IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/202246.html
   My bibliography  Save this paper

Climate Risks and State-Level Stock-Market Realized Volatility

Author

Listed:
  • Matteo Bonato

    (Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa; IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France)

  • Oguzhan Cepni

    (Copenhagen Business School, Department of Economics, Porcelaenshaven 16A, Frederiksberg DK-2000, Denmark; Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050, Ankara, Turkey)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)

Abstract

We analyze the predictive value of climate risks for state-level realized stock-market volatility, computed, along with other realized moments, based on high-frequency intra-day U.S. data (September, 2011 to October, 2021). A model-based bagging algorithm recovers that climate risks have predictive value for realized volatility at intermediate and long (one and two months) forecast horizons. This finding also holds for upside (``good") and downside (``bad") realized volatility. The benefits of using climate risks for predicting state-level realized stock-market volatility depend on the shape and (as-)symmetry of a forecaster's loss function.

Suggested Citation

  • Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Climate Risks and State-Level Stock-Market Realized Volatility," Working Papers 202246, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202246
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nasr, Adnen Ben & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2016. "Forecasting the volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. regime switching," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 559-571.
    2. Bruno Ćorić & Vladimir Šimić, 2021. "Economic disasters and aggregate investment," Empirical Economics, Springer, vol. 61(6), pages 3087-3124, December.
    3. 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.
    4. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2022. "A moving average heterogeneous autoregressive model for forecasting the realized volatility of the US stock market: Evidence from over a century of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 384-400, January.
    5. Ströbel, Johannes & Wurgler, Jeffrey, 2021. "What do you think about climate finance?," CEPR Discussion Papers 16622, C.E.P.R. Discussion Papers.
    6. Thomas Chaney & David Sraer & David Thesmar, 2012. "The Collateral Channel: How Real Estate Shocks Affect Corporate Investment," American Economic Review, American Economic Association, vol. 102(6), pages 2381-2409, October.
    7. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
    8. Bua, Giovanna & Kapp, Daniel & Ramella, Federico & Rognone, Lavinia, 2022. "Transition versus physical climate risk pricing in European financial markets: a text-based approach," Working Paper Series 2677, European Central Bank.
    9. Henk Berkman & Ben Jacobsen & John B. Lee, 2017. "Rare disaster risk and the expected equity risk premium," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(2), pages 351-372, June.
    10. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
    11. Jerry Tsai & Jessica A. Wachter, 2015. "Disaster Risk and its Implications for Asset Pricing," NBER Working Papers 20926, National Bureau of Economic Research, Inc.
    12. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
    13. 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).
    14. Sheng, Xin & Gupta, Rangan & Çepni, Oğuzhan, 2022. "The effects of climate risks on economic activity in a panel of US states: The role of uncertainty," Economics Letters, Elsevier, vol. 213(C).
    15. Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(4), pages 1107-1125.
    16. 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.
    17. 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.
    18. Amaya, Diego & Christoffersen, Peter & Jacobs, Kris & Vasquez, Aurelio, 2015. "Does realized skewness predict the cross-section of equity returns?," Journal of Financial Economics, Elsevier, vol. 118(1), pages 135-167.
    19. Herrnstadt, Evan & Muehlegger, Erich, 2014. "Weather, salience of climate change and congressional voting," Journal of Environmental Economics and Management, Elsevier, vol. 68(3), pages 435-448.
    20. Muller, Ulrich A. & Dacorogna, Michel M. & Dave, Rakhal D. & Olsen, Richard B. & Pictet, Olivier V. & von Weizsacker, Jacob E., 1997. "Volatilities of different time resolutions -- Analyzing the dynamics of market components," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 213-239, June.
    21. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    22. George M. Korniotis & Alok Kumar, 2013. "State-Level Business Cycles and Local Return Predictability," Journal of Finance, American Finance Association, vol. 68(3), pages 1037-1096, June.
    23. Jerry Tsai & Jessica A. Wachter, 2015. "Disaster Risk and Its Implications for Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 219-252, December.
    24. Ruipeng Liu & Rangan Gupta, 2022. "Investors’ Uncertainty and Forecasting Stock Market Volatility," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(3), pages 327-337, July.
    25. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    26. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023. "Investor Confidence and Forecastability of US Stock Market Realized Volatility: Evidence from Machine Learning," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 24(1), pages 111-122, January.
    27. Arthur A. Benthem & Edmund Crooks & Stefano Giglio & Eugenie Schwob & Johannes Stroebel, 2022. "The effect of climate risks on the interactions between financial markets and energy companies," Nature Energy, Nature, vol. 7(8), pages 690-697, August.
    28. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    29. 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.
    30. David E. Rapach & Jack K. Strauss & Mark E. Wohar, 2008. "Chapter 10 Forecasting Stock Return Volatility in the Presence of Structural Breaks," Frontiers of Economics and Globalization, in: Forecasting in the Presence of Structural Breaks and Model Uncertainty, pages 381-416, Emerald Group Publishing Limited.
    31. Mei, Dexiang & Liu, Jing & Ma, Feng & Chen, Wang, 2017. "Forecasting stock market volatility: Do realized skewness and kurtosis help?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 153-159.
    32. Berkman, Henk & Jacobsen, Ben & Lee, John B., 2011. "Time-varying rare disaster risk and stock returns," Journal of Financial Economics, Elsevier, vol. 101(2), pages 313-332, August.
    33. 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.
    34. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    35. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    36. Robert J. Barro & José F. Ursúa, 2012. "Rare Macroeconomic Disasters," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 83-109, July.
    37. Flori, Andrea & Pammolli, Fabio & Spelta, Alessandro, 2021. "Commodity prices co-movements and financial stability: A multidimensional visibility nexus with climate conditions," Journal of Financial Stability, Elsevier, vol. 54(C).
