IDEAS home Printed from https://ideas.repec.org/a/oup/revfin/v19y2015i1p1-54..html
   My bibliography  Save this article

Assessing Measures of Order Flow Toxicity and Early Warning Signals for Market Turbulence

Author

Listed:
  • Torben G. Andersen
  • Oleg Bondarenko

Abstract

Following the "flash crash" on May 6, 2010, warning signals for impending market stress have been in high demand, yet only the VPIN metric of Easley, López de Prado, and O’Hara (ELO) has claimed success. In addition, ELO find the metric useful in predicting short-term volatility. VPIN involves decomposing volume into active buys and sells. We utilize quotes and trade data to construct an accurate trade classification measure for E-mini S&P 500 futures. Against this benchmark, the ELO Bulk Volume Classification (BVC) scheme is inferior to a standard tick rule. Moreover, VPIN predicts volatility solely because increasing volatility induces systematic classification errors in the BVC procedure. We conclude that VPIN is unsuitable for capturing order flow toxicity or signaling ensuing market turbulence.

Suggested Citation

  • Torben G. Andersen & Oleg Bondarenko, 2015. "Assessing Measures of Order Flow Toxicity and Early Warning Signals for Market Turbulence," Review of Finance, European Finance Association, vol. 19(1), pages 1-54.
    • Handle: RePEc:oup:revfin:v:19:y:2015:i:1:p:1-54.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/rof/rfu041
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rama Cont & Arseniy Kukanov & Sasha Stoikov, 2014. "The Price Impact of Order Book Events," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 47-88.
    2. Boehmer, Ekkehart & Grammig, Joachim & Theissen, Erik, 2007. "Estimating the probability of informed trading--does trade misclassification matter?," Journal of Financial Markets, Elsevier, vol. 10(1), pages 26-47, February.
    3. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    4. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    5. Asquith, Paul & Oman, Rebecca & Safaya, Christopher, 2010. "Short sales and trade classification algorithms," Journal of Financial Markets, Elsevier, vol. 13(1), pages 157-173, February.
    6. Andersen, Torben G. & Bondarenko, Oleg, 2014. "VPIN and the flash crash," Journal of Financial Markets, Elsevier, vol. 17(C), pages 1-46.
    7. Finucane, Thomas J., 2000. "A Direct Test of Methods for Inferring Trade Direction from Intra-Day Data," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 553-576, December.
    8. 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.
    9. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    10. Chakrabarty, Bidisha & Li, Bingguang & Nguyen, Vanthuan & Van Ness, Robert A., 2007. "Trade classification algorithms for electronic communications network trades," Journal of Banking & Finance, Elsevier, vol. 31(12), pages 3806-3821, December.
    11. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
    12. Ellis, Katrina & Michaely, Roni & O'Hara, Maureen, 2000. "The Accuracy of Trade Classification Rules: Evidence from Nasdaq," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 529-551, December.
    13. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    14. Wu, Kesheng & Bethel, E. Wes & Gu, Ming & Leinweber, David & Rübe, Oliver, 2013. "A big data approach to analyzing market volatility," Algorithmic Finance, IOS Press, vol. 2(3-4), pages 241-267.
    15. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    16. Odders-White, Elizabeth R., 2000. "On the occurrence and consequences of inaccurate trade classification," Journal of Financial Markets, Elsevier, vol. 3(3), pages 259-286, August.
    17. Aitken, Michael & Frino, Alex, 1996. "The accuracy of the tick test: Evidence from the Australian stock exchange," Journal of Banking & Finance, Elsevier, vol. 20(10), pages 1715-1729, December.
    18. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Torben G. Andersen & Oleg Bondarenko & Albert S. Kyle & Anna Obizhaeva, 2016. "Intraday Trading Invariance in the E-mini S&P 500 Futures Market," Working Papers w0229, New Economic School (NES).
    2. Chakrabarty, Bidisha & Pascual, Roberto & Shkilko, Andriy, 2015. "Evaluating trade classification algorithms: Bulk volume classification versus the tick rule and the Lee-Ready algorithm," Journal of Financial Markets, Elsevier, vol. 25(C), pages 52-79.
    3. Huang, Yan & Kou, Gang & Peng, Yi, 2017. "Nonlinear manifold learning for early warnings in financial markets," European Journal of Operational Research, Elsevier, vol. 258(2), pages 692-702.
