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Climate Risks and U.S. Stock-Market Tail Risks: A Forecasting Experiment Using over a Century of Data

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometric & Allied Research, University of Ibadan, Ibadan, Nigeria; 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)

  • Rangan Gupta

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

  • Renee van Eyden

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

Abstract
We examine the predictive value of the uncertainty associated with growth in temperature for stock-market tail risk in the United States using monthly data that cover the sample period from 1895:02 to 2021:08. To this end, we measure stock-market tail risk by means of the popular Conditional Autoregressive Value at Risk (CAViaR) model. Our results show that accounting for the predictive value of the uncertainty associated with growth in temperature, as measured either by means of standard generalized autoregressive conditional heteroskedasticity (GARCH) models or a stochastic-volatility (SV) model, mainly is beneficial for a forecaster who suffers a sufficiently higher loss from an underestimation of tail risk than from a comparable overestimation.

Suggested Citation

  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Renee van Eyden, 2021. "Climate Risks and U.S. Stock-Market Tail Risks: A Forecasting Experiment Using over a Century of Data," Working Papers 202165, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202165
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    1. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    2. Cao, Melanie & Wei, Jason, 2005. "Stock market returns: A note on temperature anomaly," Journal of Banking & Finance, Elsevier, vol. 29(6), pages 1559-1573, June.
    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. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. Peillex, Jonathan & El Ouadghiri, Imane & Gomes, Mathieu & Jaballah, Jamil, 2021. "Extreme heat and stock market activity," Ecological Economics, Elsevier, vol. 179(C).
    6. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 333-376.
    7. Ravi Bansal & Marcelo Ochoa & Dana Kiku, 2016. "Climate Change and Growth Risks," NBER Working Papers 23009, National Bureau of Economic Research, Inc.
    8. Jie Hou & Wendong Shi & Jingwei Sun, 2019. "Stock Returns, weather, and air conditioning," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-10, July.
    9. Bergeaud, A. & Cette, G. & Lecat, R., 2015. "Productivity trends from 1890 to 2012 in advanced countries," Rue de la Banque, Banque de France, issue 07, June..
    10. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    11. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "International tail risk and World Fear," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 244-259.
    12. 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.
    13. 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.
    14. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 1-21, February.
    15. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2021. "Computing Macro-Effects and Welfare Costs of Temperature Volatility: A Structural Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 347-394, August.
    16. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Erratum to Rejoinder on: Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 504-504.
    17. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    18. Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
    19. Donadelli, M. & Jüppner, M. & Riedel, M. & Schlag, C., 2017. "Temperature shocks and welfare costs," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 331-355.
    20. Piergiorgio Alessandri & Haroon Mumtaz, 2021. "The Macroeconomic Cost of Climate Volatility," Working Papers 928, Queen Mary University of London, School of Economics and Finance.
    21. Jonathan Peillex & Imane El Ouadghiri & Mathieu Gomes & Jamil Jaballah, 2021. "extreme heat and stock market activity (vol 179, 106810, 2021)," Post-Print hal-03688865, HAL.
    22. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    23. Li, Xiao-Ming & Rose, Lawrence C., 2009. "The tail risk of emerging stock markets," Emerging Markets Review, Elsevier, vol. 10(4), pages 242-256, December.
    24. Lu, Jing & Chou, Robin K., 2012. "Does the weather have impacts on returns and trading activities in order-driven stock markets? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 79-93.
    25. Salisu, Afees A. & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil prices over 150 years: The role of tail risks," Resources Policy, Elsevier, vol. 75(C).
    26. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Rejoinder on: Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 418-426.
    27. John Y. Campbell, 2007. "Estimating the Equity Premium," NBER Working Papers 13423, National Bureau of Economic Research, Inc.
    28. 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.
    29. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    30. Robert J. Barro, 2009. "Rare Disasters, Asset Prices, and Welfare Costs," American Economic Review, American Economic Association, vol. 99(1), pages 243-264, March.
    31. Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan, 2021. "Geopolitical risk and forecastability of tail risk in the oil market: Evidence from over a century of monthly data," Energy, Elsevier, vol. 235(C).
    32. 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.
    33. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    34. Pindyck, Robert S., 2012. "Uncertain outcomes and climate change policy," Journal of Environmental Economics and Management, Elsevier, vol. 63(3), pages 289-303.
    35. Jonathan Peillex & Imane El Ouadghiri & Mathieu Gomes & Jamil Jaballah, 2021. "Extreme Heat and Stock Market Activity," Grenoble Ecole de Management (Post-Print) hal-02935431, HAL.
    36. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2017. "Temperature shocks and the cost of equity capital: Implications for climate change perceptions," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 18-34.
    37. Antonin Bergeaud & Gilbert Cette & Rémy Lecat, 2016. "Productivity Trends in Advanced Countries between 1890 and 2012," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(3), pages 420-444, September.
    38. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    39. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    40. Jonathan Peillex & Imane El Ouadghiri & Mathieu Gomes & Jamil Jaballah, 2021. "extreme heat and stock market activity (vol 179, 106810, 2021)," Grenoble Ecole de Management (Post-Print) hal-03688865, HAL.
    41. Chevapatrakul, Thanaset & Xu, Zhongxiang & Yao, Kai, 2019. "The impact of tail risk on stock market returns: The role of market sentiment," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 289-301.
    42. Jonathan Peillex & Imane El Ouadghiri & Mathieu Gomes & Jamil Jaballah, 2021. "Extreme Heat and Stock Market Activity," Post-Print hal-02935431, HAL.
    43. Makkonen, Adam & Vallström, Daniel & Uddin, Gazi Salah & Rahman, Md Lutfur & Haddad, Michel Ferreira Cardia, 2021. "The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns," Energy Economics, Elsevier, vol. 100(C).
    44. Gkillas, Konstantinos & Konstantatos, Christoforos & Tsagkanos, Athanasios & Siriopoulos, Costas, 2021. "Do economic news releases affect tail risk? Evidence from an emerging market," Finance Research Letters, Elsevier, vol. 40(C).
    45. Nahiomy Alvarez & Alessandro Cocco & Ketan B. Patel, 2020. "A new framework for assessing climate change risk in financial markets," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue 448, pages 1-8, November.
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    Cited by:

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    3. Polat, Onur & Gupta, Rangan & Cepni, Oguzhan & Ji, Qiang, 2024. "Can municipal bonds hedge US state-level climate risks?," Finance Research Letters, Elsevier, vol. 67(PB).
    4. 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).
    5. 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.
    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. 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.

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    More about this item

    Keywords

    Stock market; Tail risks; Climate risks; Forecasting; Asymmetric loss;
    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)

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