Prediction of corporate financial distress based on digital signal processing and multiple regression analysis
نویسندگان
چکیده
Abstract In order to reduce the default rate of corporate bond market, author proposes use digital signal processing and multiple regression analysis study prediction system financial distressed companies. First, design research method, Logistic model is most commonly used multivariate statistical method when modeling binary dependent variables, it can solve problem nonlinear classification, has no specific requirements for distribution accuracy judgment high. The selects 32 ratios from perspectives solvency, operating ability, profitability, development per share index, risk level. Taking special treatment (ST) due abnormal status as a sign distress in listed companies, selecting samples, matching principle adopted select non-ST companies samples. Two methods logistic support vector machine are empirical testing, both in-sample testing out-of-sample performed. results show that using propensity indicator (TTD) reflected text content, indeed improve model, consistent with test, this mainly reduction first type error, is, probability misjudging financially company normal company. Changes proportions have little effect on relative importance ratio variables machines, entered top ten important ratios, ranked fourth among all indicators was 1:2, increased significantly. From be seen that, build played an role. case adding tendency by information also model.
منابع مشابه
Predicting corporate financial distress based on integration of support vector machine and logistic regression
The support vector machine (SVM) has been applied to the problem of bankruptcy prediction, and proved to be superior to competing methods such as the neural network, the linear multiple discriminant approaches and logistic regression. However, the conventional SVM employs the structural risk minimization principle, thus empirical risk of misclassification may be high, especially when a point to...
متن کاملPredicting corporate financial distress based on integration of decision tree classification and logistic regression
Lately, stock and derivative securities markets continuously and rapidly evolve in the world. As quick market developments, enterprise operating status will be disclosed periodically on financial statement. Unfortunately, if executives of firms intentionally dress financial statements up, it will not be observed any financial distress possibility in the short or long run. Recently, there were o...
متن کاملA cross model study of corporate financial distress prediction in Taiwan: Multiple discriminant analysis, logit, probit and neural networks models
In 2008, financial tsunami started to impair the economic development of many countries, including Taiwan. The prediction of financial crisis turns to be much more important and doubtlessly holds public attention when the world economy goes to depression. This study examined the predictive ability of the four most commonly used financial distress prediction models and thus constructed reliable ...
متن کاملthe comparative impact of prompts and recasts in processing instruction versus meaningful output-based instruction on efl learners’ writing accuracy
the purpose of the present study was to see which one of the two instruction-processing instruction (pi) and meaningful output based instruction (mobi) accompanied with prompt and recast- is more effective on efl learners’ writing accuracy. in order to homogenize the participants in term of language proficiency a preliminary english test (pet) was administrated between 74 intermediate students ...
ذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied mathematics and nonlinear sciences
سال: 2022
ISSN: ['2444-8656']
DOI: https://doi.org/10.2478/amns.2022.2.0140