The "top-1% winners are patient limit-order liquidity providers, not insiders" finding is interesting, and I'd love to see it extended cross-venue.
I work on tooling that normalizes orderbooks across Polymarket, Kalshi, Limitless, and Smarkets. From that angle, a lot of what looks locally like skilled Polymarket market-making turns out to be cross-venue arbitrage that happens to land on Polymarket. The same underlying question routinely trades 3-8% apart across venues for hours at meaningful depth, and a fast multi-venue stack rests limits on the lagging book at the exact moments the leading book moves. Locally that's indistinguishable from disciplined liquidity provision; cross-venue it's closer to FX triangular arb on the consensus price.
If your timestamps are fine-grained enough, a clean follow-up: for the top 1% of Polymarket profit-takers, what fraction of fills land within N seconds of a same-question move on Kalshi or Limitless? If it's materially above baseline, some of "skill" resolves into "cross-venue infrastructure" — which is also a more durable edge than within-venue alpha, so it could partly explain the weak monthly persistence you observe (the cross-venue gap closes when too many players run the same stack).
This might also be consistent with your insider-trading conclusion rather than against it: an insider on a real-world event has every reason to hit the lowest-friction venue with aggressive market orders (Polymarket: permissionless wallets, no KYC, no withdrawal limits). That's a fundamentally different profile from the patient limit-posting strategy your top bucket runs, so the two populations cleanly separate in the data even if both are present.
We study trading gains and losses on Polymarket, the largest prediction market. Using 588 million trades ($67 billion in volume), we show that the gains are highly concentrated: the top 1% of users capture 76.5% of profits. Successful traders provide liquidity using limit orders that resolve favorably relative to realized outcomes while unsuccessful traders take liquidity using market orders. Monthly performance is weakly persistent, however, this may represent sample selection rather than skill. A detailed analysis of the trading behavior of the most successful accounts suggests that "insider'' trading is unlikely to explain the performance of the largest winners.
insider trading on events probably wouldn't show any trends, right? These are point in time events (they call them markets), but they are finite and short lived. An insider would be a one and done thing, so it would be pretty hard to spot them or trend any sort of month over month insider scheming imo.
Also...
> We study trading gains and losses on Polymarket, the largest prediction market
This is not a natural thing to say and I fucking hate that it's impossible to know anymore if I'm wasting time replying to an AI/bot or not
I agree - you're not going to be an insider on a significant proportion of trades and it would be stupid to use the same account for more than a couple.
Insiders are going to be earning large amounts in single trades, either by betting a lot when it's odds-on or a small amount when it's out the odds (for a large return).
I think it's just bad tense, which I think makes it not AI amusingly.
What's the baseline here - in a world where every person is betting randomly X times a month, what would the distribution look like? There'd still be a small percentage that wins most of it, right?
Nice paper, and thanks for releasing the dataset.
The "top-1% winners are patient limit-order liquidity providers, not insiders" finding is interesting, and I'd love to see it extended cross-venue.
I work on tooling that normalizes orderbooks across Polymarket, Kalshi, Limitless, and Smarkets. From that angle, a lot of what looks locally like skilled Polymarket market-making turns out to be cross-venue arbitrage that happens to land on Polymarket. The same underlying question routinely trades 3-8% apart across venues for hours at meaningful depth, and a fast multi-venue stack rests limits on the lagging book at the exact moments the leading book moves. Locally that's indistinguishable from disciplined liquidity provision; cross-venue it's closer to FX triangular arb on the consensus price.
If your timestamps are fine-grained enough, a clean follow-up: for the top 1% of Polymarket profit-takers, what fraction of fills land within N seconds of a same-question move on Kalshi or Limitless? If it's materially above baseline, some of "skill" resolves into "cross-venue infrastructure" — which is also a more durable edge than within-venue alpha, so it could partly explain the weak monthly persistence you observe (the cross-venue gap closes when too many players run the same stack).
This might also be consistent with your insider-trading conclusion rather than against it: an insider on a real-world event has every reason to hit the lowest-friction venue with aggressive market orders (Polymarket: permissionless wallets, no KYC, no withdrawal limits). That's a fundamentally different profile from the patient limit-posting strategy your top bucket runs, so the two populations cleanly separate in the data even if both are present.
If you’d like to be connected to Limitless devrel or bd you can DM me on X - jeremyjem. We also have a builders chat group.
this comment was clearly written by AI. please don't do that.
There's probably also some hedging going on across accounts that look like directional bets.
Wait- why isn't there any conflict of interest statement provided in this paper?
> the top 1% of users capture 76.5% of profits
This seems to be similar to OnlyFans, and the economy at large...
We study trading gains and losses on Polymarket, the largest prediction market. Using 588 million trades ($67 billion in volume), we show that the gains are highly concentrated: the top 1% of users capture 76.5% of profits. Successful traders provide liquidity using limit orders that resolve favorably relative to realized outcomes while unsuccessful traders take liquidity using market orders. Monthly performance is weakly persistent, however, this may represent sample selection rather than skill. A detailed analysis of the trading behavior of the most successful accounts suggests that "insider'' trading is unlikely to explain the performance of the largest winners.
Full dataset available at https://huggingface.co/datasets/vgregoire/polymarket-users
insider trading on events probably wouldn't show any trends, right? These are point in time events (they call them markets), but they are finite and short lived. An insider would be a one and done thing, so it would be pretty hard to spot them or trend any sort of month over month insider scheming imo.
Also...
> We study trading gains and losses on Polymarket, the largest prediction market
This is not a natural thing to say and I fucking hate that it's impossible to know anymore if I'm wasting time replying to an AI/bot or not
I agree - you're not going to be an insider on a significant proportion of trades and it would be stupid to use the same account for more than a couple.
Insiders are going to be earning large amounts in single trades, either by betting a lot when it's odds-on or a small amount when it's out the odds (for a large return).
I think it's just bad tense, which I think makes it not AI amusingly.
Just curious but how are bets arbritated on these website?
Meaning who decides if an outcome was yes or no? Answers to things like "Who will win the next Best Picture Oscar?" are fairly obvious and binary.
Can we make bets whose answers are not binary yes/no?
What about "Will celebraty X and Y break up?"? Does Polymarket go to X and Y to confirm if they broke up or something :D
https://docs.polymarket.com/concepts/resolution
What's the baseline here - in a world where every person is betting randomly X times a month, what would the distribution look like? There'd still be a small percentage that wins most of it, right?