TY  - JOUR
T1  - Relationship Between the Impact of Exogenous Interventions on Arma and Garch Predictions
AU - , I.U. Moffat AU - , E.H. Etuk 
JO  - Research Journal of Applied Sciences
VL  - 2
IS  - 5
SP  - 611
EP  - 616
PY  - 2007
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2007.611.616
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2007.611.616
KW  - Additive outliers
KW  -ARMA model
KW  -exogenous interventions
KW  -GARCH model
KW  -prediction error
KW  -time series
AB  - A common problem encountered in high frequency financial time series is the occurrence of extreme observations, or significant spikes in volatility, with subsequent influence on model specification, parameter estimation and future predictions in ARMA and GARCH models. We present estimated biases of Garch(1,1) model coefficients by unrecognized exogenous interventions at unknown dates with particular attention to  additive level outliers. We further determine their approximate and simulated influences on estimated predictions through the inflation of innovation variance estimates. Our conclusion maintains that the severity of bias depends on the distance of an outlier from the prediction origin.
ER  -