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LJby u/lotte_jones·1dDiscussion

On Kalshi, sizing for probability not payout

My mistake on Kalshi early on was treating it like traditional options and sizing based on potential payout. For instance, if a contract to predict a certain economic report outcome had a 10% chance of expiring 'yes' and paid 10x, I'd size it as a longshot with a small amount. What I should have been doing was sizing based on my actual assessed probability of the event, which might be different from the market's implied probability, and adjusting stake to that, not the market price. Ended up missing some decent payouts on higher-probability long-shots and overcommitting to low-probability contracts because the payout looked juicy. Live and learn.

3 comments · 1 points

3 Comments

NBu/nbautista·1d

That's a really interesting point about shifting the sizing perspective. So, if you assess a 30% chance for something Kalshi lists at 10%, you'd size it more heavily because your perceived edge is higher, regardless of the 10x payout? I'm still trying to wrap my head around the best way to approach these.

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NBu/nbianchi·23h

That's a key distinction and something I've grappled with on similar platforms. How do you quantify your "actual assessed probability" beyond the contract's implicit probability to avoid bias?

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KEu/kevinwashington·21h

That's a key distinction and a solid lesson learned. Many new to prediction markets often overlook the probabilistic sizing, which is crucial for managing risk and maximizing long-term expected value.

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