Robust online scale estimation in time series
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Date
2007-05-25T12:39:28Z
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Abstract
This paper presents variance extraction procedures for univariate time
series. The volatility of a times series is monitored allowing for non-linearities,
jumps and outliers in the level. The volatility is measured using the height of
triangles formed by consecutive observations of the time series. This idea was
proposed by Rousseeuw and Hubert (1996, Regression-free and robust estimation
of scale for bivariate data, Computational Statistics and Data Analysis, 21, 67{85)
in the bivariate setting. This paper extends their procedure to apply for online
scale estimation in time series analysis. The statistical properties of the new
methods are derived and finite sample properties are given. A financial and a
medical application illustrate the use of the procedures.
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Keywords
Breakdown point, Influence function, Online monitoring, Outliers, Robust scale estimation