Market indicators and analysis💹
This was a simple personal project to learn crypto market behaviors and indicators, and to explore correlations in the data. I used the GDAX API (Coinbase) to gather historical data on Ethereum, produced Bollinger bands and moving averages, and searched for large price changes in the data. I then examined correlations in time-series data points immediately before a spike in price change. I predicted price movements using an RBF kernel within a Support Vector Machine.
Python libraries: alpha_vantage, gdax, tzlocal, csv, json, sklearn, pandas, os, numpy, matplotlib.