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

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  • Mario Bonino
  • Matteo Camelia
  • Paolo Pigato

Abstract

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, arXiv.org, revised Dec 2016.
    • Handle: RePEc:arx:papers:1404.7632
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    1. 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.
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    6. Duan Wang & Boris Podobnik & Davor Horvati'c & H. Eugene Stanley, 2011. "Quantifying and Modeling Long-Range Cross-Correlations in Multiple Time Series with Applications to World Stock Indices," Papers 1102.2240, arXiv.org.
    7. Ross, Gordon J., 2013. "Modelling financial volatility in the presence of abrupt changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(2), pages 350-360.
    8. Alessandro Andreoli & Francesco Caravenna & Paolo Dai Pra & Gustavo Posta, 2010. "Scaling and multiscaling in financial series: a simple model," Papers 1006.0155, arXiv.org, revised Apr 2012.
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    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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