Issue #3 (Volume 17 2020)

The emerging interest in Bitcoin futures market has led to questions on its trading form and contribution to risk minimization. These questions are important for market participants, including hedgers and speculators. This paper addresses the possible trading motive in Bitcoin futures market in being speculation or hedging. The author first tests a model relating Bitcoin futures returns with trading volume and conditional volatility, estimated with a GJR-GARCH specification, on a full sample of daily futures prices. A robustness check is then conducted by investigating the hedging effectiveness of Bitcoin futures and the speculation-hedging ratios on individual Bitcoin futures contracts. The estimation results on Bitcoin futures contracts, spanning from December 2017 to February 2020, show a significant positive relationship between futures returns and lagged volume. The speculation-hedging measures used for Bitcoin futures contracts maturing in March, June, September, and December reveal an increasing demand for speculation. Also, the Bitcoin spot’s full-hedge and OLS-hedge strategies with Bitcoin futures provide no gain over a no-hedge strategy. The results reveal strong evidence that traders in the Bitcoin futures market are motivated by speculation rather than hedging. This further puts in evidence the existence of asymmetric information within informed traders in Bitcoin futures market, and therefore market participants would not insure their positions against Bitcoin price movements.

Due to the ongoing process of globalization, enterprises need to provide financial statements in accordance with international practices, in which information about assets and liabilities should be presented at fair values rather than at original prices. Fair value is supported by the International Accounting Standards Board and the Financial Accounting Standards Board. The purpose of this study is to evaluate the adoption of fair value accounting in Vietnam and the impact of factors on the adoption of fair value. The paper used the analytical framework of previous studies to identify factors affecting the adoption of fair value. Additionally, this study applied quantitative research methods and collected data by sending questionnaires to 127 accountants and directors of listed companies. Particularly, binary logistic regression was conducted to investigate the extent of the impact of each factor on the adoption of fair value. The results have shown that human resources have the strongest and positive impact on the adoption of fair value, and this is followed by the benefits of fair value. Difficulties and markets negatively affect the use of fair value. Furthermore, the control variables that affect the use of fair value are sector, size and length of operation with different levels of impact. The accuracy rate of the overall predictive model is 85.8%. The findings provide guidance of the application of fair value accounting in companies and give recommendations to policy makers in establishing a legal accounting framework in Vietnam.

Czech family businesses are currently experiencing their first changeover of generations in history. The first generation (founders or successors), two or more generations collectively operate in management and administrative authorities. This article aims to compare and evaluate preference for use of debt or equity financing in family businesses with the differing involvement of generations and the diversity of its allocation for the specific need of the company’s growth. This empirical study is performed based on a qualitative analysis of 245 family businesses. Hypotheses were confirmed using the Pearson correlation coefficient. This study confirms the dependence of equity and debt financing on the number of generations in management. This brings differing perspectives, opinions, and practices for financial management in the sense of a preference for debt or equity financing. The need for debt arises at the moment of compensating the transfer of ownership between generations. The analysis results indicate that family businesses managed by one generation prefer equity financing, companies managed by first and second generations prefer debt financing, and companies managed by second and third generations prefer equity financing.

Acknowledgment
The result was created in solving the project TA ČR ETA 2 (STA02018TL020) “Family businesses: Value drivers and value determination in the process of succession”, TL02000434. We are grateful also to representatives of enterprises who were willing to participate in this research.

Dividend policy, as part of corporate governance, is largely dependent on the institutional environment in which companies operate. The study aims to determine factors affecting dividend policy in the conditions of the Ukrainian underdeveloped stock market, legal insecurity of minority shareholders, high cost and concentration of capital. For this purpose, hypotheses about the impact of a company’s financial state, size, business risk, and ownership structure on dividend payments were tested using a sample of 58 Ukrainian non-financial public joint-stock companies and applying Interactive tree classification techniques (C&RT). The resulting classification model for predicting dividend decisions correctly classifies 92.86% of companies that paid dividends and 93.3% of companies that did not. The findings, based on the classification tree and importance scale, prove the hypothesis that companies in which individuals and institutional investors have a controlling interest are more likely to pay dividends than other non-state companies. The financial indicators accurately classify only those firms that do not pay dividends, and business risk does not affect classification accuracy at all. The paper substantiates the ways of using the study findings for economic regulation, protection of minority shareholders’ rights, and proliferation of modern corporate governance practices.

