A BOOTSTRAP BIAS CORRECTION OF LONG RUN FOURTH ORDER MOMENT ESTIMATION IN THE CUSUM OF SQUARES TEST

Davide De Gaetano ()

No 220, Departmental Working Papers of Economics - University 'Roma Tre' from Department of Economics - University Roma Tre

Abstract: The aim of this paper is to propose a bias correction of the estimation of the long run fourth order moment in the CUSUM of squares test proposed by Sansó et al. (2004) for the detection of structural breaks in financial data. The correction is made by using the stationary bootstrap proposed by Politis and Romano (1994). The choice of this resampling technique is justified by the stationarity and weak dependence of the time series under the assumptions which ensure the existence of the limiting distribution of the test statistic, under the null hypothesis. Some Monte Carlo experiments have been implemented in order to evaluate the effect of the proposed bias correction considering two particular data generating processes, the GARCH(1,1) and the log-normal stochastic volatility. The effectiveness of the bias correction has been evaluated also on real data sets.

Keywords: CUSUM of squares test; Structural breaks; Bias correction. (search for similar items in EconPapers)
JEL-codes: C12 C58 G17 (search for similar items in EconPapers)
Pages: 41
Date: 2017-07
New Economics Papers: this item is included in nep-ecm and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:rtr:wpaper:0220

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