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Superkurtosis

Author

Listed:
  • STAVROS DEGIANNAKIS
  • GEORGE FILIS
  • GRIGORIOS SIOUROUNIS
  • LORENZO TRAPANI

Abstract

Very little is known on how traditional risk metrics behave under intraday trading. We fill this void by examining the finiteness of the returns' moments and assessing the impact of their infinity in a risk management framework. We show that when intraday trading is considered, assuming finite higher order moments, potential losses are materially larger than what the theory predicts, and they increase exponentially as the trading frequency increases—a phenomenon we call superkurtosis$superkurtosis$. Hence, the use of the current risk management techniques under intraday trading imposes threats to the stability of financial markets, as capital ratios are severely underestimated.

Suggested Citation

  • Stavros Degiannakis & George Filis & Grigorios Siourounis & Lorenzo Trapani, 2023. "Superkurtosis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(8), pages 2061-2091, December.
    • Handle: RePEc:wly:jmoncb:v:55:y:2023:i:8:p:2061-2091
    DOI: 10.1111/jmcb.12988
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    Other versions of this item:

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

    References listed on IDEAS

    as
    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. Engle, Robert F. & Manganelli, Simone, 2001. "Value at risk models in finance," Working Paper Series 75, European Central Bank.
    4. Trapani, Lorenzo, 2016. "Testing for (in)finite moments," Journal of Econometrics, Elsevier, vol. 191(1), pages 57-68.
    5. 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.
    6. Horváth, Lajos & Trapani, Lorenzo, 2016. "Statistical inference in a random coefficient panel model," Journal of Econometrics, Elsevier, vol. 193(1), pages 54-75.
    7. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    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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