Learning the basics of using bank's .csv data to start understanding the building blocks of creating automated trading strategies with Python, NumPy, Pandas, and Matplotlib. I looked at adjusted closing price info from JP Morgan, CITI, Bank of America, Bank of Canada, and HSBC. Capstone 1 looked at the average returns and utilized Matplotlib to visualize comparison histograms as well as calculate sharpe ratios. Capstone 2 plotted historical daily volume of trades which allowed for macro analysis of what could cause the bigger trading volume spikes. Capstone 3 explored classic momentum strategies such as Bollinger Bands. This was part of the capstone project for the algorithmic trading with python and quantconnect course on udemy.