How Do Algorithmic Trading Strategies Affect Price Discovery and Volatility in Emerging Market Equity Markets?

Due to technological advancements and the need for prompt execution, algorithmic trading is gaining importance, thereby changing the way stocks are traded. Although research on algorithmic trading was conducted primarily in developed equity markets, there is growing interest in understanding how algorithmic trading may affect the efficiency and stability of emerging equity markets. Emerging equity markets exhibit varying levels of liquidity and market depth, as well as distinct institutional structures. Consequently, the introduction of algorithmic trading has raised concerns about its impact on these markets. The purpose of this study is to understand how algorithmic trading, as a trading strategy, affects price discovery and price volatility in the equity markets of emerging market nations. This study specifically addresses the question of whether or not algorithmic trading increases the speed and accuracy with which financial information is incorporated into a stock’s price and whether it may contribute to an increase in short-term volatility. The qualitative methodology employed in this study includes the review of existing literature related to this issue, reviewing existing academic studies about the operation of equity markets, and reviewing institutional reports related to the changing patterns of trading activity in emerging markets. Results from the above-referenced methods reveal that algorithmic trading has the potential to improve both speed and accuracy.