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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

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

    • Select a date range to analyze

    • plot.py screenshot 1

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

    • plot.py screenshot 2

    • 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

    • plot.py screenshot 3

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!