Polymarket trading: early odds do not guarantee an edge

I wanted to know whether an early move in Polymarket odds leaves time to trade the same news elsewhere. Algovibes tested that question by matching prediction-market prices with futures data. The results were less promising than the opening example: odds sometimes moved before another market could open, but following them into futures did not produce a dependable strategy.

What Polymarket trading odds tell you

Polymarket lets people buy and sell contracts on future events. For the binary questions in this analysis, a Yes share pays $1.00 if the event happens and nothing if it does not. A price of 70 cents therefore reads as an implied probability of 70%. The payout explains why the price can be read this way; it does not make the outcome certain.

Prices change as participants commit money to their views. These markets trade throughout the day and through weekends, including periods when the futures markets in the comparison are closed. That makes it possible to see changing expectations even while the related asset is unavailable for trading.

I read those probabilities as estimates made by market participants, not measurements of the future. Their decisions can be informed or mistaken, and difficulty entering or exiting a position can influence them. A price tells you what participants will trade at, rather than settling whether their forecast is right.

On a Saturday in February, odds on a US strike on Iran rose from 35% at 1:10 a.m. to 79% ten minutes later, then to 98% another forty minutes after that. Crude oil futures were closed. They reopened 41 hours later with an 8% jump, according to the creator's analysis.

The odds were early relative to the next available oil price. But a trader could not buy oil at its previous closing price after seeing the change. That is the practical distinction I care about: identifying news before a market reopens does not establish that its opening price will leave anything to capture.

How the comparison avoids early entries

The study compares 20 Federal Reserve meetings from May 2024 to September 2026, election night in 2024, and 154 war and peace markets with futures prices. The Fed markets accounted for $3.5 billion in bets. The geopolitical questions covered strikes on Iran, ceasefires, peace deals, Venezuela and Russia-Ukraine events.

The futures data covered crude oil, gold, the Nasdaq-100, the 10-year Treasury note, the euro and the yen. Futures contracts reflect expectations about an underlying market, so they can respond to the same news as a prediction contract without quoting an explicit probability.

I put more weight on the timestamps than on whether two price lines look similar. Each odds snapshot was matched with the futures price at the same minute. This avoids look-ahead bias: a historical test must not use information before a trader could have known it.

The odds data used 10-minute snapshots, with 1-minute observations on decision days and election night. The futures series used 1-minute data. To check which market moved first, the creator compared 10-minute changes at offsets of up to 30 minutes on either side. This lead-lag test asks whether one market's move consistently precedes the other's.

The trading tests imposed a further delay. Entry occurred 1 minute after the odds snapshot, using one contract, with commission plus one tick of slippage per side. A tick is the market's minimum price increment. Slippage accounts for the difference between an expected execution price and the price obtained.

That delay matters to my reading of the results. Two markets can move together on a chart without leaving a usable entry in either one. The test needs to measure what happens after the odds become observable, at a price a trader could obtain, with execution costs included.

The video does not give commission amounts or enough execution detail to reproduce every fill, so the applicable fees and fill assumptions still need checking.

The luck test moved entry times randomly within ±7 days across 300 runs. It compared the selected signal with nearby, arbitrary entries. Outperforming those entries supports the historical result, but does not establish that the rule will work in a different market environment.

The Fed forecasts were accurate, but bonds kept up

The creator found that the favorite one day before each Fed decision was correct at all 20 meetings. That included the September 2026 rate increase, which had reached an 87.5% probability the day before the decision. This was an accuracy result measured at a particular observation time, rather than at the final available price.

The January 2026 meeting attracted $659 million in bets. The probability of no change was 99.5% the day before, and the Fed left rates unchanged. Participants strongly agreed on the outcome, but agreement alone says nothing about whether Treasury futures offered a profitable entry.

I find September 2024 more informative about the limits of the accuracy score. A half-point cut was the favorite the day before the announcement. The market changed its mind that morning, and five minutes before the announcement assigned a 56% probability to a quarter-point cut. The Fed delivered the larger cut.

