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Simultaneity of Tail Events for Dynamic Conditional Distributions of Stock Market Index Returns

Author

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  • Radu Lupu

    (Bucharest University of Economic Studies, Institute for Economic Forecasting, Romanian Academy)

Abstract

The tail events represent a phenomenon long studied in the literature of stock market returns. The dynamical properties of conditional distributions are currently analyzed by means of the first four moments via Gram-Charlier likelihood functions. We propose an analysis of changes in the values of means, volatilities, skewness and kurtosis coefficients for a series of intra-daily frequency of 14 stock market returns to develop a jump detection mechanism based on the estimation of a dynamic threshold that relies on the first four moments of the distribution. Our main objective consists in the estimation of simultaneity of tail values for these moments. We consider the 5% up and 5% down event as jumps in the series of these coefficients and we compare their realizations across the series of different stock markets for simultaneity. Finally we propose an indicator that can show the degree of co-movements in the extreme values of these coefficients for different frequencies.

Suggested Citation

  • Radu Lupu, 2014. "Simultaneity of Tail Events for Dynamic Conditional Distributions of Stock Market Index Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 49-64, December.
  • Handle: RePEc:rjr:romjef:v::y:2014:i:4:p:49-64
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    1. Knif, Johan & Pynnonen, Seppo, 1999. "Local and global price memory of international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(2), pages 129-147, April.
    2. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
    3. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    4. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous‐Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, June.
    5. Francois Chesnay & Eric Jondeau, 2001. "Does Correlation Between Stock Returns Really Increase During Turbulent Periods?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(1), pages 53-80, February.
    6. Alexandros Gabrielsen & Axel Kirchner & Zhuoshi Liu & Paolo Zagaglia, 2015. "Forecasting Value-At-Risk With Time-Varying Variance, Skewness And Kurtosis In An Exponential Weighted Moving Average Framework," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 1-29.
    7. Lucian Liviu Albu & Radu Lupu & Cantemir Adrian Călin & Oana Cristina Popovici, 2014. "Estimating the Impact of Quantitative Easing On Credit Risk through an ARMA-GARCH Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 39-50, October.
    8. William N. Goetzmann & Lingfeng Li & K. Geert Rouwenhorst, 2005. "Long-Term Global Market Correlations," The Journal of Business, University of Chicago Press, vol. 78(1), pages 1-38, January.
    9. Chelley-Steeley, Patricia L., 2005. "Modeling equity market integration using smooth transition analysis: A study of Eastern European stock markets," Journal of International Money and Finance, Elsevier, vol. 24(5), pages 818-831, September.
    10. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 373-401, June.
    11. Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003. "Alternative models for stock price dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 225-257.
    12. Philippe Jorion, 1988. "On Jump Processes in the Foreign Exchange and Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 427-445.
    13. Bjørn Eraker & Michael Johannes & Nicholas Polson, 2003. "The Impact of Jumps in Volatility and Returns," Journal of Finance, American Finance Association, vol. 58(3), pages 1269-1300, June.
    14. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    15. Stijn Claessens & Daniela Klingebiel & Sergio L. Schmukler, 2002. "The Future of Stock Exchanges in Emerging Economies: Evolution and Prosepcts," Center for Financial Institutions Working Papers 02-03, Wharton School Center for Financial Institutions, University of Pennsylvania.
    16. John M. Maheu & Thomas H. McCurdy, 2004. "News Arrival, Jump Dynamics, and Volatility Components for Individual Stock Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 755-793, April.
    17. Christoffersen, Peter, 2011. "Elements of Financial Risk Management," Elsevier Monographs, Elsevier, edition 2, number 9780123744487.
    18. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
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    Cited by:

    1. LUPU, Radu & MATEESCU, Alexandra, 2016. "Systemic Risk And Cojumps In High Frequency Data," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 20(4), pages 6-16.

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    More about this item

    Keywords

    simultaneity indicator; dynamic threshold for jump detection; dynamic skewness and kurtosis; Gram-Charlier likelihood; stock market comovements; extreme events;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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