IDEAS home Printed from https://ideas.repec.org/a/eee/intfin/v101y2025ics1042443125000253.html
   My bibliography  Save this article

Climate risk and predictability of global stock market volatility

Author

Listed:
  • Zhou, Mingtao
  • Ma, Yong

Abstract

This study examines the informative role of climate risk in improving the predictability of global stock market volatility. By aggregating four climate risk proxies of Faccini et al. (2023), relating to physical climate impacts and climate mitigation actions, we reveal that aggregate climate risk is a significantly positive predictor of stock volatility across 32 international markets. This predictability persists in out-of-sample tests and cannot be subsumed by relevant economic and financial uncertainty measures. However, the predictive power of aggregate climate risk exhibits noteworthy variations over time and across regions; it weakens when economic conditions deteriorate, whereas it strengthens following the Paris Agreement and in regions with advanced financial development, high energy intensity, and strong climate change readiness. Moreover, by dissecting the multiple facets of climate risk, we show that physical risks, especially natural disasters, have much stronger predictability than transition risks. These predictive insights offer valuable guidance for risk management, policy planning, and the adjustment of asset pricing models in response to the evolving global climate risk landscape.

Suggested Citation

  • Zhou, Mingtao & Ma, Yong, 2025. "Climate risk and predictability of global stock market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 101(C).
  • Handle: RePEc:eee:intfin:v:101:y:2025:i:c:s1042443125000253
    DOI: 10.1016/j.intfin.2025.102135
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1042443125000253
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.intfin.2025.102135?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Ströbel, Johannes & Wurgler, Jeffrey, 2021. "What do you think about climate finance?," CEPR Discussion Papers 16622, C.E.P.R. Discussion Papers.
    2. Gupta, Rangan & Nielsen, Joshua & Pierdzioch, Christian, 2024. "Stock market bubbles and the realized volatility of oil price returns," Energy Economics, Elsevier, vol. 132(C).
    3. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    4. 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.
    5. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    6. Thanh D. Huynh & Ying Xia, 2023. "Panic Selling When Disaster Strikes: Evidence in the Bond and Stock Markets," Management Science, INFORMS, vol. 69(12), pages 7448-7467, December.
    7. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.
    8. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    9. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    10. Robert F Engle & Stefano Giglio & Bryan Kelly & Heebum Lee & Johannes Stroebel, 2020. "Hedging Climate Change News," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1184-1216.
    11. 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.
    12. Lu, Xinjie & Zeng, Qing & Zhong, Juandan & Zhu, Bo, 2024. "International stock market volatility: A global tail risk sight," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    13. Gong, Xu & Liao, Qin, 2024. "Physical climate risk attention and dynamic volatility connectedness among new energy stocks," Energy Economics, Elsevier, vol. 136(C).
    14. Zhang, Li & Liang, Chao & Huynh, Luu Duc Toan & Wang, Lu & Damette, Olivier, 2024. "Measuring the impact of climate risk on renewable energy stock volatility: A case study of G20 economies," Journal of Economic Behavior & Organization, Elsevier, vol. 223(C), pages 168-184.
    15. Malcolm Baker & Daniel Bergstresser & George Serafeim & Jeffrey Wurgler, 2018. "Financing the Response to Climate Change: The Pricing and Ownership of U.S. Green Bonds," NBER Working Papers 25194, National Bureau of Economic Research, Inc.
    16. Dang, Tam Hoang-Nhat & Nguyen, Canh Phuc & Lee, Gabriel S. & Nguyen, Binh Quang & Le, Thuy Thu, 2023. "Measuring the energy-related uncertainty index," Energy Economics, Elsevier, vol. 124(C).
    17. Pesaran, M. Hashem & Timmermann, Allan, 2009. "Testing Dependence Among Serially Correlated Multicategory Variables," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 325-337.
    18. repec:bla:jfinan:v:43:y:1988:i:3:p:661-76 is not listed on IDEAS
    19. Stefano Giglio & Matteo Maggiori & Krishna Rao & Johannes Stroebel & Andreas Weber & Stijn Van Nieuwerburgh, 2021. "Climate Change and Long-Run Discount Rates: Evidence from Real Estate [Abrupt climate change]," The Review of Financial Studies, Society for Financial Studies, vol. 34(8), pages 3527-3571.
    20. 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.
    21. Gupta, Rangan & Pierdzioch, Christian, 2022. "Climate risks and forecastability of the realized volatility of gold and other metal prices," Resources Policy, Elsevier, vol. 77(C).
    22. Bryan Kelly & Seth Pruitt, 2013. "Market Expectations in the Cross-Section of Present Values," Journal of Finance, American Finance Association, vol. 68(5), pages 1721-1756, October.
