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We Can Use Machine Learning to Determine Which Financial Ratios are Best for Investors

Collin Butterfield
2020

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https://web.archive.org/web/20220120081929/https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=2488&context=gradreports

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This study develops and tests the hypothesis that the machine learning algorithm, Random Forests, can be used to systematically pick financial ratios that would be best for indicating market trends and be used subsequently to perform comparable analysis to speculate whether a firm is over- or under-valued. Results show that financial ratio selection differs depending on the market sector to which a firm pertains. We examine the 11 financial sectors representing the key areas of the economy. We
more » ... lso look at four possible trading strategies that an investor could have: month-long, quarter-long, semi-annual, and annual to capture differing trading horizons.
doi:10.26076/f2b2-a6f7 fatcat:l3yvfrss25fgzmins5obsixpha
Citation

Collin Butterfield. "We Can Use Machine Learning to Determine Which Financial Ratios are Best for Investors." (2020)