Bi-Directional Grid Constrained (BGC) trading strategies have never been studied academically until now, are relatively new in the world of financial markets and have the ability to out-perform many other trading algorithms in the short term but will almost surely ruin an investment account in the long term. Whilst the Gambler’s Ruin Problem (GRP) is based on martingales and the established probability theory proves that the GRP is a doomed strategy, this research details how the semimartingale framework is required to solve the grid trading problem (GTP), i.e. a form of BGC financial markets strategies, and how it can deliver greater return on investment (ROI) for the same level of risk. A novel theorem of GTP is derived, proving that grid trading, whilst still subject to the risk of ruin, has the ability to generate significantly more profitable returns in the short term. This is also supported by extensive simulation and distributional analysis. These results not only can be studied within mathematics and statistics in their own right, but also have applications into finance such as multivariate dynamic hedging, investment funds, trading, portfolio risk optimization and algorithmic loss recovery. In today’s uncertain and volatile times, investment returns are between 2%-5% per annum, barely keeping up with inflation, putting people’s retirement at risk. BGC and GTP are thus a rich source of innovation potential for improved trading and investing.

Acknowledgement(s)
Aldo Taranto was supported by an Australian Government Research Training Program (RTP) Scholarship. The authors would like to thank A/Prof. Ravinesh C. Deo and A/Prof. Ron Addie of the University of Southern Queensland for their invaluable advice on refining this paper.

The article explores the correlation strength of the ten most important cryptocurrencies, emphasizing the examination of differences during the periods of rising and falling prices. The daily and weekly returns of selected cryptocurrencies are taken as the basis for calculating and determining the correlation strength using the Pearson correlation coefficient. The survey covers the period from the beginning of 2017 to Bitcoin’s last local bottom in mid-March 2020. Research findings are as follows: 1) the most important cryptocurrencies are mostly moderately positively correlated with each other over time; 2) correlation strength decreases slightly during the bull period, but mostly remain in the range of moderate correlation; 3) correlation strength increases significantly during the bear period, with most cryptocurrencies strongly correlated with each other. The results do not change significantly if the daily or weekly cryptocurrency returns are used as the basis. A strong correlation in the period of falling prices prevents the effective diversification of the cryptocurrency portfolio, which must be considered when investing funds in the cryptocurrency market.

Given Asian market recognition at the forefront of the investment domain, the research examines volatility spillover and asymmetric transmission between emerging and frontier stock markets of Asia. Stock returns of two frontier and nine emerging markets, during the data period spanning from August 2000 to March 2020, were analyzed using multivariate asymmetric GARCH-BEKK model around the global financial crisis (GFC). The study results suggest that the structure of cross-markets shocks and volatility spillover between emerging markets are higher during post-GFC. Therefore, this diminishes the possibility of portfolio diversification and investment opportunities to the investors in most of the Asian emerging markets. In the case of Asian frontier markets, most of the volatility generates due to its past shocks and volatility traverse from Asian emerging markets are considerably less. Hence, asset allocations prospects exist in the Asian frontier stock markets. Nevertheless, safe investment strategies need to design to reap diversification benefits from these markets, particularly during financial turmoil and market distress in the future.

