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Locally adaptive estimation methods with application to univariate time series
The paper offers a unified approach to the study of three locally adaptive estimation methods in the context of univariate time series from both theoretical and empirical points of view. A general procedure for the computation of critical values is given. The underlying model encompasses all distributions from the exponential family providing for great flexibility. The procedures are applied to simulated and real financial data distributed according to the Gaussian, volatility, Poisson, exponential and Bernoulli models. Numerical results exhibit a very reasonable performance of the methods
Locally time homogeneous time series modelling
In this paper three locally adaptive estimation methods are applied to the problems of variance forecasting, value-at-risk analysis and volatility estimation within the context of nonstationary financial time series. A general procedure for the computation of critical values is given. Numerical results exhibit a very reasonable performance of the methods.