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    A Comparison of Volatility Models in the Korean Stock Market

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    https://www.riss.kr/link?id=A104006764

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    This paper attempted, on the basis of the data of KOSPI200 daily returns and 10 minute intraday returns, to identify which one of GARCH-family models is the more suitable in modelling the volatility of Korean stock market returns. We performed a comparative analysis of a set of 252 GARCH-family models. It was found, first, that the asymmetric EGARCH and GJR-GARCH models can better explain the behavior of KOSPI200 daily returns than the others. Also, the t-distribution or GED distribution were found more appropriate in accounting for the distribution of error terms. Second, it was found that the EGARCH and APARCH models are better in explaining the pattern of intraday returns of KOSPI200. Higher-order models were more suitable for intraday returns, in contrast to daily returns. As for the distribution of error term, the t-distribution was much better than normal and GED distribution. Third, asymmetric models like EGARCH and GJR-GARCH models exhibit a lower loss functions. The asymmetric GARCH models with non normal error distribution tend to improve the volatility forecast of stock returns. To sum, the asymmetric models were found more appropriate to account for both daily and intraday returns of KOSPI200. And low-order models are recommended for daily returns and high-order models for intraday returns.
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    This paper attempted, on the basis of the data of KOSPI200 daily returns and 10 minute intraday returns, to identify which one of GARCH-family models is the more suitable in modelling the volatility of Korean stock market returns. We performed a compa...

    This paper attempted, on the basis of the data of KOSPI200 daily returns and 10 minute intraday returns, to identify which one of GARCH-family models is the more suitable in modelling the volatility of Korean stock market returns. We performed a comparative analysis of a set of 252 GARCH-family models. It was found, first, that the asymmetric EGARCH and GJR-GARCH models can better explain the behavior of KOSPI200 daily returns than the others. Also, the t-distribution or GED distribution were found more appropriate in accounting for the distribution of error terms. Second, it was found that the EGARCH and APARCH models are better in explaining the pattern of intraday returns of KOSPI200. Higher-order models were more suitable for intraday returns, in contrast to daily returns. As for the distribution of error term, the t-distribution was much better than normal and GED distribution. Third, asymmetric models like EGARCH and GJR-GARCH models exhibit a lower loss functions. The asymmetric GARCH models with non normal error distribution tend to improve the volatility forecast of stock returns. To sum, the asymmetric models were found more appropriate to account for both daily and intraday returns of KOSPI200. And low-order models are recommended for daily returns and high-order models for intraday returns.

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    참고문헌 (Reference)

    1 이경희, "중국, 홍콩 및 대만 주식시장간 변동성의 동적인 관련성에 대한 연구" 한국경영교육학회 28 (28): 279-298, 2013

    2 정헌용, "외부쇼크와 한국주식시장의 반응" 한국경영교육학회 28 (28): 119-141, 2013

    3 김상수, "스왑시장의 자산시장에 대한 변동성전이효과와 정책적 시사점" 한국경영교육학회 28 (28): 351-368, 2013

    4 김경수, "미국의 금융충격이 한국과 ASEAN 주식시장에 미친 영향" 한국경영교육학회 27 (27): 85-113, 2012

    5 김경수, "다변량 GARCH모형을 이용한 호주, 싱가포르, 영국 및 미국 주식시장간의 비대칭적 변동성의 관련성" 한국경영교육학회 27 (27): 31-48, 2012

    6 Hannan, E. J., "The estimation of the order of an ARMA process" 8 (8): 937-1178, 1980

    7 Corhay, A., "Statistical properties of daily returns: Evidence from European stock markets" 21 : 271-282, 1994

    8 Hurvich, C.M., "Regression and time series model selection in small samples" 76 : 297-307, 1989

    9 Awartani, B.M.A., "Predicting the volatility of the S&P-500stock index via GARCH models: the role of asymmetries" 21 : 167-183, 2005

