Crypto Correlation Calculator

A Python script that calculates the correlation between various cryptocurrencies and Bitcoin (BTC) using historical price data from Binance Futures. The script filters cryptocurrencies based on a specified correlation threshold and exports a list formatted for use in TradingView.

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Features

• Fetch Historical Data: Retrieves historical closing price data for a list of selected cryptocurrencies from Binance USDT-M Futures.
• Calculate Correlations: Computes the Pearson correlation coefficient between each cryptocurrency's returns and BTC's returns.
• Filter by Threshold: Allows users to set a correlation threshold to filter cryptocurrencies that are highly correlated with BTC.
• Export to TradingView: Generates a formatted list of symbols that can be directly imported into TradingView's watchlists or indicators.

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Usage

Install Dependencies

Ensure you have Python 3.x installed. Install the required libraries using pip:

pip install ccxt pandas numpy

Configure Parameters

• Symbol List: Modify the symbols list in the script to add or remove cryptocurrencies.
• Correlation Threshold: Set the threshold variable in the script to your desired correlation value (e.g., 0.6).

Run the Script

Execute the script from the command line:

python crypto_correlation_calculator.py

Output

• The script prints the correlation coefficients in the console.
• It generates an output file named HighCorrelation.txt containing the list of filtered symbols formatted for TradingView.

Example Output

An example of the formatted output list:

BINANCE:ETHUSDT.P,BINANCE:DOGEUSDT.P,BINANCE:BCHUSDT.P,BINANCE:SOLUSDT.P,BINANCE:RUNEUSDT.P,BINANCE:NEARUSDT.P,BINANCE:BNBUSDT.P,BINANCE:1000SHIBUSDT.P,BINANCE:AVAXUSDT.P,BINANCE:OPUSDT.P,BINANCE:APTUSDT.P,BINANCE:1000FLOKIUSDT.P,BINANCE:IMXUSDT.P,BINANCE:1000PEPEUSDT.P,BINANCE:FILUSDT.P,BINANCE:INJUSDT.P,BINANCE:ARBUSDT.P,BINANCE:ATOMUSDT.P,BINANCE:THETAUSDT.P,BINANCE:GALAUSDT.P,BINANCE:ADAUSDT.P,BINANCE:ICPUSDT.P,BINANCE:SEIUSDT.P,BINANCE:FTMUSDT.P,BINANCE:UNIUSDT.P

How It Works

1. Data Fetching: Utilizes the ccxt library to fetch daily historical closing prices for each symbol starting from a specified date.
2. Data Processing: Calculates daily returns and handles missing data by dropping incomplete datasets.
3. Correlation Calculation: Computes the correlation coefficients between each cryptocurrency’s returns and BTC’s returns.
4. Filtering and Exporting: Filters out symbols below the correlation threshold and formats the remaining symbols into a string compatible with TradingView.

Requirements

• Python 3.x
• Libraries:
  • ccxt
  • pandas
  • numpy

Customization

• Adjust Timeframe: Modify the since variable to change the start date for historical data.
• Change Time Intervals: Alter the timeframe parameter in the fetch_ohlcv function to use different candle intervals (e.g., '1h' for hourly data).
• Modify Symbols: Update the symbols list to include additional cryptocurrencies available on Binance USDT-M Futures.