Highest temperature in Hong Kong on July 10?

Platform comparison

Market context

The underlying event is the forecasted peak heat for Hong Kong on 10 July 2026, where daily highs are expected to reach between 35°C and 35°C (86°F to 93°F), with the average July high sitting at 32°C (89°F)[2][8]. Historical data confirms July is consistently the hottest month, with the highest recorded monthly maximum reaching 35.7°C since 1885, while recent records show July 2026 breaking eleven heat-related milestones, establishing it as the hottest month ever recorded in the city[1][4]. The current crowd-implied probability of 0% for the "YES" outcome suggests the market is leaning heavily on the expectation that temperatures will fall within the standard high range rather than exceeding extreme thresholds, a view supported by the fact that even record-breaking years rarely surpass 36°C[1].

Traders should monitor the Hong Kong Observatory’s final "Daily Extract" publication, which will confirm the absolute daily maximum temperature once data is finalized, as the market cannot resolve until this official figure is released[7]. Key catalysts include any sudden shifts in weather patterns, such as the arrival of a typhoon or heavy rain, which could suppress temperatures below the forecasted range, alongside broader climate declarations that might influence long-term heat projections[4]. Recent news from the China Daily highlights that July has already become Hong Kong’s hottest month ever, breaking multiple records, which serves as a critical indicator for traders assessing the likelihood of extreme heat on the specific date[4]. The market is primarily leaning on the Observatory’s finalized data as the definitive catalyst, with no other political or economic events expected to directly influence the temperature outcome.

Sources: 1 · 2 · 3 · 4 · 5

Methodology

Political prediction markets differ structurally from sports betting: thinner liquidity, longer settlement windows, higher sensitivity to single news events. This page shows the live Polymarket quote for Highest temperature in Hong Kong on July 10? plus platform attributes for the three reference venues, so you can see at a glance where the deepest market for this question sits.

Resolution & payout

Political markets typically settle on official candidate or agency confirmation. Polymarket uses UMA Optimistic Oracle: a proposer posts the outcome with a bond, the two-hour window opens, then the smart contract pays USDC.

Kalshi settles USD via CFTC clearinghouse, with clearly defined resolution sources (e.g. AP race calls for elections). Betfair settles after the official outcome is registered with the league or agency. Manifold is play-money.

FAQ

How accurate are political prediction markets?

Historically more accurate than polls. Polymarket's Brier score on US 2024 elections was ~0.11 — better than 538 (~0.14) and every mainstream poll. Markets aggregate information with real skin in the game.

Can prediction markets influence election outcomes?

Markets reflect expectations rather than create them. Studies show public-facing markets can anchor expectations, but don't influence the underlying outcome. Political markets are information, not advocacy.

Which platform has the deepest political liquidity?

Polymarket — by far. US 2024 presidential volume was ~$3.5B vs Kalshi (~$200M) and Betfair (~$120M). Where Polymarket is geo-blocked, brokers like Trump Prediction route into the same order book at 0% fees.

Are political prediction markets legal in my country?

It varies. They sit in legal gray areas in most jurisdictions. Polymarket is geo-blocked from US/UK/EU; some broker frontends have a different geo footprint. Trade only with capital you can afford to lose, and only if you understand the legal status in your jurisdiction.

Why do Polymarket and Kalshi differ on elections?

Kalshi must follow CFTC compliance — strict definitions, clear resolution sources, US citizens only with KYC. Polymarket operates globally without CFTC oversight — deeper liquidity, but also higher regulatory risk.