Search

The knowledge, attitudes and perceptions of the high school students on Croatia&rsquo, s European Union (EU) accession event were omitted in numerous public opinion polls conducted since the 2013 accession. Therefore, the paper shows key benefits of Croatia&rsquo, s EU accession and the recent attitudes of high school students about the meaning of this event for their future lives. Research methods include desktop analysis regarding previous researches of the population attitudes and a quantitative survey conducted in January 2017 on a sample of a total of 1944 school graduates who were interviewed on issues of knowledge, perception and attitude to the event of Croatia&rsquo, s entrance and membership in the EU. The results point out that although Croatia acquires significant benefits from the EU accession, the very event is not recognized as being the key one by high school students. Considering that in many cases the youth opinion is the best indicator of overall social problems and considering the future programs and obligations as well as the role expected from the youth in implementation of these programs, the research findings on the perception of the event of Croatia&rsquo, s accession to the EU are a field within which future policy activities are envisaged.

We propose a novel multi-period trading model that allows portfolio managers to perform optimal portfolio allocation while incorporating their interpretable investment views. This model&rsquo, s significant advantage is its intuitive and reactive design that incorporates the latest asset return regimes to quantitatively solve managers&rsquo, question: how certain should one be that a given investment view is occurring? First, we describe a framework for multi-period portfolio allocation formulated as a convex optimization problem that trades off expected return, risk and transaction costs. Using a framework borrowed from model predictive control introduced by Boyd et al., we employ optimization to plan a sequence of trades using forecasts of future quantities, only the first set being executed. Multi-period trading lends itself to dynamic readjustment of the portfolio when gaining new information. Second, we use the Black-Litterman model to combine investment views specified in a simple linear combination based format with the market portfolio. A data-driven method to adjust the confidence in the manager&rsquo, s views by comparing them to dynamically updated regime-switching forecasts is proposed. Our contribution is to incorporate both multi-period trading and interpretable investment views into one framework and offer a novel method of using regime-switching to determine each view&rsquo, s confidence. This method replaces portfolio managers&rsquo, need to provide estimated confidence levels for their views, substituting them with a dynamic quantitative approach. The framework is reactive, tractable and tested on 15 years of daily historical data. In a numerical example, this method&rsquo, s benefits are found to deliver higher excess returns for the same degree of risk in both the case when an investment view proves to be correct, but, more notably, also the case when a view proves to be incorrect. To facilitate ease of use and future research, we also developed an open-source software library that replicates our results.

In the last few years, the financing of responsibly operating small and medium-sized enterprises (SMEs) has become the focus of attention of several national and international bodies. Consequently, a number of policies and support programmes have been established aimed at supporting SMEs that take a responsible approach concerning the company and its operations. Against this background, this article presents a comprehensive international overview of support programmes for financing responsible SMEs. Based on systematic desk research, documents of national governments as well as supranational and international organisations have been investigated. The findings reveal that there are strong regional differences in terms of support policy approaches, intensity, and criteria. The largest part of the identified programmes has been launched by the European Union and/or its member states. Additionally, the findings clarify that the primary focus of extant programmes is on the environmental dimension of sustainability, mainly energy-related questions. The social dimension has been neglected so far in the programmes.

Immigration is a controversial topic that draws much debate. From a human sustainability perspective, immigration is disadvantageous for home countries causing brain drains. Ample evidence suggests the developed host countries benefit from immigration in terms of diversification, culture, learning, and brain gains, yet less is understood for emerging countries. The purpose of this paper is to examine the presence of brain gains due to immigration for emerging countries, and explore any gaps as compared to developed countries. Using global data from 88 host and 109 home countries over the period from 1995 to 2015, we find significant brain gains due to immigration for emerging countries. However, our results show that there is still a significant brain gain gap between emerging and developed countries. A brain gain to the developed host countries is about 5.5 times greater than that of the emerging countries. The results hold after addressing endogeneity, self-selection, and large sample biases. Furthermore, brain gain is heterogenous by immigrant types. Skilled or creative immigrants tend to benefit the host countries about three times greater than the other immigrants. In addition, the Top 10 destination countries seem to attract the most creative people, thus harvest the most out of the talented immigrants. In contrast, we find countries of origin other than the Top 10 seem to send these creative people to the rest of the world.

This paper conducts an empirical study on the inclusion of uniform European Collective Action Clauses (CACs) in sovereign bond contracts issued from member states of the European Union, introduced as a regulatory result of the European sovereign debt crisis. The study focuses on the reaction of sovereign bond yields from European Union member states with the inclusion of the new regulation in the European Union. A two-stage least squares regression analysis is adopted in order to determine the extent of impact effects of CACs on member states sovereign bond yields. Evidence is found that CACs in the European Union are priced on financial markets and that sovereign bond yields do respond to the inclusion of uniform CACs in the European Union.

In the Dynamic Conditional Correlation with Mixed Data Sampling (DCC-MIDAS) framework, we scrutinize the correlations between the macro-financial environment and CO2 emissions in the aftermath of the COVID-19 diffusion. The main original idea is that the economy&rsquo, s lock-down will alleviate part of the greenhouse gases&rsquo, burden that human activity induces on the environment. We capture the time-varying correlations between U.S. COVID-19 confirmed cases, deaths, and recovered cases that were recorded by the Johns Hopkins Coronavirus Center, on the one hand, U.S. Total Industrial Production Index and Total Fossil Fuels CO2 emissions from the U.S. Energy Information Administration on the other hand. High-frequency data for U.S. stock markets are included with five-minute realized volatility from the Oxford-Man Institute of Quantitative Finance. The DCC-MIDAS approach indicates that COVID-19 confirmed cases and deaths negatively influence the macro-financial variables and CO2 emissions. We quantify the time-varying correlations of CO2 emissions with either COVID-19 confirmed cases or COVID-19 deaths to sharply decrease by &minus, 15% to &minus, 30%. The main takeaway is that we track correlations and reveal a recessionary outlook against the background of the pandemic.

