Asset Representativeness in Mexican Stock Market Sectors: A Principal Component Analysis (2020–2024)

Abstract

Our work examines the Mexican capital market with the objective of identifying the key assets within each sector. This is accomplished through a principal component analysis (PCA) applied to time series data. The findings elucidate the assets that predominantly contribute to each sector concerning overall variability and illustrate the associations among them according to their correlation vectors. Ultimately, the linear combinations of each sector, referred to as the principal components, are provided, which serve as indicators of their cyclical behavior. These combinations can be utilized as measures of sector dynamism within the market and, in conjunction with other technical analysis tools, may prove valuable as trading signals and for constructing investment portfolios. These insights will be extended for future research applications.