Publications

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 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.

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.

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.

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.

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)

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.

The present study addresses three questions: 1. Whether ESG is the succeeding risk factor? 2. To study the relevance of each component of ESG in investment decision? 3. To develop a new more robust asset pricing model with ESG. This study finds that three-factor models with market, size and ESG factors perform better than the Fama–French three-factor model. Higher Sharpe ratios for ESG, environment, social and governance factors indicate that portfolios formed on these factors show better investment performance over traditional size and value-based portfolios for all cases. The main message of the study is that ESG, environment, social and governance factors play an important role in predicting returns hence they should not be ignored while considering investment decision.

This paper analyses a particular managerial problem that sports clubs face from time to time. The aim is to identify the effects that alternative stadiums and stadiums' features have in ticket prices and demand. Simultaneous equations models by three‐stage least square estimator using instrumental variables is the method employed. The findings evidence that alternative stadiums negatively impact attendances, but clubs can offset this effect playing at high‐quality alternative stadiums. Results also evidence that fans care about security levels. Some policies for football leagues are discussed as limits in the use of alternative stadiums, league fixtures and hard requirements concerning security.

We document the geographic concentration patterns of Russian manufacturing using detailed microgeographic data. About 80% of three‐digit industries are significantly agglomerated, and a similar share of three‐digit industry pairs is significantly coagglomerated. Industry pairs with stronger buyer–supplier links—as measured using Russian input–output tables—tend to be slightly more coagglomerated. This result is robust to instrumental variable estimation using either Canadian or US instruments. Using Canadian ad valorem transport costs as a proxy for transport costs in Russia, we further find that industries with higher transport costs are more dispersed, and industry pairs with higher transport costs are less coagglomerated.

The tax shield is defined as the amount of possible payments, which in turn can increase or decrease by the difference in planned changes and market fluctuations in the supply of products. The main purpose of the study is to outline the main aspects of the approach to assessing the tax burden on capital investments. A leading method of investigating this problem is the method of uncertain coefficients, which was used to obtain difference equations of high accuracy. The novelty of the research is determined by the fact that the tax shield and its tools are determined according to price fluctuations on the main products of the enterprise. For a formal expression of the influence of incentives to invest an indicator called “tax shield” was developed. It has been revealed that at the theoretical and practical levels, the impact of tax mechanisms on the development of the national economy is assessed. The practical significance of the research is determined by the fact that for the first time such tools as a stagnating economic situation are considered. This will allow predicting tax revenues and adjusting the growth of the economy in the conditions of crisis.

This study analyzes a neural networks model that forecast Sharpe ratio. The developed neural networks model is successful to predict the position of the investor who will be rewarded with extra risk premium on debt securities for the same level of portfolio risk or a greater risk premium than proportionate growth risk. The main purpose of the study is to predict highest Sharpe ratio in the future. Study grouped the data on yields of debt instruments in periods before, during and after world crisis. Results shows that neural networks is successful in forecasting nonlinear time lag series with accuracy of 82% on test cases for the prediction of Sharpe-ratio dynamics in future and investor‘s portfolio position.

The purpose of the study is to analyze the features of highly dividend strategies in the markets of developed and developing countries. For the analysis of dividend strategies, two developing countries and two developed were chosen to analyze the practical significance of dividend strategies in different markets. In addition to practical interest, this work is relevant in that there are a number of studies on individual countries, but there is no similar data for pooled data on developed or emerging markets. The paper considers the markets of such countries as Russia, India, Spain, Japan.

The study consists of two main blocks: testing the hypothesis on each market in the country separately and assessing the effectiveness of various modifications of dividend strategies on the combined data separately for developed and developing countries.

The results of this work can be used as a recommendation on investment in the considered markets, as well as for further studies of excess return on dividend strategies.

The purpose of this paper is to examine the relationship between profitability and sporting performance in European football. Profitability has been rarely studied because it has not been considered an aim of European clubs, in contrast with American clubs. However, the emergence of investors who invest on both sides of the Atlantic shows that the objectives of owners can be diverse and that profitability has to be taken into account. The study of the compatibility or incompatibility of sporting performance and profitability has implications for the existence of clubs with owners with different objectives in the same competition, or even owners with different aims in the same club. The paper finds that financial performance has a negative influence on clubs’ sporting performance, while sporting performance does not have a negative influence on profitability. Moreover, ownership concentration has a negative influence on both performance variables. These findings show that the pursuit of sport success could undermine the profitability and sustainability of clubs and that investors could focus less on sport results and focus more on maximizing the financial returns on their investments.