This paper describes the development of a chatbot as a cognitive user interface for portfolio optimization. The financial portfolio optimization chatbot is proposed to provide an easy-to-use interface for portfolio optimization, including a wide range of investment objectives and flexibility to include a variety of constraints representing investment preferences when compared to existing online automated portfolio advisory services. Additionally, the use of a chatbot interface allows investors lacking a background in quantitative finance and optimization to utilize optimization services. The chatbot is capable of extracting investment preferences from natural text inputs, handling these inputs with a backend financial optimization solver, analyzing the results, and communicating the characteristics of the optimized portfolio back to the user. The architecture and design of the chatbot are presented, along with an implementation using the IBM Cloud, SS&amp, C Algorithmics Portfolio Optimizer, and Slack as an example of this approach. The design and implementation using cloud applications provides scalability, potential performance improvements, and could inspire future applications for financial optimization services.

This paper examines relative stock market performance following the onset of the coronavirus pandemic for a sample of 80 stock markets. Weekly data on coronavirus cases and deaths are employed alongside Oxford indices on each nation’s stringency and government support intensity. The results are broken down both by month and by geographical region. The full sample results show that increased coronavirus cases exert the expected overall effect of worsening relative stock market performance, but with little consistent impact of rising deaths. There is some evidence of significantly negative stock market effects arising from lockdowns as reflected in the Oxford stringency index. There are also positive reactions to government support in March and December in the overall sample—combined with some additional pervasive effects seen in mid-2020 in Latin America.

We estimate the impact of macroeconomic risk factors on shipping stock returns, using a quantile regression (QR) model. We regress the excess return of a portfolio for the container, dry bulk, chemical/gas, oil tanker, and diversified shipping sectors on the world market portfolio excess return, volatility index, and changes in the oil price, exchange rate, and interest rate. The sensitivities of stock returns to the risk factors differ across quantiles and shipping segments and are found to be significant for the volatility index, world market portfolio return, exchange rate, and changes in long-term interest rate with variation over quantiles. This provides evidence of asymmetric and heterogeneous dependence between stock returns and certain macroeconomic risk variables. The results of the study also suggest that standard OLS regression is inadequate to uncover the risk-return relation.

The paper aims to investigate the effects of the COVID-19 pandemic on working capital management policies among Polish small and medium-sized enterprises operating in Group Purchasing Organizations (GPOs). The results show that the firms adopted a moderate–conservative strategy for their working capital management. Moreover, the evidence confirms that the COVID-19 pandemic crisis did not change Working Capital Management (WCM) strategies significantly. The companies that have high financial security as a result of the high ratio of Liquidity, Quick, and cash conversion cycle (CCC) have tried to attract more new customers in the market by increasing the due date of accounts receivable so they can improve their sales performance, and also reduce the liabilities turnover to be able to work with more suppliers in the market. Moreover, among the various WCM strategies, the companies with a higher CCC ratio, along with those whose bulk of current assets consisted of accounts receivable and short-term investments, managed to have higher sales returns. Finally, our outcomes indicate that the firms operating in large cities have lower sales returns, meaning even Polish small and medium-sized enterprises’ ability within GPOs with the aid of the central unit can also get high return on sales (ROS) results.

This paper investigates the role of institutional investors in the improvement of corporate governance for the companies in which they invest (investee companies) using evidence about the attributes of boards of directors across 15 countries. Furthermore, this paper examines the extent to which the activism of institutional investors is determined by the institutional environment, to include various economic conditions (pre-crisis, crisis and post-crisis), legal systems and ownership structures. Drawing from the agency theory and institutional theory, the results show that foreign institutional investors are the main promoters of board governance structures across the globe. This study also provides evidence that institutional investors promote the independence of a board and its audit and compensation sub-committees (but excluding its nomination committee). The study also demonstrates that institutional investors reduce board entrenchment, though it presents no evidence that institutional investors reduce board busyness. The results also suggest that institutional investors behave differently when operating within different economic conditions (pre-crisis, crisis and post-crisis), legal systems and ownership structures. This paper contributes to the growing literature on shareholder activism and comparative corporate governance mechanisms. The findings suggest that the activism of institutional investors is contingent on the institutional settings, to include economic conditions, legal systems and ownership structures.

What incentives do managers face that might give rise to inefficient investments in leases? If managers make inefficient investments in leases, what economic consequences arise for those managers and their firms? We develop a model of expected investments in leased assets and use the residuals from the model as proxies for inefficient investments. We find that, in contrast to investments in capital expenditures, leasing appears to be a mechanism through which managers can seemingly over-invest, even among firms with high quality financial reporting and negative free cash flows. Examining economic consequences, we predict and find that unexpected investments in leased assets trigger increasing future sales growth but declining future earnings growth for as long as three years ahead. We also find a negative relation with contemporaneous stock returns, suggesting investors view unexpected investments in leases as value destructive. Finally, despite negative returns consequences, we find that unexpected investments in leases are associated with higher CEO compensation driven primarily by future sales growth. Our study suggests that compensation contracts that reward growth may give managers’ incentives to drive sales growth with larger-than-expected investments in leased assets, which lead to slower future earnings growth and negative share price consequences for investors. Our results should inform managers and board members, investors, and researchers interested in investment efficiency, corporate governance, and leases.

