TOTAL VOLUME:
$116.8b
24H VOL:
$81,408,110
24H TRANSACTIONS:
1,362,287,844
OPEN INTEREST:
$1,158,719,757
338,335
Markets across
33,183
events
MATCHED EVENTS:
4,218
PLATFORM COVERAGE:
5
Polymarket:
42%
VS.
Kalshi:
58%
<$1.176M
- Polymarket
<$1.176M - Polymarket
89%
1W
News
Positive
Negative
Neutral
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Aug 20
Aug 21
Aug 22
Aug 23
Aug 25
Aug 26
Aug 27
Vol.
$3.4k
·
Resolves Sep 30, 2026
$
This market will resolve according to the median home value for all property types in the San Francisco Metro area on September 30, 2026. If the reported value falls exactly between two brackets, then this market will resolve to the higher range bracket. The resolution source will be official data from the Parcl Labs Sales Price Index for the San Francisco Metro area (Parcl_ID: 2900336). The settlement price will be calculated by multiplying the published price index value (price per square foot) by 1700 square feet, which is the median home size in the San Francisco Metro area. Parcl is set to publish this data on September 30, 2026. If no data for September 30 is released by October 10, 2026, 11:59PM ET, this market will resolve according to the most recently published data. (see: https://app.parcllabs.com/prediction-market-resolutions/52)
This market will resolve according to the median home value for all property types in the San Francisco Metro area on September 30, 2026. If the reported value falls exactly between two brackets, then this market will resolve to the higher range bracket. The resolution source will be official data from the Parcl Labs Sales Price Index for the San Francisco Metro area (Parcl_ID: 2900336). The settlement price will be calculated by multiplying the published price index value (price per square foot) by 1700 square feet, which is the median home size in the San Francisco Metro area. Parcl is set to publish this data on September 30, 2026. If no data for September 30 is released by October 10, 2026, 11:59PM ET, this market will resolve according to the most recently published data. (see: https://app.parcllabs.com/prediction-market-resolutions/52)
Prediction market odds often diverge from traditional analyst forecasts because they reflect real-money incentives and continuous price discovery rather than periodic published reports. Analysts may issue quarterly or annual housing outlooks, while this market updates minute-by-minute as traders incorporate new data. Markets tend to be faster at pricing in unexpected shifts in mortgage rates, inventory, or economic conditions. However, both sources can be useful: analyst reports provide detailed reasoning and methodology, while market odds reveal what informed traders believe will actually occur, making them complementary signals for understanding San Francisco's housing trajectory.
On Polymarket, traders set the odds by buying and selling shares of each outcome bracket. On Polymarket, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The current leading outcome reflects the highest probability assigned by the market, meaning traders have concentrated the most capital there. As new information arrives—such as employment reports, Fed decisions, or local real estate data—traders adjust their positions, which moves the odds in real time. The price of each outcome share directly represents the market's collective estimate of that scenario's likelihood, with the top outcome currently commanding 88.5% of total probability.
This market resolves around Sep 30, 2026, at which point the actual median home value for the San Francisco Metro area will be verified against credible public sources. The outcome is determined by comparing the official data to the price brackets offered in the market, and traders holding shares in the correct bracket receive their payout. Until that date, all positions remain open and can be traded. Resolution hinges on the availability of authoritative housing data for that specific date and region.
Several catalysts could shift odds significantly before resolution. Federal Reserve interest rate decisions directly influence mortgage affordability and buyer demand in the Bay Area. Employment reports and tech sector layoffs affect local purchasing power. Housing inventory releases and new construction data shape supply dynamics. Inflation readings and broader economic recession signals can trigger rapid repricing. Local policy changes—such as zoning reforms or tax adjustments—may also impact valuations. Additionally, unexpected geopolitical or financial events that ripple through equity markets often correlate with real estate sentiment, causing traders to reassess their positions and move the market.