The stock market is a place that attracts the attention of a lot of people. Everyone wants to become a millionaire with one carefully placed call. Since a huge amount of money is involved in the process, the investors hire experts who tell them when is the best time to sell or buy their stock. They also give information on which company is doing well; which looks good (rising stock), and which ones are not worth investing in. So there is a lot at stake involved in the entire system. But what happens if humans no longer predict the market outcome? What happens when AI (Artificial Intelligence) takes over? Thus, Algorithmic Traders (ATs) have been introduced. They trade faster than human traders.
ATs are classified into:
1. Proprietary Algorithmic Traders (PATs).
2. Buy-side Algorithmic Traders (BATs).
PATs trade with their own funds, and their algorithms are arbitrage seeking.
BATs trade with their clients’ funds, and their algorithms are predominantly cost reduction seeking.
This paper is the first of its kind to investigate the impact of PATs’ and BATs’ trading on market quality and vice versa. This has significant welfare implications for the securities market.
The research on ATs has just started to emerge. Some of the literature that favours ATs suggests that they offer better prices through lower order placement costs and avoid adverse selection risk through faster quote updation.
But ATs create a ‘barrier to entry’ situation for human traders, which deteriorate the market quality significantly.
In this study, it is examined whether PATs and BATs exhibit a hide-and-seek behaviour and crowd out among themselves.
The literature by Dumitrescu and Hurlin (2012) suggests a causality procedure that helps to identify the bidirectional causality between ATs’ activity and market quality metrices. The two ATs trade differently and have different impacts on the market quality. Through this research, it is found that PATs’ cancellation significantly increases the quoted spread, while BATs’ order placement reduces the same. New evidence is provided on BATs crowding out PATs but not vice versa. These new findings have substantial financial and regulatory implications.
Traders and regulators stand to gain from the market quality enhancing capabilities of BATs. However, selective regulation of PATs’ strategies is necessary. As BATs crowd out PATs, it suggests that the rivalry among ATs can affect any market imbalances created by price distorting and aggressive algorithmic strategies, thereby enhancing the price efficiency. These results are restricted primarily to the effect of ATs’ order placement and cancellation on market quality.
However, further study is required to uncover the liquidity demand and supply dynamics of PATs and BATs under various market conditions.
Article by Akshay Anantharaman
Here is the original link to the scientific paper: