Publications

This paper analyzes the factors that contribute to the government obligations yield to maturity on the EU and US markets. Both, the bond characteristics and macroeconomic factors are taken into account, and the magnitude of each of the factor is provided which compose the average yield to maturity. Due to a severe financial crisis in the past years, economies are still recovering from the effects what makes investors to look for the stable investment instruments. Results of this study are a good fundamental for private investors that desire a stable return with a low-risk exposure. The factors and obtained coefficients included in the paper, can be used by investors, both private and institutional, to understand the magnitudes of the premiums that they can take on by varying the bond characteristics which account to the bond yield to maturity. Investors can decide at which premiums they are willing to focus, to obtain the desired expected returns.

The purpose of this work is to critically evaluate the evolution of risk factors and factor models. A systematic and structured literature review is carried out to observe and understand the past trends and extant patterns/themes in the present research area, evaluate contributions and summarize knowledge, thereby identifying limitations, implications and potential directions of further research. The main message from the study is that evolution of risk factors and factor models are continuous and endless development. Still today over 300 risk factors are identified by the researchers and many other yet to be discovered but out of them all only few are significantly responsible in explaining the stock markets risk return relationship. Study classifies risk factors into two groups: global and specific risk factors. Study answer the question ‘whether evolution of risk factors and factor models are endless development’. Finally, the present study gives an appropriate direction to the future studies to be taken in terms of risk factors and factor models. Due to continuous evolution and changing of nature of the risk factor it seems quite impossible to have a stable efficient factor models that can explain stock market risk return relationship globally in long run.

This study aims to examine whether the publication of analyst recommendations has reaction in the Russian stock market. This study also aims to determine the other factors that influence the reaction. The study finds that Russian stock market significantly reacts to analyst recommendations publications. Then study deeply investigates about the influence of other factors on the Russian market when an analyst's recommendations are published such as changes in recommendation levels, companies' size and general economic situation. The analysis done in the context of three types of recommendations: “buy,” “hold” and “sell.” The study finds that the market reacts not only to separate forecasts and subsequent recommendations, but also to the changes in recommendations' levels as well. Interestingly, the study finds that the impact of crises is not found to be a significant factor in the context of the Russian market.

A maiden attempt has been made to study India's first offshore LIDAR-based wind profiling at Gulf of Khambhat. Both time series and panel data are used to derive the study conclusions. Quantile and panel analysis of the wind profiling done and based on that study finds interesting results. Study finds that wind characteristics are not constant over the quantiles and even change the polarisation. Study also concludes that wind dispersion is highly positively related to the wind speed. Finally, study concludes that there is no cross-sectional (12 sectors: 40 to 200 m) random effect. Study findings have high policy implications.

This study investigates the asymmetric effects of unanticipated monetary shocks on stock prices in India over the period 1994M4–2018M11. We find that the evolution of stock prices is state-dependent across different monetary policy processes. Unanticipated monetary shocks appear to have significantly asymmetrically lagged effects on stock prices, namely: (i) the positive effect of negative unanticipated shocks in bull markets; and (ii) the negative effect of positive unanticipated shocks in bear markets. Our findings imply that monetary policy-markers should attend to these situations for the future of money-supply policies to diminish the degree of uncertainty about the money supply in adjusting stock prices.

This paper aims to study how audit committee member expertise is related to certain features of the committee and to the audit process. Based on information from 2,477 directors from 296 firms in eight European countries between 2005 and 2014, this study measures average audit committee expertise using a continuous variable, which combines education-based and experience-based expertise. Different measures of the audit process are then regressed against this and other control variables. Average committee expertise has increased in recent years. Education-based and experience-based expertise seem to be complementary. Results also show that committees with greater expertise meet more frequently, have fewer directors with full-time dedication and pay lower audit fees. There is no link to changes in the external firm audit, which may be due to mandatory auditor rotation. The paper provides a comprehensive metric of audit committee expertise that includes directors’ academic background, professional experience and qualifications. In addition, this study expands current knowledge concerning whether and how committee expertise affects the audit process.

