TY - JOUR
T1 - Selecting between autoregressive conditional heteroskedasticity models
T2 - An empirical application to the volatility of stock returns in Peru
AU - Rodriguez, Gabriel
PY - 2017
Y1 - 2017
N2 - An extensive family of univariate models of autoregressive conditional heteroskedasticity is applied to Peru's daily stock market returns for the period January 3, 1992 to March 30, 2012 with four different specifications related to the distribution of the disturbance term. This concerns capturing the asymmetries of the behavior of the volatility, as well as the presence of heavy tails in these time series. Using different statistical tests and different criteria, the results show that: (i) the FIGARCH (1,1)-t is the best model among all symmetric models while the FIEGARCH (1,1)-Sk is selected from the class of asymmetrical models. Also, the model FIAPARCH (1,1)-t is selected from the class of asymmetric power models; (ii) the three models capture well the behavior of the conditional volatility; (iii) however, the empirical distribution of the standardized residuals shows that the behavior of the tails is not well captured by either model; (iv) the three models suggest the presence of long memory with estimates of the fractional parameter close to the region of nonstationarity.
AB - An extensive family of univariate models of autoregressive conditional heteroskedasticity is applied to Peru's daily stock market returns for the period January 3, 1992 to March 30, 2012 with four different specifications related to the distribution of the disturbance term. This concerns capturing the asymmetries of the behavior of the volatility, as well as the presence of heavy tails in these time series. Using different statistical tests and different criteria, the results show that: (i) the FIGARCH (1,1)-t is the best model among all symmetric models while the FIEGARCH (1,1)-Sk is selected from the class of asymmetrical models. Also, the model FIAPARCH (1,1)-t is selected from the class of asymmetric power models; (ii) the three models capture well the behavior of the conditional volatility; (iii) however, the empirical distribution of the standardized residuals shows that the behavior of the tails is not well captured by either model; (iv) the three models suggest the presence of long memory with estimates of the fractional parameter close to the region of nonstationarity.
KW - Asymmetries
KW - GED distribution
KW - Normal
KW - Peruvian stock market returns
KW - Skewed t-Student
KW - Symmetries
KW - T-Student
KW - Univariate autoregressive conditional heteroskedasticity models
KW - Volatility
UR - http://www.scopus.com/inward/record.url?scp=85018306163&partnerID=8YFLogxK
U2 - 10.4067/S0718-88702017000100069
DO - 10.4067/S0718-88702017000100069
M3 - Article
AN - SCOPUS:85018306163
SN - 0716-5927
VL - 32
SP - 69
EP - 94
JO - Revista de Analisis Economico
JF - Revista de Analisis Economico
IS - 1
ER -