Money market funds (MMFs) are generally considered safe investment vehicles, but the 2008 global financial crisis showed their vulnerability during market disruptions resulting in increased regulatory oversight across developed markets to protect investors. This paper examines the effect of MMF accounting regulation on investors in an emerging market context. It hypothesizes that the continued use of amortized cost methods to account for MMFs’ Net Asset Value (NAV) during market disruptions can result in unfair treatment of investors. The Egyptian money market provided a unique laboratory to test this hypothesis over a prominent economic crisis that combined high levels of interest rate volatility with a redemption-only structure for MMFs. A model that measures the discrepancies between the amortized and floating market NAVs per certificate for various money market portfolios (MMPs) simulating MMFs of different durations is tested using the Egyptian data. A sharp rise in interest rates is found to lead to significant discrepancies between the amortized NAV per certificate relative to their floating value. Serial investor redemptions of the certificates compound the discrepancies, but only certificate holders remaining in the funds bear the accumulated losses, which are augmented for portfolios with higher durations. The results suggest that emerging market regulators consider introducing the rules that switch to floating NAV calculations for MMFs during such periods to promote equality across all investors.

The government bond (GB) has become the most attractive investment portfolio option, even though many macroeconomic factors affect the bond yield. This paper aims to investigate the determining factor of local currency government bond yield by considering the inflation rate, credit default swap, stock market index, exchange rate, and volatility index. This study used 240 data panel from the Bloomberg stock market in the form of data panel covering Southeast developing countries, namely Indonesia, Thailand, Malaysia, and the Philippines, for five years or sixty months from January 2015 to December 2019. Data analysis used recursive models and multivariate regression techniques using EViews software. The random effect model results revealed that change in the foreign exchange rate and volatility indexes affected, partially and simultaneously, the changes in the stock market index. The result also showed that changes in the stock market index, inflation rate, and credit default swap affected, partially and simultaneously, government bond yield changes. These results suggest that the government bond yield could be managed by controlling volatility index, foreign exchange rate, stock market index, inflation rates, and credit default swaps. This finding could provide an insight into the policymaker and fiscal authority on managing the risk of government bonds under control during high volatility or even making it reasonably lower. This result could contribute to the current research in the field of financial management.

Acknowledgment
It is the author’s pleasure to thank Muhammad Aulia SE MSc CSA® from the Ministry of Finance of Republic Indonesia, for his invaluable contribution to encourage this study and also to share the data required for this paper. He also delivers essential insights into improving the quality of this work. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The current paper aims to investigate the effect of the capital structure on the profitability of a panel of eighteen Iraqi listed banks from 2009 to 2018. Furthermore, the unbalanced panel data approach (fixed effect and random effect) is utilized to explore the influence of capital structure on banks’ profitability. This study’s findings point out that the banks’ performance in terms of return on assets has a significant positive association with equity to assets ratio, liabilities to assets ratio, and bank size. On the other hand, long-term debt to assets ratio, short-term debt to assets ratio, and total debt to assets ratio showed a significant negative effect on banks’ performance. This study highlights new facts for an enhanced understanding of the capital structure and its association with banks’ performance in developing economies like Iraq. This study is considered one of the earliest studies of its types by determining the Iraqi banks’ optimal structure and examining capital structure’s impact on their performance. Nevertheless, the study contributes significantly to theoretical literature, policymakers, and industry so that conventional Iraqi banks can boost their performance.

The current empirical study attempts to analyze the impact of COVID-19 on the performance of the Indian stock market concerning two composite indices (BSE 500 and BSE Sensex) and eight sectoral indices of Bombay Stock Exchange (BSE) (Auto, Bankex, Consumer Durables, Capital Goods, Fast Moving Consumer Goods, Health Care, Information Technology, and Realty) of India, and compare the composite indices of India with three global indexes S&P 500, Nikkei 225, and FTSE 100. The daily data from January 2019 to May 2020 have been considered in this study. GLS regression has been applied to assess the impact of COVID-19 on the multiple measures of volatility, namely standard deviation, skewness, and kurtosis of all indices. All indices’ key findings show lower mean daily return than specific, negative returns in the crisis period compared to the pre-crisis period. The standard deviation of all the indices has gone up, the skewness has become negative, and the kurtosis values are exceptionally large. The relation between indices has increased during the crisis period. The Indian stock market depicts roughly the same standard deviation as the global markets but has higher negative skewness and higher positive kurtosis of returns, making the market seem more volatile.

