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How to Build an AI Trading Bot for Fetch.ai on OKX

Let’s keep it practical, not poetic. Focus: Fetch.ai contracts on OKX.


Setup

Use 1m. Confirm direction with order-book imbalance, then use funding rate to avoid chasing. If they fight, you sit out—a bit that’s discipline.


Execution

  • Entry: break + retest > first impulse candle.
  • Stop: position sizing by ATR where the idea is invalid.
  • Exit: scale out, then cooldown after 2 losses for the runner.

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. Rules differ by exchange; check margin and liquidation details on your platform.


Wrap: Missed trades are cheaper than liquidation.

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.