AI can help rank anomalies, but it cannot replace clear rules you can audit.
The mechanism: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers. Depth is not linear. What looks like 'a little thinner' can create a lot more price impact at size.
Where it breaks: An AI risk layer should be explainable: it can rank anomalies, but deterministic guardrails must remain stable and auditable.
A simple test: Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes. Example: small funding transfers compound; over several cycles they can materially shift equity and your maintenance buffer. Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric.
What to do next: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.
Aivora focuses on operational discipline: clean data, stable rules, and clear incident playbooks matter more than hype. Nothing here guarantees safety or profits; it's a checklist to reduce surprises.
The mechanism: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers. Depth is not linear. What looks like 'a little thinner' can create a lot more price impact at size.
Where it breaks: An AI risk layer should be explainable: it can rank anomalies, but deterministic guardrails must remain stable and auditable.
A simple test: Run a small-size rehearsal when liquidity is thin. Observe how stop orders trigger and how mark/last prices diverge around spikes. Example: small funding transfers compound; over several cycles they can materially shift equity and your maintenance buffer. Track funding together with basis and realized volatility. The combination is a better crowding signal than any single metric.
What to do next: Pitfall: assuming mark price equals last price. In stress, they diverge, and liquidation triggers can surprise you.
Aivora focuses on operational discipline: clean data, stable rules, and clear incident playbooks matter more than hype. Nothing here guarantees safety or profits; it's 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.