The performance of bid-ask spread estimators under less than ideal conditions
The performance of bid-ask spread estimators is investigated using simulation experiments. All estimators are much more accurate if the data are sampled at high frequency. In high-frequency data, the Huang-Stoll estimator, which requires order flow information, generally outperforms Roll-type estimators based on price information only. The exception is when there is feedback trading (order flows respond to past price movements), when the Huang-Stoll estimator is seriously biased. When only low-frequency (e.g. daily) data are available, the Corwin-Schultz estimator based on daily high and low prices is usually less inaccurate than the Huang-Stoll and Roll estimators. An important and empirically relevant exception is when the spread varies within the day; in this case the Corwin-Schultz estimator significantly overestimates the true spread. For a published version, please see Studies in Economics and Finance, Vol. 32 (2015).
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|Date of creation:||Sep 2013|
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- Stoll, Hans R, 1989. " Inferring the Components of the Bid-Ask Spread: Theory and Empirical Tests," Journal of Finance, American Finance Association, vol. 44(1), pages 115-34, March.
- Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-35, November.
- Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
- Holden, Craig W., 2009. "New low-frequency spread measures," Journal of Financial Markets, Elsevier, vol. 12(4), pages 778-813, November.
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