Prediction Market Arbitrage Strategies

Overview

The goal of this endeavor is to make money through automated trading on Prediction Markets.

Glossary

Platform - A website that offers betting on future predictions. This is a nascent field, and the top two platforms right now are Polymarket and Kalshi.
Market - A specific future event that is the subject of a bet. It could be the outcome of a sports event (Will Green Bay win Sunday’s Wild Card NFL game?) It could be a political event (Will Judge Sotomeyer retire from the Supreme Court in 2026?) It could be a crypto price prediction (Will Bitcoin be higher than 95,000 at the end of January 20th, 2026?)
Each market will have a name, a binary choice (Yes/No), (Up/Down), and an expiration date and time. People place a bet on that event happening in the future. Each market has explicit rules about how and when the criteria for the market will be judged to determine which side won. Some events will only be found on one Prediction platform. Other markets will be found on multiple platforms.
Strategy - A specific method of determining when and how to make a wager on a market.
Trade - The actual instantiation (execution) of a strategy. This includes the market, the position (yes/no), the amount of money put on the trade, and the expiration date and time.

There are many possible strategies to consider. For example, you can be the fastest person to obtain some information, and you trade before that information is reflected in the prediction market. Another strategy is to identify anomalies, glitches, and miscalculations in the markets. See Appendix A for an initial list of strategies.

Tenets

Here are some proposed tenets to help govern how we tackle this opportunity.

1. No Gambling - We are not gamblers. We are not simply looking for “a slight edge” when making a trade. We will only focus and execute on opportunities that offer extreme odds in our favor and/or extreme asymmetrical return.
2. Deep Over Broad - There are many strategies to consider, but we will focus on a single strategy rather than trying to spread our focus across multiple strategies. We will go deep on the selected strategy to become experts of this strategy rather than trying to master multiple strategies from the start.
3. Trade Volume over Trade Size - We prefer making many small to medium bets over taking a few huge bets. This reduces our risk and helps guard against unexpected outcomes.
4. Speed over Perfection - We know the predictions market is rapidly evolving and more traders will be flooding in. We have an early adopter advantage that we need to capitalize on. We will be scrappy in our development with quick iterations of build and test rather than a slower, more conservative approach. Time is of the essence.
5. Quick Trades Over Slow Trades - Money that is placed on a trade is money that is frozen until the trade is complete. We want short lived markets with fast turnover of the money so it can then be put to new trades. Placing $100 trades 30 times a week is better than a $2000 trade that expires in a month.

Our First Strategy

The first strategy we will master is class arbitrage across platforms. We will look for identical markets existing on both Kalshi and Polymarket, and execute trades when the combined cost for taking both sides of the trade ensures a zero-risk profit after fees.

Pros:

1. Smaller niche: Many people are focused on trading one platform. Fewer are focused on cross-platform trading since it requires more work and expertise.
2. Zero Risk: Since the trades will only be executed when the risk is zero, profit is guaranteed.
3. Lots of Opportunities: There are hundreds of markets to trade on. Once the software is working as intended for one market, you can immediately expand it to dozens of other markets.
4. No Domain Knowledge Needed: It does not require knowledge of a particular domain or expertise in being the fastest to obtain information.

Cons:

1. Edge erosion: As more bots/traders enter, windows shrink (seconds to minutes) and profitable spreads narrow.
2. Execution risk: One leg fills, the other slips or fails → turns risk-free arbitrage into directional bet.
3. Fees & costs: Kalshi taker fees (0.5–3.5%), Polymarket gas + dynamic taker fees (~2%), slippage — often eat 3–5% gross edges.
4. Liquidity risk: Thin markets mean you can't always fill at quoted prices.
5. Regulatory/platform risk: Polymarket US access limited (invite-only beta), potential bans/changes; Kalshi state restrictions.
6. Technical risk: API changes, downtime, bugs in bot logic.
7. Capital lockup: Even short trades tie up money until resolution.

Appendix A - List of Strategies

Pure Arbitrage Strategies (Risk-Free Mathematical Edges)

1. Cross-Platform Arbitrage (Primary Focus)
   Exploit pricing differences for the same or related events across platforms like Polymarket and Kalshi. Buy undervalued shares on one platform and hedge with the opposite on the other when probabilities diverge (e.g., Yes on Kalshi + No on Polymarket costs < $1). Low-risk, scalable across overlapping markets (BTC hourly, politics, sports).
2. Long Arbitrage (Yes + No < 100%)
   Buy both Yes and No shares when combined best ask prices sum to less than $1 (e.g., Yes $0.48 + No $0.50 = $0.98). Locks in risk-free profit upon redemption. Common in low-liquidity or new markets.
3. Short Arbitrage (Yes + No > 100%)
   When best bid prices sum over $1, mint a Yes/No pair for $1 and sell both at the bids. Requires position splitting; less purely risk-free due to execution/slippage risks.
4. Multi-Outcome Bundle Arbitrage
   In non-binary markets (e.g., multi-candidate elections), buy all outcomes when total cost < $1, guaranteeing payout. Similar to long arb but scaled to more options.
5. Combinatorial or Time-Based Arbitrage
   Spot violations in linked markets (e.g., election paths or term structures) where combined probabilities don't add up across time horizons. Example: Arbitrage short-term vs. longer-term BTC markets if forward curves are mispriced.

Informational/Timing Edges (Speed & Catalyst-Based)

6. Pricing Lag Exploitation
   Detect temporary lags between real-world data (e.g., spot BTC/ETH prices) and platform odds, especially in short-duration markets like 15-minute or hourly Up/Down bets. Buy undervalued shares post-reset, exit as prices normalize.
7. Anomaly Detection for Strange Price Movements
   Monitor unusual spikes, drops, or volatility in order books signaling mispricings (e.g., sudden imbalances post-news). Use rolling histories and thresholds to trigger trades.
8. Information or Catalyst Arbitrage
   Use external feeds (news APIs, oracles, calendars) to front-run repricing. Trade on releases (earnings, macro data, sports results) before markets fully adjust.
9. High-Probability Bonds
   Buy deeply mispriced near-certain shares (e.g., 99% probability at $0.95) as "bonds" yielding quick returns when they normalize. Lower frequency but steady.

Liquidity & Market Making

10. Market Rebalancing and Liquidity Providing
    Act as market maker: Provide liquidity to capture spreads, rebalance on inefficiencies (e.g., after large trades). Delta-neutral; profit from fees/rebates (especially Polymarket's dynamic taker fees).

Behavioral & Niche

11. Copy Trading or Whale Following
    Monitor profitable wallets (on-chain tools like PolymarketScan) and replicate trades, assuming alpha from bots or edges. Semi-automated; risks front-running.
12. Rules Ambiguity Arbitrage
    Bet on markets with unclear resolution rules (e.g., timing ambiguities), scanning for high-ambiguity scores and positioning based on historical outcomes/Chainlink feeds.