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
References
Afanador, C. A. y Espinoza, C. D. (2013). PCA: una nueva técnica de investigación de operaciones (Tesis de licenciatura no publicada). Lagos de Moreno, Jalisco, México: Universidad de Guadalajara.
Bouchaud, J. P. y Potters, M. (2003). Theory of financial risk and derivate pricing: from statiscal physics to risk management, Cambridge, Inglaterra: Cambridge University Press.
Cuadras, M. (2014). Nuevos métodos de análisis multivariante. Barcelona, España: CMC Editions.
Diaz, J. G.; Vermunt, J. K. y Ramos, S. (2015). Clustering financial time series: new insights from an extended hidden Markov model. European Journal of Operational Research. 104(3), 382-399.
Elton, E.; Gruber, M.; Brown, S. y Goetzmann, W. (2009). Modern portfolio theory and investment analysis, United States of America: Hamilton printing Company.
Engle, R. (2002). Dynamic condicional correlation: a simple class of multivariate generalized autoregressive condicional heterocedasticity models. Journal of Bussines and Economic Statistics, 20(339-350).
García, A. (2007). Sistema financiero mexicano mercado de derivados. Boca del Río, México.
Hernández, O. (1998). Temas de análisis estadístico multivariado. Costa Rica: Comisión editorial de la Universidad de Costa Rica.
Lind, D.; Wathen, S. y Marchal, W. (2012). Estadística aplicada a los negocios y la economía. México: Mc Graw Hill.
Mantegna, R. N. y Stanley, H. E. (2000). An introduction to econophysics Correlations and Complexity in Finance. Cambridge, Inglaterra: Cambridge University Press.
Martínez-Espinoza, J. C.; González-Solis, J. L.; Frausto-Reyes, C.; Miranda-Beltrán, M. L.; Soria-Fregoso, C.; Medina-Valtierra, J. y Sánchez-Gómez, R. (2008). Raman Spectroscopy: A new Proposal for the Detection of Leukimia Using Blood Samples. AIP Proceedings, 1032,(252).
Mellado, C. y Escobari, D. (2014). Virtual Integration of Financial Markets. A Dynamic Correlation of the Latin American Integrated Market. MPRA, 5(55).
Nica, E. A, (2011). Analysis of alocation of financial resources mangement in health systems in OECD member countries using cluster analysis. Metalurgia International, 16(12), 91-95.
Pena, J. A., Sánchez, J. M. (2007). Disparidades económicas intrarregionales a escala municipal. Evidencia empírica para el caso Gallego. Revista de Estudios Regionales, 81, 15-43.
Pla, L., (1986). Análisis multivariado: método de componentes principales. Washington, DC: Secretaría General de la Organización de los Estados Americanos.
Quiroga, C. A. y Limon, M. U. (2011). Estudio de la correlación entre las diferentes bolsas financieras en el mundo, usando el análisis multivariado (PCA y LDA) (tesis de licenciatura). Lagos de Moreno, Jalisco, México: Universidad de Guadalajara.
Restrepo, M.; Posada, S. y Noguera, R. (2012). Aplication of the principal-component analysis in the evaluation of three grass varieties. Revista Colombiana de Ciencias Pecuarias, (25), 258-266.
Rueda, A. (2005). Para entender la bolsa: financiamiento e inversión en el mercado de valores, México DF, México: Thomson.
Smith, L. F. (1997). Un principiante en Wall Street: Manual para el inversionista no experimentado. México DF, México: SICCO.
Tatham, R.; Anderson, R. y Black, B. (2006). Multivariate Data Analysis, United States of America: Pearson Education.
Unceta, K.; Gutiérrez-Goiria, J. y Goitisolo, L. (2014). Evidencias e interrogantes sobre desarrollo, financiación externa y AOD: un análisis de componentes principales. Revista de Economía Mundial, (36), 153-178.
Downloads
