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Price jumps on European stock markets

Author

Listed:
  • Jan Hanousek
  • Evzen Kocenda
  • Jan Novotny

Abstract

We analyze the dynamics of price jumps and the impact of the European debt crisis using the high-frequency data reported by selected stock exchanges on the European continent during the period January 2008 to June 2012. We employ two methods to identify price jumps: Method 1 minimizes the probability of false jump detection (the Type-II Error-Optimal price jump indicator) and Method 2 maximizes the probability of successful jump detection (the Type-I Error-Optimal price jump indicator). We show that individual stock markets exhibited differences in price jump intensity before and during the crisis. We also show that in general the variance of price jump intensity could not be distinguished as different in the pre-crisis period from that during the crisis. Our results indicate that, contrary to common belief, the intensity of price jumps does not uniformly increase during a period of financial distress. However, there do exist differences in price jump dynamics across stock markets and investors have to model emerging and mature markets differently to properly reflect their individual dynamics.

Suggested Citation

  • Jan Hanousek & Evzen Kocenda & Jan Novotny, 2014. "Price jumps on European stock markets," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 14(1), pages 10-22, March.
  • Handle: RePEc:bor:bistre:v:14:y:2014:i:1:p:10-22
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    Cited by:

    1. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    2. CĂLIN, Adrian Cantemir, 2015. "Connection Of European Economic Growth With The Dynamics Of Volatility Of Stock Market Returns," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 53-66.
    3. Martin Lausegger, 2021. "Stock markets in turmoil: political institutions and the impact of elections," Economics and Politics, Wiley Blackwell, vol. 33(1), pages 172-204, March.
    4. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    5. Maslyuk-Escobedo, Svetlana & Rotaru, Kristian & Dokumentov, Alexander, 2017. "News sentiment and jumps in energy spot and futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 186-210.
    6. Naeyoung Kang & Jungmu Kim, 2019. "An Empirical Analysis of Bitcoin Price Jump Risk," Sustainability, MDPI, vol. 11(7), pages 1-11, April.
    7. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.
    8. Kočenda, Evžen & Moravcová, Michala, 2019. "Exchange rate comovements, hedging and volatility spillovers on new EU forex markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 42-64.
    9. RNuket Kirci Cevik & Sel Dibooglu & Ali M. Kutan, 2016. "Real and Financial Sector Studies in Central and Eastern Europe: A Review," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(1), pages 2-31, February.
    10. Ahadzie, Richard Mawulawoe & Jeyasreedharan, Nagaratnam, 2020. "Trading volume and realized higher-order moments in the Australian stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).

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    Keywords

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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