An Empirical and Comparative Study into the Approaches of Hedging the Geographical Basis Risk of Weather Derivatives

Abstract

Abstract: The existence of geographical basis risk makes it less effective for weather derivatives to guard against weather risks. It is necessary to combine the characteristics of the data to compare the effects of different hedging approaches. In this paper, based on the hedging theory of geographical basis risk for temperature index options, we select the 1978-2015 daily average temperature data of Weifang, Shandong province and Nanjing, Jiangsu province in China as samples to construct a spatial portfolio of temperature index options by comparing the liner combination method with the inverse distance weighting method. The results demonstrate that, as the spatial-portfolio number of temperature index options varies in a certain range, the root mean square error (RMSE) values obtained by both liner combination method and inverse distance weighting method display a U-shapted change trend, which denotes the optimal portfolio exists. In addition, both the two methods can reduce the geographical basis risk of weather derivatives. In spite of that, the inverse distance weighting method causes slighter fluctuation of RMSE values, which decline as the power exponent increases. Thus, the inverse distance weighting method is more practical and is recommended for determining optimal portfolio weights of temperature index options.

Key words: geographical basis risk, temperature index options, inverse distance weighting, weather risk

Li Yong, Shi Feng, Jiang Zhitang. An Empirical and Comparative Study into the Approaches of Hedging the Geographical Basis Risk of Weather Derivatives[J]. Management Review, 2022, 34(5): 3-12.

