For example, one of the top trending ~~bets~~ markets right now is on whether Miami or Indiana will win the NCAA football championship tonight. You can either take "Yes" on Indiana at 74c, or "No" at 27c, or you can take "Yes" on Miami at 27c or "No" at 74c. Or, there's another potential outcome - you can also bet on a tie at 10c yes/91c no.
Is this research suggesting that an optimistic Miami fan can somehow get a better return by buying "No" on Indiana than a "Yes" on Miami?
Why is Kalshi structured with these yes vs. no options for all outcomes?
it's basically how they do margin. otherwise you wouldn't be able to sell / post asks without already having a long position. for kalshi, it's actually one single security in the background they just present it as two order books (but really it's one). for polymarket, they are two distinct products that trade separately, and technically could have arbitrage between them. although in practice they're normally priced correctly to sum to 1 (or 1.01)
There's another idea, which is make contacts that pay out in shares of an ETF, but I haven't seen this idea put into practice
In prediction markets if the markets are fully efficiently priced, in the absence of transaction costs you WILL get 100% back in the long run.
Slots are also unskilled games, prediction markets clearly some participants have a clear market edge, thus not efficiently priced.
This is basically equivalent to the observation that, in a perfectly efficient market, no entity can ever make a profit.
And yet, in the real world, entities make profits all the time. In fact, they make wild, unimaginable, world-changing, history-altering profits. This is a tacit admission that our markets aren't even remotely efficient, and that includes predictions markets. Efficient, rational markets are the exception, not the rule.
In a perfectly efficient market all entries can make the same profit on a given investment.
I have to say I was this huge fan of the idea and I didn’t anticipate it would happen like this.
jonbecker•1h ago
dataset: 72.1m trades and $18.26b volume on kalshi (2021-2025)
core findings:
longshot bias: well documented longshot bias is present on kalshi. low probability contracts are systematically overpriced. contracts trading at 5 cents only win 4.18% of the time.
wealth transfer: liquidity takers lose money (-1.12% excess return) while liquidity makers earn it (+1.12%).
optimism tax: the losses are driven by a preference for "yes" outcomes. buying "yes" at 1 cent has a -41% expected value. buying "no" at 1 cent has a +23% expected value.
category variation: finance markets are efficient (0.17% maker-taker gap) while high-engagement categories like media and world events are inefficient (>7% gap).
mechanism: makers do not win by out-forecasting takers. they win by passively selling "yes" contracts to optimistic bettors
KPGv2•57m ago
hbarka•27m ago
tasuki•56m ago
TZubiri•45m ago
snovv_crash•40m ago
hbarka•35m ago
This is interesting and makes a statement about positive or negative orientation in human psychology. Also, couldn’t the bets just be worded in the negative instead of the affirmative thus flipping the optimism bet?