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This paper investigates the forecasting performance for credit default swap (CDS) spreads by Support Vector
Machines (SVM), Group Method of Data Handling (GMDH), Long Short-Term Memory (LSTM) and Markov
switching autoregression (MSA) for daily CDS spreads of the 513 leading US companies, in the period
2009–2020. The goal of this study is to test the forecasting performance of these methods before and during the
Covid-19 pandemic and to check whether there are changes in the market efficiency. MSA outperforms all other
methods most frequently. GMDH breaks the efficient market hypothesis more frequently (75%) than other
methods. The change of the relative predictability during Covid-19 is small with some increase of the advantage
of the investigated methods over a benchmark. We find that the market has been less efficient during Covid-19,
however, there are no huge differences in prediction performances before and during the Covid-19 period.
Previous research evidence some negative effects after league relegations. However, these works focused only on domestic league figures, overlooking that football clubs play in simultaneous tournaments. Therefore, the effects of relegation in a domestic league on those simultaneous championships remain unclear. Our dataset comprises twenty men’s Brazilian State Championships from 2013 to 2017. Panel Data Ordinary Least Squares models are employed as econometric techniques. The results suggest that the promotions to the second tier of the Brazilian League increase both attendance and revenues of clubs while relegations impact them negatively. Nonetheless, the promotion to the top tier produces no significant increase, which may indicate a potential adverse demand effect. Further research may inspect whether it happens in European football.
Objective: The objective of the article is to quantitatively systematise the existing literature on country-level venture capital (VC) activity and find the sources of discrepancy in previous studies.
Research Design & Methods: This article collects studies that focus on venture investments across countries. I retrieved 840 estimates reported in 30 studies and analysed them using meta-analysis methods. The average effect sizes were estimated and corrected for publication bias. Then, I controlled for 24 aspects of study design and data in order to find the cause of differences in the primary results.
Findings: The findings suggest that the average effect of the studied determinants of VC activity is positive and significant. Technological opportunities, macroeconomic conditions and financial market development show the highest effect which confirms the previous research. The choice of data source influences the results in a systematic way, while model specification does not affect the reported coefficients. The results showed that drivers of VC in developed and developing countries do not differ significantly, the same finding is obtained for various stages of VC.
Implications & Recommendations: The analysis of existing literature delineates the research agenda for further enhancing the institutional, technological, and macroeconomic descendants of VC. It revealed that informal institutions have been studied scarcely and deserve more attention in future research. The findings show that VC is not heterogeneous across the stages of investment which is important for venture fund management. By scrutinizing different aspects of model design and data samples I provide methodological recommendations for further research.
Contribution & Value Added: To my knowledge, this is the first meta-analysis of VC determinants. The research method allowed to quantitatively summarise previous studies and detect the between-study differences. This article collects all the coefficients of VC drivers that have been reported up to date while previous literature reviews focused on some limited sets of variables. The article contributes to existing theory by answering the questions regarding VC heterogeneity.
This article contributes to the development of contestable market theory by investigating how competitiveness in the eSports industry influences the size of this industry, as measured by the volume of monetary prizes. We use data on each gamer's prize earnings for each tournament from 1999 to 2015 to estimate panel vector autoregression (VAR) model with fixed effects. The main finding is that competition does not increase industry size. This result confirms the hypothesis from the contestable market theory that perfect competition does not always facilitate better development, especially in industries where natural barriers result in a small number of leading firms or teams.
Previous research on professional football offer conflicting results regarding the impact of wage dispersion on team performance. However, the existing intra-league heterogeneity among clubs is overlooked and could be the reason for the diverging outcomes. The aim of this paper is to reanalyze this relationship having the clubs’ size as moderator. Payroll – which captures the financial strength – is used as proxy of club size. Ordinary Least Squares regressions with season and league fixed effects are employed. Dispersion is measured by three indexes for robustness check. The outputs confirm the quadratic relationship between wage dispersion and performance, but adding that identical levels of dispersion have different impact on football clubs according to their financial strength.
In recent years, U.S. share buyback costs have hit record highs, in part due to the 2017 Tax Reform, shareholder activity and record low borrowing costs.. The purpose of the study is to study the reasons for choosing a policy of payments to investors in American companies and the impact of share buybacks on the results of the company and the economic system. The study examined traditional theories that explain the choice of investor payout policy. The authors have highlighted the main motives of companies when making decisions on the payment mechanism. After examining the existing theoretical aspects of the choice of payment policy and the trend of US buybacks, a regression analysis of panel data was carried out to comprehensively study the causes and consequences of the choice of payment policy.
