Information Theoretic Ranking of Extreme Value Returns
Author
Abstract
Suggested Citation
DOI: 10.1007/s40953-020-00214-y
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012.
"Stochastic volatility models including open, close, high and low prices,"
Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
- Abel Rodriguez & Henryk Gzyl & German Molina & Enrique ter Horst, 2009. "Stochastic Volatility Models Including Open, Close, High and Low Prices," Papers 0901.1315, arXiv.org.
- 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.
- Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
- Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
- Marcus Alexander Ong, 2015. "An information theoretic analysis of stock returns, volatility and trading volumes," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3891-3906, August.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Jinghong Shu & Jin E. Zhang, 2006. "Testing range estimators of historical volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(3), pages 297-313, March.
- Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
- Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
- Hakki Ozturk & Umit Erol & Asli Yuksel, 2016. "Extreme Value Volatility Estimators and Realized Volatility of Istanbul Stock Exchange: Evidence from Emerging Market," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(8), pages 1-71, August.
- Neda Todorova & Sven Husmann, 2012. "A comparative study of range‐based stock return volatility estimators for the German market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(6), pages 560-586, June.
- Benoit Mandelbrot, 2015.
"The Variation of Certain Speculative Prices,"
World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78,
World Scientific Publishing Co. Pte. Ltd..
- Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394-394.
- Paul A. Samuelson, 1970. "The Fundamental Approximation Theorem of Portfolio Analysis in terms of Means, Variances and Higher Moments," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 37(4), pages 537-542.
- Beckers, Stan, 1983. "Variances of Security Price Returns Based on High, Low, and Closing Prices," The Journal of Business, University of Chicago Press, vol. 56(1), pages 97-112, January.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Thillaikkoothan Palanichamy & Parthajit Kayal, 2022. "Multiple Dimensions of Cyclicality in Investing," Working Papers 2022-216, Madras School of Economics,Chennai,India.
- Moinak Maiti & Parthajit Kayal, 2022. "Asymmetric Information Flow between Exchange Rate, Oil, and Gold: New Evidence from Transfer Entropy Approach," JRFM, MDPI, vol. 16(1), pages 1-14, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Parthajit Kayal & Sumanjay Dutta & Vipul Khandelwal, "undated". "Information Theoretic Ranking of Extreme Value Returns," Working Papers 2020-195, Madras School of Economics,Chennai,India.
- 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.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Lakshmi Padmakumari & S Maheswaran, 2016. "A Regression Based Approach to Capturing the Level Dependence in the Volatility of Stock Returns," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 6(12), pages 706-718, December.
- Christensen, Kim & Podolski, Mark, 2005. "Asymptotic theory for range-based estimation of integrated variance of a continuous semi-martingale," Technical Reports 2005,18, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013.
"On the predictability of stock prices: A case for high and low prices,"
Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.
- Massimiliano Caporin & Angelo Ranaldo & Paolo Santucci de Magistris, 2011. "On the Predictability of Stock Prices: A Case for High and Low Prices," "Marco Fanno" Working Papers 0136, Dipartimento di Scienze Economiche "Marco Fanno".
- Massimiliano Caporin & Angelo Ranaldo, 2011. "On the Predictability of Stock Prices: a Case for High and Low Prices," Working Papers 2011-11, Swiss National Bank.
- Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2012. "On the Predictability of Stock Prices: a Case for High and Low Prices," Working Papers on Finance 1213, University of St. Gallen, School of Finance.
- 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).
- Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012.
"Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range,"
International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
- Chen, C.W.S. & Gerlach, R. & Hwang, B.B.K. & McAleer, M.J., 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intraday Range," Econometric Institute Research Papers EI 2011-17, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
- Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," Documentos de Trabajo del ICAE 2011-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," Working Papers in Economics 11/22, University of Canterbury, Department of Economics and Finance.
- Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012.
"Stochastic volatility models including open, close, high and low prices,"
Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
- Abel Rodriguez & Henryk Gzyl & German Molina & Enrique ter Horst, 2009. "Stochastic Volatility Models Including Open, Close, High and Low Prices," Papers 0901.1315, arXiv.org.
- Aris Kartsaklas, 2018. "Trader Type Effects On The Volatility‐Volume Relationship Evidence From The Kospi 200 Index Futures Market," Bulletin of Economic Research, Wiley Blackwell, vol. 70(3), pages 226-250, July.
- Sergey S. Stepanov, 2009. "Resilience of Volatility," Papers 0911.5048, arXiv.org.
- Muneer Shaik & S. Maheswaran, 2019. "Robust Volatility Estimation with and Without the Drift Parameter," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(1), pages 57-91, March.
- Kumar, Dilip & Maheswaran, S., 2014. "A new approach to model and forecast volatility based on extreme value of asset prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 128-140.
- Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
- 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).
- Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
- 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.
- Dilip Kumar, 2018. "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 313-335, June.
- Xie, Haibin & Wu, Xinyu, 2017. "A conditional autoregressive range model with gamma distribution for financial volatility modelling," Economic Modelling, Elsevier, vol. 64(C), pages 349-356.
- Li, Hongquan & Hong, Yongmiao, 2011. "Financial volatility forecasting with range-based autoregressive volatility model," Finance Research Letters, Elsevier, vol. 8(2), pages 69-76, June.
More about this item
Keywords
Extreme value estimators; Information theory; Volatility;All these keywords.
JEL classification:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jqecon:v:19:y:2021:i:1:d:10.1007_s40953-020-00214-y. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.