This thesis surveys the method of extending Cox proportional hazard models (1972) and the general class of semiparametric model (2004) in the upgrades or downgrades of credit ratings by S&P. The two kinds of models can be used to modify the relationship of covariates to a recurrent event data of upgrades or downgrades. The benchmark credit-scoring model with a quintet of financial ratios which is inspired by the Z-Score model is employed. These financial ratios include measures of short-term liquidity, leverage, sales efficiency, historical profitability and productivity. The evidences of empirical results show that the financial ratios of historical profitability, leverage, and sales efficiency are significant factors on the rating transitions of upgrades. For the downgrades data setting, the financial ratios of short-term liquidity, productivity, and leverage are significant factors in the extending Cox models, whereas only the historical profitability is significant in the general class of semiparametric model. The empirical analysis of S&P credit ratings provide evidence supporting that the transitions of credit ratings are related to some determined financial ratios under these new econometrics methods.

The aim of my diploma thesis was the application of the selected method of identifying accounting fraud in setting of chosen company. In the first part of this work were used methods based on the comparison of data chosen company with the data of competitive companies in the same industry or with the data of industry. I compare the return on equity (ROE), return on assets (ROA), Daily income and balance of accounts receivable, profit margin. In the next part of this work were used special methods to identify accounting fraud. I used methods Beneish M-score model, cash realization ratio, Jones nondiscretionary accruals. As an additional analysis, I used the bankruptcy Altman Z-score model. In conclusion, I compared the risks identified possible manipulation of financial statements for all tests and analyzes. All performed tests and analyzes in aggregate have identified this risk as low. Yet some of them pointed to further more detailed research in revenues, margins and setting transfer prices.