• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.295-307
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• 2023

The heterogeneous autoregressive (HAR) model is a simple linear model that is commonly used to explain long memory in the realized volatility. However, as realized volatility has more complicated features such as conditional heteroscedasticity, leverage effect, and volatility clustering, it is necessary to extend the simple HAR model. Therefore, to better incorporate the stylized facts, we propose a threshold HAR model with GARCH errors, namely the THAR-GARCH model. That is, the THAR-GARCH model is a nonlinear model whose coefficients vary according to a threshold value, and the conditional heteroscedasticity is explained through the GARCH errors. Model parameters are estimated using an iterative weighted least squares estimation method. Our simulation study supports the consistency of the iterative estimation method. In addition, we show that the proposed THAR-GARCH model has better forecasting power by applying to the realized volatility of major 21 stock indices around the world.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.267-267
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• 2016

Extreme events, such as Winnie(1987), Rusa(2002), Maemi(2003) at sea-side urban area, resulted not only economic losses but also life losses. The Korean sea-side characterisitcs are so complicated thar the prediction of sea level rise makes difficult. Geomophologically, Korean pennisula sits on the rim of the Pacific mantle so the sea level is sensitive to the surges due to earth quake, typoon and abnormal climate changes. These environmetns require closer investigation for the preparing the inundatioin due to the sea level rise with customized prediction for local basin. The goal of this research is provide the information of inundation risk so the sea side urban basin could be more safe from the natural water disastesr.