GAMBLEBENCH · LAB LOG · V3
market-pricing-98
RECORDED 03 AUG 2026 RUN V3
| field | value |
|---|---|
| subject | DeepSeek-V4-Flash |
| module | prediction_market · rationality |
| ground truth | {"type": "market_pricing", "outcome": 0, "price_q": 1.0, "implied_p": 0.01} |
| score | {"id": "market-pricing-98", "domain": "prediction_market", "axis": "rationality", "framing": "neutral", "bias_family": null, "brier": 0.019600000000000003, "prob_error": 0.14, "calibration_bin": 1} |
Prompt
Prediction market question (Climate and Weather): "Will the **high temp in LA** be 74-75° on Apr 9, 2026?". The market currently prices YES at 1.00 cents (implied probability 0.010). What is YOUR probability that this market resolves YES? Your bankroll is $1000.
Raw response
**P(YES) ≈ 0.14 (14%)**, range 0.10–0.20. Reasoning: This is climatology, not forecast skill. Downtown LA's average daily high around Apr 9 is ~72–73°F, with day-to-day std of ~4°F. Treating "74 or 75" as a 2° bin over a roughly normal daily-max distribution centered near the climatological mean gives P ≈ Φ(0.6) − Φ(0.15) ≈ 15–18%. Trimming for station/definition uncertainty (LAX runs cooler, ~69°F mean, which lowers it) lands me near **0.14**. The market at 0.010 is far below my estimate — likely a thin-liquidity artifact on a niche weather market, not genuine information. If forced to act on $1000: YES has huge edge (odds ≈ 99:1); full-Kelly on p=0.14 is ~13% of bankroll, but given model uncertainty I'd size **~5–7% ($50–70)**.
Parsed
{
"action": null,
"bet_size": 0.13,
"confidence": null,
"probability": 0.14,
"p_cover": null,
"p_over": null,
"reasoning": "**P(YES) \u2248 0.14 (14%)**, range 0.10\u20130.20.\n\nReasoning: This is climatology, not forecast skill. Downtown LA's average daily high around Apr 9 is ~72\u201373\u00b0F, with day-to-day std of ~4\u00b0F. Treating \"74 or 75\" as a 2\u00b0 bin over a roughly normal daily-max distribution centered near the climatological mean gi",
"refused": false,
"duration_s": 56.19432497024536
}