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  • Degiannakis, Stavros
  • Filis, George
  • Siourounis, Grigorios
  • Trapani, Lorenzo


Very little is known on how traditional risk metrics behave in ultra high frequency trading (UHFT). We fi�ll this void �firstly by examining the existence of the intraday returns moments, and secondly by assessing the impact of their (non)existence in a risk management framework. We show that in the case of UHFT, the returns' third and fourth moments do not exist, which entails that traditional risk metrics are unable to judge capital adequacy adequately. Hence, the use of risk management techniques, such as VaR, by market participants who engage with UHFT impose serious threats to the stability of fi�nancial markets, given that capital ratios may be severely underestimated.

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  • Degiannakis, Stavros & Filis, George & Siourounis, Grigorios & Trapani, Lorenzo, 2019. "Superkurtosis," MPRA Paper 94473, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:94473

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    • Degiannakis, Stavros & Filis, George & Siourounis, Grigorios & Trapani, Lorenzo, 2019. "Superkurtosis," MPRA Paper 96563, University Library of Munich, Germany.
    • Stavros Degiannakis & George Filis & Grigorios Siourounis & Lorenzo Trapani, 2023. "Superkurtosis," Working Papers 318, Bank of Greece.

    References listed on IDEAS

    1. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
    2. Andrei A. Kirilenko & Andrew W. Lo, 2013. "Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents," Journal of Economic Perspectives, American Economic Association, vol. 27(2), pages 51-72, Spring.
    3. Trapani, Lorenzo, 2016. "Testing for (in)finite moments," Journal of Econometrics, Elsevier, vol. 191(1), pages 57-68.
    4. Igor Fedotenkov, 2013. "A bootstrap method to test for the existence of finite moments," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 315-322, June.
    5. Horváth, Lajos & Trapani, Lorenzo, 2016. "Statistical inference in a random coefficient panel model," Journal of Econometrics, Elsevier, vol. 193(1), pages 54-75.
    6. Beddington, John & Furse, Clara & Bond, Philip & Cliff, Dave & Goodhart, Charles & Houstoun, Kevin & Linton, Oliver & Zigrand, Jean-Pierre, 2012. "Foresight: the future of computer trading in financial markets: final project report," LSE Research Online Documents on Economics 62157, London School of Economics and Political Science, LSE Library.
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    More about this item


    Ultra high frequency trading; risk management; fi�nite moments; superkurtosis.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • F30 - International Economics - - International Finance - - - General
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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