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Journal of Asset Management

, Volume 19, Issue 5, pp 301–315 | Cite as

Managing the financial consequences of weather variability

  • Jean-Louis BertrandEmail author
  • Xavier Brusset
Original Article
  • 27 Downloads

Abstract

Cool summers or warm winters affect sales of scores of products of all businesses operating in the 70% of activity sectors that are exposed to weather variability. The renewed interest in investigating the role of weather on business activity is prompted by the development of the weather index-based financial market, fostered by increasing weather variability and more reliable weather data. Drawing on the case of a manufacturer of sunscreen products, we model the influence of weather on sales in a way that supports the implementation of index-based financial cover. We evaluate the maximum potential sales loss caused by adverse weather, construct a weather index-based cover, and demonstrate its effectiveness in reducing sales variability. Knowledge of models that link weather and sales allows analysts and asset managers to better understand the contribution of weather to sales, to anticipate its effects on financial performance, and to implement risk mitigation strategies.

Keywords

Weather sensitivity Weather risk management Decision making Statistical model 

References

  1. Agnew, M.D., and J.P. Palutikof. 1999. The impacts of climate on retailing in the UK with particular reference to the anomalously hot summer of 1995. International Journal of Climatology 19(13): 1493–1507.CrossRefGoogle Scholar
  2. Agnew, M.D., and J.E. Thornes. 1995. The weather sensitivity of the UK food retail and distribution industry. Meteorological Applications 2: 137–147.CrossRefGoogle Scholar
  3. Ahčan, A. 2012. Statistical analysis of model risk concerning temperature residuals and its impact on pricing weather derivatives. Insurance Mathematics and Economics 50: 131–138.CrossRefGoogle Scholar
  4. Ailawadi, K.L., B.A. Harlam, J. César, and D. Trounce. 2006. Promotion profitability for a retailer: The role of promotion, brand, category, and store characteristics. Journal of Marketing Research 43: 518–535.CrossRefGoogle Scholar
  5. Arguez, A., and R. Vose. 2011. The definition of the standard WMO climate normal the key to deriving alternative climate normals. Bulletin of American Meteorological Society 92: 699–704.CrossRefGoogle Scholar
  6. Arunraj, N.S., and D. Ahrens. 2016. Estimation of non-catastrophic weather impacts for retail industry. International Journal of Retail and Distribution Management 44: 731–753.CrossRefGoogle Scholar
  7. Auffhammer, M., S. Hsiang, W. Schlenker, and A. Sobel. 2013. Global climate models: A user guide for economists. Review of Environmental Economics and Policy 7(2): 181–198.CrossRefGoogle Scholar
  8. Bahng, Y., and D. Kincade. 2012. The relationship between temperature and sales. International Journal of Retail and Distribution Management 40(6): 410–426.CrossRefGoogle Scholar
  9. Banks, E. 2001. Weather risk management: Markets, products, and applications. Basingstoke: Palgrave Macmillan.Google Scholar
  10. Barndorff-Nielsen, O. 1978. Hyperbolic distributions and distributions on hyperbolae. Scandinavian Journal of Statistics 5: 151–157.Google Scholar
  11. Barndorff-Nielsen, O. 1997. Normal inverse gaussian distributions and stochastic volatility modelling. Scandinavian Journal of Statistics 24: 1–13.CrossRefGoogle Scholar
  12. Beatty, T.K., J.P. Shimshack, and R.J. Volpe. 2015. Disaster preparedness and disaster response: Evidence from bottled water sales before and after tropical cyclones. Working paper.Google Scholar
  13. Bertrand, J.-L. 2010. La gestion du risque météorologique en entreprise. Ph.D. thesis, Université Paris Ouest Nanterre La Défense.Google Scholar
  14. Bertrand, J.-L., X. Brusset, and M. Fortin. 2015. Assessing and hedging the cost of unseasonal weather: Case of the apparel sector. European Journal of Operational Research 244(1): 261–276.CrossRefGoogle Scholar
  15. Bertrand, J.-L., and Parnaudeau, M. 2015. Ranking the impact of climate variability on UK retail sectors: A path to resilience. Working Paper Available at SSRN: http://ssrn.com/abstract=2675965 or  https://doi.org/10.2139/ssrn.2675965.
