Quant-Arena 实测：GPT-6 Astra 选股跑输等权基准
Einsia AI 的量化竞技场让 agent 先研究策略再冻结，用留出年份回测；GPT-6 Astra 在九个模型中得分最高，但 2024 年收益 10.7%，低于 3042 只股票等权基准的 17.1%。
being the smartest model in the room doesn't mean you beat the dumbest portfolio. Einsia AI's Quant-Arena makes that gap measurable: agents research a strategy, freeze it, then face a withheld historical test year. in the authors' results, GPT-6 Astra was the highest-scoring of nine evaluated LLMs. its strategy returned 10.7% in the 2024 test. the equal-weight benchmark across the 3,042-stock universe returned 17.1%. research feedback came from 2022–2023. the final evaluation included trading costs and estimated market impact. that's a useful test for agent builders: not just whether the code runs, but whether the strategy beats a baseline outside its research window. Quant-Arena accepts submissions from any model or agent harness. can yours beat the equal-weight benchmark? http://quant.lab.einsia.ai/arena
这条是引用着另一条写的：x.com/einsiaai/status/2113276693108408812