Upcoming MATLAB and Simulink Webinars

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)

Please allow approximately 45 minutes to attend the presentation and Q&A session. We will be recording this webinar, so if you can't make it for the live broadcast, register and we will send you a link to watch it on-demand.

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.

Product Focus

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