陳安斌;姜林杰祐;
頁: 1-10
日期: 1999/01
摘要: 本研究針對芝加哥商業交易所之德國馬克外匯選擇權市場進行實證研究，嘗試利用基因演算法自動演化之類神經網路來架構一新的選擇權評價模式，與傳統之Black-Scholes評價模式相比較，並評估這兩種方法對市場價格的誤差程度與解釋能力。研究期間涵蓋1990年至1992年，共計3年。研究結果顯示，類神經網路評價模式不論在誤差程度、變 動程度或解釋能力上都優於Black-Scholes評價模式。表示在德國馬克外匯選擇權市場中，基因演算法自動演化之類神經網路能夠提供一個比Black-Scholes評價模式更接近市價且更穩定的選擇權價格之評價模式。
關鍵字: 外匯選擇權;實證研究;Black-Scholes評價模式;基因演算法;類神經網路 ;
Abstract: This research applies the Neural Network on the pricing of specific options and then compares the results with the outputs from the traditional method. Here, Deutsche Mark (DM) options traded in CME are chosen as the foreign currency option contracts. The test-ing time period considered is during January 1, 1990 to December 31, 1992. The result show that no matter in error degrees, variant degrees and interpret capability, the Neural Network-based method always has better result than that from the Black-Scholes pricing model. Meanwhile, in the test of the Deutsche Mark currency market, the pricing process by using the new pricing model also shows that the pricing outcome is better and more stable than that from the traditional Black-Scholes pricing model.
Keywords: Currency option;Empirical study;Black-Scholes pricing model;Neural network ;

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