Taming the Greeks: Option Portfolios with Inductive Biases
We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of portfolio-level risk exposures. While neural networks trained to optimize risk-adjusted performance have been shown to outperform traditional rules-based strategies, such approaches remain agnostic to the sensitivities of the resulting portfolios with respect to specific underlying risk factors. We propose a general training objective that combines a performance-driven loss with a differentiable risk-sensitivity penalty, enforcing neutrality to selected risk dimensions. Unlike reinforcement learning methods that approximate optimal hedging polic...
| Authors | Wee Ling Tan, Stephen Roberts, Stefan Zohren |
|---|---|
| Primary category | q-fin.PM |
| Published | 27 September 2026 |
| Last updated at source | 27 September 2026 |
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