Multivariate Long-Memory Modeling of Daily Surface Air Temperatures and the Valuation of Weather Derivative Portfolios

25 Pages Posted: 25 Jul 2003

See all articles by Stephen Jewson

Stephen Jewson

Risk Management Solutions

Rodrigo Caballero

University of Chicago - Department of the Geophysical Sciences

Date Written: July 2002

Abstract

It has been shown in earlier work that long memory can be detected in multidecadal time series of daily surface air temperature measured at individual weather stations. Here, we present a multivariate stochastic model capable of capturing both the long memory at each station, and the lagged cross-correlations between the stations. It is shown that this model can be useful for the management of portfolios of weather derivatives.

Keywords: weather derivatives, weather risk, daily temperatures, temperature time-series, arfima, varfima, multivariate

JEL Classification: G12, G13

Suggested Citation

Jewson, Stephen and Caballero, Rodrigo, Multivariate Long-Memory Modeling of Daily Surface Air Temperatures and the Valuation of Weather Derivative Portfolios (July 2002). Available at SSRN: https://ssrn.com/abstract=405800 or http://dx.doi.org/10.2139/ssrn.405800

Stephen Jewson (Contact Author)

Risk Management Solutions ( email )

London EC3R 8NB
United Kingdom

Rodrigo Caballero

University of Chicago - Department of the Geophysical Sciences ( email )

5734 S. Ellis Avenue
Chicago, IL 60637
United States
001 773 702 9505 (Phone)

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