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Using High-Frequency Data in Dynamic Portfolio Choice
Citations
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Cited by:
- Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015.
"Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
- Hautsch, Nikolaus & Kyj, Lada. M. & Malec, Peter, 2013. "Do high-frequency data improve high-dimensional portfolio allocations?," SFB 649 Discussion Papers 2013-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- repec:hum:wpaper:sfb649dp2013-014 is not listed on IDEAS
- Qianqiu Liu, 2009. "On portfolio optimization: How and when do we benefit from high-frequency data?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 560-582.
- repec:uts:finphd:39 is not listed on IDEAS
- repec:ipg:wpaper:2014-053 is not listed on IDEAS
- Xiangyu Cui & Xuan Zhang, 2021. "Index tracking strategy based on mixed-frequency financial data," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-15, April.
- Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
- Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018.
"Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions,"
Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
- Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
- 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.
- Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
- Jianlei Han & Martina Linnenluecke & Zhangxin Liu & Zheyao Pan & Tom Smith, 2019. "A general equilibrium approach to pricing volatility risk," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.
- Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016.
"Intraday volatility interaction between the crude oil and equity markets,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
- Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2015. "Intraday volatility interaction between the crude oil and equity markets," Working Papers fe_2015_14, Deakin University, Department of Economics.
- Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
- Sergey Lototsky & Henry Schellhorn & Ran Zhao, 2016. "A String Model of Liquidity in Financial Markets," Papers 1608.05900, arXiv.org, revised Apr 2018.
- Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.
- Audrino, Francesco, 2014.
"Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks,"
Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
- Audrino, Francesco, 2011. "Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks," Economics Working Paper Series 1112, University of St. Gallen, School of Economics and Political Science.
- Sévi, Benoît, 2014.
"Forecasting the volatility of crude oil futures using intraday data,"
European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
- Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Working Papers 2014-53, Department of Research, Ipag Business School.
- Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Post-Print hal-01463921, HAL.
- Lucey, Brian & Sevic, Aleksandar, 2010.
"Investigating the determinants of banking coexceedances in Europe in the summer of 2008,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(3), pages 275-283, July.
- Brian Lucey* School of Business and Institute for International Integration Studies,Trinity College Dublin Aleksandar Ševic, School of Business, Trinity College Dublin, 2009. "Investigating the Determinants of Banking Coexceedances in Europe in the Summer of 2008," The Institute for International Integration Studies Discussion Paper Series iiisdp301, IIIS.
- 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.
- Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
- Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018, January-A.
- 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.
- Fulvio Corsi & Francesco Audrino, 2012.
"Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects,"
Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 591-616, September.
- Fulvio Corsi & Francesco Audrino, 2008. "Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects," University of St. Gallen Department of Economics working paper series 2008 2008-04, Department of Economics, University of St. Gallen.
- M.C. M�nnix & R. Sch�fer & O. Grothe, 2014. "Estimating correlation and covariance matrices by weighting of market similarity," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 931-939, May.
- Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
- Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
- Gael M. Martin & Andrew Reidy & Jill Wright, 2009.
"Does the option market produce superior forecasts of noise-corrected volatility measures?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
- Gael M. Martin & Andrew Reidy & Jill Wright, 2007. "Does the Option Market Produce Superior Forecasts of Noise-Corrected Volatility Measures?," Monash Econometrics and Business Statistics Working Papers 5/07, Monash University, Department of Econometrics and Business Statistics.
- Vincenzo Candila, 2013. "A Comparison of the Forecasting Performances of Multivariate Volatility Models," Working Papers 3_228, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
- Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
- Michael Johannes & Arthur Korteweg & Nicholas Polson, 2014. "Sequential Learning, Predictability, and Optimal Portfolio Returns," Journal of Finance, American Finance Association, vol. 69(2), pages 611-644, April.
- repec:uts:finphd:38 is not listed on IDEAS
- Jying‐Nan Wang & Hung‐Chun Liu & Jiangze Du & Yuan‐Teng Hsu, 2019. "Economic benefits of technical analysis in portfolio management: Evidence from global stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(2), pages 890-902, April.