This study analyses the impact of social media popularity on the global mergers and acquisitions (M&amp, A) market using a sample of 66,905 M&amp, A transactions across 50 countries for the sample period from 2011 to 2017. Social media influence on M&amp, A transactions is tested using competing bids and proportion of cash paid in the transaction deal characteristics. We find that social media popularity has increased the probability of competing bids by 7.7% across countries and the proportion of cash paid in transactions decreased by 2.5% across countries. The results of additional analyses using the introduction of the internet are consistent with the conclusion that technologies that enhance the transmission of public information have an effect on the M&amp, A variables tested. We test the robustness of our results using subsample analysis and placebo tests. This study is distinct from existing literature due to its globally diverse M&amp, A dataset, unique social media and internet data, and cross-country approach to social media’s influence on financial markets.

The current pandemic situation has created many challenges for maintaining positive relationships between fast fashion retailers and their suppliers. In the proposed paper it is assumed that strong and ethical relationships may be beneficial for all supply chain members, especially in the era of global pandemic. Therefore, the aforementioned issues (fast fashion retailers’ ethical behavior towards suppliers) constituted the subject of the paper. Our knowledge about relationships between fast retail chains and their suppliers in the times of global pandemic is relatively week. Trying to fill the gap, this paper discussed relationships between fast fashion retail chains and their suppliers’ customers on the basis of literature review and case study research. Purpose: The aim of the paper was to indicate the scope of activities undertaken by retailers and addressed at suppliers by fast fashion retail chains in pandemic times. The following goals of descriptive and cognitive character were assumed in the paper: (a) Identification of the fast fashion retailers’ common behavior in the era of pandemic, and (b) indication of ethical practices applied by fast fashion retail chains which are beneficial for all retail chain members, based on the Inditex example. Methodology: Based on the theoretic deliberation of retail chain relationships with suppliers in the pandemic times, qualitative research was conducted to supplement the theoretical background. The purpose of this study was to identify how fast fashion retailers maintain relationships with their suppliers in supply chains. The conducted research enabled us to reveal answers to the following research questions: What are good practices of fast fashion retailers in terms of relationships with suppliers? Can socially responsible, trustworthy fast fashion retailers stay profitable in the Covid-19 pandemic? The theoretical deliberation was based on a critical literature review. The empirical part of the paper was based on case study research. The conducted research was descriptive in nature, conducted in order to describe a particular phenomenon within its context, and was not intended to provide conclusive evidence, but to have a better understanding of the problem. A descriptive intrinsic case study was the method applied in the research. Results: On the grounds of literature studies, as well as collected information, we can state that close and ethical cooperation with suppliers, based on socially responsible relationships, are becoming a more and more important part of the strategy for commercial chains. There are companies that use any legal measures to not fulfil their obligations as contractors and avoid paying for orders completed and in production. The descriptive case study research allowed us to observe, analyze, and report good practices of fast fashion retailers in terms of relationships with their suppliers based on the Inditex example. The theoretical contribution: On the grounds of the case study, we can state that during pandemic times fast fashion retail chains have focused on the development of relationships with suppliers, which means changing from transactional to relationship marketing in cooperation strategies. Practical implications (if applicable): The paper provided intellectual input into the managerial problem of how to develop mutual beneficiary relationships between fast retail chains and their suppliers. The study suggests that fast fashion retail chains have to take into consideration growing customer expectations, which regard their cooperation’s strategies toward suppliers.

Using US firms with over $5b market cap, this paper tests the impact of levered beta on the firm’s market value and optimal capital structure. Using the synthetic rating method in a recursive model, the paper shows the current and optimal weighted average cost of capital sensitivities as the firm’s market risk measured by beta changes. The paper shows that the change in the value of beta due to alternative leverage levels or other risk factors will alter the cost of capital insignificantly and has no impact on the optimal capital structure due to those firms’ extra-strong bond ratings. As a side-benefit of the synthetic rating method, one may also observe the market-level variables’ impacts on the cost of capital computations and the optimal debt ratio. The paper uses Disney Corporation to show how the synthetic rating methodology helps to disclose the sensitivities of hypothetical alternative leverages.

In this study, we investigated the impact of the first wave of the COVID-19 pandemic on various sectors of the Australian stock market. Market capitalization and equally weighted indices were formed for eleven Australian sectors to examine the influence of the pandemic on them. First, we examined the financial contagion between the Chinese stock market and Australian sector indices through the dynamic conditional correlation fractionally integrated generalized autoregressive conditional heteroskedasticity (DCC-FIGARCH) model. We found high time-varying correlations between the Chinese stock market and most of the Australian sector indices, with the financial, health care, information technology, and utility sectors displaying a decrease in co-movements during the pandemic. The Modified Iterative Cumulative Sum of Squares (MICSS) analysis results indicated the presence of structural breaks in the volatilities of most of the sector indices around the end of February 2020, but consumer staples, industry, information technology and real estate indices did not display any break. Markov regime-switching regression analysis depicted that the pandemic has mainly affected three sectors: consumer staples, industry, and real estate. When we considered the firm size, we found that smaller companies in the energy sector exhibited gradual deterioration, whereas small firms in the consumer staples sector experienced the largest positive impact from the pandemic.

We estimate the effect of acquisition performance and acquisition activity on CEO compensation for the full set of CEOs of large public U.S. corporations in the Execucomp database over the period 1992-2016. Most previous work has focused on publicly traded acquisition targets. We focus on the comparison between public and private targets, showing significant differences between the two. One primary finding, based on panel data regressions (both fixed and random effects) is that the performance of private acquisitions, as measured by abnormal announcement returns, has a statistically significant positive effect of plausible economic magnitude on CEO compensation. Public acquisitions exhibit a smaller positive effect that is statistically insignificant. For both, acquisition activity (number of acquisitions) has a statistically significant effect on compensation. Furthermore, compensation is more sensitive to acquisition activity than to performance. Our results suggest that agency considerations are important for both public and private acquisitions but are more important for public acquisitions.

