MSDS 690 UC Application Development Experience Discussion

Please introduce yourself to your classmate by:

Sharing your current occupation or interests

Describe how your educational and professional background relates with the topic of the project.

Respond to the discussion promptly by commenting the following:

Why is your project topic different? Or, if the topics are the same, how is that so?

Based on that write an intro and assignment requirement asked by the professor. I worked as an application developer for 2 years, so could you write how it relates to this course and project? Please read the questions clearly and mention them only. Intro : Hi, this is Sri Chandana. I am from India. I have done my bachelor’s in India and my Master’s in Data Science from Cumberlands. I had two years of IT experience back in my home country. I worked on a tool called ServiceNow as a developer and used i to implement applications, forms, and pages. Currently, I am living in Jersey City, New Jersey.

Project 2: Structured Probabilistic Models for hierarchical clustering of
individual stocks or market indices
Motivation:
Graphs as a set of nodes and a set of edges between those nodes describe and explain many
real-life systems, such as social networks, financial systems, and communication networks.
Paper purpose:
Use hierarchical clustering techniques to cluster individual stock or market index.
Good methodologies to build a graph and algorithm for clustering:
Consider a graph G = (V, E), consisting of nodes V and edges E. In a correlation-based graph,
individual stock or market index is considered as a node. Pearson’s’ correlation coefficients
between returns represent the edges. Consider the close price for different sampling periods
when calculating returns and correlation coefficients. Use appropriate threshold of coefficients so
the edges are -1 and 1.
Possible additional outcomes:
Through time edges change and can be weighted, so the patterns of the weight values might
emerge.
Starting help resources:
Saha, Gao, J., & Gerlach, R. (2022). A survey of the application of graph-based approaches in
stock market analysis and prediction. International Journal of Data Science and Analytics, 14(1),
1–15.
https://www.nasdaq.com/market-activity/stocks/screener? exchange (for data sources)
Keywords:
Stock market, graph filtering, graph clustering, portfolio optimization, stock movement
prediction.