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Multiple time scales and the exponential Ornstein-Uhlenbeck stochastic volatility model

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  • Jaume Masoliver
  • Josep Perello

Abstract

We study the exponential Ornstein-Uhlenbeck stochastic volatility model and observe that the model shows a multiscale behaviour in the volatility autocorrelation. It also exhibits a leverage correlation and a probability profile for the stationary volatility which are consistent with market observations. All these features make the model quite appealing since it appears to be more complete than other stochastic volatility models also based on a two-dimensional diffusion. We finally present an approximate solution for the return probability density designed to capture the kurtosis and skewness effects.

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  • Jaume Masoliver & Josep Perello, 2006. "Multiple time scales and the exponential Ornstein-Uhlenbeck stochastic volatility model," Quantitative Finance, Taylor & Francis Journals, vol. 6(5), pages 423-433.
    • Handle: RePEc:taf:quantf:v:6:y:2006:i:5:p:423-433
    DOI: 10.1080/14697680600727547
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    3. M A Sánchez-Granero & J E Trinidad-Segovia & J Clara-Rahola & A M Puertas & F J De las Nieves, 2017. "A model for foreign exchange markets based on glassy Brownian systems," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-22, December.
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    8. Alexander Subbotin & Thierry Chauveau & Kateryna Shapovalova, 2009. "Volatility Models: from GARCH to Multi-Horizon Cascades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00390636, HAL.
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    13. 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.
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    19. Buchbinder, G.L. & Chistilin, K.M., 2007. "Multiple time scales and the empirical models for stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 168-178.

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