    23. Campbell, John & Shiller, Robert, 1988. "Stock Prices, Earnings, and Expected Dividends," Scholarly Articles 3224293, Harvard University Department of Economics.
    24. Lamperti, F. & Dosi, G. & Napoletano, M. & Roventini, A. & Sapio, A., 2020. "Climate change and green transitions in an agent-based integrated assessment model," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    25. 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.
    26. 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.
    27. Guo, Kun & Li, Yichong & Zhang, Yunhan & Ji, Qiang & Zhao, Wanli, 2023. "How are climate risk shocks connected to agricultural markets?," Journal of Commodity Markets, Elsevier, vol. 32(C).
    28. Liang, Chao & Luo, Qin & Li, Yan & Huynh, Luu Duc Toan, 2023. "Global financial stress index and long-term volatility forecast for international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    29. Yu, Xiaoling & Huang, Yirong, 2021. "The impact of economic policy uncertainty on stock volatility: Evidence from GARCH–MIDAS approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    30. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024. "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 280-293.
    31. Liu, Zhonglu & He, Shuguang & Men, Wenjiao & Sun, Haibo, 2024. "Impact of climate risk on financial stability: Cross-country evidence," International Review of Financial Analysis, Elsevier, vol. 92(C).
    32. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    33. Monasterolo, Irene & de Angelis, Luca, 2020. "Blind to carbon risk? An analysis of stock market reaction to the Paris Agreement," Ecological Economics, Elsevier, vol. 170(C).
    34. Xiaoling Yu & Yirong Huang & Kaitian Xiao, 2021. "Global economic policy uncertainty and stock volatility: evidence from emerging economies," Journal of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 416-440, January.
    35. 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.
    36. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2023. "A Machine Learning Approach to Volatility Forecasting," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1680-1727.
    37. Wang, Jiqian & Li, Liang, 2023. "Climate risk and Chinese stock volatility forecasting: Evidence from ESG index," Finance Research Letters, Elsevier, vol. 55(PA).
    38. Francois Gourio, 2012. "Disaster Risk and Business Cycles," American Economic Review, American Economic Association, vol. 102(6), pages 2734-2766, October.
    39. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    40. Robert J. Barro, 2006. "Rare Disasters and Asset Markets in the Twentieth Century," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(3), pages 823-866.
    41. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    42. 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.
    43. Gong, Xu & Fu, Chengbo & Huang, Qiping & Lin, Meimei, 2022. "International political uncertainty and climate risk in the stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    44. Paye, Bradley S., 2012. "‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables," Journal of Financial Economics, Elsevier, vol. 106(3), pages 527-546.
    45. Jessica A. Wachter, 2013. "Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?," Journal of Finance, American Finance Association, vol. 68(3), pages 987-1035, June.
    46. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    47. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    48. Michael T. Owyang & Valerie A. Ramey & Sarah Zubairy, 2013. "Are government spending multipliers greater during periods of slack? evidence from 20th century historical data," Working Papers 2013-004, Federal Reserve Bank of St. Louis.
    49. 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).
    50. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
    51. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    52. James H. Stock & Mark W. Watson, 2010. "Modeling inflation after the crisis," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 173-220.
    53. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2022. "Investor Attention and Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 57(2), pages 455-484, March.
    54. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    55. Giovanna Bua & Daniel Kapp & Federico Ramella & Lavinia Rognone, 2024. "Transition versus physical climate risk pricing in European financial markets: a text-based approach," The European Journal of Finance, Taylor & Francis Journals, vol. 30(17), pages 2076-2110, November.
    56. Bolton, Patrick & Kacperczyk, Marcin, 2021. "Do investors care about carbon risk?," Journal of Financial Economics, Elsevier, vol. 142(2), pages 517-549.
    57. Busch, Thomas & Christensen, Bent Jesper & Nielsen, Morten Ørregaard, 2011. "The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets," Journal of Econometrics, Elsevier, vol. 160(1), pages 48-57, January.
    58. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    59. Mohammadi, Hassan & Su, Lixian, 2010. "International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models," Energy Economics, Elsevier, vol. 32(5), pages 1001-1008, September.
