16 H100’s to train a Temporal Convolutional Network

Summary

• The author describes using 6TB of alternative data to train a Temporal Convolutional Network for detecting price abnormalities after unexpected events.
• He contrasts the massive compute resources at Optiver (H200 clusters) with what a retail trader can access, emphasizing the gap in finding alpha.
• This is more of a reflective / educational post rather than a specific investment thesis or trade recommendation.
• Quality assessment: Noise – no actionable analysis, data, or trade rationale; purely anecdotal.