Bachet’s game is a variant of the game of Nim. There are 𝑛 objects in one pile. Two players take turns to remove any positive number of objects not exceeding some fixed number 𝑚. The player who takes the last object loses. We consider a variant of Bachet’s game in which each move is a lottery over set {1, 2, . . . ,𝑚}. The outcome of a lottery is the number of objects that player takes from the pile. We show that under some nondegenericity assumptions on the set of available lotteries the probability that the first player wins in subgame perfect Nash equilibrium converges to 1/2 as 𝑛 tends to infinity.

In this paper, we evaluate the cross sectional relationship betweenfirm characteris-tics,financial leverage, and stock returns for the Indian stock market. The studyfinds that thereare strong size and value effects existing in the return pattern of stocks, and alsofinds a complexpattern between leverage and stock returns in the Indian context. The Gibbons, Ross, andShanken (GRS) test confirms the robustness of three factor model with market, size, and lever-age over Fama-French three factor model (1993) in most cases. The Wald test confirms that theeffects of value and leverage are the same in determining portfolio returns in most cases. Fur-ther, study estimates show that portfolios formed using value and leverage breakpoints are notmuch sensitive to the results unlike portfolios formed using size breakpoints.

Although corporate capital structure has been intriguing to scientists for a number of years, very little research has been conducted on the topic for companies in emerging markets. The purpose of this paper is to investigate the determinants of capital structure using a sample of 195 non-financial firms from emerging markets in 2012-2016.

The inclusion of a specific dataset from Chinese companies lends vital focus to this investigation and provides crucial ballast for the investigative function. The final sample contains data on 57 China companies and 90 other companies of emerging markets. Our article focusses on identifying the determinants of capital structure of Chinese companies in comparison with companies of other BRIC countries (Brazil, Russia, India), and sets out a series of hypotheses concerning capital structure with domestic and international variables. We compare and contrast our data using a series of custom evaluation models based on linear regressions.

The results confirm positive impact of tangibility on total debt ratio due to a high share of capital-intensive industries in the sample. It is revealed that growth rates and firm size have positive impacts on financial leverage in Chinese companies as compared to other BRIC countries, and these effects are stronger in capital-intensive industries. We illustrate how a strong negative impact of ROA has increased in recent years, and connect this phenomenon to a considerable decrease in lending rates following a large-scale stimulus program which encouraged Chinese companies to borrow money instead of relying on retained earnings. The presence of the Chinese state in the ownership structure of companies is revealed to be significant for the majority of Chinese companies, especially for the oil and gas and metallurgical sectors.

Our conclusions highlight the importance of government policies and special market conditions in explaining the financing behaviour of companies in emerging countries like China. While capital structure choice varies significantly across industries, nevertheless the differences between Chinese and other BRIC companies reflect the differences in the institutional structure of financing mechanisms in countries. This research and evaluation is especially timely considering the increased focus on Chinese commercial exposure on the world stage, a tendency which is bound to increase research interest in the near future across a range of disciplines. As such, our study and our broad range of conclusions will prove invaluable for students, researchers, policymakers, and decision makers in business, commerce, politics and academia at all levels.

In this study Non‐Linear forecasting models have been implemented to forecast the 7 major cryptocurrencies. To the best of the authors knowledge, this is the first study to forecast the cryptocurrencies chaotic co‐movement forecasting using non‐linear models like Neural networks. The study finds that LSTM yields better result for lags 0 and 0‐3 and for large lags 0‐7, the ANN is the best. Further study confirms that predictions using variables like volume is not suitable for forecasting in any case. The findings of the study will impact Policy makers and investors.

