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Research Express@NCKU - Articles DigestResearch Express@NCKU Volume 6 Issue 2 - October 17, 2008[ http://research.ncku.edu.tw/re/articles/e/20081017/3.html ]HDD AND CDD OPTION PRICING WITHMARKET PRICE OF WEATHER RISK FORTAIWANHung-Hsi Huang 1 , Yung-Ming Shiu 2,* , Pei-Syun Lin 31 Graduate Institute of Finance, National Pingtung University of Science & Technology, 1, HseuhFu Road, Neipu, Pingtung 91201, Taiwan2 Department of Business Administration, National Cheng Kung University, Tainan, Taiwan3 Cathay United Bank, Taichung, Taiwanyungming@mail.ncku.edu.twJournal of Futures Markets, Vol. 28, No. 8, 790-814 (2008)In the past few years, we have witness the tremendous growth of derivativecontract in terms of volume. In order to meet the demand of arbitrager,hedgers and speculators, different types of derivatives are newly designed andtransacted on the market. One of the types of derivatives which are gettingpopular is weather derivatives. The main reason why weather derivatives aremore and more important is that many sectors whose business profits aredirectly related to variations in weather, e.g., the farming industry, the energysector, and theme parks.Weather derivatives are relatively new to Taiwan. With a view to develop localized weather derivatives, itis necessary to price such derivatives with market price of weather risk. To date, however, there is nouniversally recognized approach to pricing these contracts. It should be noted that pricing weatherderivatives is different from pricing traditional derivatives, because the payoff from weather derivativesis dependent on weather indexes which are calculated based on temperature, rather than the price ofcash market instruments such as stocks, currencies, interest rates, and commodities. Because theunderlying assets of weather derivatives, weather indexes, are not tradable, we cannot use the arbitragefreeapproach to pricing weather derivatives. Moreover, temperature follows a mean reverting processand the temperature derivatives market is incomplete. Therefore, we cannot apply the Black-Scholesformula to price such derivatives. So far, some methods have been proposed to price weather derivatives,such as burn analysis.This research further develops the long-term temperature model proposed in prior studies by taking intoaccount ARCH/GARCH effects to reflect the clustering of volatility in temperature. We employ adatabase of daily maximum and minimum temperatures measured in degrees Celsius over the 1974-2003 periods. A sample of 21,900 daily highs/lows is obtained from the Central Weather Bureau,Taiwan. As shown in Figures 1a and 1b, the temperature has been oscillating and has increased oversample time. These characteristics justify the inclusion of seasonality and trend of temperature in themodel. Having investigating the graphs and descriptive statistics of daily average temperature andresiduals of ordinary least squares for the model for temperature, we further find that the distributionsfor daily average temperature and residuals are platkurtic and leptokurtic respectively and that both ofthem are negatively skewed. In our research, both the fixed variance model and the ARCH model are1 of 3
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