About acceptodds
Abstract
acceptodds is a prediction market for papers under review. Every paper has a market on its decision (e.g. Accept or Reject), and its price is what the people trading it think the odds are. Users buy shares in the outcome they believe in. Shares can be bought and sold at any time and when a market is settled users who are holding the winning outcome are paid out 1 $rep for each of their shares. Prices are set by an automated logarithmic market maker so there is always enough liquidity in the market. Trading is in reputation, which cannot be bought: everyone starts with 1,000 $rep. It is a game made for fun, and has no connection to ICLR, OpenReview, OpenAI or any other organization and the code is available at: github.com/benedict-armstrong/acceptodds. The outcome of this experiment is yet to be determined by everyone here
Why
Peer review decides which papers a conference accepts, and it is noisy: two equally qualified referees can reach opposite verdicts on the same paper [1]. A market asks a different question — not what two or three referees will say, but what everyone who has read the paper expects them to — and puts a number on the answer that anyone can check against the decision.
A trader who is right before the decision gains reputation, and one who is wrong loses it, so over many papers the leaderboard shows whose judgement of research holds up. Anyone with an institutional email address can take part, and every paper under review has a market, opened the first time someone asks for one.
What you trade
Each paper has one market, which asks its venue’s question:
- ICLR 2027: Will this paper get accepted to ICLR 2027? Outcomes Accept and Reject.
- OpenAI Math: Will this result be independently verified by the end of 2027? Outcomes Verified and Not verified.
Each market’s contract, on its page, says exactly how it resolves, edge cases included.
You buy shares in an outcome. When the market settles, every share of the outcome that happened pays 1 $rep; every other share pays nothing.
So an outcome’s price is the market’s probability for it: a share at 30% costs about 0.30 $rep and pays 1 $rep if it wins. The two prices always add up to 100%, and the figure shown for a paper (“accept”, “verified”) is the price of its first outcome.
Reputation
Trading is in reputation, $rep, not money. Everyone starts with 1,000 $rep once they have confirmed an institutional email address. There is no way to buy more: the only way to gain is to be right before everyone else is.
Buying
You say how much to stake; the trade box shows how many shares that buys, as what it pays if the outcome wins. You always trade with the market maker (§6), so there is never anyone to wait for.
Buying moves the price (2). Each share you buy makes the next one dearer, so a large stake pays a higher average price than the one shown before you bought — the box shows the price before and after your trade.
The cost you are shown is a limit. If someone else trades first and the price moves against you, your order is refused rather than filled at a worse price. If it moves in your favour, you pay less.
Selling
You can sell shares you hold, in part or in full, at any time until trading closes. You cannot sell shares you do not hold: there is no shorting. To bet against acceptance, buy Reject.
Selling moves the price down as you sell, so selling a holding pays less than its shares times the current price. That is why your positions show a “current value” — what selling everything now would actually pay — and not shares × price. Right after a buy it is a little below what you paid: buying and immediately selling back loses a little, never gains.
The market maker
Prices are set by an automated market maker, Hanson’s logarithmic market scoring rule (LMSR) [2, 3]. It always quotes a price for any outcome, and the price depends only on how many shares of each outcome have been bought so far. Write for the shares of outcome bought so far, out of outcomes. The market maker keeps the cost function
and the price of outcome is how fast that cost grows with its shares,
which is always between 0 and 1, and sums to 1 over the outcomes. Buying shares of costs the difference in (1) before and after; selling is the same with negative, and pays back that difference. Costs are rounded to a millionth of a $rep, always in the house’s favour.
The depth — how far a given stake moves the price — is sized when the market is created, from the number of traders expected and the starting balance, so no single trader can pin a price on their own. It is then fixed for the life of the market. The house funds each market maker with
the most it can lose however the market resolves [2], so every winning share is always paid.
Resolution
Trading closes at the date shown on the market. When the decision is published, the market is settled on the outcome that happened, with a link to the evidence where there is one: each of its shares pays 1 $rep into your cash, and every other outcome’s shares are worth nothing.
Net worth and the leaderboard
Your net worth is your cash plus what selling every holding right now would pay (§5). It is never shares × price, which would let a trader show a profit just by pushing up the price of what they hold.
The leaderboard ranks everyone on that net worth, or on profit from settled markets alone.
References
- [1]L. Wasserman. A world without referees. Essay, Carnegie Mellon University, 2012.
- [2]R. Hanson. Combinatorial information market design. Information Systems Frontiers, 5(1):107–119, 2003.
- [3]R. Hanson. Logarithmic market scoring rules for modular combinatorial information aggregation. Journal of Prediction Markets, 1(1):3–15, 2007.