Remora + Freqtrade Integration

Add real-time market risk filtering to your existing Freqtrade strategies

Block high-risk trades in seconds with a simple snippet — no dependencies required

Why Remora + Freqtrade?

Remora helps your Freqtrade strategies avoid high-risk market periods:

Volatility Spikes Skip entries during sudden market volatility

Extreme Fear / Panic Block trades during fear & greed extremes

Choppy Markets Avoid sideways, choppy trading regimes

Market-Wide Selloffs Detect and avoid broad market downturns

Liquidity Traps Skip trades during low liquidity periods

News-Driven Whipsaws Avoid entries during major news events

Important: Remora does NOT replace your strategy. It simply acts as a "risk filter" that blocks the entries most likely to lose money. Your existing logic stays intact, but you avoid the worst trades.

⚡ Quickest Start (Beginner-Friendly)

If you already have a strategy and want to start protecting it immediately, this is all you need.

Step 1: Set your API key

export REMORA_API_KEY="your-api-key"

(Or add it to ~/.bashrc / ~/.zshrc for persistence.)

Step 2: Add Remora to your strategy

Inside your strategy class, add this method (or integrate into your entry logic):

import os
import requests

def confirm_trade_entry(self, pair: str, **kwargs) -> bool:
    api_key = os.getenv("REMORA_API_KEY")
    headers = {"Authorization": f"Bearer {api_key}"} if api_key else {}
    try:
        response = requests.get(
            "https://remora-ai.com/api/v1/risk",
            params={"pair": pair},
            headers=headers,
            timeout=2.0
        )
        data = response.json()
        return data.get("safe_to_trade", True)
    except Exception:
        return True  # Fail-open if Remora is unavailable

Then wrap your entry logic:

if not self.confirm_trade_entry(pair):
    dataframe.loc[:, 'enter_long'] = 0

That's it. No extra dependencies, no plugins, no cloning a repo. Your strategy will skip risky entries automatically.

Step 3: Verify it works

Run a small backtest:

freqtrade backtesting --strategy YourStrategy

Watch your logs — entries blocked by Remora will show safe_to_trade=False.

Example Strategies

The Remora Freqtrade repository includes complete working examples:

simple_risk_filter_strategy.py — minimal Remora integration
advanced_risk_filter_strategy.py — position sizing, dataframe columns, multi-timeframe context
freqtrade_config_snippet.json — example Freqtrade configuration file

These examples show how to extend your strategy with more features like risk-based position sizing and detailed logging.

View Repository on GitHub →

Advanced Usage (Free Tier)

For more control with the current free tier, you can use the remora.client for structured access to risk_score and reasoning:

from remora.client import RemoraClient

client = RemoraClient()
risk_data = client.get_risk("BTC/USDT")

if risk_data["risk_score"] > 0.7:
    dataframe.loc[:, 'enter_long'] = 0

Advanced features include:

Adjust thresholds for risk sensitivity in your own code
Combine Remora with technical indicators
Block only specific patterns during high-risk regimes
Multi-timeframe context and detailed logging

Note: Advanced users using remora.client may want to check requirements-advanced.txt for optional dependencies. The simple snippet integration requires no additional dependencies.

Want Proof?

Backtests comparing with/without Remora show actual trade improvements, smoother equity curves, and fewer losing entries.

See comprehensive backtesting results in the Remora Backtests Repository.

You can also view our Evidence & Backtesting page for detailed analysis and results.

Who This Is For

Beginners

Add the snippet — start blocking risky entries instantly

Intermediate

Use advanced_risk_filter_strategy.py — log risk, adjust sizing

Advanced

Full API + custom weighting — regime-aware optimisation

Ready to Get Started?

Start protecting your Freqtrade strategies today. No credit card required.

Get Your Free API Key View API Documentation

💬 Contributing & Feedback

PRs, issues, and feature requests are welcome! Visit the GitHub repository to contribute or ask questions.

Questions? Visit remora-ai.com

Remora Risk Engine