heteroscedasticity and autocorrelation in asset returns are the primary sources of test mis-specification in these linearity …-in-the-mean hypothesis tests. To address this problem, an innovative approach is proposed to control heteroscedasticity and autocorrelation … the theme of the previous two studies, the effects of heteroscedasticity and autocorrelation are examined in the portfolio …

slowly decaying periodic behaviour of autocorrelation function and pronounced peaks in periodogram but residuals analysis … model because higher frequencies might not be obvious from autocorrelation function or periodogram. However, we face …

measure of determinants or heteroscedasticity. Both cases are considered in the empirical sections of this thesis. In the …

inefficiencies are sensitive to specification errors. One source of such errors is heteroscedasticity. This paper addresses this … issue by extending the Hadri (1999) correction for heteroscedasticity to stochastic production frontiers and to panel data …. It is argued that heteroscedasticity within an estimation can have a significant effect on results, and that correcting …

applicationsexhibit heteroscedasticity. The practical importance of detecting heteroscedasticityin regression analysis is widely …

The Durbin Watson, DW, test for first order autocorrelation in regression residuals is among the most widely applied … errors in a seasonal model. Considering the PAR(1) process, we show such errors display both (seasonal) autocorrelation and … heteroscedasticity, even if the original data is homoscedastic. However, there is no reason to suppose the implications of PAR(1) errors …