Pricing temperature‐based weather derivatives in China

Ahmet Göncü

Journal of Risk Finance, 2012, vol. 13, issue 1, 32-44

Abstract: Purpose - The purpose of this paper is to propose a feasible model for the daily average temperatures of Beijing, Shanghai and Shenzhen, in order to price temperature‐based weather derivatives; also to derive analytical approximation formulas for the sensitivities of these contracts. Design/methodology/approach - This study proposes a seasonal volatility model that estimates daily average temperatures of Beijing, Shanghai and Shenzhen using the mean‐reverting Ornstein‐Uhlenbeck process. It then uses the analytical approximation and Monte Carlo methods to price heating degree days and cooling degree days options for these cities. In addition, it derives and calculates the option sensitivities on the basis of an analytical approximation formula. Findings - There exists a strong seasonality in the volatility of daily average temperatures of Beijing, Shanghai and Shenzhen. To model the seasonality Fourier approximation is applied to the squared volatility of daily temperatures. The analytical approximation formulas and Monte Carlo simulation produce very similar prices for heating/cooling degree days options in Beijing and Shanghai, a result that also verifies the convergence of the Monte Carlo and approximation estimators. However, the two methods do not produce converging option prices in the case of HDD options for Shenzhen. Originality/value - The article provides important insight to investors and hedgers by proposing a feasible model for pricing temperature‐based weather contracts in China and derives analytical approximations for the sensitivities of heating/cooling degree days options.

Keywords: China; Temperature distribution; Forecasting; Weather derivatives; Heating degree days options; Cooling degree days options; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers

Related works:
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:eme:jrfpps:15265941211191921

DOI: 10.1108/15265941211191921

Access Statistics for this article

Journal of Risk Finance is currently edited by Nawazish Mirza

More articles in Journal of Risk Finance from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().