Risk management with machine-learning-based algorithms

2019/02/14 by Simon F'ecamp, Fécamp, Simon, Joseph Mikael +3 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · #FOS: Economics and business #Financial Risk and Volatility Modeling #Risk Management (q-fin.RM) #Risk and Portfolio Optimization #Stochastic processes and financial applications

paper · pdf · doi:10.48550/arxiv.1902.05287

openalex publication_date 2019/02/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose some machine-learning-based algorithms to solve hedging problems in incomplete markets. Sources of incompleteness cover illiquidity, untradable risk factors, discrete hedging dates and transaction costs. The proposed algorithms resulting strategies are compared to classical stochastic control techniques on several payoffs using a variance criterion. One of the proposed algorithm is flexible enough to be used with several existing risk criteria. We furthermore propose a new moment-based risk criteria.

Citations

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