The article refers to the theoretical framework of the possibility of using real estate derivatives in the Polish financial market. Although the Polish property market is well developed, and Poland is the leader in the Central and Eastern Europe region, there is a gap in the use of financial instruments concerning the property market. Given the lack of a property derivatives market in Poland, conditions and opportunities for this market development are presented. The experience of the United Kingdom and the United States in this field shows that one of the most important aspects is stable and a well-functioning financial market. Therefore, the macroeconomic data and the data of the Polish financial market are examined.
The analysis carried out indicates sufficient conditions and opportunities for the development of real estate derivatives in Poland. The macroeconomic data and data from the capital market have shown the economic environment’s stability and balance. One of the limitations is the existence of a clear and respectable index used as an underlying asset in derivatives on the Polish market. Only WIG real estate index is listed on the Polish Exchange. Although there are sufficient conditions for introducing the real estate derivatives in Poland, the success of all financial innovations depends on the willingness of potential users to use them.

Ukraine’s European integration requires the involvement of seaports in the international TEN-T network, so it is extremely important to create favorable investment conditions to develop port infrastructure. This study aims to make a comprehensive assessment of the seaports’ investment attractiveness to use it for increasing the efficiency of attracting investment in the development of Ukrainian seaports, which are part of the European transport network. The study was conducted using the Saati method and the method of calculating the integrated indicator of seaports’ investment attractiveness. The integrated indicator includes assessing indicators of business activity in the region and consolidated indicators of financial and property status, logistical attractiveness, and prospects for port development. According to the results of calculations, the seaports of Ukraine were divided into three groups. The ports of Yuzhne, Odesa, Illichivsk, and Mykolaiv have a high level of investment attractiveness. The ratio of investment attractiveness ranges from 3 to 2.6. The ports of Izmail, Mariupol, Oktyabrsk, and Kherson have an average level (ratio from 2.2 to 1), and other ports have a low investment attractiveness (coefficient from 0.9 to 0.7).

There is an academic discussion about investment efficiency, regarding its determinants and effects. Corporate Governance (CG) and Audit Quality (AQ) are determinants of investment efficiency The main objective of the article is to investigate the effect of CG and AQ on investment efficiency, this objective is divided into sub-objectives: to investigate the direct effect of CG on AQ, AQ on investment efficiency, and CG on investment efficiency. Moreover, the indirect effect of CG on investment efficiency through AQ as a mediator variable. This paper focuses on non-financial listed firms in the Egyptian Stock Exchange (EGX), especially firms recorded in EGX 100 for four years’ period (2013–2018), for 103 firms and 412 completed observations. The researcher uses Structural Equation Modeling (SEM) through SmartPLS software. The paper shows evidence that management that has good CG mechanisms obtains a suitable atmosphere to prepare transparent financial statements, which helps enhance the auditor’s role and improve AQ. Improving AQ lowering IA, which increases the trust of investors in management decisions, this leads to reduce pressure on management and improve efficiency of investment decisions. Having good CG mechanisms provides management with a good atmosphere to make right investment decisions, and having good CG mechanisms increases AQ, which helps management to have a good environment to make investment decisions with higher efficiency, or in other words, there is a significant and positive effect of integration between CG and AQ on investment efficiency.

Portfolio allocation strategies, and notably the mean-variance approach, use past returns to assign optimal weights. Even though both past and expected returns should come from the same distribution, a formal test of whether this holds in practice has not been conducted yet. Thus, the study examines if the daily returns of 242 companies with continuous trading in the S&P index come from the same distribution using the Kolmogorov-Smirnov, Cramér-Von Mises, and Wilcoxon rank-sum tests. The tests suggest that generally stock returns do come from the same distribution. However, the hypothesis is rejected during the Great Recession, with the rejection rate increasing as the forecast horizon increased. The rejection rate, using an array of macroeconomic variables, is found to record high levels of persistence. Although macroeconomic variables were not found to be statistically significant determinants of the rejection rate, market distress has a small but significant effect.

