Estimating Fluctuating Volatility Using Advanced Garch Models: Evidence from Denmark Stock Exchange

In the stock market, volatility is a term used to describe the degree to which the prices of assets oscillate and determines the level of risk or uncertainty. The foremost objective of the present analysis is to model the behaviour of the Denmark stock market using data from December 20, 2016, to September 20, 2023. Through the application of GARCH family prototypes which, include GARCH/TARCH, EGARCH, Component ARCH (1,1), and PARCH. The analysis used a sample number of 1668 daily observations for OMXC 25 or OMX Copenhagen 25 Stock Index representing the Denmark stock market. We used some statistical techniques such as Phillips-Perron and Augmented Dickey Fuller tests, Kwiatkowski-Phillips-Schmidt-Shin test statistic, The ARCH Lagrange Multiplier (LM) test, PARCH model. We utilized the E-Views 12 Econometrics package. This empirical investigation adds to the corpus of financial econometrics and emphasizes the importance of precisely and painstakingly modelling the behaviour of stock markets. Our ability to forecast market movements and make informed decisions in a turbulent financial climate will be improved by the findings and research methodologies covered in this paper, which will serve as a solid foundation for future investigations. Keywords: Volatility, Uncertainty, Forecasting, GARCH family prototypes, stock marketplace, heteroscedasticity.