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Performance evaluation enables decision makers (DMs) to have a better view about the weaknesses and strengths of leading units to improve efficiencies as a crucial goal. Data envelopment analysis (DEA) is the most popular technique to measure performance efficiency of decision making units (DMUs). However, conventional DEA is unable to consider uncertainty of input and output data in the evaluations. In this study, in order to address uncertainty in data, a robust credibility DEA (RCDEA) model has been introduced. First, a fuzzy credibility approach is used to construct fuzzy data. Then, a robust optimization approach is applied to consider uncertainty in constructing fuzzy sets. Moreover, perturbation level is considered as exact and fuzzy values. To illustrate the capability of the proposed model, 28 hospitals are evaluated in northwestern region of Iran and results are analyzed. According to the results, as perturbation degree increases, DMUs get normalized lower efficiencies and vise-versa.
The paper aims to study digital learning as an innovation in higher education and a mechanism for increasing its attractiveness to young people in Russia and Central Asia. The authors apply the method of case study to study the experience of formation and development of digital learning as an innovation of higher education in Central Asia and Russia. The authors also conduct econometric modeling of the impact of digital learning on the attractiveness of higher education for young people. To obtain the most accurate and reliable results, statistics are collected for each Central Asian country for 2013–2020. As a result, the authors substantiate that digital learning, which is an innovation of higher education, is an efficient, highly effective, and affordable mechanism for increasing the attractiveness of higher education for young people in Central Asia. The evaluation shows that the development of digital learning will increase enrollment of young people in higher education in Central Asia by 18.51% (from 38.16% in 2020 to 45.23%). This fact points to the significant potential of digital learning. Therefore, it is recommended to increase the scale of digital learning in Central Asia to increase the accessibility and attractiveness of higher education among young people.
We investigate the impact of geopolitical risk (GPR) generated by the Russian-Ukrainian conflict on European and Russian bonds, equity, and global commodity markets. We employ the GPR index and apply the quantile-on-quantile regression approach to the GRP index and financial asset returns. Our findings indicate that (i) most assets are in a mix of negative and positive relationship with GPR; (ii) GPR leads to changes in asset returns during normal market conditions; and (iii) the magnitude and direction of GPR's effect on asset returns depend on the type of market and market conditions.
This paper aims to study the perspectives of sustainable development amid the COVID-19 pandemic and crisis in 2021, backed by financial risk management and corporate social responsibility. To achieve this goal, the authors use the methods of regression analysis, horizontal and trend analysis, and variation analysis. As a result, it is proven—for the first time—that in isolation, investments and corporate social responsibility do not contribute positively to sustainable development. In addition, the authors determine the absence of the outflow of investments from the world economy during crises. Based on this, a new approach to crisis management of sustainable development is developed—it is based on stimulating corporate social responsibility, for which the complex recommendations in the sphere of state management are offered. The theoretical significance of the conclusions made consists in specifying the essence of financial risk management of sustainable development, which has to be conducted with a strict connection to and based on corporate social responsibility. The practical significance of the developed new approach and offered recommendations on its practical implementation consists of strengthening the scientific and methodological provision of economic crisis management of COVID-19 and the maximization of its contribution to sustainable development to support the Decade of Action.
We perform a comprehensive study of different illiquidity effects in the relatively illiquid Russian stock market. Over the period 2010–2020, we apply cross-sectional and time-series regressions using two low-frequency illiquidity proxies: the Amihud ratio and the invariance-implied ratio. The evidence suggests that implicit trading costs influence only the returns of small-capitalization stocks or low size double-sorted portfolios. The Amihud ratio overestimates the illiquidity premium for small-cap stocks as predicted by the invariance theory. However, we find that the effect is economically and statistically significant only in the time-series.
Using high-frequency transaction-level data for liquid Russian stocks, we empirically reveal a joint nonlinear relationship between the average trade size, log-return variance per transaction, trading volume, and the asset price level described by the Intraday Trading Invariance hypothesis. The relationship is also confirmed during stock market crashes. We show that the invariance principle explains a significant fraction of the endogenous variation between market activity variables at the intraday and daily levels. Moreover, our tests strongly reject the mixture of distributions hypotheses that assume linear relationships between log-return variance and transaction intensity variables such as trading volume or the number of transactions. We demonstrate that the increase in the ruble risk transferred by one bet per unit of business time was accompanied by the rise in the average spread cost. Different aggregation schemes are used to mitigate the impact of errors-in-variables effects. Following the predictions of the Information Flow Invariance hypothesis, we also study the relationship between trading activity and the information process approximated by either the flows of news articles or Google relative search volumes of Russian stocks over the 2018–2021 period. The evidence suggests that a sharp increase in the number of retail investors who entered the Moscow Exchange in 2020 entailed a higher synchronization between trading activity and search queries in Google since February 2020, in contrast to the arrival rates of news articles. The changes are driven by the increasing influence of the trading behavior of individual investors using Google Search rather than professional news services as the main source of information.
