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    题名: 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
    作者: 李沃牆
    贡献者: 陳樹衡
    李沃牆
    关键词: 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
    日期: 1998
    上传时间: 2016-04-01 17:13:17 (UTC+8)
    摘要: 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.
    描述: 博士
    國立政治大學
    經濟學系
    資料來源: http://thesis.lib.nccu.edu.tw/record/#A2002000460
    数据类型: thesis
    显示于类别:[經濟學系] 學位論文

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