Data & Feature Engineering for Trading with Ermest P.Chan & Roger Hunter

How often have you developed a profitable backtesting strategy that failed to generate profits in the real markets? A required course for developing machine learning strategies executable on trading platforms. This course focuses on the data cleansing of financial datasets using real-world examples.

  • Section 1: Introduction to the Course
  • Section 2: Challenges in Financial Data Engineering
  • Section 3: Exploratory Data Analysis in Finance
  • Section 4: Survivorship Bias for Stock Data
  • Section 5: Redundant Stocks Data
  • Section 6: Multiple Stock Classes: One or All?
  • Section 7: Outliers-How to Identify and Deal With Them?
  • Section 8: News Data-Numerical Features
  • Section 9: News Data-Categorical Features
  • Section 10: Structural Breaks in Financial Data
  • Section 11: Fundamental Data-Merge Them Correctly
  • Section 12: Look-ahead Bias-Deceptive Returns
  • Section 13: Types of Bars-Features Extraction
  • Section 14: Information Bars-Market Order Imbalances
  • Section 15: Data Labelling for Better Outcomes
  • Section 16: Why Stationary Features?
  • Section 17 (Optional): Python Installation
  • Section 18: Summary

Educating students about the importance of data engineering and feature engineering for trading encompasses both individual and institutional contexts. Preprocessing of financial datasets is necessary to render them suitable for analysis. Extracting features from these datasets and defining the target variable for a specific machine learning problem enhances the predictive capacity of your algorithm.

Who are Ermest P. Chan & Roger Hunter? The company’s founder is Dr. Ernest P. Chan. Since 1994, Ernie has been engaged in developing statistical models and advanced computer algorithms for the detection of patterns and trends within extensive data sets. His proficiency in machine learning has been put to use in various settings, including the Human Language Technologies group at IBM T.J. Watson Research Center, the Data Mining and Artificial Intelligence Group at Morgan Stanley, and the Horizon Trading Group at Credit Suisse. Furthermore, he established and manages QTS Capital Management, LLC, a quantitative investment management company.

Dr. Roger Hunter, serving as the scientific advisor for, possesses expertise in crafting high-performance automated execution systems and machine learning software. Roger founded and formerly managed a remarkably lucrative equity fund. He also founded and was formerly the CEO of a scientific software company, which was acquired by Thomson Reuters. The Federal Reserve currently employs his company’s software. Roger, a former mathematics professor at New Mexico State University, earned his Ph.D. in mathematics from the Australian National University. Bloomberg Businessweek featured a profile on Roger.