A Study for Forecasting Methods of ARMA-GARCH Model Using MCMC Approach Chae, Wha-Yeon; Choi, Bo-Seung; Kim, Kee-Whan; Park, You-Sung;
The volatility is one of most important parameters in the areas of pricing of financial derivatives an measuring risks arising from a sudden change of economic circumstance. We propose a Bayesian approach to estimate the volatility varying with time under a linear model with ARMA(p, q)-GARCH(r, s) errors. This Bayesian estimate of the volatility is compared with the ML estimate. We also present the probability of existence of the unit root in the GARCH model.
Volatility;GARCH model;Bayesian inference;MCMC;
김우환 (2011). GARCH_ARJI 모형을 활용한 KOSPI 수익률의 변동성에 관한 실증분석, <응용통계연구>, 24, 78-81.