Stochastic Volatility with Heterogeneous Time Scales
AbstractAgents' heterogeneity is recognized as a driver mechanism for the persistence of financial volatility. We focus on the multiplicity of investment strategies' horizons, we embed this concept in a continuous time stochastic volatility framework and prove that a parsimonious, two-scale version effectively captures the long memory as measured from the real data. Since estimating parameters in a stochastic volatility model is challenging, we introduce a robust methodology based on the Generalized Method of Moments supported by a heuristic selection of the orthogonal conditions. In addition to the volatility clustering, the estimated model also captures other relevant stylized facts, emerging as a minimal but realistic and complete framework for modelling financial time series.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1206.0026.
Date of creation: May 2012
Date of revision: Apr 2013
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