The difference in the GDP levels is crucial for the macroeconomic forecasting to develop adequate and supportive fiscal and monetary policies. Most mismeasurements under current geoeconomics challenges can be explained by the difficulty in predicting recessions and the overestimation of the economy’s potential capacity. The research aims to consider the GDP gap’s effectiveness for the possible forecasting of the monetary policy, particularly the central bank’s interest rate. The study uses quantitative methods, particularly VAR modeling. The VAR model is chosen as a proven useful tool for describing the dynamic behavior of economic time series and forecasting. The data sample is chosen as Eurozone, the United States, and Japan. The similarity is detected on output gaps implementation in the considered states; however, the variety in the responses to the financial crisis is revealed. This difference is due to the different sensitivity of economies on the impact of monetary instruments. In particular, the Japanese economy has a relatively low level of sensitivity to changes in monetary instruments. In terms of the reactions of central banks to the current economic crisis caused by COVID-19, then due to the global lockdown and the incredible decline in economic activity, almost all countries are in a situation of negative GDP gap according the paper’s approach. However, the measures to mitigate it will vary in different states.

Acknowledgment
The paper is done in the framework of scientific faculty research 16КF040-04 “Steady-state security assessment: a new framework for analysis” (2016–2021), Taras Shevchenko National University of Kyiv (Ukraine).

This study examines the predictive power of implied volatility smirk to forecast foreign exchange (FX) return. The volatility smirk contains critical information, especially when the market experiences negative news. The Australian dollar, Canadian dollar, Swiss franc, Euro, and British pound options traded in the opening, midday and closing periods of the trading day are selected to estimate the currency smirk. Research results reveal that the currency smirk outperforms in forecasting FX returns. In addition, the steeper slope in the middle of the trading day suggests that the predictive power of currency smirk in the midday period is higher compared to the opening and closing periods. However, currency smirks’ predictability lasts for a short period, as the FX market is highly adept at incorporating the vital information embedded in the currency smirk. These findings imply that the currency smirk is distinctive for forecasting very short-term FX fluctuations, and the day- or overnight FX traders can use its uniqueness to profit from quick price swings in the 24-hour global FX market.

Most Australian domestic investors rely on fund managers, and in India, this is not the same as they are primarily in direct investment rather than indirect. The study attempts to investigate the causal relationship between the returns of the standard indices, namely BSE500 and ASX300, and customized indices, MIMF and MAMF, for both India and Australia. The study uses econometric tools and techniques such as unit root test, vector error correction model, Wald test, Johansen co-integration, and model efficacy assumptions on the historical closing NAV of the selected mutual fund schemes for the period from April 2008 to March 2018. The econometric investigation using Johansen’s Co-Integration test confirmed the co-integration between BSE500, ASX300 and customized indices. Empirical evidence suggests that the Australian customized MAMF index is not Granger-caused by the Indian customized index MIMF, and therefore the MIMF index value cannot be used to predict the future rate of index MAMF returns, and vice versa.

This study investigates the direct and indirect effects of financial capability, financial advice, financial anxiety, and the use of an electronic payment system (EPS) on financial satisfaction. In the current era of digitalization and financial innovations, it seems quite unlikely that an individual remains unaffected by its use. The research was conducted in northern India on individual level using a partial least square structural equation modeling statistical technique to analyze responses collected from a close-ended questionnaire using a 5-point Likert scale. The results show that financial capability, financial advice, financial anxiety, and EPS usage have a direct positive effect on an individual’s financial satisfaction. EPS usage plays a significant mediating role, as all the financial constructs depict a positive effect on financial satisfaction via EPS use. These findings contribute to the literature by offering an understanding of the determinants of financial satisfaction in the context of a low-income developing country, as well as the vital role of using EPS in an individual’s financial satisfaction in today’s digitally driven era. The results of this study could be a useful factor for policymakers and digital service providers for implementation and control.

