Investigating the risk-return trade-off for crude oil futures using high-frequency data
Author
Abstract
Suggested Citation
DOI: 10.1016/j.apenergy.2016.11.112
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
- Ji, Qiang & Guo, Jian-Feng, 2015. "Oil price volatility and oil-related events: An Internet concern study perspective," Applied Energy, Elsevier, vol. 137(C), pages 256-264.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007.
"Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility,"
The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," CREATES Research Papers 2007-18, Department of Economics and Business Economics, Aarhus University.
- Haugom, Erik & Langeland, Henrik & Molnár, Peter & Westgaard, Sjur, 2014. "Forecasting volatility of the U.S. oil market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 1-14.
- Zhang, Yue-Jun & Zhang, Lu, 2015. "Interpreting the crude oil price movements: Evidence from the Markov regime switching model," Applied Energy, Elsevier, vol. 143(C), pages 96-109.
- Pettinau, Alberto & Ferrara, Francesca & Amorino, Carlo, 2012. "Techno-economic comparison between different technologies for a CCS power generation plant integrated with a sub-bituminous coal mine in Italy," Applied Energy, Elsevier, vol. 99(C), pages 32-39.
- Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
- Yu, Jun, 2012.
"A semiparametric stochastic volatility model,"
Journal of Econometrics, Elsevier, vol. 167(2), pages 473-482.
- Jun Yu, 2008. "A Semiparametric Stochastic Volatility Model," Working Papers CoFie-04-2008, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
- Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011.
"A reduced form framework for modeling volatility of speculative prices based on realized variation measures,"
Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
- Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
- Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
- Cifarelli, Giulio & Paladino, Giovanna, 2010.
"Oil price dynamics and speculation: A multivariate financial approach,"
Energy Economics, Elsevier, vol. 32(2), pages 363-372, March.
- Giulio Cifarelli & Giovanna Paladino, 2008. "Oil price Dynamics and Speculation. A Multivariate Financial Approach," Working Papers - Economics wp2008_15.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
- Lucas, Andre, 2000.
"A Note on Optimal Estimation from a Risk-Management Perspective under Possibly Misspecified Tail Behavior,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 31-39, January.
- Lucas, André, 1997. "A note on optimal estimation from a risk management perspective under possibly mis-specified tail behavior," Serie Research Memoranda 0056, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
- Xin Huang & George Tauchen, 2005. "The Relative Contribution of Jumps to Total Price Variance," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 456-499.
- Sévi, Benoît, 2013.
"An empirical analysis of the downside risk-return trade-off at daily frequency,"
Economic Modelling, Elsevier, vol. 31(C), pages 189-197.
- Benoît Sévi, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Post-Print hal-01500860, HAL.
- Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Wang, Tianyang, 2016. "An examination of the flow characteristics of crude oil: Evidence from risk-neutral moments," Energy Economics, Elsevier, vol. 54(C), pages 213-223.
- Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
- Souček, Michael & Todorova, Neda, 2013. "Realized volatility transmission between crude oil and equity futures markets: A multivariate HAR approach," Energy Economics, Elsevier, vol. 40(C), pages 586-597.
- Broda, Simon A. & Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013.
"Stable mixture GARCH models,"
Journal of Econometrics, Elsevier, vol. 172(2), pages 292-306.
- Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
- Conlon, Thomas & Cotter, John, 2013.
"Downside risk and the energy hedger's horizon,"
Energy Economics, Elsevier, vol. 36(C), pages 371-379.
- Thomas Conlon & John Cotter, 2012. "Downside risk and the energy hedger's horizon," Working Papers 201219, Geary Institute, University College Dublin.
- Shakouri, Mahmoud & Lee, Hyun Woo & Choi, Kunhee, 2015. "PACPIM: New decision-support model of optimized portfolio analysis for community-based photovoltaic investment," Applied Energy, Elsevier, vol. 156(C), pages 607-617.
- Zhang, Xibin & King, Maxwell L., 2008.
"Box-Cox stochastic volatility models with heavy-tails and correlated errors,"
Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
- Xibin Zhang & Maxwell L. King, 2004. "Box-Cox Stochastic Volatility Models with Heavy-Tails and Correlated Errors," Monash Econometrics and Business Statistics Working Papers 26/04, Monash University, Department of Econometrics and Business Statistics.
- Shen, Zhiwei & Ritter, Matthias, 2016.
"Forecasting volatility of wind power production,"
Applied Energy, Elsevier, vol. 176(C), pages 295-308.
- Shen, Zhiwei & Ritter, Matthias, 2015. "Forecasting volatility of wind power production," SFB 649 Discussion Papers 2015-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Cotter, John & Hanly, Jim, 2010.
"Time-varying risk aversion: An application to energy hedging,"
Energy Economics, Elsevier, vol. 32(2), pages 432-441, March.
- John Cotter & Jim Hanly, 2010. "Time Varying Risk Aversion: An Application to Energy Hedging," Working Papers 201007, Geary Institute, University College Dublin.
- John Cotter & Jim Hanly, 2011. "Time Varying Risk Aversion: An Application to Energy Hedging," Papers 1103.5968, arXiv.org.
- 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.
- Galsband, Victoria, 2012. "Downside risk of international stock returns," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2379-2388.
- Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009.
"Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms,"
The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
- Benjamin Y. Zhang & Hao Zhou & Haibin Zhu, 2005. "Explaining credit default swap spreads with the equity volatility and jump risks of individual firms," Finance and Economics Discussion Series 2005-63, Board of Governors of the Federal Reserve System (U.S.).
