Last Update: March, 2018
1. Course Objective
Learn Investment Portfolio Analysis main topics using Python programming language® in this practical course for all knowledge levels. Feel free to take a look at Course Curriculum.
2. Skills Learned
At the end of this course you will know how to:
- Compare main asset classes returns and risks tradeoffs (cash, bonds, stocks, commodities, real estate, currencies).
- Estimate portfolio expected returns, historical volatility and market participants implied volatility.
- Approximate portfolio expected excess returns (capital asset pricing model CAPM, Fama-French-Carhart factors model, arbitrage pricing theory APT model).
- Calculate portfolio performance metrics (Sharpe ratio, Treynor ratio, Sortino ratio, Kelly ratio).
- Optimize global portfolios assets allocation weights (Markowitz portfolio theory).
- Approximate global portfolios returns (optimized assets allocations) and compare them with benchmark global portfolios returns (equal weighted assets allocation, well-known investment managers assets allocation).
- Evaluate global portfolios performance (global risk factors model).
3. Typical Student
This course is ideal for you as:
- Undergraduate or postgraduate who wants to learn about the subject.
- Finance professional or academic researcher who wishes to deepen your knowledge in quantitative finance.
- Experienced investor who desires to research optimized asset allocation strategies.
- This course is NOT about “get rich quick” trading systems or magic formulas.