Last Update: September, 2018
1. Course Objective
Learn Quantitative Trading 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:
- Implement trading strategies (technical indicators, trading signals and rules).
- Explore trend-following strategy category (simple moving averages, moving averages convergence/divergence MACD) and mean-reversion strategy category (Bollinger bands®, relative strength index RSI, statistical arbitrage z-score).
- Evaluate simulated strategy historical risk adjusted performance (trading statistics, performance metrics).
- Calculate main trading statistics (net trading profit and loss, maximum drawdown, equity curve).
- Measure principal strategy performance metrics (annualized return, standard deviation, and Sharpe ratio).
- Maximize historical risk adjusted performance (strategy parameters optimization).
- Reduce strategy parameters optimization back-testing over-fitting or data snooping (training/testing subsets delimiting).
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 quantitative trading strategies.
- This course is NOT about “get rich quick” trading systems or magic formulas.