Bayesian methods in finance
Svetlozar T. Rachev, John S. J. Hsu, Biliana S. Bagasheva, Frank J. Fabozzi
- xviii, 329 páginas ilustrado 24 cm.
- The Frank J. Fabozzi series. .
- Frank J. Fabozzi series .
Incluye referencias bibliográficas e índice.
Introduction -- The Bayesian Paradigm -- Prior and Posterior Information, Predictive Inference -- Bayesian Linear Regression Model -- Bayesian Numerical Computation -- Bayesian Framework For Portfolio Allocation -- Prior Beliefs and Asset Pricing Models -- The Black-Litterman Portfolio Selection Framework -- Market Efficiency and Return Predictability -- Volatility Models -- Bayesian Estimation of ARCH-Type Volatility Models -- Bayesian Estimation of Stochastic Volatility Models -- Advanced Techniques for Bayesian Portfolio Selection -- Multifactor Equity Risk Models. Ch. 1. Ch. 2. Ch. 3. Ch. 4. Ch. 5. Ch. 6. Ch. 7. Ch. 8. Ch. 9. Ch. 10. Ch. 11. Ch. 12. Ch. 13. Ch. 14.
"The aim of Bayesian Methods in Finance is to provide an overview of the theory of Bayesian methods and explain their real-world applications to financial modeling. While the principles and concepts explained in 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." "Bayesian Methods in Finance offers both students of finance and practitioners an invaluable resource in the form of a previously unavailable, highly accessible, unified look at the use of the Bayesian methodology - as well as numerical computational methods - in financial models and asset management."--BOOK JACKET.
9780471920830
Finance--Mathematical models.
Bayesian statistical decision theory.
Finanzas--Modelos matemáticos
Teoría estadística bayesiana
Toma de decisión en finanzas
658.15 / B357b
Incluye referencias bibliográficas e índice.
Introduction -- The Bayesian Paradigm -- Prior and Posterior Information, Predictive Inference -- Bayesian Linear Regression Model -- Bayesian Numerical Computation -- Bayesian Framework For Portfolio Allocation -- Prior Beliefs and Asset Pricing Models -- The Black-Litterman Portfolio Selection Framework -- Market Efficiency and Return Predictability -- Volatility Models -- Bayesian Estimation of ARCH-Type Volatility Models -- Bayesian Estimation of Stochastic Volatility Models -- Advanced Techniques for Bayesian Portfolio Selection -- Multifactor Equity Risk Models. Ch. 1. Ch. 2. Ch. 3. Ch. 4. Ch. 5. Ch. 6. Ch. 7. Ch. 8. Ch. 9. Ch. 10. Ch. 11. Ch. 12. Ch. 13. Ch. 14.
"The aim of Bayesian Methods in Finance is to provide an overview of the theory of Bayesian methods and explain their real-world applications to financial modeling. While the principles and concepts explained in 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." "Bayesian Methods in Finance offers both students of finance and practitioners an invaluable resource in the form of a previously unavailable, highly accessible, unified look at the use of the Bayesian methodology - as well as numerical computational methods - in financial models and asset management."--BOOK JACKET.
9780471920830
Finance--Mathematical models.
Bayesian statistical decision theory.
Finanzas--Modelos matemáticos
Teoría estadística bayesiana
Toma de decisión en finanzas
658.15 / B357b