STATS242 -
Algorithmic Trading and Quantitative Strategies
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Overview
This introduction to financial trading strategies will focus on stock and equity markets as well as the use of statistical arbitrage methods. Particular emphasis will be on developing, automating and evaluating models that reflect market and behavioral patterns. This course will balance between learning and practicing theory for practical application to realistic trading and strategy problems.
Instructors
- Raja Velu Visiting Professor, Statistics
Topics Include
- Methodologies related to high frequency data and stylized facts on asset returns
- Dynamic trade planning with feedback
- Momentum strategies
- Pairs trading.
Grading
- Homework
- Final Project
Units
3.0
Prerequisites
STATS240P or equivalent
Other
Tuition & Fees
For course tuition, reduced tuition (SCPD member companies and United States Armed forces), and fees, please click Tuition & Fees.
Raja Velu is a Visiting Professor in the Statistics department at Stanford. His research interests in statistics include multivariate methods, longitudinal and time series modeling, and exploratory data analysis. He is currently interested in applied areas such as scanner data modeling in marketing research, analysis of high frequency data in finance, and outcome research in health sciences. He is also involved in training and consulting for leading companies such as Saks Fifth Avenue and Time, Inc. Velu received his Ph.D. in business statistics from University of Wisconsin-Madison.