Written by: G_Gyeomm

Translated by: AIdidiaoJP, Foresight News

1. A new type of insurance directly priced by the market

The recently launched AI risk management tool Blanket is attempting to turn prediction markets into actual insurance tools that businesses can use. The logic is straightforward: businesses input their operational information, the system automatically diagnoses major risk exposures, and then recommends corresponding Kalshi event contracts to help businesses hedge these risks.

The mechanism of hedging itself is not complex. The structure of prediction market contracts is extremely clear—if the event occurs, pay $1; if it does not occur, pay $0. The real-time price of the contract is the market's collective judgment of the probability of the event occurring.

It is precisely this simple structure that gives prediction markets the potential to become real hedging tools. Businesses can buy event contracts in advance that will affect their operations, such as abnormal weather, fluctuations in energy prices, or changes in tariff policies. Once these risks actually materialize, the contract payouts can partially or even fully offset operational losses.

For a specific example: an ice cream shop would lose about $20,000 in revenue during a cool summer.

The hedging operation is as follows: buy 20,000 temperature contracts at a price of $0.30 each. If the average temperature in summer is below the preset threshold, each contract pays $1. The total cost is $6,000.

There are only two possible outcomes:

• Cool summer: temperature below the threshold, revenue down by $20,000, but the contract pays out $20,000 in one go. The final net loss is locked in at $6,000—which is exactly the cost paid to buy the contracts.
• Hot summer: temperature above the threshold, revenue unaffected, but the contract expires worthless, and the $6,000 cost is completely lost.

Regardless of the outcome, the final loss is firmly locked at $6,000. This $6,000 is essentially the insurance premium. And the rate for this premium is set not by an insurance company's actuary or any traditional underwriting institution, but by the market itself—thousands of buyers and sellers providing real-time prices with real money.

2. Is the hedging market actually functioning?

Prediction markets have accumulated sufficient speculative demand. They first gained a reputation through election predictions, then successfully expanded into sports, and the issue of trading volume has basically been resolved. The industry widely believes that the next growth area lies in expanding more practical use cases, and hedging demand has been repeatedly mentioned as one of the most promising directions.

In theory, its value is indeed significant. The existing gaps not covered by hedging tools are quite broad. Traditional business insurance for business interruption usually requires physical damage as a prerequisite. For example, a ski shop that misses out on revenue because it has not snowed much throughout the winter—this purely "operational risk" finds very few appropriate insurance products available in the market.

The futures market does have mature hedging tools, but the barriers are high: it requires signing an ISDA agreement, opening a dedicated futures account, providing margin, and meeting minimum contract size limitations. These conditions are not an issue for large institutions but are almost unreachable for ordinary small and medium-sized enterprises. Goldman Sachs can maintain a professional derivatives trading team, but a corner café clearly cannot.

The problem is that there has always been a significant gap between theoretical rationality and actual usage. Prediction markets have long carried the label of "gambling", and whether they can really operate as an independent hedging market—not merely as a speculative tool—has never been systematically validated.

The real question that needs to be answered is: has the prediction market been used for hedging? Does real hedging demand exist? Trading behaviors themselves can provide clues. We selected three sets of data for comparison.

The first set is CME grain futures—a typical traditional hedging market mainly used to mitigate losses from fluctuations in agricultural and livestock prices.

The second set is the Kalshi sports market—where the hedging demand is extremely limited, and trading is almost entirely driven by speculation.

The third set is the Kalshi weather market—it addresses weather risks in a way similar to CME weather futures while sharing the exact same event contract structure and trading environment with the Kalshi sports market. This makes it an excellent test sample—to see whether its trading behavior leans more toward one side or the other.

Hedging and speculation typically exhibit different trading characteristics. Hedgers tend to establish positions before the real risk window arrives and hold them until expiration; speculators enter and exit more frequently, chasing prices, and have noticeably higher turnover rates.

If the turnover rate and holding behavior of the Kalshi weather market are closer to traditional hedging markets rather than sports markets, then hedging demand does indeed exist.

Conversely, if it bears no difference from the sports market, then actual usage is much closer to pure speculation. In this case, tools like Blanket may be responding only to an idealistic vision in the industry rather than to verified real demand supported by data.

This analysis's dataset covers 1,265 Kalshi markets settled between August 2025 and August 2026. The selection criteria are: cumulative volume of at least 500 contracts and trading sustained for at least three days.

3. Data 1: Average Daily Turnover Rate

First, let’s look at how frequently positions in each market are traded. The turnover rate is defined as daily trading volume divided by open interest (OI) on that day. We calculated the daily turnover rate for each contract in every market and then took the median for the entire trading period.

