Int. J. Financial Stud., Volume 8, Issue 3 (September 2020) – 21 articles

We examine stock prices and the number of stocks traded around ex-dividend dates of German stocks with tax-free dividend. Tax-free dividends are temporarily tax-exempt, as they reduce the initial purchasing price of a stock. With our analysis of this particular group of German stocks, we can make clear predictions regarding ex-date prices and analyze the number of stocks traded around ex-dates, doing so without the systematic bias of cum-ex trades over time. For XETRA, our empirical results indicate that ex-date prices decline, on average, by the amount of the dividend. We do not find a significant relationship between a stock’s price-drop ratio and dividend yield. Further, the empirical analysis suggests that there is no significant correlation between an abnormal number of a stock being traded and its dividend yield. These results are most consistent with tax-motivated reasoning. However, our volume analysis reveals no consistency regarding the abnormal number of stocks traded for multilateral trading facilities. Full article

Stock repurchases have become a preferred method of distributing cash to stockholders. However, given the high level of information asymmetry and weak corporate governance as well as poor investor protection in Vietnam, many Vietnamese firms use stock repurchases as a tool to manipulate stock prices in the market. Using event study methodology and Tobit regression models, this study examines the stock price behaviors surrounding the event dates and the impact of earnings management activities prior to the stock repurchases on the completion of repurchase announcements in Vietnam. The results show that earnings management practices prior to stock repurchase programs, the percentage of intended buyback shares, and CEO characteristics have a significant impact on the completion of these repurchase programs. Moreover, most of the windows surrounding the event dates do not have any significant abnormal movement of the stock prices. A plausible explanation is that, due to weak corporate governance and poor investor protection, Vietnamese firms send lots of misleading signals through various corporate activities, especially stock repurchase programs. Thus, these signals have less meaning to investors. Full article

Mortgage banking began to develop in Slovakia after 1998 as an ambitious project, the goal of which was to elevate the lagging development of the real estate market, the development of the financial market and the creation of banks’ long-term resources. Our goal is a comprehensive assessment of the development of Slovak mortgage banking for the past 20 years from the perspectives of the development of banking, the mortgage bond market, the real estate market and selected interactions between individual elements of the mortgage system. The specific aim of the study is to evaluate the substantial links between the basic economic indicators, indicators of housing finance and real estate prices in Slovakia. To evaluate these issues VAR (Vector Autoregression) models, models of panel and linear regression and DEA (Data Envelopment Analysis) models were used. Slovakia has specific indicators of the development of mortgage banking, adequate to its historical and economic development. It was confirmed that the availability of real estate loans had a significant impact on the increase in real estate prices. Real estate prices in Bratislava have different development factors than real estate prices from a nationwide perspective. Low interest rates have an important role in housing financing. The second part of the study is oriented towards an evaluation of the technical efficiency of individual banks. The results of DEA point out that the largest banks in Slovakia were the most efficient in the pre-crisis year 2007. The overall results show that policymakers should react not only to the household indebtedness rate and risks for individual clients, but should also see the risks for banks in possible changes in the real estate market, or the risks of changes in interest rates in the future. Full article

This study explored the option value embedded in a reverse mortgage in Korea through an empirical analysis, using the Black–Scholes option-pricing model. The value of a reverse mortgage is affected by the variation in house prices. However, older homeowners using reverse mortgages are able to choose this option due to the unique characteristics of reverse mortgages, such as non-recourse clauses or being able to redeem the loan. This paper found the following results. First, the call option value is 5.8% of the house price at the age of 60, under the assumption of a KRW three hundred million house value, while the put option value is only 2.0%. Contrary to what it is at sixty years of age, only the call option value will remain when the homeowner reaches the age of 80. Second, this article analyzed the sensitivity of the key variables of real-option analytical models, such as the change of the exercise price, the change of the risk-free rate, volatility, and maturity, on the option value of a reverse mortgage. The sensitivity results of the key variables supported economic rationales for the option pricing model. Full article

