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High-frequency trading in the Bund futures market

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  • Schlepper, Kathi

Abstract

In this work, I study the impact of high-frequency trading (HFT) on price discovery and volatility in the Bund futures market. Using a new dataset based on microseconds, the focus of the study is on the reaction of high-frequency traders (HFTs) to major macroeconomic news events. I show that through their fast and strong reaction to news, HFTs contribute more to price discovery compared to Non-HFTs, but also add a higher share to noise than to permanent volatility. Moreover, I find evidence that HFTs tend to supply less liquidity after an unexpected rise in market volatility and prior to upcoming macroeconomic news events. These findings suggest that in times of high market stress, HFT behavior may exacerbate intraday price volatility and amplify the risk of market disruptions in fixed income markets.

Suggested Citation

  • Schlepper, Kathi, 2016. "High-frequency trading in the Bund futures market," Discussion Papers 15/2016, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdps:152016
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    References listed on IDEAS

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    1. Altavilla, Carlo & Giannone, Domenico & Modugno, Michele, 2017. "Low frequency effects of macroeconomic news on government bond yields," Journal of Monetary Economics, Elsevier, vol. 92(C), pages 31-46.
    2. Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    3. Jones, Charles M. & Lamont, Owen & Lumsdaine, Robin L., 1998. "Macroeconomic news and bond market volatility," Journal of Financial Economics, Elsevier, vol. 47(3), pages 315-337, March.
    4. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    5. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    6. Benos, Evangelos & Sagade, Satchit, 2012. "High-frequency trading behaviour and its impact on market quality: evidence from the UK equity market," Bank of England working papers 469, Bank of England.
    7. Hasbrouck, Joel & Saar, Gideon, 2009. "Technology and liquidity provision: The blurring of traditional definitions," Journal of Financial Markets, Elsevier, vol. 12(2), pages 143-172, May.
    8. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    9. Breckenfelder, Johannes, 2013. "Competition between high-frequency traders, and market quality," MPRA Paper 66715, University Library of Munich, Germany, revised Dec 2013.
    10. Hasbrouck, Joel, 1991. "The Summary Informativeness of Stock Trades: An Econometric Analysis," Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 571-595.
    11. Hasbrouck, Joel, 1993. "Assessing the Quality of a Security Market: A New Approach to Transaction-Cost Measurement," Review of Financial Studies, Society for Financial Studies, vol. 6(1), pages 191-212.
    12. Gao, Cheng & Mizrach, Bruce, 2016. "Market quality breakdowns in equities," Journal of Financial Markets, Elsevier, vol. 28(C), pages 1-23.
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    Cited by:

    1. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).

    More about this item

    Keywords

    High-Frequency Trading; Price Discovery; Volatility;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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