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Equilibrium trading of climate and weather risk and numerical simulation in a Markovian framework

机译:马氏框架中气候和天气风险的均衡交易及数值模拟

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摘要

We consider financial markets with agents exposed to external sources of risk caused, for example, by short-term climate events such as the South Pacific sea surface temperature anomalies widely known by the name El Nino. Since such risks cannot be hedged through investments on the capital market alone, we face a typical example of an incomplete financial market. In order to make this risk tradable, we use a financial market model in which an additional insurance asset provides another possibility of investment besides the usual capital market. Given one of the many possible market prices of risk, each agent can maximize his individual exponential utility from his income obtained from trading in the capital market, the additional security, and his risk-exposure function. Under the equilibrium market-clearing condition for the insurance security the market price of risk is uniquely determined by a backward stochastic differential equation. We translate these stochastic equations via the Feynman-Kac formalism into semi-linear parabolic partial differential equations. Numerical schemes are available by which these semilinear pde can be simulated. We choose two simple qualitatively interesting models to describe sea surface temperature, and with an ENSO risk exposed fisher and farmer and a climate risk neutral bank three model agents with simple risk exposure functions. By simulating the expected appreciation price of risk trading, the optimal utility of the agents as a function of temperature, and their optimal investment into the risk trading security we obtain first insight into the dynamics of such a market in simple situations.
机译:我们考虑金融市场中的代理商面临外部风险,例如短期气候事件(如南太平洋海表温度异常现象,通常被称为厄尔尼诺现象)引起的风险。由于不能仅通过在资本市场上进行投资来对冲此类风险,因此我们面临着金融市场不完整的典型例子。为了使这种风险可交易,我们使用了金融市场模型,在该模型中,除了通常的资本市场之外,额外的保险资产还提供了另一种投资可能性。给定多种可能的市场风险价格,每个代理商都可以通过从资本市场交易中获得的收入,额外的证券以及其风险敞口功能,最大化自己的指数效用。在保险证券的均衡市场结算条件下,风险的市场价格唯一地由后向随机微分方程确定。我们通过Feynman-Kac形式主义将这些随机方程式转换为半线性抛物型偏微分方程。可以使用数值方案来模拟这些半线性pde。我们选择两个简单的定性有趣的模型来描述海表温度,并使用ENSO风险暴露的渔民和渔民以及气候风险中性库这三种具有简单风险暴露功能的模型代理。通过模拟风险交易的预期升值价格,作为温度函数的代理的最佳效用以及它们对风险交易安全性的最佳投资,我们可以在简单的情况下首次了解这种市场的动态。

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