An empirical study of price clustering on the Nairobi securities exchange

Abstract

Price clustering is a phenomenon where some prices are observed more frequently than others. Several hypotheses have been put forth to explain this phenomenon. This study therefore set to empirically investigate price clustering phenomenon on the Nairobi Securities Exchange for the period 2009 to 2013. The study used secondary sources of data obtained from the Nairobi Securities Exchange and revealed that there is a preference by investors for stock whose prices end with the digit 5 which accounted for 67.88 percent of all the stocks examined. This was followed by stocks whose prices ended with the digit 0 which accounted for 4.55 percent. In order to establish the determinants of this observed behaviour, a multivariate regression model was adopted where price clustering was regressed against stock volatility, number of trades, market capitalization, and own stock price. The regression results indicated that the number of trades and market capitalization were positive and significantly related to price clustering. Stock price was found to be negative and significantly related to price clustering. On the other hand, stock volatility was established to be an insignificant predictor of price clustering. The multivariate regression model was found to be significant in explaining the observed relationship and that 15.4 percent of the variance in price clustering was explained by the number of trades, stock volatility, own stock price and the market capitalization