Python: Finance Analytics and Data Science (S-IT0042)

Anaconda, Python and its prerequisites
Knowledge of programming
Knowledge of basic statistics and linear algebra

Walkthrough everything you need to know to use Python for finance, financial analysis and algorithmic trading: The basics of Python, the different
base libraries used in it, Py-Finance ecosystem on Spyder as well as the libraries NumPy, Pandas, Matplotlib, Statsmodels, the Quantopian platform for Trading.

• Python's NumPy library to quickly work with numeric data.
• Python's Pandas library to analyze and visualize data.
• Python's Matplotlib library to create custom charts.
• The statsmodels module for time series analysis.
• Financial statistics such as daily returns, cumulative returns, volatility,etc.
• Exponentially Weighted Moving Averages.
• ARIMA models on time series data.
• Fundamental Finance Techniques.
• The Sharpe ratio.
• Optimizing your financial portfolio management.
• The financial asset valuation model.
• Learn more about efficient financial market assumptions.
• Perform algorithmic trading on Quantopian.