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A multivariate model for financial indices and an algorithm for detection of jumps in the volatility


  • Mario Bonino
  • Matteo Camelia
  • Paolo Pigato


We consider a mean-reverting stochastic volatility model which satisfies some relevant stylized facts of financial markets. We introduce an algorithm for the detection of peaks in the volatility profile, that we apply to the time series of Dow Jones Industrial Average and Financial Times Stock Exchange 100 in the period 1984-2013. Based on empirical results, we propose a bivariate version of the model, for which we find an explicit expression for the decay over time of cross-asset correlations between absolute returns. We compare our theoretical predictions with empirical estimates on the same financial time series, finding an excellent agreement.

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  • Mario Bonino & Matteo Camelia & Paolo Pigato, 2014. "A multivariate model for financial indices and an algorithm for detection of jumps in the volatility," Papers 1404.7632,, revised Dec 2016.
  • Handle: RePEc:arx:papers:1404.7632

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    References listed on IDEAS

    1. Alessandro Andreoli & Francesco Caravenna & Paolo Dai Pra & Gustavo Posta, 2010. "Scaling and multiscaling in financial series: a simple model," Papers 1006.0155,, revised Apr 2012.
    2. B. Podobnik & D. F. Fu & H. E. Stanley & P. Ch. Ivanov, 2007. "Power-law autocorrelated stochastic processes with long-range cross-correlations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 56(1), pages 47-52, March.
    3. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Ole E. Barndorff‐Nielsen & Neil Shephard, 2001. "Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 167-241.
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    Cited by:

    1. Dai Pra, P. & Pigato, P., 2015. "Multi-scaling of moments in stochastic volatility models," Stochastic Processes and their Applications, Elsevier, vol. 125(10), pages 3725-3747.

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