Do algorithmic trading impact the quality of the United States financial market? - Verant, Maxence Emilien Valere (2024)
This paper aims to examine the effects of algorithmic trading on the market quality in the US market. Over the past decades, the introduction to sophisticated and complex algorithms into the financial sector has seduced many institutions and traders. Indeed, they are willing to pay large amount of money in research and development in order to improve their decision making of just some milliseconds. However, the rise of these new technologic tools came with some interrogations about its impact on the market quality. Many studies have been done all over the world without clearly agreeing on whether it was beneficial for the market or no. This study use aggregates values of 20 NYSE listed stocks to create a set of proxies for algorithmic trading such as the cancel-to-trade ratio, odd-lot volume ratio and trade-to-order volume ratio and analyse their relationships to another set of proxies representing the different measures of market quality (Liquidity, volatility, and price discovery). The analysis is made through a panel data regression and the findings concluded that AT proxies had a positive impact on the liquidity except for the Odd-lot volume ratio that was insignificant. The volatility in the opposite way is worsened and increased by the algorithmic trading activity. Finally, the results admit a strong positive relationship between odd-lot volume ratio and price discovery process and a strong inversely related correlation between trade-to-order volume ratio (negatively related to algorithmic trading activity) as AT proxy and the price discovery meaning that price efficiency was improved due to AT. This study draws the inference that algorithmic trading is beneficial for the market quality and its participants.