IDEAS home Printed from https://ideas.repec.org/r/eee/finana/v23y2012icp20-29.html
   My bibliography  Save this item

Properties of range-based volatility estimators

Citations

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


Cited by:

  1. Seiler, Volker, 2024. "The relationship between Chinese and FOB prices of rare earth elements – Evidence in the time and frequency domain," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 160-179.
  2. Jonathan A. Batten & Cetin Ciner & Brian M. Lucey, 2015. "Which precious metals spill over on which, when and why? Some evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 466-473, April.
  3. Aneta Wlodarczyk & Iwona Otola, 2016. "Analysis of the Relationship between Market Volatility and Firms Volatility on the Polish Capital Market," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 87-116.
  4. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2019. "Range-based DCC models for covariance and value-at-risk forecasting," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 58-76.
  5. Lepori, Gabriele M., 2023. "Acute illness symptoms among investment professionals and stock market dynamics: Evidence from New York City," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 165-181.
  6. Bazán-Palomino, Walter, 2023. "The increased interest in Bitcoin and the immediate and long-term impact of Bitcoin volatility on global stock markets," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1080-1095.
  7. Lyócsa, Štefan, 2014. "Growth-returns nexus: Evidence from three Central and Eastern European countries," Economic Modelling, Elsevier, vol. 42(C), pages 343-355.
  8. Brian M. Lucey & Charles Larkin & Fergal O'Connor, 2014. "Gold markets around the world - who spills over what, to whom, when?," Applied Economics Letters, Taylor & Francis Journals, vol. 21(13), pages 887-892, September.
  9. Alexandre Aidov & Olesya Lobanova, 2021. "Volatility and Depth in Commodity and FX Futures Markets," JRFM, MDPI, vol. 14(11), pages 1-16, November.
  10. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
  11. Peter Arendas & Jana Kotlebova, 2019. "The Turn of the Month Effect on CEE Stock Markets," IJFS, MDPI, vol. 7(4), pages 1-19, October.
  12. Vortelinos, Dimitrios I., 2014. "Optimally sampled realized range-based volatility estimators," Research in International Business and Finance, Elsevier, vol. 30(C), pages 34-50.
  13. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
  14. Shi, Yanlin & Ho, Kin-Yip, 2015. "Long memory and regime switching: A simulation study on the Markov regime-switching ARFIMA model," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 189-204.
  15. Khoo, Zhi De & Ng, Kok Haur & Koh, You Beng & Ng, Kooi Huat, 2024. "Forecasting volatility of stock indices: Improved GARCH-type models through combined weighted volatility measure and weighted volatility indicators," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
  16. Lyócsa, Štefan & Todorova, Neda, 2024. "Forecasting of clean energy market volatility: The role of oil and the technology sector," Energy Economics, Elsevier, vol. 132(C).
  17. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
  18. Vyrost, Tomas & Baumöhl, Eduard & Lyocsa, Stefan, 2013. "What Drives the Stock Market Integration in the CEE-3?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 61(1), pages 67-81.
  19. Fałdziński, Marcin & Fiszeder, Piotr & Molnár, Peter, 2024. "Improving volatility forecasts: Evidence from range-based models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
  20. Bašta, Milan & Molnár, Peter, 2018. "Oil market volatility and stock market volatility," Finance Research Letters, Elsevier, vol. 26(C), pages 204-214.
  21. Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America, Middle East, and BRICs," Economic Systems, Elsevier, vol. 39(2), pages 253-268.
  22. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
  23. Roman Horváth & Štefan Lyócsa & Eduard Baumöhl, 2018. "Stock market contagion in Central and Eastern Europe: unexpected volatility and extreme co-exceedance," The European Journal of Finance, Taylor & Francis Journals, vol. 24(5), pages 391-412, March.
  24. Huynh, Nhan & Phan, Hoa, 2023. "Emotions in the crypto market: Do photos really speak?," Finance Research Letters, Elsevier, vol. 55(PB).
  25. Zaremba, Adam, 2019. "Price range and the cross-section of expected country and industry returns," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 174-189.
  26. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.
  27. Kim, Neri & Lučivjanská, Katarína & Molnár, Peter & Villa, Roviel, 2019. "Google searches and stock market activity: Evidence from Norway," Finance Research Letters, Elsevier, vol. 28(C), pages 208-220.
  28. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(4), pages 445-463, October.
  29. Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.
  30. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
  31. Peter Molnár, 2016. "High-low range in GARCH models of stock return volatility," Applied Economics, Taylor & Francis Journals, vol. 48(51), pages 4977-4991, November.
  32. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
  33. José Luis Miralles-Quirós & María Mar Miralles-Quirós, 2021. "Alternative Financial Methods for Improving the Investment in Renewable Energy Companies," Mathematics, MDPI, vol. 9(9), pages 1-25, May.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.