Russian stock market: The practice of using credit derivatives

Subject. This article explores the practice of using credit derivatives in the Russian stock market. Objectives. The article aims to identify the problems and advantages of the Russian credit derivatives market, and propose certain improvements concerning this derivatives market segment. Methods. For the study, we used analysis, comparison, and statistical methods. Results. The article describes the problems and advantages of using credit derivatives in the Russian stock market and proposes certain activities to improve this segment of the market. Conclusions. The results obtained can be used by students and university staff to study over-the-counter derivatives. The proposed measures to improve the credit derivatives market can also be applied for practical purposes to improve the legislative framework and develop the market infrastructure.

The Economics of Central Clearing

Central clearing counterparties (CCPs) have a variety of economic rationales. The Great Recession of 2007–2009 led regulators to mandate CCPs for most interest-rate and credit derivatives, markets in which large amounts of risks are transferred across agents. This change led to a large increase in CCP studies, which along with classical studies are surveyed in this article. For example, multilateral netting, the insurance against counterparty risk, the effect of CCPs on asset prices and fire sales, margins setting, the default waterfall, and CCP governance are discussed here. We review both CCP theory and empirical work and conclude by discussing regulatory issues. Expected final online publication date for the Annual Review of Financial Economics, Volume 13 is March 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Mathematical Estimation Methods and Models for Industrial Companies

The collateralized debt obligations and credit default swaps applications are shown in this paper. The industry obligations secondary market risk estimation methods are considered in this work. The new methods taking into account statistically significant parameters for industrial credit derivatives portfolio are offered for single-name investment risks numerical experiments realization. The mathematical estimation of tranche were shown. The single and multiple name default obligations necessary mathematical modeling methods and formulae for the industrial materials manufacturers derivative credit tools market are shown. It is determined that the portfolio of synthetic debt tools is made of the given parameters. The task of a loss derivative tranches mathematical estimation is solved. Late defaults raise the equity tranches payment required sums with high spreads, early defaults reduce. Also the functional characteristics required for an estimation huge debts problem solving are partly considered in this paper. The problem of the default modeling for market tools and numerical simulation of the obligations influence on conditions of current bistability mode are shown here. Some credit derivatives of industrial manufacturers are demonstrated in the modeling process of default as an example. It is found that the model is an additional factor help us to estimate the default opportunity.