The study examined traditional theories that explain the choice of investor payout policy. The authors highlighted the main motives of companies when making decisions on the mechanism of payments. After examining the existing theoretical aspects of payment policy choices and US buyback trends, panel data regression analysis was performed to comprehensively investigate the causes and consequences of payment policy choices. The study identified management's motives for the share buyback and demonstrated the positive impact of share buybacks on the company's development.
In this paper, stochastic parameters are introduced into the network games model with production and knowledge’s externalities. This model was formulated by V. Matveenko and A. Korolev and generalized two-period Romer model. Agents’ productivities have deterministic and Wiener components. We consider the dynamics that occur when two complete networks are combined. Explicit expressions in the form of Brownian random processes are obtained. A qualitative analysis of the solution of a system of stochastic equations is carried out.
In this study, an algorithm has been developed that allows one to assess the creditworthiness of a borrower-agricultural enterprise. It consists of a scoring model and standard values of the coefficients included in the model. The industry model is based on panel data from 99 companies, 39 of which went bankrupt between 2011 and 2020. The regulatory framework was compiled on the basis of an analysis of the most resilient enterprises in the industry, as well as bankrupts. To analyze the creditworthiness of enterprises, 11 indicators used by JSC Rosselkhozbank were analyzed. Using correlation analysis and other econometric tests, 5 optimal coefficients were selected out of 11 and a scoring model was built. The overall accuracy of the credit rating was high and amounted to 86.1%. The scoring model correctly verified 85% of non-bankrupt companies and 87.2% of bankrupts.
*Реализация соц. сети Instagram запрещена на территории России по основаниям осуществления экстремистской деятельности
The purpose of this article is to assess how museums have changed their presence on Instagram, how subscribers have responded to these changes, and what opportunities are opening up for museums in this regard. The study reveals an increase in the educational focus of museum Instagram during and after the lockdown, as well as an increase in subscriber activity, and offers recommendations on how to use these changes for the future development of museums. Statistical tests, namely the one-sample Kolmogorov-Smirnov test, the t-test, and the Wilcoxon signed rank test for linked samples, are used to test hypotheses. The research sample includes 7,776 Instagram posts from 74 Russian museums and covers three time periods: before, during and after the lockdown.
This article deals with an analysis of the M&A strategy utilized by Unilever Group, as well as with issues relating to identifying the factors defining the value of a diversified company. This article includes an estimation of the effectiveness of Unilever Group’s mergers and acquisitions strategy, aimed at creating the optimum business portfolio within the diversified corporate structure (company) by how it affects value of the company. The general hypothesis assumes that diversification does not have a destructive effect on the value of an international multi-business company that builds its portfolio based on the success of certain brands and business areas.
Purpose – The paper analyzes the effects of the capital structure on company performance (return on assets).
The analysis is conducted in a large sample of high-tech manufacturing and service companies in the transition
economy (Russian Federation). In addition to the aggregated analysis, separate investigations are conducted to
scrutinize the impact of company age, size and location factors (the effects of agglomerations). This research
postulates the existence and variability of the optimal capital structure and its dependence on economic crisis.
Design/methodology/approach – We utilized a large sample that includes 1,826 enterprises over the period
from 2013 to 2017. The estimation was performed using the panel-corrected standard error estimation
technique (Prais–Winsten regression) to account for the panel nature and distributional properties of our data.
The existence of the optimal capital structure was assessed based on a curvilinear (quadratic) function.
Findings – The results are consistent with the Static Trade-off Theory and show that this theory is applicable
to countries with transition economy. They demonstrate that effective management of the capital structure can
increase return on assets by 16–22%. The optimal share of borrowed capital is higher for small businesses
compared to larger ones and for enterprises located in agglomerations compared to those located in other
regions. A greater increase in profitability can be achieved by larger firm companies compared to smaller ones.
High share of borrowed capital leads to negative profitability, i.e. to losses by enterprises. No significant
differences in profitability growth were identified between young and mature enterprises. The optimal share of
borrowed capital that maximizes return on assets is in the range of 0–21%.
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.
This paper compares the profitability of French acquiring firms following the launch of corporate acquisition programs with that of single takeovers, by examining wealth of acquirers in both cases. While using the event study methodology for the calculation of abnormal returns for single takeovers, this study also considers the model of partially anticipated events for the assessment of the economic impact and the announcement effect of acquisition attempts. For the acquisition programs, we used a sample containing 46 French active acquirers, which launched 97 acquisition attempts between 1997 and 2007. For single takeovers, we examined 23 acquisitions by the same acquirers. The results of this study show that French investors obtain positive returns during and around the month of takeover announcement. French acquirers earn an average of 3.75% in two months, the month of announcement and the following month, and 4.02% in the month of announcement and the month preceding the announcement. These results show that single takeovers outperform corporate acquisition programs, since these
same French acquiring firms do not generate any profitability following the launch of these investment programs.
