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Utility-based pricing of weather derivatives

机译:基于公用事业的天气衍生产品定价

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Since the underlying of the weather derivatives is not a traded asset, these contracts cannot be evaluated by the traditional financial theory. Cao and Wei [2004. Weather derivatives valuation and market price of weather risk. The Journal of Futures Markets 24, no. 11: 1065-89] price them by using the consumption-based asset pricing model of Lucas [1978. Asset prices in an exchange economy. Econometrica 46, no. 6: 1429-45] and by assuming different values for the constant relative risk aversion coefficient. Instead of taking this coefficient as given, we suggest in this article to estimate it by using the consumption data and the quotations of one of the most transacted weather contracts which is the New York weather futures on the Chicago Mercantile Exchange. We apply the well-known generalized method of moments introduced by Hansen [1982. Large sample properties of generalized method of moments estimators. Econometrica 50, no. 4: 1029-54] to estimate it as well as the simulated method of moments (SMM) attributed to Lee and Ingram [1991. Simulation estimation of time-series models. Journal of Econometrics 47, no. 2-3: 197-205] and Duffie and Singleton [1993. Simulated moments estimation of Markov models of asset prices. Econometrica 61, no. 4: 929-52], This last method is studied since it is presumed to give satisfactory results in the case of the weather derivatives for which the prices are simulated. We find that the estimated coefficient from the SMM approach must have improbably high values in order to have the calculated weather futures prices matching the observations.
机译:由于天气衍生工具的基础不是交易资产,因此这些合同无法通过传统金融理论进行评估。曹和魏[2004。天气衍生品的估值和天气风险的市场价格。期货市场杂志24,没有。 11:1065-89]使用卢卡斯[1978]的基于消费的资产定价模型对它们进行定价。交换经济中的资产价格。计量经济学46,没有。 [6:1429-45],并为恒定的相对风险规避系数假设不同的值。在本文中,我们建议不要使用给定的系数,而是使用消费数据和交易量最大的天气合约之一(即芝加哥商业交易所的纽约天气期货)的报价进行估算。我们应用了由Hansen [1982.]引入的著名的矩量广义方法。矩量估计器广义方法的大样本属性。 Econometrica 50,否。 [4:1029-54]进行估计,以及Lee和Ingram [1991。时序模型的仿真估计。计量经济学杂志47,没有。 2-3:197-205]和Duffie and Singleton [1993。资产价格马尔可夫模型的模拟矩估计。计量经济学61,没有。 [4:929-52],研究了最后一种方法,因为在模拟价格的天气导数的情况下,假定可以给出令人满意的结果。我们发现,SMM方法的估计系数必须具有难以置信的高值,以使计算出的天气期货价格与观测值匹配。

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