The impact of algorithmic trading on market quality: Evidence from the Johannesburg Stock Exchange

ABSTRACT

High-frequency trading (HFT) is a trading method that relies on sophisticated algorithms to analyse markets and execute large numbers of orders within milliseconds. In the last two decades, this new technology has gained traction globally and now accounts for the majority of the trading volume on the Johannesburg Stock Exchange (JSE). Despite the dominance of HFT, studies on the topic have been scarce outside of the United States. This study seeks to examine the effects of HFT on market quality in a South African context. First, the study makes use of a set of proxies for algorithmic trading (AT), namely average trade size, odd-lot volume ratio and trade-to-order volume ratio. Second, panel regressions are used to determine the relationship between these proxies and two measures of market quality (market liquidity and short-term volatility). The study found a strong positive relationship between market liquidity and average trade size but an inverse relationship with the other two AT proxies. Finally, the study confirmed a strong positive relationship with short-term volatility. The study concludes that, overall, AT has a positive impact on market quality, despite carrying the risk of causing instability in certain markets.

KEYWORDS:

• Algorithmic trading
• market liquidity
• short-term volatility
• high frequency trading
• panel data

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Correction

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been corrected with a minor change. This change does not impact the academic content of the article. Please see correction (10.1080/10293523.2022.2131136).