The issue of capital structure in an enterprise is often described in the literature on the subject, however, theories are classified into various approaches, and their characteristics are often limited to selected theories. This work is an attempt at a synthetic presentation of the theory of capital structure. The aim of the article was to review and try to organise the most important theories of capital structure, paying attention to the influence of capital structure on the processes of creating value. The paper also highlights the most important theoretical works in this area. The study consists of two main parts. The first part indicates the diversity of defining the concepts of capital structure and indicates the approaches in classifying this structure. The second part characterises the theories of capital structure in the context of value creation. Based on the presented theories, it can be stated that there is no agreement as to whether and to what extent capital structure translates into the process of creating enterprise value. Therefore, it seems justified to conduct appropriate empirical research in this respect.

Many studies have attempted to investigate the drivers of preventive behaviour. This study contributes to this strand of literature by examining the association between higher insurance deductibles in the Swiss health system and preventive behaviour that allows for maintaining a good diet, exercising and limiting/abstaining from smoking and alcohol consumption. To conduct our study, we made use of the 2017 Swiss Health Survey and employed an ordered probit model with each prevention aspect as a dependant variable. Our results show that, except for alcohol consumption, higher insurance deductibles were significantly associated with higher behavioural prevention. Our study also highlighted how numerous other factors influenced prevention and offered some guidance for public policies to further incentivise prevention decisions.

This study explores the contrasting impacts of the COVID-19 pandemic on various industries in Australia. Considering all daily announced information, we analyzed the diverse impacts of COVID-19 on the sectoral stock returns from 26 January to 20 July 2020. Sixteen out of twenty examined stock indices negatively react to the daily rise in COVID-19 confirmed cases. Several actions from the Australian government to control the pandemic are relatively ineffective in boosting the overall financial market, however, some positive interactions are captured in five sectors of industrials, health care, metals and mining, materials, and resources. The result shows that all industries that benefited from government financial assistance are either shielded or less severely affected by the pandemic. While sectors that did not directly receive financial remedies relatively showed no enhancement in their overall performance. Having achieved short-term success in helping the economy, the government recorded an all-time high deficit since 2004 that might eventually lead to adverse effects on the overall economy. The Australian equity market is found to be rationally distinct to the crude oil price risk, while positive correlations between AUD/USD rate and real estate-related sectors are reported.

The COVID-19 pandemic and induced economic and social constraints have significantly impacted the confidence of both consumers and businesses. Despite that, comprehensive studies of the impact of the COVID-19 pandemic on the consumer and business sentiment are still lacking. Thus, in our research we aim to identify consumer and business confidence indicators’ reaction to the spread of the COVID-19 pandemic in the Eurozone, the United States, and China. For this purpose, we used the method of correlation–regression analysis. We chose the consumer-confidence index, manufacturing purchasing manager’s index, and services purchasing manager’s index as dependent variables, and the number of confirmed cases of COVID-19, the number of deaths caused by COVID-19, and the mortality rate of COVID-19 infections as independent variables. The results showed a relatively rapid and robust effect of COVID-19 in the short period, but longer-term results depended on the region and were not so unambiguous: in the case of the Eurozone, the spread of COVID-19 pandemic did not affect the consumer-confidence index (CCI) or, in the cases of the United States and China, affected this index negatively, the purchasing managers’ index (PMI) in the services sector was significantly negatively affected by the mortality risk of COVID-19 infection, and the impact on the purchasing managers’ index (PMI) in the manufacturing industry appeared to be mixed.

Expected utility theory (EUT) is currently the standard framework which formally defines rational decision-making under risky conditions. EUT uses a theoretical device called von Neumann–Morgenstern utility function, where concepts of function and random variable are employed in their pre-set-theoretic senses. Any von Neumann–Morgenstern utility function thus derived is claimed to transform a non-degenerate random variable into its certainty equivalent. However, there can be no certainty equivalent for a non-degenerate random variable by the set-theoretic definition of a random variable, whilst the continuity axiom of EUT implies the existence of such a certainty equivalent. This paper also demonstrates that rational behaviour under utility theory is incompatible with scarcity of resources, making behaviour consistent with EUT irrational and justifying persistent external inconsistencies of EUT. A brief description of a new paradigm which can resolve the problems of the standard paradigm is presented. These include resolutions of such anomalies as instant endowment effect, asymmetric valuation of gains and losses, intransitivity of preferences, profit puzzle as well as the St. Petersburg paradox.

Cancellation of the events offered by cultural institutions was caused by the restrictions introduced by the government and, at a critical moment, a national lockdown. The COVID-19 pandemic forced cultural institutions to adapt to the new reality. The aim of this article was to present the impact of the pandemic on the activities of cultural institutions, as well as to identify and systematize the activities of such institutions during the pandemic. The following classification, dividing the activities into three groups, has been proposed: virtualization of existing activities, expansion of activities with additional initiatives, and implementation of corporate social responsibility (CSR) initiatives. The greatest challenge was the virtualization of the existing activities and finding new customer markets. The pandemic has contributed to a significant deterioration in the financial situation of cultural institutions because of the reduced income. Long-term effects on cultural institutions may be difficult to predict and losses may be difficult to rebuild.

Departing from previous studies, which have mostly focused on Western countries, our work investigates the determinants of the corporate environment, social and governance (ESG) reporting among Asian firms. Examining Asian public listed firms from 2005 to 2017, our cross-sectional model results indicate that firm characteristics (economic performance, profitability, leverage and size) are found to disclose additional ESG information. The outcome is consistent with the legitimacy theory, which posits that firms provide higher ESG reporting to legitimize and justify the firm’s continuous existence. The findings are important for firms, stakeholders and policymakers. While firms may formulate ways to improve ESG reporting to compete in the international market, the stakeholders may pressure firms to disclose more information on ESG and policymakers to designalegal framework on ESG that suits firms in Asia.

