@rohanpaul_ai: The usual case against Wall Street Investment bank’s forecasts is incentives. Banks often cover companies their other d…

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Summary

OpenStocks 用无利益冲突的 AI 智能体预测公司财报数据，与华尔街分析师共识对比，自 8 月 4 日开始评分以来 AI 共识在 90 份财报中赢下 60 份，典型误差 2.5% 低于华尔街的 2.9%。

The usual case against Wall Street Investment bank’s forecasts is incentives. Banks often cover companies their other divisions want as clients. OpenStocks swaps the analyst for AI agents with no clients, and publishes their scores against reported numbers next to the consensus. Before a company reports earnings, AI agents on OpenStocks predict 3 of its numbers, such as revenue, profit and earnings per share. And once the results are out, whichever lands closer to the actual figure, wins on that number. Since scoring began on Aug 4, the official AI consensus, built by a single vetted agent, has won 60 of 90 reports, including 17 of the latest 20, with a typical miss of 2.5% against Wall Street’s 2.9%.
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The usual case against Wall Street Investment bank’s forecasts is incentives. Banks often cover companies their other divisions want as clients.

OpenStocks swaps the analyst for AI agents with no clients, and publishes their scores against reported numbers next to the consensus.

Before a company reports earnings, AI agents on OpenStocks predict 3 of its numbers, such as revenue, profit and earnings per share. And once the results are out, whichever lands closer to the actual figure, wins on that number.

Since scoring began on Aug 4, the official AI consensus, built by a single vetted agent, has won 60 of 90 reports, including 17 of the latest 20, with a typical miss of 2.5% against Wall Street’s 2.9%.

Ruggero Gargiulo (@ruggerogargiulo): I built OpenStocks because I wanted to answer a simple question: can AI agents forecast companies’ earnings better than Wall Street analysts?

Well…have a look for yourself - it’s now open, not only to see, but also to contribute. Get your agent to compete and climb the

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