The results are clear: the turnover rate for Kalshi weather contracts is the lowest at 0.210. The traditional hedging product, corn futures, stands at 0.266, while Kalshi sports contracts are the highest at 0.315.

The turnover speed for sports contracts is about 1.5 times that of weather contracts. This indicates that weather contracts have a relatively longer holding tendency, preliminarily suggesting the potential existence of real hedging demand.

However, we should be cautious: corn futures have a turnover rate that falls in between, and the differences among the three sets of data are not particularly dramatic. Relying solely on turnover rates does not fully confirm the existence of hedging demand in the weather market. Currently, this data only clearly indicates that the turnover for weather contracts is significantly lower than that of sports contracts.

4. Data 2: Hold to Expiration Ratio

The second key metric is the hold to expiration ratio—measuring how much open interest remains untouched when settling. The calculation is the final open interest for each contract divided by total trading volume. A higher value indicates that more positions were firmly held until expiration.

The differences in results are striking: regardless of how long trading lasts, the hold to expiration ratio for weather contracts exceeds 0.5. In contrast, sports contracts only have ratios of 0.012 and 0.033. Within the 3 to 45 days trading window, weather contracts are 42.8 times that of sports contracts; in the period exceeding 45 days, the difference is still 16.7 times.

This clearly indicates that weather contracts are far more inclined to "be held and not touched" compared to sports contracts. Hedgers hold contracts with the expectation of receiving payouts once the risk occurs, rather than trying to make profits from price fluctuations. Therefore, the high hold to expiration ratio strongly supports the judgment that real hedging demand exists in the weather market.

Of course, this cannot be directly interpreted as meaning that the entire weather market is used for hedging. This data has not tracked the identities of the buyers and sellers of individual positions, so it cannot be simply equated to the proportion of original buyers holding to expiration. What can be confirmed is that there are significant behavioral differences between the holding actions of weather contracts and those of sports contracts.

5. Data 3: When Positions Were Established

The final question is: when were these positions established? We calculated the daily open interest for each contract divided by its peak open interest and transformed the time from launch to expiration into a progress bar from 0% to 100%, then plotted the median curve.

The judgment standard is to check when the peak open interest has reached half. If it reaches half with a longer time remaining until expiration, it indicates that the positions were established earlier—which aligns more with the behavior of hedgers.

For weather contracts in a trading duration of 3 to 45 days, they reach half of peak open interest at 47% of their life cycle, with 53% time left until expiration. In the same range, sports contracts only reach half at 65%, leaving only 36% of time remaining.

For contracts exceeding 45 days, the differences are even more pronounced. Weather contracts reach half with 32% left until expiration, while sports contracts only have 1.3% remaining. Across all ranges, weather positions are established much earlier than sports positions.

This tendency of "early layout" is precisely a characteristic feature of traditional hedging markets. As of August 11, 2026, in CME grain and livestock futures, contracts with six months left until expiration have already built substantial open interest. Corn futures even have positions held on contracts that expire after 16 months, with 65,127 contracts still open.

This reflects a tendency to take action before risks truly materialize. The behavior of Kalshi weather contracts clearly aligns more closely with traditional hedging markets than with sports markets.

6. Hedging relies on the liquidity established by speculative institutions

To conclude: the Kalshi weather market is neither a purely hedging market nor a purely speculative market like sports. Speculative demand still contributes a significant portion of liquidity, but above that, hedging demand has also relatively clearly emerged.

Three indicators point in the same direction: weather contracts have lower trading frequency, retain more positions at settlement, and are established earlier. No single indicator can confirm trading intent at 100%, but the high consistency of these behaviors collectively supports one judgment—that there indeed exists a holding demand in the Kalshi weather market that differs from sports, and a significant portion of it is likely real hedging demand.

More importantly, speculative demand is not so much a weakness of prediction markets as it is a prerequisite for the establishment of hedging functionality. A market with only hedgers and no speculators would struggle to find enough counterparty liquidity.

In prediction markets, speculators are responsible for pricing and providing liquidity, while hedgers transfer risks they do not wish to bear based on this foundation. Risks are no longer directly underwritten by insurance companies but are naturally dispersed among market participants through trading.

Therefore, the next stage of growth for prediction markets does not hinge on "squeezing out" speculation or completely shifting towards hedging. What is truly important is how much real corporate hedging demand can be layered on top of the liquidity foundation already built by speculation. This is the core variable that will determine whether it can evolve from an "interesting speculative tool" to "usable risk management infrastructure."