We review the Lagrange Multiplier (LM) test for detection of non-linear features through a robust analysis with forward search tool of Atkinson and Riani (2000). We focus on test for detection of ARCH components. Robust estimators of regression coefficients and graphical tools give insights into the structure and the effect of influential observations. We show how difficult can be to identify the order of the underlying ARCH model. Influential observations are monitored through t−statistics of the LM test, yielding to difficult identification of ARCH order.
Robust detection of nonlinearity in financial time series
GROSSI, Luigi;
2006-01-01
Abstract
We review the Lagrange Multiplier (LM) test for detection of non-linear features through a robust analysis with forward search tool of Atkinson and Riani (2000). We focus on test for detection of ARCH components. Robust estimators of regression coefficients and graphical tools give insights into the structure and the effect of influential observations. We show how difficult can be to identify the order of the underlying ARCH model. Influential observations are monitored through t−statistics of the LM test, yielding to difficult identification of ARCH order.
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