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Home Joshua Thompson How to Use a Post-only Order Edge Cases Practical Walkthrough

How to Use a Post-only Order Edge Cases Practical Walkthrough

Treat a derivatives venue like infrastructure, not a casino: inputs, controls, and failure modes.

The mechanism: Funding is a transfer between traders, but timing, rounding, and caps can change equity at the worst moment. Verify schedule and limits.

Where it breaks: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.

A simple test: Compute liquidation price twice: once with optimistic assumptions, and once with conservative slippage and fees. The gap is your uncertainty budget. Example: small funding transfers compound; over several cycles they can materially shift equity and your maintenance buffer. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.

What to do next: Pitfall: ignoring fees and funding in liquidation math. The platform can close you earlier than your stop-loss plan expects.

Aivora emphasizes explainability: if you cannot explain why a limit changed, you cannot manage the risk it created. Derivatives are risky; test assumptions before you scale size.

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.
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