Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/192583 
Year of Publication: 
2009
Series/Report no.: 
Discussion Papers No. 601
Publisher: 
Statistics Norway, Research Department, Oslo
Abstract: 
This paper aims to develop new methods for statistical inference in a class of stochastic volatility models for financial data based on non-Gaussian Ornstein-Uhlenbeck (OU) processes. Our approach uses indirect inference methods: First, a quasi-likelihood for the actual data is estimated. This quasi-likelihood is based on an approximative Gaussian state space representation of the OU-based model. Next, simulations are made from the data generating OU-model for given parameter values. The indirect inference estimator is the parameter value in the OU-model which gives the best "match" between the quasi-likelihood estimator for the actual data and the quasi-likelihood estimator for the simulated data. Our method is applied to Euro/NOK and US Dollar/NOK daily exchange rates for the period 1.7.1989 until 15.12.2008. Accompanying R-package, that interfaces C++ code is documented and can be downloaded.
Subjects: 
stochastic volatility
financial econometrics
Ornstein-Uhlenbeck processes
indirect inference
state space models
exchange rates
JEL: 
C13
C22
C51
G10
Document Type: 
Working Paper

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