|Title:||Use data ming [sic] techniques to build financial crisis prediction models : joining financial and non financial indicator|
|Other Title:||Use data mining techniques to build financial crisis prediction models : joining financial and non financial indicator|
|Subject:||Hong Kong Polytechnic University -- Dissertations|
Financial crises -- Prevention
|Department:||Department of Computing|
|Pages:||45 leaves : ill. ; 30 cm.|
|Abstract:||Enterprise operating status will be disclosed periodically in financial statement and investors can get fully information once the formal financial statements are disclosed and published. If executives of firms intentionally dress financial statement up, investors can not get real enterprise operating status from it. However, non-financial information was proved to be able to predict financial distress by former researchers. But few studies exploit stock information to construct financial crisis prediction model. The study uses financial information to predict corporate financial distress. We get 93 financial distresses and 85 normal firms for sampling data. Regarding to my data gathering and former researchers' experience, we exploit 26 financial indicators and 5 non-financial indicators for our input data. Decision tree and neural network analysis were used by the study to construct financial crisis prediction model and found decision tree analysis obtains better prediction accuracy financial crisis, also found to not improve to prediction accuracy when joining in non-financial indicators in China mainland.|
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