TESTING FOR MARKET ANOMALIES IN DIFFERENT SECTORS OF THE JOHANNESBURG STOCK EXCHANGE

Abstract

This study compared the performance of different asset-pricing models and their ability to account for market anomalies in different sectors of the Johannesburg Stock Exchange (JSE). The total sample size of the study consisted of 156 companies categorised into six different sectors namely, resources, consumer goods, consumer services, financial, industrial and others. Various asset-pricing models such as the Capital Asset pricing Model (CAPM), the Fama and French three-factor model and the Carhart four-factor model were used to analyse monthly data from January 2002 to December 2014. Variables used include the monthly stock return for each company and different market anomalies namely, size, value, January and momentum effects. The study revealed that whenever the asset-pricing models were not restricted, they tend to capture the market anomalies in four out of the six sectors. In contrast, when the models are restricted, they only seem to capture the anomalies in one of the six examined sectors. Thus, market anomalies are sensitive to model specifications, as restricting the models tends to reduce the likelihood of finding the presence of the market anomalies across the sectors. Our findings also show that market anomalies tend to differ across sectors and some sectors seem to be more efficient than others.

Keywords

• Asset pricing model, efficient market hypothesis, market anomalies, expected return, JSE