论文标题
在随机因素模型中使用的游戏理论方法，用于稳健的前瞻性投资绩效过程
A game theoretical approach to homothetic robust forward investment performance processes in stochastic factor models
论文作者
论文摘要
本文研究了模型不确定性的不完整市场中的最佳前瞻性投资问题，其中潜在的股票取决于相关的随机因素。不确定性源于投资者选择评估绩效的概率度量。我们通过结合零和零随机差异游戏和ergodic BSDE方法来直接获得均匀稳健前向性能过程的代表。我们还建立了与无限型的零零和随机差速器游戏的联系，并具有厄尔贡的回报标准，以及与长期远距离的经典强大预期公用事业。最后，我们举一个例子来说明我们的方法可以应用于具有负面实现过程的一种强大的远期投资绩效过程。
This paper studies an optimal forward investment problem in an incomplete market with model uncertainty, in which the underlying stocks depend on the correlated stochastic factors. The uncertainty stems from the probability measure chosen by an investor to evaluate the performance. We obtain directly the representation of the homothetic robust forward performance processes in factor-form by combining the zero-sum stochastic differential game and ergodic BSDE approach. We also establish the connections with the risk-sensitive zero-sum stochastic differential games over an infinite horizon with ergodic payoff criteria, as well as with the classical robust expected utilities for long time horizons. Finally, we give an example to illustrate that our approach can be applied to address a type of robust forward investment performance processes with negative realization processes.
