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http://dx.doi.org/10.5351/KJAS.2011.24.2.293

A Study for Forecasting Methods of ARMA-GARCH Model Using MCMC Approach  

Chae, Wha-Yeon (Citibank Korea Inc.)
Choi, Bo-Seung (Department of Computer Science and Statistics, Daegu University)
Kim, Kee-Whan (Department of Information and Statistics, Korea University)
Park, You-Sung (Department of Statistics, Korea University)
Publication Information
The Korean Journal of Applied Statistics / v.24, no.2, 2011 , pp. 293-305 More about this Journal
Abstract
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.
Keywords
Volatility; GARCH model; Bayesian inference; MCMC;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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