Denarios is a full-stack trading infrastructure built with Python and Django to research, simulate, and execute crypto futures trading strategies.
It supports multi-timeframe analysis, backtesting with detailed metrics, and real-time trading via the Binance Futures API.
This is not a toy bot. It's a flexible, production-grade framework to develop, validate, and iterate algorithmic trading ideas at scale.
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📉 Multi-asset & Multi-timeframe support
Backtest and execute strategies across BTC, ETH, SOL, XRP — or any asset available on Binance Futures. -
🧠 Strategy-agnostic architecture
Plug any technical logic or indicator — dozens of strategies already tested using EMA, RSI, volume signals, engulfing candles, and more. -
🧪 Custom backtesting engine
Simulates entry/exit conditions, stop loss, take profit, and trailing stops. Logs every trade to SQL for analytics. -
📊 Real-time visual analytics
Built-in charts for drawdown, Sharpe ratio, profit factor, win/loss ratio — filterable by asset or strategy. -
🤖 Live execution-ready
Two real-time bots (Agripina & Anastasia) manage entry and exits on Binance Futures using REST API with optional email alerts. -
⚙️ Modular indicator system
Easily add indicators to any timeframe or asset using theAddIndicatorsmodule. -
🗄️ Database integration
Trades (real or simulated) are logged into SQL via Django models for later querying and performance review.
Denarios/
├── app/ # Django models for trades, simulations, strategies
├── templates/ # Web frontend for reviewing position history and stats
├── bots/
│ ├── simulaciones/ # Core simulation/backtesting logic
│ │ ├── A90/ # Most recent strategy logic
│ │ ├── snippets/ # Metrics & visualizations (drawdown, Sharpe, etc.)
│ ├── samples/
│ │ ├── CryptoGetSamples/ # Data download from Binance
│ │ ├── AddIndicators/ # Custom indicators for OHLCV data
│ ├── AA/ and AA9/ # Real-time bots
│ │ ├── Agripina.py # Strategy execution & trade entry
│ │ ├── Anastasia.py # TP/SL management & trade closure
│ ├── Funciones/ # Live loop, filters, time checks
├── CryptoAnalyzer/ # Binance connection, trade functions, price feed
├── BotsForex/ # (WIP) Future forex bot replication
└── settings/ # Django configuration
- Python 3
- Django
- Pandas / NumPy
- TA-Lib /
ta - Binance REST API (Futures)
- PostgreSQL / SQLite
- Matplotlib / Seaborn
- SMTP (email alerts)
This project was built from scratch over years of experimentation. While it’s not currently profitable, it has been instrumental in learning how to:
- Design scalable, testable quant trading systems
- Automate market data ingestion, strategy execution, and reporting
- Evaluate performance with real metrics and visual feedback
- Iterate fast over dozens of strategies with minimal code changes
This system is for educational and research purposes. It does not guarantee returns. Use at your own risk when trading real funds.