    60. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    61. Darwin Choi & Zhenyu Gao & Wenxi Jiang, 2020. "Attention to Global Warming," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1112-1145.
    62. Nazlioglu, Saban & Soytas, Ugur, 2011. "World oil prices and agricultural commodity prices: Evidence from an emerging market," Energy Economics, Elsevier, vol. 33(3), pages 488-496, May.
    63. 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).
    64. Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
    65. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    66. Whitney Newey & Kenneth West, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    67. Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2024. "Volatility Forecasting with Machine Learning and Intraday Commonality," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 492-530.
    68. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    69. Po‐Hsuan Hsu & Kai Li & Chi‐Yang Tsou, 2023. "The Pollution Premium," Journal of Finance, American Finance Association, vol. 78(3), pages 1343-1392, June.
    70. Khalfaoui, Rabeh & Mefteh-Wali, Salma & Viviani, Jean-Laurent & Ben Jabeur, Sami & Abedin, Mohammad Zoynul & Lucey, Brian M., 2022. "How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    71. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    72. Shanghui Jia & Xinhui Chen & Liyan Han & Jiayu Jin, 2023. "Global climate change and commodity markets: A hedging perspective," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1393-1422, October.
    73. Yuqin Zhou & Shan Wu & Zhenhua Liu & Lavinia Rognone, 2023. "The asymmetric effects of climate risk on higher-moment connectedness among carbon, energy and metals markets," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    74. Gong, Xu & Song, Yijie & Fu, Chengbo & Li, Huijing, 2023. "Climate risk and stock performance of fossil fuel companies: An international analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    75. 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.
    76. Ma, Dandan & Zhang, Dayong & Guo, Kun & Ji, Qiang, 2024. "Coupling between global climate policy uncertainty and economic policy uncertainty," Finance Research Letters, Elsevier, vol. 69(PB).
    77. Huang, Zih-Chun & Sangiorgi, Ivan & Urquhart, Andrew, 2024. "Forecasting Bitcoin volatility using machine learning techniques," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
    78. Feng Ma & Yangli Guo & Julien Chevallier & Dengshi Huang, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," Post-Print halshs-04250304, HAL.
    79. Ye, Liping, 2022. "The effect of climate news risk on uncertainties," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    80. Sabine Fuss, 2016. "Substantial risk for financial assets," Nature Climate Change, Nature, vol. 6(7), pages 659-660, July.
    81. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    82. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    83. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
    84. Xavier Gabaix, 2012. "Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(2), pages 645-700.
    85. Wang, Jiqian & Ma, Feng & Wang, Tianyang & Wu, Lan, 2023. "International stock volatility predictability: New evidence from uncertainties," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    86. Nazlioglu, Saban & Gupta, Rangan & Gormus, Alper & Soytas, Ugur, 2020. "Price and volatility linkages between international REITs and oil markets," Energy Economics, Elsevier, vol. 88(C).
    87. Sheng, Xin & Kim, Won Joong & Gupta, Rangan & Ji, Qiang, 2023. "The impacts of oil price volatility on financial stress: Is the COVID-19 period different?," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 520-532.
    88. Francis X. Diebold & Kamil Yılmaz, 2007. "Macroeconomic Volatility and Stock Market Volatility,World-Wide," Koç University-TUSIAD Economic Research Forum Working Papers 0711, Koc University-TUSIAD Economic Research Forum.
    89. 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.
    90. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    91. Zhang, Si Ying, 2022. "Are investors sensitive to climate-related transition and physical risks? Evidence from global stock markets," Research in International Business and Finance, Elsevier, vol. 62(C).
    92. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
    93. 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.
    94. Haohua Li & Elie Bouri & Rangan Gupta & Libing Fang, 2023. "Return Volatility, Correlation, and Hedging of Green and Brown Stocks: Is there a Role for Climate Risk Factors?," Working Papers 202301, University of Pretoria, Department of Economics.
    95. Chi, Yeguang & Hao, Wenyan, 2021. "Volatility models for cryptocurrencies and applications in the options market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    96. Michael Barnett, 2023. "Climate Change and Uncertainty: An Asset Pricing Perspective," Management Science, INFORMS, vol. 69(12), pages 7562-7584, December.
    97. 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.
