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Citations for "Weather Forecasting for Weather Derivatives"

by Sean D. Campbell & Francis X. Diebold

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  1. Atak, Alev & Linton, Oliver B. & Xiao, Zhijie, 2010. "A Semiparametric Panel Model for Unbalanced Data with Application to Climate Change in the United Kingdom," MPRA Paper 22079, University Library of Munich, Germany.
  2. Elias, R.S. & Wahab, M.I.M. & Fang, L., 2014. "A comparison of regime-switching temperature modeling approaches for applications in weather derivatives," European Journal of Operational Research, Elsevier, vol. 232(3), pages 549-560.
  3. Caiado, Jorge, 2007. "Forecasting water consumption in Spain using univariate time series models," MPRA Paper 6610, University Library of Munich, Germany.
  4. Tseng, Chung-Li & Zhu, Wei & Dmitriev, Alexandre, 2009. "Variable capacity utilization, ambient temperature shocks and generation asset valuation," Energy Economics, Elsevier, vol. 31(6), pages 888-896, November.
  5. Ahčan, Aleš, 2012. "Statistical analysis of model risk concerning temperature residuals and its impact on pricing weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 131-138.
  6. Sun, Baojing & van Kooten, G. Cornelis, 2015. "Financial weather derivatives for corn production in Northern China: A comparison of pricing methods," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 201-209.
  7. Adam Clements & A S Hurn & K A Lindsay, 2008. "Developing analytical distributions for temperature indices for the purposes of pricing temperature-based weather derivatives," NCER Working Paper Series 34, National Centre for Econometric Research.
  8. Wolfram Schlenker & Michael J. Roberts, 2008. "Estimating the Impact of Climate Change on Crop Yields: The Importance of Nonlinear Temperature Effects," NBER Working Papers 13799, National Bureau of Economic Research, Inc.
  9. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
  10. Cees Diks & Valentyn Panchenko & Dick Van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
  11. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Tinbergen Institute Discussion Papers 08-050/4, Tinbergen Institute.
  12. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
  13. Dupuis, Debbie J., 2011. "Forecasting temperature to price CME temperature derivatives," International Journal of Forecasting, Elsevier, vol. 27(2), pages 602-618.
  14. Pai, Jeffrey & Ravishanker, Nalini, 2009. "A multivariate preconditioned conjugate gradient approach for maximum likelihood estimation in vector long memory processes," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1282-1289, May.
  15. Anbarci, Nejat & Boyd III, John & Floehr, Eric & Lee, Jungmin & Song, Joon Jin, 2011. "Population and income sensitivity of private and public weather forecasting," Regional Science and Urban Economics, Elsevier, vol. 41(2), pages 124-133, March.
  16. Jacob Boudoukh & Matthew Richardson & YuQing Shen & Robert F. Whitelaw, 2003. "Do Asset Prices Reflect Fundamentals? Freshly Squeezed Evidence from the OJ Market," NBER Working Papers 9515, National Bureau of Economic Research, Inc.
  17. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
  18. Jorge Caiado, 2009. "Performance of combined double seasonal univariate time series models for forecasting water demand," CEMAPRE Working Papers 0903, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  19. Hélène Hamisultane, 2008. "Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts," Working Papers halshs-00355857, HAL.
  20. Ngoc Mai Tran & Maria Osipenko & Wolfgang Karl Härdle, 2014. "Principal Component Analysis in an Asymmetric Norm," SFB 649 Discussion Papers SFB649DP2014-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  21. Preve, Daniel, 2015. "Linear programming-based estimators in nonnegative autoregression," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 225-234.
  22. 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.
  23. Massimiliano Caporin & Juliusz Pres, 2010. "Modelling and forecasting wind speed intensity for weather risk management," "Marco Fanno" Working Papers 0106, Dipartimento di Scienze Economiche "Marco Fanno".
  24. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
  25. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
  26. Musshoff, Oliver & Odening, Martin & Xu, Wei, 2006. "Modeling and Hedging Rain Risk," 2006 Annual meeting, July 23-26, Long Beach, CA 21050, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  27. 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.
  28. Ohana, Steve, 2010. "Modeling global and local dependence in a pair of commodity forward curves with an application to the US natural gas and heating oil markets," Energy Economics, Elsevier, vol. 32(2), pages 373-388, March.
  29. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
  30. FRED ESPEN BENTH & JŪRATĖ SALTYTĖ 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.
  31. 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.
