用 Grok Bot 搭量化策略的自校验循环
作者认为量化里真正的优势不是生成更多策略,而是让 Grok Bot 协调研究—回测—验证—反馈的闭环,用硬规则剔除假 alpha,人只审批过关的。

Grok Bot loop engineering is where AI agents stop being demos and start becoming systems One agent finds the idea Another tests it Another tries to break it The loop keeps running until the result survives verification or gets rejected Research → Analyze → Backtest → Verify → Report → Feedback → Repeat That matters even more in quant A strategy can show: +48.6% annualized return 2.31 Sharpe -12.4% max drawdown 214 trades and still be fake alpha The real edge is not generating more strategies It is building a self-correcting loop that checks out-of-sample performance, transaction costs, leakage, robustness, and regime dependence before capital moves Grok Bot coordinates the loop Python runs the math hard rules reject the bullshit the human approves what survives that is what AI trading should look like read the full breakdown below ↓
这条是引用着另一条写的:x.com/0xkvro/status/2106763188100362388