Cross-sectional uncertainty and stock market volatility: New evidence
Author
Abstract
Suggested Citation
DOI: 10.1016/j.frl.2023.104202
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
- Ian Dew-Becker & Stefano Giglio, 2023.
"Cross-Sectional Uncertainty and the Business Cycle: Evidence from 40 Years of Options Data,"
American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 65-96, April.
- Ian Dew-Becker & Stefano Giglio, 2020. "Cross-Sectional Uncertainty and the Business Cycle: Evidence from 40 Years of Options Data," NBER Working Papers 27864, National Bureau of Economic Research, Inc.
- Giglio, Stefano & Dew-Becker, Ian, 2021. "Cross-sectional uncertainty and the business cycle: evidence from 40 years of options data," CEPR Discussion Papers 16306, C.E.P.R. Discussion Papers.
- Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018.
"Risk Everywhere: Modeling and Managing Volatility,"
The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
- Pedersen, Lasse Heje & Bollerslev, Tim & Hood, Benjamin & Huss, John, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.
- Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
- 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.
- Atsushi Inoue & Lutz Kilian, 2005.
"In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?,"
Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
- Kilian, Lutz & Inoue, Atsushi, 2002. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," CEPR Discussion Papers 3671, C.E.P.R. Discussion Papers.
- Inoue, Atsushi & Kilian, Lutz, 2002. "In-sample or out-of-sample tests of predictability: which one should we use?," Working Paper Series 195, European Central Bank.
- 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.
- 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.
- 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.
- Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
- Zeng, Qing & Ma, Feng & Lu, Xinjie & Xu, Weiju, 2022. "Policy uncertainty and carbon neutrality: Evidence from China," Finance Research Letters, Elsevier, vol. 47(PB).
- Fenghua Wen & Yupei Zhao & Minzhi Zhang & Chunyan Hu, 2019. "Forecasting realized volatility of crude oil futures with equity market uncertainty," Applied Economics, Taylor & Francis Journals, vol. 51(59), pages 6411-6427, December.
- Chao Liang & Yaojie Zhang & Xiafei Li & Feng Ma, 2022. "Which predictor is more predictive for Bitcoin volatility? And why?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1947-1961, April.
- 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.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2024. "Political Geography and Stock Market Volatility: The Role of Political Alignment across Sentiment Regimes," Working Papers 202414, University of Pretoria, Department of Economics.
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.- Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
- Luo, Qin & Ma, Feng & Wang, Jiqian & Wu, You, 2024. "Changing determinant driver and oil volatility forecasting: A comprehensive analysis," Energy Economics, Elsevier, vol. 129(C).
- Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
- Lu, Fei & Ma, Feng & Guo, Qiang, 2023. "Less is more? New evidence from stock market volatility predictability," International Review of Financial Analysis, Elsevier, vol. 89(C).
- Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
- Charles, Amelie & Darne, Olivier & Kim, Jae, 2016.
"Stock Return Predictability: Evaluation based on Prediction Intervals,"
MPRA Paper
70143, University Library of Munich, Germany.
- Amélie Charles & Olivier Darné & Jae H. Kim, 2016. "Stock Return Predictability: Evaluation based on prediction intervals," Working Papers hal-01295037, HAL.
- He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
- Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
- Amélie Charles & Olivier Darné & Jae H. Kim, 2022.
"Stock return predictability: Evaluation based on interval forecasts,"
Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
- Amélie Charles & Olivier Darné & Jae Kim, 2022. "Stock Return Predictability: Evaluation based on interval forecasts," Post-Print hal-03656310, HAL.
- Li, Dakai, 2024. "Forecasting stock market realized volatility: The role of investor attention to the price of petroleum products," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 115-122.
- Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
- Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
- Xianfeng Hao & Yudong Wang, 2023. "Cloud cover and expected oil returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
- Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
- Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
- Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
- Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
- Liu, Zhichao & Liu, Jing & Zeng, Qing & Wu, Lan, 2022. "VIX and stock market volatility predictability: A new approach," Finance Research Letters, Elsevier, vol. 48(C).
- 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.
- Fameliti Stavroula & Skintzi Vasiliki, 2024. "Macroeconomic attention and commodity market volatility," Empirical Economics, Springer, vol. 67(5), pages 1967-2007, November.
More about this item
Keywords
Cross-sectional uncertainty; Economic policy uncertainty; Stock market volatility; Out-of-sample forecast; Financial crisis;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:finlet:v:57:y:2023:i:c:s1544612323005743. 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/locate/frl .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.