Gecko

Analyze daily prices and 3, 7, 14, 30, 50, 90, and 200-day simple moving averages

For $BTC, $ETH, $KAVA, $XMR, $ATOM, and $DAI

Data provided by the CoinGecko API using the PyCoinGecko library

1. Create environment and install dependencies

   • python3 -m venv geckoEnv

   • source geckoEnv/bin/activate

   • pip install -r req.txt

2. Run main.sh

   • Executes fetchGecko.py && movingAvgs.py

3. Visualize data with a PyQt5 GUI using matplotlib with plot.py

   • Select a date range to analyze

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   • Use the simple GUI to choose which pair you want to view

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   • Try to recognize trends between price and various moving averages

   • Moving the mouse around the chart show's different dates / prices

   • The dates on the X-axis clearly need work

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Work in Progress 0: analyzing correlation coefficients

Create and analyze correlation coefficient data with fetchCC.py, readCC.py, and plotCC.py

Work in Progress 1: analyzing simple moving avg data

The algo.py script finds the difference between the various moving averages.

Hopefully these numbers can be used to find actionable intelligence.

More to come!