Trading performance and market efficiency: Evidence from algorithmic trading

Sudhakara Reddy Syamala and Kavita Wadhwa

Research in International Business and Finance, 2020, vol. 54, issue C

Abstract: In India, National Stock Exchange directly identifies algorithmic trading participation. Algorithmic traders possess intraday market timing skills. Results are not motivated by extreme short-term signals or transitory price trading. Magnitude of market timing performance in cross-sectional group of traders shows that they earn profit across all the cases, and maximize while providing liquidity. Volume-weighted-average-price decomposition analysis reports algorithmic traders earn profits through intraday market timing performance for five-minute and one-minute intervals, and it is higher compared to short-term market timing performance across all trader groups. Order imbalance and price delay regressions show that algorithmic trading significantly improves price efficiency.

Keywords: Algorithmic trading; VWAP; Trading performance; Intraday trading (search for similar items in EconPapers)
JEL-codes: G1 G10 G18 G2 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:54:y:2020:i:c:s0275531920304050

DOI: 10.1016/j.ribaf.2020.101283

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