Decentralized prediction markets led by Polymarket and Kalshi have accumulated over $9 billion in monthly trading volume by 2025, allowing users to bet on the outcomes of political, economic, and sporting events. As AI technology drives the emergence of various arbitrage strategies—from discovering cross-platform mispricings to large-scale information manipulation—thousands of traders are participating. However, these strategies relying on market inefficiencies and information asymmetry are not without risks. This article will analyze the principles, processes, and potential dangers of each strategy.
Basic Logic: What Does Polymarket’s “Shared Order Book” Represent?
Before diving into arbitrage strategies, it’s essential to understand Polymarket’s core mechanism: the Shared Order Book.
Unlike traditional exchanges, Polymarket’s YES and NO orders are mirror images. When someone places a buy order for 10 shares at $0.2 for YES, the system automatically places a corresponding sell order for 10 shares at $0.8 for NO.
This design can be described with the invariant formula “YES + NO = 1,” ensuring that the two options for a binary event can be combined and exchanged for a single $1 asset at expiration.
(Understanding Polymarket: What Is a Mirror Order Book? Why Must YES + NO Equal 1?)
Hedging Arbitrage: Hedging Risks to Lock in Profits
The most straightforward arbitrage opportunity in prediction markets lies in their “insurance” feature, which is equally important for traditional stock investors and crypto traders.
ICO Event Arbitrage
Operation Principles and Case Study
This strategy is common before a new token’s Token Generation Event (TGE), used to lock in profits. Investors observe the valuation of a token in pre-market trading platforms like Whales Market or Hyperliquid, as well as on Polymarket, to make initial estimates and comparisons.
For example, with Lighter (LIT), if the token is trading in pre-market at a fully diluted valuation (FDV) of $3–4 billion in December 2025, but the latest funding round values it at only $1.5 billion, and the high trading volume may be due to airdrop-induced wash trading, investors might consider the pre-market price overheated.
In this case, investors holding airdrops or long positions can buy NO on Polymarket regarding “Is LIT’s FDV over $4 billion?” Once the market opens and the price corrects, the predicted market’s profit can offset the paper losses in the spot holdings.
Potential Risks
The risk here lies in whether the platform’s terminology refers to circulating market cap or FDV, and whether settlement occurs at market open or days later (e.g., the example shows “after one day”).
Event-Driven Hedging
Operation Principles and Case Study
The core idea of event-driven hedging is “buying inverse insurance against external events that impact asset value,” which is useful during corporate earnings seasons.
Suppose an investor holds $10,000 worth of NVIDIA stock and is optimistic about AI but worries that recent market overheating might lead to a price correction if earnings fall short.
To hedge this uncertainty, the investor can find events on the prediction market such as “Will NVIDIA’s revenue this quarter beat expectations?” or “Will NVIDIA’s stock close higher or lower today?” They can buy NO on “revenue exceeding expectations.”
Potential Risks
While this strategy can hedge some risks, investors must also consider unanticipated risks—namely, correlation failure. For example, if revenue hits the forecast (predicting market loses), but the stock price still drops due to market overheating or high standards, resulting in a paper loss.
Financial-Style Arbitrage: Using Math to Improve Win Rate
For players with larger capital and lower risk appetite, prediction markets offer higher-probability profit opportunities.
High-Probability Betting Strategy
Operation Principles and Case Study
This approach focuses on stability: traders select events with over 95% probability, where the outcome is almost certain, and invest to capture small gains before final settlement. They continuously identify near-settling markets that are unlikely to reverse and buy YES options.
For example, consider the challenge “Can Alex Honnold successfully climb Taipei 101 free solo?” If the event is nearing its end, and live footage shows him close to the top with full stamina, the YES price might be around 0.97 and unlikely to reverse. Traders can buy in.
Although the profit per trade is only about 3%, the short time to settlement and repeated operations across multiple events can yield a substantial annualized return.
(Globally betting on Alex Honnold climbing Taipei 101! Prediction markets favor reaching the top within 90 minutes)
Potential Risks
This strategy is essentially “pure gambling.” Even with a 99% win rate, rare accidents—such as Honnold choosing to give up at the last moment due to fatigue—can lead to significant losses.
Multiple-Choice Arbitrage
Operation Principles and Case Study
This strategy exploits temporary gaps caused by differing liquidity or market inefficiencies in multiple-choice markets. When the sum of YES prices for all mutually exclusive options should be ≥ 1 but is less than 1, a riskless arbitrage opportunity arises.
For example, in “Who will win the US presidential election?” or “What will ETH’s price range be at the end of the month,” if all options are mutually exclusive and cover the entire range, and the total cost of buying all YES options is below 1, arbitrage exists.
The trader can buy all YES options proportionally. Regardless of the final winner, the settlement will total 1, which exceeds the initial investment.
Potential Risks
Such inefficiencies are rare and often quickly exploited by high-frequency bots. Transaction fees and slippage can also erode profits.
Information Edge Arbitrage: Tracking Smart Money and Correlated Reactions
In the transparent Web3 environment, following “whales” or informed traders with informational advantages has become a mainstream strategy.
Smart Money Copying
Operation Principles and Case Study
Due to blockchain’s transparency, the entry points and positions of whales or smart money are visible. Traders can monitor wallets with high historical success rates and use automation tools to copy or follow their trades.
(Introduction to Polymarket Ecosystem: How the Top 10 Prediction Market Tools Assist Traders)
Potential Risks
Risks include delays in copying trades, leading to buying at too high a price or selling too low, resulting in negative expected value over time. Additionally, large traders may manipulate liquidity to “front-run” or “whale wash,” impacting market fairness.
Event Linkage Strategies
Operation Principles and Case Study
This approach aims to exploit pricing inconsistencies between highly correlated events caused by different reaction speeds or non-obvious linkages. Traders observe two markets with logical or causal connections, and when the main market moves before the related market, arbitrage opportunities arise.
For example, “Who will be elected US president in 2028?” and “Which party will win the election” are related. If a major scandal hits a Republican candidate, the probability of a Democratic win increases, affecting both markets. Buying “Democrat will win” before the market fully reacts can generate profit.
Potential Risks
Risks include the breakdown of event correlations, differing settlement rules, or black swan events (e.g., candidate withdrawal or replacement), which can cause the linkage to fail and strategies to lose effectiveness.
Market Manipulation Strategies
Operation Principles and Case Study
This is the most well-known but also market-manipulative tactic—creating false “insider information” to lure traders into traps.
For example, manipulators buy large amounts of inverse options on a short-term event like “Will the US attack Iran today?” to drive up the YES price and attract media or bot attention, then use a clean wallet to buy large amounts of NO. If the event doesn’t happen, the manipulator profits from the NO position while incurring minimal cost on YES.
Potential Risks
Manipulation risks include black swan events, such as a US-Iran conflict, which could wipe out the NO position. Excessive or repeated manipulation may also attract legal or regulatory scrutiny.
Summary of Strategy Risks and Recommendations
In summary, the core competitive advantage of prediction markets lies in “information asymmetry” and “logical inference.” However, the fundamental risk always stems from how the platform interprets settlement rules. Before participating, thoroughly review market details and understand that the market is betting on the platform’s definition of events, not reality itself.
(Does the US consider “invasion” of Venezuela? Polymarket’s “No” ruling sparks outrage)
This article, “Overview of Prediction Market Arbitrage Strategies: Low-Risk Money Printing Machine or High-Risk Gambling?” was first published by Chain News ABMedia.
