• Category: Research Paper
• Publisher: Twin Cities ACM Chapter, Minnesota State IT Center of Excellence, Minnesota State University Mankato, and Metropolitan State University
• Conference: CADSCOM2021
• Full Text: Google Scholar

Abstract: Stock market is suggested and regarded as one of the high-yielding long-term investments, yet a majority of people don’t capitalize on the same. Dubious advice and attempts to ‘beat the market’ usually give rise to skepticism and distrust among first-time investors. This paper proposes a subjective, low-risk stock market advising platform that leverages Machine Learning clustering (K-Means) on basic Financial Indicators that are used to track the performance of stocks in the exchange to serve as an aid in investment decision, particularly for first-time investors. The results suggest that clusteringpowered subjective recommendations can prove to be a low-risk advising tool.