Acknowledgement
“This paper was supported by Internal Grant Agency of FaME TBU No. IGA/FaME/2019/002”

The mean-variance framework coupled with the Sharpe ratio identifies optimal portfolios under the passive investment style. Optimal portfolio identification under active investment approaches, where performance is measured relative to a benchmark, is less well-known. Active portfolios subject to tracking error (TE) constraints lie on distorted elliptical frontiers in return/risk space. Identifying optimal active portfolios, however defined, have only recently begun to be explored. The Ω – ratio considers both down and upside portfolio potential. Recent work has established a technique to determine optimal Ω – ratio portfolios under the passive investment approach. The authors apply the identification of optimal Ω – ratio portfolios to the active arena (i.e., to portfolios constrained by a TE) and find that while passive managers should always invest in maximum Ω – ratio portfolios, active managers should first establish market conditions (which determine the sign of the main axis slope of the constant TE frontier). Maximum Sharpe ratio portfolios should be engaged when this slope is > 0 and maximum Ω – ratios when < 0.

Traditional finance explains all human activity on the ground of rationality and suggests all decisions are rational because all current information is reflected in the prices of goods. Unfortunately, the development of information technology and a growth of demand for new, attractive possibilities of investment caused the process of searching new, unique signals supporting investment decisions. Such a situation is similar to risk-taking, so it must elicit the emotional reactions of individual traders.
The paper aims to verify the question that the market risk may be the determinant of traders’ emotions, and if volatility is a useful tool during the investment process as the measure of traders’ optimism, similarly to Majewski’s work (2019). Likewise, various econometric types of models of estimation of the risk parameter were used in the research: classical linear using OLS, general linear using FGLS, and GARCH(p, q) models using maximum likelihood method. Hypotheses were verified using the data collected from the most popular world stock exchanges: New York, Frankfurt, Tokyo, and London. Data concerned stock exchange indexes such as SP500, DAX, Nikkei, and UK100.

The research focuses on finding a superior forecasting technique to predict stock movement and behavior in the Shanghai Stock Exchange. The author’s interest is in stock market activities during high volatility, specifically 13 years from 2002 to 2015. This volatile period, fueled by events such as the dot-com bubble, SARS outbreak, political leadership transitions, and the global financial crisis, is of interest. The study aims to analyze changes in stock prices during an unstable period. The author used advanced computer sciences, Machine Learning through information processing and training, and the traditional statistical approach, the Multiple Linear Regression Model, with the least square method. Both techniques are accurate predictors measured by Absolute Percent Error with a range of 1.50% to 1.65%, using a data file containing 3,283 observations generated to record the daily close prices of individual Chinese companies. The t-test paired difference experiment shows the superiority of Neural Network in the finance sector and potentially not in other sectors. The Multiple Linear Regression Model performs equivalent to the Neural Network in other sectors.

This study begins with the assumption that the existence of abnormal circumstances will force investors to take measures to protect their investments in the capital market. Recently, the stock index in the Indonesian market has been declining and continued to fall until the end of April 2020 due to the impact of the Covid-19 pandemic. In terms of efficient market theory, prospect theory and signaling theory, this study aims to analyze the relationship between risk and return in the Indonesian capital market during the Covid-19 pandemic as a manifestation of investor behavior. To test hypotheses, the correlation test, the independent sample t-test and the Cohen test for 629 public firms with 52,836 observable data are used. The findings show that for financial sectors and non-financial sectors, the fourth period differs from previous periods when the relationship between systematic risk and stock returns is positive, although only non-financial sectors have a significant effect. The results show that efficient market theory, prospect theory and signaling theory are consistent with the phenomena around the Covid-19 pandemic in Indonesia. In addition, Cohen’s test results suggest that government policies in the face of the pandemic are successful in stimulating the market.

