財務比率、投資決策與公司績效之實證研究－全球金融海嘯前後比較

An Empirical Study on Financial Rations, Investment Decision and Corporate Performance-Before Financial Tsunami and after

余惠芳(Hui-Fun Yu) ； 陳瑞惠(Jui-Hui Chen) ； 陳家蓁(Chia-Chen Chang)

《全球管理與經濟》 6卷2期 (2010/12) Pp. 1-18

https://doi.org/10.6565/JGME.2010.6(2).1

摘要

本文研究係首次嘗試探討全球金融海嘯發生前後，台灣上市公司之存活分析，找出影響公司績效之顯著變數並比較其差異，建立財務預警棋型，期能在公司發生財務危機前，提前預測出可能發生之機率，降低公司發生財務危機之可能性，進而提高公司績效，達事前預警與風險管理之效。實證分析上，利用財務比率變數作為解釋變數，以統計科學方法羅吉斯迴歸模型，建構出企業財務預警模式。實證結果發現，預測金融海嘯前後企業之財務危機，其前一至前三年金融海嘯前的預測竿確率分別為91.62%，93.55%，90.38%；金融海嘯後的預測準確率分別為92.90%，91.67%，100.00%。除前二年外，其餘兩個年度金融海嘯後之預測準確率較金融海嘯前顯然有提高，財務比率變數可為投資人做投資決策分析之參考指標；就金融海嘯後之財務資訊觀察，企業適度增加負債比率、降低自有資金比率，可改善財務結構；增加總資產週轉率，可增強企業之經管能力；增加借款依存度，可提升現金流量；增加內部保留比率，可提高公司獲利能力，則發生財務危機的機率將下降，進而提高公司績效。準此，本文之實證價值與管理意涵為財務風險管理、投資決策與財務預測。

關鍵字

金融海嘯 ； 財務風險管理 ； 投資決策 ； 財務預測

並列摘要

This paper primarily used statistical methods to establish financial early-warning models that made it be possible to predict in advance the probability of a company experiencing financial distress in Taiwan. This empirical analysis is the first study that attempts to use the financial ratios before the global financial tsunami and after, and this study used Logistic regressions model. Findings, upon examining the predictor variables for corporate financial distress at one, two and three years prior to distress, we found that after the global financial tsunami predictive accuracy is 92.90%, 91.67%, 100.00% higher before the global financial tsunami that is 91.62%, 93.55%, 90.38%. To increase the degrees of predictive accuracy, we employed the investment decisions variables is financial ratios. And we found that the achievement result of the conventional company after the global financial tsunami, the debt outside appropriately, to increase total assets turnover and debt/equity ratio and retention ratio. Therefore, this paper may be useful for researchers and practitioners who are focusing on financial risk management, investment decisions and financial forecasting implementation.

並列關鍵字

Financial Tsunami ； Financial Risk Management ； Investment Decisions ； Financial Forecasting