DOI QR코드

DOI QR Code

Long Memory Characteristics in the Korean Stock Market Volatility

  • Cho, Sinsup (Department of Statistics, Seoul National University) ;
  • Choe, Hyuk (College of Business Administration, Seoul National University) ;
  • Park, Joon Y (School of Economics, Seoul National University)
  • Published : 2002.12.01

Abstract

For the estimation and test of long memory feature in volatilities of stock indices and individual companies semiparametric approach, Geweke and Porter-Hudak (1983), is employed. Empirical study supports the strong evidence of volatility persistence in Korean stock market. Most of indices and individual companies have the feature of long term dependence of volatility. Hence the short memory models are unable to explain the volatilities in Korean stock market.

Keywords

References

  1. 「계량경제학보」 v.9 AFRIMA with GARCH-M모형을 통한 주가변동위험의 추정 김진호
  2. 「중권학회지」 v.25 주가의 장기기억과 분수적분 일잔자기희귀 조건부 이분산 : 주가결정과정에 대한 한 탐구 이일균
  3. Journal of Time Series Analysis v.14 Bias in an estimator of the fractional difference parameter Agiakloglou, C.;Newbold, P.;Wohar, M. https://doi.org/10.1111/j.1467-9892.1993.tb00141.x
  4. Journal of Econometrics v.74 Fractionally integrated generalized autoregressive conditional heteroscedasticity Billie, R.;Bollerslev, T.;Mikkelsen, H. https://doi.org/10.1016/S0304-4076(95)01749-6
  5. Journal of Econometrics v.31 Generalized autoregressive conditional heteroskedastivity Bollerslev, T. https://doi.org/10.1016/0304-4076(86)90063-1
  6. Journal of Econometrics v.73 Modelling and pricing long memory in stock market volatility Bollerslev, T.;Mikkelsen, H. https://doi.org/10.1016/0304-4076(95)01736-4
  7. Journal of Econometrics v.83 The detection and estimation of long memory in stochastic volatility Breidt, F. J.;Crato, N.;de Lima, P. https://doi.org/10.1016/S0304-4076(97)00072-9
  8. Econometric Theor v.17 On the periodogram regression estimator of the memory parameter in long memory stochastic volatlity models Deo, R. S.;Hurvich, C. M. https://doi.org/10.1017/S0266466601174025
  9. Working Paper Estimation of long memory in volatility Deo, R. S.;Hurvich, C. M.
  10. Annals of Statistics v.7 A central limit theorem for parameter estimation in stationary vector time series and its application to model for a signal observed with noise Dunsmuir, W. https://doi.org/10.1214/aos/1176344671
  11. Econometrica v.50 Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation Engle, R. F. https://doi.org/10.2307/1912773
  12. Annals of Statistics v.14 Large sample properties of parameter estimates for storongly dependent stationary Gaussian time series Fox, R.;Taqqu, M. S. https://doi.org/10.1214/aos/1176349936
  13. Probability Theory and Related Fields v.86 A central limit theorem for quadratic form in strongly dependent linear variables and its application to Whittle's estimate Giraitis, R. F.;Surgailis, D. https://doi.org/10.1007/BF01207515
  14. Journal of Time Series Analysis v.1 An introduction to long memory time series models and fractional differencing Granger, C. W. J.;Joyeux, R. https://doi.org/10.1111/j.1467-9892.1980.tb00297.x
  15. Journal of Time Series Analysis v.4 The estimation and application of long memory time series models Geweke, J.;Porter-Hudak, S. https://doi.org/10.1111/j.1467-9892.1983.tb00371.x
  16. Working paper Long memory in stochastic volatility Harvey, A. C.
  17. Annals of Statistics v.25 A limit theory for long range dependence and statistical inference on related models Hosoya, Y. https://doi.org/10.1214/aos/1034276623
  18. Journal of Time Series Analysis v.19 The mean squared error of Geweke and Porter-Hudak's estimator of the momory parameter of a long-memory time series Hurvich, C. M.;Deo, R.;Brodsky, J. https://doi.org/10.1111/1467-9892.00075
  19. Working Paper Log peroidogram regression : the nonstationary case Kim, C. S.;Phillips, P. C. B.
  20. Working Paper Modified log periodegram regression Kim, C. S.;Phillips, P. C. B.
  21. Journal of Applied Probability v.23 Discrimination between monotonic trends and long-range dependence Kunsch, H. R. https://doi.org/10.2307/3214476
  22. Econometrica v.59 Conditional heteroskedasticity in asset returns : A new approach Nelson, D. B. https://doi.org/10.2307/2938260
  23. Journal of Econometrics v.47 Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regression Robinson, P. M. https://doi.org/10.1016/0304-4076(91)90078-R
  24. Annals of Statistics v.23 Log-periodogram regression of time series wit long range dependence Robinson, P. M. https://doi.org/10.1214/aos/1176324636
  25. Modeling Financial Time Series Taylor, S.
  26. Biometrika v.34 The cumulants of the z and of the logarithmic x² and t distributions Wishart, J.