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This research delves into the influence of algorithmic trading (AT) on various facets of liquidity within the Indian energy futures market. Through regression analysis, we scrutinize how AT intensity affects market tightness, breadth, depth, and resiliency utilizing measures such as relative spread (RS), Amihud illiquidity ratio (AIR), commodity turnover (CT), and Price/Trade ratio. Our results uncover a notable and positive relationship between AT and market tightness and breadth, indicating improved liquidity with narrower spreads and increased order depth. However, the impact of AT on depth, measured by CT, is negative and significant, suggesting lower turnover for algorithmic trades compared to manual ones. Additionally, AT demonstrates a positive influence on resiliency, as measured by the P/T ratio, suggesting a quicker recovery from price shocks.
Jain et al. (Sun,) studied this question.