    98. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    99. Steven J. Davis, 2016. "An Index of Global Economic Policy Uncertainty," NBER Working Papers 22740, National Bureau of Economic Research, Inc.
    100. Gupta, Rangan & Sheng, Xin & Pierdzioch, Christian & Ji, Qiang, 2021. "Disaggregated oil shocks and stock-market tail risks: Evidence from a panel of 48 economics," Research in International Business and Finance, Elsevier, vol. 58(C).
    101. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    102. Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022. "Scaled PCA: A New Approach to Dimension Reduction," Management Science, INFORMS, vol. 68(3), pages 1678-1695, March.
    103. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    104. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    105. Ji, Qiang & Ma, Dandan & Zhai, Pengxiang & Fan, Ying & Zhang, Dayong, 2024. "Global climate policy uncertainty and financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 95(C).
    106. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and state-level stock market realized volatility," Journal of Financial Markets, Elsevier, vol. 66(C).
    107. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    108. 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.
    109. Michael T. Owyang & Valerie A. Ramey & Sarah Zubairy, 2013. "Are Government Spending Multipliers Greater during Periods of Slack? Evidence from Twentieth-Century Historical Data," American Economic Review, American Economic Association, vol. 103(3), pages 129-134, May.
    110. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    111. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
    112. Gargano, Antonio & Timmermann, Allan, 2014. "Forecasting commodity price indexes using macroeconomic and financial predictors," International Journal of Forecasting, Elsevier, vol. 30(3), pages 825-843.
    113. Bernstein, Asaf & Gustafson, Matthew T. & Lewis, Ryan, 2019. "Disaster on the horizon: The price effect of sea level rise," Journal of Financial Economics, Elsevier, vol. 134(2), pages 253-272.
    114. Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
    115. Mele, Antonio, 2007. "Asymmetric stock market volatility and the cyclical behavior of expected returns," Journal of Financial Economics, Elsevier, vol. 86(2), pages 446-478, November.
    116. 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).
    117. Faccini, Renato & Matin, Rastin & Skiadopoulos, George, 2023. "Dissecting climate risks: Are they reflected in stock prices?," Journal of Banking & Finance, Elsevier, vol. 155(C).
    118. James H. Stock & Mark W. Watson, 2010. "Modeling Inflation After the Crisis," Working Papers 2010-1, Princeton University. Economics Department..
    119. Arseny Gorbenko & Marcin Kacperczyk, 2023. "Short Interest and Aggregate Stock Returns: International Evidence," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 13(4), pages 691-733.
    120. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    121. Liang, Chao & Goodell, John W. & Li, Xiafei, 2024. "Impacts of carbon market and climate policy uncertainties on financial and economic stability: Evidence from connectedness network analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    122. Xu, Liao & Zhang, Xuan & Zhao, Jing, 2023. "Limited investor attention and biased reactions to information: Evidence from the COVID-19 pandemic," Journal of Financial Markets, Elsevier, vol. 62(C).
    123. 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.
    124. Rangan Gupta & Xin Sheng & Christian Pierdzioch & Qiang Ji, 2021. "Disaggregated Oil Shocks and Stock-Market Tail Risks: Evidence from a Panel of 48 Countries," Working Papers 202106, University of Pretoria, Department of Economics.
    125. Kelly, Bryan & Pruitt, Seth, 2015. "The three-pass regression filter: A new approach to forecasting using many predictors," Journal of Econometrics, Elsevier, vol. 186(2), pages 294-316.
    126. Zhao, Rui & Zhang, Dayong & Guo, Mengmeng, 2024. "Do natural disasters affect stock price crash risk? Evidence from emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 93(C).
    127. Ma, Yong & Zhou, Mingtao & Li, Shuaibing, 2024. "Weathering market swings: Does climate risk matter for agricultural commodity price predictability?," Journal of Commodity Markets, Elsevier, vol. 36(C).
    128. Painter, Marcus, 2020. "An inconvenient cost: The effects of climate change on municipal bonds," Journal of Financial Economics, Elsevier, vol. 135(2), pages 468-482.
    129. Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Transition risk, physical risk, and the realized volatility of oil and natural gas prices," Resources Policy, Elsevier, vol. 81(C).
    130. Cepni, Oguzhan & Demirer, Riza & Pham, Linh & Rognone, Lavinia, 2023. "Climate uncertainty and information transmissions across the conventional and ESG assets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ruizhi Liu & Jiajia Li & Mark Wu, 2025. "The Impact of Climate Change Risk on Corporate Debt Financing Capacity: A Moderating Perspective Based on Carbon Emissions," Sustainability, MDPI, vol. 17(14), pages 1-37, July.

