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.
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