Penerapan Model Dynamic Conditional Correlation GARCH Pada Data Saham

Article History

Submited : June 30, 2020
Published : July 23, 2021

Stock is one of the popular financial market instruments. Issuing shares are one of the company's choices when deciding to fund a company. The uncertainty of stock prices in the stock market is an important event to be taken into consideration in making a decision by investors so that a model is needed to describe a stock event. GARCH Dynamic Conditional Correlation (DCC) is a model with a conditional and variance time-dependent that describes the dynamics of stock volatility. This study discusses the DCC GARCH model equation which is applied to the LQ 45 data. The model obtained for BCA shares ?t = +  +  so it can be concluded that DCC GARCH is more appropriate for BCA shares.

References

  1. Firmansyah. Analisis Volatilitas Harga Kopi Internasional. Jakarta: Usahawan, 2006.
  2. Bollerslev, T. Modelling The Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized ARCH Model. Review of Economics and Statistics, 72,498-505, 1990.
  3. Engle, R.F. Dynamic Conditional Correlation - A Simple Class of Multivariate GARCH Model. Journal of Bussiness and Economic, Statistics, 20,339-350, 2002.
  4. Harris, H. and Sollis, R. Applied Time Series Modelling and Forecasting. Wiley, West Sussex, 2003.
  5. Cryer, J.D. Time Series Analysis. Boston:PWS-Kent Publishing Company, 1986.
  6. Enders,W. Appliied Econometric Time Series. Canada: Jhon Willey & Sons, Inc, 1995.

Downloads

Download data is not yet available.
Fulltext
statcounter