Macroeconomic and financial time series are often tested for the presence of non-linearity effects. Sometimes, small patches of extremal observations may wrongly influence non-linearity tests. In this paper, a robust analysis of the Lagrange multiplier (LM) test for GARCH components is suggested. Using Monte-Carlo simulations we show that extreme observations might cause over-estimation of the number of GARCH components, with the main contribution consisting by introducing the forward search method into the GARCH model family. Using robust estimators of regression coefficients and graphical displays of results, the effect of influential observations on estimates can be efficiently monitored. Analysing macroeconomic and financial time series we show that identifying the order of a GARCH model can be unduly influenced by a few isolated large values, and extremal observations affect p-values and t-statistics in an unexpected manner.

Analysis of economic time series: effects of extremal observations on testing heteroscedastic components

GROSSI, Luigi;
2004

Abstract

Macroeconomic and financial time series are often tested for the presence of non-linearity effects. Sometimes, small patches of extremal observations may wrongly influence non-linearity tests. In this paper, a robust analysis of the Lagrange multiplier (LM) test for GARCH components is suggested. Using Monte-Carlo simulations we show that extreme observations might cause over-estimation of the number of GARCH components, with the main contribution consisting by introducing the forward search method into the GARCH model family. Using robust estimators of regression coefficients and graphical displays of results, the effect of influential observations on estimates can be efficiently monitored. Analysing macroeconomic and financial time series we show that identifying the order of a GARCH model can be unduly influenced by a few isolated large values, and extremal observations affect p-values and t-statistics in an unexpected manner.
GARCH models; Influential observations; Lagrange multiplier test
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/230239
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 4
social impact