Classifying Trading Signals using Machine Learning and Deep Learning
Overview
In this webinar, we will show how to apply machine learning and deep learning algorithms to classify trading signals into “buy” or “sell”. Using the stock index data, we will show how to create simple workflows for training machine learning and deep learning models. Based on the trained models, we will perform backtesting on in-sample and out-of-sample data.
Highlights
- Data preprocessing, factor creation, and data partitioning
- Rule-based trading
- Classifying trading signals using Classification Learner App
- Classifying trading signals using LSTM (deep learning algorithm)
About the Presenter
Kawee Numpacharoen is a computational finance product manager at MathWorks. Prior to joining MathWorks, Kawee worked at Phatra Securities as a senior vice president in Equity and Derivatives Trading department. Kawee earned a B.S. in Electrical Engineering from King Mongkut’s Institute of Technology Ladkrabang, M.S. in Financial Engineering from University of Michigan, Ann Arbor, and a Ph.D. in Mathematics from Mahidol University.
Recorded: 19 Apr 2018
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