Hands-on coding session with real market data
8:00 PM - 10:00 PM HKT, 8:00 AM - 10:00 AM EST
Why should you attend this webinar?
This online session is a hands-on learning tutorial, where you will work directly on a Jupyter Notebook to create a classification tree model. The predictor variables are technical indicators which predict the market trends. We will understand the intuition behind each of these indicators and how to use them. The target variable is a one-day future trend. The classification tree we create will help us build trading rules for when the future return is expected to be positive or negative. We will work on the US equities markets data to create the necessary trading indicators.
Speaker Profile
Mr. Varun Divakar, AI Expert & Faculty at QuantInsti
Varun heads the Quantra Research & Development team at QuantInsti. His team is responsible for creating quality content related to trading strategies using Quantitative & Machine Learning techniques. He has worked as the Algorithmic Trading Consultant for a New York-based firm and as a successful commodities trader with Futures First. He has over 12 years of experience in financial markets both as a manual and quant trader.
Who should attend it?
Traders, Quants, AI enthusiasts, Students, Academicians and anyone who loves problem-solving and working with data. We do not expect our audience to have a formal background in computer science, although some familiarity with programming would be nice to have. The concepts and ideas here are covered with several examples to help connect theory to practice.
