tokenometry 1.0.3

A sophisticated multi-strategy crypto analysis bot for trading signals

Tokenometry

A tool that measures and analyzes all the critical data points of a crypto token—such as its price, volume, volatility, and market sentiment—to help users make informed decisions.

NOTE: in the 1.0.2 I removed the external API to fectch the data for Sentiment. It slows down the process, the code is still in main_milesstone in case you want to take a look.

Crypto Analysis Bot

This repository contains a sophisticated, multi-strategy crypto analysis bot written in Python. The bot is designed to scan the cryptocurrency market, apply a range of analytical models, and generate trading signals based on a confluence of technical, sentiment, and on-chain data. It is architected to be flexible, allowing the user to switch between long-term investment, swing trading, and high-frequency day trading strategies.

Features

• Multi-Asset Scanning: Monitors a configurable list of cryptocurrencies from Coinbase.
• Multi-Timeframe Analysis (MTA): Establishes a long-term trend on a higher timeframe to filter and confirm signals on a lower timeframe.
• Multi-Factor Signal Confirmation:
  • Technical Analysis: Utilizes a robust combination of indicators, including Exponential Moving Averages (EMAs), the Relative Strength Index (RSI), and the Moving Average Convergence Divergence (MACD).
  • News Sentiment Analysis: Integrates with NewsAPI to gauge the prevailing market narrative and filter signals that run contrary to strong market sentiment.
  • On-Chain Analysis: Connects to the Glassnode API to analyze fundamental investor behavior, such as accumulation or distribution patterns based on exchange net flows.
• Automated & Continuous Operation: Designed to run 24/7 on a server, with a configurable analysis frequency and comprehensive logging for performance tracking and debugging.
• Dynamic Risk Management: Automatically calculates a suggested stop-loss and position size for every BUY signal based on market volatility (using the Average True Range - ATR) and a predefined risk percentage.
• Secure Configuration: All API keys and sensitive information are managed securely using an .env file.

Strategies

The bot can be run in one of three distinct modes, each designed for a different trading style.

Feature	Milestone 7 (Long-Term)	Milestone 10 (Aggressive Swing)	Milestone 11 (Day Trader)
Primary Goal	Identify major, multi-month market trends	Capture multi-day or multi-week market swings	Capture intraday momentum shifts
Trader Profile	Position Trader / Long-Term Investor	Swing Trader	Day Trader
Analysis Frequency	Every 24 hours	Every 4 hours	Every 5 minutes
Trend Timeframe	Weekly (W1)	Daily (D1)	1-Hour (H1)
Signal Timeframe	Daily (D1)	4-Hour (H4)	5-Minute (M5)
Core Indicators	50/200 SMA Crossover	20/50 EMA Crossover	9/21 EMA Crossover
Data Filters	Technicals + Sentiment + On-Chain	Technicals + Sentiment	Technicals Only
Risk Per Trade	1.0%	1.0%	0.5% (Tighter)

Installation

Option 1: Install from PyPI (Recommended)

pip install tokenometry

Option 2: Install from Source

1. Clone the repository:

   git clone [https://github.com/nguyenph88/Tokenometry.git](https://github.com/nguyenph88/Tokenometry.git)
   cd Tokenometry
   

2. Create and activate a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install the package in development mode:

   pip install -e .
   

4. Set up your API keys (optional):

   • Copy env.example to .env
   • Add your API keys to the .env file. The bot will gracefully handle missing keys by skipping the corresponding analysis.

   cp env.example .env
   # Edit .env with your actual API keys
   

Usage

The bot can be configured to run in three different trading modes, each optimized for different trading styles and timeframes. The configuration is handled through the example_usage.py script, which demonstrates how to use the Tokenometry library.

Quick Start

1. Run the example script:

   python example_usage.py
   

2. Choose your strategy by uncommenting one of the three configurations in the script:

   # CHOOSE YOUR STRATEGY HERE
   chosen_config = DAY_TRADER_CONFIG      # For day trading
   # chosen_config = SWING_TRADER_CONFIG  # For swing trading
   # chosen_config = LONG_TERM_CONFIG     # For long-term investing
   

Strategy Configurations

1. Day Trader Strategy (High-Frequency)

Best for: Active day traders who want to capture intraday momentum shifts Analysis Frequency: Every 5 minutes Timeframes: 5-minute signals, 1-hour trend confirmation

DAY_TRADER_CONFIG = {
    "STRATEGY_NAME": "Day Trader",
    "PRODUCT_IDS": ["BTC-USD", "ETH-USD", "SOL-USD", "AVAX-USD"],
    "GRANULARITY_SIGNAL": "FIVE_MINUTE",    # 5-minute chart for signals
    "GRANULARITY_TREND": "ONE_HOUR",        # 1-hour chart for trend
    "SHORT_PERIOD": 9,                      # Fast EMA
    "LONG_PERIOD": 21,                      # Slow EMA
    "RISK_PER_TRADE_PERCENTAGE": 0.5,      # Conservative 0.5% risk
    "ATR_STOP_LOSS_MULTIPLIER": 2.0,       # Tight stop-loss
}

When to use: During active trading hours when you want to catch quick momentum shifts and scalp small profits.

