Comparison of Empirical Methods for the Reproduction of Global Manufacturing Companies’ Credit Ratings
The quantitative assessment of the credit quality of manufacturing companies is a task of great interest to researchers and practitioners. This is underpinned by the elevated credit risk of these companies stemming from rapid technological changes. However, few studies have addressed this issue specifically for manufacturing companies. This study aimed to fill this research gap by comparing the predictive power of various methods in reproducing manufacturing companies’ public credit ratings from available financial and non-financial data. The sample included 109 manufacturing companies from developed and emerging markets over the period 2005–2016. The analysis included three methods: ordered logistic regression (OLR) and two machine learning techniques, random forest and gradient boosting. The results showed that machine learning techniques outperformed OLR in terms of predictive power. In the best specification model, random forest had an accuracy of 50%, followed by gradient boosting (47%) and OLR (25%). We also tested two types of sampling in the training and test sets: random and time-dependent. The results showed that the models’ predictive power was greater with random sampling. The inclusion of macroeconomic variables did not improve the models’ predictive power due to the rating agencies’ preferred through-the-cycle rating approach. The study’s findings have implications for the development of manufacturing firms’ internal credit ratings. They can also be useful for researchers exploring the accuracy of empirical models in predicting industrial firms’ insolvency and creditworthiness.
Purpose: The purpose of the article is to develop a strategy of provision of security of wireless future of digital economy. Methodology: The author determines, analyzes, and compares scenarios of wireless future of digital economy depending on completeness of provision of security, with the help of the methods of logical and problem analysis and imitation modeling. Results: As a result of modeling the wireless future of digital economy, the risks to security, causes of their emergence (factors that require management), and perspectives of risk management are determined. A strategy of provision of security of wireless future of digital economy is presented-it reflects the structure of risk management of this process through the prism of its subjects and performed functions, as well as the tools that include robototronics, cloud and blockchain technologies, and human monitoring of digital devices. Implementation of this strategy will allow reducing the risk component of functioning and development of digital economy, its quick growth and stimulation of social progress (increase of population's living standards)-i.e., implementation of the optimistic scenario. Recommendations: As a result, it is concluded that even in case of highly-effective risk management there preserves a rather high level of risk of provision of security of digital economy's wireless future. Thus, with digital modernization of modern socio-economic systems together with practical implementation of the offered strategy of provision of security of digital economy's wireless future, it is recommended to conduct measures for reducing the level of social tension and preventing the opposition to changes. © Springer Nature Switzerland AG 2019.
A mechanism has been developed for assessing a company’s strategic risks and selecting the risk factors on which the risk management actions of the company must be focused. The risk factors are projections of the company’s internal and external environment which create its competitive advantages but are exposed to the most dangerous threats. The mechanism is an integral part of strategic risk controlling, the application of strategic controlling to risk management, and was built as a set of interrelated procedures which perform the selection of risk factors. The design of the mechanism is based on the integration of strategic analysis of fthe company’s value chain and failure mode and effects analysis (FMEA). This design, unlike that of the alternatives, allows maximum accounting for the majority of links and correlations among strategic goals, projections and risks. The paper elaborates on the main tasks and functions of strategic risk controlling and shows the advantages of integration of value chain analysis and FMEA in a single risk assessment mechanism. It works out the flow chart of the mechanism of assessment of the company's strategic risks. It develops the procedure of calculation of FMEA’s risk scores (risk priority numbers (RPNs)) for individual end-risks; at the level of each strategic perspective and at the level of the entire strategy. It develops the procedure of selecting the optimal strategy among the strategic alternatives using the Hurwicz minimax criterion in which strategy-level PRNs are utilized as the measures of risks. Finally, the paper works out the procedure for choosing the risk factors among strategic perspectives and develops the key tool of this procedure, the risk-factor positioning matrix. This matrix allows searching for the optimal ways and tools of risk control. The mechanism allows increasing the efficiency of risk management in strategic controlling and concentrating the management’s attention on the company’s strategic factors which are exposed to the most dangerous risks.
