Determinants of the probability of default: the case of the internationally listed shipping corporations
In this study, we use a sample of 192 listed shipping companies and employ a logit model in order to investigate the determinants of the probability of default. We enhance our analysis by isolating not only the cases of company liquidations but also those cases where companies had to change their legal status due to warning liquidity signals. Our key findings are in line with prior research and moreover we depict a changing trend in the marginal effects of relevant variables, on the probability of default. We further show, through an empirical application, how the obtained results can be used in a managerial decision-making process and in a bank credit underwriting process in order to assess the creditworthiness of a shipping company.
We suggest an econometric model of probability of default based on regular financial disclosures of Russian banks. We also suggest a quantization of the continuous explanatory variables that allows to account for non-linear effects and to achieve superior accuracy compared with regression tree and Bayesian network models estimated over the same sample. The econometric estimates of probability of default are broadly consistent with the historical default frequencies of rated obligors and risk-neutral probabilities of default inferred from credit spreads in a reduced-form model.
The cornerstone of retail banking risk management is the estimation of the expected losses when granting a loan to the borrower. The key driver for loss estimation is probability of default (PD) of the borrower. Assessing PD lies in the area of classification problem. In this paper we apply FCA query-based classification techniques to Kaggle open credit scoring data. We argue that query based classification allows one to achieve higher classification accuracy as compared to applying classical banking models and still to retain interpretability of model results, whereas black-box methods grant better accuracy but diminish interpretability.
In the paper some prominent features of a modern financial system are studied using the model of leverage dynamics. Asset securitization is considered as a major factor increasing aggregate debt and hence systems uncertainty and instability. A simple macrofinancial model includes a logistic equation of leverage dynamics that reveals origins of a financial bubble, thus corresponding closely to the Minsky financial instability hypothesis. Using ROA, ROE, and the interest rate as parameters, the model provides wide spectrum of leverage and default probability trajectories for the short and long run.
Credit rating agencies evaluate corporate risks and assign ratings to companies. Each rating grade corresponds to certain boundaries of default probability. KMV is a popular model to assess the default probability of a company. In this paper, a method to predict the default probability of a company is proposed. This method is based on the main concept of the KMV model; however, financial statements are applied instead of stock prices, i.e. time-series of EBIT (earnings before interest and taxes), net debt, sales, and the last year value of WACC (weighted average cost of capital). Default probabilities for 150 companies are evaluated. Results and limitations are discussed.
In this article Russian stock market information efficiency is analyzed. The quantitative measure of the analysis is the indicator of Shannon entropy. On the basis of logit model the relation between the level of information efficiency and financial crisis probability is investigated.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.