| Summary: | 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.
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