IDEAS home Printed from
   My bibliography  Save this item

Long-Range Dependence in Daily Stock Volatilities


Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

Cited by:

  1. Per Frederiksen & Morten Orregaard Nielsen, 2008. "Bias-Reduced Estimation of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(4), pages 496-512, Fall.
  2. Gil-Alana, Luis A. & Gupta, Rangan, 2014. "Persistence and cycles in historical oil price data," Energy Economics, Elsevier, vol. 45(C), pages 511-516.
  3. DiSario, Robert & Saraoglu, Hakan & McCarthy, Joseph & Li, Hsi, 2008. "Long memory in the volatility of an emerging equity market: The case of Turkey," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 305-312, October.
  4. G. Mesters & S. J. Koopman & M. Ooms, 2016. "Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 659-687, April.
  5. Frederiksen, Per & Nielsen, Frank S. & Nielsen, Morten Ørregaard, 2012. "Local polynomial Whittle estimation of perturbed fractional processes," Journal of Econometrics, Elsevier, vol. 167(2), pages 426-447.
  6. Lux, Thomas & Kaizoji, Taisei, 2007. "Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1808-1843, June.
  7. Paulo Ferreira, 2020. "Dynamic long-range dependences in the Swiss stock market," Empirical Economics, Springer, vol. 58(4), pages 1541-1573, April.
  8. Asai, Manabu & McAleer, Michael, 2015. "Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance," Journal of Econometrics, Elsevier, vol. 189(2), pages 251-262.
  9. Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149,, revised Jan 2019.
  10. Tobias Hartl & Roland Weigand, 2018. "Approximate State Space Modelling of Unobserved Fractional Components," Papers 1812.09142,, revised May 2020.
  11. Ghassan, Hassan Belkacem & AlHajhoj, Hassan Rafdan, 2016. "Long run dynamic volatilities between OPEC and non-OPEC crude oil prices," Applied Energy, Elsevier, vol. 169(C), pages 384-394.
  12. KALNINA, Ilze, 2015. "Inference for nonparametric high-frequency estimators with an application to time variation in betas," Cahiers de recherche 2015-08, Universite de Montreal, Departement de sciences economiques.
  13. Garvey, John & Gallagher, Liam A., 2013. "The economics of data: Using simple model-free volatility in a high-frequency world," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 370-379.
  14. Serda S. Öztürk & Thanasis Stengos, 2017. "A Multivariate Stochastic Volatility Model Applied to a Panel of S&P500 Stocks in Different Industries," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 479-490, September.
  15. Clifford M. Hurvich & Eric Moulines & Philippe Soulier, 2005. "Estimating Long Memory in Volatility," Econometrica, Econometric Society, vol. 73(4), pages 1283-1328, July.
  16. Cathy Ning & Dinghai Xu & Tony Wirjanto, 2009. "Modeling Asymmetric Volatility Clusters Using Copulas and High Frequency Data," Working Papers 006, Ryerson University, Department of Economics.
  17. Wang, Lu & Zhang, Rong & Yang, Lin & Su, Yang & Ma, Feng, 2018. "Pricing geometric Asian rainbow options under fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 8-16.
  18. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2015. "Is volatility clustering of asset returns asymmetric?," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 62-76.
  19. Jeonggyu Huh, 2018. "Measuring Systematic Risk with Neural Network Factor Model," Papers 1809.04925,
  20. Chalamandaris, Georgios & Rompolis, Leonidas S., 2012. "Exploring the role of the realized return distribution in the formation of the implied volatility smile," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1028-1044.
  21. Wang, Xiao-Tian & Wu, Min & Zhou, Ze-Min & Jing, Wei-Shu, 2012. "Pricing European option with transaction costs under the fractional long memory stochastic volatility model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1469-1480.
  22. Sun, Yiguo & Hsiao, Cheng & Li, Qi, 2011. "Measuring correlations of integrated but not cointegrated variables: A semiparametric approach," Journal of Econometrics, Elsevier, vol. 164(2), pages 252-267, October.
  23. Engle, Robert F. & Marcucci, Juri, 2006. "A long-run Pure Variance Common Features model for the common volatilities of the Dow Jones," Journal of Econometrics, Elsevier, vol. 132(1), pages 7-42, May.
  24. Hassan Ghassan & Prashanta Banerjee, 2015. "A threshold cointegration analysis of asymmetric adjustment of OPEC and non-OPEC monthly crude oil prices," Empirical Economics, Springer, vol. 49(1), pages 305-323, August.
  25. Bhandari, Avishek, 2020. "Long memory and fractality among global equity markets: A multivariate wavelet approach," MPRA Paper 99653, University Library of Munich, Germany.
  26. Huh, Jeonggyu, 2020. "Measuring systematic risk with neural network factor model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
  27. Gordon V. Chavez, 2019. "Dynamic tail inference with log-Laplace volatility," Papers 1901.02419,, revised Jul 2019.
  28. John Elder & Sriram Villupuram, 2012. "Persistence in the return and volatility of home price indices," Applied Financial Economics, Taylor & Francis Journals, vol. 22(22), pages 1855-1868, November.
IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.