One of the important financial issues for the public companies is how to achieve the most optimal way to maximize firm value and shareholder wealth in a competitive environment. Another problem is connected with the search for an efficient method of the evaluation of social media mood impact on companies` values as it creates their image and reputation. The paper aims to investigate the impact of financial indicators and news related to enterprise on luxury companies` performance. Luxury industry is chosen as an object of the study as it has a range of specifics, which can cause the changes in the variables` effects. To accomplish the purpose of the research, the authors design fixed effect regression models on a sample of 45 European, Asian and American luxury companies for the period 2010-2019 and conduct sentiment, correlation and Granger-causality analyses using the extracted Twitter data. The results show that Net Margin, Return on Investments, Total Revenue, Earnings per Share, Current Ratio and Asset Turnover have a significant positive effect on the luxury companies` market capitalization while Total Debt Percentage of Total Equity influences negatively and significantly. The study also finds that participation in M&A and luxury companies` location have a significant impact on their market capitalization. Various impacts within the specifics of luxury sectors are also established for the sample examined in this research. Furthermore, strong relationships between news background and companies` performance is discovered.
The development of digital technology has raised concerns about a decline in labor activity. In this paper, we offer predictions of the possible dynamics of the share of labor income for G7 countries, based on an assessment of the parameters of the factor-augmenting CES function. Particular attention is paid not only to the parameter of elasticity of substitution, but also to the measurement of relative labor intensity, which is ignored in most similar works. We show that a decrease in the share of labor income under a substitution elasticity of less than one occurs due to a trend towards an increase in relative labor intensity while reducing the ratio of investment to output. This pattern is a theoretical anomaly and can be reasonably explained by the growth of monopoly power under the development of the digital economy. Continuation of this trend in the next 30 years may lead to a decrease in the share of labor income in the G7 countries by an average of 5–16%.
The COVID-19 pandemic affected the US economy at different levels. Since credit default swaps can be viewed as a default probability indicator, the article shows the credit default swap market perspective on how the US economy was hit by the pandemic. Forecasting models are built to estimate the predictability of the CDS market sectors during the pandemic, i.e., manufacturing, energy, banks, consumer goods, and services and financial sector excluding banks. Econometric tests are applied to check the uniqueness of credit default swap market sectors after the declaration of the pandemic. The results indicate that the financial sector excluding banks performed uniquely during the pandemic; i.e., the predictability of this sector dropped significantly, and the Chow breakpoint test and Wald coefficient test can identify the shift in the data after declaration of the pandemic.
It is well established that the effectiveness of pay-for-performance (PfP) schemes depends on employee- and organization-specific factors. However, less is known about the moderating role of external forces such as market competition. Our theory posits that competition generates two counteracting effects—the residual market and competitor response effects—that vary with competition and jointly generate a curvilinear relationship between PfP effectiveness and competition. Weak competition discourages effort response to PfP because there is little residual market to gain from rivals, whereas strong competition weakens incentives because an offsetting response from competitors becomes more likely. PfP hence has the strongest effect under moderate competition. Field data from a bakery chain and its competitive environment confirm our theory and let us refute several alternative interpretations.
Modern corporate theory interprets enterprise-wide risk management (ERM) as an agent between stakeholders and corporate governance. In accordance with the latest ERM framework, corporate risk management in business includes the methods and processes used by organizations to manage uncertainty and use the opportunities associated with achieving their goals. The aim of the study is to measure corporate management in business maturity forecasting models. The author predicted a company cluster based on signal to noise ratio. As the basic model, the author used the calculation method proposed by G. Taguchi to assess product quality as well as for the design and optimization of processes. The research method used for the study was empirical. The author obtained financial performance data relating to all 218 companies from the SPARK database. It was applied two-step cluster analysis to compare companies within the sample. Also, it was calculated the geometric mean for each quantitative variable to avoid the influence of temporary shocks and distortions. The results of a nonparametric test showed that the relationship between the signal-to-noise ratio (SNR) and ERM is significant. Thus, based on the results of the theoretical and empirical studies, we can argue that the measurement of ERM through the SNR is justified.
In a randomized controlled trial, a large retail chain’s Chief Executive Officer (CEO) sets new goals for the managers of the treated stores by asking them to “do what they can” to reduce the employee quit rate. The treatment decreases the quit rate by a fifth to a quarter, lasting nine months before petering out, but reappearing after a reminder. There is no treatment effect on sales. Further analysis reveals that treated store managers spend more time on human resources (HR) and less on customer service. Our findings show that middle managers are instrumental in reducing personnel turnover, but they face a trade-off between investing in different activities in a multitasking environment with limited resources. The treatment does produce efficiency gains. However, these occur only at the firm level.