Geopolitical risk and oil volatility: A new insight
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DOI: 10.1016/j.eneco.2019.104548
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- Pesaran, M. Hashem & Timmermann, Allan, 2005.
"Small sample properties of forecasts from autoregressive models under structural breaks,"
Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
- Allan Timmermann & M. Hashem Pesaran, 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," CESifo Working Paper Series 990, CESifo.
- Pesaran, M. Hashem & Timmermann, Allan, 2004. "Small Sample Properties of Forecasts From Autoregressive Models Under Structural Breaks," CEPR Discussion Papers 4401, C.E.P.R. Discussion Papers.
- Pesaran, M.H. & Timmermann, A., 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," Cambridge Working Papers in Economics 0331, Faculty of Economics, University of Cambridge.
- Dario Caldara & Matteo Iacoviello, 2022.
"Measuring Geopolitical Risk,"
American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
- Matteo Iacoviello, 2018. "Measuring Geopolitical Risk," 2018 Meeting Papers 79, Society for Economic Dynamics.
- Dario Caldara & Matteo Iacoviello, 2018. "Measuring Geopolitical Risk," International Finance Discussion Papers 1222r1, Board of Governors of the Federal Reserve System (U.S.), revised 23 Mar 2022.
- 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.
- Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
- Riza Demirer & Rangan Gupta & Qiang Ji & Aviral Kumar Tiwari, 2018. "Geopolitical Risks and the Predictability of Regional Oil Returns and Volatility," Working Papers 201860, University of Pretoria, Department of Economics.
- Yang, Ke & Tian, Fengping & Chen, Langnan & Li, Steven, 2017. "Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 276-291.
- Andrea Coppola, 2008.
"Forecasting oil price movements: Exploiting the information in the futures market,"
Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(1), pages 34-56, January.
- Andrea Coppola, 2007. "Forecasting Oil Price Movements: Exploiting the Information in the Future Market," CEIS Research Paper 100, Tor Vergata University, CEIS.
- Feng Ma & M. I. M. Wahab & Jing Liu & Li Liu, 2018. "Is economic policy uncertainty important to forecast the realized volatility of crude oil futures?," Applied Economics, Taylor & Francis Journals, vol. 50(18), pages 2087-2101, April.
- Antonakakis, Nikolaos & Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos, 2017.
"Geopolitical risks and the oil-stock nexus over 1899–2016,"
Finance Research Letters, Elsevier, vol. 23(C), pages 165-173.
- Nikolaos Antonakakis & Rangan Gupta & Christos Kollias & Stephanos Papadamou, 2017. "Geopolitical Risks and the Oil-Stock Nexus Over 1899-2016," Working Papers 201702, University of Pretoria, Department of Economics.
- Charles, Amélie & Darné, Olivier, 2014.
"Volatility persistence in crude oil markets,"
Energy Policy, Elsevier, vol. 65(C), pages 729-742.
- Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
- Amélie Charles & Olivier Darné, 2014. "Volatility persistence in crude oil markets," Post-Print hal-00940312, HAL.
- Hedi Arouri, Mohamed El & Khuong Nguyen, Duc, 2010.
"Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade,"
Energy Policy, Elsevier, vol. 38(8), pages 4528-4539, August.
- Mohamed El Hedi Arouri & Duc Khuong Nguyen, 2010. "Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over the Last Decade," Working Papers hal-00507823, HAL.
- Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
- Plakandaras, Vasilios & Gupta, Rangan & Wong, Wing-Keung, 2019.
"Point and density forecasts of oil returns: The role of geopolitical risks,"
Resources Policy, Elsevier, vol. 62(C), pages 580-587.
- Vasilios Plakandaras & Rangan Gupta & Wing-Keung Wong, 2018. "Point and Density Forecasts of Oil Returns: The Role of Geopolitical Risks," Working Papers 201847, University of Pretoria, Department of Economics.
- Labidi, Chiaz & Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Bekiros, Stelios, 2018. "Quantile dependence between developed and emerging stock markets aftermath of the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 179-211.
- Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
- 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.
- Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013.
"An analysis of commodity markets: What gain for investors?,"
Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
- Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: what gain for investors?," Working Papers fe_2013_02, Deakin University, Department of Economics.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2011.
"The Model Confidence Set,"
Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2010. "The Model Confidence Set," CREATES Research Papers 2010-76, Department of Economics and Business Economics, Aarhus University.
- 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.
- 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.
- Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016.
"Measuring Economic Policy Uncertainty,"
The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2015. "Measuring Economic Policy Uncertainty," Economics Working Papers 15111, Hoover Institution, Stanford University.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2015. "Measuring Economic Policy Uncertainty," NBER Working Papers 21633, National Bureau of Economic Research, Inc.
- Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2015. "Measuring Economic Policy Uncertainty," CEP Discussion Papers dp1379, Centre for Economic Performance, LSE.