This paper examines the performance of a naïve equally weighted buy-and-hold portfolio and optimization-based commodity futures portfolios for various lookback and holding periods using data from January 1986 to December 2018. The application of Monte Carlo simulation-based mean-variance and conditional value-at-risk optimization techniques are used to construct the robust commodity futures portfolios. This paper documents the benefits of applying a sophisticated, robust optimization technique to construct commodity futures portfolios. We find that a 12-month lookback period contains the most useful information in constructing optimization-based portfolios, and a 1-month holding period yields the highest returns among all the holding periods examined in the paper. We also find that an optimized conditional value-at-risk portfolio using a 12-month lookback period outperforms an optimized mean-variance portfolio using the same lookback period. Our findings highlight the advantages of using robust optimization for portfolio formation in the presence of return uncertainty in the commodity futures markets. The results also highlight the practical importance of choosing the appropriate lookback and holding period when using robust optimization in the commodity portfolio formation process. Full article

This study presents empirical evidence about the determinants of long-term government bond yields for 19 economies of the European Monetary Union (EMU) over the period 1995–2018 within a multivariate panel framework. The fixed effects estimators reveal that the relationship between public debt to the GDP ratio and yields is non-linear. We observe a threshold, which is determined to be at the area 90% of the ratio of public debt to GDP. Beyond that, area government borrowing costs increase as the public debt rises. Furthermore, we find evidence that a GDP decline and the downgrades of sovereign ratings increase the costs of government borrowing. In contrast, the operation of independent fiscal institutions helps to reduce government’s debt risk premium. Finally, liquidity in the Euro area plays a significant role on yields determination. The results remain robust when the dynamic instrumental variable fixed effect (FE-2SLS) and dynamic panel least square dummy variable corrected (LSDVC) estimators are employed. Empirical findings suggest important policy implications for the ongoing Covid-19 crisis for the EMU. Full article

The 2008 global financial crisis provides us with a wide range of study fields on cross-asset contagion mechanisms in the US financial markets. After a decade of the so-called subprime crisis, the impact of market news on asset volatilities increased significantly. Consequently, return and volatility spillovers became the most extensive channel for spreading out the news generated in one market to the other ones, which made the financial markets inherit international risk factors as their own local risks. Moreover, as a result of the Chinese economy becoming the main driver of the global economy in the last decade, Chinese markets became more interconnected with developed markets which were followed by a “digital cold war” era via Twitter. In this study, we investigate the relationship between the US stock market, Chinese stock markets, rare earth markets and industrial metals, and mining products via three different models by utilizing VAR–VECH–TARCH models. According to our findings, bilateral spillover exists between US and Chinese stock markets. Cross-market spillovers show that there is a risk transmission channel between the industrial metals, rare earth, and Chinese and US stock markets due to China’s strengthening position in the global economy. Full article

In Kenya, the last few years has seen the performance of companies listed under the commercial and services segment on the Nairobi Securities Exchange (NSE), experience mixed fortunes. The study sought to assess the implications of financial risk on the performance of these companies. The study applied explanatory research design. The target population were the 14 companies listed under this segment of NSE. Secondary panel data contained in published annual reports for the period 2013–2017 was collected. Panel regression model was applied with the random effect model being used based on the Hausman specification test. Findings showed that credit risk had an insignificant positive effect on return on equity (ROE) while liquidity risk had a significantly negative effect on ROE and operational risk had a positive insignificant effect on ROE. The positive coefficients from the data analysis indicated that commercial and service companies at NSE were able to take in more credit to boost performance of these companies however the negative coefficients shows that within the period of study these companies experienced high liquidity problems in that the current liabilities exceeded the current assets. Thus, concluding that these companies were unable to pay all their obligation when they were due. Full article

The objectives of this study are to determine the level of conformity between Current Issued Reports (CIRs) and Integrated Report (IR) elements of the Amman Stocks Exchange (ASE) listed companies, as well as to determine whether the investigated corporate characteristics (size, age, quality assurance (QA), earning per share (EPS), industry type, foreign ownership (FO)) of these companies have any impact on the conformability of CIRs. It is worth mentioning that (QA), and (EPS), have never been examined by looking at its association with corporate disclosures, and IR in particular. Based on adoption of the IR framework and using the method of content analysis, corporate annual reports and other stand-alone reports of 82 companies in 2017 and 2018 within the financial, industrial, and services sectors, were chosen for this study. The findings of the study provide an answer to the research question and show that sectors vary in their levels of conformity. It reveals that the service sector shows the lowest conformability compared to other sectors, whereas the financial firms conform 65%, followed by the industrial sector. It also finds a positive association between CIRs conformability and variables of size, age of company and quality assurance. However, EPS, FO and type of industry were found to have no impact on the conformability of CIRs to the IR framework. This study has contributed to IR research, which, as a field, has previously received very little recognition among scholars in Jordan. Moreover, IR still does not exist in Jordan’s business practices. Full article

