Disciplines

Business | Computer Sciences | Mathematics | Statistics and Probability

Abstract (300 words maximum)

The stock market provides an abundant source of data. However, when the amount of raw data becomes overwhelming it grows increasingly difficult to know how the stocks interact with each other. Stock data visualization as a market graph serves as one of the most popular way of summarizing important information. When modelling the data as a graph, vertices correspond to stocks and edges correspond to strong correlation in their pricing in a certain period of time. This project presents a technique to find stocks that behave very similarly. Such information helps investors make decisions on which stocks to purchase next. The investors can utilize this information to select a valuable portfolio of stocks showing an increasing price trend. On the other hand, it can also help stock owners to make decisions on whether or not they should sell their stocks.

Academic department under which the project should be listed

CCSE - Data Science and Analytics

Primary Investigator (PI) Name

Dr. Joseph DeMaio

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Finding similar stocks by detecting cliques in market graphs

The stock market provides an abundant source of data. However, when the amount of raw data becomes overwhelming it grows increasingly difficult to know how the stocks interact with each other. Stock data visualization as a market graph serves as one of the most popular way of summarizing important information. When modelling the data as a graph, vertices correspond to stocks and edges correspond to strong correlation in their pricing in a certain period of time. This project presents a technique to find stocks that behave very similarly. Such information helps investors make decisions on which stocks to purchase next. The investors can utilize this information to select a valuable portfolio of stocks showing an increasing price trend. On the other hand, it can also help stock owners to make decisions on whether or not they should sell their stocks.