Notice: Course Sharing Network Closure!
The website (www.coursesharing.net) will be closing soon.
Please use up all your credits before "Sun, 18 Oct 2026".
Get 100% bonus credits for all packages.
detail here
Hanguk Quant – Statistical Inferencing for Quantitative Trading Strategies
Learn how to apply probability theory and statistical inference techniques to validate algorithmic trading strategies.
What you'll learn
- Learn the basics of finance and probability theory for algorithmic trading.
- Learn statistical inference techniques such as parametric and nonparametric hypothesis tests.
- Employ statistical learning techniques on quantitative trading strategies in Python.
- Learn practical validation methods quants use before taking strategies into production.
Description
Is my quant trading strategy performance statistically significant?
Are my in-sample performances statistically significant while controlling for model complexity and bias? Is my ML model an inefficiency detector or a piece of overfitting poppycock software?
If I backtest 10 strategies, pick those with Sharpe > 1, am I headed for wealth or ruin?
Statistical Inferencing for Quantitative Trading Strategies is a one-of-a-kind quantitative lecture series on applying probability theory and statistical methods to construct robust hypothesis tests for validation of trading strategies using distribution-free methods.
The course takes the student on a whirlwind tour of finance basics, statistics basics, as well as more advanced and modern techniques in statistical decision/inference theory.
Hypothesis testing concepts, Type I/II errors, powers, FWER control, and multiple testing frameworks are introduced under both parametric and non-parametric assumptions for quantitative research.
Classical location tests (t, sign, rank-sum) are discussed in addition to cutting-edge techniques using Monte-Carlo permutation methods. The lectures take you through the motivation for the need to employ rigorous scientific procedures in validating trading strategies.
In pharmaceuticals, medicine and other high-stakes industries, experimental design and implementation are key to decision-making, such as the acceptance of new chemicals in treatments. Unfortunately, hardly the same amount of scientific rigour is paid in deciding whether to take a trading strategy live. Apparently, moon cycles and lunar phases are enough! For these people, the writing is on the wall.
Hanguk Quant – Statistical Inferencing for Quantitative Trading Strategies, Statistical Inferencing for Quantitative Trading Strategies, Hanguk Quant.