The prediction market is likely to be one of the themes of the upcoming market. There are several participation angles.
One is betting that the Binance ecosystem will produce a leader in the prediction market. Polymarket is doing so well, how can the BSC chain be absent? Just as the Binance ecosystem produced the leading aster in the pep market, it is only natural for a Chinese prediction market to emerge. So focus on potential targets.
Another participation angle is researching the leading ploymarket. Ploymarket has raised billions and has expectations for issuing tokens, so how can this wool be sheared? At the same time, ploymarket has become an arbitrage market. This article mainly discusses the arbitrage logic of ploymarket.
If you have done a lot of interactions during the arbitrage process and have expectations for issuing coins, why not?
Friends who are interested can contact me to study together, and are there any programmer friends with scripts or who can create a script?
The following is the main text; I saw it from a plagiarizing blogger. If the original author sees it, they can delete it.
How to arbitrage in Polymarket?
The first type of arbitrage is called cross-platform arbitrage. When there are deviations in the probabilities of the same event between Polymarket, Kalshi, and CME, it is a signal that market information has not fully circulated. For example, in the FOMC decision, Polymarket's 25bps probability is 94%, Kalshi is 93%, and CME FedWatch is 95%. Arbitrageurs will sell Yes (+94U) on Polymarket and buy Yes (-93U) on Kalshi, waiting for the market to converge to earn that 1% risk-free profit. This sounds small, but with millions of dollars in position, it becomes a stable cash flow made of flesh and blood. The risk is in delays and transaction fees, and the key is reaction speed— arbitrage always belongs to the first person who discovers the error.
The second type of arbitrage is the 'holy grail' within Polymarket: the total arbitrage of multi-option markets. When the total price of all options in a multi-choice event sums to < 1.00, you can buy one of each option, and regardless of the outcome after settlement, you will get back 1 dollar. For example, in the Federal Reserve decision market with four options (cutting rates by 50bps, cutting rates by 25bps, maintaining, raising rates by 25bps), if the prices add up to 0.995, you buy the whole set to lock in a 0.5% profit. It sounds small, but it is zero risk. Such opportunities usually exist for only a few seconds and are captured by programmed scripts (bots). Once automated systems take over, arbitrage shifts from cognition to computation, from reaction to execution. True arbitrageurs do not watch the market; they watch the API.
The third type of arbitrage is called tail-end trading. When the result is determined and settlement is not yet reached, and the price still fluctuates in the range of 0.97 to 0.999, you can buy in and wait for settlement, exchanging time for certainty. For example, if the election results have been announced and the market has not yet closed, you buy Yes at 0.997, and a few hours later, when the event settles, you reliably capture a 0.3% price difference. This is a form of 'delayed wealth management' and is also the easiest arbitrage method for retail investors to participate in. The risk lies in extremely small black swan events, such as a reversal of results or manipulation, but if positions are diversified and near-term settlement markets are chosen, this risk is almost controllable.
The last type is the highest-level play in Polymarket: market-making arbitrage. You simultaneously place buy and sell orders to earn the price difference and incentives provided by the platform. Polymarket's liquidity rewards follow a quadratic mechanism— the closer the quote is to the market midpoint, the higher the reward. Experts maintain a tight spread in markets with low volatility and high trading volume, achieving an annualized return of 50% to 150%. The essence of market-making arbitrage is not to judge direction but to provide order. It makes the market smoother, makes prices more real, and makes predictions more credible.
