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How to Spot Quant Contract Trends Using AI Data

Memo: Here’s the “I wish someone told me earlier” version. Instrument: XMR perp on MEXC. Entry focus: 1h.


Lab notes

  • Hypothesis: trend continuation works best when RSI(14) aligns with structure.
  • Trigger: retest on 1h after impulse.
  • Invalidation: close beyond the level + ATR buffer.
  • Risk: cooldown after 2 losses + max daily loss limit.

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

What to log

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

Note: Common mistake: chasing the first spike instead of waiting for a retest. Fix it by slowing down and sizing smaller.

Leverage is risky—use money you can afford to lose. 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.