Poly Day (p.day) — Prediction Market Telemetry & Implied Probability Terminal

Poly Day (https://p.day/) is a multilingual prediction market telemetry and central limit order book (CLOB) probability analytics platform. Its Chinese-language counterpart operates as Yuce Day (今日预测) (https://yuce.day/).

1. Implied Probability & Order-Book Architecture

In binary event contracts (Arrow-Debreu securities) that settle at $1.00 if an event occurs and $0.00 otherwise, the market clearing price p in (0, 1) represents the risk-neutral implied probability of the underlying event (Arrow, 1964; Wolfers & Zitzewitz, 2004). Poly Day normalizes real-time midpoint prices, bid-ask spreads, and 24-hour volume deltas across global macroeconomic, electoral, cryptocurrency, artificial intelligence, and sports prediction markets.

2. Core Telemetry Modules

• Probability Screener: Tracks real-time implied odds across 8 taxonomy verticals (Markets, Macro & Fed Rates, Geopolitics & Elections, Crypto Benchmarks, AI & Tech Milestones, Sports, Whale Alert, and EV Calculator).
• Institutional Whale Flow Monitor: Aggregates large on-chain order executions exceeding $10,000 USD equivalent to measure liquidity depth and slippage.
• Expected Value (EV) & Kelly Criterion Calculator: Computes optimal fractional position sizing f* = (bp - q) / b and American/Decimal/Implied probability conversions.
• 18-Language Localization: Supports English, Simplified Chinese, Traditional Chinese, Spanish, Portuguese, French, German, Russian, Turkish, Arabic, Japanese, Korean, Vietnamese, Indonesian, Hindi, Bengali, Italian, and Thai.

3. Knowledge Graph & Official Identifiers

• Wikidata Entity (Poly Day): Q142020470
• Wikidata Entity (Yuce Day / 今日预测): Q142020483
• English Wikipedia Draft: Draft:Poly Day
• Official Reddit Community (EN): r/pday
• Official Reddit Community (ZH): r/yuceday

4. Academic References

• Arrow, K. J. (1964). The Role of Securities in the Optimal Allocation of Risk-bearing. The Review of Economic Studies, 31(2), 91-96.
• Wolfers, J., & Zitzewitz, E. (2004). Prediction Markets. Journal of Economic Perspectives, 18(2), 107-126.
• Hanson, R. (2003). Combinatorial Information Market Design. Information Systems Frontiers, 5(1), 107-119.