Python for Financial Analysis and Algorithmic Trading

What you'll learn

• Use NumPy to quickly work with Numerical Data
• Use Matplotlib to create custom plots
• Calculate Financial Statistics, such as Daily Returns, Cumulative Returns, Volatility, etc..
• Use ARIMA models on Time Series Data
• Optimize Portfolio Allocations
• Learn about the Efficient Market Hypothesis
• Use Pandas for Analyze and Visualize Data
• Learn how to use statsmodels for Time Series Analysis
• Use Exponentially Weighted Moving Averages
• Calculate the Sharpe Ratio
• Understand the Capital Asset Pricing Model
• Conduct algorithmic Trading on Quantopian