Showing 1 - 8 of 8
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...
Persistent link: https://www.econbiz.de/10009578026
For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...
Persistent link: https://www.econbiz.de/10009578559
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data or a model estimated from the data. The methods that are available for implementing the bootstrap and the accuracy of bootstrap estimates depend on whether the data are a random...
Persistent link: https://www.econbiz.de/10009614877
Newly developed and advanced methods for nonlinear time series analysis are in general not available in standard software packages. Moreover, their implementation requires substantial time, computing power as well as programming skills. The recent results on lag and bandwidth selection methods...
Persistent link: https://www.econbiz.de/10009582397
VaR models are related to statistical forecast systems. Within that framework different forecast tasks including Value-at-Risk and shortfall are discussed and motivated. A backtesting method based on the shortfall is developed and applied to VaR forecasts of areal portfolio. The analysis shows...
Persistent link: https://www.econbiz.de/10009582401
Persistent link: https://www.econbiz.de/10009611560
The testing of a computing model for a stationary time series is a standard task in statistics. When a parametric approach is used to model the time series, the question of goodness-of-fit arises. In this paper, we employ the empirical likelihood for an a-mixing process and formulate a statistic...
Persistent link: https://www.econbiz.de/10009612573
The analysis of diffusion processes in financial models is crucially dependent on the form of the drift and diffusion coefficient functions. A methodology is proposed for estimating and testing coefficient functions for ergodic diffusions that are not directly observable. It is based on...
Persistent link: https://www.econbiz.de/10009613611