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標題: A Comparison of Different Methods in Forecasting Financial Crisis
作者: 黃堂軒
Huang, Tang-Hsuan
關鍵字: 財務危機;financial crisis;類神經網路;類神經模糊;存活分析法;訊號分析法;neural network;neuro fuzzy;survival analysis;signal approach
出版社: 企業管理學系所
引用: 中文部分 林金賢、劉沂佩、鄭育書、陳育成 (民93)。具學習性之模糊專家系統在財務危機預測上之應用。管理學報,21 (3),291-309。 林郁翎 (民91)。銀行危機預警綜合指標之建立—Signal Extraction Approach與Panel Logit Model 之結合。未出版之碩士論文,東吳大學經濟學研究所,台北市。 郭芳宜 (民92)。訊號分析法於企業財務預警之應用。未出版之碩士論文,靜宜大學企業管理研究所,台中縣。 陳耀茂 (民93)。類神經網路PC Neuron使用手冊。臺北市:鼎茂圖書出版股份有限公司。 葉怡成 (民92)。類神經網路模式應用與實作。臺北市:儒林圖書有限公司。 葉銀華、李存修 (民91)。整合公司治理、會計資訊與總體經濟敏感度之財務危機模型(行政院國家科學委員會專題研究計畫成果報告,NSC90-2416-H-030-004)。台北縣:輔仁大學國際貿易與金融學系。 魏曉琴 (民93)。財務危機預警模型之研究—以台灣地區上市公司為例。未出版之碩士論文,國立交通大學財務金融研究所,新竹市。 英文部分 Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609. Altman, E. I., Haldeman, R. G., and Narayanan, P. (1977). ZETA analysis: a new model to identify bankruptcy risk of corporations. Journal of Banking and Finance, 1(1), 29–51. Altrock, C. V. (1996). Fuzzy logic and neuron fuzzy applications in business and finance. New Jersey: Prentice-Hall Inc. Atiya, A. F. (2001). 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Over forty years of development in the Finance literature, scholars have researched on issues concerning financial crisis forecasting. The researches could be classified into two groups. The first group incorporates different types of forecasting variables to improve the accuracy of financial crisis forecasting models, such as corporate governance variables and macroeconomic sensitivities. The second group uses different analytical methods to formulate financial crisis model in order to improve the model's forecasting ability
In terms of analytical tools, the main focus of previous literature is using different analytical tools to improve the model's predictibility and performance. However, a gap exists in the literature in which differences in analytical tools have not been addressed and compared to one another when applying to financial crisis forcasteing related issues, such as choices of research sample, neglecting the influences of time. Hence, this research uses twenty years of financial informations of Taiwan's firms and employ six analytical tools (multivariate discriminant analysis, logit regression, neural network, neuro fuzzy, survival analysis, and signal approach) to formulate the financial crisis forecasting model in order to compare the differences in usability and applicability related issues of analytical tools.
Empirical evidences show that in the short run, all the analytical tools exibit sound performance. Moreover, as the time period increases between the forecasting point and the crisis, artificial intelligence have a better performance than other tools. Using logitudinal analysis not only can solve the problem of sampling biase, but it can also observe the dynamic process of the financial crisis. Lastly, this research discusses the applicability of different analytical tools under different requirements and circumstances.

在分析方法方面,過去文獻多著重以不同方析工具來改善模型的預測能力與績效,缺乏相關文獻去釐清分析工具之間的差異性,並廣泛地比較各種不同分析方法在財務危機預測的應用與其相關問題,例如:樣本的選擇、忽略時間構面的影響等問題。因此,本研究以台灣上市公司二十年的財務資訊,並採用六種分析方法 (多變量區別分析、羅吉斯迴歸、類神經網路、類神經模糊、存活分析法和訊號分析法) 來建構財務危機預測模型,藉此比較不同分析方法在財務危機預測問題上的使用性和相關問題。
其他識別: U0005-2706200701522700
Appears in Collections:企業管理學系所

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