  16. Bertrand, J.-L., and M. Parnaudeau. 2017a. No more blaming the weather: A retailer’s approach to measuring and managing weather variability. International Journal of Retail and Distribution Management 45: 730–761.CrossRefGoogle Scholar
  17. Bertrand, J.-L., and Parnaudeau, M. 2017b. Understanding the economic effects of abnormal weather to mitigate the risk of business failures. Journal of Business Research.  https://doi.org/10.1016/j.jbusres.2017.09.016.Google Scholar
  18. Brockett, P., M. Wang, and C. Yang. 2005. Weather derivatives and weather risk management. Risk Management and Insurance Review 8(1): 127–140.CrossRefGoogle Scholar
  19. Brooks, H.E., A. Witt, and M.D. Eilts. 1997. Verification of public weather forecasts available via the media. Bulletin of the American Meteorological Society 78: 2167–2178. https://doi.org/10.1175/1520-0477(1997)078<2167:VOPWFA>2.0.CO;2.
  20. Cachon, G. 2004. Supply chain coordination with contracts. In Handbooks in operations research and management science: Supply chain management, Ch. 6, vol. 11, ed. T. de Kok and S. Graves, 229–340. New York: Elsevier.Google Scholar
  21. Cao, M. 2000. Pricing the weather. Risk, 67–70. http://www.riskpublications.com/risk.
  22. Davis, M. 1998. Option prices in incomplete markets. In Mathematics of derivatives securities. Cambridge University Press.Google Scholar
  23. Dell, M., B.F. Jones, and B.A. Olken. 2014. What do we learn from the weather? The new climate-economy literature. Journal of Economic Literature 52(3): 740–798.CrossRefGoogle Scholar
  24. Dischel, R., 2002a. Introduction to the weather market: Dawn to mid-morning. In Climate risk and the weather market: Financial risk management with weather hedges, 25–41. London, Risk Books.Google Scholar
  25. Dischel, R., 2002b. . Weather Derivative Modelling and Valuation: A Statistical Perspective. In Climate Risk and the Weather Market: Financial Risk Management with Weather Hedges, 127–150. London: Risk Books.Google Scholar
  26. Dutton, J. 2002. Opportunities and priorities in a new era for weather and climate services. Bulletin of American Meteorological Society 83(9): 1303–1311.CrossRefGoogle Scholar
  27. Eriksson, A., E. Ghysels, and F. Wang. 2009. The normal inverse gaussian distribution and the pricing of derivatives. The Journal of Derivatives 16(3): 23–37.CrossRefGoogle Scholar
  28. Geman, H. 1999. Insurance and weather derivatives: From exotic options to exotic underlyings, Working Paper, Dauphine Recherche en Management. http://ideas.repec.org/p/dau/papers/123456789-3433.html.
  29. Geman, H., and M.-P. Leonardi. 2005. Alternative approaches to weather derivatives pricing. Managerial Finance 31(6): 46–72.CrossRefGoogle Scholar
  30. Granger, C.W.J., and Pesaran, M.H. 1999. Economic and statistical measures of forecast accuracy, Working Paper. https://www.repository.cam.ac.uk/handle/1810/421.
  31. Gustafson, K. 2016. A $500 million hit and a bleak forecast for retail. CNBC.Google Scholar
  32. Hanley, H. 1999. Hedging the force of nature. Risk Professional 1: 21–25.Google Scholar
  33. Hershey, L., and Breslin, E. 2015. Meteo protect: Empowering the bottom line wth weather modeling. Report, SAP.Google Scholar
  34. Hu, Q.S., Skaggs, K. 2009. Accuracy of 6–10 day precipitation forecasts and its improvement in the past six years. In: 7th NOAA Annual climate prediction Application Science Workshop. Science and Technology Infusion Climate Bulletin. NOAA National Weather Service. http://www.nws.noaa.gov/ost/climate/STIP/RServices/huq_032509.htm
  35. IPCC. 2014. Climate change 2014: Impacts, adaptation and vulnerability. Report, Intergovernmental Panel on Climate Change. www.ipcc-wg2.gov/AR5.
  36. Jewson, S., and A. Brix. 2005. Weather derivative valuation: The meteorological, statistical, financial and mathematical foundations. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  37. Jewson, S., and Zervos, M. 2005. No-arbitrage pricing of weather derivatives in the presence of a liquid swap market, Working Paper. http://www.mth.kcl.ac.uk/research/finmath/articles/jewson-zervos.pdf.
  38. Kalnin, A. 2004. An empirical analysis of territorial encroachment within franchised and company-owned branded chains. Marketing Science 23(4): 476–489.CrossRefGoogle Scholar
  39. Larsen, P.H. 2006. Estimating the sensitivity of U.S. economic sectors to weather. Working Paper, Cornell University.Google Scholar
