Last Update: February, 2019
1. Course Objective
Learn Advanced Trading Analysis main topics using R statistical software® in this practical course for expert knowledge level. Feel free to take a look at Course Curriculum.
2. Skills Learned
At the end of this course you will know how to:
- Implement trend-following trading strategies (simple moving averages, moving averages convergence/divergence MACD) and mean-reversion trading strategies (Bollinger bands®, relative strength index RSI, statistical arbitrage z-score).
- Maximize historical risk adjusted performance (strategy parameters optimization).
- Evaluate simulated strategy optimization trials historical risk adjusted performance (annualized return, standard deviation, and Sharpe ratio).
- Reduce strategy parameters optimization back-testing over-fitting or data snooping (multiple hypothesis testing adjustment, individual time series bootstrap hypothesis testing multiple comparison adjustment).
- Estimate strategy optimization trials population mean statistical inference test multiple probability values and adjust them for multiple hypothesis testing (family-wise error rate/Bonferroni procedure, false discovery rate/Benjamini-Hochberg procedure).
- Simulate individual strategy optimization trial bootstrap population mean probability distribution (random fixed block re-sampling with replacement), approximate bootstrap population mean statistical inference test percentile probability value and correct it for multiple comparison (family-wise error rate adjustment).
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 advanced quantitative finance.
- Experienced investor who desires to research advanced quantitative trading strategies.
- This course is NOT about “get rich quick” trading systems or magic formulas.