Penerapan Model Dynamic Conditional Correlation GARCH Pada Data Saham

Abstract
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 𝑸t = + + so it can be concluded that DCC GARCH is more appropriate for BCA shares.