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Title: | 香港企業信用風險預警制度之建構與研究 Research of Credit Risk Prediction in Hong Kong |
Authors: | 林霈吾 Lin, Pei-Wu |
Contributors: | 林宛瑩 林霈吾 Lin, Pei-Wu |
Keywords: | 信用風險預警 企業失敗 邏輯迴歸分析 多元判別分析 credit risk prediction financial distress logistic regression analysis multiple discriminant analysis |
Date: | 2019 |
Issue Date: | 2019-09-05 15:40:20 (UTC+8) |
Abstract: | 近十年的快速成長吸引了各類國際企業與投資機構進入中國市場,然而由於法制的不成熟及國家體制的特殊,舞弊層出不窮。在此背景下,香港轉而成為眾多外資的首選,然而國內外資金的流入帶來繁榮也為香港市場帶來未知數,市場對信用風險預警制度的需求日漸提高,至今卻沒有太多相關之研究。為了瞭解影響香港企業信用風險之因素,本文以2008年到2017年間的香港主板上市公司為研究對象,參考過去文獻與香港市場現況為危機事件定義,再透過邏輯迴歸、常態機率迴歸及多元判別分析進行實證研究,分別以流動性、獲利性及安全性三個面向探討有關之解釋變數,研究結果顯示多元辦別分析模型在特定組合下於危機事件發生前一年有高達66.25%的危機樣本預測準確率,而於危機事件前兩年之危機樣本預測效果則僅不到1%的下降。 Due to the high-speed of growth in China, the hot money of foreign investors pours in and the China stock market become popular in Asian. However, the weakness in laws and regulations make it risky to invest in this market. In contrast to China, the stable financial environment and relatively sound legal systems make Hong Kong a better choice for foreign companies and investors. These cash flows bring prosperity to Hong Kong, and increase the instability and the needs of credit risk prediction model in the whole market at the same time. In order to realize the factors of financial distress for Hong Kong listed company, I select some listed company during 2008-2017 as the samples. By taking the financial environment into account, I determine the definitions of distress. Then, I use logistic regression model, probit model and multiple discriminant analysis model to test the three different kinds of variables and figure out which are significant to distress prediction. The result shows that the accuracy of multiple discriminant analysis model in distress company can up to 66.25 percent. |
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Description: | 碩士 國立政治大學 會計學系 106353020 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0106353020 |
Data Type: | thesis |
DOI: | 10.6814/NCCU201900968 |
Appears in Collections: | [會計學系] 學位論文
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