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

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 on the significance of data engineering and feature engineering for trading is the focus of the course “Data & Feature Engineering for Trading.” These techniques are applicable to both individual and institutional trading scenarios. To make financial datasets suitable for analysis, preprocessing steps are required. Extracting features from these datasets and defining the target variable for a specific machine learning problem contribute to enhancing the predictive capabilities of your algorithm.

Could you provide information about Ermest P. Chan and Roger Hunter?

Founding the company, Dr. Ernest P. Chan has been dedicated to developing statistical models and advanced computer algorithms since 1994. These efforts aim to detect patterns and trends within extensive data sets. His expertise in machine learning has been enlisted by entities such as 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. Additionally, he is the initiator and managing member of QTS Capital Management, LLC, a firm specializing in quantitative investment management.

As the scientific advisor for PredictNow.ai, Dr. Roger Hunter possesses extensive expertise in creating high-performance automated execution systems and machine learning software. He previously founded and managed a highly profitable equity fund. He also founded and served as CEO of a scientific software company acquired by Thomson Reuters, with their software now in use by the Federal Reserve. Formerly a mathematics professor at New Mexico State University, Roger earned his Ph.D. in mathematics from the Australian National University. A profile of Roger was featured in Bloomberg Businessweek.

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