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Using Gleaned Computing Power to Forecast Emerging-market Equity Returns with Machine Learning

Ren, Xida
Abstract
This paper examines developing machine learning and statistic models to build forecast models for equity returns in an emergent market, with an emphasis on computing. Distributed systems were pared with random search and Bayesian optimization to find good hyperparameters for neural networks. No significant results were found.
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2019-04-01
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Undergraduate Honors Theses
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merged_xrthesis.pdf
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Liu, Zhenming
Lewis, Robert Michael
Ren, Bin
Frazier, Tyler
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Computer Science
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https://scholarworks.wm.edu/handle/internal/10685
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