    10 Chong, C., "Performance of GARCH models in forecasting stock market volatility" 18 : 333-343, 1999

    1 이경희, "중국, 홍콩 및 대만 주식시장간 변동성의 동적인 관련성에 대한 연구" 한국경영교육학회 28 (28): 279-298, 2013

    2 정헌용, "외부쇼크와 한국주식시장의 반응" 한국경영교육학회 28 (28): 119-141, 2013

    3 김상수, "스왑시장의 자산시장에 대한 변동성전이효과와 정책적 시사점" 한국경영교육학회 28 (28): 351-368, 2013

    4 김경수, "미국의 금융충격이 한국과 ASEAN 주식시장에 미친 영향" 한국경영교육학회 27 (27): 85-113, 2012

    5 김경수, "다변량 GARCH모형을 이용한 호주, 싱가포르, 영국 및 미국 주식시장간의 비대칭적 변동성의 관련성" 한국경영교육학회 27 (27): 31-48, 2012

    6 Hannan, E. J., "The estimation of the order of an ARMA process" 8 (8): 937-1178, 1980

    7 Corhay, A., "Statistical properties of daily returns: Evidence from European stock markets" 21 : 271-282, 1994

    8 Hurvich, C.M., "Regression and time series model selection in small samples" 76 : 297-307, 1989

    9 Awartani, B.M.A., "Predicting the volatility of the S&P-500stock index via GARCH models: the role of asymmetries" 21 : 167-183, 2005

    10 Chong, C., "Performance of GARCH models in forecasting stock market volatility" 18 : 333-343, 1999

    11 Al-Marshadi, A. H., "New procedure to improve the order selection of autoregressive time series model" 7 (7): 270-274, 2011

    12 Magnus, F., "Modelling and forecasting volatility of returns of the Ghana stock exchange rate using GARCH models" 3 : 2042-2048, 2006

    13 Aladag, C. H., "Improving weighted information criterion by using optimization" 233 : 2683-2687, 2010

    14 Bollerslev, T., "Generalized autoregressive conditional heteroscedasticity" 31 : 307-327, 1986

    15 Javed, F., "GARCH-Type models and performance of information criteria" 42 (42): 1917-1933, 2013

    16 Engle, R. F., "GARCH 101: The use of ARCH/GARCH models in applied econometrics" 15 : 157-168, 2001

    17 Apolinario, R. M. C., "Day of the week effects on European stock markets" 2 : 53-70, 2006

    18 Kadilar, C., "Comparison of performance among information criteria in var and seasonal var models" 31 : 127-137, 2002

    19 Hurvich, C.M., "Bias of the corrected AIC criterion for underfitted regression and time series models" 78 : 499-509, 1991

    20 Engle, R. F., "Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation" 50 : 987-1007, 1982

    21 Nazar, D., "Asymmetry effects of information on information uncertainty in Iran. Using from EGARCH model" 7 : 535-539, 2010

    22 Bengtsson, T., "An improved akaike information criterion for state-space model selection" 10 : 2635-2654, 2006

    23 Hansen, P.R., "A forecast comparison of volatility models: Does anything beat a GARCH(1,1)" 20 : 873-889, 2005

    24 Nakamura, T., "A comparative study of information criteria for model selection" 8 : 2153-2175, 2006

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    연월일 이력구분 이력상세 등재구분
    2026 평가 재인증평가 신청대상 (재인증)
    2020-01-01 등재 등재학술지 유지 (재인증) KCI등재
    2017-01-01 등재 등재학술지 유지 (계속평가) KCI등재
    2013-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2011-01-24 학술지명변경 한글명 : 경영교육논총 -> 경영교육연구 KCI등재
    2010-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2007-01-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2006-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2005-01-01 등재 등재후보 1차 FAIL (등재후보2차) KCI등재후보
    2004-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2003-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 1.39 1.39 1.34
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    1.3 1.28 1.351 0.59
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