Optimal portfolio in partially observed stochastic volatility models
成果类型:
Article
署名作者:
Pham, H; Quenez, MC
署名单位:
Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Universite Paris Cite; Sorbonne Universite; Universite Gustave-Eiffel
刊物名称:
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN:
1050-5164
DOI:
10.1214/aoap/998926991
发表日期:
2001
页码:
210-238
关键词:
Incomplete information
Utility maximization
consumption
policies
investor
ECONOMY
MARKETS
摘要:
We address the maximization problem of expected utility from terminal wealth. The special feature of this paper is that we consider a financial market where price process of risky assets follows a stochastic volatility model and we require that investors observe just the vector of stock prices. Using stochastic filtering techniques and adapting martingale duality methods in this partially observed incomplete model, we characterize the value function and the optimal portfolio policies. We study in detail the Bayesian case, when risk premia of the stochastic volatility model are unobservable random variables with known prior distribution. We also consider the case of unobservable risk premia modelled by linear Gaussian processes.