  40. Lazo, J.K., M. Lawson, P.H. Larsen, and D.M. Waidmann. 2011. U.S. economic sensitivity to weather variability. Bulletin of American Meteorological Society 92: 709–720.CrossRefGoogle Scholar
  41. Linden, F. 1962. Consumer markets: Merchandising weather. The Conference Board Business Record 19(6): 15–16.Google Scholar
  42. Maunder, W.J. 1968. Effect of significant climatic factors on agricultural production and incomes: A New Zealand example. Monthly Weather Review 96(1): 39–46.CrossRefGoogle Scholar
  43. Maunder, W.J. 1973. Weekly weather and economic activities on a national scale: An example using united states retail trade data. Weather 28(1): 2–19.CrossRefGoogle Scholar
  44. Milne, R. 2016. Late spring chills h&m sales. London: The Financial Times.Google Scholar
  45. Mu, X. 2007. Weather, storage, and natural gas price dynamics: Fundamentals and volatility. Energy Economics 29: 46–63.CrossRefGoogle Scholar
  46. Müller, A., and M. Grandi. 2000. Weather derivatives: A risk management tool for weather-sensitive industries. The Geneva Papers on Risk and Insurance 25(2): 273–287.CrossRefGoogle Scholar
  47. Murray, K.B., F.D. Muro, A. Finn, and P.P. Leszczyc. 2010. The effect of weather on consumer spending. Journal of Retailing and Consumer Services 17: 512–520.CrossRefGoogle Scholar
  48. Nenni, M.E., L. Giustiniano, and L. Pirolo. 2013. Demand forecasting in the fashion industry: A review. International Journal of Engineering Business Management 5(Special issue: innovations in fashion industry): 1–6.Google Scholar
  49. Parnaudeau, M., and J.-L. Bertrand. 2018. The contribution of weather variability to economic sectors. Applied Economics.  https://doi.org/10.1080/00036846.2018.1458200.Google Scholar
  50. Parsons, A.G. 2001. The association between daily weather and daily shopping patterns. Australasian Marketing Journal 9: 78–84.CrossRefGoogle Scholar
  51. Pres, J. 2009. Measuring non-catastrophic weather risks for businesses. The Geneva Papers on Risk and Insurance Issues and Practice 34: 425–439.CrossRefGoogle Scholar
  52. Prettenthaler, F., J. Köberl, and D.N. Bird. 2016. Weather value at risk: A uniform approach to describe and compare sectoral income risks from climate change. Science of the Total Environment 543: 1010–1018.CrossRefGoogle Scholar
  53. Quayle, R.G., and H.F. Diaz. 1980. Heating degree day data applied to residential heating energy consumption. Journal of Applied Meteorology 19: 241–246.CrossRefGoogle Scholar
  54. Rosselló-Nadal, J. 2014. How to evaluate the effects of climate change on tourism. Tourism Management 42: 334–340.CrossRefGoogle Scholar
  55. Shor, M. 1963. Exploratory work in measurement of the effect of weather factors on retail sales. In Proceedings of the American Statistical Association, 54–58.Google Scholar
  56. Starr-McCluer, M. 2000. The effect of weather on retail sales. Tech. rep.Google Scholar
  57. Steele, A.T. 1951. Weather’s effect on sales of a department store. Journal of Marketing 15: 436–443.CrossRefGoogle Scholar
  58. Subak, S., J.P. Palutikof, M.D. Agnew, S.J. Watson, C.G. Bentham, M.G.R. Cannell, M. Hulme, S. McNally, J.E. Thornes, D. Waughray, and J.C. Woods. 2000. The impact of the anomalous weather of 1995 on the UK economy. Climatic Change 44(1): 1–26.CrossRefGoogle Scholar
  59. Swamynathan, Y., and Layne, N. 2016. Macy\(^{\prime }\)s to cut jobs, shut stores amid weak holiday sales. Reuters.Google Scholar
  60. WeatherUnlocked. 2014. Weather and ecommerce: How weather impacts retail website traffic and online sales. Report. http://www.weatherunlocked.com/blog/2014/august/weather-and-ecommerce-how-weather-impacts-retail-website-traffic-and-online-sales.
  61. Wilks, D.S. 1998. Multisite generalization of a daily stochastic rainfall generation model. Journal of Hydrology 210: 178–191.CrossRefGoogle Scholar
  62. WMO. 2013. WMO statement on the status of the global climate in 2012. Report 1108, World Meteorological Organization.Google Scholar
  63. Zhelyazkov, G. 2011. Agile supply chain: Zara’s case study analysis. Tech. rep. http://galinzhelyazkov.com/?cat=3.

Copyright information

© Macmillan Publishers Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.ESSCA School of ManagementAngersFrance
  2. 2.Skema Business SchoolUCALilleFrance

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