شماره ركورد كنفرانس :
3503
عنوان مقاله :
Comparison of forecasting performance of long memory GARCH models and Markov switching GARCH models
Author/Authors :
E. Amiri Imam Khomeini International University
كليدواژه :
Long memory , MS-GARCH , Markov switching , GARCH , FIEGARCH
عنوان كنفرانس :
چهل و هفتمين كنفرانس رياضي ايران
چكيده لاتين :
It is well known that structural change or stochastic regime switching and long memory
are intimately related concepts . In an emprical study the forecasting performance of the long
memory GARCH models and Markov switching GARCH model are compared using Tehran stock
market returns. The results indicate that in out of sample performance, long memory exponential
GARCH (FIEGARCH) model outperforms the competing models.