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Pricing of Asian temperature risk

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  • Benth, Fred
  • Härdle, Wolfgang Karl
  • López Cabrera, Brenda

Abstract

Weather derivatives (WD) are different from most financial derivatives because the underlying weather cannot be traded and therefore cannot be replicated by other financial instruments. The market price of risk (MPR) is an important parameter of the associated equivalent martingale measures used to price and hedge weather futures/options in the market. The majority of papers so far have priced non-tradable assets assuming zero MPR, but this assumption underestimates WD prices. We study the MPR structure as a time dependent object with concentration on emerging markets in Asia. We find that Asian Temperatures (Tokyo, Osaka, Beijing, Teipei) are normal in the sense that the driving stochastics are close to a Wiener Process. The regression residuals of the temperature show a clear seasonal variation and the volatility term structure of CAT temperature futures presents a modified Samuelson effect. In order to achieve normality in standardized residuals, the seasonal variation is calibrated with a combination of a fourier truncated series with a GARCH model and with a local linear regression. By calibrating model prices, we implied the MPR from Cumulative total of 24-hour average temperature futures (C24AT) for Japanese Cities, or by knowing the formal dependence of MPR on seasonal variation, we price derivatives for Kaohsiung, where weather derivative market does not exist. The findings support theoretical results of reverse relation between MPR and seasonal variation of temperature process.

Suggested Citation

  • Benth, Fred & Härdle, Wolfgang Karl & López Cabrera, Brenda, 2009. "Pricing of Asian temperature risk," SFB 649 Discussion Papers 2009-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  • Handle: RePEc:zbw:sfb649:sfb649dp2009-046
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    References listed on IDEAS

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    1. Fred Espen Benth & Jurate Saltyte-Benth, 2005. "Stochastic Modelling of Temperature Variations with a View Towards Weather Derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(1), pages 53-85.
    2. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2007. "Putting a Price on Temperature," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 746-767, December.
    3. Eckhard Platen & Jason West, 2004. "A Fair Pricing Approach to Weather Derivatives," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 11(1), pages 23-53, March.
    4. Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2004. "Pricing Weather Derivatives," Working Papers 28536, Arizona State University, Morrison School of Agribusiness and Resource Management.
    5. Jewson,Stephen & Brix,Anders, 2005. "Weather Derivative Valuation," Cambridge Books, Cambridge University Press, number 9780521843713, September.
    6. Turvey, Calum G., 1999. "The Essentials Of Rainfall Derivatives And Insurance," Working Papers 34149, University of Guelph, Department of Food, Agricultural and Resource Economics.
    7. Ulrich Horst & Matthias Müller, 2007. "On the Spanning Property of Risk Bonds Priced by Equilibrium," Mathematics of Operations Research, INFORMS, vol. 32(4), pages 784-807, November.
    8. Fred Espen Benth, 2003. "On arbitrage-free pricing of weather derivatives based on fractional Brownian motion," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(4), pages 303-324.
    9. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
    10. Wolfgang Karl Härdle & Brenda López Cabrera, 2012. "The Implied Market Price of Weather Risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 19(1), pages 59-95, February.
    11. Melanie Cao & Jason Wei, 2004. "Weather derivatives valuation and market price of weather risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(11), pages 1065-1089, November.
    12. Peter Alaton & Boualem Djehiche & David Stillberger, 2002. "On modelling and pricing weather derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(1), pages 1-20.
    13. Dorje Brody & Joanna Syroka & Mihail Zervos, 2002. "Dynamical pricing of weather derivatives," Quantitative Finance, Taylor & Francis Journals, vol. 2(3), pages 189-198.
    14. Hélène Hamisultane, 2007. "Extracting Information from the Market to Price the Weather Derivatives," Working Papers halshs-00079192, HAL.
    15. M. Davis, 2001. "Pricing weather derivatives by marginal value," Quantitative Finance, Taylor & Francis Journals, vol. 1(3), pages 305-308, March.
    16. Dwight R. Sanders, 2004. "Pricing Weather Derivatives," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1005-1017.
    17. Hung‐Hsi Huang & Yung‐Ming Shiu & Pei‐Syun Lin, 2008. "HDD and CDD option pricing with market price of weather risk for Taiwan," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(8), pages 790-814, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. A. Alexandridis & A. Zapranis, 2013. "Wind Derivatives: Modeling and Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 299-326, March.
    2. repec:hum:wpaper:sfb649dp2017-020 is not listed on IDEAS
    3. Härdle, Wolfgang Karl & López-Cabrera, Brenda & Ritter, Matthias, 2012. "Forecast based pricing of weather derivatives," SFB 649 Discussion Papers 2012-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. repec:hum:wpaper:sfb649dp2013-026 is not listed on IDEAS
    5. Melzer, Awdesch & Härdle, Wolfgang Karl & López Cabrera, Brenda, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers 2017-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. repec:hum:wpaper:sfb649dp2012-027 is not listed on IDEAS
    7. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, August.
    8. Šaltytė Benth, Jūratė & Benth, Fred Espen, 2012. "A critical view on temperature modelling for application in weather derivatives markets," Energy Economics, Elsevier, vol. 34(2), pages 592-602.
    9. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.
    10. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.
    11. Heng Xiong & Rogemar Mamon, 2018. "Putting a price tag on temperature," Computational Management Science, Springer, vol. 15(2), pages 259-296, June.

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    More about this item

    Keywords

    Weather derivatives; continuous autoregressive model; CAT; CDD; HDD; risk premium;
    All these keywords.

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • N23 - Economic History - - Financial Markets and Institutions - - - Europe: Pre-1913
    • N53 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - Europe: Pre-1913
    • Q59 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Other

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