본문 바로가기 주메뉴 바로가기
kiep logo

Contents

Citation

Citation
No Title

Abstract

This study has attempted to seek a volatility forecasting model that can reflect sufficiently the long memory characteristic in the volatility of four Eastern European emerging stock markets, naThis study has attempted to seek a volatility forecasting model that can reflect sufficiently the long memory characteristic in the volatility of four Eastern European emerging stock markets, namely, Hungary, Poland, Russia, and Slovakia. From the results of our empirical analysis, we found that the FIGARCH model is better equipped to capture the long memory property in the volatility of these markets than the GARCH and IGARCH models. More importantly, the FIGARCH model is found to provide superior performance in one-day-ahead volatility forecasts. Thus, this study recommends researchers, portfolio managers, and traders to use the long memory FIGARCH model in analyzing and forecasting the volatility dynamics of Eastern European emerging markets.

JEL classification: C22, C52, G12

Keywords

Eastern European, Emerging Market, Volatility, Long Memory, FIGARCH, DM Test

Language

Korean

References

  1. Baillie, Richard T., Tim Bollerslev, and Hans Ole Mikkelsen. 1996. "Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity." journal of Econometrics, 74 (1), pp. 3-30. CrossRef
  2. Bentes, Sonia R., Rui Menezes, and Diana A. Mendes. 2008. "Long Memory and Volatility Clustering: Is the Empirical Evidence Consistent Across Stock Markets?" Physica A, 387 (15), pp. 3826-3830. CrossRef
  3. Bollerslev, Tim. 1986. "Generalized Autoregressive Conditional Heteroskedasticity." journal of Econometrics, 31 (3), pp. 307-327. CrossRef
  4. Bollerslev, Tim and Jeffrey M. Wooldridge. 1992. "Quasi-Maximum Likelihood Estimation of Dynamic Models with Time Varying Covariances." Econometric Reviews, 11 (2), pp. 143-172. CrossRef
  5. Brailsford, Timothy J. and Robert W. Faff. 1996. "An Evaluation of Volatility Forecasting Techniques." journal of Banking & Finance, 20 (3), pp. 419-438. CrossRef
  6. Brooks, Chris and Gita Persand. 2003. "Volatility Forecasting for Risk Management." journal of Forecasting, 22 (1), pp. 1-22. CrossRef
  7. Coricelli, Fabrizio and Elena Ianchovichina. 2004. "Managing Volatility in Transition Economies: The Experience of the Central and Eastern European Countries." Discussion Papers No. 4413. CEPR.
  8. Degiannakis, Stavros. 2004. "Volatility Forecasting, Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model." journal Applied Financial Economics, 14 (18), pp. 1333-1342. CrossRef
  9. Diebold, Francis X. and Roberto S. Mariano. 1995. "Comparing Predictive Accuracy." journal of Business & Economic Statistics, 13 (3), pp. 253-263. CrossRef
  10. Dionisio, Andreia, Rui Menezes, and Diana A. Mendes. 2007. "On the Integrated Behaviour of Non-stationary Volatility in Stock Markets." Physica A, 382 (1), pp. 58-65. CrossRef
  11. Egert, Balazs and Yosra Koubaa. 2004. "Modelling Stock Returns in the G-7 and in Selected CEE Economies: A Non-Linear GARCH Approach." Working Paper No. 663. William Davidson Institute.
  12. Engle, Robert F. 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation." Econometrica, 50 (4), pp. 987-1007. CrossRef
  13. Engle, Robert F. and Tim Bollerslev. 1986. "Modelling the Persistence of Conditional Variances." Econometric Reviews, 5 (1), pp. 1-50. CrossRef
  14. Granger, C. W. J. 1980. "Long Memory Relationships and the Aggregation of Dynamic Models." journal of Econometrics, 14 (2), pp. 227-238. CrossRef
  15. Hosking, J. R. M. 1981. "Fractional Differencing." Biometrika, 68 (1), pp. 165-176. CrossRef
  16. Jansen, Marion. 2004. "Income Volatility in Small and Developing Economies: Export Concentration Matters." Discussion Paper No. 3. ERSD, World Trade Organization.
  17. Kang, Sang Hoon and Seong-Min Yoon. 2007. "Long Memory Properties in Return and Volatility: Evidence from the Korean Stock Market." Physica A, 385 (2), pp. 591-600. CrossRef
  18. Kasman, Adnan, Saadet Kasman, and Erdost Torun. 2009. "Dual Long Memory Property in Returns and Volatility: Evidence from the CEE Countries' Stock Markets." Emerging Markets Review, 10 (2), pp. 122-139. CrossRef
  19. Kilic, Rehim. 2004. "On the Long Memory Properties of Emerging Capital Markets: Evidence from Istanbul Stock Market." Applied Financial Economics, 14 (13), pp. 915-922.
  20. Lux, Thomas and Taisei Kaizoji. 2007. "Forecasting Volatility and Volume in the Tokyo Stock Market, Long Memory, Fractality and Regime Switching." journal of Economic Dynamics and Control, 31 (6), pp. 1808-1843. CrossRef
  21. McMillan, David G. and Pako Thupayagale. 2008. "Efficiency of the South African Equity Market." Applied Financial Economics Letters, 4 (5), pp. 327-330. CrossRef
  22. McMillan, David G. and Isabel Ruiz. 2009. "Volatility Persistence, Long Memory and Time-Varying Unconditional Mean: Evidence from 10 Equity Indices." Quarterly Review of Economics and Finance, 49 (2), pp. 578-595. CrossRef
  23. Poon, Ser-Huang and Clive W. J. Granger. 2003. "Forecasting Volatility in Financial Markets, A Review." journal of Economic Literature, 41 (2), pp. 478-539. CrossRef
  24. Scheicher, Martin. 2001. "The Comovements of Stock Markets in Hungary, Poland and the Czech Republic." International journal of Finance & Economics, 6 (1), pp. 27-39. CrossRef
  25. Vilasuso, Jon. 2002. "Forecasting Exchange Rate Volatility." Economics Letters, 76 (1), pp. 59-64. CrossRef
  26. Wang, Ping and Tomoe Moore. 2009. "Sudden Changes in Volatility, The Case of Five Central European Stock Markets." journal of International Financial Markets, Institutions and Money, 19 (1), pp. 33-46. CrossRef
  27. Yoon, Seong-Min and Sang Hoon Kang. 2007. "A Skewed Student-t Value-at-Risk Approach for Long Memory Volatility Processes in Japanese Financial Markets." journal of international Economic Studies, 11 (1), pp. 211-242.
  28. Zumbach, Gilles. 2004. "Volatility Processes and Volatility Forecast with Long Memory." Quantitative Finance, 4 (1), pp. 70-86. CrossRef