This study investigates the relationship between algorithmic trading and a change in market structure. Furthermore, the study aims to determine if there is a relationship between algorithmic trading and the liquidity of the JSE. The level of algorithmic trading is measured through an algorithmic trading proxy based on current academic theory. The results illustrate that there is a strong statistical relationship between the AT proxy and a change in market structure. The relationship between algorithmic trading and the liquidity of JSE is measured via four specific low-frequency measures: the stock turnover ratio, the proportional bid ask spread, the price impact ratio, and the zero return measure. Each liquidity measure is able to quantify a specific component of liquidity. Each liquidity measure was regressed against the algorithmic trading proxy. The results attained were mixed, with only two of the four measures producing statistically significant relationships. The results seem to indicate that the increase in algorithmic activity has resulted in a reduction of the price impact effect; however, a parallel increase in volatility was observed. An increase in the zero return measure was observed, which indicates that AT increases the efficiency of trading by reducing trading costs, and gathering information at a faster rate. The findings of this study may indicate that liquidity has improved, but has done so with a repercussion of an increase in volatility. Certain regulatory policy adjustments may be required to curb volatility while maintaining the heightened level of liquidity. / Dissertation (MBA)--University of Pretoria, 2013. / zkgibs2014 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted