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(Re-)Imag(ine)ing Price Trends
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(Re-)Imag(ine)ing Price Trends

 Export to Your Calendar 9/24/2020
When: Thursday, September 24, 2020
4:00 - 5:00 PM EDT
Where: Zoom.com (link to be distributed prior to the Seminar)
Contact: Rebecca Harrington
518-694-3157


Online registration is available until: 9/24/2020
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 “(Re-)Imag(ine)ing Price Trends.” 

 

Tired of using the same indicators and factors for your technical and quantitative analysis? We will show a new way to discover money making patterns in good old price charts, using computer vision! No prior assumptions about what kind of patterns to look for. We start with a clean slate and let the algorithm do the discovery work, which has seen tremendous success in so many other industries. It’s time to learn a thing or two about how computer vision can help you in your investment!

 

We reconsider the idea of trend-based predictability using methods that flexibly learn price patterns that are most predictive of future returns, rather than testing hypothesized or pre-specified patterns (e.g., momentum and reversal).  Our raw predictor data are images---stock-level price charts---from which we elicit the price patterns that predict returns using computer vision techniques.  The predictive patterns we identify are largely distinct from trend signals commonly analyzed in the literature, give more accurate return predictions, and translate into more profitable investment strategies. They also appear context-independent: patterns learned from US stocks predict equally well in international markets.

 

Speaker information and bio:

 

Dacheng Xiu, University of Chicago Booth School of Business

 

 

Dacheng Xiu is Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. His current research focuses on developing machine learning solutions to big-data problems in empirical finance. Xiu’s work has appeared in the Journal of Finance, Review of Financial Studies, Econometrica, the Journal of the American Statistical Association, the Annals of Statistics, etc. He is a Co-Editor for the Journal of Financial Econometrics, an Associate Editor for the Journal of Econometrics, the Journal of Business & Economic Statistics, Management Science, etc. He has received several recognitions for his research, including the Fellow of the Society for Financial Econometrics, Fellow of the Journal of Econometrics, the AQR Insight Award, the Swiss Finance Institute Outstanding Paper Award, etc. Xiu earned his PhD and MA in applied mathematics from Princeton University.

 

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