The aim of this study is to forecast credit ratings of E.U. banking institutions, as dictated by Credit Rating Agencies (CRAs). To do so, we developed alternative forecasting models that determine the non-disclosed criteria used in rating. We compiled a sample of 112 E.U. banking institutions, including their Fitch assigned ratings for 2017 and the publicly available information from their corresponding financial statements spanning the period 2013 to 2016, that lead to the corresponding ratings. Our assessment is based on identifying the financial variables that are relevant to forecasting the ratings and the rating methodology used. In the empirical section, we employed a vigorous variable selection scheme prior to training both Probit and Support Vector Machines (SVM) models, given that the latter originates from the area of machine learning and is gaining popularity among economists and CRAs. Our results show that the most accurate, in terms of in-sample forecasting, is an SVM model coupled with the nonlinear RBF kernel that identifies correctly 91.07% of the banks’ ratings, using only 8 explanatory variables. Our findings suggest that a forecasting model based solely on publicly available financial information can adhere closely to the official ratings produced by Fitch. This provides evidence that the actual assessment procedures of the Credit Rating Agencies can be fairly accurately proxied by forecasting models based on freely available data and information on undisclosed information is of lower importance. Full article

This case study is based on actual project and consultancy work, balancing real life experience with a review and analysis of empirical and theoretical literature. Tidal stream energy (TSE) is still a nascent technology, but with much better predictability than the classical alternatives of sun and wind. Being still more expensive than other renewable technologies, it is important to find locations in order to initiate a learning process to bring down cost to a competitive level as it was the case for solar and wind technologies. Locations for an initial phase of operation of TSE small islands in the Philippines (and other Asian countries) were found to be most suitable, because expensive and polluting diesel generators can be replaced and a reliable 24 h electricity supply can be established. Different appraisal methods in different scenarios show that under normal circumstances a hybrid combination of TSE, solar energy and battery storage is financially and economically superior to existing fossil energy based power stations as well as to solar energy alone. However, the traditional financial approaches are not always reliable, in spite of superficial mathematical exactness, and the parameters used must be analysed carefully, especially if we deal with innovative technologies with fast changes. In times of global warming we must also include the controversial issue of evaluating damages from greenhouse gases if choosing fossil alternatives. When evaluating and planning renewable technologies, engineering know-how is important, but insufficient. Since financing is a crucial issue for most renewable technologies with high front loaded cost and long amortisation periods, a thorough and trustworthy financial and economic analysis is necessary not only to avoid financial failure later on, but also to attract stakeholders like private investors, banks and government institutions to support a still unknown technology. Full article

This study empirically analyzes the effect of debt origin on investment efficiency. According to previous studies that report that the quality of financial reporting may vary depending on the origin of the debt, the empirical analysis predicted that the effects of the origin of the debt on investment efficiency would be differential. Debt origin was divided into private and public debt. The analysis results of this study are as follows. First, there is a significant negative relationship between the private debt and investment efficiency, while there is a significant positive relationship between public debt and investment efficiency. This means that capital gains under public debt may be more profitable to managers by improving the quality of their accounting information than those under private debt. This is in line with the previous research which found that, when financing with public debt, the earnings management is reduced and accounting transparency is high. This study focuses on the origin of debt as a determinant of investment efficiency and analyzes the level of investment efficiency according to the origin of debt. We examine the sustainability of firms from the perspective of investment efficiency, such as raising capital and selecting optimal investment options. The results of this study suggest that the level of incentives and investment efficiency of managers may be differentiated depending on the origin of the debt. Full article

