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Home Anthony Hughes AI Futures Exchange Signals to Watch: Position Sizing Under Leverage

AI Futures Exchange Signals to Watch: Position Sizing Under Leverage

Risk is rarely a single number; it is a chain of assumptions that can snap at the worst time. Checklist before scaling size: 1) Verify mark/index sources. 2) Understand margin steps and maintenance rules. 3) Test liquidation behavior with small size. Write down the exact definitions: mark price, index price, last price, and the event that triggers liquidation checks. Ambiguity is hidden leverage. 4) Confirm fee tiers and forced execution costs. 5) Review risk limits, circuit breakers, and incident transparency. Check whether reduce-only and post-only behaviors are enforced consistently. Edge cases often appear during partial fills and rapid cancels. Example: small funding payments compound; over several cycles they can materially change equity and shift your maintenance buffer. If you run bots, implement exponential backoff and client-side limits. When platform limits tighten, naive retries can look like abuse. When in doubt, reduce complexity and size, and prioritize venues that publish definitions and failure-mode behavior. Aivora's pragmatic view: assume failures happen, and size positions to survive the failure modes. 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.
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