Please use this identifier to cite or link to this item:
Delpini, Danilo
Bormetti, Giacomo
Year of Publication: 
Series/Report no.: 
Quaderni di Dipartimento 128
In this work we afford the statistical characterization of a linear Stochastic Volatility Model featuring Inverse Gamma stationary distribution for the high frequency volatility. We detail the derivation of the moments of the return distribution, revealing the role of the Inverse Gamma law in the emergence of fat tails, and of the relevant correlation functions. We also propose a systematic methodology for estimating the parameters, and we describe the empirical analysis of the Standard & Poor 500 index daily returns, confirming the ability of the model to capture many of the established stylized fact as well as the scaling properties of empirical distributions over different time horizons.
Document Type: 
Working Paper

Files in This Item:
294.96 kB

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.