We investigate the impact of geopolitical risks caused by the Russian-Ukrainian conflict on Russia, European financial markets, and the global commodity markets. We measure the dynamic connectedness among them using time- and frequency-based time-varying parameter vector autoregression (TVP-VAR) approaches. The empirical findings indicate that (i) their relationship has changed due to the conflict; (ii) European equities and Russian bonds are the net transmitters of shocks; and (iii) the conflict affects returns and volatility connectedness among them in terms of short- and long-term frequencies, respectively.
Modern social networks are becoming a significant factor in stock market pricing because the information they generate expands the aggregate news background that determines stock prices according to currently prevailing efficient market theory. The news generated in the electronic media affect all the spheres forming supply and demand not only for manufactured goods but also through them for the prices of their manufacturers’ stocks. Normally, the relationship between the production of goods and the share price of its manufacturer is traced through economic indicators of profit, size of dividends, etc. Social information does not have a direct economic content. However, according to efficient market theory this kind of information should influence the share price. The article proves the influence of a trendsetter photo wearing certain brand clothes on the stock quotes of the company that owns this brand. The event analysis method reveals a short-term increase in company's share market price after the publication of a trend-setting blogger photos on Instagram, especially when it comes to a luxury brand. At the same time, the trend-setter profession and gender do not affect the abnormal rate of stock return resulted from the publication of his photograph. It proves a relative isolation of the “trend setter” itself in comparison with the personal characteristics of a blogger and turns this title into a specific independent factor in stock pricing.
Gaming is a human activity opposite to his labor activity. The market aspect of gaming activity develops in two relatively independent directions: in the form of gambling and in the form of a game for money. Gambling is directly related to the financial market and is a direct redistribution of funds, for example, between participants in the stock, currency, derivatives markets. Game for money is a game as an object of purchase and sale. In this case, the gaming industry appears as a dual unity of the market for games as goods and the market for gaming services. The economic specificity of the game-for-money market is that its main users are nonworking children and adolescents, and payment for the game is made from the financial income of their working parents. Thanks to this, the market dramatically expands the circle of its customers, even at the expense of insolvent consumers.
The monograph examines the trends in the development of renewable energy, the competition of wind and solar energy with other generations. The theoretical substantiation of a fundamentally new original author's model for calculating resource savings arising from the replacement of natural gas, coal and oil with wind and solar energy is presented. The model takes into account the economic cost of living, CO2 emissions and the preservation of one life, the social discount rate, the social carbon tax. It analyzes which factors and to what extent were unaccounted for in the normalized cost of generations. The relationship between the reduction of CO2 emissions and the replacement of fossil energy sources with wind and solar energy in the world and in the energy balances of ten countries has been determined. A critical analysis of the production of blue hydrogen compared to green hydrogen is presented.The book is intended for teachers and scientists for research in the field of renewable energy, environmental protection, stock market; economists, power engineers, environmentalists, sociologists, bankers, insurers.
An increase in the number of shareholders which is typical for public joint-stock companies leads to the fact that the direct management of the assets of a jointstock company is concentrated in the company’s top management (top managers) who, not being the owner of its capital, manages it as its own capital. Such inconsistency of the management system in a joint-stock company gives rise to the need to develop external control over it on the part of all other participants in the modern market represented by participants in the stock market, the state, and the public (citizens). The main forms of control on the part of the stock market are the groups of relations regarding the purchase and sale of shares leading both to a change in the composition of shareholders and to a change in the company’s
management. The most significant part of the relations of the stock market leading to the change of the top management of the company at the will of the market participants relates to the market of corporate control. State control in the sphere of the functioning of joint-stock companies covers not only the regulation and control of their activities but also includes the direct presence of the state as a shareholder of a number of companies important for the country’s economy. However, the controlling participation of the state is strongly opposed by those who defend the relationship of private ownership of capital. Civil control over the activities of joint-stock companies is based on the broad development of the media and on the growth of public consciousness in the direction of protecting the environment from the negative impact of capital relations on it. The deep reason for the development of various forms of public control over the activities of joint-stock companies is the transformation of modern society into a society of shareholders, i.e. into a society in which the majority of citizens are not just direct or indirect shareholders who receive their income from share capital but also persons interested in making this capital socially useful.
Abstract. In our paper, for the first time, we examine the influence of the sentiment of private investors in social networks on the trade characteristics of stocks in the Russian market. Monthly return rates and trading volumes are analyzed under the control of financial indicators and indicators of the quality of corporate governance of stock issuers, as well as the changing external environment in the period from 2013 to 2020. The sample for various sentiment metrics is based on unique data: messages in the Telegram and mfd.ru platforms. The tonality of messages is diagnosed according to the authors’ method using artificial intelligence (neural network). The main conclusion is: the sentiment can be seen as an explanatory factor in pricing and trading activity. The influence of sentiment is non-linear. The author’s HYPE indicator of sentiment is proposed and compared in terms of explanatory ability of the trade characteristics with a wide range of proxy variables. The explanatory ability to identify differences is realized through regression constructions on panel data. It is shown that trade characteristics are more sensitive to the growth of negative messages, which is consistent with the postulates of behavioral finance. An increase in messages’ number of both positive and negative sentiment contributes to the growth of trading activity. An important practical conclusion is: following the crowd when the company is most intensely discussed will not result in high returns to an investor.