Corporate finance research focuses on C corps (CCs) neglecting pass-throughs (PTs). We answer this neglect by examining PT outputs for the categories of debt choice, valuation, and leverage gain. In the process, we expand on the nongrowth PT research and supplement the recent CC research on the same outputs. Before the Tax Cuts and Jobs Act (TCJA) became effective in January 2018, PTs had an after-tax valuation advantage over CCs. Under TCJA, we demonstrate this advantage has been reverse. This suggests that, ceteris paribus, a typical PT can now find it advantageous to switch to the CC ownership form. More importantly, we show that nongrowth firm values are comparable to growth firm values unless we assume a rise in growth consistent with projections under TCJA where tax rates are lower. We demonstrate this projected growth increase is the key to make businesses more profitable. Additionally, we show PTs achieve optimal debt-to-firm value ratios (ODVs) well below those for CCs; PTs generally attain slightly higher quality credit ratings at their ODVs compared to CCs; and, PTs have lower leverage gains outputs (in the form of the maximum gain to leverage and the percentage increase in unlevered firm value) compared to CCs. Full article

This study sought to investigate the impact of AI on digital financial inclusion. Digital financial inclusion is becoming central in the debate on how to ensure that people who are at the lower levels of the pyramid become financially active. Fintech companies are using AI and its various applications to ensure that the goal of digital financial inclusion is realized that is to ensure that low-income earners, the poor, women, youths, small businesses participate in the mainstream financial market. This study used conceptual and documentary analysis of peer-reviewed journals, reports and other authoritative documents on AI and digital financial inclusion to assess the impact of AI on digital financial inclusion. The present study discovered that AI has a strong influence on digital financial inclusion in areas related to risk detection, measurement and management, addressing the problem of information asymmetry, availing customer support and helpdesk through chatbots and fraud detection and cybersecurity. Therefore, it is recommended that financial institutions and non-financial institutions and governments across the world adopt and scale up the use of AI tools and applications as they present benefits in the quest to ensure that the vulnerable groups of people who are not financially active do participate in the formal financial market with minimum challenges and maximum benefits. Full article

Traditionally, public procurement has been associated with the measurement of achieving savings. However, recent research shows that the economic impact of public procurement is not limited only to savings, but by measuring the impact of four capitals—natural, human, social, and economic—on sustainable well-being over time. Ukraine is a country with a very low gross domestic product (GDP) per capita, which exacerbates the problem of the impact of public procurement results on the population’s welfare. Ukrainian public procurement legislation allows customers to apply non-price criteria (the share of non-price criteria cannot be more than 70%), which, together, are taken into account in the formula of the quoted price. The studies show that the effect of the use of non-price criteria depends on the relevance of the method of the evaluation of non-price criteria. The most important non-price criteria for Ukrainian customers by product categories and the methods of their evaluation are analyzed according to the Bi.prozorro.org analytics module. Therefore, it is concluded that the quoted price method, which is used in Ukrainian practice, is not relevant in comparison with the method used in the EU. A survey of the government buyers on the practice of applying non-price criteria was conducted, and the areas of their use were identified. Full article

Information about the possibilities of changes in national and international macroeconomic variables affects the expectations and behavior of individuals and firms more quickly than real changes in those macroeconomic variables. In this research, we investigate the impacts of international information (news) on the financial markets in Japan. We examine how news about the results of the Brexit referendum (BR) and the United States presidential election (USE) affected foreign exchange rates and stock market indexes. This research reveals evidence of statistically significant changes in exchange rates and stock market indexes within two weeks after the BR and USE, statistically significant changes in the exchange rate variance within the first week after the BR, and changes in the causality relationship between the variables after each event. Full article

This study aims to examine the effect of the bank-specific and macroeconomic determinants of profitability for the banking sector of Pakistan. To incorporate the issues of endogeneity, unobserved heterogeneity, and profit persistence, we apply a generalised method of moments (GMM) technique under the Arellano–Bond framework to a panel of Pakistani banks that covers the period 2003–2017. The results of a dynamic panel data approach reveal that capital adequacy accelerates the profitability of the banking sector in Pakistan. Capital adequacy helps the financial system to absorb any negative shock by reducing the number of bank failures and losses. Conversely, our empirical investigation reveals that the liquidity ratio, business mix indicators, interest rates, and industrial production deteriorates the bank profitability. Liquidity risks enhance the probability of default risks and transmit into the unpaid loans and hence the lower return. Our empirical evidence further reveals that Pakistani banks are not getting any benefit of the economies of scale in terms of financial performance. Full article

