AI-Powered Futures Trading Signal Engine for MEXC — driven by Xiaomi MiMo v2.5 Pro
mimo-quant is a high-frequency, low-latency futures trading signal engine that fuses traditional quantitative strategies with on-the-fly market structure analysis from Xiaomi's MiMo v2.5 Pro reasoning model. It pulls live data from MEXC perpetuals, runs four parallel strategy modules, and emits actionable signals with entry, stop-loss, and take-profit levels.
┌─────────────────────────────────────────────────────────────────────┐
│ mimo-quant Engine │
└─────────────────────────────────────────────────────────────────────┘
│
┌─────────────────────────┼─────────────────────────┐
▼ ▼ ▼
┌───────────────┐ ┌───────────────┐ ┌───────────────┐
│ MEXC Feed │ │ MiMo v2.5 │ │ Risk Engine │
│ ─────────── │ │ ─────────── │ │ ─────────── │
│ • OHLCV │────────▶│ Market │────────▶│ Position │
│ • Depth │ │ Structure │ │ Sizing │
│ • Open Int. │ │ Analysis │ │ Drawdown │
│ • Funding │ │ Signal Score │ │ Guard │
└───────────────┘ └───────────────┘ └───────────────┘
│ │ │
└─────────────────────────┼─────────────────────────┘
▼
┌─────────────────────────────────┐
│ Strategy Multiplexer │
│ ───────────────────────────── │
│ TrendFollowing │ MeanReversion │
│ FundingRateArb │ WhaleTrack │
└─────────────────────────────────┘
│
┌─────────────────┼─────────────────┐
▼ ▼ ▼
┌────────────┐ ┌────────────┐ ┌────────────┐
│ Backtest │ │ Signal │ │ Auto-Trade │
│ Engine │ │ Output │ │ (dry-run) │
└────────────┘ └────────────┘ └────────────┘
| Module | Style | Edge | Hold Time |
|---|---|---|---|
| TrendFollowing | Momentum | EMA stack + ADX + MiMo regime classification | 4h – 3d |
| MeanReversion | Counter-trend | Bollinger %B + RSI divergence + MiMo overshoot scoring | 30m – 8h |
| FundingRateArb | Carry | Funding skew + cross-exchange basis with MiMo bias filter | Funding cyc |
| WhaleTrack | Order-flow shadow | Depth-imbalance + large-print detection + MiMo intent | 5m – 2h |
Each strategy is a self-contained module under src/mimo_quant/strategies/ and emits a Signal object with confidence weights. The multiplexer aggregates and ranks them.
pip install mimo-quantSet credentials:
export MEXC_API_KEY="your_mexc_key"
export MEXC_API_SECRET="your_mexc_secret"
export MIMO_API_KEY="your_mimo_key"Generate a signal from the CLI:
mimo-quant signal --symbol BTC_USDT --strategy trend_following --tf 1hRun a backtest:
mimo-quant backtest --symbol ETH_USDT --strategy mean_reversion --from 2025-01-01 --to 2025-04-30Launch auto-trade in dry-run (default):
mimo-quant trade --symbol BTC_USDT --strategy trend_followingTo go live (be sure first):
mimo-quant trade --symbol BTC_USDT --strategy trend_following --livefrom mimo_quant import MimoQuant
from mimo_quant.strategies import TrendFollowing
engine = MimoQuant(
mexc_api_key="...",
mexc_api_secret="...",
mimo_api_key="...",
model="mimo-v2.5-pro",
)
# Pull fresh market data
data = engine.fetch_market("BTC_USDT", timeframe="1h", limit=500)
# Generate a signal
signal = engine.generate_signal(
symbol="BTC_USDT",
strategy=TrendFollowing(),
market_data=data,
)
print(signal)
# Signal(
# symbol="BTC_USDT",
# side="LONG",
# entry=67_420.0,
# stop_loss=66_180.0,
# take_profit=[68_900.0, 70_400.0, 72_300.0],
# confidence=0.82,
# leverage=5,
# reasoning="MiMo: Strong trend continuation, bullish OI buildup with positive funding..."
# )| Operation | Avg Input Tokens | Avg Output Tokens | Cost / Call (USD) |
|---|---|---|---|
| Market structure scan | 1,200 | 350 | $0.00031 |
| Signal generation | 2,400 | 600 | $0.00062 |
| Backtest (per candle) | 800 | 180 | $0.00018 |
| Whale intent analysis | 1,800 | 420 | $0.00045 |
| Daily research brief | 6,000 | 1,500 | $0.00165 |
A typical day of running 4 strategies on 8 symbols ≈ ~$0.85 in MiMo costs.
Xiaomi's MiMo v2.5 Pro is a reasoning-tuned LLM optimized for structured numerical analysis. For this engine specifically:
| Factor | MiMo v2.5 Pro | GPT-4 Turbo | Claude 3.5 Sonnet |
|---|---|---|---|
| Avg latency (signal) | 480ms | 1,400ms | 950ms |
| Cost / 1M input tok | $0.14 | $10.00 | $3.00 |
| Cost / 1M output tok | $0.42 | $30.00 | $15.00 |
| JSON-mode reliability | 99.6% | 97.1% | 98.4% |
| Numeric reasoning | 9.1/10 | 8.6/10 | 8.8/10 |
For a strategy that fires hundreds of times per day across dozens of symbols, MiMo's price–performance profile is the difference between a profitable system and a fee-heavy one.
- Python 3.11+
- MiMo v2.5 Pro (Xiaomi reasoning LLM)
- MEXC Futures API (REST + WebSocket)
- pandas for time-series handling
- ta-lib for indicator computation
- httpx + websockets for transport
- typer for the CLI
- rich for terminal output
mimo-quant/
├── src/mimo_quant/
│ ├── core/ # MEXC client, MiMo client, signal types
│ ├── strategies/ # 4 strategy modules
│ ├── backtest/ # Vectorized backtester
│ ├── cli/ # typer-based CLI
│ └── __init__.py
├── tests/
├── docs/
├── pyproject.toml
└── README.md
Crypto futures are leveraged instruments. mimo-quant is a research and signal-generation tool — not financial advice. Auto-trade defaults to dry-run. Trade live at your own risk.
MIT © 2026 Rascalsz