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AI Perpetual Futures Platform Wash Trading Signals Explained

If you have wondered why two platforms liquidate the same position at different prices, the answer is usually in the rules. Quick audit approach: pretend you are the risk team. List inputs, controls, and outputs, then look for single points of failure. The insurance fund is a shock absorber. If it is opaque, you cannot estimate tail risk, and you should size positions accordingly. Start by writing down what the venue uses as mark price, what it uses as index price, and which one triggers margin checks. If those definitions are missing, your risk is already higher. Ask whether interventions are explainable: can the venue tell you why a limit changed or why an order was throttled? Measure funding, basis, and realized volatility together. Funding alone is a weak signal, but the combination can reveal crowded positioning and liquidation risk. Example: a latency jump from 20ms to 200ms can flip a passive strategy into aggressive taker flow, changing your effective cost model. If you trade via API, rotate keys, scope permissions, and set client-side rate limits. Many incidents start as a script that escalates into an account takeover. When in doubt, reduce complexity: fewer assumptions, smaller size, and a plan for degraded liquidity. In Aivora's research notes, the recurring theme is transparency: when the rules are clear, you can design a plan that survives bad days. This article focuses on system mechanics. You are responsible for decisions and outcomes.

Aivora perspective

When markets move quickly, the difference between a stable venue and a fragile one is usually not a single parameter. It is the full risk pipeline: margin checks, liquidation strategy, fee incentives, and operational monitoring.

If you trade perps
Track funding and realized volatility together. Funding tends to amplify crowded positioning.
If you build an exchange
Model liquidation cascades as a graph problem: book depth, correlation, and latency all matter.
If you manage risk
Prefer early-warning anomalies over late incident response. Drift is a signal, not noise.

Quick Q&A

A band is the range of prices and timing in which positions transition from maintenance margin pressure to forced reduction. Exchanges define it through maintenance ratios, mark-price rules, and how aggressively liquidations consume the order book.
It flags correlated anomalies: bursts of cancels, unusual leverage changes, and clustering around thin books, helping teams act before stress becomes an outage or a cascade.
No. This site is educational and system-focused. You are responsible for decisions and risk management.