Prediction Market Arbitrage Bot: Verify Every Leg

Prediction Market Arbitrage Bot: Begin With a Payoff Table

List every relevant state of the world and the amount each proposed position pays in that state. For a simple binary event with exhaustive complementary outcomes, buying one Yes and one No may produce a combined one-unit payout regardless of the ordinary result. That statement depends on the contracts having the same event definition and compatible settlement treatment.

Write the states down even when the relationship seems obvious. Include cancellation, postponement, unresolved results, and any special treatment specified by the actual contracts. A strategy that covers only ordinary Yes and No outcomes may leave a different payoff in an exceptional case. If the exceptional treatment is unknown, the combination has an unverified assumption rather than a guaranteed floor.

The payoff table should use exact quantities and units. One contract on one service may not represent the same amount as one contract elsewhere. Normalize only after verifying the unit definitions. Store the raw identifiers and terms alongside the normalized representation so that a reviewer can trace each calculated payoff back to a specific tradable instrument.

Prove Equivalence Beyond the Headline

Two markets can ask apparently similar questions while using different deadlines, data sources, thresholds, or revision policies. A contract based on an initial statistic is not necessarily equivalent to one based on a final revised statistic. A contract about an announcement is not necessarily equivalent to one about the action taking effect. Small wording differences can create large differences in payoff.

Build an equivalence checklist containing the event, subject, measurement, cutoff, resolution authority, and exceptional rules. The comparison should be stored as evidence, not merely asserted by a model or inferred from text similarity. Automated matching can suggest candidates, but an accepted mapping needs a reason that survives close inspection of both contracts.

Revalidate when terms or identifiers change. An old mapping should not be reused for a new market simply because its title follows the same pattern. Version the mapping and attach it to every decision. If a contract update arrives while an order sequence is in progress, stop new dependent actions until the system knows whether the original payoff assumptions still apply.

The Polymarket outcome-matching guide applies that equivalence test to complete sets, multi-outcome baskets and separately funded cross-venue positions.

The NHL prediction market bot examples compare regulation and eventual-win conditions, including a game path on which apparently offsetting positions can both lose.

Calculate the Complete Entry Cost

Suppose complementary hypothetical contracts can be purchased at 0.46 and 0.50. Their displayed total is 0.96 against an assumed combined payout of one unit. That creates a gross difference of 0.04 before fees, execution effects, funding costs, and exceptional-case risk. Reporting four percent as a realized return would skip nearly the entire decision process.

Price the actual requested quantity across the order book. If only a small amount is available at the best ask, the average cost can exceed the displayed pair of prices. Add the venue's applicable fee calculation for each leg and any required conversion or network expense. Preserve the inputs and calculation version so that later reconciliation can explain deviations.

Use a margin requirement above the modeled costs. The requirement can account for uncertainty in latency, depth, or fee estimates, but it should be an explicit policy rather than an arbitrary number adjusted after losses. Test how the result changes under less favorable fills. If a tiny price movement removes the advantage, the execution policy must recognize that sensitivity before the first order is sent.

Reserve Capital for the Whole Sequence

A multi-leg opportunity can require funds in more than one account. Having enough aggregate value across the application does not mean the necessary buying power is available where each leg must execute. Check each account's settled balance, reserved funds, open orders, and any conversion requirements before starting the sequence.

Do not assume that transfers will complete in time to rescue a partially executed trade. Funding movement can involve delays, fees, eligibility requirements, or unavailable services. A strategy should use capital that is already verified and available under its policy, or explicitly model the transfer process as another uncertain stage. A dashboard total is not an execution guarantee.

Reserve funds atomically within the local risk system so that another strategy cannot spend the same capacity while the sequence is being prepared. If preparation fails, release only the reservations that are no longer needed. When an order outcome is uncertain, retain the corresponding reservation until reconciliation establishes the true exposure. Premature release can create accidental leverage across concurrent strategies.

Treat Execution as a Sequence of Exposures

Two orders sent close together are not necessarily executed together. One can fill while the other is rejected, delayed, or partially filled. From the first fill until the intended combination is complete, the account may carry directional exposure. The strategy needs a defined policy for that interval, including maximum time and maximum acceptable recovery cost.

Choose the order sequence deliberately. Available depth, account reliability, supported order types, and the ease of closing an unmatched leg may influence the choice. There is no universal rule that one side should always go first. The decision should be justified by measured behavior for the actual integrations rather than by a generic diagram of simultaneous arrows.

