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Journal ArticleDOI

Examining Intraday ETF Liquidity: When Should Investors Trade?

31 Mar 2019-The Journal of Index Investing (Institutional Investor Journals Umbrella)-Vol. 9, Iss: 4, pp 6-17
TL;DR: In this paper, the authors analyzed the effect of time of day on the average bid/ask spread of an exchange-traded fund (ETF) and found that, both before and after they add controls, average spreads are highest in the early morning.
Abstract: In this article, the authors analyze the effect of time of day on the average bid/ask spread of an exchange-traded fund (ETF). They examine a cross-section of 55,781 intraday spread observations generated by 744 US-domiciled ETFs in 2017, controlling for fund category, trading volume, and issuer. The authors find that, both before and after they add controls, average spreads are highest in the early morning, supporting the argument that investors should avoid trading near market open. Before controls, average spreads are tightest in the late afternoon. After controls, they appear elevated during the final five minutes. However, because volume increases substantially during that period, spreads still appear tighter overall. Therefore, our analysis does not support the argument that investors should avoid trading near market close. Unexpectedly, after controls, the authors find higher spreads during Federal Open Market Committee announcements. This suggests that investors should be vigilant when trading at such times.
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TL;DR: In this article, the authors developed a five-factor liquidity scoring algorithm that enables a ranking of ETFs from the most liquid to the least liquid, and presented the top and bottom 50 most and least liquid ETFs.
Abstract: There are about 900 ETFs trading in the market, of which a large number appear to be duplicative in design and coverage. Some of them possibly serve as a tool for issuing firms to gain market share. We suspect that many of the newer funds have low liquidity, asynchronous trading, and wider bid-ask spreads. This article develops a five-factor liquidity scoring algorithm that enables a ranking of ETFs from the most liquid to the least liquid. The authors present the top and bottom 50 ETFs from this ranked liquidity list. They also find that there is a very active bond ETF market, as evidenced by the fact that about 20% of the most liquid ETFs are bond-based. The factors that the authors find most indicative of liquidity are a lower bid-ask spread, a higher market capitalization, a lower expense ratio, and higher average trading volume. In contrast, the least liquid funds have larger bid-ask spreads, smaller market capitalizations, higher expense ratios, and much lower investor interest as proxied by trailing 3-month daily trading volumes. While low-liquidity ETFs may provide the investor with exposure to a very narrow market segment, the costs of trading, market price impact, and ease of establishing or unwinding a sizable position must be carefully evaluated before initiating holdings in ETFs that exhibit low liquidity.

4 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the relationship between time of day and bid-ask spread for US-domiciled fixed income exchange-traded funds (ETFs) with US dollar exposure and found that both before and after they add controls, average spreads are highest in the morning, supporting the argument that investors trading on the basis of NBBO spreads should avoid trading near market open.
Abstract: In this article, the authors analyze the relationship between time of day and bid-ask spread for US-domiciled fixed income exchange-traded funds (ETFs) with US dollar exposure. They aggregate millions of national best bid and offer (NBBO) spread data points into 168,324 sample observations according to 166 ETFs over 78 intra-day time intervals across 13 calendar quarters. The authors find that both before and after they add controls, average spreads are highest in the morning, supporting the argument that investors trading on the basis of NBBO spreads should avoid trading near market open. After falling from morning peaks, spreads generally flatten out the rest of the day, even after adding controls. Therefore, the analysis does not support the argument that investors should systematically avoid trading US fixed income ETFs near market close. TOPICS:Exchange-traded funds and applications, fixed-income portfolio management Key Findings • Average spreads are highest in the morning before and after adding a battery of variables, supporting the argument that investors trading on the basis of national best bid and offer (NBBO) spreads should avoid trading US fixed income ETFs near market open. • After falling from morning peaks, spreads generally flatten out the rest of the day, contradicting the argument that investors should systematically avoid trading US fixed income ETFs near market close. • Our findings do not negate other trading best practices such as using limit orders, consulting a block desk for large orders, and not trading during the open and/or closing auctions.
References
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Journal ArticleDOI
TL;DR: Ozenbas et al. as mentioned in this paper investigated the quality of price determination at these times (compared to midday periods) for large-, mid-, and small-cap stocks on the NYSE, NASDAQ, and London Stock Exchange.
Abstract: In equity markets, the opening and closing of trading are particularly stressful periods. Ozenbas, Pagano, and Schwartz investigate the quality of price determination at these times (compared to midday periods) for large-, mid-, and smallcapitalization stocks on the NYSE, NASDAQ, and London Stock Exchange. Using three different metrics, they consistently find lower quality at both the open and the close.The deterioration of market quality at openings is greatest for large-cap stocks, but no systematic association with cap size is observed at the close. Large-cap stocks evidently lead smaller-cap stocks in finding new equilibrium values, and accentuated volatility at the open is in large part attributable to the complexities of price discovery.

