Author(s) :

Rohan Jha, Rishabh Jha.

Volume/Issue :

Abstract :

We analyze the Standard and Poor's 500 (S&P 500) variation with all eleven S&P sectors. There are effectively nine sectors because we combined real estate with financials, and communication with technology. We performed regression analysis and found that all sectors, except utilities, are statistically significant predictors of the S&P 500 variation, with p-values less than 0.05. However, the impact of the technology sector is lower at only ~10% because its impact is strongly correlated with other sectors except energy and financial. We subsequently used only three independent variables: the technology, energy, and financials sectors. The regression analysis revealed they are statistically significant with p-values less than 10 -10 and an R-square greater than 0.98. The technology sector covers over 50% of S&P variations, the financials sector covers ~35%, and energy comprises the remaining ~15%. These were validated by taking different frequencies such as monthly and weekly over time spans of the last 20, 15, and 8 years of data. Thus, we analyzed S&P 500 variability with key sectors like technology, financials, and energy. Due to economic, market, and technological interconnection, most sectors are related. Financials offer access to capital and energy is a significant part of the cost across sectors. The energy sector is also driven by global supply and demand dynamics, geopolitics, and OPEC (Organization of the Petroleum Exporting Countries) policies