Efficiency of Algorithmic Trading in Modern Markets

Abstract

Algorithmic trading (AT) is the use of<br> computer programs to execute trades in financial<br> markets. AT has become increasingly popular in recent<br> years, as it offers a number of advantages over<br> traditional manual trading, such as speed, accuracy, and<br> consistency.<br> This research paper examines the efficiency of AT<br> in modern markets. It begins by providing a brief<br> overview of AT and its benefits. It then discusses the<br> different types of AT algorithms and how they are used.<br> The paper then reviews the literature on the efficiency of<br> AT, and presents the findings of a data analysis on the<br> impact of AT on market quality.<br> The findings of the study suggest that AT has a<br> number of positive effects on market efficiency. For<br> example, AT can help to reduce bid-ask spreads,<br> improve liquidity, and enhance price discovery.<br> However, the study also finds that AT can have some<br> negative effects on market quality, such as increasing<br> market volatility and facilitating market manipulation.<br> Overall, the study concludes that AT is a generally<br> efficient and beneficial trading method. However, it is<br> important to be aware of the potential negative effects of<br> AT on market quality, and to take steps to mitigate these<br> risks.

Cite this paper

@article{salecha2023efficiency,
  title = {{Efficiency of Algorithmic Trading in Modern Markets}},
  author = {Salecha, Swayam},
  journal = {Zenodo (CERN European Organization for Nuclear Research)},
  year = {2023},
  doi = {10.5281/zenodo.8372303}
}

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