The predictability of asset returns in the BRICS countries: a nonparametric approach

Muteba Mwamba, John Weirstrass and Webb, Daniel (2014): The predictability of asset returns in the BRICS countries: a nonparametric approach.

Abstract

One of the earliest and most enduring questions of financial econometrics is the predictability of financial asset prices. In this article, stock market data from Brazil, Russia, India, China and South Africa are used to assess the out-of-sample performance of the ARMA(1,1)-GARCH(1,1) and Non-parametric kernel (Epanechnikov) regression models. The results reveal that the non-parametric kernel regression model outperforms its parametric rival based on the predicted mean square error (PMSE), Diebold-Mariano criterion, Mean-Absolute Deviation (MAD) and Variance statistics. These results confirm those found previously by other researchers whereby non-parametric forecasting models outperform parametric models in the short-term forecasting horizon.

• Item Type: MPRA Paper
• Language: English
• Keywords: kernel regression, forecasting, non-parametric, BRICS markets
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; F - International Economics > F3 - International Finance > F37 - International Finance Forecasting and Simulation: Models and Applications

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