We analyse the determinants of football fans’ happiness in the Russian Premier League using facial emotion recognition. We propose a new way of measuring subjective well-being and provide its empirical validation using sports data. Our sample consists of about 10,000 photos from football matches uploaded on the most popular social network in Russia during the seasons 2014/15–2017/18. The dataset of photos is analysed with the Emotion Recognition software, which takes a facial expression in an image as an input and returns the confidence across a set of emotions for each face in the image. Next we use multinomial logistic regression to identify the determinants of happiness. The results show that uncertainty and expectations are important drivers of football fans’ happiness. A win decreases the probability of being unhappy, and the effect becomes stronger for late rounds of a national championship. The change in happiness because of a home team win is stronger for males.

To minimize credit risks, banks must first analyze the financial condition of a potential borrower and evaluate their creditworthiness. The technique used for this purposes should be comprehensive, accurate and reliable. However, criticism of existing approaches to assessing creditworthiness is often associated with their lack of flexibility and absence of industry-specific approach. The metallurgical industry is very important for the Russian economy. Many organizations operating in related industries consume the metallurgical production, and the products themselves have a significant share in national exports. Russian metallurgical organizations are leaders not only in the domestic, but also in the global market. The concepts of credit risk, insolvency and creditworthiness were studied. The milestones of assessing the creditworthiness of organizations were considered, the evolution of approaches to valuation was presented during the second half of the last century and to the present moment. A brief overview of existing banking practices is provided. The financial performance of Russian metallurgic enterprises were analyzed. Particular attention is paid to the review of industry leaders as examples of the most sustainable organizations. Based on the reporting data, the characteristics of financial indicators and capital structure inherent in the industry were identified. The process of creating the methodology for assessing creditworthiness, which would take into account the characteristics of metallurgical organizations, is presented. A compilation of financial ratios for analysis was selected, the probability of bankruptcy was estimated for each company in the sample. Based on panel data on 35 companies for 2014-2018, through using a logistic regression, a scoring model was built to assess the creditworthiness of metallurgical organizations. The result of the work was an express methodology that allows to assess the creditworthiness of a metallurgical organization quickly and transparently, and at the same time, with sufficient accuracy, taking into account industry specifics

Purpose – Video games are considered as a leisure activity that makes being unemployed more attractive than before. In this study, the authors use eSports prizes as a proxy for the popularity of video games to analyze its influence on total and youth unemployment. Design/methodology/approach – The authors develop a theoretical model and empirically test it using the total prize money won by representatives of a country in a given season in eSports tournaments, via a panel regression model with the country-year as a unit of observation. The data set includes information about 191 countries between 2000 and 2015. Findings – The authors’ results of regression analysis show a positive influence of the popularity of video games on the unemployment rate. In addition, the authors analyze this effect for countries with different levels of income and labor productivity. The authors found a significant inverse relationship between income level and the effect of the popularity of video games on total and youth unemployment. Originality/value – While previous studies rely mostly on self-reported data, the authors suggest a new approach to measure video game popularity. This paper contributes to existing knowledge with empirical evidence on how leisure activities affect unemployment at the country level.  

Growing importance of human resources places the role of managers at the core of company efficiency. However, there are studies that demonstrate the efficiency of teams without a manager, so-called self-managed teams, is higher comparing with managed teams. Thus, despite the focus on managerial efficiency in the economic literature, the issue of whether a team needs amanager is far from settled. In this paper, we use a quasiexperimental setting from e-Sports (competitive video gaming) to understand whether the hiring a manager is of benefit to team performance. The empirical part of the study is based on endogenous switching regression model. This method allows investigating what performance of self-managed team would be if it will have a manager and vice versa. The dataset includes the information of prize money and features of top e-Sports teams in Counter-Strike: Global Offensive (e-Sports discipline) from 2013 to 2017. The main finding of this study is that managed teams perform better than self-managed ones but this is not due to the manager.

