Machine Learning High-Frequency Time Series with Brian Peterson of DV Trading
Details
Join us for a spirited conversation on Applied Machine Learning for Time Series with Brian Peterson, Head Trader and Partner at DV Trading (https://www.dvtrading.co/). We thank Raise and Ray Buhr for providing Pizza, Beer, and an excellent venue for this talk! Raise uses R extensively for Data Science and Analytics.
Talk begins at 6:00 PM.
As the author or co-author of over 10 popular R packages in Finance, if you’ve used R for Finance, it’s likely you’ve used Brian’s functions! In addition to his leadership at DV Trading, he is also a Senior Lecturer at the University of Washington’s Computational Finance and Risk Management department (http://depts.washington.edu/compfin/), and admin for R’s participation (https://github.com/rstats-gsoc) in the Google Summer of Code (https://summerofcode.withgoogle.com/)program.
Brian will discuss Machine Learning, high-frequency time series, relevant R packages, and the crucial question of how to evaluate model over-fit in this context. In addition to a concrete presentation of the entire ML pipeline, he will transition into a Case Study on high-frequency trading, making features useful, and back test evaluation. The Case study will be related to a paper he co-authored: Bayesian Hierarchical Hidden Markov Models applied to financial time series (Damiano, Peterson, and Weylandt 2017).
Bring your intellect and questions to this excellent talk, it promises to be an exciting one!