Decision Technologies for Computational Finance

Part 1: Market Dynamics and Risk. Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management; F.X. Diebold, et al. Stability Analysis and Forecasting Implications; J. del Hoyo, J.G. Llorente. Time-Varying Risk Premia; M. Steiner, S. Schneider. A Data Matrix to Investigate Independence, Over-Reaction and/or Shock Persistence in Financial Data; R. Dacco, S.E. Satchell. Forecasting, High-Frequency Exchange Rates Using Cross Bicorrelations in; C. Brooks, M. Hinich. Stochastic Lotka-Volterra Systems of Competing Auto-Catalytic Agents Lead Generically to Truncated Pareto Power Wealth Distribution, Truncated Levy-Stable Intermittent Market Returns, Clustered Volatility, Booms and Crashes; S. Solomon. Part 2: Trading and Arbitrage Strategies Controlling Nonstationarity in Statistical Arbitrage Using a Portfolio of Cointegration Models; A.N. Burgess. Non-Parametric Test for Nonlinear Cointegration; J. Breitung. Comments on `A Non-Parametric Test for Nonlinear Cointegration'; H. White. Reinforcement Learning for Trading Systems and Portfolios: Immediate and Future Rewards; J.E. Moody, et al. An Evolutionary Bootstrap Method for Selecting Dynamic Trading Strategies; B. LeBaron. Discussion on `An Evolutionary Bootstrap Method for Selecting Dynamic Trading Strategies'; A.S. Weigend. Multitask Learning in a Neural VEC Approach for Exchange Rate Forecasting; F. Rauscher. Selecting Relative Value Stocks with Nonlinear Cointegration; C. Kollias, K. Metaxas. Part 3: Volatility Modelling and Option Pricing. Option Pricing with Neural Networks and a Homogeneity Hint; R. Garcia, R. Gencay. Bootstrapping GARCH(1,1) Models; G. Maerker. Using Option Prices to Recover ProbabilityDistributions; F. Gonzales-Mirand, A.N. Burgess. Modelling Financial Time Series Using State-Space Models; J. Timmer, A.S. Weigend. Forecasting Properties of Neural Network Generated Volatility Estimates; P. Ahmed, S. Swidle. Interest Rates Structure Dynamics: A Non-Parametric Approach; M.