Save an opportunity identifier that connects every order, fill, cancellation, and recovery action. This allows the system to reconstruct the combination after restart and prevents a replacement worker from treating a half-completed sequence as a fresh opportunity. A durable state machine is especially important when a connection fails immediately after an order reaches the venue.

Define Partial-Fill Policy in Advance

Suppose the strategy requests one hundred units on each of two complementary outcomes. The first leg fills one hundred, but the second fills only sixty. The completed sixty-unit combination and the unmatched forty-unit position are economically different. The application must show them separately rather than labeling the whole opportunity successfully hedged.

A recovery policy might try to complete the remaining quantity within a strict price limit, reduce the first leg at a bounded loss, or stop for review when neither action is supported safely. The policy depends on the venue and the user's constraints. It must not keep increasing the acceptable price indefinitely in pursuit of the original theoretical profit.

Test cancel-versus-fill races. A request to cancel the second leg may arrive after some additional quantity has filled. Reconcile the final filled amount before sizing a recovery order, or the hedge itself can create an opposite unmatched position. Recovery calculations should be driven by observed account evidence, not the last quantity displayed on a local screen.

Prediction Market Arbitrage Bot: Include Settlement Timing in the Economics

Even a completed combination can tie up capital until resolution and settlement. A small surplus over a long period is economically different from the same surplus released quickly. Record the expected holding period and stress longer delays. The relevant return comparison must account for how long funds are unavailable, without implying that a projected annualized figure is a dependable yield.

Different accounts may release funds at different times. One contract can resolve while another remains pending under its own process. During that interval, the combined payoff may be expected but not fully realized. Keep unsettled claims separate from available balances and avoid using them to fund new orders unless the account itself makes that capacity available and the risk policy permits it.

Settlement delays also affect monitoring. A strategy cannot forget an opportunity after its trading legs fill. It needs to observe final resolution, verify the account changes, and close the opportunity record only when reconciliation is complete. Long-lived records should survive application updates and machine restarts without losing the terms that justified the original trade.

Compare Account and Market Constraints

Cross-profile trading requires each account to be independently eligible, connected, funded, and permitted to trade the selected contracts. A working public data feed does not establish private order capability. International and US profiles should not be treated as interchangeable accounts, and software should not attempt to bypass access restrictions to complete a proposed combination.

Record supported order types and quantity increments for each integration. A desired hedge ratio may need rounding, which leaves residual exposure. Minimum order sizes can also make a small opportunity impractical. Include these constraints before calculating the required capital and expected payout, rather than discovering them after one leg has already filled.

Use the Polymarket module guide for the product's account and strategy context. An arbitrage research feature belongs inside those boundaries. It should explain when a candidate cannot proceed because an account capability is missing, rather than presenting unavailable operations as a temporary inconvenience that the bot can somehow route around.

Avoid Double-Counting Opportunities

The same underlying discrepancy may appear through several related contract combinations. If the bot treats each combination independently, it can overuse the same liquidity or accumulate concentrated exposure. Group candidates by shared instruments and underlying event, and allocate depth conservatively across them. A book level cannot be assumed available in full to every simultaneous strategy.

Repeated scans also require deduplication. An unchanged quote observed several times is not several new opportunities. Use market versions, decision timestamps, and active opportunity state to prevent duplicate sequences. After a failed attempt, a retry should require a clear reason and a fresh risk check, not merely another timer tick.

Distinguish detected candidates from attempted and completed combinations. A scanner can identify many price differences while few survive contract matching, complete cost calculations and executable depth. Review the reasons candidates were excluded. A large candidate count describes the breadth of the search; it does not establish that equivalent positions were available or that a complete combination could be entered profitably.

Stress the Assumptions Separately

Review the assumptions that could invalidate an apparent opportunity. A different deadline can break contract equivalence, a higher fee can consume the margin and disappearing depth can leave one leg unmatched. Consider each independently before committing funds. Knowing which condition the plan depends on is more useful than treating every price gap as the same low-risk transaction.

Then combine failures. An account request may time out while the market terms update and the app restarts. The system should recover the existing opportunity, query authoritative state, and refuse to create new exposure until the ambiguity is resolved. A single happy-path simulation cannot demonstrate that behavior; it needs durable records and deliberate interruption tests.

