11,403 research outputs found
Failure prediction of Chinese A-share listed companies : comparisons using logistic regression model and neural network analysis : a thesis presented in partial fulfilment of the requirements for the degree of Master of Business Studies in Finance at Massey University, Palmerston North, New Zealand
This study compares the relative prediction accuracy of corporate failure between two prediction methods –logistic regression model and neural network analysis– based on a sample of 3598 observations and companies data obtained from the Chinese A- Share market during the period 1991 to 2002. Seven criteria have been set up to define failure according to attributes of Chinese listed companies. Using forty financial ratios and seven misclassification cost ratios of Type I and Type II error, two models achieve ranges of minimal misclassification cost at optimal cut-off points for two years prior to business failure; The logistic regression model is slightly superior to neural network analysis. Compared with random prediction, both models are efficient. In addition, the study points out that Total Asset Turnover (TATR), Cash Ratio (CASR), Earning per Share (EPS), Total Debt to Total Asset (TDTA), Return on Assets (ROA) and the natual log of Total Market Value (MVLN) could be significant financial indictors of corporate failure. Results of the study have important implications in credit evaluation, internal risk control and capital market investment guidelines
Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates
We study semiparametric varying-coefficient partially linear models when some
linear covariates are not observed, but ancillary variables are available.
Semiparametric profile least-square based estimation procedures are developed
for parametric and nonparametric components after we calibrate the error-prone
covariates. Asymptotic properties of the proposed estimators are established.
We also propose the profile least-square based ratio test and Wald test to
identify significant parametric and nonparametric components. To improve
accuracy of the proposed tests for small or moderate sample sizes, a wild
bootstrap version is also proposed to calculate the critical values. Intensive
simulation experiments are conducted to illustrate the proposed approaches.Comment: Published in at http://dx.doi.org/10.1214/07-AOS561 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Spectra of some invertible weighted composition operators on Hardy and weighted Bergman spaces in the unit ball
In this paper, we investigate the spectra of invertible weighted composition
operators with automorphism symbols, on Hardy space and
weighted Bergman spaces , where is the
unit ball of the -dimensional complex space. By taking ,
the unit disc, we also complete the discussion about
the spectrum of a weighted composition operator when it is invertible on
or .Comment: 23 Page
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