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Do algorithmic traders exploit volatility?

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  • Arumugam, Devika
  • Prasanna, P. Krishna
  • Marathe, Rahul R.

Abstract

This study examines the impact of trading by Algorithmic Traders (ATs) and Non-Algorithmic Traders (NATs) on volatility, and conversely, the impact of volatility shocks on ATs and Non-ATs. ATs are classified as High-Frequency Traders (HFTs) and Buy-side Algorithmic Traders (BATs). Using jump robust volatility estimates, we find that excessive directional and non-directional trading by BATs and HFTs increases volatility, whereas that by NATs marginally decreases volatility. Conversely, all traders increase their non-directional trading one hour following a volatility shock. BATs carry out more directional trades during a volatility shock, whereas HFTs withdraw from such activities.

Suggested Citation

  • Arumugam, Devika & Prasanna, P. Krishna & Marathe, Rahul R., 2023. "Do algorithmic traders exploit volatility?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    • Handle: RePEc:eee:beexfi:v:37:y:2023:i:c:s2214635022001009
    DOI: 10.1016/j.jbef.2022.100778
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    Cited by:

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    More about this item

    Keywords

    Algorithmic trading; High-frequency trading; Volatility;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G40 - Financial Economics - - Behavioral Finance - - - General

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