Temperature modelling and pricing of temperature index insurance

Abstract

In this paper, we use continuous-time autoregressive process to explain evolution of the temperature dynamics. We take data of New York daily average temperatures as our empirical study. Our analysis indicates continuous-time autoregressive of order 3 fits data very well. The model is employed in the pricing of index based temperature insurance. In the context of agricultural industry, our study revealed that the price of insurance obtained from temperature dynamical modelling is far more expensive than the price obtained from classical approaches of burn analysis and index modelling.