Investigating the effect of estimating ARCH model parameters on financial process control charts
Volume 7, Issue 2, Summer 2017, Pages 106-113
Mohammad Hadi Doroudyan, Mohammadsaleh Avlia, Amir Hossain Amiri, Hojatollah Sadeghi
Abstract Identifying significant changes in key indicators of financial processes is one of the points of interest in recent years and after the financial crisis. Control charts are one of the most powerful tools used in this field. A noteworthy point in the practical use of control charts is the estimation of process parameters based on available data. Despite extensive research into the effect of parameter estimation on the performance of control charts, little research has been done on processes with time-dependent observations. Due to the importance and widespread use of the Auto Regressive Conditional Heteroskedasticity (ARCH) time series model in monitoring financial processes, in this paper, the effect of prototype size for estimating model parameters on the performance of phase 2 control charts is investigated. The performance of each control diagram is evaluated using simulation studies based on AARL and SDARL criteria and the results are described.