    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.
    1. Ma, Yong & Zhou, Mingtao & Li, Shuaibing, 2024. "Weathering market swings: Does climate risk matter for agricultural commodity price predictability?," Journal of Commodity Markets, Elsevier, vol. 36(C).
    2. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    3. Fava, Santino Del & Gupta, Rangan & Pierdzioch, Christian & Rognone, Lavinia, 2024. "Forecasting international financial stress: The role of climate risks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    4. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    5. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
    6. Ma, Yong & Li, Shuaibing & Zhou, Mingtao, 2025. "Twitter-based market uncertainty and global stock volatility predictability," The North American Journal of Economics and Finance, Elsevier, vol. 75(PA).
    7. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    8. He, Mengxi & Wen, Danyan & Xing, Lu & Zhang, Yaojie, 2024. "Industry volatility concentration and the predictability of aggregate stock market volatility," International Review of Economics & Finance, Elsevier, vol. 95(C).
    9. Pham, Linh & Kamal, Javed Bin, 2024. "Blessings or curse: How do media climate change concerns affect commodity tail risk spillovers?," Journal of Commodity Markets, Elsevier, vol. 34(C).
    10. Alexandridis, Antonios K. & Panopoulou, Ekaterini & Souropanis, Ioannis, 2024. "Forecasting exchange rate volatility: An amalgamation approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
    11. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    12. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2024. "Machine-learning stock market volatility: Predictability, drivers, and economic value," International Review of Financial Analysis, Elsevier, vol. 94(C).
    13. 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.
    14. 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.
    15. Jiang, Fuwei & Liu, Hongkui & Tang, Guohao & Yu, Jiasheng, 2024. "Global mispricing matters," Journal of International Money and Finance, Elsevier, vol. 147(C).
    16. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    17. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2025. "Volatility forecasting and volatility-timing strategies: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 75(C).
    18. 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.
    19. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
    20. 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.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

    Statistics

    Access and download statistics

    Corrections

    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:intfin:v:101:y:2025:i:c:s1042443125000253. 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/intfin .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.