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VPIN and the Flash Crash

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  • Torben G. Andersen

    ()
    (Kellogg School of Management; Northwestern University and CREATES)

  • Oleg Bondarenko

    ()
    (Department of Finance (MC 168), University of Illinois at Chicago)

Abstract

Easley, Lopez de Prado and O'Hara introduce VPIN as a real-time indicator of order flow toxicity. They find it useful for monitoring order fl ow imbalances and signaling impending market turmoil, exemplified by the ash crash. They also deem VPIN a good forecaster of short-term volatility. In contrast, we find that VPIN is a poor volatility predictor, that it only reached an all-time high following the ash crash, and that its predictive content stems from a mechanical relation with trading intensity. Generally, we caution against adoption of any specific market stress metric until it is compared thoroughly to suitable benchmarks.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2011-50.

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Length: 38
Date of creation: 30 Oct 2011
Date of revision:
Handle: RePEc:aah:create:2011-50

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: VPIN; PIN; High-Frequency Trading; Order Flow Toxicity; Order Imbalance; Flash Crash; VIX; Volatility Forecasting.;

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  1. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
  2. Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
  3. Torben G. Andersen & Oleg Bondarenko, 2007. "Construction and Interpretation of Model-Free Implied Volatility," NBER Working Papers 13449, National Bureau of Economic Research, Inc.
  4. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  5. Lee, Charles M C & Ready, Mark J, 1991. " Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-46, June.
  6. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
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Cited by:
  1. Torben G. Andersen & Oleg Bondarenko, 2013. "Reflecting on the VPN Dispute," CREATES Research Papers 2013-42, School of Economics and Management, University of Aarhus.

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