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SOTA: Stock Options Trading Agents Guided by Option-Implied Return Distributions

Paper recorded by Signals 4 on 2026-10-07 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-07 on arXiv · recorded by Signals 4 on 2026-10-08

Category: cs.AI · 人工智能 · first seen 2026-10-08

Abstract

As option markets grow and AI advances, agentic systems for option trading are gaining increasing attention. Language-model-based agents can reason over contextual information such as news, but option trading presents a particularly challenging decision problem: a single stock can have thousands of contracts, and the agent must decide both which contracts to trade and how to combine them. Existing

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#399 most recent of 960 cs.AI papers we have recorded · ↑ newer: Training Parallel Speculative Draft Models by Directly Minimizing Expe · ↓ older: Reasoning-Token Spikes Under Prompted Untruthful Responding in Large L

Cite this page: SOTA: Stock Options Trading Agents Guided by Option-Implied Return Distributions: the #399 most recent of 960 cs.AI papers we have recorded (as of 2026-10-07). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/sota-stock-options-trading-agents-guided-by-option-implied-return-distributions.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json

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