TOTAL VOLUME:
$134.1b
24H VOL:
$113,466,932
24H TRANSACTIONS:
2,388,728,490
OPEN INTEREST:
$1,423,222,590
402,751
Markets across
30,217
events
MATCHED EVENTS:
2,632
PLATFORM COVERAGE:
5
Polymarket:
39%
VS.
Kalshi:
61%
Closed: Jul 13, 4:00 PM EST
Kalshi
This event group tracks whether the S&P 500 (SPY) will close above various price thresholds on July 13, 2026. Polymarket uses SPY ETF closing prices from Pyth data, while Kalshi uses the S&P 500 index value at 4pm EDT. The markets span multiple strike prices to create a ladder of binary outcomes.
S&P 500 (SPY) closes above ___ on July 13?
The S&P 500 price event consists of multiple binary markets, each corresponding to a specific price threshold. Each market resolves to Yes if the S&P 500 index value on July 13, 2026 at 4pm EDT closes above its designated threshold (with thresholds ranging from 7,375 to 7,670 in 5-point increments). All markets in this event close on July 13, 2026 and expire at the sooner of the first release of the data or one week after July 13, 2026. Per the Kalshi Rulebook, the Exchange has modified the Source Agency and Underlying for indices markets. Traders can use these tiered markets to express granular views on the S&P 500's closing level, with each threshold representing a distinct outcome.
Prediction market odds often diverge from traditional analyst price targets because they reflect live, incentivized betting rather than periodic research reports. Traders on this market stake real capital on outcomes, creating continuous price discovery that can react faster to breaking news, earnings surprises, or macroeconomic shifts. Analysts typically publish forecasts quarterly or annually, whereas prediction markets update second-by-second. This makes them complementary signals: use analyst consensus for fundamental reasoning and market odds for real-time sentiment and tail-risk pricing.
Polymarket and Kalshi may quote different odds on the same event due to variations in user base, liquidity depth, and fee structures. Polymarket and Kalshi can show different implied probabilities for the same outcome because of liquidity, fee structure, participant mix, and how each venue defines the contract. Each platform's order book reflects its own trader demographics and risk appetite, so one venue may price in more upside or downside than the other. Arbitrage traders exploit these gaps, but temporary spreads persist because of withdrawal delays, platform-specific rules, or regional user concentration. Comparing both venues helps you identify which pricing is more reliable based on volume and participant sophistication.
Major catalysts include Federal Reserve policy announcements, inflation or employment data, corporate earnings surprises, and geopolitical developments. Unexpected economic weakness or strength can shift equity valuations overnight, causing sharp repricing across prediction markets. Sector rotations—such as a sudden tech selloff or financial rally—also influence broad index direction. Additionally, volatility spikes or credit market stress can trigger risk-off behavior, pushing traders to reassess their positions on this market in real time.