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Comparison of temperature models using heating and cooling degree days futures

Comparison of temperature models using heating and cooling degree days futures Purpose – The purpose of this paper is to compare the ability of popular temperature models, namely, the models given by Alaton et al. , by Benth and Benth, by Campbell and Diebold and by Brody et al. , to forecast the prices of heating/cooling degree days (HDD/CDD) futures for New York, Atlanta, and Chicago. Design/methodology/approach – To verify the forecasting power of various temperature models, a statistical backtesting approach is utilised. The backtesting sample consists of the market data of daily settlement futures prices for New York, Atlanta, and Chicago. Settlement prices are separated into two groups, namely, “in‐period” and “out‐of‐period”. Findings – The findings show that the models of Alaton et al. and Benth and Benth forecast the futures prices more accurately. The difference in the forecasting performance of models between “in‐period” and “out‐of‐period” valuation can be attributed to the meteorological temperature forecasts during the contract measurement periods. Research limitations/implications – In future studies, it may be useful to utilize the historical data for meteorological forecasts to assess the forecasting power of the new hybrid model considered. Practical implications – Out‐of‐period backtesting helps reduce the effect of any meteorological forecast on the formation of futures prices. It is observed that the performance of models for out‐of‐period improves consistently. This indicates that the effects of available weather forecasts should be incorporated into the considered models. Originality/value – To the best of the author's knowledge this is the first study to compare some of the popular temperature models in forecasting HDD/CDD futures. Furthermore, a new temperature modelling approach is proposed for incorporating available temperature forecasts into the considered dynamic models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Risk Finance Emerald Publishing

Comparison of temperature models using heating and cooling degree days futures

Ahmet Göncü
The Journal of Risk Finance , Volume 14 (2): 20 – Feb 22, 2013
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References (20)

Publisher
Emerald Publishing
Copyright
Copyright © 2013 Emerald Group Publishing Limited. All rights reserved.
ISSN
1526-5943
DOI
10.1108/15265941311301198
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to compare the ability of popular temperature models, namely, the models given by Alaton et al. , by Benth and Benth, by Campbell and Diebold and by Brody et al. , to forecast the prices of heating/cooling degree days (HDD/CDD) futures for New York, Atlanta, and Chicago. Design/methodology/approach – To verify the forecasting power of various temperature models, a statistical backtesting approach is utilised. The backtesting sample consists of the market data of daily settlement futures prices for New York, Atlanta, and Chicago. Settlement prices are separated into two groups, namely, “in‐period” and “out‐of‐period”. Findings – The findings show that the models of Alaton et al. and Benth and Benth forecast the futures prices more accurately. The difference in the forecasting performance of models between “in‐period” and “out‐of‐period” valuation can be attributed to the meteorological temperature forecasts during the contract measurement periods. Research limitations/implications – In future studies, it may be useful to utilize the historical data for meteorological forecasts to assess the forecasting power of the new hybrid model considered. Practical implications – Out‐of‐period backtesting helps reduce the effect of any meteorological forecast on the formation of futures prices. It is observed that the performance of models for out‐of‐period improves consistently. This indicates that the effects of available weather forecasts should be incorporated into the considered models. Originality/value – To the best of the author's knowledge this is the first study to compare some of the popular temperature models in forecasting HDD/CDD futures. Furthermore, a new temperature modelling approach is proposed for incorporating available temperature forecasts into the considered dynamic models.

Journal

The Journal of Risk Finance – Emerald Publishing

Published: Feb 22, 2013

Keywords: Temperatures; Modelling; Forecasting; Futures markets; Weather derivatives; HDD/CDD futures; Backtesting; Temperature modelling; Heating/cooling degree days

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