05584nam 2200793Ia 450 991081705930332120200520144314.09786611217266978111920214111192021409781281217264128121726397804702492460470249242(CKB)1000000000414804(EBL)331607(OCoLC)211911037(SSID)ssj0000109307(PQKBManifestationID)11135765(PQKBTitleCode)TC0000109307(PQKBWorkID)10045733(PQKB)10491474(MiAaPQ)EBC331607(Au-PeEL)EBL331607(CaPaEBR)ebr10225368(CaONFJC)MIL121726(OCoLC)72655606(FINmELB)ELB177444(FR-PaCSA)88944042(FRCYB88944042)88944042(Perlego)2751765(EXLCZ)99100000000041480420070403d2008 uy 0engur|n|---|||||txtccrBayesian methods in finance /Svetlozar T. Rachev ... [et al.]1st ed.Hoboken, N.J. Wileyc20081 online resource (351 p.)The Frank J. Fabozzi seriesDescription based upon print version of record.9780471920830 0471920835 Includes bibliographical references (p. 298-309) and index.Bayesian Methods in Finance; Contents; Preface; About the Authors; CHAPTER 1 Introduction; A FEW NOTES ON NOTATION; OVERVIEW; CHAPTER 2 The Bayesian Paradigm; THE LIKELIHOOD FUNCTION; THE BAYES' THEOREM; SUMMARY; CHAPTER 3 Prior and Posterior Information, Predictive Inference; PRIOR INFORMATION; POSTERIOR INFERENCE; BAYESIAN PREDICTIVE INFERENCE; ILLUSTRATION: POSTERIOR TRADE-OFF AND THENORMAL MEAN PARAMETER; SUMMARY; APPENDIX: DEFINITIONS OF SOME UNIVARIATE AND MULTIVARIATE STATISTICAL DISTRIBUTIONS; CHAPTER 4 Bayesian Linear Regression Model; THE UNIVARIATE LINEAR REGRESSION MODELTHE MULTIVARIATE LINEAR REGRESSION MODELSUMMARY; CHAPTER 5 Bayesian Numerical Computation; MONTE CARLO INTEGRATION; ALGORITHMS FOR POSTERIOR SIMULATION; APPROXIMATION METHODS: LOGISTIC REGRESSION; SUMMARY; CHAPTER 6 Bayesian Framework for Portfolio Allocation; CLASSICAL PORTFOLIO SELECTION; BAYESIAN PORTFOLIO SELECTION; SHRINKAGE ESTIMATORS; UNEQUAL HISTORIES OF RETURNS; SUMMARY; CHAPTER 7 Prior Beliefs and Asset Pricing Models; PRIOR BELIEFS AND ASSET PRICING MODELS; MODEL UNCERTAINTY; SUMMARY; APPENDIX A: NUMERICAL SIMULATION OF THE PREDICTIVE DISTRIBUTIONAPPENDIX B: LIKELIHOOD FUNCTION OF A CANDIDATE MODELCHAPTER 8 The Black-Litterman Portfolio Selection Framework; PRELIMINARIES; COMBINING MARKET EQUILIBRIUM AND INVESTOR VIEWS; THE CHOICE OF τ AND ω; THE OPTIMAL PORTFOLIO ALLOCATION; INCORPORATING TRADING STRATEGIES INTO THE BLACK-LITTERMAN MODEL; ACTIVE PORTFOLIO MANAGEMENT AND THE BLACK-LITTERMAN MODEL; COVARIANCE MATRIX ESTIMATION; SUMMARY; CHAPTER 9 Market Efficiency and Return Predictability; TESTS OF MEAN-VARIANCE EFFICIENCY; INEFFICIENCY MEASURES IN TESTING THE CAPM; TESTING THE APT; RETURN PREDICTABILITYILLUSTRATION: PREDICTABILITY AND THE INVESTMENT HORIZONSUMMARY; APPENDIX: VECTOR AUTOREGRESSIVE SETUP; CHAPTER 10 Volatility Models; GARCH MODELS OF VOLATILITY; STOCHASTIC VOLATILITY MODELS; ILLUSTRATION: FORECASTING VALUE-AT-RISK; AN ARCH-TYPE MODEL OR A STOCHASTIC VOLATILITY MODEL?; WHERE DO BAYESIAN METHODS FIT?; CHAPTER 11 Bayesian Estimation of ARCH-Type Volatility Models; BAYESIAN ESTIMATION OF THE SIMPLE GARCH(1,1) MODEL; MARKOV REGIME-SWITCHING GARCH MODELS; SUMMARY; APPENDIX: GRIDDY GIBBS SAMPLER; CHAPTER 12 Bayesian Estimation of Stochastic Volatility ModelsPRELIMINARIES OF SV MODEL ESTIMATIONTHE SINGLE-MOVE MCMC ALGORITHM FOR SV MODEL ESTIMATION; THE MULTIMOVE MCMC ALGORITHM FOR SV MODEL ESTIMATION; JUMP EXTENSION OF THE SIMPLE SV MODEL; VOLATILITY FORECASTING AND RETURN PREDICTION; SUMMARY; APPENDIX: KALMAN FILTERING AND SMOOTHING; CHAPTER 13 Advanced Techniques for Bayesian Portfolio Selection; DISTRIBUTIONAL RETURN ASSUMPTIONS ALTERNATIVE TO NORMALITY; PORTFOLIO SELECTION IN THE SETTING OF NONNORMALITY: PRELIMINARIES; MAXIMIZATION OF UTILITY WITH HIGHER MOMENTS; EXTENDING THE BLACK-LITTERMAN APPROACH: COPULA OPINION POOLINGEXTENDING THE BLACK-LITTERMAN APPROACH: STABLE DISTRIBUTIONBayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management-since these are the areas in finance where Bayesian methods have had the greatest penetration to date.Frank J. Fabozzi series.FinanceMathematical modelsBayesian statistical decision theoryFinanceMathematical models.Bayesian statistical decision theory.332332.01519542Rachev S. T(Svetlozar Todorov)59738MiAaPQMiAaPQMiAaPQBOOK9910817059303321Bayesian methods in finance4126207UNINA