Open AccessPenerapan Model Dynamic Conditional Correlation GARCH Pada Data Saham
Author(s) -
Ika Fitriana,
Erna Tri Herdiani,
Georgina Maria Tinungki
Publication year - 2021
Publication title -
estimasi
Language(s) - English
Resource type - Journals
eISSN - 2721-3803
pISSN - 2721-379X
DOI - 10.20956/ejsa.v2i2.10569
Subject(s) - autoregressive conditional heteroskedasticity , volatility (finance) , econometrics , conditional variance , stock (firearms) , stock market , economics , financial economics , engineering , geography , mechanical engineering , context (archaeology) , archaeology
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.