How to Trade Prediction Markets During Elections

Elections are the single largest driver of prediction market volume and liquidity. The 2024 US presidential election alone generated over $3 billion in trading volume on Polymarket, dwarfing every other event category combined. Elections attract this attention because they combine several features that make for ideal prediction markets: high public interest, abundant public information, clearly defined outcomes, specific resolution dates, and genuine uncertainty that persists until the final result.

The volume and liquidity during election season create unique opportunities for traders. Spreads tighten to $0.01 or less in major markets, making it cheap to enter and exit positions. The sheer number of participants means diverse viewpoints are represented in the price, creating one of the most efficient prediction mechanisms available. But efficiency does not mean accuracy — election markets can and do misprice outcomes, especially in the early stages of a race, in down-ballot contests, and during periods of rapid information change.

For prediction market traders, elections represent the Super Bowl of the calendar. The stakes are high, the data is abundant, and the competition is fierce. Succeeding requires not just good political judgment but also disciplined trading strategies, careful position sizing, and the ability to distinguish between genuine information signals and the noise that floods the information ecosystem during campaign season. The traders who profit most from elections are those who prepare months in advance and have a clear framework for every stage of the race.

The pre-election period — months before primary voting begins — offers some of the widest mispricings in prediction markets. During this phase, markets are pricing in early polls, pundit analysis, and general vibes rather than hard data. Because the election is far off, many traders are not yet paying attention, and liquidity is lower. This combination of low attention and thin data creates opportunities for traders who do their homework early.

One effective pre-election strategy is to identify candidates or outcomes that the market is underpricing based on structural factors. Look for candidates with strong fundraising, institutional support, or demographic advantages that are not yet reflected in early polls. Markets tend to overweight recent headlines and underweight structural fundamentals in the pre-election phase. A candidate who raised $50 million in Q3 but is polling at 8% may be significantly underpriced if the money is about to translate into advertising and organization.

Another approach is to trade the correlation between primary and general election markets. If you believe a candidate will win the primary, the general election market for that candidate is often mispriced because it compounds the uncertainty of two events. If the primary is priced at $0.60 and the general at $0.30, and you think the primary probability is actually 80%, the general election market may offer better risk-adjusted value than the primary market itself. These correlation trades are a staple of sophisticated election traders.

Primary season is the most dynamic phase of election trading. Markets move rapidly as candidates debate, polls shift, endorsements land, and early states vote. The key to profitable primary trading is maintaining a framework that distinguishes signal from noise. Not every poll is equally informative — a high-quality poll of likely voters in the next primary state is far more valuable than a national poll of registered voters taken months before voting begins.

State-by-state primary markets offer some of the best opportunities because they are less liquid than national markets and more sensitive to local information. A trader who follows New Hampshire politics closely can have a genuine edge in the New Hampshire primary market against participants who are applying national-level analysis. The same applies to Super Tuesday states, delegate-rich states, and states with unusual primary rules. Local expertise translates directly into prediction market edge during primary season.

Momentum trading is particularly relevant during primaries. When a candidate outperforms expectations in an early state, markets for subsequent states often do not fully adjust. The Iowa bump, the New Hampshire bounce — these momentum effects are real but imprecise, creating opportunities to trade into the next state's market before the full adjustment occurs. Conversely, a candidate who underperforms in an early state may be overpriced in subsequent markets because the market has not fully processed the negative signal. Speed of analysis matters here: the window of mispricing after a primary result is measured in hours, not days.

The relationship between polls and prediction market prices is one of the most debated topics in political forecasting. Polls are surveys of voter intent at a specific moment. Market prices are real-time aggregations of trader beliefs, backed by real money. The two often diverge, and understanding why is critical for election trading. When polls and markets disagree, one of them is wrong — and figuring out which one gives you a tradeable edge.

Polls are most reliable when they are recent, use high-quality methodology (likely voter screens, large sample sizes, proven pollsters), and converge across multiple firms. When three A-rated pollsters show the same candidate ahead by 5 points, the signal is strong. Markets should reflect this. If markets are pricing in a tighter race than high-quality polls suggest, it may indicate that traders are factoring in something polls do not capture — or it may indicate that the market is wrong. Your job is to determine which case applies.