The close relationship between governments and their central banks generates risks for both partners. This paper presents an original qualitative empirical approach based on textual analysis of the United States of America, China, and their Central Banks’ respective communications. These financial communications are the subject of comparison through a textual analysis to determine these actors’ positions in the “cultural theory” and, more widely, the sociology of risk. The risk profiles identified of the United States of America Federal government and the People’s Bank of China do not necessarily correspond to their legal status and economic role. These results also shed light on the fact that the cultural background cannot be separated from the risk perception in these countries. However, an eye needs to be kept on the geopolitics and securities risk factors that can influence the global economy’s evolution.

This research intends to explore the relationship between capital buffer, nominator effect, denominator effect, and economic growth for large insured commercial banks of the USA. The study applied a two-step system Generalized Method of Moment (GMM) framework by taking the unique and comprehensive dataset over the period extending from 2002 to 2018. The research found a countercyclical relationship between a capital buffer and economic growth. In the case of well-capitalized banks, this relationship is more critical than adequately capitalized banks. In the case of low-liquid banks, counter-cyclicality is more significant than high-liquid banks. The results also suggest the pro-cyclical relationship between nominator, denominator, and economic growth. The results remain consistent and robust with the use of the tier-one capital buffer ratio. The findings have implications for regulators to incorporate the counter-cyclicality between the capital buffer and economic growth, while formulating the policies for capital requirements in the future.

Since their introduction, quanto options have steadily gained popularity. Matching Black–Scholes-type pricing models and, more recently, a fat-tailed, normal tempered stable variant have been established. The objective here is to empirically assess the adequacy of quanto-option pricing models. The validation of quanto-pricing models has been a challenge so far, due to the lack of comprehensive data records of exchange-traded quanto transactions. To overcome this, we make use of exchange-traded structured products. After deriving prices for composite options in the existing modeling framework, we propose a new calibration procedure, carry out extensive analyses of parameter stability and assess the goodness of fit for plain vanilla and exotic double-barrier options.

The purpose of this study is to determine the mutual influence of financial security on the textile enterprises development level. The proposed methodological approach is based on the formation of an integrated financial security indicator and its regression model. The study is based on 16 textile enterprises in the European Union. Integral indicators on capital structure, current financing sufficiency and financial efficiency of the investigated enterprises have been defined according to the rapid diagnostics of financial provision of the textile enterprises. The state of financial support for the studied companies' development has been evaluated. It has been established that the development of textile enterprises depends to a large extent on their financial support as a whole. The change in the development level of companies depends substantially on the change in the integrated indicator of their financial provision. In particular, textile enterprises' development is significantly affected by the capital structure and the predominance of equity in it, as well as current financing. The financial efficiency factors taken into account do not have a significant impact on the development of textile enterprises. This study proposes a financial security model, developed by partial integrated indicators. It enables visual comparison, collation of the capital structure state, current financing and financial efficiency of the studied enterprises with optimal value. info:eu-repo/semantics/publishedVersion

The present research focuses on the influence of the well-being indicators, more specifically, the indicators reflecting the life quality on the banking systems evolution from the EU member states. The study offers a unique approach to comparing the two country groups: the eurozone countries and the EU noneuro countries during the 2008–2019 period. The model is estimated with the help of the OLS method by using panel data. The study aims to identify which life quality indicators significantly influence the EU member states’ banking systems evolution and develop models dividing the countries into two groups. Our conclusions show that, among all the determinant factors analysed in this study, household consumption and internet users strongly influence all EU countries’ banking systems.

Frontier markets have become increasingly investible, providing diversification opportunities, however, there is very little research (with conflicting results) on the relationship between Foreign Exchange (FX) and frontier stock markets. Understanding this relationship is important for both international investor and policymakers. The Markov-switching Vector Auto Regressive (VAR) model is used to examine the relationship between FX and frontier stock markets. There are two distinct regimes in both the frontier stock market and the FX market: a low-volatility and a high-volatility regime. In contrast with emerging markets characterised by “high volatility/low return”, frontier stock markets provide high (positive) returns in the high-volatility regime. The high-volatility regime is less persistent than the low-volatility regime, contrary to conventional wisdom. The Markov Switching VAR model indicates that the relationship between the FX market and the stock market is regime-dependent. Changes in the stock market have a significant impact on the FX market during both normal (calm) and crisis (turbulent) periods. However, the reverse effect is weak or nonexistent. The stock-oriented model is the prevalent model for Sub-Saharan African (SSA) countries. Irrespective of the regime, there is no relationship between the stock market and the FX market in Cote d’Ivoire. Our results are robust in model selection and degree of comovement.

The purpose of our paper is to investigate whether any differences between International Financial Reporting Standards (IFRS) and local Generally Accepted Accounting Principles (GAAP) impact the transparency of financial reporting of non-listed companies through bankruptcy prediction. This contributes to extant research that has focused on the effects of IFRS adoption in the context of listed companies. For our investigation, we used logistic regression, well-established accounting-based predictors, and a sample of financial statements from privately held Swedish companies using IFRS, and Norwegian companies using Norwegian GAAP. The results indicate that financial statements made under IFRS may be better suited for bankruptcy prediction than those made under Norwegian GAAP. Our findings suggest that the use of IFRS could aid in increasing the informativeness of financial reports by promoting transparency and prevent managers of firms facing insolvency from engaging in creative accounting practices. Our results should, however, be applied with caution, as they may be due to the differences in characteristics across firms that are not captured by our research design. We leave this issue open to future research.