  32. Fred Benth & Wolfgang Karl Härdle & Brenda López Cabrera, 2009. "Pricing of Asian temperature risk," SFB 649 Discussion Papers SFB649DP2009-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  33. Taylor, James W. & Buizza, Roberto, 2006. "Density forecasting for weather derivative pricing," International Journal of Forecasting, Elsevier, vol. 22(1), pages 29-42.
  34. Benth, Fred Espen & Taib, Che Mohd Imran Che, 2013. "On the speed towards the mean for continuous time autoregressive moving average processes with applications to energy markets," Energy Economics, Elsevier, vol. 40(C), pages 259-268.
  35. Hélène Hamisultane, 2008. "Which Method for Pricing Weather Derivatives ?," Working Papers halshs-00355856, HAL.
  36. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
  37. repec:hal:journl:peer-00834423 is not listed on IDEAS
  38. Janda, Karel & Vylezik, Tomas, 2011. "Financial Management of Weather Risk with Energy Derivatives," MPRA Paper 35037, University Library of Munich, Germany.
  39. Eckhard Platen & Jason West, 2003. "Fair Pricing of Weather Derivatives," Research Paper Series 106, Quantitative Finance Research Centre, University of Technology, Sydney.
  40. Musshoff, Oliver & Odening, Martin & Xu, Wei, 2005. "Zur Bewertung von Wetterderivaten als innovative Risikomanagementinstrumente in der Landwirtschaft," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 54(4).
  41. Mengmeng Guo & Lhan Zhou & Jianhua Z. Huang & Wolfgang Karl Härdle, 2013. "Functional Data Analysis of Generalized Quantile Regressions," SFB 649 Discussion Papers SFB649DP2013-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  42. Zhao, Jing & Guo, Zhen-Hai & Su, Zhong-Yue & Zhao, Zhi-Yuan & Xiao, Xia & Liu, Feng, 2016. "An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed," Applied Energy, Elsevier, vol. 162(C), pages 808-826.
  43. Adam Clements & A S Hurn & K A Lindsay, 2008. "Estimating the Payoffs of Temperature-based Weather Derivatives," NCER Working Paper Series 33, National Centre for Econometric Research.
  44. Demers, Jean-Guy, 2009. "Multiple zone power forwards: A value at risk framework," Energy Economics, Elsevier, vol. 31(5), pages 714-726, September.
  45. Balvers, Ronald & Du, Ding & Zhao, Xiaobing, 2012. "The Adverse Impact of Gradual Temperature Change on Capital Investment," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124676, Agricultural and Applied Economics Association.
  46. Roberto Buizza & James W. Taylor, 2004. "A comparison of temperature density forecasts from GARCH and atmospheric models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(5), pages 337-355.
  47. Andrea Barth & Fred Espen Benth & Jurgen Potthoff, 2011. "Hedging of Spatial Temperature Risk with Market-Traded Futures," Applied Mathematical Finance, Taylor & Francis Journals, vol. 18(2), pages 93-117.
  48. 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.
  49. Mengmeng Guo & Wolfgang Härdle, 2012. "Simultaneous confidence bands for expectile functions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(4), pages 517-541, October.
  50. repec:hal:journl:peer-00844810 is not listed on IDEAS
  51. Turvey, Calum G. & Norton, Michael T., 2008. "An Internet-Based Tool for Weather Risk Management," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(1), April.
  52. Baojing Sun & G. Cornelis van Kooten, 2014. "Financial Weather Options for Crop Production," Working Papers 2014-03, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
  53. Mu, Xiaoyi, 2007. "Weather, storage, and natural gas price dynamics: Fundamentals and volatility," Energy Economics, Elsevier, vol. 29(1), pages 46-63, January.
  54. 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.
  55. Dupuis, Debbie J., 2011. "Forecasting temperature to price CME temperature derivatives," International Journal of Forecasting, Elsevier, vol. 27(2), pages 602-618, April.
  56. Matthias Ritter, 2012. "Can the market forecast the weather better than meteorologists?," SFB 649 Discussion Papers SFB649DP2012-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  57. Ron Balvers & Ding Du & Xiaobing Zhao, 2009. "What Do Financial Markets Reveal about Global Warming?," Working Papers 09-04, Department of Economics, West Virginia University.
  58. Ahmet Göncü, 2013. "Comparison of temperature models using heating and cooling degree days futures," Journal of Risk Finance, Emerald Group Publishing, vol. 14(2), pages 159-178, February.
  59. Ahmet Göncü, 2011. "Pricing temperature-based weather derivatives in China," Journal of Risk Finance, Emerald Group Publishing, vol. 13(1), pages 32-44, December.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.