About sessions
In this comprehensive session, we will explore scenarios where machine learning can be seamlessly integrated into momentum trading practices. We take a closer look at different types of momentum trading strategies, understand the need and effectiveness of machine learning in this field, and explore practical applications. Learn the implementation of ML-based classifiers and clustering algorithms with practical examples to unlock the vast potential of machine learning in momentum trading.
overview
- Types of momentum trading approaches
- Consideration of traditional time-series momentum trading approaches and advanced time-series momentum trading approaches
- The need for ML in momentum trading
- Implementing machine learning to trade time series momentum
- Improving ML models used for momentum trading
- Risk management using ML
- Traditional cross-sectional momentum trading approach
- Implement machine learning to trade cross-sectional momentum
- Interactive Q&A
Prerequisites
- Basic understanding of trading terminology.
- Basic knowledge of machine learning concepts.
Who should attend?
Traders, financial analysts, quantitative analysts, algorithmic traders, financial engineers, students, researchers, and anyone interested in financial markets.
About the speaker
Varun Kumar Pothula (QuantInsti Quantitative Analyst)
Varun holds a master’s degree in financial engineering. He has experience working as a trader, global macro analyst, and algo trading strategist. He is currently working as a Quantitative Analyst in the QuantInsti Content & Research team, contributing to the creation of services for learners in the field of algorithms and quantitative trading.
This event will be held on the following dates:
Tuesday, April 16, 2024
9:30 AM EST | 7 PM IST | 9:30 PM SGT