The Gulf Cooperation Council (GCC) countries of late have made considerable attempts to achieve financial consolidation. However, this was limited to cuts in government expenditures. While scholars suggest the need for overall fiscal policy adjustments, countries should pay particular attention to efficient revenue generation and public debt management. In this paper, an attempt has been made to examine public finance of the GCC countries. The study has taken into account four significant components of public finance: public revenue, inflation, government expenditure and public debt. The co-integration rank test using the vector auto-regression method is employed to determine whether the chosen variables play any influential role in the GDP of the GCC economies. The results suggest that the effect of the consumer price inflation, total government revenue, revenue (percent of non-oil), and total government gross debt have a strong influence on the GDP of these economies. Thus, this means that the countries in the GCC region should focus on inflation, revenue, and public debt to have robust, viable and comprehensive development.

Since countries differ in their traditions, cultures or different tax systems, investment allocation can be a difficult task for some investors. Effective tax rates present indicators of the real corporate tax burden and consider the impact of all legislation elements. This paper deals with the effective taxation of selected intangible and tangible assets. The analysis will be processed by calculating average and marginal tax rates (EATR and EMTR) according to the methodology of the Centre for European Economic Research (ZEW). Then, the relationship between these two tax rates was calculated, and the relationship was identified that evaluates the most optimal criteria between location, amount and source of investment financing. The analyzed period is the year 2020. The analysis is a quantification of the amount of the tax rates for a hypothetical investment. The next step in the analysis is a calculation of the tax shield, which expresses tax saving of investment and the economic income of project, including taxation, and means financial benefit for an investor. The results have shown that Ukraine is a better choice for the investor, as this country reached lower values of effective tax rates for all other types of assets, except land, than Slovakia. In the case of own funds financing, there is a difference between 10.7% and 11.6%, and in the case of debt financing, the difference ranged from 10.8% to 11.7%. The exception was land, the rates for which were higher than in Slovakia by 0.70%. This paper has confirmed the research hypothesis that Ukraine is a more tax-attractive country than Slovakia.

Acknowledgment
This research was supported by VEGA project No. 1/0430/19 “Investment decision-making of investors in the context of effective corporate taxation”.

Stock split should not have any impact on share prices, and there should be no value creation. The purpose of this study is to find any impact of stock splits announced in India between 1999 and 2019 on stock returns. The study aims to find differences in the impact of stock splits on stock returns with differences in stock split ratios. To examine the impact, the study includes 224 splits and adopts the standard event study methodology to find results. The presence of an abnormal return around split announcement day is the main factor, which determines the impact of stock split on the stocks. Average Abnormal Returns and Cumulative Average Abnormal Returns on percentage basis, z-test and p-value are used to statistically analyze the impact on stock prices around the announcement day of splits. These tests are used across different window periods (e.g., 20 days, 10 days and 5 days) around the event day (announcement day) to check if the impact of the event continues or decreases over time. The results point to a significant positive impact of stock splits on the returns of stock around the day the split was announced. The results also show that the impact is stronger for stock splits with ratios 10:1 (2.72 percent) and 10:2 (2.14 percent). It can be suggested that 10:1 and 10:2 are the most popular split ratios that receive maximum ongoing response to splits in the announcement window.

The individual and implicit nature of the trade credit cost can provoke its increase, and, as a result, violate payment discipline and negative influence on the business price.
This research is dedicated to improving the sale terms definition to minimize the cost of trade credit.
The methods for determining the cost of trade credit of a particular company are proposed to apply, considering the results of the comparative analysis of other enterprises from the same industry.
Based on the example of Ukrainian food processing enterprises, it was revealed that 66% of them for the period 2013–2018 had an aggressive policy, and in 44% of the cases, it was connected with the growing role of trade credit. Minimum (23 days) and average (79 days) days payable outstanding, defined in the industry, were equated, respectively, to discount period and payment delay. Considering and comparing the cost of trade credit with alternative financial resources, the marginal level of the discount was determined. Considering the rate of short-term credit, according to the failed discount method, this level is 2.7% for 2018; toward the effective annual rate method – 2.48%. In the case of the overdraft, the marginal discount is 2.9% and 2.66%, respectively.
When the actual discount is equal or below this level, the buyer attracts trade credit instead of bank loans. Discount higher than marginal, longer discount period, and cheap alternative financing sources provide early payments, positive financial results, and make trade credit free of charge.