2. Aggressive Swing Trader Strategy

Best for: Swing traders who hold positions for days to weeks Analysis Frequency: Every 4 hours Timeframes: 4-hour signals, daily trend confirmation

SWING_TRADER_CONFIG = {
    "STRATEGY_NAME": "Aggressive Swing Trader",
    "PRODUCT_IDS": ["BTC-USD", "ETH-USD", "LINK-USD"],
    "GRANULARITY_SIGNAL": "FOUR_HOUR",     # 4-hour chart for signals
    "GRANULARITY_TREND": "ONE_DAY",        # Daily chart for trend
    "SHORT_PERIOD": 20,                    # Medium-term EMA
    "LONG_PERIOD": 50,                     # Long-term EMA
    "RISK_PER_TRADE_PERCENTAGE": 1.0,     # Standard 1% risk
    "ATR_STOP_LOSS_MULTIPLIER": 2.5,      # Moderate stop-loss
}

When to use: For capturing multi-day market swings and trend reversals, ideal for part-time traders.

3. Long-Term Investor Strategy

Best for: Position traders and long-term investors Analysis Frequency: Every 24 hours Timeframes: Daily signals, weekly trend confirmation

LONG_TERM_CONFIG = {
    "STRATEGY_NAME": "Long-Term Investor",
    "PRODUCT_IDS": ["BTC-USD", "ETH-USD"],
    "GRANULARITY_SIGNAL": "ONE_DAY",       # Daily chart for signals
    "GRANULARITY_TREND": "ONE_WEEK",       # Weekly chart for trend
    "TREND_INDICATOR_TYPE": "SMA",         # Simple Moving Average
    "SHORT_PERIOD": 50,                    # 50-day SMA
    "LONG_PERIOD": 200,                    # 200-day SMA
    "RISK_PER_TRADE_PERCENTAGE": 1.0,     # Standard 1% risk
    "ATR_STOP_LOSS_MULTIPLIER": 2.5,      # Moderate stop-loss
}

When to use: For identifying major market trends and making long-term investment decisions.

Customizing Your Strategy

You can modify any configuration by editing the parameters:

# Example: Custom day trading configuration
CUSTOM_DAY_TRADE = {
    "STRATEGY_NAME": "Custom Day Trader",
    "PRODUCT_IDS": ["BTC-USD", "ETH-USD"],  # Monitor fewer assets
    "GRANULARITY_SIGNAL": "FIVE_MINUTE",
    "GRANULARITY_TREND": "ONE_HOUR",
    "SHORT_PERIOD": 5,                      # Faster signals
    "LONG_PERIOD": 13,                      # Shorter trend
    "RSI_PERIOD": 10,                       # More sensitive RSI
    "RISK_PER_TRADE_PERCENTAGE": 0.25,     # Very conservative
    "ATR_STOP_LOSS_MULTIPLIER": 1.5,       # Tighter stops
}

Understanding the Signals

The bot generates three types of signals:

• BUY: Golden cross (fast EMA > slow EMA) + bullish trend + RSI not overbought + MACD bullish
• SELL: Death cross (fast EMA < slow EMA) + bearish trend + RSI not oversold + MACD bearish
• HOLD: No crossover or trend misalignment

Risk Management Features

• Automatic Stop-Loss: Calculated using ATR (Average True Range) for volatility-adjusted stops
• Position Sizing: Automatically calculates position size based on your risk percentage
• Portfolio Protection: Each trade risks only the specified percentage of your portfolio

Logging and Monitoring

The bot provides comprehensive logging:

• Console Output: Real-time signal information
• File Logging: Complete audit trail in trading_app.log
• Signal Details: Timestamp, asset, signal type, trend, price, and trade plan

Running in Production

For 24/7 operation on a server:

1. Use a process manager like systemd, supervisord, or PM2
2. Set up monitoring to restart the bot if it crashes
3. Configure log rotation to manage log file sizes
4. Set up alerts for critical errors or signal generation

Example Output

2025-08-19 21:20:12,698 - CryptoTraderApp - INFO - Starting new scan with 'Day Trader' strategy.
2025-08-19 21:20:12,699 - CryptoTraderApp - INFO - Fetching ONE_HOUR data for BTC-USD...
2025-08-19 21:20:12,886 - CryptoTraderApp - INFO - Trend for BTC-USD on ONE_HOUR chart: Bearish
2025-08-19 21:20:12,886 - CryptoTraderApp - INFO - Fetching FIVE_MINUTE data for BTC-USD...
2025-08-19 21:20:13,108 - CryptoTraderApp - INFO - Calculating technical indicators...
2025-08-19 21:20:13,114 - CryptoTraderApp - INFO - Generating signals on FIVE_MINUTE chart...
2025-08-19 21:20:14,249 - CryptoTraderApp - INFO - Scan complete. Found 0 actionable signals.
2025-08-19 21:20:14,249 - CryptoTraderApp - INFO - Sleeping for 5.0 minutes until the next scan.

Disclaimer

This tool is for analytical and educational purposes only. It is not financial advice. The signals generated by this bot are based on algorithmic analysis and do not guarantee any specific outcome. Always conduct your own research and consult with a qualified financial advisor before making any investment decisions.

Disclaimer This tool is for analytical and educational purposes only. It is not financial advice. The signals generated by this bot are based on algorithmic analysis and do not guarantee any specific outcome. Always conduct your own research and consult with a qualified financial advisor before making any investment decisions.