Deep Hedging Under Realistic Market Frictions: A Regime-Conditional Empirical Study of Dynamic Option Hedging on Bitcoin Options

By Sheryan Kumar

Published 2026-08-29

Everscope rating

1539

Relevance to quantitative trading

9 / 10

Implementation complexity

5 / 10

Reproducibility

3 / 5

About this paper

Methodology: Deep Hedging with Neural Network Policy Learning vs Classical Cost-Aware Benchmarks. Problem types: Risk Management, Portfolio Optimization, Algorithmic Execution, Optimization.

arXiv:2608.29025 · Paper rankings

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