經濟的好壞和天氣息息相關，過去企業只能利用保險或銷售策略來規避天氣對其造成之營收不穩，但自 1997 年芝加哥商業交易所 (Chicago Mercantile Exchange; CME) 開始發行天氣衍生性金融商品 (weather derivatives) 後，天氣衍生性金融商品便成為天氣相關風險的有效管理工具。本研究以 Melanie Cao 及 Jason Wei 在 2004 年所提出之消費型定價方法 (consumption-based pricing method) 為基礎。研究目標主要有二；首先為氣溫模型之比較。在已知氣溫實際資料下，計算 Campbell and Diebold (2005) 氣溫模型對真實情況的配適殘差，以 p-value 值檢定氣溫模型之好壞。第二個目標為在考量天氣風險為數量風險的情況下，將氣溫衍生性金融商品著重數量避險之概念 (quantity hedge)，加入於定價模型中，並以此定價模型與未加入數量避險特點之定價方法作比較、分析模擬結果，映證數量避險對於氣溫衍生性金融商品之重要性。

　Economic outcomes and weather conditions are closely related. Until CME started to release weather derivatives in 1997, industries used to purchase insurances or use other selling strategies to protect their profits from serious losses caused by adverse weather conditions. As the weather derivatives trading market developing, weather derivatives have become efficient hedging tools for companies to fight against weather risk. The thesis is based on Melanie Cao and Jason Wei's (2004) consumption-based pricing method. And it has two objectives. The first one is the comparison of the temperature modeling. We use the actual meteorological data to compute the residuals of the Campbell and Diebold's (2005) temperature model, and use p-value to test if the temperature model is good enough. Since the weather risk is one kind of quantity risk, the second goal is to combine consumption-based pricing method and quantity hedge. Then we contrast the modified pricing model to the previous one to prove the importance of the quantity hedge.

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