A multivariate model for the prediction of stock returns in an emerging market: A comparison of parametric and non-parametric models

Bonga-Bonga, Lumengo and Mwamba, Muteba (2015): A multivariate model for the prediction of stock returns in an emerging market: A comparison of parametric and non-parametric models.

Abstract

This paper compares the forecasting performance of three structural econometric models, namely the non-parametric, ARIMAX and the Kalman filter models, in predicting stock returns in an emerging market economy using South Africa as case study. The proposed models have different functional forms. Each of the functional forms accounts for specific characteristics and properties of stock returns in general and in a small open economy in particular. The findings of the paper indicate the importance of the US stock returns in predicting stock returns in an emerging market economy. Moreover, the results of the Diebold-Mariano statistics show that the Kalman filter and ARIMAX model both outperform the non-parametric model indicating the dominant characteristics of nonlinearity and Markov properties of stock market returns in South Africa.

• Item Type: MPRA Paper
• Language: English
• Keywords: stock returns, emerging markets, ARIMAX, Kalman-filter, Non-parametric
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric 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; G - Financial Economics > G1 - General Financial Markets; G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation

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