & Associates optimisation optimization out-of-sample Pictet prediction price changes random walk rescaled range returns sample sample sample Standard error statistics state-space models stochastic process stochastic volatility Table threshold tick data tick-by-tick trading model true price USD/DEM USD/FRF values variables variance vector Zhou