Purpose: The purpose of the article consists in conceptual substantiation of automatization of the labor resources market in the age of the Internet of Things and development of recommendations for risk management of this process. Methodology: In this article, the process of automatization of the labor resources market in the age of the Internet of Things is studied with the help of the method of problem and logical analysis, modeling, formalization, and qualitative scenario analysis (it is used for determining the possible risks and perspectives of managing the risks). Results: As a result of studying the process of functioning and development of the online market of labor resources, its problems are determined, as well as perspectives and advantages of solving them with the help of the Internet of Things. A concept of automatization of the labor resources market with the help of the Internet of Things is developed and presented. The risks of automatization of the labor resources market with the help of the Internet of Things and perspectives of risk management are determined. Recommendations: It is substantiated that digital modernization of the labor resources market on the basis of the Internet of Things allows for authomatization and rationalization of behavior of this market's participants, ensuring quick optimal decisions with minimum resource intensity. The offered conceptual substantiation of automatization of the labor resources market in the age of the Internet of Things reflects the logic and essence of this process, and the stated perspectives of risk management allow preserving sustainability of the online market of labor resources in case of its authomatization and maximizing the effectiveness of this process. © Springer Nature Switzerland AG 2019.
We consider 11 credit ratings of Russian banks, assigned by international and Russian rating agencies during 2012—2016. Econometric models of these ratings designed on the public information reveal difference in the approaches of the rating agencies to the Russian bank ratings. We also design econometric models of the Russian bank defaults, where we consider default as the bank license withdrawal by the Bank of Russia. Using these models we analyze to what extent rating agencies take into account probability of the license withdrawal in short-run period and if Central Bank of the Russian Federation decisions are related to the bank ratings. We found that the international and domestic rating agencies have different attitudes to the various reasons of the bank license withdrawal formulated in the Bank of Russia orders. Models of the ratings of agencies S&P, Moody’s, and Russian rating «Expert RA» show better performance than other rating models in the prediction of bank licenses withdrawals. Thus these ratings are more close to the purposes of the Bank of Russia. However binary choice models constructed by the historical data of bank licenses withdrawals beat rating models in the prediction of bank licenses withdrawals.
Genome rearrangement is a hallmark of all cancers. Cancer breakpoint prediction appeared to be a difficult task, and various machine learning models did not achieve high prediction power. We investigated the power of machine learning models to predict breakpoint hotspots selected with different density thresholds and also compared prediction of hotspots versus individual breakpoints. We found that hotspots are considerably better predicted than individual breakpoints. While choosing a selection criterion, the test ROC AUC only is not enough to choose the best model, the lift of recall and lift of precision should be taken into consideration. Investigation of the lift of recall and lift of precision showed that it is impossible to select one criterion of hotspot selection for all cancer types but there are three to four distinct groups of cancer with similar properties. Overall the presented results point to the necessity to choose different hotspots selection criteria for different types of cancer.
This article explores the reasons for creating alliances between drug manufacturers and
developers in the pharmaceutical sector. Also, attention is paid to the classification of such
partnerships depending on the level of integration. Classification is necessary for further study
of relations in alliances. It is important to understand how such partnerships are economically
effective and justified.
One of the most important activities of enterprises today is responsible entrepreneurship. Corporate social responsibility (CSR) activities can help to forge a stronger bond between employees and corporations, can boost morale, and can help both employees and employers feel more connected with the world around them. Moreover, the growing importance of this concept results from the fact that it is perceived as an effective tool for increasing competitiveness, improving the image of the company, or contributing to the generation of higher profits. In today’s world, an active commitment to social responsibility is becoming more common for a company.
CSR and Socially Responsible Investing Strategies in Transitioning and Emerging Economies is an essential reference source that identifies the scale and scope of implementation of CSR and socially responsible investing strategies and standards in companies operating in different transitioning and emerging economies as well as assessing the global effects of these activities. Featuring research on topics such as economic growth, responsible investing, and business ethics, this book is ideally designed for managers, executives, directors, corporate professionals, government officials, industry leaders, academicians, students, and researchers in the fields of international economics, international business, marketing, finance management, and public relations.
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.