Quantum mechanics

Volatility (finance)

Microeconomics

Archaeology

Economics

Computer science

Jump diffusion

Architecture

Physics

Geography

Realized variance

Econometrics

Jump

Profit (economics)

Risks

We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional) Markovian setup. In particular, we analyse the hedging performance of the original architecture under rough volatility models in view of existing theoretical results for those. Furthermore, we suggest parsimonious but suitable network architectures capable of capturing the non-Markoviantity of time-series. We also analyse the hedging behaviour in these models in terms of Profit and Loss (P&amp;L) distributions and draw comparisons to jump diffusion models if the rebalancing frequency is realistically small.

Deep Hedging under Rough Volatility