Social investment means investment not only into market economy but in society development. Green color is often used to mark such investment. In social investing both the character of investment project and the method of attaining result are important, the latter does not imply only investment and project profitability. As a result social investment is characterized by lower profit-making capacity. It builds the economic foundation for relatively cheap transition of economy to a new material base in the field of advanced power engineering and in respect to the environment. Social investing is also characterized by morality, therefore it turns into a specific opposition to traditional market investing, which, in spite of low profit-making capacity of social investing, does not motivate saving owners to increase private consumption. The authors show that social investing can be used as a tool of political struggle in today’s world. Under the pretext of obligatory investing into attaining universal human goals industrialized countries try to retain their leading position in the world.
We investigate how Covid-19 affects the emerging market (EM) bonds by analysing, on a standalone basis, investment grade (IG) and high yield (HY) debt per type of issuer. We document evidence that the option-adjusted spreads (OAS) of the IG and HY financials have recovered to the pre-Covid levels by the end of year 2020, while for the HY sovereigns and corporates the OAS remain twice as wide as before the pandemic. The weight of the liquidity component in the OAS for the IG sovereigns has climbed to astonishing 45%. Our results are potentially useful for investors, traders, risk managers and regulators.
Factor momentum and high volume separately work well in developed markets, but they have shown poor results in extremely volatile and illiquid emerging markets. Guided by the characteristics of illiquid markets, we combined momentum and high volume into a composite factor by a unique technique. The stability of momentum winners was improved by an increase in trading volume, which may reflect an inflow of foreign money. The problem of volatility and momentum crashes disappeared with the inclusion of a volatility switch for each stock in the portfolio. The daily calculation of volatility for a possible closing of the position for each stock is due to the spike volatility and a small number of liquid securities. This combination of factors allows us to capture significant inefficiency of a diversified market using Russia as an example and shed light on the puzzle of factor investing.
Data envelopment analysis (DEA) is one of the widely used methods to measure the efﬁciency scores of decision making units (DMUs). Conventional DEA is unable to consider both uncertainty in data and decision makers’ (DMs) judgments in the evaluations. This study, to address the shortcomings of the conventional DEA, proposes a new best worst method (BWM)-robust credibility DEA (BWM-RCDEA) model to estimate the efﬁciency scores of DMUs considering DMs’ preferences and uncertain data, simultaneously. First, to handle uncertainty in input and output variables, fuzzy credibility model has been applied. Additionally, uncertainty in constructing fuzzy sets is modeled using robust optimization with fuzzy perturbation degree. In this paper, two new types of RCDEA models are proposed: RCDEA model with exact perturbation in fuzzy inputs and outputs and RCDEA model with fuzzy
perturbation in fuzzy inputs and outputs. In addition, to deal with ﬂexibility of weights and incorporating DMs’ judgement into the RCDEA model, a bi-objective BWM-RCDEA model is introduced. Finally, the proposed bi-objective model is solved using min–max approach. To illustrate the usefulness and capability of the proposed model, efﬁciency scores of 39 distribution companies in Iran is investigated and results are analyzed and discussed. Finally,
based on the results, recommendations have been made for policy makers.
We apply wavelet analyses to study how the Covid-19 fueled panic influenced the volatility of ESG (environmental, social and governance) leaders’ indices encompassing the World, the USA, Europe, China, and the Emerging Markets. We document intervals of the low, medium, and high coherence between the Coronavirus Panic Index and the price moves of the ESG Leaders indices. The low coherence intervals signify the diversification potential of ESG investments during a systemic pandemic such as Covid-19. We document differences in the pattern exhibited by various geographical indices highlighting their potential role for designing cross-geography hedge strategies, both now and in the future.
National Research University – Higher School of Economics (Moscow) and author has been researching the leasing market of Russia for 20 years. The work presents the results of 2018, based on the author's survey of the leasing market, on the cost of new contracts and portfolios of leaseholders, the place of leasing in macroeconomic indicators (GDP), investments in fixed assets, the structure of the Russian leasing market in the most important sectors, such as railways, motor vehicles, air transport, energy, engineering, etc., the structure of leasing by the Russian regions. The article presents the structure of financing leasing on main sources, including loans, own funds, advances, issuance of bonds, etc.; Analysis of problem debt; variative calculations of leverage in leasing based on the author's methodology; Tax design of Russian leasing; use of leasing for renewable energy.
We apply wavelet analyses to study how the Covid pandemic influenced the volatility of commodity prices, covering various classes of commodities. We document the intervals of low, medium, and high coherence between the coronavirus panic index and the moves of the commodity prices. The low coherence intervals indicate the diversification potential of commodity investments during a systemic pandemic such as Covid-19. We document differences in the observed patterns per commodity category and evidence their potential role for designing cross-assets hedge strategies based on investments in commodities.