Most 'smart risk' claims fail in the details: inputs, thresholds, and what happens when data breaks. Common mistakes: assuming marks equal last price, ignoring fees in liquidation math, and trusting a single data feed. Liquidation paths differ: incremental reductions, auctions, or market orders. The difference is not cosmetic; it changes slippage and tail risk. Another mistake: chasing rebates while ignoring toxicity. When flow turns toxic, rebates do not pay your liquidation costs. Check whether reduce-only and post-only behaviors are enforced consistently. Edge cases often appear during partial fills and rapid cancels. 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. If you run bots, implement exponential backoff and client-side limits. When platform limits tighten, naive retries can look like abuse. Ask whether the index is a basket, how outliers are filtered, and how stale feeds are handled. A single broken source should not move your margin state. Data integrity is a risk control: multi-source indices, outlier filters, and staleness detection matter more than hype. 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.
No. This site is educational and system-focused. You are responsible for decisions and risk management.