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Kalshi Ideas

Hacker News

Kalshi Ideas

Hey everyone, Luana from Kalshi here! I’m really excited to announce a new feature we’ve been working on for a while: Kalshi Ideas. Kalshi’s allows people to trade directly on the events that impact them most. Everyone faces different risks: inflation, extreme weather, mortgage rates, Supreme Court decisions, student debt, government shutdowns, and more. Typically, you’d get exposure to these events by trading assets that are correlated to the event, or paying a bank tons of money to get exposure to that event - both are messy options. An important element of trading and mitigating the risks is understanding those risks at a deep level. Our users often have intense debates about where the world is going…those debates result in a market price for an event. Someone looking at the price without knowing the why behind it might feel at a disadvantage compared to those who are in the middle of that debate. We launched Kalshi Ideas to create a new venue for the debate to take place, from those with skin in the game, directly on the Kalshi platform. Kalshi Ideas allows those with a position to share why they made that trade, and opens up the floor for those on opposing sides to have an open debate. We hope this encourages a thoughtful discussion, and helps those who are thinking about entering a market form their own opinions. Kalshi Ideas is currently available only on our mobile app, which you can download at https://kalshi.app.link/ideas1 We plan on adding many improvements and new features in the coming months, so if you have any feedback please reach out directly at luanalopeslara@kalshi.com. I look forward to hearing from you!

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: excited, lua, ide · Missing: https docs, just released, exist
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, open · Missing: mac, agents, macos
47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, users, trading · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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