An Extension of Spatial Dependence Models for Estimating Short-Term Temperature Portfolio Risk |
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Authors: | Robert Erhardt David Engler |
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Affiliation: | 1. Department of Mathematics and Statistics, Wake Forest University, Winston-Salem, North Carolina;2. Department of Statistics, Brigham Young University, Provo, Utah |
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Abstract: | Temperature risk is any adverse financial outcome caused by temperature outcomes. The Chicago Mercantile Exchange lists a series of financial products that link payments to temperature outcomes, and these products can help buyers manage temperature risk. Financial institutions can also hold a portfolio of these products as counterparty to the buyers facing temperature risk. Here we take an actuarial perspective to measuring the risk by modeling the daily temperatures directly. These models are then used to simulate distributions of future temperature outcomes. The model for daily temperature is a spatial ARMA-EGARCH statistical model that incorporates dependence in both time and space, in addition to modeling the volatility. Simulations from this model are used to build up distributions of temperature outcomes, and we demonstrate how actuarial risk measures of the portfolio can then be estimated from these distributions. |
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