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A receding horizon control approach to portfolio optimization using a risk-minimax objective for wealth tracking

机译:使用风险最小目标进行资产追踪的​​投资组合优化的后退控制方法

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In this paper, we consider the problem of financial portfolio optimization. A hierarchical framework is used, and receding horizon control (RHC) ideas are exploited to pose and solve two relevant constrained optimization problems. We first present the classic problem of wealth maximization subject to risk constraints. We also formulate a new approach to portfolio optimization which attempts to minimize the peak risk over the prediction horizon, while trying to track a wealth objective. This approach is designed to assist investors that might be unable to precisely specify their risk tolerance. We compare this methodology with the classical approach. It is concluded that this approach may be particularly beneficial during downturns — appreciably limiting losses during downturns while providing most of the upturn benefits.
机译:在本文中,我们考虑了金融资产组合优化的问题。使用了分层框架,后退水平控制(RHC)思想被利用来提出和解决两个相关的约束优化问题。我们首先提出受风险约束的财富最大化的经典问题。我们还制定了一种投资组合优化的新方法,该方法试图在预测范围内最大程度地降低峰值风险,同时尝试追踪财富目标。此方法旨在为可能无法精确指定其风险承受能力的投资者提供帮助。我们将这种方法与经典方法进行比较。结论是,这种方法在低迷时期可能特别有益-在低迷时期显着地限制损失,同时提供大部分的向上利益。

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