Minimizing Geographical Basis Risk of Weather Derivatives Using A Multi-Site Rainfall Model

Matthias Ritter, Oliver Musshoff and Martin Odening

Computational Economics, 2014, vol. 44, issue 1, 67-86

Abstract: It is well known that the hedging effectiveness of weather derivatives is interfered by the existence of geographical basis risk, i.e., the deviation of weather conditions at different locations. In this paper, we explore how geographical basis risk of rainfall based derivatives can be reduced by regional diversification. Minimizing geographical basis risk requires knowledge of the joint distribution of rainfall at different locations. For that purpose, we estimate a daily multi-site rainfall model from which optimal portfolio weights are derived. We find that this method allows to reduce geographical basis risk more efficiently than simpler approaches as, for example, inverse distance weighting. Copyright Springer Science+Business Media New York 2014

Keywords: Risk management; Weather risk; Regional diversification; Portfolio weights (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://hdl.handle.net/10.1007/s10614-013-9410-y (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:44:y:2014:i:1:p:67-86

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-013-9410-y

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().