Indian Institute of Technology Madras Researchers is studying the impact of Algorithmic Traders (ATs) on the stock market. This research is the first-of-its-kind to investigate the impact of Proprietary Algorithmic Traders’ (PATs’) and Buy-side Algorithmic Traders’ (BATs)’ trading on market quality and vice versa.
This has significant welfare implications for the securities market as in Algorithmic Trading, computer programs trade faster than human traders. The Research focused on processes that happen when computer programs predict market order flow and take over the trading process.
The research on Algorithmic Traders has just started to emerge. Some of the literature that favors ATs suggests that they offer better prices through lower-order placement costs and update quotes faster. However, other studies suggest that Algorithmic Traders create a ‘barrier to entry’ situation for human traders, which deteriorates the market quality significantly.
This research was led by Prof. P. Krishna Prasanna, Department of Management Studies, IIT Madras, and Ms. Devika Arumugam, Fulbright Fellow and a Ph.D. Scholar, Department of Management Studies, IIT Madras. It examined the impact of ATs on the National Stock Exchange (NSE). The findings were published in the reputed peer-reviewed journal Applied Economics, Taylor and Francis.
Elaborating on the importance of this research, Prof. P. Krishna Prasanna, Department of Management Studies, IIT Madras, said, “Existing studies consider ATs as a homogenous group, which is far from reality. ATs use different algorithms based on their source of funds. So, they are classified into two categories – (1) Proprietary Algorithmic Traders (PATs) and (2)Buy-side Algorithmic Traders (BATs).”
Further, Prof. P. Krishna Prasanna said, “The crucial difference between the two is, Proprietary Algorithmic Traders or PATs trade with their own funds, and their algorithms are arbitrage seeking, while Buy-side Algorithmic Traders or BATs trade with their clients’ funds and their algorithms are predominantly cost reduction seeking.”
The Key Learnings and Outcomes from this Research include:
– PATs and BATs trade differently and have a differential impact on the market quality.
– PATs’ cancellation increases the quoted spread, while BATs’ order placement reduces the same.
– BATs’ crowd out PATs’ orders, but not vice versa.
Highlighting the implications of this research for Trading, Ms. Devika Arumugam, Ph.D. scholar and Fulbright Fellow, Department of Management Studies, IIT Madras, said, “These new findings have substantial financial and regulatory implications. Traders and regulators stand to gain from the market quality enhancing capabilities of BATs.”
Also, as PATs and BATs trade differently, they have a differential impact on the market quality. PATs’ cancellation significantly increases the quoted spread, while BATs’ order placement reduces the same. The researchers also examined whether PATs and BATs exhibit a “hide-and-seek” behavior and find that BATs crowd out PATs’ orders but not vice versa.
However, selective regulation of PATs’ strategies is necessary. As BATs crowd out PATs, it suggests that the rivalry among ATs can counteract any market imbalances created by price distorting and aggressive algorithmic strategies, thereby enhancing the price efficiency. These results are primarily based on ATs’ order placement and cancellation activity in the market.
Original News Link
https://www.iitm.ac.in/happenings/press-releases-and-coverages/iit-madras-researchers-study-impact-algorithmic-traders