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to futures markets. First, we preprocess futures time series comprised of front months to render them suitable for our returns-based trading framework and compile a data set comprised of 60 futures covering nearly 10 trading years. Next, we train several machine learning models to predict whether the h-day-ahead return of each future out- or underperforms the corresponding cross-sectional median return. Finally, we enter long/short positions for the top/flop-k futures for a duration of h days and assess the financial performance of the resulting portfolio in an out-of-sample testing period. Thereby, we find the machine learning models to yield statistically significant out-of-sample break-even transaction costs of 6.3 bp—a clear challenge to the semi-strong form of market efficiency. Finally, we discuss sources of profitability and the robustness of our findings.

Financial literacy is extremely important, both from the perspective of the financial well-being of individuals and the stability of the financial market and the whole economy. The more financially literate a bank’s customers are, the more frequently and consciously they use financial products and services. Thus, banks are potentially significant stakeholders in the financial education process. Considering that social media have become the leading channel for communication and relationship building, especially regarding young clients, this channel should also be used by banks to increase financial literacy. The aim of this paper is to assess banks’ involvement in financial education activities through social media. We assume that banks use social media as a modern and attractive channel for improving financial education among social media users. The empirical analysis was conducted using several data sources, including non-financial statements and a unique self-collected dataset that describes the specifics of the most popular social media platforms (like Facebook, Twitter, YouTube, Instagram, GoldenLine, and LinkedIn) in the activities of commercial and cooperative banks in Poland between 2010 and 2019. Descriptive statistical methods and cluster analysis were used. The results show that educational activities provided by banks in Poland differ for each social media channel. Additionally, although financial education topics have become more popular among content published by banks, there is a huge disproportion between cooperative and commercial banks. Generally, banks that are more active on social media (mostly commercial banks) also pay more attention to the financial education context.

The aim of the paper is to assess the evolution of the cost of credit risk (CoR) of Polish banks as a result of the COVID-19 pandemic in the first three quarters of 2020 as well as its microeconomic determinants. We analysed the structural diversity of the sample of the 13 largest Polish commercial banks in terms of the evolution of their CoR. For this purpose, a diagraphic method of Jan Czekanowski was used. It allowed us to distinguish two groups of banks displaying features characteristic of multi-object structures and three groups consisting of individual banks characterized by atypical CoR developments, significantly different from the structures of objects classified to the first and second groups. In the second part of the research, in order to identify the determinants of the observed trends, a multiple regression model was used in which the explanatory variable was the dynamics of CoR in the first three quarters of 2020. The parameters of return on capital (ROE) at the end of 2019, Non-Performing Loans (NPLs) at the end of 2019 and the dynamics of write-offs in the period 2017–2019 proved to be important explanatory variables.

There is a lack of a holistic perspective on bank performance. This study proposes a multidimensional (three-pronged) approach encompassing regulation, profitability, and nonperforming assets (NPAs) and their interactions as a measure of the performance of a bank. Moreover, the impact of equity holdings of promoters, institutional investors, and retail investors on the proposed three-pronged approach of the bank performance are also explored. Values of the concerned variables were gathered from 2016 to 2019. The dynamic panel data method was applied to empirically test the proposed model. The main findings supported the premises of the proposed approach to bank performance. Furthermore, various ownership classes provided mixed results for their impact on bank performance. Unfavorable roles of promoters and institutional investors and an indifferent role of the retail investors group were startling outcomes of the study. Successful empirical endorsement of the proposed approach for bank performance provides a fresh perspective and has varied policy- and managerial-level implications. The findings regarding various shareholder groups (ownership classes) can be a catalyst to set the policy for ownership distribution in banks, as well as shareholder protection and activism, which are conspicuously absent in India.

While the outbreak of the COVID-19 disease has caused asset markets to experience an unprecedented spike of risk and uncertainty worldwide, the real estate market in many global cities appears to be immune to the adverse effects. How does COVID-19 affect urban housing markets? This study is a first attempt to identify the pandemic’s impact on house prices by applying a price gradient analysis to the COVID-19 epicentre in China. Considering microlevel housing transaction data in 62 areas from nine districts in Wuhan City from January 2019 to July 2020, the hedonic pricing and the price gradient models suggest that there was, respectively, a 4.8% and a 5.0–7.0% year-on-year fall in house prices immediately after the pandemic outbreak. Although house prices rebounded after the lockdown period, the gradient models show that the price gradients were flattened from the epicentre to the urban peripherals. The price premiums in high-density areas were also substantially discounted after the city’s lockdown. Our findings are robust to different model specifications. The implication is that the risk associated with the pandemic is localised and transitory in nature. People may be able to internalise the risk by residing in low-density residential areas.

We developed a model-free Bayesian extraction procedure for the stochastic discount factor under a yield curve prior. Previous methods in the literature directly or indirectly use some particular parametric asset-pricing models such as with long-run risks or habits as the prior. Here, in contrast, we used no such model, but rather, we adopted a prior that enforces external information about the historically very low levels of U.S. short- and long-term interest rates. For clarity and simplicity, our data were annual time series. We used the extracted stochastic discount factor to determine the stripped cash flow risk premiums on a panel of industrial profits and consumption. Interestingly, the results align very closely with recent limited information (bounded rationality) models of the term structure of equity risk premiums, although nowhere did we use any theory on the discount factor other than its implied moment restrictions.

In this paper, we explore the relationship between a firm’s environmental policies and their risk-adjusted stock returns, using a sample of stock exchange-listed Australian firms over the period of 2010–2018. We observed a positive and statistically significant relationship suggesting that a firm’s environmental policies partially explain their stock performance. Moreover, we found that investors in the Australian market significantly value a companies’ efforts to reduce emissions, and that this primarily drives the investors’ observed reaction to a firm’s social corporate policies. Next, we formed portfolios and observed that portfolios formed on high environmental, social, and governance (ESG) Environmental Pillar scores consistently outperformed those formed on low-ESG Environmental Pillar scores. Overall, our results lend support to the notion that investors in the Australian market value information about a firm’s social policies.

