Testing the Non-Parametric Conditional CAPM in the Brazilian Stock Market

Authors

  • Daniel Reed Bergmann Universidade Nove de Julho - Uninove
  • Marcela Monteiro Galeno Universidade de São Paulo
  • José Roberto Securato Universidade de São Paulo
  • José Roberto Ferreira Savoia Universidade de São Paulo

DOI:

https://doi.org/10.5007/2175-8077.2014v16n38p213

Abstract

This paper seeks to analyze if the variations of returns and systematic risks from Brazilian portfolios could be explained by the nonparametric conditional Capital Asset Pricing Model (CAPM) by Wang (2002). There are four informational variables available to the investors: (i) the Brazilian industrial production level; (ii) the broad money supply M4; (iii) the inflation represented by the Índice de Preços ao Consumidor Amplo (IPCA); and (iv) the real-dollar exchange rate, obtained by PTAX dollar quotation.This study comprised the shares listed in the BOVESPA throughout January 2002 to December 2009. The test methodology developed by Wang (2002) and retorted to the Mexican context by Castillo-Spíndola (2006) was used. The observed results indicate that the nonparametric conditional model is relevant in explaining the portfolios’ returns of the sample considered for two among the four tested variables, M4 and PTAX dollar at 5% level of significance.

Author Biographies

Daniel Reed Bergmann, Universidade Nove de Julho - Uninove

Professor Doutor do Mestrado Profissional em Gestão de Projetos da UNINOVE

Marcela Monteiro Galeno, Universidade de São Paulo

Mestre em Administração pela FEA-USP

José Roberto Securato, Universidade de São Paulo

Professor Titular em Finanças do Departamento de Administração da FEA-USP

José Roberto Ferreira Savoia, Universidade de São Paulo

Professor Doutor em Finanças do Departamento de Administração da FEA-USP

Published

2014-04-14

How to Cite

Bergmann, D. R., Galeno, M. M., Securato, J. R., & Savoia, J. R. F. (2014). Testing the Non-Parametric Conditional CAPM in the Brazilian Stock Market. Journal of Administration Science, 16(38), 213–227. https://doi.org/10.5007/2175-8077.2014v16n38p213

Issue

Section

Articles