📈 Prediction Markets Recorded Over Billion Trades in Q3 The number of trades across prediction markets exceeded 1B in Q3 2026, setting a new all-time high and more than doubling from the start of the year. The biggest driver of growth in Q3 was @Kalshi , which accounted for the majority of the increase and significantly widened its lead in trade count.

@tradingview Criticize the moderation, then get suspended over a trading idea from June. Who checks the people handing out these bans? Here’s the context. I told another trader that trading isn’t about being right or wrong. That message got moderated too. With public chat closing, people started trolling about who I’d tell about DTT now, throwing around accusations of “advertising.” I challenged that and called out the poor moderation. Then Vanathi flagged an old June idea showing my DTT checklist and issued a month-long suspension. Her written explanation: “You have mentioned DTT in the ideas which is a violation.” I asked why mentioning ICT is acceptable. “ICT is a general technique like Pivot.” DTT means Direction, Target, Timing. It’s how I structure my trading analysis. That response still doesn’t explain why mentioning one trading method is acceptable and mine isn’t. Given the sequence, this looks retaliatory to me. I’m supposed to believe the sudden issue with a 4 months-old post had nothing to do with me criticizing the moderation? I couldn’t care less about getting unbanned. But I’m absolutely going to question how these decisions are made. I have an audience to show this to. What happens to users who don’t? Who independently reviews disputed decisions, and what happens when a moderator gets it wrong? If TradingView trusts moderators with the power to silence users, it needs to hold them accountable for how they use it. Screenshots below. Judge the exchange for yourself.

Morgan Stanley accidentally leaked its deal book. A staffer sent an internal file listing 100+ investment-banking deals, mostly across Asia, including IPO candidates in China, South Korea, and India, plus PE and pension-fund backers. The email was recalled. Too late. A blurred version surfaced on Instagram. The bank says it acted quickly and is engaging the parties involved.

I can’t underscore enough how much of a tailwind AI advancements are for prediction markets. Historically futures and options have always been significantly more liquid than prediction markets because pricing them and providing delta-neutral liquidity is a lot easier. It’s super simple to run a market making strategy that just hedges exposure to an asset on any liquid venue. After all, there are 100s of liquidity sources for ETH or BTC. But it’s orders of magnitude harder to run a delta neutral strategy for the rental cost of NVDA’s chips, for example. Which is why the majority of prediction markets liquidity comes from LPs and traders that model the outcome of a specific contract, then make liquidity where they think the price should be. It’s the modelling part that used to be too intensive for even the most active and performant high frequency trading shops. But now, what once required significant engineering resources to build a custom machine learning algo from scratch is as simple as connecting a number of data APIs to a strategy that runs through the frontier models. And with new innovations like Jev, these strategies become increasingly feasible at scale. This is an area of priority interest for Trueo. I’m regularly told that if we can solve for liquidity on our platform we have an opportunity to directly competing with Poly and Kalshi. What I’m saying is that this goal has never been more achievable. And we’re going to prove it very soon.

A federal judge dismissed a multi state lawsuit led by New York Attorney General Letitia James targeting the DOGE Treasury initiative. The court tossed the challenge brought by 18 states as moot, clearing another hurdle for the White House.