- Baker, Scott R. & Bloom, Nicholas & Davis, Steven J., 2015. "Measuring economic policy uncertainty," LSE Research Online Documents on Economics 64986, London School of Economics and Political Science, LSE Library.
- Davis, Steven & Bloom, Nicholas & Baker, Scott, 2015. "Measuring Economic Policy Uncertainty," CEPR Discussion Papers 10900, C.E.P.R. Discussion Papers.
- Fengping Tian & Ke Yang & Langnan Chen, 2017. "Realized Volatility Forecasting of Agricultural Commodity Futures Using Long Memory and Regime Switching," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(4), pages 421-430, July.
- Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
- Barbara Rossi & Atsushi Inoue, 2012.
"Out-of-Sample Forecast Tests Robust to the Choice of Window Size,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
- Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
- Barbara Rossi & Atsushi Inoue, 2012. "Out-of-sample forecast tests robust to the choice of window size," Economics Working Papers 1404, Department of Economics and Business, Universitat Pompeu Fabra.
- Rossi, Barbara & Inoue, Atsushi, 2011. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," CEPR Discussion Papers 8542, C.E.P.R. Discussion Papers.
- Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
- Ma, Feng & Liu, Jing & Huang, Dengshi & Chen, Wang, 2017. "Forecasting the oil futures price volatility: A new approach," Economic Modelling, Elsevier, vol. 64(C), pages 560-566.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006.
"Predicting volatility: getting the most out of return data sampled at different frequencies,"
Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
- Ma, Feng & Liao, Yin & Zhang, Yaojie & Cao, Yang, 2019. "Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 40-55.
- Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, vol. 68(C), pages 77-88.
- Gkillas, Konstantinos & Gupta, Rangan & Wohar, Mark E., 2018.
"Volatility jumps: The role of geopolitical risks,"
Finance Research Letters, Elsevier, vol. 27(C), pages 247-258.
- Konstantinos Gkillas & Rangan Gupta & Mark E. Wohar, 2018. "Volatility Jumps: The Role of Geopolitical Risks," Working Papers 201805, University of Pretoria, Department of Economics.
- Omar, Ayman M.A. & Wisniewski, Tomasz Piotr & Nolte, Sandra, 2017. "Diversifying away the risk of war and cross-border political crisis," Energy Economics, Elsevier, vol. 64(C), pages 494-510.
- 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," Post-Print hal-01463921, HAL.
- Benoît Sévi, 2014. "Forecasting the volatility of crude oil futures using intraday data," Working Papers 2014-53, Department of Research, Ipag Business School.
- Narayan, Paresh Kumar & Narayan, Seema, 2007. "Modelling oil price volatility," Energy Policy, Elsevier, vol. 35(12), pages 6549-6553, December.
- Hossein Asgharian & Ai Jun Hou & Farrukh Javed, 2013. "The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH‐MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(7), pages 600-612, November.
- John Y. Campbell & Samuel B. Thompson, 2008.
"Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?,"
The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
- Campbell, John & Thompson, Samuel P., 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Scholarly Articles 2622619, Harvard University Department of Economics.
- Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
- Yin, Libo & Yang, Qingyuan, 2016. "Predicting the oil prices: Do technical indicators help?," Energy Economics, Elsevier, vol. 56(C), pages 338-350.
- Wei, Yu & Wang, Yudong & Huang, Dengshi, 2010. "Forecasting crude oil market volatility: Further evidence using GARCH-class models," Energy Economics, Elsevier, vol. 32(6), pages 1477-1484, November.
- Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
- Raffaella Giacomini & Barbara Rossi, 2010.
"Forecast comparisons in unstable environments,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
- Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
- Su, Zhi & Fang, Tong & Yin, Libo, 2017. "The role of news-based implied volatility among US financial markets," Economics Letters, Elsevier, vol. 157(C), pages 24-27.
- Liu, Zhicao & Ye, Yong & Ma, Feng & Liu, Jing, 2017. "Can economic policy uncertainty help to forecast the volatility: A multifractal perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 181-188.
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004.
"The MIDAS Touch: Mixed Data Sampling Regression Models,"
University of California at Los Angeles, Anderson Graduate School of Management
qt9mf223rs, Anderson Graduate School of Management, UCLA.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
- Brandt, Michael W. & Gao, Lin, 2019. "Macro fundamentals or geopolitical events? A textual analysis of news events for crude oil," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 64-94.
- Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
- 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.
- Lutz Kilian & Daniel P. Murphy, 2014.
"The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 454-478, April.
- Kilian, Lutz & Murphy, Daniel, 2010. "The Role of Inventories and Speculative Trading in the Global Market for Crude Oil," CEPR Discussion Papers 7753, C.E.P.R. Discussion Papers.
- Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018. "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, vol. 70(C), pages 472-483.
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Keywords
Volatility forecasting; Geopolitical risk; Oil market; Model confidence set;All these keywords.
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