利用人工智慧技術預測企業財務危機

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Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/51288

Title:	利用人工智慧技術預測企業財務危機 Predicting Financial Distress Using Artificial Intelligence Techniques
Authors:	高煜軒
Contributors:	會計學系
Keywords:	深度學習財務危機預測決策樹隨機森林長短期記憶模型卷積神經網路 deep learning Predicting Financial Distress Decision Tree Random Forest long short-term memory model convolutional neural network
Date:	2022
Issue Date:	2023-03-03 09:43:40 (UTC+8)
Abstract:	金融市場陸續開放與自由化使資本市場發展迅速，導致財務危機的發生更是層出不窮，如果能提前預測財務危機的發生，更能當下找出應對之策，找出失敗的根源避免危機的產生。本研究以台灣經濟新報(Taiwan Economic Journal, TEJ)收集2000 年至2021 年台灣上市櫃發生財務危機之公司為主要研究對象，以二階段來建構模型，第一階段使用隨機森林(Random Forest)與決策樹C5.0(Decision Tree C5.0)來進行重要變數的篩選，再以卷積神經網路(convolutional neural network)和長短期記憶模型(long short-term memory model)來建立有效的財務危機預測模型，並對學術研究及實務界提出有效建議。 The successive opening and liberalization of the financial market has led to the rapid development of the capital market, which has led to the occurrence of financial crises. The research data comes from Taiwan Economic Journal (TEJ), the sampling period is from 2000 to 2021. This study uses a two-stage way to construct the model. First, the decision tree C5.0 and random forest are used to screen out important variables, and then the convolutional neural network (CNN) and long short-term memory (LSTM) model are used to construct an effective financial crisis prediction model. This study will make effective suggestions for academic research and practice.
Appears in Collections:	[Department of Accounting & Graduate Institute of Accounting] Thesis

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