Intraday high-frequency data of stock returns exhibit not only typical characteristics (e.g., volatility clustering and the leverage effect) but also a cyclical pattern of return volatility that is known as intraday seasonality. In this paper, we extend the stochastic volatility (SV) model for application with such intraday high-frequency data and develop an efficient Markov chain Monte Carlo (MCMC) sampling algorithm for Bayesian inference of the proposed model. Our modeling strategy is two-fold. First, we model the intraday seasonality of return volatility as a Bernstein polynomial and estimate it along with the stochastic volatility simultaneously. Second, we incorporate skewness and excess kurtosis of stock returns into the SV model by assuming that the error term follows a family of generalized hyperbolic distributions, including variance-gamma and Student’s t distributions. To improve efficiency of MCMC implementation, we apply an ancillarity-sufficiency interweaving strategy (ASIS) and generalized Gibbs sampling. As a demonstration of our new method, we estimate intraday SV models with 1 min return data of a stock price index (TOPIX) and conduct model selection among various specifications with the widely applicable information criterion (WAIC). The result shows that the SV model with the skew variance-gamma error is the best among the candidates.

‘Financial crisis’ is sometimes regarded as synonymous with ‘economic crisis’, but this is an oversimplification and risks missing the feedback loops between the financial and real economies. In this paper, the role of money is revisited in the context of distinguishing the real economy from the financial economy. A theoretical framework is developed to explain how endogenous (bank credit) and central bank exogenous (quantitative easing, QE) money creation feed into the real and financial economies. It looks at how the velocity of monetary circulation varies between the two economies and across asset types within the financial economy. Monetary transmission mechanisms are set into a framework that helps explain how QE stimulus risks combining asset price bubbles with poor growth in the real economy. The real economy transmission mechanism of ‘helicopter money’ is given context, enabling an assessment of the efficacy of both the QE and helicopter money policy routes. Finally, we present a new type of monetary transmission, ‘Smart Helicopter Money’, to deliver monetary stimulus to innovators, SMEs and high-growth firms via both complementary currencies and a modified form of QE in order to achieve proportionally greater impact on the real economy.

Data science and machine-learning techniques help banks to optimize enterprise operations, enhance risk analyses and gain competitive advantage. There is a vast amount of research in credit risk, but to our knowledge, none of them uses credit registry as a data source to model the probability of default for individual clients. The goal of this paper is to evaluate different machine-learning models to create accurate model for credit risk assessment using the data from the real credit registry dataset of the Central Bank of Republic of North Macedonia. We strongly believe that the model developed in this research will be an additional source of valuable information to commercial banks, by leveraging historical data for all the population of the country in all the commercial banks. Thus, in this research, we compare five machine-learning models to classify credit risk data, i.e., logistic regression, decision tree, random forest, support vector machines (SVM) and neural network. We evaluate the five models using different machine-learning metrics, and we propose a model based on credit registry data from the central bank with detailed methodology that can predict the credit risk based on credit history of the population in the country. Our results show that the best accuracy is achieved by using decision tree performing on imbalanced data with and without scaling, followed by random forest and linear regression.

In the beginning of the second book of his Politeia (Republic) Plato in passage 2.358e–359a–c raises the issue of the administration of justice as a means of motivating people to behave fairly regarding their relationships and when cooperating with each other because, at the end, this is mutually beneficial for all of them. We argue that this particular passage could be seen as a part of a wider process of evolution and development of the institutions of the ancient Athenian economy during the Classical period (508–322 BCE) and could be interpreted through modern theoretical concepts, and more particularly, game theory. Plato argued that there are two players, each with two identical strategies, to treat the other justly or unjustly. In the beginning, each player chooses the “unjust” strategy, trying to cheat the other. In this context, which could be seen as a prisoner’s dilemma situation, both end with the worst possible outcome, that is, deceiving each other and this has severe financial consequences for both of them. Realizing this, in a repeated game situation, with increasing information on the outcome and on each other, they choose the “just” strategy so achieving the best outcome and transforming the game in a cooperative one. We analyze this, formulating a dynamic game which is related to international commercial transactions, after explaining how such a situation could really arise in Classical Athens. We argue that this is the optimal scenario for both parties because it minimizes the risk of deceiving each other and creates harmony while performing financial transactions.

This research seeks to analyze the export differences facing countries in the EU and EFTA. This is firstly to analyze the effects on international trade of the trade bloc of the European Union (EU), and secondly the European Free Trade Association (EFTA), and provide a comparison of these two. This research seeks to analyze exports determinants to answer these two questions. There are two countries selected for this study, the small EFTA country Iceland, and the large EU country UK, before BREXIT. We apply a gravity model in our econometric analysis, with exports dependent on the gross domestic product, population, and geographic distance. We estimate these effects on the exports of both the UK and Iceland in separate equation systems. We conclude that exports from the UK, before BREXIT, are more negatively affected by geographical distance than exports for the EFTA country Iceland, when corrected for gross domestic product and population size.

