J. Risk Financial Manag., Volume 15, Issue 1 (January 2022) – 38 articles

This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares estimator, is used to estimate the nonparametric component. We discuss how to estimate the semiparametric estimator using real data and how to use this estimator to make forecasts for the conditional variance. Simulations are conducted to show the dominance of the proposed estimator in terms of mean squared error. An empirical application using S&P 500 daily returns is analyzed, and the semiparametric estimator effectively forecasts future volatility. Full article

This paper studies the effects of a firm’s financial performance (FP) and chief executive officer’s (CEO) duality on the quality of corporate social responsibility (CSR) disclosure in the context of state-owned enterprises (SOEs) among Chinese A-share-registered companies. The results depict a negative relationship between CEO duality and CSR disclosure. Our results demonstrate that better-performing firms disclose CSR information more frequently and of higher quality compared with firms with poor financial performance. This role of financial performance in the quality of CSR disclosure is generally valuable in public enterprises; however, it is relatively sluggish in state-owned enterprises the outcomes indicate that the dual leadership structure reduces assessments and renders CEOs less liable to their stakeholders. Therefore, this study offers valuable information and details for regulators to improve corporate governance and CSR from the perspective of stakeholder theory. Full article

The motivation for this study hinges around the fact that Trinidad and Tobago (T&T) is suffering from the Dutch disease which inadvertently hinders the growth of non-energy exports. This paper examines measures that can be adopted for a small petroleum-exporting economy to dampen the effect of Dutch disease by promoting non-energy trade. This paper is novel and contributes to the literature in using panel data for the T&T case, as it investigates the effect of a devaluation of the TT dollar in order to stimulate non-energy exports (a combination of agriculture and manufacturing trade). Note that previous studies would have examined the Marshall–Lerner condition on the aggregate trade balance which is heavily influenced by energy revenues. The panel autoregressive distributed lag (ARDL) method is used for ten of T&T’s main trading partners for the period 1991 to 2019 to establish findings. The results show that the Marshall–Lerner condition does not hold for aggregate trade in the long run, as expected. However, when non-energy trade is isolated, it is found that a devaluation of the TT dollar does have a positive impact on non-energy trade and the Marshall–Lerner condition holds. Other measures are also recommended to stimulate non-energy exports in the long run. Full article

In this study, we apply several advanced machine learning techniques including extreme gradient boosting (XGBoost), support vector machine (SVM), and a deep neural network to predict bankruptcy using easily obtainable financial data of 3728 Belgian Small and Medium Enterprises (SME’s) during the period 2002–2012. Using the above-mentioned machine learning techniques, we predict bankruptcies with a global accuracy of 82–83% using only three easily obtainable financial ratios: the return on assets, the current ratio, and the solvency ratio. While the prediction accuracy is similar to several previous models in the literature, our model is very simple to implement and represents an accurate and user-friendly tool to discriminate between bankrupt and non-bankrupt firms. Full article

Trading activities represent the flow of market information to the investors. This paper examines the effect of trading activities, i.e., trading volume and open interest, on the volatility of return for Malaysian Crude Palm Oil Futures. The GARCH model is applied by adding the expected and unexpected elements of trading activities (trading volume and open interest) as the independent variables. The results show that there is a negative contemporaneous relationship between the expected volume and volatility, but that a positive relationship exists between unexpected volume and volatility. On the contrary, the expected and unexpected open interest mitigate the volatility. Therefore, both trading volume and open interest should be considered together when information flows into the market. Full article

This paper aims to contribute to the lack of research on the learning process of mutual fund markets. The empirical design is focused on the ability of the Spanish equity mutual fund industry to learn from its important errors. The choice of this industry is justified by both its relevance in the European mutual fund markets and some specific characteristics, such as the concentration and the banking control of the industry, which may affect the learning process. Our main objectives are to identify important trading errors in mutual fund management by applying three independent filters based on the relative importance of each decision, and then testing the evolution of these errors both at the industry level and at the fund family level. We apply the dynamic model of generalized method of moments (GMM), and we find an overall significant decrease in the percentage of important trading errors over time, thereby providing evidence of the global learning process of the industry. In addition, we find that a large number of fund families drive this evidence. Finally, we obtain that the family size and its dependence on financial groups do not seem to play significant roles in explaining the learning process. Therefore, we conclude that fund managers have incentives to learn from their important trading errors, in order to avoid them in future decisions, due to their serious negative consequences on fund performance, regardless of the characteristics of the families to which they belong. Full article

