Forecasting stock market volatility using commodity futures volatility information
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DOI: 10.1016/j.resourpol.2021.102481
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- Li, Jiahan & Tsiakas, Ilias, 2017.
"Equity premium prediction: The role of economic and statistical constraints,"
Journal of Financial Markets, Elsevier, vol. 36(C), pages 56-75.
- Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
- Ben Jacobsen & Ben R. Marshall & Nuttawat Visaltanachoti, 2019. "Stock Market Predictability and Industrial Metal Returns," Management Science, INFORMS, vol. 65(7), pages 3026-3042, July.
- Ivo Welch & Amit Goyal, 2008.
"A Comprehensive Look at The Empirical Performance of Equity Premium Prediction,"
The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
- Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
- Amit Goyal & Ivo Welch & Athanasse Zafirov, 2021. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction II," Swiss Finance Institute Research Paper Series 21-85, Swiss Finance Institute.
- Amit Goval & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," NBER Working Papers 10483, 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.
- 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.
- Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
- Francis X. Diebold & Kamil Yilmaz, 2009.
"Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets,"
Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
- FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
- Francis X. Diebold & Kamil Yılmaz, 2007. "Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets," Koç University-TUSIAD Economic Research Forum Working Papers 0705, Koc University-TUSIAD Economic Research Forum.
- Francis X. Diebold & Kamil Yilmaz, 2008. "Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets," NBER Working Papers 13811, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Kamil Yilmaz, 2008. "Measuring financial asset return and volatility spillovers, with application to global equity markets," Working Papers 08-16, Federal Reserve Bank of Philadelphia.
- Diebold, Francis X. & Yilmaz, Kamil, 2008. "Measuring financial asset return and volatilty spillovers, with application to global equity markets," CFS Working Paper Series 2008/26, Center for Financial Studies (CFS).
- Francis X. Diebold & Kamil Yilmaz, 2007. "Measuring Financial Asset Return and Volatility Spillovers, With Application to Global Equity Markets," PIER Working Paper Archive 07-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Diebold, Francis X. & Yilmaz, Kamil, 2007. "Measuring financial asset return and volatility spillovers, with application to global equity markets," CFS Working Paper Series 2007/02, Center for Financial Studies (CFS).
- Tom Doan, "undated". "RATS programs to replicate Diebold and Yilmaz EJ 2009 spillover calculations," Statistical Software Components RTZ00044, Boston College Department of Economics.
- 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.
- 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.
- Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
- 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.
- 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.
- 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.
- Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
- 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.
- 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.
- Asgharian, Hossein & Nossman, Marcus, 2011. "Risk contagion among international stock markets," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 22-38, February.
- 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.
- Chao Liang & Yu Wei & Xiafei Li & Xuhui Zhang & Yifeng Zhang, 2020. "Uncertainty and crude oil market volatility: new evidence," Applied Economics, Taylor & Francis Journals, vol. 52(27), pages 2945-2959, May.
- Bessembinder, Hendrik & Seguin, Paul J, 1992. "Futures-Trading Activity and Stock Price Volatility," Journal of Finance, American Finance Association, vol. 47(5), pages 2015-2034, December.
- Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
- Li, Yan & Liang, Chao & Ma, Feng & Wang, Jiqian, 2020. "The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 36(C).
- Virk, Nader & Javed, Farrukh, 2017. "European equity market integration and joint relationship of conditional volatility and correlations," Journal of International Money and Finance, Elsevier, vol. 71(C), pages 53-77.
- 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.
- Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
- Francesco Audrino & Simon D. Knaus, 2016.
"Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics,"
Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1485-1521, December.
- Audrino, Francesco & Knaus, Simon, 2012. "Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics," Economics Working Paper Series 1224, University of St. Gallen, School of Economics and Political Science.
- Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012.
"A comprehensive look at financial volatility prediction by economic variables,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
- Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2010. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," CREATES Research Papers 2010-58, Department of Economics and Business Economics, Aarhus University.
- Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," BIS Working Papers 374, Bank for International Settlements.
- Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
- Berger, Theo & Uddin, Gazi Salah, 2016. "On the dynamic dependence between equity markets, commodity futures and economic uncertainty indexes," Energy Economics, Elsevier, vol. 56(C), pages 374-383.
- 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.
- Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
- Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021.
"Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks,"
Resources Policy, Elsevier, vol. 74(C).
- Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," EconStor Preprints 235529, ZBW - Leibniz Information Centre for Economics.
- Rabeh Khalfaoui & Eduard Baumöhl & Suleman Sarwar & Tomáš Výrost, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Post-Print hal-03797575, HAL.
- Cheung, Yin-Wong & Lai, Kon S, 1995. "Lag Order and Critical Values of the Augmented Dickey-Fuller Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 277-280, July.
- 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.
- 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.
- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- 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.
- 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.
- Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
- Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
- B., Anand & Paul, Sunil, 2021. "Oil shocks and stock market: Revisiting the dynamics," Energy Economics, Elsevier, vol. 96(C).
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
- 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.
- 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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- Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
- Soni, Rajat Kumar & Nandan, Tanuj, 2022. "Modeling Covid-19 contagious effect between asset markets and commodity futures in India," Resources Policy, Elsevier, vol. 79(C).
- Chao Liang & Yongan Xu & Zhonglu Chen & Xiafei Li, 2023. "Forecasting China's stock market volatility with shrinkage method: Can Adaptive Lasso select stronger predictors from numerous predictors?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3689-3699, October.
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More about this item
Keywords
Commodity futures volatility; Stock market volatility; Elastic net; Lasso; Combination forecast;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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