{"id":586,"date":"2026-06-09T07:47:00","date_gmt":"2026-06-09T14:47:00","guid":{"rendered":"https:\/\/quantcha.com\/news\/?p=586"},"modified":"2026-06-08T18:33:01","modified_gmt":"2026-06-09T01:33:01","slug":"quantcha-launches-consequitur-beta-free-cross-event-sensitivity-analytics-for-prediction-markets","status":"publish","type":"post","link":"https:\/\/quantcha.com\/news\/quantcha-launches-consequitur-beta-free-cross-event-sensitivity-analytics-for-prediction-markets\/","title":{"rendered":"Quantcha Launches Consequitur Beta: Free Cross-Event Sensitivity Analytics for Prediction Markets"},"content":{"rendered":"\n

Quantcha, the options trading analytics platform that has served thousands of investors since 2014, today announced the public beta of Consequitur<\/strong>\u2014a free tool that lets anyone map how real-world events move each other and model what a shift in one event does to the probabilities of the others.<\/p>\n\n\n\n

The beta is available now at consequitur.com<\/a>. No account or signup is required to explore the graph, set your own estimates, or run what-if scenarios.<\/p>\n\n\n\n

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Prediction markets already price levels\u2014the probability that any single event resolves YES\u2014continuously and in public. What no market shows you is the conditionals: how much one event\u2019s probability should move when another resolves. That gap is what Consequitur is built to work in. Every event arrives with a live AI baseline, informed by market prices where a market exists\u2014Kalshi, Polymarket, and more\u2014and every link between two events carries a starting estimate of how strongly one bears on the other. Where you disagree, you set your own. Then you run the what-if: hold an event at YES or NO and watch the implied probabilities ripple across everything connected to it.<\/p>\n\n\n\n

\u201cMarkets have gotten remarkably good at pricing whether any single event happens,\u201d said Ed Kaim, Founder of Quantcha<\/strong>. \u201cWhat nothing prices is how events move each other. If the ceasefire collapses, what happens to oil? If oil spikes, what does the next inflation print look like? If inflation surprises, what does the Fed do? Every desk carries a mental model of that cascade, but it lives in heads and hallway conversations\u2014there\u2019s nowhere to put real numbers on it and see what it implies. In options, your edge comes from estimating whether implied volatility is priced correctly. In prediction markets, it comes from estimating whether the probability itself is correct. Consequitur extends that one more step: estimating whether the relationship between two probabilities is correct\u2014then showing what that implies for every connected event. Map enough of those relationships across a book of positions and you have a sensitivity layer for event exposure\u2014the role a risk book plays on a trading desk, but over events instead of prices. That\u2019s the direction we\u2019re building toward.\u201d<\/p>\n\n\n\n

A Maturing Market\u2019s Unpriced Layer<\/strong><\/p>\n\n\n\n

Prediction markets have scaled from niche curiosity to mainstream financial instruments, with regulated exchanges, institutional market makers, and broadcast partnerships putting implied probabilities in front of millions of investors. The analytical layer on top of those markets is maturing quickly\u2014but it is almost entirely within-market: charting, order books, and portfolio tools for contracts the exchanges already list. The structure connecting those contracts\u2014how a move in one event reprices the next\u2014is something no tool has let an individual work with directly.<\/p>\n\n\n\n

The beta launches with a single anchor graph built on the question most likely to move every other market this year: does the Fed deliver at least one rate cut in 2026? The graph spans 21 events and 22 dependencies covering inflation prints, labor data, energy and geopolitics\u2014including the ceasefire-to-oil-to-inflation-to-Fed transmission chain\u2014and cross-domain catalysts.<\/p>\n\n\n\n

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Key Features<\/strong><\/p>\n\n\n\n