- Haibin Zhu & Benjamin Yibin Zhang & Hao Zhou, 2005. "Explaining credit default swap spreads with equity volatility and jump risks of individual firms," BIS Working Papers 181, Bank for International Settlements.
- Asger Lunde & Peter R. Hansen, 2005.
"A forecast comparison of volatility models: does anything beat a GARCH(1,1)?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
- Kolos, Sergey P. & Ronn, Ehud I., 2008. "Estimating the commodity market price of risk for energy prices," Energy Economics, Elsevier, vol. 30(2), pages 621-641, March.
- Bollerslev, Tim & Osterrieder, Daniela & Sizova, Natalia & Tauchen, George, 2013. "Risk and return: Long-run relations, fractional cointegration, and return predictability," Journal of Financial Economics, Elsevier, vol. 108(2), pages 409-424.
- William J. Baumol, 1963. "An Expected Gain-Confidence Limit Criterion for Portfolio Selection," Management Science, INFORMS, vol. 10(1), pages 174-182, October.
- Efimova, Olga & Serletis, Apostolos, 2014.
"Energy markets volatility modelling using GARCH,"
Energy Economics, Elsevier, vol. 43(C), pages 264-273.
- Olga Efimova & Apostolos Serletis, "undated". "Energy Markets Volatility Modelling using GARCH," Working Papers 2014-39, Department of Economics, University of Calgary, revised 24 Feb 2014.
- Tauchen, George & Zhou, Hao, 2011.
"Realized jumps on financial markets and predicting credit spreads,"
Journal of Econometrics, Elsevier, vol. 160(1), pages 102-118, January.
- George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
- Yi Hu & Dongmei Guo & Mingxi Wang & Xi Zhang & Shouyang Wang, 2015. "The Relationship between Energy Consumption and Economic Growth: Evidence from China’s Industrial Sectors," Energies, MDPI, vol. 8(9), pages 1-15, August.
- 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.
- Kristoufek, Ladislav, 2014.
"Leverage effect in energy futures,"
Energy Economics, Elsevier, vol. 45(C), pages 1-9.
- Kristoufek, Ladislav, 2014. "Leverage effect in energy futures," FinMaP-Working Papers 17, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
- Feng, Zhen-Hua & Wei, Yi-Ming & Wang, Kai, 2012.
"Estimating risk for the carbon market via extreme value theory: An empirical analysis of the EU ETS,"
Applied Energy, Elsevier, vol. 99(C), pages 97-108.
- Zhen-Hua Feng & Yi-Ming Wei & Kai Wang, 2011. "Estimating risk for the carbon market via extreme value theory: An empirical analysis of the EU ETS," CEEP-BIT Working Papers 19, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
- Bali, Turan G. & Demirtas, K. Ozgur & Levy, Haim, 2009. "Is There an Intertemporal Relation between Downside Risk and Expected Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 883-909, August.
- Carl Chiarella & Boda Kang & Christina Sklibosios Nikitopoulos & Thuy‐Duong Tô, 2016.
"The Return–Volatility Relation in Commodity Futures Markets,"
Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(2), pages 127-152, February.
- Carl Chiarella & Boda Kang & Christina Sklibosios Nikitopoulos & Thuy-Duong To, 2013. "The Return-Volatility Relation in Commodity Futures Markets," Research Paper Series 336, Quantitative Finance Research Centre, University of Technology, Sydney.
- Contreras, Javier & Rodríguez, Yeny E., 2014. "GARCH-based put option valuation to maximize benefit of wind investors," Applied Energy, Elsevier, vol. 136(C), pages 259-268.
- Gorbacheva, Natalya V. & Sovacool, Benjamin K., 2015. "Pain without gain? Reviewing the risks and rewards of investing in Russian coal-fired electricity," Applied Energy, Elsevier, vol. 154(C), pages 970-986.
- Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
- Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
- Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
- Price, Kelly & Price, Barbara & Nantell, Timothy J, 1982. "Variance and Lower Partial Moment Measures of Systematic Risk: Some Analytical and Empirical Results," Journal of Finance, American Finance Association, vol. 37(3), pages 843-855, June.
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.- Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
- Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
- Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
- Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.
- Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
- Feng Ma & Yu Wei & Wang Chen & Feng He, 2018. "Forecasting the volatility of crude oil futures using high-frequency data: further evidence," Empirical Economics, Springer, vol. 55(2), pages 653-678, September.
- Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
- Degiannakis, Stavros & Filis, George, 2017.
"Forecasting oil price realized volatility using information channels from other asset classes,"
Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
- Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
- Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2022.
"Risk aversion and the predictability of crude oil market volatility: A forecasting experiment with random forests,"
Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1755-1767, August.
- Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Risk Aversion and the Predictability of Crude Oil Market Volatility: A Forecasting Experiment with Random Forests," Working Papers 201972, University of Pretoria, Department of Economics.
- Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
- Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
- Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
- Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
- Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
- Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
- Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
- Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020.
"Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss,"
Journal of International Money and Finance, Elsevier, vol. 104(C).
- Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
- Mei, Dexiang & Ma, Feng & Liao, Yin & Wang, Lu, 2020. "Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models," Energy Economics, Elsevier, vol. 86(C).
- Klein, Tony & Todorova, Neda, 2021. "Night trading with futures in China: The case of Aluminum and Copper," Resources Policy, Elsevier, vol. 73(C).
- Degiannakis, Stavros & Filis, George, 2016. "Forecasting oil price realized volatility: A new approach," MPRA Paper 69105, University Library of Munich, Germany.
More about this item
Keywords
Risk-return trade-off; High-frequency data; Volatility risk; Downside risk; Jump risk;All these keywords.
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:eee:appene:v:196:y:2017:i:c:p:152-161. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.