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Open AccessArticle

Robust Portfolio Optimization in an Illiquid Market in Discrete-Time

Financial Engineering and Risk Management laboratory, National Research University Higher School of Economics, 20 Myasnitskaya Ulitsa, 101000 Moscow, Russia
Mathematics 2019, 7(12), 1147; https://doi.org/10.3390/math7121147
Received: 27 October 2019 / Revised: 20 November 2019 / Accepted: 21 November 2019 / Published: 24 November 2019
(This article belongs to the Special Issue Mathematical Game Theory 2019)
We present a robust dynamic programming approach to the general portfolio selection problem in the presence of transaction costs and trading limits. We formulate the problem as a dynamic infinite game against nature and obtain the corresponding Bellman-Isaacs equation. Under several additional assumptions, we get an alternative form of the equation, which is more feasible for a numerical solution. The framework covers a wide range of control problems, such as the estimation of the portfolio liquidation value, or portfolio selection in an adverse market. The results can be used in the presence of model errors, non-linear transaction costs and a price impact. View Full-Text
Keywords: dynamic games; robust optimization; dynamic programming; portfolio selection; transaction costs dynamic games; robust optimization; dynamic programming; portfolio selection; transaction costs
MDPI and ACS Style

Andreev, N. Robust Portfolio Optimization in an Illiquid Market in Discrete-Time. Mathematics 2019, 7, 1147.

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