References

[1] Roth M., Ulardic C., and Trueb J. Critical Success Factor for Weather Risk Transfer Solutions in the Agricultural Sector:A Reinsurer's View[J]. Agricultural Finance Review, 2008,68(1):1-7
[2] 朱晓寒,李向阳,王诗莹. 自然灾害链情景态势组合推演方法[J]. 管理评论, 2016,28(8):143-151
[3] 吴吉东,傅宇,张洁,李宁. 1949-2013年中国气象灾害灾情变化趋势分析[J]. 自然资源学报, 2014, 29(9):1520-1530
[4] Vedenov D. V., Barnett B. J. Efficiency of Weather Derivatives as Primary Crop Insurance Instruments[J]. Journal of Agricultural and Resource Economics, 2004,29(3):387-403
[5] Chen G., Roberts M. C. Weather Derivatives in the Presence of Index and Geographical Basis Risk:Hedging Dairy Profit Risk[C]. Proceeding of the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management. St. Louis, MO., 2004
[6] Woodard J. D., Garcia P. Basis Risk and Weather Hedging Effectiveness[J]. Agricultural Finance Review, 2007,68(1):99-117
[7] Dischel B. At Last:A Model for Weather Risk[J]. Energy and Power Risk Management, 1998,11(3):20-21
[8] Garman M., Blanco C., Erickson R. Weather Derivative:Instruments and Pricing Issue[R]. Financial Engineering Associates, 2000
[9] Diebold F. X., Campbell S. D. Weather Forecasting for Weather Derivatives[R]. University of Pennsylvania Institute for Economic Research, Technical Report, 2001
[10] Ah čan A. Statistical Analysis of Model Risk Concerning Temperature Residuals and Its Impact on Pricing Weather Derivatives[J]. Insurance:Mathematics and Economics, 2012,50(1):131-138
[11] Markus H. Pricing and Hedging Temperature Futures Derivatives under Weather Forecasts[R]. SSRN Electronic Journal, 2015
[12] Hess M. Pricing Temperature Derivatives under Weather Forecasts[R]. Social Science Electronic Publishing, 2018
[13] Tesfahun B., Aemiro S., Gurju A. Pricing Weather Derivatives Index Based on Temperature:The Case of Bahir Dar, Ethiopia[J]. Journal of Resources and Ecology, 2019,10(4):415-423
[14] Campbell S., Diebold F. X. Weather Forecasting for Weather Derivatives[J]. Journal of the American Statistical Association, 2005,100(469):6-16
[15] Wolfgang K. H., Brenda L. C., Okhrin O., et al. Localizing Temperature Risk[J]. Journal of the American Statistical Association, 2016,111(516):1491-1508
[16] Hess M. Modeling and Pricing Precipitation Derivatives Under Weather Forecasts[J]. International Journal of Theoretical and Applied Finance, 2016,19(7):93-117
[17] Alexandridis A. K., Kampouridis M., Cramer S. A Comparison of Wavelet Networks and Genetic Programming in the Context of Temperature Derivatives[J]. International Journal of Forecasting, 2017,33(1):21-47
[18] 李永,夏敏,梁力铭. 基于O-U模型的天气衍生品定价研究——以气温期权为例[J]. 预测, 2012,31(2):18-22
[19] 王晶. 天气衍生品定价模型的构建[J]. 统计与决策, 2016,(15):152-155
[20] Ederington L. The Hedging Performance of the New Futures Markets[J]. Journal of Finance, 1979,(34):157-170
[21] Haushalter G. D. Financing Policy, Basis Risk, and Corporate Hedging:Evidence from Oil and Gas Producers[J]. Journal of Finance, 2000,55(1):107-152
[22] Jensen N. D., Mude A. G., Barrett C. B. How Basis Risk and Spatiotemporal Adverse Selection Influence Demand for Index Insurance:Evidence from Northern Kenya[J]. Food Policy, 2018,74:172-198
[23] Ceballos F. Estimating Spatial Basis Risk in Rainfall Index Insurance:Methodology and Application to Excess Rainfall Insurance in Uruguay[R]. IFPRI Discussion Papers, 2016
[24] Berg E., Schmitz B. Weather-based Instruments in the Context of Whole-farm Risk Management[J]. Agricultural Finance Review, 2008,68(1):119-133
[25] Odening M., Musshoff O., Xu W. Analysis of Rainfall Derivatives Using Daily Precipitation Models:Opportunities and Pitfalls[J]. Agricultural Finance Review, 2007,67(1):135-156
[26] Stowasser M. Modelling Rain Risk:A Multi-order Markov Chain Model Approach[J]. The Journal of Risk Finance, 2011,13(1):45-60
[27] Ritter M., Mußhoff O., Oding M. Minimizing Geographical Basis Risk of Weather Derivatives Using a Multi-site Rainfall Model[J]. Computational Economics, 2014, 44(1):67-86
[28] 李永,马宇,崔习刚. 天气衍生品基差风险量化及对冲效果研究[J]. 管理评论, 2015,27(10):33-43
[29] Cao X. F., Okhrin O. Odening M., Ritter M. Modelling Spatio-temporal Variability of Temperature[J]. Computational Statistics, 2015,30(3):745-766
[30] Boyd M., Porth B., Porth L., et al. The Impact of Spatial Interpolation Techniques on Spatial Basis Risk for Weather Insurance:An Application to Forage Crops[J]. North American Actuarial Journal, 2019,23(2):1-22
[31] Dalhaus T., Musshoff O., Finger R. Phenology Information Contributes to Reduce Temporal Basis Risk in Agricultural Weather Index Insurance[J]. Scientific Reports, 2018,8(1):1-10
[32] Mußhoff O., Odening M., Xu W. Management of Climate Risks in Agriculture:Will Weather Derivatives Permeate?[J]. Applied Economics, 2011,43(9):1067-1077
[33] Shepard D. A. Two-dimensional Interpolation Function for Irregularly-spaced Data[C]. In Proceedings of the 1968 ACM National Conference, 1968
[34] 高晓梅,秦增良,李树军,等. 近45年来潍坊市气温的年际和年代际变化分析[J]. 现代农业科技, 2008,(12):351-354
[35] 邓山,陆晓明,陆宝宏,等. 南京市近53年气温和降水量特征分析[J]. 水电能源科学, 2014,32(8):14-17
[36] 王晓莹,杨丹,邵银龙. 南京市近60年气候变化特征分析[J]. 水资源与水工程学报, 2016, 27(4):119-124