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Properties of Bias-Corrected Realized Variance Under Alternative Sampling Schemes

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Cited by:

  1. Bollerslev, Tim & Kretschmer, Uta & Pigorsch, Christian & Tauchen, George, 2009. "A discrete-time model for daily S & P500 returns and realized variations: Jumps and leverage effects," Journal of Econometrics, Elsevier, vol. 150(2), pages 151-166, June.
  2. Bertrand Maillet & Jean-Philippe Médecin & Thierry Michel, 2009. "High Watermarks of Market Risks," Post-Print halshs-00425585, HAL.
  3. Chaboud, Alain P. & Chiquoine, Benjamin & Hjalmarsson, Erik & Loretan, Mico, 2010. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 212-240, March.
  4. Maheu, John M. & McCurdy, Thomas H., 2011. "Do high-frequency measures of volatility improve forecasts of return distributions?," Journal of Econometrics, Elsevier, vol. 160(1), pages 69-76, January.
  5. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
  6. Large, Jeremy, 2011. "Estimating quadratic variation when quoted prices change by a constant increment," Journal of Econometrics, Elsevier, vol. 160(1), pages 2-11, January.
  7. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.
  8. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
  9. Marcelo C. Carvalho & Marco Aurélio S. Freire & Marcelo Cunha Medeiros & Leonardo R. Souza, 2006. "Modeling and Forecasting the Volatility of Brazilian Asset Returns: a Realized Variance Approach," Brazilian Review of Finance, Brazilian Society of Finance, vol. 4(1), pages 55-77.
  10. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
  11. MArcelo Carvalho & MArco Aurelio Freire & Marcelo Cunha Medeiros & Leonardo Souza, 2006. "Modeling and forecasting the volatility of Brazilian asset returns," Textos para discussão 530, Department of Economics PUC-Rio (Brazil).
  12. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2008. "A multivariate integer count hurdle model: theory and application to exchange rate dynamics," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 31-48, Springer.
  13. Bandi, Federico M. & Russell, Jeffrey R., 2011. "Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations," Journal of Econometrics, Elsevier, vol. 160(1), pages 145-159, January.
  14. Cartea, Álvaro & Karyampas, Dimitrios, 2011. "Volatility and covariation of financial assets: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3319-3334.
  15. Todorova, Neda & Worthington, Andrew & Souček, Michael, 2014. "Realized volatility spillovers in the non-ferrous metal futures market," Resources Policy, Elsevier, vol. 39(C), pages 21-31.
  16. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
  17. Wuyts, Gunther, 2008. "The impact of liquidity shocks through the limit order book," CFS Working Paper Series 2008/53, Center for Financial Studies (CFS).
  18. Bannouh, K. & van Dijk, D.J.C. & Martens, M.P.E., 2008. "Range-based covariance estimation using high-frequency data: The realized co-range," Econometric Institute Research Papers EI 2007-53, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  19. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
  20. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
  21. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
  22. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
  23. Christian T. Brownlees & Giampiero M. Gallo, 2010. "Comparison of Volatility Measures: a Risk Management Perspective," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 29-56, Winter.
  24. Wu, Liuren, 2011. "Variance dynamics: Joint evidence from options and high-frequency returns," Journal of Econometrics, Elsevier, vol. 160(1), pages 280-287, January.
  25. Vuorenmaa, Tommi A., 2008. "Decimalization, Realized Volatility, and Market Microstructure Noise," MPRA Paper 8692, University Library of Munich, Germany.
  26. Bandi, Federico M. & Russell, Jeffrey R. & Yang, Chen, 2008. "Realized volatility forecasting and option pricing," Journal of Econometrics, Elsevier, vol. 147(1), pages 34-46, November.
  27. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
  28. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
  29. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
  30. Jiang, George J. & Oomen, Roel C.A., 2008. "Testing for jumps when asset prices are observed with noise-a "swap variance" approach," Journal of Econometrics, Elsevier, vol. 144(2), pages 352-370, June.
  31. Vortelinos, Dimitrios I., 2015. "The Greek equity market in European equity portfolios," Economic Modelling, Elsevier, vol. 49(C), pages 144-153.
  32. Josip Arneriæ & Mario Matkoviæ, 2019. "Challenges of integrated variance estimation in emerging stock markets," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(2), pages 713-739.
  33. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
  34. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
  35. Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Effect of Long Memory in Volatility on Stock Market Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 684-700, November.
  36. Ingmar Nolte & Valeri Voev, 2011. "Least Squares Inference on Integrated Volatility and the Relationship Between Efficient Prices and Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 94-108, April.
  37. Mike Buckle & Jing Chen & Julian Williams, 2014. "How Predictable Are Equity Covariance Matrices? Evidence from High‐Frequency Data for Four Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(7), pages 542-557, November.
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