Uncertainty and robustness in weather derivative models

Ahmet Göncü, Yaning Liu, Giray Ökten*, M. Yousuff Hussaini

*Bu çalışma için yazışmadan sorumlu yazar

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2 Atıf (Scopus)

Özet

Pricing of weather derivatives often requires a model for the underlying temperature process that can characterize the dynamic behavior of daily average temperatures. The comparison of different stochastic models with a different number of model parameters is not an easy task, especially in the absence of a liquid weather derivatives market. In this study, we consider four widely used temperature models in pricing temperature-based weather derivatives. The price estimates obtained from these four models are relatively similar. However, there are large variations in their estimates with respect to changes in model parameters. To choose the most robust model, i.e., the model with smaller sensitivity with respect to errors or variation in model parameters, the global sensitivity analysis of Sobol’ is employed. An empirical investigation of the robustness of models is given using temperature data.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıMonte Carlo and Quasi-Monte Carlo Methods - MCQMC 2014
EditörlerRonald Cools, Dirk Nuyens
YayınlayanSpringer New York LLC
Sayfalar351-365
Sayfa sayısı15
ISBN (Basılı)9783319335056
DOI'lar
Yayın durumuYayınlandı - 2016
Harici olarak yayınlandıEvet
Etkinlik11th International Conference on Monte Carlo and Quasi Monte Carlo Methods in Scientific Computing, MCQMC 2014 - Leuven, Belgium
Süre: 6 Nis 201411 Nis 2014

Yayın serisi

AdıSpringer Proceedings in Mathematics and Statistics
Hacim163
ISSN (Basılı)2194-1009
ISSN (Elektronik)2194-1017

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???event.eventtypes.event.conference???11th International Conference on Monte Carlo and Quasi Monte Carlo Methods in Scientific Computing, MCQMC 2014
Ülke/BölgeBelgium
ŞehirLeuven
Periyot6/04/1411/04/14

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Publisher Copyright:
© Springer International Publishing Switzerland 2016.

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