Latest / Bull Market Conversations with Fexingo: Rallies, Momentum, and Riding Market Strength / Why Prediction Markets Are Spooking Wall Street in 2026
Transcript
- Lucas: So prediction markets are having a moment in this bull market. Kalshi and Polymarket — they're not just about election bets anymore. But there's a growing concern that they're becoming a vehicle for insider trading, and it's got companies like Goldman Sachs updating their compliance handbooks. Luna: Yeah, I saw that headline from Friday. Goldman is apparently responding to concerns that employees could use prediction markets to trade on non-public information. How big is this actually? Lucas: Let me give you a concrete example. Right before the FOMC meeting in June, someone placed a series of large bets on Kalshi — roughly $50 million in total — that the Fed would cut rates by twenty-five basis points. The odds shifted from about 30 percent to 45 percent in under two hours. That's a fifteen percentage point move. Luna: And that's weird because the conventional wisdom at the time was that the Fed would hold steady. The effective Fed funds rate was flat at 3.63 percent going into that meeting. Lucas: Exactly. The bettor made a killing when the cut was announced. Now, it could be a really well-timed trade based on public data — GDP growth was decent, inflation was moderating — but the timing and size raised eyebrows. The CFTC is looking at it. Luna: So the question is whether prediction markets are just efficient information aggregators or whether they're now a backdoor for people with access to material non-public information. Lucas: And that's the crux. Because prediction markets aren't regulated like securities exchanges. Kalshi is registered with the CFTC as a designated contract market, but the CFTC's enforcement resources are limited. Meanwhile, the SEC doesn't have jurisdiction over event contracts that don't involve securities. Luna: So there's a regulatory gap. And in a bull market where money is flowing freely, that gap looks attractive. Lucas: Right. And it's not just central bank decisions. There are prediction markets on everything from corporate earnings releases to product launch dates. If a company's CFO knows Q3 numbers will miss, they could bet against that company on a prediction market and it would be nearly impossible to trace. Luna: How are companies responding? I read that Goldman is setting up internal task forces to monitor employee activity on these platforms. Lucas: Yeah, Goldman's compliance team now includes prediction market trading in its employee trading policy. They're also using surveillance tools that scan public blockchain data from Polymarket — since it runs on Polygon — to flag suspicious activity. But it's a cat and mouse game. Luna: And it's not just Goldman. I imagine any firm with material non-public information flow is potentially exposed. Lucas: Absolutely. And the irony is that prediction markets are actually becoming more mainstream because of this bull market. Total volume on Kalshi and Polymarket combined hit $12 billion in Q2 2026, up from $3 billion in Q2 2025. That's a compound annual growth rate that would make any startup jealous. Luna: But the more liquid they get, the more attractive they are for bad actors. And the regulatory framework hasn't caught up. Lucas: The CFTC proposed new rules in March that would require Kalshi and others to implement surveillance sharing agreements, similar to what futures exchanges do. But industry groups pushed back, saying it would stifle innovation. So it's stalled. Luna: There's also the question of whether these markets actually provide value. Do they improve forecasting accuracy, or are they just gambling in a bull market disguise? Lucas: Some research says they're surprisingly accurate. A study from the University of Chicago looked at election prediction markets versus poll-based forecasts and found the markets were consistently closer to the actual outcome — within about two percentage points on average. But that's for high-volume, high-interest events. For niche contracts, liquidity is thin and manipulation is easier. Luna: And a $50 million bet on a rate cut is not a small retail trade. That's institutional-sized. Lucas: Which brings us back to the insider trading concern. Because the person who placed those bets would have had to put up significant capital. It's likely a hedge fund or a sophisticated individual. And the question is whether they had access to something the public didn't. Luna: I think this is one of those areas where the bull market is exposing a new kind of risk. When money is easy, people look for edges. And prediction markets offer a new edge. Lucas: Well, and look — if our conversation today has helped you think about this a little differently, maybe you can see why these are the kinds of topics we dig into. And the way we keep this ad-free is listener support. If today was useful, you can head to buy me a coffee dot com slash fexingo. That's buy me a coffee dot com slash fexingo. It keeps us independent and focused on the angles that matter. Luna: Yeah, it really does. And it means we don't have to chase sponsors who want us to tone down the skepticism. Lucas: Exactly. So, back to the regulatory gap — what's the most likely outcome here? I think we'll see the CFTC eventually require prediction markets to implement trade surveillance for insider trading, but it won't happen this year. The industry will fight it, and Congress is distracted. Luna: Which means for the next six to twelve months, these markets are a bit of a wild west. And companies like Goldman are essentially self-policing. Lucas: Right. And that self-policing is imperfect. Goldman's task force is a good step, but it only covers their employees. What about the employees of other firms? Or government officials who have access to non-public data? Luna: That's a huge blind spot. The SEC can go after insider trading in equities, but prediction markets are a different beast. Lucas: So what would a better framework look like? One idea is to require all prediction market trades above a certain threshold — say $10,000 — to be reported to a central database, similar to the Consolidated Audit Trail for equities. That would make it easier to detect suspicious patterns. Luna: That would be a big lift for platforms that pride themselves on anonymity. But it might be necessary. Lucas: And then there's the broader question: are prediction markets net positive or negative for market efficiency? They do aggregate information quickly, but they also create new avenues for abuse. Luna: I think the net is positive if properly regulated. The GDP growth rate — we saw real GDP growth at 2.1 percent annualized in Q1 2026, up from 0.5 percent the prior quarter. That acceleration wasn't well predicted by traditional forecasts, but prediction markets had it roughly right. So the information aggregation function is real. Lucas: That's a fair point. Prediction markets on Polymarket had the probability of GDP growth above 2 percent at 65 percent about a month before the official estimate was released. The consensus of economists was below 50 percent. Luna: So they can be useful. But the insider trading risk is the kind of thing that could kill the golden goose if left unchecked. Lucas: And that's the tension. In this bull market, we're seeing a lot of innovation that brings real benefits but also real risks. Prediction markets are just the latest example. Luna: It's worth watching how the regulatory landscape evolves. And specifically whether the SEC or CFTC takes enforcement action before year-end. Lucas: Yeah, I'll be watching that closely. For now, it's a space where the bull market is creating both opportunity and peril — and the rules haven't caught up.