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    政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 >  Item 140.119/32653
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32653


    Title: 以財務比率、共同比分析和公司治理指標預測 上市公司財務危機之基因演算法與支持向量機的計算模型
    Applying Genetic Algorithms and Support Vector Machines for Predicting Financial Distresses with Financial Ratios and Features for Common-Size Analysis and Corporate Governance
    Authors: 黃珮雯
    Huang, Pei-Wen
    Contributors: 劉昭麟
    Liu, Chao-Lin
    黃珮雯
    Huang, Pei-Wen
    Keywords: 財務危機預測
    共同比分析
    公司治理
    基因演算法
    支持向量機
    Financial Distress Prediction
    Common-Size Analysis
    Corporate Governance
    Genetic Algorithms
    Support Vector Machines
    Date: 2005
    Issue Date: 2009-09-17 13:57:07 (UTC+8)
    Abstract: 過去已有許多技術應用來建立預測財務危機的模型,如統計學的多變量分析或是類神經網路等分類技術。這些早期預測財務危機的模型大多以財務比率作為變數。然而歷經安隆(Enron)、世界通訊(WorldCom)等世紀騙局,顯示財務數字計算而成的財務比率有其天生的限制,無法在公司管理階層蓄意虛增盈餘時,及時給予警訊。因此,本論文初步探勘共同比分析、公司治理及傳統的Altman財務比率等研究方法,試圖突破財務比率在財務危機預測問題的限制,選出可能提高財務危機預測的特徵群。接著,我們進一步應用基因演算法篩選質性與非質性的特徵,期望藉由基因演算法裡子代獲得親代間最優基因的交配過程,可以讓子代的適應值最大化,找出最佳組合的特徵群,然後以此特徵群訓練支持向量機預測模型,以提高財務預測效果並降低公眾的損失。實驗結果顯示,共同比分析與公司治理等相關特徵確實能提升預測財務危機模型的預測效果,我們應當用基因演算法嘗試更多質性與非質性的特徵組合,及早預警財務危機公司以降低社會成本。
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    28 葉銀華、李存修與柯承恩,「公司治理與評等系統」,初刷,商智文化,台灣,民國91年10月
    29 湯玲郎與施並洲,「灰關聯分析、類神經網路、案例推理法於財務危機預警模式之應用研究」,中華管理評論,第四卷,第二號,頁25-37,民國90年3月
    Description: 碩士
    國立政治大學
    資訊科學學系
    93753013
    94
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0093753013
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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