Quantitative researchers often use Student’s t-test (and its p-values) to claim that a particular regressor is important (statistically significantly) for explaining the variation in a response variable. A study is subject to the p-hacking problem when its author relies too much on formal statistical significance while ignoring the size of what is at stake. We suggest reporting estimates using nonlinear kernel regressions and the standardization of all variables to avoid p-hacking. We are filling an essential gap in the literature because p-hacking-related papers do not even mention kernel regressions or standardization. Although our methods have general applicability in all sciences, our illustrations refer to risk management for a cross-section of firms and financial management in macroeconomic time series. We estimate nonlinear, nonparametric kernel regressions for both examples to illustrate the computation of scale-free generalized partial correlation coefficients (GPCCs). We suggest supplementing the usual p-values by “practical significance” revealed by scale-free GPCCs. We show that GPCCs also yield new pseudo regression coefficients to measure each regressor’s relative (nonlinear) contribution in a kernel regression. Full article

This study investigates the time evolution of market efficiency in the Japanese stock markets, considering three indices: Tokyo Stock Price Index (TOPIX), Tokyo Stock Exchange Second Section Index, and TOPIX-Small. The Hurst exponent reveals that the Japanese markets are inefficient in their early stages and improve gradually. TOPIX and TOPIX-Small showed an anti-persistence around the year 2000, which still persists. The degree of multifractality varies over time and does not show that the Japanese markets are permanently efficient. The multifractal properties of the Japanese markets changed considerably around the year 2000; this may have been caused by the complete migration from the stock trading floor to the Tokyo Stock Exchange’s computer trading system and the financial system reform, also known as the “Japanese Big Bang”. Full article

The redistribution of resources in global stock markets is prevalent: the capital is transferred from one investor to another. Sometimes, earning a substantial return in the stock market seems complicated to implement for an individual investor. Investing contributes to the welfare of society and the wealth of citizens. This is why people should look for efficient ways to invest. Investment should become a natural part of personal finance management in the majority of households. For this reason, an investment model is developed where stocks are selected based only on market intelligence using historical data. The model helps find one or several stocks that generate the highest return on a separate step. Applying this model, experiments were performed with daily data from German, US, and UK stock markets. The possibility of obtaining higher than average returns in these markets has been noticed. In the German market, during the 97-day period, the authors obtained a 1.46 return, which implies a 2.31 annual return: in the USA market, a 2.37 return (7.93 annual return), and in the UK market, a 1.90 return (4.09 annual return). Thus, the proposed investment decision-making system could be an efficient tool for forming a sustainable individual or household portfolio. It can generate higher investment returns for an investor and, moreover, make the market more efficient by applying market intelligence and related historical data. Full article

Hedging down-and-out puts (and up-and-out calls), where the maximum payoff is reached just before a barrier is hit that would render the claim worthless afterwards, is challenging. All hedging methods potentially lead to large errors when the underlying is already close to the barrier and the hedge portfolio can only be adjusted in discrete time intervals. In this paper, we analyze this hedging situation, especially the case of overnight trading gaps. We show how a position in a short-term vanilla call option can be used for efficient hedging. Using a mean-variance hedging approach, we calculate optimal hedge ratios for both the underlying and call options as hedge instruments. We derive semi-analytical formulas for optimal hedge ratios in a Black–Scholes setting for continuous trading (as a benchmark) and in the case of trading gaps. For more complex models, we show in a numerical study that the semi-analytical formulas can be used as a sufficient approximation, even when stochastic volatility and jumps are present. Full article

This paper examines the impact of changes in economic policy uncertainty (EPU) and COVID-19 shock on stock returns. Tests of 16 global stock market indices, using monthly data from January 1990 to August 2021, suggest a negative relation between the stock return and a country’s EPU. Evidence suggests that a rise in the U.S. EPU causes not only a decline in a country’s stock return, but also a negative spillover effect on the global market; however, we cannot find a comparable negative effect from global EPU to U.S. stocks. Evidence suggests that the COVID-19 pandemic has a negative impact that significantly affects stock return worldwide. This study also finds an indirect COVID-19 impact that runs through a change in domestic EPU and, in turn, affects stock return. Evidence shows significant COVID-19 effects that change relative stock returns between the U.S. and global markets, creating a decoupling phenomenon. Full article

