vgm-risk 1.0.0

Market regime-aware risk firewall for algorithmic trading bots

VGM Risk Engine

A real-time market risk scoring API for algorithmic trading bots.

VGM is not a prediction system. It is a Risk Firewall — a safety layer that evaluates market conditions before any trade is executed.

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What It Does

Submit market features в†’ receive a structured risk assessment:

{
  "action":     "BUY",
  "score":      0.6397,
  "confidence": 0.6603,
  "risk":       0.0205,
  "regime":     "LOW_VOL",
  "optimizer":  "MEAN_VARIANCE"
}

Fields:

• action — BUY / SELL / HOLD
• score — signal strength (0–1)
• confidence — model certainty (0–1)
• risk — estimated position risk (0–1)
• regime — market regime classification (LOW_VOL, HIGH_VOL, TRENDING, etc.)
• optimizer — active portfolio optimization mode

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Quickstart

Start the server

python server/vgm_v13_api.py
# Listens on http://127.0.0.1:8010

Test with curl

curl -X POST http://127.0.0.1:8010/predict \
  -H "Content-Type: application/json" \
  -d '{"features":[1,2,3,4,5],"returns":[0.01,-0.02,0.03]}'

Test with PowerShell

Invoke-RestMethod -Method POST `
  -Uri "http://127.0.0.1:8010/predict" `
  -ContentType "application/json" `
  -Body '{"features":[1,2,3,4,5],"returns":[0.01,-0.02,0.03]}'

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Request Schema

{
  "features": [float, ...],   // OHLCV-derived feature vector
  "returns":  [float, ...]    // recent return series
}

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Freqtrade Integration

See freqtrade/vgm_strategy.py for a ready-to-use strategy that calls the VGM API before placing any order.

from freqtrade.strategy import IStrategy
import requests

class VGMStrategy(IStrategy):
    def confirm_trade_entry(self, pair, order_type, amount, rate, ...):
        payload = {
            "features": self.get_features(pair),
            "returns":  self.get_returns(pair)
        }
        r = requests.post("http://127.0.0.1:8010/predict", json=payload, timeout=1)
        result = r.json()

        if result["action"] == "BUY" and result["risk"] < 0.05:
            return True
        return False

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Architecture

Market Data
    в”‚
    в–ј
Feature Engine  в”Ђв”Ђв–є  VGM Neural Net  в”Ђв”Ђв–є  Risk Firewall
                                               в”‚
                          ┌────────────────────┤
                          в–ј                    в–ј
                     Action Signal        Risk Score
                    (BUY/SELL/HOLD)     + Regime + Confidence

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Stack

• Python 3.10 / FastAPI
• PyTorch neural network (ONNX exportable)
• Freqtrade compatible strategy module
• MT5 bridge (mt5/mt5_risk_bridge.py)
• Docker support (docker-compose.yml)

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Beta Testing

Looking for Freqtrade / crypto bot users to test the live risk scoring API.

Contact: [e-mail] GitHub: https://github.com/Kretski/VGM-Risk-Engine