Someone acting just before the announcement would have faced a different forecast from the one counted in the day-before record. That is why the observation time belongs beside any accuracy statistic: an earlier correct estimate cannot substitute for the odds available when a trade is entered.

For the timing comparison, the creator examined 86,400 ten-minute windows across the 30 days before each meeting. The strongest correlation between odds changes and Treasury futures occurred in the same window. Even there, the relationship was small, at 0.06.

The creator's explanation was that both markets reacted to economic releases together. On July 3, 2025, for example, Polymarket odds and 10-year Treasury futures dropped in the same ten minutes at 8:30 a.m. after a jobs report. The test found no useful tendency for the odds to predict the next bond move.

I would not treat that shared reaction as evidence that the odds supplied new information to bond traders. The relevant trading test entered after the probability changed and produced these results after costs:

The longer hold raised the share of winning trades, but every version lost money. Win rate leaves out the size of gains and losses, as well as execution costs. A better percentage of winners therefore did not rescue these entries.

Election futures moved before the odds

The presidential outcome attracted $1.5 billion in bets on election night. Trump's probability stood at 61% at 6:00 p.m. and approached 100% by the next morning. Matching those odds with Nasdaq, euro and Treasury futures minute by minute allowed the creator to compare how quickly each market responded.

The creator interpreted a Trump victory as favorable to a stronger dollar, higher yields and higher stocks. Those relationships guided the reading of the futures response; they were not guarantees about how the assets would behave after the election.

I would keep the contract's question separate from that interpretation. The election contract asked who would win. A futures price reflected what participants thought the result meant for that asset, alongside other influences. Knowing the winner would not, by itself, specify the size or timing of the Nasdaq's move.

At 10:00 p.m., Trump's probability was 83%, while Nasdaq futures were already up 1.1%. Between then and midnight, the Nasdaq added only another 0.1, according to the analysis. Much of the cited price move had happened while the prediction market still expressed substantial uncertainty.

Across the night, futures tended to move 10 to 30 minutes before the prediction odds. The creator cautioned that a single night was not proof of a general rule. It challenges a claim that prediction markets always lead, but does not establish that futures always move first.

For me, the useful lesson from this example is about waiting for confidence. An asset can move substantially before an outcome becomes nearly certain. A later, more reassuring probability may describe the result more accurately while arriving after most of the associated price adjustment.

War odds did not reliably predict the next oil move

The creator focused on geopolitical markets because that is where stories about informed insiders are most common. Across the war and peace sample, roughly 200 probability jumps met the test: at least 10 points within 10 minutes while oil futures were trading. The study compared crude oil's behavior before, during and after those jumps.

The analysis found no reliable oil pattern before the jump. Oil moved in the implied direction during the same ten-minute window, then continued in that direction about half the time afterward. A visible response to news was therefore different from a reliable signal for the next move.

I also need to know which question the contract asks before interpreting a rising Yes price. In this analysis, higher odds of a strike and higher odds of a peace agreement implied different directions for oil. The price change alone cannot tell a reader which direction the strategy would take.

On June 23, 2025, Iran fired missiles at a US base in Qatar. Oil began falling at noon and was down 9% by 4:00 p.m. Polymarket ceasefire odds remained somewhere between 8% and 30% through the afternoon. Just after 6:00 p.m., Trump announced a ceasefire, and the odds reached 81%.

The creator interpreted the earlier oil decline as traders pricing in peace before the announcement. That is an interpretation of the sequence, rather than a complete account of what those traders believed. The price move cannot establish every reason behind their decisions.

I would compare the later odds jump with the preceding oil move before calling it a fresh signal. Confirmation of an event may arrive after the related asset has repriced. The useful timestamp is when the probability changed relative to the asset's response, not simply when the event was announced.

An event contract also has a narrower job than an oil forecast. It concerns a defined outcome, while oil can respond to expectations about disruption and prior market positioning. Even a correct forecast leaves open how much of that outcome the current oil price already includes.

