The analysis is interesting, but I think it ignores a few factors:

1. The article mentions the bid/ask spread for contracts, but I believe that Kalshi also has its own fee structure. Small edges (an expected loss of 0.57¢ on a 1¢ contract implies an expected gain of 0.43¢ on a 99¢ contract, or a 5.75ppt edge) can be easily eaten by even small fees, and liquidity provision is all about small edges.

2. The article ignores the time value of money, and contracts take time to resolve. If a contract won't resolve for six months and the risk-free rate is 5%, then buying a "sure thing" over 97.5¢ is a loss net of otherwise earnable interest.

3. Long shots offer greater implied leverage to bettors, making them more attractive. This is still (sometimes) an exploitable mispricing, but it's closer to the well-understood "bet against beta" factor.

(Edit to add) Also, I think their explanation of the non-returns on finance is lacking:

> Why is Finance efficient? The likely explanation is participant selection; financial questions attract traders who think in probabilities and expected values rather than fans betting on their favorite team or partisans betting on a preferred candidate. The questions themselves are dry ("Will the S&P close above 6000?"), which filters out emotional bettors.

Financial contracts are the ones that are most perfectly hedges with existing markets. "Will the S&P close above X?" is a binary option, after all, so it's comparatively easy for a market-maker to almost perfectly offset their Kalshi positions with opposite positions in traditional markets.

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postflopclarity a day ago | parent [-]

on point 1, an important thing to know is that these markets have a non-linear fee structure where the rate is higher near 0.5 and lower near tail prices

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Majromax a day ago | parent [-]

True, but from the pdf it seems like the fee charged of market makers is 1.75¢ × P × (1-P) per contract. Near P=0 that's approximately 1.75% of the notional amount invested, but near P=1 that's approximately 1.75% of the potential gain.

As I read it, the implication is that a market maker in the high-P regime needs to still have an expected edge of 1.75% to profit net of fees, which means that the 'maker return' table in this article is net negative after fees for all categories save for entertainment, media, and world events.

	▲	hardluck a day ago \| parent [-]
		Fees are also waved if a market maker hits a certain monthly quota. With the recent adoption of “professional” market makers on the platform, I’m sure they can get around such fees. I will also add to the 2nd point that some of these platforms due give fixed interest to positions in unresolved markets.