The Incremental Explanatory Power of Qualified Opinions to Predict Entities'' Financial Distress

• Main Authors: Tan, Huey-Mwnq, 田惠夢
• Other Authors: Wu Yung-Sun
• Format: Others
• Language: zh-TW
• Published: 1998
• Online Access: http://ndltd.ncl.edu.tw/handle/02634088692347434335

碩士 === 國立交通大學 === 管理科學研究所 === 86 === The probabilities for business to encounter financial difficulties are increasing because of the tremendously changing environment in recent years. Therefore, this paper want to construct a reliable model for all stakeholders to avoid unnecessary losses. Past research build prediction models by financial ratios or stock prices, but it is a debate that Taiwan is an efficacy market, and the change in stock prices are affected by a lot of uncontrollable factors. So the paper only keep financial ratios as useful variables to construct model. ! Additional financial ratios, the paper believe that CPAs'' qualified opinions have incremental explanatory power in prediction of business failure. The paper examines does qualified opinions have incremental explanatory power by comparing models which build only by financial ratios and financial ratios adding qualified opinions categorical variable. In methodology, the real data from financial statements usually do not qualify the assumptions of normal distribution and linear. There will have biases if we use traditional statistical analysis. However, if we use neural network to construct prediction model, we can ignore the above two assumptions, and are more likely the way we make judgement. The paper will compare models which construct by neural network and by traditional statistical methods(logistic and MDA). The results indicate that no matter model constructs by BPN or traditional statistical analysis, qualified opinions have incremental explanatory power. Compare with BPN and traditional statistical models, the paper finds that the prediction ability of BPN is better than of traditional statistical analysis, regarding model constructing by only financial ratios or financial ratios adding qualified opinions, no matter in training sample or test sample.