Teaching Qwen3-4B to Trade: From Hold-Collapse to +9.4% Returns
Can you turn an LLM into a profitable trader? I spent three months finding out. This post covers the full arc: a 5-stage supervised fine-tuning pipeline on Qwen3-4B, a catastrophic failure mode I had to diagnose and fix, the checkpoint that hit +9.4% returns with perfect format validity, and why supervised learning hit a ceiling that only RL can break through. The Setup The model is Qwen3-4B. The task: given 30 days of OHLCV data plus 20+ quantitative features (RSI, MACD, volatility, beta, etc.) for a stock, output a structured JSON trade plan inside <think>...</think><answer>{plan}</answer> tags. The plan includes decision (enter/hold), side (long/short), stop loss, take profit, holding days, and position size. ...