Topical Problems of Green Architecture, Civil and Environmental Engineering 2019 (TPACEE 2019)

The article focuses on models that can assess the efficiency of mergers and acquisitions (M&A) deals by evaluating their synergistic effect. Such studies are much needed in the modern society, which is demonstrated by the current state of the market and various integration processes, which produce quite different results. We analyze M&A deals in developed and developing countries from two corresponding regions, Western Europe and Middle East and North Africa (the MENA region), in an attempt to find the most appropriate model for determining the main factors that influence the efficiency of M&A deals in the construction industry.

Football is an industry driven by emotions. Fans experience many different emotions related to their teams. This paper aims to inspect how emotions impact attendance at football matches, examining whether football fans prefer to watch highly competitive matches or matches between good teams with star-players. The paper also considers behavioral and emotional differences of match spectators when brand-teams play away or at home. Importantly, we are also looking for the effects that the expectations of these emotions have on the tickets’ price mechanism. We use data from three seasons of the Brazilian State championship with information on more than 1,100 matches. The OLS estimator with the moderation marginal effects allows for analysis of a brand-team playing with different levels of uncertainty over the outcomes measured by the relative level of the divisions of rivals. We look for the difference between the marginal contribution of the brand-team and the uncertainty of outcomes that might change under some conditions. The analysis is performed later using two subsamples and, finally, we address the problem of endogeneity in price using an instrumental variable. From our results, the main findings are: first, that the price of tickets does not much affect the demand when a brand-team is playing. In case of competitive matches between non-brand-teams, price behavior correlates to the rationality of the demand curve having a negative impact. The fact that price is not relevant for matches with the brand-team comes to corroborate the idea that fans are driven more by emotions than by economic reasoning; second, the phenomena of highly competitive matches does not work when a brand-team is playing against a small one; and third, the effect of a brand-team playing is relatively more important than the uncertainty of outcome. The last two findings mean that the satisfaction of watching star-players or big-teams is stronger than the emotion brought by a competitive match.

This paper study regional attractiveness through passive portfolio investment based on duration, immunization and convexity (in case of higher interest rate volatility) of municipal bonds by using data from Standard and Poor’s. The massive variety of financial incentives to promote regional investment attractiveness is dependent on governmental strategy. Municipal bonds are the one of the most efficient ways of direct investments in the region, however, it is still a question of a good balance between a certain rate of return and an adequate risk. The purpose of this paper is to analyze the investment opportunities in municipal revenue bonds. An analysis of the municipal bond market indicates that both municipal general and revenue bonds had stable and good level of yields to maturity in the past ten years. Their standard deviations were very low and in the past two years almost approached the level of standard deviations of treasury bonds. With the duration of 4–6 years on 5-year investment in municipal revenue bonds and their immunization, it is possible to provide good returns for investor.

The present study focuses on five cryptocurrencies co-movements physiognomies both in time and frequency domain. The present study highlighted several interesting facts related to cryptocurrencies co-movements both in time and frequency domain that have high policy and investment implications. Overall wavelet coherence diagrams clearly indicate about the very short and long contagion effect among the cryptocurrency pairs for the whole study period. The contagion effect is different at different time scales. Finally wavelet clustering diagram indicates that by investing only in XBP and BitCoin cryptocurrencies investors are not going to get any benefit from diversification. This predictable co-movements pattern among the cryptocurrencies could be the basic investment strategies to gain maximum profit by diversifying the risk in cryptocurrency investments.

Business‐like approaches are applied more and more widely in nonprofit organization contexts, and theaters are no exception. Revenue generation, customer segmentation, and personalized marketing are becoming the key managerial concerns. Our study focuses on two relevant aspects of theater attendees' behavior. We examine visitors' willingness‐to‐pay (WTP) for theater seats (to derive revenue drivers), and its difference between two segments – single and couple visitors (to uncover the social motivation effect). These aspects taken together have never been previously studied in the nonprofit marketing context. We model WTP using the actual purchase data from Perm Opera and Ballet Theatre in Russia. Unlike most marketing studies which use stated preference for WTP evaluation, we employ the revealed preference approach. The results verify that single and couple visitors may be treated as separate segments, allowing for personalized promotion and other marketing decisions.