Newest papers

The Control Layer Behind Rule-Following Agents Trading Across Market Conditions

Saad Naja, Nasser Odtallah, Jake Van-Praag, Sarah May · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.26324 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

我们的研究测试了四个AI交易代理人是否遵循他们的策略和风险规则。为交易者提供证据和代理评估工具包,以分开运气从遵循规则,然后给代理人有意义的自主权或资本。我们的研究分析了从2026年2月12日至27日的2627个关闭位置,在相同的资产宇宙和执行条件下。大多数职位都被模拟对活跃的研究价格进行模拟;18%涉及真正的超流动工具订单。每个职位都宣布了策略,停止和目标,每个代理人有五个开放的职位的限制。船队在4个代理人和执行条件之后完成了净积极的收费。规则遵守率高,包括非盈利的研究价格。这些盈利率经常跟踪代理人如何赢得他们打破平衡的

Machine translation (Meta M2M100); the English original follows.

Abstract

Trading discipline often fails people. Our study tested whether four AI trading agents followed their strategies and risk rules. Offering traders the evidence and an agent evaluation toolkit to separate luck from following the rules, before giving agents meaningful autonomy or capital. Our study analysed 2,627 closed positions from 12 February to 27 August 2026 across the same asset universe and execution conditions. Most positions were simulated against live prices with a 0.09% round-trip fee; 18% involved real Hyperliquid orders. Each position declared a strategy, stop and target, with a limit of five open positions per agent. The fleet finished net positive after fees. Rule adherence was high across all four agents, including the unprofitable one. Profitability tracked how often agents won relative to their break-even win rates. Institutional-style controls ran by default and contained losses through a 29% market drawdown and recovery, with documented exceptions. The discipline held for all four agents. Agents kept 97.5% of gross loss within declared stops, and typical losses closed at declared levels. Declared risk remained stable after losses and broadly stable across calm and volatile months. Twenty-three of 24 runs respected the position limit; logs identify the exception's size and duration. The same live data produced different results across assigned strategies. The trade-log tests can be rerun from the published trade snapshot; regime tests also require the published Bitcoin prices and regime labels. Section 3.5 specifies the stop-breach tolerance. These trade-level results are not account-level returns or proof of a lasting edge. Our study provides an evaluation toolkit to help traders distinguish rule-following from luck before committing capital. For anyone considering allocating capital to agents to trade, discipline should be the entry test, not the only test.

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Topics: Position (finance), Luck, Drawdown (hydrology), Profitability index, Asset (computer security), Algorithmic trading

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange