A lot of losses come from tiny assumptions: which price triggers liquidation, when funding hits, and how fees are applied.
Quick definition: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately. Operational failures often look like market losses. Log your requests and monitor throttling so you know what changed.
Why it matters: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk.
How to verify: If you automate, use scoped API keys, IP allow-lists, and exponential backoff. Limits often tighten exactly when volatility rises. Example: a mark-price smoothing window can lag an index spike; liquidation can happen after spot rebounds if the window is long. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.
Practical habit: Pitfall: treating automation as set-and-forget. Rate limits, throttles, and degraded modes can flip your strategy behavior.
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.
Quick definition: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately. Operational failures often look like market losses. Log your requests and monitor throttling so you know what changed.
Why it matters: Liquidation is a path, not a single event. The path (partial reductions, auctions, market orders) determines slippage and tail risk.
How to verify: If you automate, use scoped API keys, IP allow-lists, and exponential backoff. Limits often tighten exactly when volatility rises. Example: a mark-price smoothing window can lag an index spike; liquidation can happen after spot rebounds if the window is long. Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes.
Practical habit: Pitfall: treating automation as set-and-forget. Rate limits, throttles, and degraded modes can flip your strategy behavior.
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.
No. This site is educational and system-focused. You are responsible for decisions and risk management.