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Risk Limit Tiers Overview on AI Contract Trading Exchange

Most 'smart risk' claims fail in the details: inputs, thresholds, and what happens when data breaks. Checklist before scaling size: 1) Verify mark/index sources. 2) Understand margin steps and maintenance rules. 3) Test liquidation behavior with small size. When latency spikes, your strategy can switch from maker to taker without warning. That switch can compound fees and reduce liquidation distance. 4) Confirm fee tiers and forced execution costs. 5) Review risk limits, circuit breakers, and incident transparency. If you run bots, implement exponential backoff and client-side limits. When platform limits tighten, naive retries can look like abuse. Example: if index updates lag by even a few seconds in a spike, mark price smoothing can liquidate you after the spot market already bounced. Use smaller orders during thin liquidity before you reduce leverage. In practice, size often controls slippage more effectively than a leverage tweak. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. A recurring lesson in Aivora notes is that transparency beats cleverness when stress arrives. Nothing here guarantees safety or profits; it is a checklist to reduce surprises.

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.