Analysis of stock market behavior of the major financial exchanges worldwide using multivariate analysis (principal component analysis PCA) for the period 2011 to 2014

Abstract

The objective of this research is to analyze the stock performance of 27 stock markets around the world, using Principal Components Analysis (PCA). This method allows grouping the correlated variables together, obtaining an orthogonal basis where the analysis and interpretation of data is easier. The data used was collected from the official website of Wall Street every day, at “close trading”, from 27 financial markets for the period 2011 - 2014. Then, the database was saved in excel, and after that the PCA method was applied in Matlab software. The Principal components are plotted in an orthogonal basis to represent the formation of groups based on their market performance. Among the results, the Singapore stock stands out due to its decreasing trend, while the Argentina stock protrudes for its rising trend. Both markets are distant from the container sets from other stock markets.

Keywords

• Stock Markets
• Multivariate Analysis
• PCA
• Financial Analysis