Computational Finance 1999.
Abu-Mostafa, Yaser S.
Computational Finance 1999. - 1st ed. - 1 online resource (732 pages) - The MIT Press Series . - The MIT Press Series .
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. jn Optimal VinaryPredictor for an Investor -- in Futures Market -- jn Introduction to Risk Neutral Forecasting -- TemporalyDiyerence Learning and jpplications -- in Finance -- Heterogeneous Agents -- Technical Trading Creates a PrisonerCs DilemmaK -- Results from an Agent'Based Model -- Cycles of Market Stability and Instability Due to -- Endogenous Use of Technical Trading Rules -- Relative Performance of Incentive Mechanisms in -- Delegated InvestmentsK A Computational Study -- Credit Risk -- Rules Extractions from BanksP Bankrupt Data Using -- Connectionist and Symbolic Learning Algorithms -- Evaluating Bank Lending Policy and Consumer -- Credit Risk -- Loan Duration and Bank Lending Policy -- Option Pricing -- Estimation of Stochastic Volatility Models for the Purpose -- of Option Pricing -- Option Pricing via Genetic Programming -- Nonparametric Testing of ARCH for Option Pricing -- A Computational Framework for Contingent Claim -- Pricing and Hedging under Time Dependent Asset -- Processes -- A Framework for Comparative Analysis of Statistical -- and Machine Learning Methodsq An Application to the -- BlackDScholes Option Pricing Equation -- Option Pricing with the EPcient Method of Moments -- Option Valuation with the Genetic Programming -- Approach -- Contact Information.
This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation.
9780262266741
Finance -- Data processing -- Congresses.
Finance -- Mathematical models -- Congresses.
Electronic books.
HG174 -- .C64 2000eb
332.0285
Computational Finance 1999. - 1st ed. - 1 online resource (732 pages) - The MIT Press Series . - The MIT Press Series .
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. jn Optimal VinaryPredictor for an Investor -- in Futures Market -- jn Introduction to Risk Neutral Forecasting -- TemporalyDiyerence Learning and jpplications -- in Finance -- Heterogeneous Agents -- Technical Trading Creates a PrisonerCs DilemmaK -- Results from an Agent'Based Model -- Cycles of Market Stability and Instability Due to -- Endogenous Use of Technical Trading Rules -- Relative Performance of Incentive Mechanisms in -- Delegated InvestmentsK A Computational Study -- Credit Risk -- Rules Extractions from BanksP Bankrupt Data Using -- Connectionist and Symbolic Learning Algorithms -- Evaluating Bank Lending Policy and Consumer -- Credit Risk -- Loan Duration and Bank Lending Policy -- Option Pricing -- Estimation of Stochastic Volatility Models for the Purpose -- of Option Pricing -- Option Pricing via Genetic Programming -- Nonparametric Testing of ARCH for Option Pricing -- A Computational Framework for Contingent Claim -- Pricing and Hedging under Time Dependent Asset -- Processes -- A Framework for Comparative Analysis of Statistical -- and Machine Learning Methodsq An Application to the -- BlackDScholes Option Pricing Equation -- Option Pricing with the EPcient Method of Moments -- Option Valuation with the Genetic Programming -- Approach -- Contact Information.
This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation.
9780262266741
Finance -- Data processing -- Congresses.
Finance -- Mathematical models -- Congresses.
Electronic books.
HG174 -- .C64 2000eb
332.0285