Former CFTC Commissioner Brian Quintenz stated that prediction markets have for the first time allowed small businesses to access risk management tools long used by Wall Street, specifically through contracts that transfer the risk of loss from specific business events to market participants willing to take on that risk.

In an article for Fortune, he cited the example of Tim Arrowsmith, a goat rancher in Northern California, who anticipates that his labor costs may triple due to the expiration of a state wage exemption policy on June 30; traditional insurance companies do not cover the risk of this policy, and there are no corresponding standard futures contracts available in the market.

Arrowsmith subsequently paid $50,000 on Kalshi to buy an event contract: if the relevant rules are not fixed by October 1 in Sacramento, California's capital, the contract will pay $500,000. If the policy is fixed, his labor costs remain unchanged, but he loses the $50,000 premium; if the policy is not changed, he can use the $500,000 to offset the increased labor costs.

This transaction is essentially purchasing insurance for policy outcomes at a fixed cost. Unlike traditional call or put options on financial assets, the contract's payment conditions are tied to a verifiable government action; it allows businesses to convert the discrete risk of "whether regulations will change before the deadline"—which is typically hard to insure—into a clear cash payout arrangement.

Quintenz believes that the derivatives market has long helped farmers, oil producers, and financial institutions stabilize costs and prices, allowing those willing to take on uncertainty to earn returns while conveying risk expectations to participants through market prices. Prediction markets extend this mechanism to policies, regulations, and other real-world events.

In terms of market mechanics, small businesses or those exposed to risk pay the contract cost to lock in compensation for the worst-case scenario, while counterparties sell the risk because they judge the probability of the event occurring to be lower than the implied probability of the contract. Platforms like Kalshi benefit from contract trading and market liquidity; market makers and speculators bear the losses from incorrect event judgments. Whether this model can expand depends on the legality of the contracts, trading depth, pricing efficiency, payment caps, and regulators' definitions of the boundaries of event contracts.

Source: Public Information