Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/177673
Year of Publication: 
2017
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 17-105/III
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
In recent years fractionally differenced processes have received a great deal of attention due to their flexibility in financial applications with long memory. In this paper, we develop a new realized stochastic volatility (RSV) model with general Gegenbauer long memory (GGLM), which encompasses a new RSV model with seasonal long memory (SLM). The RSV model uses the information from returns and realized volatility measures simultaneously. The long memory structure of both models can describe unbounded peaks apart from the origin in the power spectrum. For estimating the RSV-GGLM model, we suggest estimating the location parameters for the peaks of the power spectrum in the first step, and the remaining parameters based on the Whittle likelihood in the second step. We conduct Monte Carlo experiments for investigating the finite sample properties of the estimators, with a quasi-likelihood ratio test of RSV-SLM model against the RSV-GGLM model. We apply the RSV-GGLM and RSV-SLM model to three stock market indices. The estimation and forecasting results indicate the adequacy of considering general long memory.
Subjects: 
Stochastic Volatility
Realized Volatility Measure
Long Memory
Gegenbauer Polynomial
Seasonality
Whittle Likelihood
JEL: 
C18
C21
C58
Document Type: 
Working Paper

Files in This Item:
File
Size
315.06 kB





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