This is the final project for CS 2316 (Data Science and Manipulation). In this semester long project, students were tasked with analysing data in a field of their interest. I have chosen my project to be centered along analyzing holistic financial data within the last 20 years. Using time-series data and analysis, I hope to identify trends as well as understand how current events and other financial trends can have an effect.
Phase II
This file contains the process of collecting and manipulating the data required for my project. The data was stored in .csv for the duration of the project. However, an .xls file is provided to easily view the (manipulated) data used.
The Data Used Comes From the Following:
https://simfin.com/data/bulk
https://www.barchart.com/etfs-funds/performance/percent-change/advances?timeFrame=10y
https://data.nasdaq.com/api/v3/datasets/
Phase III
This phase involves analysis and interpretation of the data. In short, there are 5 generated "insights" and 3 "visualizations". The insights are as followed:
- Insight 1: Descriptive Statistcs of Individual and Institutional Confidence
- Insight 2: Measuring Statistical Deviations in S&P 500 Companies' Fundamentals During COVID-19
- Insight 3: Good vs. Bad Investments: What's the difference? (Correlation, Covariance, Skewness and Kurtosis)
- Insight 4: Seasonal CPI forecasting Using Schiller Index, Bill Rates, and Real Yields
- Insight 5: Basic S&P Volatility Modelling Using AutoRegressive Models