Analysis of idiosyncratic risks of listed companies in the V4 countries in 2010–2020

The risk of distortion of financial statements has been growing. Following the 2008 crisis, recipients of financial information are increasingly focusing on the likelihood of financial statements being distorted through fraudulent presentation of financial information. Therefore, scientific research pays more attention to models capable of detecting financial statement manipulation.
The paper aims to present the principles of functioning and the possibility of using the Beneish M-score model in Polish realities. It analyzes the history of more than 30 companies listed on the Warsaw Stock Exchange to select those whose history indicates that they can be classified as manipulators, and to select the same number of companies from the control group that are considered as non-manipulators.
The research method involves the analysis of empirical data on companies listed on the Warsaw Stock Exchange.
The analysis showed the 8-factor Beneish model identified manipulators with 100% accuracy and succeeded in identifying non-manipulators. The effectiveness of the 5-factor model was much lower.
To serve the purpose of the study, the effectiveness of the Beneish model was tested on a small sample of Polish listed companies as an introduction to a planned larger scale research. The results obtained are consistent with the results of numerous studies by authors from various countries and confirm the effectiveness of the Beneish model in detecting financial statement manipulation.

Acknowledgment
The publication is sponsored by funds from the Cracow University of Economics for the maintenance and development of research potential.

Highly concentrated banking system risks and the cumulative effect due to their accumulation act as a driver for improving the macro-prudential policy implemented by central banks. For this reason, an effectively and comprehensively assessed systemic risk in the banking system is declared an express condition for the early detection of its production sources and blocking of potential spreading channels, reducing the possible implementation. In light of this, the article develops an approach to the aggregated systemic risk assessment and interpretation of its results. The proposed approach is based on the considered influence exerted by financial risks of systemically important banks on the destabilized banking system and interconnections between banks in the context of the possible crisis impulse spreading. The following steps should be accomplished to form an aggregated systemic risk indicator in the banking system. Firstly, the differentiation of systemically important banks by the degree of their systemic importance; secondly, an integral assessment of the bank operation riskiness within certain bank groups; thirdly, the cumulative composition of the corresponding integral indicators, taking into account their weighting coefficients based on two criteria, namely values of the systemic importance indicator differentiating the bank groups, and the correlation of their risks. Interpreting the quantitative measurement results with regard to the systemic risk in the banking system is followed by the recommendations below: the systemic risk grading into high, medium and low levels and the respective definition of the threshold aggregated systemic risk indicator value which informs about the possible systemic crisis when approached; justification of the selected supervision regime types (strengthened, moderate or weakened) for systemically important banks, depending on the riskiness level specific for their operation and the systemic importance degree. The developed approach to measuring the systemic risk by means of constructing an aggregated indicator and interpreting the obtained results was being tested considering the financial risk indicators of the systemically important banks in Ukraine during 2009–2018.

The study aims to investigate the impact of determinants of financial distress on financial sustainability of Ethiopian commercial banks. The balanced panel data of 12 commercial banks of Ethiopia have been taken for the study from 2011 to 2017. The research deploys Ordinary Least Square (OLS) Regression Model. The indicators of financial distress are bank’s specific internals and macro-economic factors. The proxies of financial sustainability are Return on Assets, Return on Equity, Financial Stability Index and Bank Soundness. The findings reveal that the Absolute Liquidity Risk and Net Income Growth are found to be positive and significant and Solvency Risk negative and significant in relation to Return on Assets. Asset Quality is found to be positive and significant and Solvency Risk negative and significant with respect to Return on Equity. The Asset Quality and Net Income Risk are positive and significant and Solvency Risk is negative and significant with relation to the Financial Stability Index. Absolute Liquidity Risk and Liquidity Risk are positive and significant and Credit Risk negative and significant with Bank Soundness. Free Cash Flow and Net Income Growth are essential for enhancing Return on Assets and Bank Soundness, and managing equity within the prudential norms could bring forth short-term financial sustainability of commercial banks. By lowering provisioning of loan loss, Growth in Net Interest Income and managing Solvency Risk could ensure financial stability to the banks, which in turn leads to financial sustainability. The study reveals that financial sustainability of banks is insulated from the exposures of systematic risks originating from macroeconomic factors.