Agents' 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.
|Titolo:||Stochastic Volatility with Heterogeneous Time Scales|
|Data di pubblicazione:||2015|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1080/14697688.2015.1024159|
|Appare nelle tipologie:||1.1 Articolo in rivista|