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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제14권 제4호
- 발행연도
- 2012.1
- 수록면
- 1,749 - 1,758 (10page)
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초록· 키워드
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Volatility is known to be an important characteristic that measures the variation of stock price over time. This paper proposes a prediction method for the volatility of a composite KOSPI via a Bayesian approach. For this, Bayesian model averaging procedure, based on a full Bayesian analysis of EGARCH models, is proposed. The procedure, consists of parameter estimation, model comparison, and volatility prediction. Analysis of each step is fully described, which involves implementation of Markov chain Monte Carlo (MCMC) methodology such as the Metropolis-Hastings algorithm and reversible-jump strategy. Details of MCMC implementation in each step using a composite KOSPI data are provided.
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참고문헌 (18)
참고문헌 신청
Bolleslev, T. / 1986 / Generalized autoregressive conditional heteroskedasticity / Journal of Economentrics 31 : 307 ~ 327
Bolleslev, T. / 1992 / ARCH modeling in finance-A review of the theory andempirical evidence / Journal of Economentrics 52 : 5 ~ 59
Engle, R. F. / 1982 / Autoregressive conditional heteroskedasticity with estimate of the variance of United Kingdom Inflation / Econometrica 50 : 987 ~ 1007
Gelfand, A. / 1990 / Sampling based approaches to calculating marginal densities / Journal of the American Statistical Association 85 : 398 ~ 409
Geman, S. / 1984 / Stochastic relaxation, Gibbs distributions and Bayesian restoration of images / IEEE Transactions on Pattern Analysis and Machine Intelligence 6 : 721 ~ 74
Bolleslev, T. / 1992 / ARCH modeling in finance-A review of the theory andempirical evidence / Journal of Economentrics 52 : 5 ~ 59
Engle, R. F. / 1982 / Autoregressive conditional heteroskedasticity with estimate of the variance of United Kingdom Inflation / Econometrica 50 : 987 ~ 1007
Gelfand, A. / 1990 / Sampling based approaches to calculating marginal densities / Journal of the American Statistical Association 85 : 398 ~ 409
Geman, S. / 1984 / Stochastic relaxation, Gibbs distributions and Bayesian restoration of images / IEEE Transactions on Pattern Analysis and Machine Intelligence 6 : 721 ~ 74
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