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Home insurance fund vs slippage on ai margin trading platform How to Build an AI Trading Bot for Quant on Deribit

How to Build an AI Trading Bot for Quant on Deribit


Me: Alright, let’s do this the clean way.
You: “So how do I trade Quant on Deribit without blowing up?”


Me: Use 1m to enter, confirm with liquidation clusters.
You: “Stops?”
Me: cooldown after 2 losses where your idea is invalid, not where it feels safe. lowkey.


Note: Common mistake: ignoring fees/funding because it ‘seems small’. Fix it by slowing down and sizing smaller.

One-sentence rule

If structure is unclear, I do nothing. If it’s clear, I risk small and follow the plan.


Funding, fees, and slippage can flip a “good” idea fast. Educational only, not financial advice.


Wrap: If it feels like gambling, size down. Immediately.

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.