Historical data shows that prediction markets are generally more accurate than polls for final outcomes, but polls can be more accurate during specific windows — particularly when a new, high-quality poll is released and the market has not yet fully incorporated it. This creates a repeatable edge: monitor poll releases in real time, assess their quality, and trade into the market before the price fully adjusts. Use polling aggregators and tracker sites to identify when new data drops. The traders who consistently beat election markets are the ones who process polling data fastest and most accurately.

Election night is the most intense and volatile period in prediction market trading. Prices swing by tens of percentage points as votes are counted, exit polls are released, and results trickle in state by state. The traders who profit on election night are not the ones who predicted the final outcome months ago — they are the ones who understand the counting process, know which counties report early versus late, and can interpret partial results faster than the market.

The key to election night trading is understanding the order in which votes are counted. In many US states, mail-in votes (which lean toward one party) and in-person votes (which lean toward the other) are counted in different sequences. This creates predictable patterns: early results from a state may look dramatically different from the final count. A trader who knows that a particular state counts mail-in ballots first can stay calm when the early results appear to favor one candidate, knowing that the in-person votes that follow will shift the margin. The market, which is driven by many participants who do not understand these mechanics, often overreacts to early results.

Position sizing on election night should be conservative relative to your normal approach. Volatility is extreme, liquidity can be unpredictable, and even well-informed trades carry higher-than-normal risk. Many experienced traders reduce their position sizes by half on election night and focus on a small number of states or races where they have the deepest understanding of the counting process. The goal is to exploit a few high-conviction mispricings rather than to trade everything that moves.

The period between election day and official resolution can last days or even weeks in close races. Prediction markets remain open during this period, and prices converge toward the final result as counting continues. This convergence creates opportunities for traders who can accurately assess the remaining vote to be counted. If a candidate leads by 10,000 votes with 100,000 mail-in ballots remaining, and those ballots are expected to break 60-40 for the trailing candidate, the math determines the final outcome. Traders who can do this calculation quickly profit from the slow adjustment of market prices.

Resolution disputes add another layer of complexity. In contested elections, legal challenges can delay resolution and create uncertainty even when the vote count appears decisive. Prediction markets are particularly sensitive to resolution ambiguity because the final payout depends on the oracle's interpretation of the resolution criteria. Read the resolution criteria carefully before trading — some markets resolve based on the certified result, others based on the projected winner, and others based on media calls. These distinctions matter when the result is contested.

After an election resolves, review your trades carefully. What did you get right? Where did you miss? Were your probability estimates well-calibrated? Election seasons are the largest sample of correlated political markets you will encounter, making them ideal for calibration analysis. Use 0xInsider's analytics to compare your performance against the market and against top-ranked political traders. The lessons learned from one election cycle are directly applicable to the next — prediction market traders who perform post-election reviews consistently improve their results in subsequent cycles.

The 2024 US presidential election was the largest prediction market event in history and established several patterns that traders should internalize for future elections. First, markets can be wrong for extended periods. Prediction market prices diverged significantly from polling aggregates at several points during the campaign, and the resolution ultimately validated the market's view over the polls in some contests while validating the polls in others. Neither information source was universally superior.

Second, liquidity concentration matters. The presidential race attracted billions in volume with extremely tight spreads, while down-ballot races had orders of magnitude less liquidity and significantly wider spreads. The most profitable opportunities in 2024 were often found in lower-profile races where dedicated specialists could outperform the thin, less-informed market. Senate, gubernatorial, and proposition markets all presented recurring mispricings that were absent from the ultra-competitive presidential market.

Third, event-driven volatility on election night followed the counting-order patterns described above. Traders who understood state-specific counting mechanics — which states count early votes first, which count in-person first, which have same-day registration — had significant information advantages during the chaotic hours of vote counting. These patterns are structural, not coincidental, and will repeat in future elections.

Finally, the 2024 cycle demonstrated that prediction market prices have real influence on public discourse, media coverage, and even campaign strategy. This reflexivity means that prediction market traders must consider not just what will happen but how market prices themselves affect the narrative. A leading candidate whose prediction market price drops may face a wave of negative coverage that further damages their prospects — a self-reinforcing dynamic that creates both risk and opportunity for traders who anticipate it.