Predicting ETF liquidity

Son Pham; Ben R. Marshall; Nhut H. Nguyen; Nuttawat Visaltanachoti

doi:10.1177/03128962221143494

Predicting ETF liquidity

Son Pham, Ben R. Marshall, Nhut H. Nguyen, Nuttawat Visaltanachoti^* (Corresponding Author)

^*Corresponding author for this work

Accountancy & Finance, Finance

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Number of pages	31
Journal	Australian Journal of Management
Early online date	10 Jan 2023
DOIs	https://doi.org/10.1177/03128962221143494
Publication status	E-pub ahead of print - 10 Jan 2023

Keywords

Bid-ask spread; Diversification; ETFs; Forecasting; Liquidity; Portfolio Liquidity

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AB - 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.

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Predicting ETF liquidity

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