Software developer working across quant finance, real-time systems, and AI tooling.
I write code; occasionally it works.
1 sessions Β· 0% hit rate Β· best streak 0 Β· 0 exact / 0 near / 1 miss
π 2026-09 earnings report: 1 sessions, 0% hit rate, probability -0.2pts. The alpha is imaginary but the vibes are quarterly-confirmed.
| Date (IST) | Predicted | Actual | Result | Ξ pts | Hire probability |
|---|---|---|---|---|---|
| 2026-10-01 (today) | 22 | β³ | Market open | ||
| 2026-09-30 | 39 | 12 | β Miss | -0.25 | 0.17% |
How does this work? (a.k.a. why is this in my README)
- Every day at 00:05 IST a GitHub Action predicts how many commits I'll make that day (rounded 7-day average).
- The next midnight it fetches my real commit count and settles the trade.
- Exact hit: +1 pts. Off by one: +0.5 pts. Streaks add a small bonus.
- Miss: -0.25 pts. Zero commits after predicting some: -0.5 pts.
- 10+ commits and 3x the forecast counts as market manipulation: -1.5 pts.
- 10+ commits within 60 minutes is hourly manipulation: -1.5 pts.
- Visitors: π/π on today's voting issue to predict whether the bot hits. No prize, just bragging rights.
- Monthly: on the 1st, an earnings report summarises the previous month.
- Probability is 100% fiction. The 100% real part: I actually ship code, and I'm actually looking for a job.
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