The aim of the study is to investigate the influence of the capitalist spirit in conjunction with the distribution of income on economic growth. The capitalist spirit is represented by the fact that savings rates increase with increasing relative income. We extend an endogenous AK growth model in an overlapping generational framework by implementing imperfect competition and Cournot competition. Using this model, we investigate the influence of profits on the intra- and inter-generational distributions of income and economic growth. While increasing incomes lead to a more unequal intra-generational distribution and to a redistribution of income from the old to the young generation, the impact on economic growth is in general ambiguous, although under specific assumptions it becomes positive. Furthermore, the model shows that increasing market power of firms is associated with declining labor and capital shares, declining interest rates, and an increased wealth-to-income ratio. Full article

Financial data are expensive and highly sensitive with limited access. We aim to generate abundant datasets given the original prices while preserving the original statistical features. We introduce the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) into the field of the stock market, futures market and cryptocurrency market. We train our model on various datasets, including the Hong Kong stock market, Hang Seng Index Composite stocks, precious metal futures contracts listed on the Chicago Mercantile Exchange and Japan Exchange Group, and cryptocurrency spots and perpetual contracts on Binance at various minute-level intervals. We quantify the difference of generated results (836,280 data points) and original data by MAE, MSE, RMSE and K-S distances. Results show that WGAN-GP can simulate assets prices and show the potential of a market simulator for trading analysis. We might be the first to look into multi-asset classes in a systematic approach with minute intervals across stocks, futures and cryptocurrency markets. We also contribute to quantitative analysis methodology for generated and original price data quality. Full article

Corporate bond yields are the manifestation of the cost of financing for private firms, and if properly evaluated, they provide researchers with valuable risk information. Within this context, this work is the first study producing corporate yield spreads for all S&P-rated bonds of G20 nations to explain their comparative riskiness. The option-adjusted spread analysis is an advanced method that enables us to compare the bonds with embedded options and different cash flow characteristics. For securities with embedded options, the volatility in the interest rates plays a role in ascertaining whether the option is going to be invoked or not. Therefore, researchers need a spread that, when added to all the forward rates on the tree, will make the theoretical value equal to the market price. The spread that satisfies this condition is called the option-adjusted spread, since it considers the option embedded into the issue. Ultimately, this work investigates the credit risk differentials of S&P rated outstanding bonds issued by the G20 nations to provide international finance professionals with option-adjusted corporate yield spreads showing the credit risk attributable to debt instruments. Detailed results computed using OAS methodology are presented in tables and used to answer the six vital credit-risk-related questions introduced in the introduction. Full article

This study proposes a wavelet procedure for estimating partial correlation coefficients between stock market returns over different time scales. The estimated partial correlations are subsequently used in a cluster analysis to identify, for each time scale, groups of stocks that exhibit distinct market movement characteristics and are therefore useful for portfolio diversification. The proposed procedure is demonstrated using all the major S&P 500 sector indices as well as precious metals and energy sector futures returns during the last decade. The results suggest cluster formations that vary by time scale, which entails different stock selection strategies for investors differing in terms of their investment horizon orientation. Full article

Entrepreneurs are constantly looking for new models to address growing global challenges in a sustainable manner. Over the past several decades, those challenges have been identified and responded to through the development of social entrepreneurship. There is a number of research dealing with the theoretical concepts of those topics; however, the definitions and framework for action are different from country to country. Having in mind that the main idea of social entrepreneurship is to enable decent work for employees and to gain broader welfare for communities, the purpose of this paper is to analyse the development of social entrepreneurship in Croatia. The research is focused on recent developments, connecting key definitions and principles of social entrepreneurship with common trends and concrete case studies. This study’s results show that there are different approaches to social entrepreneurship globally. However, social entrepreneurship in Croatia develops within a clear legal framework. The current state of social enterprises is connected with respective public policies, while the number and types of social entrepreneurs are constantly rising in the last few years. The results of the analysis also show that there are still actions to be taken in order to encourage future policy measures aiming to support social entrepreneurs in Croatia. Full article

