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arXiv cs.AI· Arther Tian, Alex Ding, Simon Wu, Aaron Chan·· 13 小时前AI 评分31

FIDES-Live:评估顺序交易智能体的行为一致性

FIDES-Live: Evaluating Behavioral Concordance in Sequential Trading Agents

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FIDES-Live 将 FIDES 从生成策略一致性扩展到顺序智能体轨迹审计,分离决策有效性、数值承诺遵守、执行与账本对账及基于回执的报告。对 7,299 个加密货币账户轮次和 310 轮股票试点审计显示,加密货币决策有效性为 97.35%,可评分响应中结构化报告准确率为 90.81%,但路由级决策与报告表现可能明显分化。

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Abstract:Sequential trading agents produce decisions, orders, execution receipts, account states, and reports that need not agree, even when the final portfolio value is correctly computed. We present FIDES-Live, an operational extension of FIDES from generated strategy concordance to the audit of sequential agent traces. The protocol separates structured decision validity, optional numerical commitment adherence, execution and ledger reconciliation, and receipt- grounded reporting, with explicit coverage and unscorable outcomes. We retrospectively audit ten requested inference routes over 7,299 cryptocurrency account-rounds and a 310-round equity pilot, using real market observations and local paper execution. Cryptocurrency decision validity is 97.35% and structured reporting accuracy is 90.81% among scorable responses, but route-level decision and reporting performance can diverge sharply. Commitment adherence is 94.36% overall; it falls to 62.63% on constraints emitted with nonempty order proposals, compared with 97.56% for valid empty proposals. All retained cash and position transitions reconcile with recorded fills, while execution controls and unavailable quotes explain separate rejection populations. Short-window marked returns provide descriptive context rather than a new test of whether concordance predicts alpha. These observations motivate reporting concordance, evidence coverage, activity, and financial outcomes separately. They do not establish long-run trading skill, semantic faithfulness of explanations, or causal benefits from audit feedback.
Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.36476 [cs.CR]
  (or arXiv:2610.36476v1 [cs.CR] for this version)
  https://doi.org/10.48550/arXiv.2610.36476

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Arther Tian [view email]
[v1] Tue, 27 Oct 2026 01:33:30 UTC (465 KB)

来源:arXiv cs.AI · arxiv.org