QuantKit QuantKit

Strategy log — simulated, methodology first.

Algorithmic strategies on crypto perpetual futures, run in simulation. Every simulated trade is logged, and a public track record is published after the evaluation cohort completes.

  • StatusSimulated
  • Risk per trade1–2% (policy target)
  • Maximum monthly drawdown15% (policy target)
  • Public track recordAfter the evaluation cohort

Targets describe the risk policy. They are not guarantees of results, and nothing on this page is a performance claim.

Three strategies, one portfolio

Each strategy targets a distinct market regime. They combine into a portfolio with per-trade risk limits.

  • Momentum Regime

    Identifies trending markets and captures directional moves.

  • Funding Carry

    Captures perpetual funding rate differentials.

  • Volatility Breakout

    Enters on breakout from defined volatility ranges.

Risk framework: keep every trade small

Risk controls keep each trade small and each drawdown bounded. The numbers are policy targets, not guarantees.

  • Per-trade risk cap: 1–2% of account equity (a policy target, not a guarantee)
  • Maximum monthly drawdown: 15% (a policy target, not a guarantee)
  • Four-week cohort reviews: underperformers get paused
  • Every simulated trade is logged with entry, exit and rationale
  • AI-assisted strategy logic with deterministic fallbacks

Methodology first, record later

A public track record is planned after Q4 2026. Until then the strategies run in simulation, and nothing here is a performance claim.

  • StatusSimulated
  • Published resultsNone yet

How the system works

From venue to simulated execution, the full stack.

  • Binance perpetual futures: deep liquidity, 24/7 markets
  • kimi-k3 AI layer: pattern recognition across regime, funding and volatility inputs
  • Deterministic fallbacks: rule-based execution when model confidence is low
  • Four-week cohorts: every strategy runs in an isolated cohort for independent evaluation