The paper discusses an extension of the variance-gamma process with stochastic linear drift coefficient. It is assumed that the linear drift coefficient may switch to a different value at the exponentially distributed time. The size of the drift jump is supposed to have a multinomial distribution. We have obtained the distribution function, the probability density function and the lower partial expectation for the considered process in closed forms. The results are applied to the calculation of the value at risk and the expected shortfall of the investment portfolio in the related multivariate stochastic model. Full article

The role of digital transformation in creating value for commercial banks has been interesting to researchers for a long time. While many commercial banks have significantly investigated digital transformation, researchers and managers have still met many difficulties examining the distribution of digital transformation to business performance. This paper aims to evaluate the impact of digital transformation on Vietnamese commercial banks’ performance by different sizes, from there proposing policy implications of digital transformation to improve the banking performance. To achieve this goal, we used a quantitative research method. Specifically, we applied the GMM system (SGMM) of Blundell and Bond for the data of 13 joint-stock commercial banks in Vietnam in the period from 2011 to 2019. Then Bayesian analysis is performed to test the robustness of the models estimated by the SGMM method. The result shows that the digital transformation has a positive impact on the performance of Vietnamese commercial banks. Besides, we also find that the larger the banks, the greater the positive impact of digital transformation on bank performance. Therefore, the efficiency of digital transformation depends on a bank scale. Full article

Human resources are very important in a business; however, the return on investment in human resources is longer than in fixed assets, so entrepreneurs frequently consider how much to actually invest. This article, based on primary research, examines the motivations for investment when a 20% profit is typically invested with a model return of around 14%. Those findings are supported by the results presented in Archetype models based on similarity clustering. The results are based on an empirical study (278 respondents, omnibus survey) in the Czech Republic. Moreover, the study concludes that the business experience positively influences human resource management and future development to increase the investment share. In essence, this article displays the paramount importance of human resources and human resource management in the international business environment, demonstrating that investments in human resources are crucial to the success of all businesses, positively and consistently supporting organizations’ performance, and entrepreneurship will continue to remain a vital component of the activities belonging to the post COVID-19 era. In addition, in an era governed by the influences specific to the knowledge-based society and the knowledge-based economy, in which intellectual capital will be considered one of the most relevant intangible assets of entities all over the world, the measurement of human resources investment will turn out to be essential for the success of all businesses, while taking the necessary steps in supporting sustainability, sustainability assessment and Sustainable Development Goals (SDGs). Full article

In the context of the great turmoil in the financial markets caused by the COVID-19 pandemic, the predictability of daily infectious diseases-related uncertainty (EMVID) for international stock markets volatilities is examined using heterogeneous autoregressive realised variance (HAR-RV) models. A recursive estimation approach in the short-, medium- and long-run out-of-sample predictability is considered and the main findings show that the EMVID index plays a significant role in forecasting the volatility of international stock markets. Furthermore, the results suggest that the most vulnerable stock markets to EMVID are those in Singapore, Portugal and The Netherlands. The implications of these results for investors and portfolio managers amid high levels of uncertainty resulting from infectious diseases are discussed. Full article

This paper reports the results of analysing desk-based data on organisational support for high performance athletes to develop their financial literacy and self-management skills when transitioning out of sport. There are two research questions: (1) Do sport organisations provide support schemes or other interventions such that high-performance athletes develop their financial literacy and self-management skills? and (2) Do sport organisations provide financial support schemes for high-performance athletes’ retirements? If so, what do they involve? Desk-based data collection was applied to 23 sporting organisations; these comprised 21 national organisations representing 19 countries, the International Olympic Committee (IOC) and the Oceanic National Olympic Committee (ONOC). Fifteen of the 23 organisations, representing 14 countries, provided some support or interventions on financial planning and self-management within their career assistance programmes. The findings also indicate that most organisations in 17 different countries did not provide any financial support for athletes’ retirements. While a number of sport organisations have developed appropriate interventions to assist high-performance athletes to develop financial literacy and self-management skills, such schemes appear only to be provided to high-performance athletes who have competed at the highest level e.g., Olympics, world championships, etc. Support for athletes at lower levels should also be developed and delivered by national governments, or by national sport organisations. Full article