    4. Prodromou, Tina & Westerholm, P. Joakim, 2022. "Are high frequency traders responsible for extreme price movements?," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 94-111.
    5. Easley, David & de Prado, Marcos Lopez & O'Hara, Maureen, 2016. "Discerning information from trade data," Journal of Financial Economics, Elsevier, vol. 120(2), pages 269-285.
    6. Allen Carrion & Madhuparna Kolay, 2020. "Trade signing in fast markets," The Financial Review, Eastern Finance Association, vol. 55(3), pages 385-404, August.
    7. Abad, David & Massot, Magdalena & Pascual, Roberto, 2018. "Evaluating VPIN as a trigger for single-stock circuit breakers," Journal of Banking & Finance, Elsevier, vol. 86(C), pages 21-36.
    8. Yildiz, Serhat & Van Ness, Bonnie & Van Ness, Robert, 2020. "VPIN, liquidity, and return volatility in the U.S. equity markets," Global Finance Journal, Elsevier, vol. 45(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Torben G. Andersen & Oleg Bondarenko, 2013. "Assessing Measures of Order Flow Toxicity via Perfect Trade Classification," CREATES Research Papers 2013-43, Department of Economics and Business Economics, Aarhus University.
    2. Chakrabarty, Bidisha & Pascual, Roberto & Shkilko, Andriy, 2015. "Evaluating trade classification algorithms: Bulk volume classification versus the tick rule and the Lee-Ready algorithm," Journal of Financial Markets, Elsevier, vol. 25(C), pages 52-79.
    3. Aktas, Osman Ulas & Kryzanowski, Lawrence, 2014. "Trade classification accuracy for the BIST," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 259-282.
    4. Donglian Ma & Pengxiang Zhai, 2021. "The Accuracy of the Tick Rule in the Bitcoin Market," SAGE Open, , vol. 11(2), pages 21582440211, May.
    5. Frömmel, Michael & D'Hoore, Dick & Lampaert, Kevin, 2021. "The Accuracy of Trade Classification Systems on the Foreign Exchange Market: Evidence from the RUB/USD Market," Finance Research Letters, Elsevier, vol. 42(C).
    6. Ben Omrane, Walid & Welch, Robert, 2016. "Tick test accuracy in foreign exchange ECN markets," Research in International Business and Finance, Elsevier, vol. 37(C), pages 135-152.
    7. Mark Fedenia & Tavy Ronen & Seunghan Nam, 2024. "Machine learning and trade direction classification: insights from the corporate bond market," Review of Quantitative Finance and Accounting, Springer, vol. 63(1), pages 1-36, July.
    8. Paul Asquith & Rebecca Oman & Christopher Safaya, 2008. "Short Sales and Trade Classification Algorithms," NBER Working Papers 14158, National Bureau of Economic Research, Inc.
    9. Boehmer, Ekkehart & Grammig, Joachim & Theissen, Erik, 2007. "Estimating the probability of informed trading--does trade misclassification matter?," Journal of Financial Markets, Elsevier, vol. 10(1), pages 26-47, February.
    10. Asquith, Paul & Oman, Rebecca & Safaya, Christopher, 2010. "Short sales and trade classification algorithms," Journal of Financial Markets, Elsevier, vol. 13(1), pages 157-173, February.
    11. Jurkatis, Simon, 2022. "Inferring trade directions in fast markets," Journal of Financial Markets, Elsevier, vol. 58(C).
    12. Andersen, Torben G. & Bondarenko, Oleg, 2014. "VPIN and the flash crash," Journal of Financial Markets, Elsevier, vol. 17(C), pages 1-46.
    13. Chan, Choon Chat & Fong, Wai Mun, 2006. "Realized volatility and transactions," Journal of Banking & Finance, Elsevier, vol. 30(7), pages 2063-2085, July.
    14. David Michayluk & Laurie Prather, 2008. "A Liquidity Motivated Algorithm for Discerning Trade Direction," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 45-66, March-Jun.
    15. Michael Frömmel & Eyup Kadioglu, 2023. "Impact of trading hours extensions on foreign exchange volatility: intraday evidence from the Moscow exchange," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    16. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021, January-A.
    17. Perlin, Marcelo & Brooks, Chris & Dufour, Alfonso, 2014. "On the performance of the tick test," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 42-50.
    18. Allen Carrion & Madhuparna Kolay, 2020. "Trade signing in fast markets," The Financial Review, Eastern Finance Association, vol. 55(3), pages 385-404, August.
    19. Thomas Pöppe & Michael Aitken & Dirk Schiereck & Ingo Wiegand, 2016. "A PIN per day shows what news convey: the intraday probability of informed trading," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1187-1220, November.
    20. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oup:revfin:v:19:y:2015:i:1:p:1-54.. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/eufaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.