Volatility on financial markets has been an interesting phenomenon for researchers and practicians during the past decades and nowadays it is still one of the most active research topics of financial econometrics. The turbulent period of the past eight years has only confirmed significant effects of time-varying volatility on the financial markets as well as the entire global economy. The development of econometric models of volatility has progressed hand in hand with their application in academ... show full abstractVolatility on financial markets has been an interesting phenomenon for researchers and practicians during the past decades and nowadays it is still one of the most active research topics of financial econometrics. The turbulent period of the past eight years has only confirmed significant effects of time-varying volatility on the financial markets as well as the entire global economy. The development of econometric models of volatility has progressed hand in hand with their application in academia and financial industry. This development has triggered pronounced need for more efficient volatility modelling framework and we can indeed witness gradual shift from simple parametric models based on daily data to more complex stochastic models based on high-frequency data. This thesis illustrates the trend using estimation and subsequent comparison of an extremely popular GARCH (1,1) model with HAR-RV model and its extensions. |