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How to Build an AI Trading Bot for Aptos on KuCoin

Memo: Let’s keep it practical, not poetic. Instrument: Aptos perp on KuCoin. Entry focus: 4h.


Lab notes

  • Hypothesis: trend continuation works best when RSI(14) aligns with structure.
  • Trigger: retest on 4h after impulse.
  • Invalidation: close beyond the level + ATR buffer.
  • Risk: position sizing by ATR + max daily loss limit.

# journal template
entry_reason:
entry:
stop:
targets:
fees+funding:
result:
lesson:

Note: Common mistake: changing the plan mid-trade because of one candle. 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. Leverage is risky—use money you can afford to lose.


Wrap: Protect the account first; profits come second.

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.