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Articles 1 - 2 of 2
Full-Text Articles in Business
Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater
Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater
SMU Data Science Review
The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide best …
Project Insight: A Granular Approach To Enterprise Cybersecurity, Sunna Quazi, Adam Baca, Sam Darsche
Project Insight: A Granular Approach To Enterprise Cybersecurity, Sunna Quazi, Adam Baca, Sam Darsche
SMU Data Science Review
In this paper, we disambiguate risky activity corporate users are propagating with their software in real time by creating an enterprise security visualization solution for system administrators. The current problem in this domain is the lag in cyber intelligence that inhibits preventative security measure execution. This is partially due to the overemphasis of network activity, which is a nonfinite dataset and is difficult to comprehensively ingest with analytics. We address these concerns by elaborating on the beta of a software called "Insight" created by Felix Security. The overall solution leverages endpoint data along with preexisting whitelist/blacklist designations to unambiguously communicate …