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政大機構典藏 > 社會科學學院 > 經濟學系 > 學位論文 > Item 140.119/83839

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/83839

Title:	計算智慧在選擇權定價上的發展－人工神經網路、遺傳規劃、遺傳演算法
Authors:	李沃牆
Contributors:	陳樹衡李沃牆
Keywords:	Black-Scholes選擇權定價模型人工神經網路遺傳規劃遺傳演算法加權殘差法 Black-Scholes option pricing theory artificial neural networks genetic programming genetic algorithms weight-residual method
Date:	1998
Issue Date:	2016-04-01 17:13:17 (UTC+8)
Abstract:	Black-Scholes選擇權定價模型是各種選擇定價的開山始祖，無論在理論或實務上均獲致許多的便利及好評，美中不足的是，這種既定模型下結構化參數的估計問題，在真實體系的結構訊息未知或是不明朗時，或是模式錯誤，亦或政治結構或金融環境不知時，該模型在實證資料的評價上會面臨價格偏誤的窘境。是故，許多的數值演算法（numerical algorithms）便因應而生，這些方法一則源於對此基本模型的修正，一則是屬於逼近的數值解。 The option pricing development rapid in recent years. However, the recent rapid development of theory and the application can be traced to the pathbreaking paper by Fischer Black and Myron Scholes(1973). In that pioneer paper, they provided the first explicit general equilibrium solution to the option pricing problem for simple calls and puts and formed a basis for the contingent claim asset pricing and many subsequent academic studies. Although the Black-Scholes option pricing model has enjoyed tremendous success both in practice and research, Nevertheless, it produce biased price estimates. So, many numerical algorithms have advanced to modify the basic model.
Description:	博士國立政治大學經濟學系
Source URI:	http://thesis.lib.nccu.edu.tw/record/#A2002000460
Data Type:	thesis
Appears in Collections:	[經濟學系] 學位論文

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