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Asymmetry Effects in Volatility on the Major European Stock Markets: the EGARCH Based Approach

  • Received: 15 June 2017 Accepted: 31 October 2017 Published: 13 December 2017
  • The main goal of this paper is to investigate the asymmetric impact of innovations on volatility in the case of the largest European stock markets in the United Kingdom, France and Germany by using the EGARCH based approach. The sample period begins in January 2003 and ends in December 2016, and it includes the 2007 U.S. subprime crisis. The robustness analysis of empirical results is provided with respect to the whole sample and three adjacent subsamples, each of equal size: 1) the pre-crisis, 2) the Global Financial Crisis (GFC) and 3) the post-crisis periods. The GFC periods are formally detected by using a statistical method of dividing market states into bullish and bearish markets. Moreover, the common trading window procedure is employed to avoid the nonsynchronous trading problem in the group of investigated markets and to get the overlapping information set. We estimate univariate EGARCH models based on daily percentage logarithmic returns of major stock market indexes: FTSE100 (London), CAC40 (Paris), and DAX (Frankfurt). Pronounced negative asymmetry effects in volatility are presented in the case of all markets and are rather robust to the choice of the period. Our findings are consistent with the literature and suggest that the major European stock markets are more sensitive to 'bad' than 'good' news.

    Citation: Joanna Olbrys, Elzbieta Majewska. Asymmetry Effects in Volatility on the Major European Stock Markets: the EGARCH Based Approach[J]. Quantitative Finance and Economics, 2017, 1(4): 411-427. doi: 10.3934/QFE.2017.4.411

    Related Papers:

  • The main goal of this paper is to investigate the asymmetric impact of innovations on volatility in the case of the largest European stock markets in the United Kingdom, France and Germany by using the EGARCH based approach. The sample period begins in January 2003 and ends in December 2016, and it includes the 2007 U.S. subprime crisis. The robustness analysis of empirical results is provided with respect to the whole sample and three adjacent subsamples, each of equal size: 1) the pre-crisis, 2) the Global Financial Crisis (GFC) and 3) the post-crisis periods. The GFC periods are formally detected by using a statistical method of dividing market states into bullish and bearish markets. Moreover, the common trading window procedure is employed to avoid the nonsynchronous trading problem in the group of investigated markets and to get the overlapping information set. We estimate univariate EGARCH models based on daily percentage logarithmic returns of major stock market indexes: FTSE100 (London), CAC40 (Paris), and DAX (Frankfurt). Pronounced negative asymmetry effects in volatility are presented in the case of all markets and are rather robust to the choice of the period. Our findings are consistent with the literature and suggest that the major European stock markets are more sensitive to 'bad' than 'good' news.


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