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Predicting ETF liquidity

Author

Listed:
  • Son D Pham
  • Ben R Marshall

    (Massey University, Auckland, New Zealand)

  • Nhut H Nguyen

    (Auckland University of Technology, Auckland, New Zealand)

  • Nuttawat Visaltanachoti

    (School of Economics and Finance, Massey University, Auckland, New Zealand)

Abstract

Substantial transaction costs are incurred in exchange-traded fund (ETF) trading each year. This article examines a vector autoregressive (VAR) model’s performance and other trading schedules to time trades in a large sample of 1350 ETFs over the 2011–2017 period. We reject the notion of a one-size-fits-all trading schedule that maximizes spread savings for all ETF traders. ETF traders who want to split their orders could save 7.40% of ETF spread costs, whereas trading at the market closing time would be optimal for ETF traders without motives to split trades. The spread savings for ETF traders are diverse across ETF sectors and depend on the spread volatility. JEL Classification: G11, G23

Suggested Citation

  • Son D Pham & Ben R Marshall & Nhut H Nguyen & Nuttawat Visaltanachoti, 2024. "Predicting ETF liquidity," Australian Journal of Management, Australian School of Business, vol. 49(3), pages 478-508, August.
    • Handle: RePEc:sae:ausman:v:49:y:2024:i:3:p:478-508
    DOI: 10.1177/03128962221143494
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    More about this item

    Keywords

    Bid-ask spread; diversification; ETFs; forecasting; liquidity; portfolio liquidity;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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