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cs.LG2026
Deep catastrophic-risk-aware reinforcement learning
Carlos Octavio Pérez Mendoza, Carlos Pérez Octavio Mendoza, Frédéric Godin
Estimating extreme risk in reinforcement learning becomes increasingly difficult as the confidence level increases, since only a small number of observations contribute to empirica…
q-fin.CP2026
Insights on Time-consistent Deep Hedging under Elicitable Dynamic Risk Measures
Shuyi Zhang, Frédéric Godin
We study deep hedging where the objective is expressed in terms of a dynamic risk measure, under which sequential decisions are time-consistent. We tackle the problem of basket opt…
q-fin.CP2026
Is Deep Hedging Reinforcement Learning?
Frédéric Godin
The deep hedging framework of Buehler et al. (2019) trains a neural network policy, via Monte Carlo simulation of price paths and stochastic gradient descent, to minimize a risk me…