Which types of commodity price information are more useful for predicting US stock market volatility?
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DOI: 10.1016/j.econmod.2020.03.022
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- Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017.
"Rolling window selection for out-of-sample forecasting with time-varying parameters,"
Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
- Atsushi Inoue & Lu Jin & Barbara Rossi, 2014. "Rolling Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," Working Papers 768, Barcelona School of Economics.
- Atsushi Inoue & Lu Jin & Barbara Rossi, 2014. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Economics Working Papers 1435, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2016.
- Sung C. Bae & Taek Ho Kwon & Jong Won Park, 2004. "Futures trading, spot market volatility, and market efficiency: The case of the Korean index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(12), pages 1195-1228, December.
- Fulvio Corsi & Stefan Mittnik & Christian Pigorsch & Uta Pigorsch, 2008.
"The Volatility of Realized Volatility,"
Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 46-78.
- Corsi, Fulvio & Kretschmer, Uta & Mittnik, Stefan & Pigorsch, Christian, 2005. "The volatility of realized volatility," CFS Working Paper Series 2005/33, Center for Financial Studies (CFS).
- Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007.
"The Effect of Long Memory in Volatility on Stock Market Fluctuations,"
The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 684-700, November.
- Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Effect of Long Memory in Volatility on Stock Market Fluctuations," CREATES Research Papers 2007-03, Department of Economics and Business Economics, Aarhus University.
- Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
- Bollerslev, Tim & Ole Mikkelsen, Hans, 1996.
"Modeling and pricing long memory in stock market volatility,"
Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
- Tom Doan, "undated". "RATS program to replicate Bollerslev-Mikkelson(1996) FIEGARCH models," Statistical Software Components RTZ00173, Boston College Department of Economics.
- Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
- Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
- Narayan, Paresh Kumar & Narayan, Seema, 2010. "Modelling the impact of oil prices on Vietnam's stock prices," Applied Energy, Elsevier, vol. 87(1), pages 356-361, January.
- Christoffersen, Peter & Lunde, Asger & Olesen, Kasper V., 2019.
"Factor Structure in Commodity Futures Return and Volatility,"
Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(3), pages 1083-1115, June.
- Peter Christoffersen & Asger Lunde & Kasper V. Olesen, 2014. "Factor Structure in Commodity Futures Return and Volatility," CREATES Research Papers 2014-31, Department of Economics and Business Economics, Aarhus University.
- 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.
- Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
- Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2018. "Forecasting the prices of crude oil using the predictor, economic and combined constraints," Economic Modelling, Elsevier, vol. 75(C), pages 237-245.
- Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010.
"Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model,"
Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
- Bent Jesper Christensen & Morten Ørregaard Nielsen & Jie Zhu, 2007. "Long Memory in Stock Market Volatility and the Volatility-in-Mean Effect: The FIEGARCH-M Model," CREATES Research Papers 2007-10, Department of Economics and Business Economics, Aarhus University.
- Bent Jesper Christensen & Jie Zhu & Morten Ø. Nielsen, 2009. "Long Memory In Stock Market Volatility And The Volatility-in-mean Effect: The Fiegarch-m Model," Working Paper 1207, Economics Department, Queen's University.
- Clark, Todd E. & West, Kenneth D., 2007.
"Approximately normal tests for equal predictive accuracy in nested models,"
Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
- Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.
- Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
- 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.
- 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.
- 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.
- 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.
- Crain, Susan J & Lee, Jae Ha, 1996. "Volatility in Wheat Spot and Futures Markets, 1950-1993: Government Farm Programs, Seasonality, and Causality," Journal of Finance, American Finance Association, vol. 51(1), pages 325-343, March.
- Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014.
"Forecasting the Equity Risk Premium: The Role of Technical Indicators,"
Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
- Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2010. "Out-of-sample equity premium prediction: economic fundamentals vs. moving-average rules," Working Papers 2010-008, Federal Reserve Bank of St. Louis.
- Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2011. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Working Papers CoFie-02-2011, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
- Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018.
"Commodity Connectedness,"
Central Banking, Analysis, and Economic Policies Book Series, in: Enrique G. Mendoza & Ernesto Pastén & Diego Saravia (ed.),Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures, edition 1, volume 25, chapter 4, pages 097-136,
Central Bank of Chile.
- Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2017. "Commodity Connectedness," PIER Working Paper Archive 17-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Mar 2017.
- Diebold, Francis X. & Liu, Laura & Yilmaz, Kamil, 2017. "Commodity connectedness," CFS Working Paper Series 575, Center for Financial Studies (CFS).
- Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2017. "Commodity Connectedness," NBER Working Papers 23685, National Bureau of Economic Research, Inc.
- Narayan, Paresh Kumar & Sharma, Susan Sunila, 2011. "New evidence on oil price and firm returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3253-3262.
- 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.
- Diebold, Francis X. & Yilmaz, Kamil, 2012.
"Better to give than to receive: Predictive directional measurement of volatility spillovers,"
International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
- Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
- 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.
- Narayan, Paresh Kumar & Narayan, Seema, 2007. "Modelling oil price volatility," Energy Policy, Elsevier, vol. 35(12), pages 6549-6553, December.
- 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.
- Yaojie Zhang & Feng Ma & Tianyi Wang & Li Liu, 2019. "Out‐of‐sample volatility prediction: A new mixed‐frequency approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(7), pages 669-680, November.
- Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
- 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.
- Suleyman Basak & Anna Pavlova, 2016.
"A Model of Financialization of Commodities,"
Journal of Finance, American Finance Association, vol. 71(4), pages 1511-1556, August.
- Basak, Suleyman & Pavlova, Anna, 2015. "A Model of Financialization of Commodities," CEPR Discussion Papers 10651, C.E.P.R. Discussion Papers.
- Koutmos, Gregory & Booth, G Geoffrey, 1995. "Asymmetric volatility transmission in international stock markets," Journal of International Money and Finance, Elsevier, vol. 14(6), pages 747-762, December.
- Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
- Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019.
"Futures-based forecasts: How useful are they for oil price volatility forecasting?,"
Energy Economics, Elsevier, vol. 81(C), pages 639-649.
- Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," MPRA Paper 96446, University Library of Munich, Germany.
- Cipollini, Andrea & Cascio, Iolanda Lo & Muzzioli, Silvia, 2015.
"Volatility co-movements: A time-scale decomposition analysis,"
Journal of Empirical Finance, Elsevier, vol. 34(C), pages 34-44.
- Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2013. "Volatility co-movements: a time scale decomposition analysis," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0044, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
- Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
- Ercan Balaban & Asli Bayar & Robert Faff, 2006. "Forecasting stock market volatility: Further international evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 12(2), pages 171-188.
- John Board & Gleb Sandmann & Charles Sutcliffe, 2001.
"The Effect of Futures Market Volume on Spot Market Volatility,"
Journal of Business Finance & Accounting,
Wiley Blackwell, vol. 28(7‐8), pages 799-819, September.
- John Board & Gleb Sandmann & Charles Sutcliffe, 2001. "The Effect of Futures Market Volume on Spot Market Volatility," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(7&8), pages 799-819.
- Robert S. Pindyck, 2001.
"The Dynamics of Commodity Spot and Futures Markets: A Primer,"
The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-30.
- Robert S. Pindyck, 2001. "The Dynamics of Commodity Spot and Futures Markets: A Primer," The Energy Journal, , vol. 22(3), pages 1-29, July.
- David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
- 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.
- 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.
- Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
- Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
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More about this item
Keywords
Commodity futures volatility; Stock market volatility; Factor analysis; Principal component analysis;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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