Stress-testing and credit risk revisited: a shipping sector application
Conventional stress-testing in credit risk management may considerably underestimate economic losses associated with the most negative scenarios. In this paper, we show that in order to properly stress-test credit risk, we need to derive initially the default correlation among assets or companies. Then a risk measure needs to be applied to the stressed default rate distribution, in order to obtain default rates attached to the most negative scenarios. We find that the application of both the stressed default correlation and the risk measure deliver considerable deviations from the conventional approach. To illustrate our approach we use 192 publicly listed shipping corporations, over 2000-2016, and show that conventional stress-testing tools may underestimate losses under certain conditions. Furthermore, we show that the Vasicek (1987) model assumption of independence, between the systemic factor and the default correlation may not hold in certain cases. This assumption may actually be the reason for the likelihood of underestimation of credit risk capital requirements as applied in the context of the Basel internal ratings based (IRB) approach.
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.
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.
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.