Forecasting volatility with the realized range in the presence of noise and non-trading
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DOI: 10.1016/j.najef.2013.02.020
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- Bannouh, K. & Martens, M.P.E. & van Dijk, D.J.C., 2012. "Forecasting Volatility with the Realized Range in the Presence of Noise and Non-Trading," ERIM Report Series Research in Management ERS-2012-018-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
References listed on IDEAS
- Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
- Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
- Aït-Sahalia, Yacine & Mancini, Loriano, 2008. "Out of sample forecasts of quadratic variation," Journal of Econometrics, Elsevier, vol. 147(1), pages 17-33, November.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003.
"Modeling and Forecasting Realized Volatility,"
Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- Michael McAleer & Marcelo Medeiros, 2008.
"Realized Volatility: A Review,"
Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
- Michael McAleer & Marcelo Cunha Medeiros, 2006. "Realized volatility: a review," Textos para discussão 531 Publication status: F, Department of Economics PUC-Rio (Brazil).
- Martens, Martin & van Dijk, Dick, 2007.
"Measuring volatility with the realized range,"
Journal of Econometrics, Elsevier, vol. 138(1), pages 181-207, May.
- Martens, M.P.E. & van Dijk, D.J.C., 2006. "Measuring volatility with the realized range," Econometric Institute Research Papers EI 2006-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- 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.
- Christensen, Kim & Podolskij, Mark & Vetter, Mathias, 2006. "Bias-Correcting the Realized Range-Based Variance in the Presence of Market Microstructure Noise," Technical Reports 2006,52, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005.
"A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data,"
Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
- Lan Zhang & Per A. Mykland & Yacine Ait-Sahalia, 2003. "A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data," NBER Working Papers 10111, National Bureau of Economic Research, Inc.
- Peter Reinhard Hansen & Zhuo Huang & Howard Howan Shek, 2012. "Realized GARCH: a joint model for returns and realized measures of volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 877-906, September.
- Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
- Becker, Ralf & Clements, Adam E. & White, Scott I., 2006. "On the informational efficiency of S&P500 implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 17(2), pages 139-153, August.
- O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.
- Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
- Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
- Robert F. Engle, 2000.
"The Econometrics of Ultra-High Frequency Data,"
Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
- Robert F. Engle, 1996. "The Econometrics of Ultra-High Frequency Data," NBER Working Papers 5816, National Bureau of Economic Research, Inc.
- Jim Griffin & Roel Oomen, 2008. "Sampling Returns for Realized Variance Calculations: Tick Time or Transaction Time?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 230-253.
- 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.
- Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
- Ghysels, Eric & Sinko, Arthur, 2011. "Volatility forecasting and microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 257-271, January.
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- Chia-Lin Chang & Allen, David & McAleer, Michael, 2013.
"Recent developments in financial economics and econometrics: An overview,"
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- Chia-Lin Chang & David Allen & Michael McAleer, 2013. "Recent Developments in Financial Economics and Econometrics: An Overview," Tinbergen Institute Discussion Papers 13-021/III, Tinbergen Institute.
- Chia-Lin Chang & David Allen & Michael McAleer, 2013. "Recent Developments in Financial Economics and Econometrics: An Overview," Documentos de Trabajo del ICAE 2013-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Chang, C-L. & Allen, D.E. & McAleer, M.J., 2013. "Recent Developments in Financial Economics and Econometrics: An Overview," Econometric Institute Research Papers EI 2013-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Chia-Lin Chang & David Allen & Michael McAleer, 2013. "Recent Developments in Financial Economics and Econometrics: An Overview," Working Papers in Economics 13/06, University of Canterbury, Department of Economics and Finance.
- Chia-Lin Chang & David E Allen & Michael McAleer, 2013. "Recent Developments in Financial Economics and Econometrics:An Overview," KIER Working Papers 842, Kyoto University, Institute of Economic Research.
- Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
- Liu, Qiang & Liu, Yiqi & Liu, Zhi & Wang, Li, 2018. "Estimation of spot volatility with superposed noisy data," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 62-79.
- Vortelinos, Dimitrios I. & Lakshmi, Geeta, 2015. "Market risk of BRIC Eurobonds in the financial crisis period," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 295-310.
- Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015.
"Aggregate volatility expectations and threshold CAPM,"
The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
- Eser Arisoy & Aslihan Altay-Salih & Levent Akdeniz, 2015. "Aggregate Volatility Expectations and Threshold CAPM," Post-Print hal-01634175, HAL.
- Kearney, Fearghal & Murphy, Finbarr & Cummins, Mark, 2015. "An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 199-216.
- Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
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More about this item
Keywords
Realized variance; Realized range; Two time scales; High frequency data; Market microstructure noise; Forecasting;All these keywords.
JEL classification:
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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