Computational Finance

Intro -- Contents -- Preface -- Contributors -- Introduction -- Risk Management and Portfolio Optimization -- Importance Sampling and StratiEcation for Value-at-Risk -- ConEdence Intervals and Hypothesis Testing for the -- Sharpe and Treynor Performance Measures: -- A Bootstrap Approach -- Conditional Value at Risk -- Advances in Importance Sampling -- Arbitrage and the APTZA Note -- Bayesian Network Models of Portfolio Risk and Return -- Volatility -- Change of Measure in Monte Carlo Integration -- via Gibbs Sampling with an Application to -- Stochastic VolatilityModels -- Comparing Models of Intra daySeasonal Volatility -- in the Foreign Exchange Market -- A Symbolic Dynamics Approach to Volatility Prediction -- Does Volatility Timing Matter? -- Time Series Methods -- Goodness of FitG Stability and Data Mining -- A Bayesian Approach to Estimating Mutual Fund Returns -- Independent Component Ordering in ICS Snalysis -- of Financial Data -- Curved Gaussian Models with Spplication to Modeling -- Foreign Exchange Rates -- Nonparametric EJciency Testing of Ssian -- Foreign Exchange Markets -- Term Structure of Interactions of Foreign Exchange Rates -- Exchange Rates and Fundamentals¸ Evidence from -- Out(of(Sample Forecasting Using Neural Networks -- Dynamic Trading Strategies -- Trading Models as Specimcation Tools -- Statistical Arbitrage Models of the FTSE JDD -- Implementing Trading Strategies for Forecasting Models -- Using Nonlinear Neurogenetic Models with Prokt Related -- Objective Functions to Trade the US THbond Future -- Parameter Tuning in Trading Algorithms Using ASTA -- Hedge Funds Styles -- Optimization ofTechnical Trading Strategy Using Split -- Search Genetic Algorithms -- Trading Mutual Funds with PieceMwise Constant Models -- Minimizing Downside Risk via Stochastic -- Dynamic Programming.