Although some studies recently address the association between COVID-19 sentiment and returns, volatility, or stock trading volume, no one conducts an analysis to measure the impact of investor rationality or irrationality on the influence on countries and sectors’ returns.
This work creates a text media sentiment and combines its influence with the outbreak cases on the stock market sector returns of the US, Europe, and their main countries most affected by the pandemic.
This allows us to perceive the ranking impact of rationality or irrationality on country and sector stock returns. This work applies a random-effects robust panel estimation, with an M-estimator. This paper concludes that US returns are more sensitive to sentiment, and thus more prone to irrational factors than confirmed cases compared to Europe and that country factors influence the returns differently. In Italy and Spain as the most punished countries in Europe apart from the UK, present sector indexes return more reactive to verified cases, or rationality, namely, tourism, real estate, and the automobile (this last one in Italy).
The importance of this work resides in providing a new in-depth analysis of irrational behavioral metrics among countries, which allows for comparison. Moreover, it allows observing which sectors’ and which countries’ asset returns are most sensitive to rational or irrational expressions of events, allowing for arbitraging, financial planning for investors, decision-makers, and academia on an in and out of pandemic context.

Acknowledgment
This work is funded by National Funds through the FCT – Foundation for Science and Technology, I.P., within the scope of the project Refª UIDB/05583/2020. Furthermore, we would like to thank the Research Centre in Digital Services (CISeD) and the Polytechnic Institute of Viseu for their support.

Liquid liabilities are required to develop key sectors that drive the Nigerian economy by ensuring that loans are available for investment purposes. However, controversies concerning the effectiveness of growth finance in fostering liquid liabilities in Nigeria exist. Thus, this study examines the relationship between growth finance and liquid liabilities in Nigeria, with insight into Nigeria’s real sector. In achieving its objective, the study utilizes secondary data from the annual reports of the Central Bank of Nigeria (1980–2018). The study finds that gross domestic savings significantly drive liquid liabilities in the long run compared to other growth finance indicators, which include stock market development and remittance inflows. Therefore, the study recommends that to improve liquid liability, gross domestic savings, among other growth finance indicators, should be harnessed as a tool to efficiently influence liquid liabilities in the Nigerian economy. The study concludes that attention should be paid to development policies that drive all stakeholders’ gross domestic savings.

This study examines the impact of International Financial Reporting Standards (IFRS) on the stock exchange development (SED) in sub-Saharan Africa (SSA). The essence is to offer suggestions on how the adoption of IFRS in the SSA region can benefit their SED. The study employed logistic regression analysis of data for 40 SSA countries for the period 2010–2018. Data were extracted from the World Bank’s World Development Index (WDI) database, sampled countries’ stock exchange websites, and the IFRS website. The dependent variable (SED) took two values: 1 – if a stock exchange is established in the observed country’s period, otherwise – 0. The model result was well fitted: p < 0.0001, correctly classified an overall SED accuracy up to 84.84% and excellent area predictive power at a receiver operator characteristic of 0.9347. The study observed that IFRS had high degree of co-movement with SED, and changes in IFRS had a strong positive impact on SED. Besides, changes in market size, ICT infrastructure, and public sector management and institution (PSMI) had a positive and significant impact on SED. The odd ratio of SED compared to non-SED is greatest with IFRS (40.67 times), and for the other variables, the ratios are: market size (4.02), ICT infrastructure (1.26), and PSMI (2.73), respectively. On a greater extent, SSA countries should allow the use of IFRS for financial reporting to expedite SED.