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A consistent two-factor model for pricing temperature derivatives

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  • Andreas Groll
  • Brenda López-Cabrera
  • Thilo Meyer-Brandis

Abstract

We analyze a consistent two-factor model for pricing temperature derivatives that incorporates the forward looking information available in the market by specifying a model for the dynamics of the complete meteorological forecast curve. The two-factor model is a generalization of the Nelson-Siegel curve model by allowing factors with mean-reversion to a stochastic mean for structural changes and seasonality for periodic patterns. Based on the outcomes of a statistical analysis of forecast data we conclude that the two-factor model captures well the stylized features of temperature forecast curves. In particular, a functional principal component analysis reveals that the model re ects reasonably well the dynamical structure of forecast curves by decomposing their shapes into a tilting and a bending factor. We continue by developing an estimation procedure for the model, before we derive explicit prices for temperature derivatives and calibrate the market price of risk (MPR) from temperature futures derivatives (CAT, HDD, CDD) traded at the Chicago Mercantile Exchange (CME). The factor model shows that the behavior of the implied MPR for futures traded in and out of the measurement period is more stable than other estimates obtained in the literature. This con rms that at least parts of the irregularity of the MPR is not due to irregular risk perception but rather due to information misspecification. Similar to temperature derivatives, this approach can be used for pricing other non-tradable assets.

Suggested Citation

  • Andreas Groll & Brenda López-Cabrera & Thilo Meyer-Brandis, 2014. "A consistent two-factor model for pricing temperature derivatives," SFB 649 Discussion Papers SFB649DP2014-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    • Handle: RePEc:hum:wpaper:sfb649dp2014-006
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    1. Gilli, Manfred & Maringer, Dietmar & Schumann, Enrico, 2011. "Numerical Methods and Optimization in Finance," Elsevier Monographs, Elsevier, edition 1, number 9780123756626.
    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. 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.
    4. Jewson,Stephen & Brix,Anders With contributions by-Name:Ziehmann,Christine, 2005. "Weather Derivative Valuation," Cambridge Books, Cambridge University Press, number 9780521843713, January.
    5. Dorfleitner, Gregor & Wimmer, Maximilian, 2010. "The pricing of temperature futures at the Chicago Mercantile Exchange," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1360-1370, June.
    6. 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.
    7. Benth, Fred Espen & Biegler-König, Richard & Kiesel, Rüdiger, 2013. "An empirical study of the information premium on electricity markets," Energy Economics, Elsevier, vol. 36(C), pages 55-77.
    8. 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.
    9. Wolfgang Karl Härdle & Brenda López Cabrera & Ostap Okhrin & Weining Wang, 2016. "Localizing Temperature Risk," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1491-1508, October.
    10. Han Shang, 2014. "A survey of functional principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 121-142, April.
    11. Wolfgang Karl Härdle & Brenda López-Cabrera & Matthias Ritter, 2012. "Forecast based Pricing of Weather Derivatives," SFB 649 Discussion Papers SFB649DP2012-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    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. 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, December.
    14. Matthias Ritter & Oliver Mußhoff & Martin Odening, 2010. "Meteorological forecasts and the pricing of weather derivatives," SFB 649 Discussion Papers SFB649DP2010-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Benth, Fred Espen & Cartea, Álvaro & Kiesel, Rüdiger, 2008. "Pricing forward contracts in power markets by the certainty equivalence principle: Explaining the sign of the market risk premium," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2006-2021, October.
    16. Manfred Gilli & Stefan Große & Enrico Schumann, 2010. "Calibrating the Nelson–Siegel–Svensson model," Working Papers 031, COMISEF.
    17. Patrick L. Brockett & Mulong Wang & Chuanhou Yang & Hong Zou, 2006. "Portfolio Effects and Valuation of Weather Derivatives," The Financial Review, Eastern Finance Association, vol. 41(1), pages 55-76, February.
    18. Dwight R. Sanders, 2004. "Pricing Weather Derivatives," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1005-1017.
    19. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Financial markets for weather," World Scientific Book Chapters, in: Modeling and Pricing in Financial Markets for Weather Derivatives, chapter 1, pages 1-13, World Scientific Publishing Co. Pte. Ltd..
    20. 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.
    21. Philipp Hell & Thilo Meyer-Brandis & Thorsten Rheinländer, 2012. "Consistent Factor Models For Temperature Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-24.
    22. 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.
    23. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
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    Cited by:

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    3. Awdesch Melzer & Wolfgang K. Härdle & Brenda López Cabrera, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers SFB649DP2017-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Cui, Hairong & Zhou, Ying & Dzandu, Michael D. & Tang, Yinshan & Lu, Xunfa, 2019. "Is temperature-index derivative suitable for China?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    5. Alessio Giorgini & Rogemar S. Mamon & Marianito R. Rodrigo, 2021. "A Stochastic Harmonic Oscillator Temperature Model for the Valuation of Weather Derivatives," Mathematics, MDPI, vol. 9(22), pages 1-15, November.
    6. Yuji Yamada & Takuji Matsumoto, 2021. "Going for Derivatives or Forwards? Minimizing Cashflow Fluctuations of Electricity Transactions on Power Markets," Energies, MDPI, vol. 14(21), pages 1-28, November.
    7. Peng Li, 2021. "The Valuation of Weather Derivatives Using One Sided Crank–Nicolson Schemes," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 825-847, October.
    8. Shinji Kuno & Kenji Tanaka & Yuji Yamada, 2022. "Effectiveness and Feasibility of Market Makers for P2P Electricity Trading," Energies, MDPI, vol. 15(12), pages 1-24, June.

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    More about this item

    Keywords

    factor models; consistency; pricing and hedging; weather derivatives; market price of risk;
    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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