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
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Create environment and install dependencies
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python3 -m venv geckoEnv
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source geckoEnv/bin/activate
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pip install -r req.txt
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Run main.sh
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Visualize data with a PyQt5 GUI using matplotlib with plot.py
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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
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Moving the mouse around the chart show's different dates / prices
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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.