id: 01755434
dt: j
an: 01755434
au: Mittnik, S.; Paulauskas, V.; Rachev, S.T.
ti: Statistical inference in regression with heavy-tailed integrated variables.
so: Math. Comput. Modelling 34, No.9-11, 1145-1158 (2001).
py: 2001
pu: Elsevier Science Ltd. (Pergamon), Oxford
la: EN
cc: 
ut: infinite variance; financial modeling; cointegration; integrated variables
ci: 
li: doi:10.1016/S0895-7177(01)00123-6
ab: Summary: We consider the problem of statistical inference in a bivariate
    time series regression model when the innovations are heavy-tailed and
    the OLS estimator is used for parameter estimation. We develop the
    asymptotic theory for the OLS estimator and the corresponding
    $t$-statistics. Limit distributions, that enable us to construct
    confidence intervals for the estimated parameters, are obtained via
    Monte Carlo simulations. The approach allows the components of the
    innovation vector to have different tail behavior.
rv: