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The purpose of this paper is to propose and validate the combined model for bankruptcy prediction for the Malaysian firms. This combined model is adopted from previous studies by combining Ohlson logit model, Springate-Canadian model and macroeconomic factors. The proposed combined model is developed by using the financial and macroeconomic constructs. The result indicates that logistic regression...
This paper does the empirical research on the relevance of ownership structure and financial distress in listed companies based on the data of ST corporations because of abnormal financial positions in year 2005–2009 and the paired corporations. The ownership structure is described by the nature of controlling shareholder, ownership centralization, ownership balancing and managements' holding percentage...
Most scholars applied dichotomy to the company financial distress research, which classifies listed companies into two categories. We apply trisection method, which classifies listed companies into three categories: financial distress companies, financial unstable companies and financial healthy companies, and apply principal component analysis method and ternary Logistic model to construct a financial...
Western finance theory indicates that hedging increases firm value by reducing expected taxes, expected costs of financial distress, or other agency costs. This paper examines the use of financial derivatives for the purpose of risk management in a sample of 1151 China non-financial firms and its potential impacts on firm value and accounting performance. We find a positive relation between firm accounting...
Based on a lot of related literatures, the authors suggest a Financial Distress Prediction System incorporated the Expected Default Frequency (EDF) into Logit regression model. The empirical findings suggest that the EDF calculated by KMV model is significantly associated with the probability of default in both 3rd and 4th quarters prior to the financial crisis of sample firms. Thus, an incorporation...
To eliminate limitations of traditional early-warning of financial distress methods, an artificial immune algorithm based early-warning of financial distress is presented. To begin with, both antigens and memory antibodies with class information added to artificial immune network are trained to learn the feature of training samples. In this way, memory antibody cells pool can represent these samples...
This paper studies debt holders' belief updating and equity owners' financing decisions under asymmetric information during financial distress. This is done within a continuous-time framework, where the relevant state variable is assumed to follow an arithmetic Brownian motion (ABM). ABM can take negative values and has very realistic feature compared with geometric Brownian motion (GBM). Using Chapter...
This work analyzes the use of linear discriminant models, multi-layer perceptron neural networks and wavelet networks for corporate financial distress prediction. Although simple and easy to interpret, linear models require statistical assumptions that may be unrealistic. Neural networks are able to discriminate patterns that are not linearly separable, but the large number of parameters involved...
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