TY  - CHAP
AU  - Miguel Gil-Pugliese
AU  - Fernando Olsina
ED  - Mohammad Saber Fallah Nezhad
Y1  - 2014-04-29
PY  - 2014
T1  - Risk-Constrained Forward Trading Optimization by Stochastic Approximate Dynamic Programming
N2  - Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. Because of these developments, interest in dynamic programming and Bayesian inference and their applications has greatly increased at all mathematical levels. The purpose of this book is to provide some applications of Bayesian optimization and dynamic programming.
BT  - Dynamic Programming and Bayesian Inference
SP  - Ch. 4
UR  - https://doi.org/10.5772/57466
DO  - 10.5772/57466
SN  - 
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-26
ER  -