Corporate Governance, Ownership and Financial Distress of Publicly Listed Companies in China

This paper examines the effects of internal control mechanisms on the financial distress of publicly listed companies in China. Using t-test and Logistic regression analysis, we investigated the following aspects: ownership by top managers and the CEO, the number of directors, the percentage of inside directors, CEO duality, and ownership concentration. The empirical tests indicate a lower probability of financial distress when ownership by top managers and that by the CEO are higher. The evidence also shows that a combination of two parts, the CEO and the chairman of the board, may influence the internal control system of a publicly listed companies.

A New Approach to Predict Financial Failure： Classification and Regression Trees （CART）

The increase of competition, economic recession and financial crises has increased business failure and depending on this the researchers have attempted to develop new approaches which can yield more correct and more reliable results. The classification and regression tree （CART） is one of the new modeling techniques which is developed for this purpose. In this study, the classification and regression trees method is explained and tested the power of the financial failure prediction. CART is applied for the data of industry companies which is trade in Istanbul Stock Exchange （ISE） between 1997-2007. As a result of this study, it has been observed that, CART has a high predicting power of financial failure one, two and three years prior to failure, and profitability ratios being the most important ratios in the prediction of failure.

Impact of sustainability on financial distress in the air transport industry:the moderating effect of Asia–Pacific

The tremendous impact of the coronavirus pandemic on the global aviation industry has led to many cases of airline financial distress and bankruptcy.The Asia–Pacific region(APAC)contains more than half of the world’s population,and its airlines had the highest profit margin of any region.In this study,we investigate whether corporate sustainability practice can reduce the financial distress risk of air carriers,and,if so,what would the effect be in APAC?We first examine the relationship between environmental,social,and governance disclosure and the likelihood of financial distress of airlines as measured by the Altman Z″-score.Second,we analyze the moderating role of being an APAC airline in this relationship.The findings support the claim that implementing environmental actions may increase financial distress risk,and by improving social and governance activities,airlines can mitigate the risk of financial distress.The negative influence of the environmental pillar and the positive influence of the social pillar can be smaller for APAC airlines.Our study provides empirical evidence of the influence of environmental,social,and governance(ESG)on the likelihood of financial distress in the airline industry.Moreover,we analyze the moderating role of being an APAC airline in the relationship between sustainability and financial distress.This study has significant implications for executives,managers,and policymakers in the aviation industry on ESG strategy decisions and the general issue of sustainability.

Forecasting Financial Distress of Chinese High-tech Manufacturing Companies Based on a Hybrid Model of GA-SVM

Owing to the radical changing of Chinese economy, it is essential to build an effective financial distress prediction model. In this paper, we present a genetic algorithm （GA） approach for optimizing parameters of support vector machine （SVM）. We validate the proposed model on datasets of Chinese high-tech manufacturing industry. Experimental results reveal that the proposed GAo SVM model can compare to and even outperform other exiting classifiers. Compared to grid-search algorithm, the proposed GA-based takes less time to optimize SVM parameter without degrading the prediction accuracy of SVM.

An Empirical Analysis on the Prediction of Chinese Financially Distressed Listed Companies

This paper presents an in-depth analysis of financially distressed listed companies in China between 1998 and 2002. We compare the predictive power of multiple discriminant analysis （MDA）, logistic regression, and neural network models. We design and implement 126 different forecasting models using different predictive methods, different sample proportions, and different initial independent variables. The aim is to determine which model（s） and variables are best applicable for the short-term prediction of financial distress in China. We find that logistic regression models are superior to multiple discriminant analysis models in terms of prediction accuracy rate, restriction of sample distribution or prediction cost, but the neural network models show promise in their low Type I and Type II errors. The paper also inherently tests the applicability of variables traditionally used for bankruptcy prediction to the purpose of financial distress prediction in China.

Audit Reports of Financially Distressed Companies： Emphasis of Matter （EOM） Versus Disclaimers

This paper examines audit reports issued to 39 Malaysian listed companies in financial distress categorized as Practice Note 17 （PNI7） companies by Bursa Malaysia. The study finds that for companies which experienced financial distress, the audit reports are not similar, despite all companies are similarly troubled financially. Companies receive either a disclaimer or an emphasis of matter （EOM） report. The study finds that which of the two reports is given is associated with three variables： current-year operating loss, shareholders＇ deficit, and default status, implying that audit reports do convey information that financial distress is not of the same level and severity among PN 17 companies.

The Impact of Financial Distress Status and Corporate Governance Structures on the Level of Voluntary Disclosure Within Annual Reports of Firms （Case Study of Non-financial Firms in Indonesia Over the Period of 2009-2011）

The purpose of this research is to examine the impact of financial distress status and corporate governance structures on the level of voluntary disclosure. We apply six independent variables, including the firm＇s financial distress status and five components of corporate governance structures, such as board independence, audit committee independence, institutional ownership, board meeting frequency, and audit committee meeting frequency. This research is carried out by examining the annual reports of 114 non-financial firms listed at the Indonesian Stock Exchange over the period of 2009-2011. To test hypotheses, we undergo two different analyses, including independent samples t-test and Multiple Linear Regression. We find that： （1） The audit committee independence and the audit committee meeting frequency have significant positive impacts on the level of voluntary disclosure; （2） The financial distress status is negatively related to the level of disclosure at various levels of significance; and （3） All the independent variables are simultaneously related to voluntary disclosure.

Estimating the shareholder's terminal payoff based on insurer's solvency ratio in mixed fractional Brownian market

This paper studies the insurer’s solvency ratio model in a class of mixed fractional Brownian motion(MFBM) market, where the prices of assets follow a Wick-It? stochastic differential equation driven by the MFBM, by the method of the stochastic calculus of the MFBM and the pricing formula of European call option for the MFBM, the explicit formula for the expected present value of shareholders’ terminal payoff is given. The model extends the existing results.

Estimating the Shareholder's Terminal Payoff in Insurer's Solvency Ratio Model under Fractional Market

The insurer's solvency ratio model in a class of fractional Black-Scholes markets is studied. In this market,the price of assets follows a Wick-It stochastic differential equation,which is driven by the fractional Brownian motion. The market coefficients of market model are deterministic functions. By the stochastic calculus of the fractional Brownian motion and the pricing formula of European call option for the fractional Brownian motion,the explicit formula for the expected present value of shareholder's terminal payoff is given. The model extends the existing results.

The Application of the Emerging Market Score Model in China During the Global Crisis Period： A Countertrend

The global economic crisis that blew up at the end of 2006 in the United States has had extremely negative impacts on the social, political, and economic fields. The countries operating in the most affected macro areas---the United States and Europe---have put through the wringer the domestic trade relationships as well as the international ones, by injecting a chain reaction into the global economic scenario. However, there are countries that seem to be free from the economic and financial contagion overflowing over the past years, as they are moved by an ＂invincible projection toward the growth＂. The present study aims to analyze how much the main emerging market of China has been effectively involved in this vicious circle. More specifically, the study intends to propose an empirical analysis on the real connection between the macroecnnomic data and the strong structure of the Chinese publicly listed companies. This paper investigates the prediction of failure among 3,220 Chinese publicly traded companies （listed companies） during the global crisis period. By analysing the financial accounting data over the past seven years （2008 to 2014）, the emerging market score （EMS） has been adopted in order to investigate the impact of the crisis on financial distress in the main emerging market of China. The results confirm the following hypotheses： On one hand, the great majority of companies have not been suffering the downturn, since 71.93% of the entire samples present no risk of financial distress during the global crisis; on the other hand, only 6.18% have a reasonable risk of financial distress.