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Understanding the determinants of volatility clustering in terms of stationary Markovian processes

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  • Miccichè, S.

Abstract

Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ−β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock’s volatility is a linear function of the average correlation of such stock’s volatility with all other volatilities.

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  • Miccichè, S., 2016. "Understanding the determinants of volatility clustering in terms of stationary Markovian processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 186-197.
    • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:186-197
    DOI: 10.1016/j.physa.2016.06.081
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