NDLI: Rainfall derivatives pricing with an underlying semi-Markov model for precipitation occurrences

Content Provider	Springer Nature Link
Author	Masala, Giovanni
Copyright Year	2013
Abstract	Weather derivatives represent a new and particular kind of contingent claim which shares a specific underlying weather index. These derivatives are written for different temperature indices, hurricanes, frost, snowfall and rainfall, and they are available for several cities. Our paper focuses on rainfall derivatives. In order to price this kind of derivatives, we have to model daily rainfall sequences at a specific location. For this purpose, we adopt a non-homogeneous parametric semi-Markov model to describe the rainfall occurrences, and a mixture of exponential distributions for rainfall amounts. The underlying Markov process has the obvious two states: dry and wet. In addition, dry and wet sequences are estimated by using best-fitting techniques. The model parameters are determined thanks to classical log-likelihood maximization. We finally price some rainfall contracts issued by the Chicago Mercantile Exchange through Monte Carlo simulation. The numerical applications and the parameter estimations are carried out using real data.
Starting Page	717
Ending Page	727
Page Count	11
File Format	PDF
ISSN	14363240
Journal	Stochastic Environmental Research and Risk Assessment
Volume Number	28
Issue Number	3
e-ISSN	14363259
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2013-08-30
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Semi-Markov process Waiting time distributions Rainfall occurrences Rainfall intensity Monte Carlo simulation Rainfall derivatives Math. Application in Environmental Science Earth Sciences Probability Theory and Stochastic Processes Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Computational Intelligence Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
Content Type	Text
Resource Type	Article
Subject	Environmental Chemistry Environmental Engineering Water Science and Technology Safety, Risk, Reliability and Quality

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