The role of algorithmic trading systems on stock market efficiency

Ji Yong Seo, Sangmi Chai

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The rapid development of information technology has changed the dynamics of financial markets. The main purpose of this study is laid on examining the role of IT based stock trading on financial market efficiency. This research specifically focused on algorithmic trading. Algorithmic trading enables investors to trade stocks through a computer program without the need for human interventions. Based on an empirical analysis of the Korean stock market, this study discovered the positive impact of algorithmic trading on stock market efficiency at three-fold. First, the study results indicate that algorithmic trading contributes to the reduction in asymmetric volatility, which causes inefficiency of information in a stock market. Second, an algorithmic trading also increases the operation efficiency of a stock market. Arbitrage trading contributes on the equilibrium between the spot market and futures market as well as on the price discovery. Third, algorithmic trading provides liquidity for market participants contributing to friction free transactions. The research results indicate that stock exchanges based on electronic communications networks (ECNs) without human intervention could augment a financial market quality by increasing trading share volumes and market efficiency so that it can eventually contribute to the welfare of market investors.

Original languageEnglish
Pages (from-to)873-888
Number of pages16
JournalInformation Systems Frontiers
Issue number5
StatePublished - Nov 2013

Bibliographical note

Funding Information:
Acknowledgments The research of the first author, Ji-Yong Seo, was supported by Sangmyung University.


  • Asymmetric volatility
  • Efficiency of information
  • Efficiency of operation
  • Equilibrium
  • Liquidity


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