The Beta-Skew-t-EGARCH model was recently proposed in literature to
model the volatility of financial returns. The inferences over the
parameters of the model are based on maximum likelihood method. These
estimators have good asymptotic properties, however in finite sample sizes
their performance can be poor. With the purpose of evaluating the finite
sample performance of point estimators and of the likelihood ratio test
proposed to the presence of two components of volatility, we present a Monte
Carlo simulation study. Numerical results indicate that the maximum
likelihood estimators of some parameters of the model are considerably
biased in sample sizes smaller than 3000. The evaluation results of the
proposed two-component test, in terms of size and power of the test, showed
its practical usefulness in sample sizes greater than 3000. At the end of
the work we present an application in a real data of the proposed
two-component test and the model Beta-Skew-t-EGARCH.