Keep hypothetical payoff analysis separate from completed account results. A calculation can show how matched outcomes would settle under its assumptions. Actual orders reveal timing, depth and partial fills that the calculation does not establish. Use both in the review, while retaining the distinction between a theoretical surplus and money realized after the entire sequence is reconciled.

Report Every Component of the Result

For a completed opportunity, review the original quotes, requested quantities, actual fills, fees, recovery costs and settlement amounts. Include elapsed time and any period with an unmatched leg. Compare the theoretical surplus at detection with the confirmed result. This explains where the apparent advantage was consumed and provides a specific basis for reviewing the scanner's selection limits.

Include failed and abandoned opportunities. An unmatched leg closed at a loss belongs in the strategy result even if the intended combination never completed. Research costs and account-level operational expenses should also be disclosed when they are part of the evaluation. A performance report that retains only completed profitable combinations selects away the most important execution risks.

Aggregate results by contract family and integration pair. A method can work tolerably in one setting and fail in another because liquidity or order behavior differs. Do not generalize a narrow successful test to every market shown in the header. The scope of a supported strategy should follow the scope of its evidence.

Use a Bounded Worked Example

Take a hypothetical fifty-unit combination with asks of 0.47 and 0.49, and modeled total fees of 0.01 per completed pair. If all units fill at those prices and ordinary complementary settlement pays one unit, the modeled surplus is 0.03 per pair, or 1.50 total. This is a conditional calculation, not a guaranteed result.

Now suppose the first fifty units fill at 0.47, while the second leg fills thirty at 0.49 and the remaining twenty would cost 0.55. Completing at the higher price would make those twenty pairs cost 1.03 including the same simplified fee assumption. The original opportunity no longer applies uniformly. The policy must evaluate the unmatched quantity and its recovery choices using the current book and actual costs.

If the configured maximum completion price is 0.51, the bot must not override it simply to mark the opportunity complete. It may attempt another permitted recovery action or stop with explicit unmatched exposure. The report should show thirty completed pairs and twenty units requiring resolution, with every subsequent action attached to the same opportunity record. This example demonstrates why a small displayed discrepancy needs a full order and recovery policy.

Decide Whether the Workflow Deserves Activation

Before activating the approach, document the contract-matching rule, payoff cases, account permissions, complete costs and response to an unmatched leg. Review the effect of partial fills and ordinary connection failures on total exposure. A plan that explains only perfect combinations leaves its most consequential decisions unspecified. Keep those decisions within the account's capital and loss limits.

Keep a clear stop condition for each unresolved dependency. Missing settlement semantics, unsupported cancellation, unverified fees, or ambiguous account balances should prevent the affected strategy from proceeding. Those conditions can be investigated and corrected without weakening the policy. The purpose of automation is consistent execution of a justified process, including a consistent decision to skip an attractive-looking quote.

The strongest arbitrage tool is therefore an evidence and execution system, not merely a price-difference alarm. It can explain why instruments match, how the proposed payout is constructed, what happens when execution is incomplete, and how the account result was reconciled. Until those explanations are backed by tests for the intended markets, the appropriate output is a research candidate rather than a promise of low-risk income.

For one completed combination, reconstruct the opportunity from its saved records. Identify both contracts, the order sequence, any unmatched interval and the final account changes. If a detail is missing, preserve that limitation in the review. Understanding the full sequence is more useful than judging an arbitrage approach solely from a theoretical surplus at the moment of detection.

Related Guides and Worked Examples

• Polymarket Arbitrage Bot: Complete-Set Economics — Test complementary-share economics against executable prices and incomplete trade legs.
• Polymarket Automated Arbitrage Bot: Leg Risk and Funds — Coordinate complementary trades when execution is not atomic and collateral is limited.
• Polymarket Odds Arbitrage Software: Compare Claims — Compare odds only after matching contract rules and realistic execution costs.
• Kalshi Arbitrage Bot: Test the Payoff First — Test whether apparently offsetting contracts truly have equivalent payoff rules.
• Kalshi Odds Arbitrage Bot: Compare Like With Like — Distinguish apparent odds differences from executable, rule-matched opportunities.
• Kalshi Vs Polymarket Arbitrage Bot: Verify Both Legs — Compare two independent venues without assuming equivalent rules or simultaneous execution.