Rank-dependent ppredictableforward performance processes  

作　　者：Bahman Angoshtari Shida Duan 

机构地区：[1]Department of Mathematics,University of Miami,Coral Gables FL 33146,USA

出　　处：《Probability, Uncertainty and Quantitative Risk》2024年第2期181-218,共38页概率、不确定性与定量风险（英文）

摘　　要：Predictable forward performance processes(PFPPs)are stochastic optimal control frameworks for an agent who controls a randomly evolving system but can only prescribe the system dynamics for a short period ahead.This is a common scenario in which a controlling agent frequently re-calibrates her model.We introduce a new class of PFPPs based on rank-dependent utility,generalizing existing models that are based on expected utility theory(EUT).We establish existence of rank-dependent PFPPs under a conditionally complete market and exogenous probability distortion functions which are updated periodically.We show that their construction reduces to solving an integral equation that generalizes the integral equation obtained under EUT in previous studies.We then propose a new approach for solving the integral equation via theory of Volterra equations.We illustrate our result in the special case of conditionally complete Black-Scholes model.

关 键 词：Forward performance criteria Rank dependent utility Probability distortion Time consistency Inverse investment problems Volterra integral equations Completely monotonic inverse marginals 

分 类 号：O17[理学—数学]