This paper aims to develop some static and conditional (dynamic) models to predict portfolio returns in the Borsa Istanbul (BIST) that are calibrated to combine the capital asset-pricing model (CAPM) and corporate governance quality. In our conditional model proposals, both the traditional CAPM (beta) coefficient and model constant are allowed to vary on a binary basis with any degradation or improvement in the country’s international trade competitiveness, and meanwhile a new variable is added to the models to represent the portfolio’s sensitivity to excess returns on the governance portfolio (BIST Governance) over the market. Some robust and Bayesian linear models have been derived using the monthly capital gains between December 2009 and December 2019 of four leading index portfolios. A crude measure is then introduced that we think can be used in assessing governance quality of portfolios. This is called governance quality score (GQS). Our robust regression findings suggest both superiority of conditional models assuming varying beta coefficients over static model proposals and significant impact of corporate governance quality on portfolio returns. The Bayesian model proposals, however, exhibited robust findings that favor the static model with fixed beta estimates and were lacking in supporting significance of corporate governance quality.

This paper investigates the determinants behind persistent and prolonged stays under the International Monetary Fund (IMF) program and its effectiveness, using panel data consisting of 70 countries that have requested IMF support multiple times, during the period 1980–2018. By employing panel survival analysis, we conclude that weak economic indicators, e.g., current account deficit, high debt service ratio, low GDP, are the main reasons that force a country to reach out to the IMF support program. We further extend our analysis to investigate the effectiveness of the IMF program by dividing our sample into two groups, based on income level. To overcome the issue of endogeneity, we implement the panel instrumental two-stage least squares (2SLS) fixed-effect model. In the light of our analysis, we find a contemporaneous positive impact of the IMF fund program on the economic growth of upper middle-income countries, while, for low-income countries, its contemporaneous impact is insignificant, but becomes visible over time.

In this paper, we examine the impact of risk disclosure practices on trade credit. We hypothesize that risk information could reduce information opacity that arises between companies and their suppliers. We collected annual reports for Tunisian listed companies for the period 2008–2013. This gives us 146 firm-year observations. We find that risk disclosure has a positive impact on the level of trade credit. Our paper offers a new empirical evidence on the role of risk disclosure in reducing information asymmetry and increase companies’ access to short-term external funds. Our study provides managerial implications for firms, suppliers, and regulatory authorities.

This paper investigates the relationship between economic policy uncertainty (EPU), an index capturing newspaper coverage of policy-related issues, and momentum profits. Momentum remains an unexplained anomaly. Our findings reveal a statistically negative association between EPU and hedge momentum portfolios. The short side portfolio dominates this effect as compared to the long side. EPU is statistically significant after controlling for macroeconomic variables. Further-more, the paper conducts a battery of time series analysis, which highlights that EPU has a causal relationship with the hedge portfolio in the short run. On the other hand, the hedge portfolio has along-term relationship with EPU, not the other way around. info:eu-repo/semantics/publishedVersion

This article examines the propensity to pay dividends in the U.S banking sector during 1973–2014. Although the propensity to pay dividends has been declining over the 52 years of our sample period, banks are consistently more likely to pay dividends than non-financial firms. Using the coefficients from logit models estimated early in the sample period to forecast the percentage of dividend payers in each subsequent year, we conclude that there has been a decline in the likelihood of paying dividends in the banking sector. However, the decline started from a very high level as compared to that of the non-banking sectors. In addition, the variables taken from the non-financial firm literature do not explain the difference between the actual and expected percentage of dividend payers in the banking sector. We also conduct exploratory analyses with bank-specific variables. Although newly included variables are significantly related to the likelihood of paying dividends, they do not explain the declining propensity to pay dividends in the banking sector.

Some of the constructs in the field of performance management are intuitive or not empirically validated. This study provides a data-driven framework for measuring and improving the performance through synchronized strategies. The ultimate goal was to provide support for increasing business performance. Empirical research materializes in an exploratory case study and a statistical analysis with econometric models. The case study revealed that a company can improve its performance, even in periods of growth, being characterized by consistent investments. The statistical analysis, performed on a restricted sample of companies, confirmed the results that were provided by the case study. The measurement of performance was made by capitalizing on financial and non-financial data precisely to intensify the interest for corporate sustainability. The obtained results, contrary to previous research that showed that economic value added (EVA) is negatively influenced by the increase in invested capital, open up new research perspectives to find out whether, at the industry level, performance appraisal that is based on EVA stimulates the development of a business’s economic capital. The research has a double utility: scientific (by providing an overview of the state of the art in the field of performance management) and practical (by providing a reference model for measuring and monitoring performance).

As a core activity in the tourism sector, hospitality accounts for the largest share of the sector’s revenue. The last few years, prior to the COVID‐19 pandemic, have been years of strong growth both in the number of hotel companies and in the number of available rooms. The hospitality industry has also been betting on diversification as well as on the quality of its services. This activity has a strong impact on the various agents in the sector, thus it makes it essential to measure and analyze the sustainability of these hotels. One of the indicators that proficiently measure short‐term sustainability is the company’s liquidity level, as it demonstrates its ability to meet short‐term financial obligations. This type of indicator is useful since it provides relevant information not only for managers, but also for banks and lenders, and investors. Volatility is a characteristic of hotels which are associated with geographic location, implying changes in the main operating revenue indicators. In this sense, this research aimed to investigate if the ability to reimburse short‐term responsibilities differs according to the geographic location, food and beverage service existence, official stars classification, and hotel size. Portuguese hotels with and without restaurants were analyzed in the 2013–2017 period and the number of available rooms and star rating were included in the database. All the information was obtained on SABI (a database of detailed financial information of Portuguese and Spanish companies) and RNET (the Portuguese Register of Tourist Enterprises). Findings show that the behavior of some hotels concerning short‐term obligations does not differ much considering the location of the hotels. However, the Algarve and the North region have the highest values. In fact, the official star rating proved to have the greatest influence. The size of the hotels, as well as the existence of restaurants negatively influences liquidity. This information is very important for hotel investors. This study can also provide management information that allows more informed decision‐making as well as the definition of corrective measures if necessary. info:eu-repo/semantics/publishedVersion