Forward robust portfolio selection: The binomial case  

作　　者：Harrison Waldon 

机构地区：[1]Oaford-Man Institute of Quantitative Finance,University of Oaford,Eagle House Walton Well Road,Orford,OX26ED,UK

出　　处：《Probability, Uncertainty and Quantitative Risk》2024年第1期107-122,共16页概率、不确定性与定量风险（英文）

摘　　要：We introduce a new approach for optimal portfolio choice under model ambiguity by incorporating predictable forward preferences in the framework of Angoshtari et al.[2].The investor reassesses and revises the model ambiguity set incrementally in time while,also,updating his risk preferences forward in time.This dynamic alignment of preferences and ambiguity updating results in time-consistent policies and provides a richer,more accurate learning setting.For each investment period,the investor solves a worst-case portfolio optimization over possible market models,which are represented via a Wasserstein neighborhood centered at a binomial distribution.Duality methods from Gao and Kleywegt[10];Blanchet and Murthy[8]are used to solve the optimization problem over a suitable set of measures,yielding an explicit optimal portfolio in the linear case.We analyze the case of linear and quadratic utilities,and provide numerical results.

关 键 词：Forward robust portfolio selection Binomial case Optimal portfolio Forward performance processes Linear utilities Quadratic utilities Robust forward performance criteria 

分 类 号：O17[理学—数学]