Thesis Type: Doctorate
Institution Of The Thesis: Middle East Technical University, Turkey
Approval Date: 2016
Thesis Language: English
Student: Aysun Türkvatan
Consultant: AZİZE HAYFAVİAbstract:
Weather has an enormous impact on many institutions, for example, in energy, agriculture, or tourism sectors. For example, a gas provider faces the reduced demand in gas in case of hot winter. Weather derivatives can be used as a tool to manage the risk exposure towards adverse or unexpected weather conditions. Weather derivatives are the ﬁnancial contracts with underlying depending on weather variables such as temperature,humidity,precipitationorsnow. Sincethetemperatureisthemostcommonly used weather variable, we consider the temperature based weather derivatives. These are the ﬁnancial contracts written on several temperature indices, such as the cumulative average temperature (CAT), or the cooling degree days (CDD). We ﬁrst propose a regime-switching model for the temperature dynamics, where the parameters depend on a Markov chain. Also, since the jumps in the temperature are directly related to the regime switch, we model them by the chain itself. Morever, the estimation and forecast of the proposed model is considered. It is shown that forecast performance of the proposed model is in line with the existing models considered. After modeling the temperature dynamics, to price the derivatives, the risk-neutral probability is to be speciﬁed. Since temperature (and hence the index) is not a tradeable asset, any probability measure being equivalent to the objective probability is a risk-neutral probability. We consider a generalized version of the Esscher transform to select an equivalent measure. Then we derive prices of weather derivatives written on several temperature indices.