Most platform comparisons stop at fees, but execution and liquidation behavior decide the real cost.
What it is: Fee design is part of risk: forced execution costs can reduce your liquidation distance, and rebates can attract toxic flow that degrades fills. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
What to check: An AI risk layer should be explainable: it can rank anomalies, but deterministic guardrails must remain stable and auditable.
How to test it: 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. Treat cross margin as a correlated portfolio. Correlations converge during stress, so diversification can vanish when you need it most.
Common pitfalls: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. Derivatives are risky; test assumptions before you scale size.
What it is: Fee design is part of risk: forced execution costs can reduce your liquidation distance, and rebates can attract toxic flow that degrades fills. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
What to check: An AI risk layer should be explainable: it can rank anomalies, but deterministic guardrails must remain stable and auditable.
How to test it: 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. Treat cross margin as a correlated portfolio. Correlations converge during stress, so diversification can vanish when you need it most.
Common pitfalls: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. 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.
No. This site is educational and system-focused. You are responsible for decisions and risk management.