Vol. 23 No. 41 (2010), Artículos
Vol. 23 No. 41 (2010)

Weather Derivative Assessment Using Temperature Stochastic Modeling at El Dorado International Airport in Bogotá

Artículos
Published 2010-12-01
Mariano González Sánchez
Juan M. Nave Pineda
PDF (Spanish)

Keywords

weather derivatives
stochastic process
mean reversion
seasonality

How to Cite

González Sánchez, M., & Nave Pineda, J. M. (2010). Weather Derivative Assessment Using Temperature Stochastic Modeling at El Dorado International Airport in Bogotá. Cuadernos De Administración, 23(41). https://doi.org/10.11144/Javeriana.cao23-41.vdsc
ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver AMA

Download Citation

Endnote/Zotero/Mendeley (RIS) BibTeX
Almetrics
 
Dimensions
 

Google Scholar
 
Search GoogleScholar

Abstract

The weather and its effects have been two of the main fields of scientific discussion in recent years. In economics, that has meant greater analysis of the risks that the weather generates on the economy, in general, and on business activities, in particular. Therefore, financial derivative products have been developed, enabling economic agents to protect themselves against such risks. Some of the most customary weather derivatives include an underlying factor that is a city’s temperature measured at the airport. In that context, this article analyzes how such temperature derivatives can be applied to Eldorado International Airport. To do so, an Ornstein-Uhlenbeck mean reversion model is adjusted to the observed temperature, its validity is verified using simulation techniques, and diverse derivative products are assessed.

 

PDF (Spanish)

Alaton, P.; Djehiche, B. and Stillberger, D. (2002). On modelling and pricing weather derivatives. Applied Mathematical Finance, 9 (1), 1-20.

Basawa, I. V. and Prasaka Rao, B. L. S. (1980). Statistical inference for stochastic processes. New York: Academic Press.

Benth, F. E. (2003). On arbitrage-free pricing of weather derivatives based on fractional Brownian Motion. Applied Mathematical Finance, 10 (4), 303-324.

Bibby, B. M. and Sørensen, M. (1995). Martingale estimation functions for discretely observed diffusion processes. Bernoulli, I (1-2), 17-39.

Brockwell, P. J. and Davis, R. A. (1990). Time Series: theory and methods (2nd ed.). New York: Springer.

Brody, D. C.; Syroka, J. and Zervos, M. (2002). Dynamical pricing of weather derivatives. Quantitative Finance, 2 (3), 189-198.

Davis, M. H. A. (2001). Pricing weather derivatives by marginal value. Quantitative Finance, 1 (3), 305-308.

Dornier, F. and Queruel, M. (2000). Caution to the Wind. Risk, Energy and Power Risk Management, August, 30-32.

Geman, H. (1999). The Bermuda triangle: weather, electricity and insurance derivatives. En H. Geman (ed.), Insurance and weather derivatives: from exotic options to exotic underlyings. London: Risk Books.

Platen, E. and West, J. (2004). A fair pricing approach to weather derivatives. Asian-Pacific Financial Markets, 11 (1), 23-53.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.