14 citations

Journal ArticleDOI
TL;DR: This paper examined price discovery and its determinants for equivalent instruments across futures markets, electronically traded exchange-traded funds (ETFs), and spot markets, and found that most price discovery occurs in the more liquid and highly leveraged futures market.
Abstract: Using high-frequency datasets, we examine price discovery and its determinants for equivalent instruments across futures markets, electronically traded exchange-traded funds (ETFs), and spot markets. We compare futures to ETFs—leveraged and unleveraged—for stock indexes, using both a normal period and the 2008 financial crisis. Yan and Zivot’s information leadership procedure is employed to determine which instrument dominates price discovery. We then examine the determinants and characteristics of the price discovery process using Hasbrouck’s sequential trading model for the price impact of large trades. We find that most price discovery occurs in the more liquid and highly leveraged futures market. Although liquidity declined in all markets during the financial crisis, the relative contribution of ETFs to price discovery increased. We also find that the information leadership shares of futures and ETFs depend on the ratio of the quoted percentage spread between futures and ETFs and the aggregate volatility occurring in these markets.

10 citations

21 Sep 2009
TL;DR: In this article, the authors developed a five-factor liquidity scoring algorithm that enables a ranking of ETFs from the most liquid to the least liquid, and presented the top and bottom 50 most and least liquid ETFs.
Abstract: There are about 900 ETFs trading in the market, of which a large number appear to be duplicative in design and coverage. Some of them possibly serve as a tool for issuing firms to gain market share. We suspect that many of the newer funds have low liquidity, asynchronous trading, and wider bid-ask spreads. This article develops a five-factor liquidity scoring algorithm that enables a ranking of ETFs from the most liquid to the least liquid. The authors present the top and bottom 50 ETFs from this ranked liquidity list. They also find that there is a very active bond ETF market, as evidenced by the fact that about 20% of the most liquid ETFs are bond-based. The factors that the authors find most indicative of liquidity are a lower bid-ask spread, a higher market capitalization, a lower expense ratio, and higher average trading volume. In contrast, the least liquid funds have larger bid-ask spreads, smaller market capitalizations, higher expense ratios, and much lower investor interest as proxied by trailing 3-month daily trading volumes. While low-liquidity ETFs may provide the investor with exposure to a very narrow market segment, the costs of trading, market price impact, and ease of establishing or unwinding a sizable position must be carefully evaluated before initiating holdings in ETFs that exhibit low liquidity.

4 citations


"Examining Intraday ETF Liquidity: W..." refers background in this paper

  • ...A significant amount of research indicates that high trading volume correlates with tighter spreads (Agrrawal and Clark, 2009)....

    [...]

Posted Content
TL;DR: In this article, the authors developed a five-factor liquidity scoring algorithm that enables a ranking of ETFs from the most liquid to the least liquid, and presented the top and bottom 50 most and least liquid ETFs.
Abstract: There are about 900 ETFs trading in the market, of which a large number appear to be duplicative in design and coverage. Some of them possibly serve as a tool for issuing firms to gain market share. We suspect that many of the newer funds have low liquidity, asynchronous trading, and wider bid-ask spreads. This article develops a five-factor liquidity scoring algorithm that enables a ranking of ETFs from the most liquid to the least liquid. The authors present the top and bottom 50 ETFs from this ranked liquidity list. They also find that there is a very active bond ETF market, as evidenced by the fact that about 20% of the most liquid ETFs are bond-based. The factors that the authors find most indicative of liquidity are a lower bid-ask spread, a higher market capitalization, a lower expense ratio, and higher average trading volume. In contrast, the least liquid funds have larger bid-ask spreads, smaller market capitalizations, higher expense ratios, and much lower investor interest as proxied by trailing 3-month daily trading volumes. While low-liquidity ETFs may provide the investor with exposure to a very narrow market segment, the costs of trading, market price impact, and ease of establishing or unwinding a sizable position must be carefully evaluated before initiating holdings in ETFs that exhibit low liquidity.

4 citations