Tech contracts are some of the most mispriced things you can trade, and the reason is simple. They pull in people who have very strong opinions about technology and very poor calibration on how long things actually take. High conviction plus bad timelines is a great recipe for spreads that do not show up in more efficiently priced categories.
Product Launch and Adoption Markets
A contract on whether a company ships a specific product by a certain date looks easy and prices terribly. Launches hang on internal corporate decisions, supply chain readiness, competitive pressure, and sometimes regulatory sign-off. Almost none of that is visible from the outside.
Tech insiders, the analysts who cover the company, and supply chain contacts have a real edge here. If you are not one of those people, you are trading against someone who might literally know the company's plans, and that is a bad seat to sit in.
Adoption contracts are friendlier. Asking how many users a product lands or whether it hits a market-share number depends on observable dynamics, not a boardroom. You can build a reasonable estimate from public download data, web traffic, and competitive comparisons. These tend to be priced loosely because most participants never bother modeling an adoption curve.
AI Milestone Markets
Markets on AI capabilities have exploded. Whether a model clears a benchmark, whether autonomous vehicles reach a deployment level, whether AI-generated content passes some quality bar. They are also about the least efficient markets I've seen.
The inefficiency comes straight from disagreement about the pace of AI progress. One camp thinks we're on the edge of rapid, transformative jumps. The other thinks current approaches are already hitting diminishing returns. Both price the same contract, and they price it wildly differently, so you get fat spreads and jumpy moves.
The useful split is between milestones that need a research breakthrough and milestones that just need scaling something that already works. Whether a model surpasses human performance on a brand-new benchmark is a research bet, genuinely hard to price. Whether AI-powered customer service reaches some market penetration is a business-adoption bet, and adoption follows curves you can actually reason about.
The Hype Cycle Effect
Tech markets ride the Gartner hype cycle hard. Inflated expectations, then disillusionment, then slow productivity. When a technology is at peak coverage, contracts on its near-term milestones tend to be overpriced. Once it slides into the trough, the same contracts tend to get cheap.
Track media sentiment, map it to where the technology sits on that curve, and you get a rough sense of which way the mispricing leans. Near peak hype, selling the optimistic side is usually right. During the disillusionment stretch, buying it often is, because the technology usually does deliver eventually, just on a slower clock than the peak promised.
Resolution Challenges in Tech Markets
Tech contracts also carry ugly resolution criteria. What counts as an autonomous vehicle, Level 3, 4, or 5? What separates a real market launch from a limited beta? When is a benchmark truly surpassed versus hit under narrow conditions that don't generalize?
That definitional mush is real resolution risk, and it doesn't exist in simpler markets. Before you touch a tech contract, read the resolution rules and ask whether they're tight enough to produce one unambiguous outcome. If they're vague, the price on screen might be answering a different question than the one in your head.
The Time Horizon Advantage
There's a consistent bias worth naming. Tech markets underestimate how long things take and overestimate how big the impact will be. That's Amara's Law, and it hands you a clean playbook. On near-term contracts inside six months, the NO side tends to be underpriced because everyone's too optimistic about timelines. On long-dated contracts three years out or more, the YES side tends to be underpriced because people discount the cumulative odds of the thing eventually just working.
None of this is a substitute for reading the fine print on each contract, but if you start from that timeline bias and check the resolution rules before you size in, you're already ahead of most of the room.