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Published in: Schmalenbach Business Review 3/2018

12-04-2018 | Original Article

Bid-Ask Spread Patterns and the Optimal Timing for Discretionary Liquidity Traders on Xetra

Authors: Martin Angerer, Georg Peter, Sebastian Stoeckl, Thomas Wachter, Matthias Bank, Marco Menichetti

Published in: Schmalenbach Business Review | Issue 3/2018

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Abstract

This paper explores the statistical and economical significance of intra-day and -week patterns in bid-ask spreads. We investigate a large panel of high frequency data for stocks traded on the XETRA trading platform and observe significant patterns in spreads. In addition to showing the robustness of our findings over time, as well as in cross-section, we are also able to demonstrate the patterns’ predictability in an out-of-sample approach. Our findings have clear implications, especially for uninformed but discretionary liquidity traders, which allow significant and economically relevant reductions of transaction costs.

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Appendix
Available only for authorised users
Footnotes
1
MiFID I replaced the Investment Services Directive (ISD) in November 2007. MiFID II will be in force on the 3rd of January 2018.
 
2
See, for example, „Trade management guidelines“ by the CFA Institute: http://​www.​cfapubs.​org/​doi/​pdf/​10.​2469/​ccb.​v2004.​n3.​4007.
 
3
Imagine the letter „J“ mirrored along the vertical axis. In other words, the spread has the highest value on the left side of the x‑axis, declines going to the right and increases by a smaller amount further to the right at the end.
 
4
Imagine the letter „m“ mirrored along the horizontal axis. The result is a pattern with peaks on the left, in the middle and on the right, and valleys in between.
 
5
In what follows, we report results including spreads during the midday auction. Table 4 of the Appendix shows that omitting the midday auction changes our results only very marginally.
 
6
We define small and large caps by ranking all stocks by initial market capitalisation and sorting the upper 50% into the large-cap sample, with the remaining lower 50% being assigned to the small-cap sample.
 
7
To test the robustness of our out-of-sample findings, we have re-estimated all results based on a 50-day observation period to compute the optimal trading interval. As the results remain qualitatively similar, they are not reported in this manuscript but can be obtained from the authors upon request.
 
8
Detailed results are provided in Table 10 of the Appendix.
 
Literature
go back to reference Hora, M. 2006. Tactical liquidity trading and intraday volume. Social science research network working paper series. Hora, M. 2006. Tactical liquidity trading and intraday volume. Social science research network working paper series.
go back to reference Krogmann, Michael. 2011. Ch. 6: Quantifying liquidity risk. In Buy-side intelligence: the euromoney guide to securities trading, ed. Xetra Institutional Equity – Deutsche Boerse AG Krogmann, Michael. 2011. Ch. 6: Quantifying liquidity risk. In Buy-side intelligence: the euromoney guide to securities trading, ed. Xetra Institutional Equity – Deutsche Boerse AG
Metadata
Title
Bid-Ask Spread Patterns and the Optimal Timing for Discretionary Liquidity Traders on Xetra
Authors
Martin Angerer
Georg Peter
Sebastian Stoeckl
Thomas Wachter
Matthias Bank
Marco Menichetti
Publication date
12-04-2018
Publisher
Springer International Publishing
Published in
Schmalenbach Business Review / Issue 3/2018
Print ISSN: 1439-2917
Electronic ISSN: 2194-072X
DOI
https://doi.org/10.1007/s41464-018-0049-z