Author Description

Contents: Heavy-Tailed and Nonlinear Continuous-Time ARMA Models for Financial Time Series (P J Brockwell) Nonlinear State Space Model Approach to Financial Time Series with Time-Varying Variance (G Kitagawa & S Sato) Nonparametric Estimation and Bootstrap for Financial Time Series (J-P Kreiβ) A Note on Kernel Estimation in Integrated Time Series (Y-C Xia et al.) Stylized Facts on the Temporal and Distributional Properties of Absolute Returns: An Update (C W J Granger et al.) Volatility Computed by Time Series Operators at High Frequency (U A Müller) Missing Values in ARFIMA Models (W Palma) Second Order Tail Effects (C G de Vries) Bayesian Estimation of Stochastic Volatility Model via Scale Mixtures Distributions (S T B Choy & C M Chan) On a Smooth Transition Double Threshold Model (Y N Lee & W K Li) Interval Prediction of Financial Time Series (B Cheng & H Tong) A Decision Theoretic Approach to Forecast Evaluation (C W J Granger & M H Pesaran) Portfolio Management and Market Risk Quantification Using Neural Networks (J Franke) Detecting Structural Changes Using Genetic Programming with an Application to the Greater-China Stock Markets (X B Zhang et al.) and other papers Readership: Researchers in finance, time series analysis, economics and actuarial science, as well as investment bankers, stock market analysts and risk managers.