From Natural Language to Executable Option Strategies via Large Language Models
“We also present a new dataset for this task and demonstrate that our neuro-symbolic pipeline significantly improves execution accuracy and logical consistency over direct baselines.”
AssetVolatility and optionsoptions
StrategyOptions strategiesnews sentiment
TechniqueLarge language model
InputsText and news
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
Institutional-grade audit of this strategy.
£5 — Request the audit- Audit of the paper claims accounting for costs, luck, crises, originality, geography, etc.
- Reproduction code integratable into Bloomberg, IBKR, etc.
- Bias-free datasets for backtesting included
- Delivered in 2 working days
The paper's neighbourhoodOptions trading strategies by year
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
| Similar papers | citation | same method | same asset | same authors | |
|---|---|---|---|---|---|
| Call Calendar Spread on Overnight Option Strategy by Tang et al. | 2026 | ||||
| Evolutionary Factor Searching for Sparse Portfolio Optimization Using Large Language Models by Chen et al. | 2026 | ||||
| Volatility Disagreement in the Options Market by Bali et al. | 2026 | ||||
| Profitability of Delta-Neutral Option Strategies on Nifty 50 and Constituent Stocks: Evidence from 2019-2024 by Pillai | 2026 | ||||
| Engineering the Mean-Reversion Delay in Dispersion Trading: A Market-Implied Finite-Dimensional Proxy for High-Dimensional Correlation Manifolds by WANG | 2026 |