Applying unsupervised learning using K-means clustering.
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Updated
Sep 10, 2017 - R
Applying unsupervised learning using K-means clustering.
An algorithmic approach to predicting US Sector ETF price movement using machine learning techniques. The goal was to create an asset allocation framwrok using ETFs as proxies for secotr behavior, and to test different clustering and predictive models to accomplish this goal using the R programming language.
This repo contains all the necessary data and code files needed to reproduce the results and figures reported in our project: Comparing the Hierarchical Risk Parity Algorithm and Mean Variance Portfolio Selection. Refer to README.md for full project and files description.
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