    38. Matthew E. Kahn & Matthew J. Kotchen, 2011. "Business Cycle Effects On Concern About Climate Change: The Chilling Effect Of Recession," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 257-273.
    39. Salisu, Afees A. & Demirer, Riza & Gupta, Rangan, 2022. "Financial turbulence, systemic risk and the predictability of stock market volatility," Global Finance Journal, Elsevier, vol. 52(C).
    40. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    41. Sheng, Xin & Gupta, Rangan & Cepni, Oguzhan, 2022. "Persistence of state-level uncertainty of the United States: The role of climate risks," Economics Letters, Elsevier, vol. 215(C).
    42. Joshua D. Coval & Tobias J. Moskowitz, 1999. "Home Bias at Home: Local Equity Preference in Domestic Portfolios," Journal of Finance, American Finance Association, vol. 54(6), pages 2045-2073, December.
    43. Joshua D. Coval & Tobias J. Moskowitz, 2001. "The Geography of Investment: Informed Trading and Asset Prices," Journal of Political Economy, University of Chicago Press, vol. 109(4), pages 811-841, August.
    44. Azi Ben-Rephael & Zhi Da & Ryan D. Israelsen, 2017. "It Depends on Where You Search: Institutional Investor Attention and Underreaction to News," The Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 3009-3047.
    45. repec:hal:spmain:info:hdl:2441/75koqefued8i7pihbrl9u84p4u is not listed on IDEAS
    46. Christo Pirinsky & Qinghai Wang, 2006. "Does Corporate Headquarters Location Matter for Stock Returns?," Journal of Finance, American Finance Association, vol. 61(4), pages 1991-2015, August.
    47. Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate risk and commodity currencies," Working Paper 2020/18, Norges Bank.
    48. Robert J. Barro & Jose F. Ursua, 2008. "Macroeconomic Crises since 1870," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 39(1 (Spring), pages 255-350.
    49. Pham, Anh Viet & Adrian, Christofer & Garg, Mukesh & Phang, Soon-Yeow & Truong, Cameron, 2021. "State-level COVID-19 outbreak and stock returns," Finance Research Letters, Elsevier, vol. 43(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. Li, Xiaodan & Gong, Xue & Xing, Lu, 2024. "The impact of presidential economic approval rating on stock volatility: An industrial perspective," Finance Research Letters, Elsevier, vol. 63(C).
    2. Rangan Gupta & Anandamayee Majumdar & Christian Pierdzioch & Onur Polat, 2024. "Climate Risks and Real Gold Returns over 750 Years," Forecasting, MDPI, vol. 6(4), pages 1-16, October.
    3. Massimiliano Caporin & Petre Caraiani & Oguzhan Cepni & Rangan Gupta, 2024. "Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks," Working Papers 202407, University of Pretoria, Department of Economics.
    4. Carè, R. & Fatima, R. & Boitan, I.A., 2024. "Central banks and climate risks: Where we are and where we are going?," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 1200-1229.
    5. 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).
    6. Elie Bouri & Rangan Gupta & Christian Pierdzioch, 2024. "Modeling the Presidential Approval Ratings of the United States using Machine-Learning: Does Climate Policy Uncertainty Matter?," Working Papers 202406, University of Pretoria, Department of Economics.
    7. Matteo Foglia & Vasilios Plakandaras & Rangan Gupta & Qiang Ji, 2024. "Long-Span Multi-Layer Spillovers between Moments of Advanced Equity Markets: The Role of Climate Risks," Working Papers 202415, 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.
    1. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Business applications and state‐level stock market realized volatility: A forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 456-472, March.
    2. 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).
    3. 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).
    4. Rangan Gupta & Qiang Ji & Christian Pierdzioch, 2024. "Climate Policy Uncertainty and Financial Stress: Evidence for China," Working Papers 202428, University of Pretoria, Department of Economics.
    5. Massimiliano Caporin & Petre Caraiani & Oguzhan Cepni & Rangan Gupta, 2024. "Predicting the Conditional Distribution of US Stock Market Systemic Stress: The Role of Climate Risks," Working Papers 202407, University of Pretoria, Department of Economics.
    6. Kejin Wu & Sayar Karmakar & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Stock Market Volatility Over a Century in an Emerging Market Economy: The Case of South Africa," Working Papers 202326, University of Pretoria, Department of Economics.
    7. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
    8. Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch, 2023. "El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 785-801, July.
    9. Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2022. "Risk aversion and the predictability of crude oil market volatility: A forecasting experiment with random forests," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1755-1767, August.
    10. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2022. "Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 303-315, March.
    11. 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.
    12. Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Realized Stock-Market Volatility: Do Industry Returns have Predictive Value?," Working Papers 2020107, University of Pretoria, Department of Economics.
    13. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    14. Elie Bouri & Rangan Gupta & Asingamaanda Liphadzi & Christian Pierdzioch, 2024. "Forecasting Stock Returns Volatility of the G7 Over Centuries: The Role of Climate Risks," Working Papers 202424, University of Pretoria, Department of Economics.
    15. Demirer, Riza & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2019. "Time-varying risk aversion and realized gold volatility," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    16. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
    17. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023. "Investor Confidence and Forecastability of US Stock Market Realized Volatility: Evidence from Machine Learning," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 24(1), pages 111-122, January.
    18. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Sustainability, MDPI, vol. 12(10), pages 1-11, May.
    19. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
    20. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "The role of time‐varying rare disaster risks in predicting bond returns and volatility," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 327-340, July.

    More about this item

    Keywords

    Finance; State-level data; Realized stock-market volatility; Climate-related predictors; Forecasting;
    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
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pre:wpaper:202246. 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: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    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.