A profitable backtest depended on a few trades

One oil rule did make money in the historical test. It selected probability jumps of at least 20 points, entered futures in the implied direction 1 minute later, and held for 30 minutes. Only 1% of randomized entry-time tests did as well, according to the creator.

I take that comparison more seriously than an attractive chart alone. It tests a stated entry rule, includes costs and checks nearby random entries. Still, a total profit does not tell me whether many trades contributed or whether a few exceptional outcomes account for most of it.

A single trade on April 17, 2026 generated $6,885. That morning, the probability of a US-Iran meeting rose from 35% to 70%, and oil fell $7 in half an hour. The table shows how much the result depended on that trade and on the selected holding period:

The creator concluded that the apparent strategy depended on an unusually favorable morning. My narrower reading is that profits were concentrated and sensitive to the exit rule. Those findings make the result less convincing as evidence of a repeatable method, even though the original test was profitable.

Removing winners is not a neutral replacement for the original test. A genuine strategy can earn much of its money from uncommon events, so deleting its best outcomes will naturally hurt it. What needs explaining is whether those events follow a repeatable mechanism or happen to suit a rule chosen from historical data.

The longer holding periods raise a separate issue: extending the position erased the profit. That does not automatically disprove the shorter exit, but it makes the precise exit time important to evaluating the result. A claim about following odds in general would be broader than the evidence here supports.

I would also keep the luck test separate from protection against overfitting. A rule is overfit when it suits historical data better than new opportunities. Beating randomized entries in the original sample does not resolve whether the chosen threshold, exit time or selected events account for its success.

Weekend odds described a gap traders could not capture

Weekends were the clearest case of prediction odds moving first in the study. The futures schedule used here closed on Friday afternoon and resumed on Sunday evening. Polymarket kept trading, so its prices could change with news while oil futures could not respond through trading.

Across 86 weekends with active war and peace markets, the creator selected the 18 with the largest probability changes. Oil opened in the implied direction on 16 occasions. That result applies to the selected group, not to every weekend or every change in odds.

I see a use for those probabilities in explaining why oil reopens away from its previous close. The trading problem is that the reopening price already includes the gap. A gap is the difference between the earlier closing price and the next opening price; entering afterward does not provide access to the old price.

The continuation test addressed the entry a trader could actually make. It entered at the Sunday open in the direction implied by weekend odds and held until Monday. According to the creator, that approach performed no better than random. The relationship with the opening gap did not extend to a dependable move after entry.

In the February strike example, oil opened at 72.86 on Sunday evening and stood at 71.24 on Monday afternoon. Buying at the open would have lost money over that interval, despite the earlier odds change correctly pointing toward the opening gap.

I would not read that loss as evidence that the event forecast was wrong. The forecast and the later trade answer different questions. An event can happen and the asset can reprice before the buyer enters, leaving that buyer exposed to what happens next rather than to the move already completed.

Test the entry with fixed rules and fresh data

For any proposed prediction-market strategy, I would first establish when the odds became observable, when the related asset could be traded and which entry price the test uses. A signal during a closure needs a reopening test. Using the earlier closing price would credit the strategy with an entry unavailable after the news.

Then examine individual trade results, rather than relying on total profit. The distribution shows whether ordinary trades contribute or a few extreme outcomes carry the test. Checking nearby exit choices also reveals how much the result depends on one precise holding period.

The risks are not confined to statistical interpretation. Futures generally involve leverage: exposure can exceed the money committed, which can magnify losses. Prediction contracts can lose their purchase value if the chosen outcome fails. Ambiguous wording or settlement disputes can also complicate how a real-world event translates into a payout.

Before interpreting a probability, I would check the exact question and resolution terms. A contract about an event by a deadline forecasts that defined outcome. It does not directly forecast an asset's return over a holding period chosen by the trader.

A stronger evaluation uses fresh data that played no part in selecting the rule. During that test, keep the probability threshold, entry delay, trading costs and exit fixed.