Time: 11AM HKT
Date: 24 January 2017

Title of the webinar:
“Developing Trading Models Using Machine Learning on Financial News and Social Media Data”

Abstract of the webinar

In this webinar, Dr. Peterson introduces nonlinear techniques for predictive modeling on financial time series data including random forests, decision trees, neural networks, and boosting.  Such techniques identify significant value in nonlinear data sources such as media sentiment data.  Attendees will learn about sentiment data dynamics, simple machine learning techniques, toolkits for implementation of ML, and common pitfalls in such approaches.  The live trading track record of Dr. Peterson’s firm will be presented as evidence of the value (and the vulnerabilities) of such ML approaches.

Speaker Profile: Richard Peterson is CEO of MarketPsych Data which produces psychological and macroeconomic data derived from text analytics of news and social media. MarketPsych’s data is consumed by the world’s largest hedge funds. Dr. Peterson is an award-winning financial writer, an associate editor of the Journal of Behavioral Finance, has published widely in academia, and performed postdoctoral neuroeconomics research at Stanford University.

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