Flexible stochastic volatility structures for high frequency financial data

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a simulation study and apply the test to the HFDF96 data set. Our results confirm a linear AR(1) structure for the analyzed stock indices S&P500, Dow Jones Industrial Average and for the exchange rate DEM/USD.