Sustainable and responsible investing (SRI) is a strategy that seeks to combine both financial return and social good. The need to create and preserve SRI represents a key argument in investment decision-making, which leads other firms and investors to make strategic decisions beyond financial logic, based on environmental, social, and governance (ESG) factors. Within this framework, this paper aims to further clarify the understanding of potentially profitable strategies for firms during a global crisis such as a pandemic. Both primary and secondary data were gathered, and descriptive analyses were conducted. In Spain, several IBEX-35 companies announced donations amid the COVID-19 crisis. First, companies were classified into two groups based on donations made. For this, we searched for ESG online news. Then, profitability records amongst companies were identified and compared. In the trading session after the announcements, we found 12 of the 35 companies that made donations had a higher performance index of more than 2 and 3 points over the companies that did not make donations. With a weekly perspective, the difference was 91 and 60 basis points, respectively. These results suggest that in times of upheaval, investors base their strategy on ESG factors, contributing to the emerging literature on individual motives of SRI. Second, by conducting a survey and collecting data from 575 Spanish citizens, we conclude that after this crisis, people’s perceptions towards corporate social responsibility (CSR) will change, affecting consumption preferences in those companies that exhibited socially irresponsible or unsupportive behaviour. Hence, the reputation of firms, their social image, and social trust will play an important role in the near future. Full article

Vision 2030 of the Kingdom of Saudi Arabia (KSA) requires numerous national and multinational organizations to re-engineer themselves to achieve the required targets for the upturn of the Saudi economy. In this respect, the quality of indigenous goods and services has been the biggest challenge to satisfy consumers of Saudi businesses. The banking and finance sector, specifically, has a great deal of responsibility to put in place a strong financial system that is capable of attracting capital from both local and foreign investors. SERVQUAL, with the five conventional dimensions—tangibility, reliability, responsiveness, assurance and empathy—offers a great deal of flexibility in modifying the model to the specific requirements of a service in carrying out gap analysis. In this context, we have applied SERVQUAL by adding two new dimensions—functional and technical—to the conventional five dimensions. We applied SERVQUAL using a “performance-only approach” to identify quality gaps present in the services of national and multinational banks. Our analysis shows that gaps exist in the service quality—both in national and multinational banking systems. We therefore present weighted gap scores to assist service managers in setting up priorities to improve the quality of their services. This study suggests that there is much to be done to improve retail banking quality and gain customers’ confidence, both from within and outside the KSA. Full article

Marketing communication is a concise part of modern museum management. Museums operate in a competitive environment; therefore, it is important to pay sustained attention to every component of a given museum’s marketing communication. Changes, international trends, and visitor preferences have an influence on marketing communication. Museum management must devote expert deliberation towards determining which components of their marketing communication are significant for museum visitors. Moreover, the effectiveness of the use of expenses plays an important role in museum management; it is also essential to combine effectively the individual components of marketing communication. The present research aims to find a correlation between the components of museum marketing communication, which is not being addressed in detail in the contemporary research. The aim of the research is therefore to determine the dependence amongst elements of the marketing communication of museums on questioning the visitors. The aim was achieved by implementing the modern audit approach and empirical research into marketing communication: the Paper Aided Personal Interview (PAPI) method with a Likert scale, a reliability check with Cronbach’s alpha, and dependency determination with Pearson’s correlation. All results were investigated through the use of a questionnaire on the international EU 27 sample of museum visitors. These conclusions allow museum management to build their marketing communication on the principles of Economy, Efficiency, and Effectiveness (the 3E principles). Full article

We examined the determinants of the U.S. consumer sentiment by applying linear and nonlinear models. The data are monthly from 2009 to 2019, covering a large set of financial and nonfinancial variables related to the stock market, personal income, confidence, education, environment, sustainability, and innovation freedom. We show that more than 8.3% of the total of eigenvalues deviate from the Random Matrix Theory (RMT) and might contain pertinent information. Results from linear models show that variables related to the stock market, confidence, personal income, and unemployment explain the U.S. consumer sentiment. To capture nonlinearity, we applied the switching regime model and showed a switch towards a more positive sentiment regarding energy efficiency, unemployment rate, student loan, sustainability, and business confidence. We additionally applied the Gradient Descent Algorithm to compare the errors obtained in linear and nonlinear models, and the results imply a better model with a high predictive power. Full article