Could Prediction Markets Be a New Hedge Against Business Risk?

A recent disclosure from prediction market platform Kalshi offers a glimpse into a potentially emerging approach to business risk management: using event-based markets to hedge against revenue losses tied to uncertain outcomes.

A Los Angeles hospitality group operating 25 bars, many near Dodger Stadium, placed a $60,000 trade on Kalshi that would pay off if the Los Angeles Dodgers failed to reach the World Series. After the team's playoff elimination, the position reportedly returned nearly twice the original stake, helping offset revenue the business expected to lose from the absence of additional postseason games. Reuters described the trade as part of a small but growing effort by businesses to hedge risks that traditional financial products may not cover.

For businesses whose revenue depends heavily on sports seasons, weather events, entertainment schedules, tourism patterns, or other unpredictable factors, the case raises an important question: Could prediction markets become a mainstream tool for managing customer-demand risk? 

The concept has appeal, but only when companies fully understand the financial exposure they are trying to hedge, says Associate Professor of Marketing Daniel McCarthy at the University of Maryland's Robert H. Smith School of Business.

Measuring the Real Cost of an Event

McCarthy’s research focuses on customer lifetime value, customer-based corporate valuation and business forecasting. He says the first challenge is determining how much a specific event actually affects sales.

A playoff loss may seem to have an obvious impact on nearby restaurants and bars, but isolating that effect from other factors is more complicated than it appears.

“The hard part is isolating the impact of the playoff exit from other factors at the time, such as weather, promotions and other local events,” McCarthy says. “Past exits can help, but close comparisons may be scarce, and older data may no longer reflect how the business operates.”

Companies increasingly collect detailed customer-level data, including foot traffic, transaction volume and repeat visitation patterns. Those data can help estimate how much revenue is truly tied to a specific event. “A company with locations in several cities can compare sales and foot traffic around similar exits, using less affected venues as a benchmark and accounting for those other differences,” McCarthy says. “So, it's doable, but you need to be careful; it's easy to get it wrong.”

The challenge reflects a broader business reality: Before a company can hedge a risk, it must quantify that risk accurately.

From Betting to Business Risk Management

While prediction markets are often discussed through the lens of speculation or sports wagering, the Dodgers example highlights a different use case. 

Businesses routinely purchase insurance or use financial derivatives to protect against interest-rate fluctuations, currency movements and commodity-price changes. Prediction markets could potentially extend that logic to event-driven risks that are difficult or impossible to hedge through traditional channels.

McCarthy believes such tools could become valuable when there is a clear link between an event and business performance. “I can see these becoming useful when a business has a clear financial exposure to a particular event,” he says. “Kalshi can help put a probability on that event, but the company still needs its own estimate of the profit at risk.”

In other words, the market may provide a mechanism for transferring risk, but it cannot tell a business how much revenue is actually at stake.

For broader adoption, McCarthy says several conditions must be met. “For this to become routine, the contracts need to match the business's exposure, be reasonably priced and have enough buyers and sellers to support meaningful trades.”

That requirement points to a key limitation of prediction-market hedging. Unlike standardized insurance products, event contracts may not perfectly correspond to a firm's specific financial exposure.

Matching the Hedge to the Risk

Even when a company's analysis is sound, execution matters. A hedge that is too large or poorly aligned with the underlying exposure can create new problems instead of reducing risk. “The first risk is that the bet does not actually offset the business's losses, either because the contract is a poor match or because the company bets too much,” McCarthy says.

Finance professionals call this "basis risk" — the possibility that a hedge will not closely track the losses it is intended to offset. As businesses explore event-based derivatives, another concern involves incentives and market integrity. 

Guarding Against Conflicts of Interest

McCarthy says the biggest long-term challenge may emerge when organizations or individuals can influence the outcomes they are betting on. “My bigger concern is when someone can both bet on an event and influence its outcome, since larger bets can create stronger incentives to interfere,” he says. 

Such conflicts have long been a focus of regulation in traditional financial markets, and similar safeguards could become increasingly important if prediction-market hedging expands. “As with other derivatives, that makes trading limits, disclosure of conflicts and credible enforcement really important.”

Whether prediction markets become a routine component of corporate risk management remains uncertain. But as companies gain access to increasingly sophisticated customer and revenue data, McCarthy says they may become more proactive in identifying and hedging risks once viewed as little more than bad luck.