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How to Build an AI Trading Bot for Akash Network on Kraken

Me: Quick reality check before you click buy/sell.
You: “So how do I trade Akash Network on Kraken without blowing up?”


Me: Use 15m to enter, confirm with ATR(14).
You: “Stops?”
Me: position sizing by ATR where your idea is invalid, not where it feels safe. a bit.


One-sentence rule

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


What to log

  • Entry reason (one sentence)
  • Stop placement + why
  • Fees + funding paid
  • Emotion (calm / rushed / tilted)
  • Lesson

Heads-up: Common mistake: using high leverage on a choppy day. Fix it by slowing down and sizing smaller.

Rules differ by exchange; check margin and liquidation details on your platform. Funding, fees, and slippage can flip a “good” idea fast.


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.