The Uppsala model explains the traditional internationalisation process of multinational enterprises (MNEs), which gradually begin to internationalise from countries with smaller psychic distances. However, in the turbulent global economy, an increasing number of MNEs from emerging markets (EMNEs) adopts a more radical and aggressive approach, strategically using international expansion as a springboard to enter an overseas market and radiate surrounding countries and regions. By combining the springboard perspective and the Uppsala model, we analyse a series of processes from EMNE’s first entry into an overseas market to the successful localisation and expansion of international business. This radical model of international expansion has not been thoroughly studied. This empirical study aims to address this research gap by using a qualitative method and an in-depth case study. This paper conducted a semi-structured interview with 16 expatriates, executives, and middle-level managers from the case company in 2016. As one of the few single case studies that systematically studies the internationalisation process of EMNEs and provides first-hand empirical evidence, it contributes to practice and provides a contextual reference for EMNEs. Full article

The effectiveness of the unification of enterprises in the cluster is also associated with high uncertainty and risks. Thus, the development of theoretical approaches and methodological instruments for efficient risk management of enterprises under the conditions of cluster association is an urgent scientific task. The methodology of a comprehensive risk assessment of the cluster enterprise is based on the use of the approach for building a functional-target model of a cluster enterprise, and is reduced to the search for a response to the question: can an event change the value of a providing indicator in such a way that this will lead to a deterioration in the resulting indicator in each enterprise subsystem? Based on the results of forecasting external risks, it was established that the group of state and global risks, in particular, political, territorial and financial, is characterized by significant threats for the next 5 years for the studied cluster enterprises. We proposed and tested a methodology for a comprehensive assessment of the risks of cluster enterprises, based on a functional-target approach, according to which a cluster enterprise as a socio-economic system is considered as a set of three basic subsystems: management, production and financial and economic. Full article

This paper presents a new hierarchical methodology for estimating multi factor dynamic asset pricing models. The approach is loosely based on the sequential Fama–MacBeth approach and developed in a kernel regression framework. However, the methodology uses a very flexible bandwidth selection method which is able to emphasize recent data and information to derive the most appropriate estimates of risk premia and factor loadings at each point in time. The choice of bandwidths and weighting schemes are achieved by a cross-validation procedure; this leads to consistent estimators of the risk premia and factor loadings. Additionally, an out-of-sample forecasting exercise indicates that the hierarchical method leads to a statistically significant improvement in forecast loss function measures, independently of the type of factor considered. Full article

Institutional investors often have to decide which strategy to use across international business cycles. This is especially important during economic and financial crises. The exogenous nature of the outbreak of the dramatic COVID-19 crisis represents a unique opportunity to understand the performance of risk factors during severe economic times across international stock markets. Even more important is to analyze how these factors behave across very different economic crises, such as the COVID-19 pandemic and the Great Recession. Although, the overall results show that the momentum and quality factors are the winners, with the value factor as the loser, this research also reports different responses of factors across crises and countries. The size, value, and defensive factors tend to perform worse during the health crisis relative to the Great Recession, while the momentum factor shows a poor performance during the financial crisis, but a positive one during the outbreak of COVID-19. The quality factor is an extraordinary defensive factor in both crises. Similarly, this paper reports heterogeneous responses of option-implied expected market risk premia across alternative stock market indices, and between the Great Recession and the COVID-19 crisis. Full article

This paper proposes new dynamic conditional futures hedge ratios and compares their hedging performances along with those of common benchmark hedge ratios across three broad asset classes. Three of the hedge ratios are based on the upward-biased carry cost rate hedge ratio, where each is augmented in a different bias-mitigating way. The carry cost rate hedge ratio augmented with the dynamic conditional correlation between spot and futures price changes generally: (1) provides the highest hedging effectiveness and (2) has a statistically significantly higher hedging effectiveness than the other hedge ratios across assets, sub-periods, and rolling window sizes. Full article

This paper examines equilibrium relationships and dynamic causality between economic growth, exports, and imports in Nepal using time-series data between 1965 and 2020. This research examines the impact of exports and imports on the economic growth of Nepal and documents empirical evidence in exports-led growth, imports-led growth, growth-led exports, and growth-led imports hypotheses in both the short and long run. The test results show no evidence favoring the exports-led growth and growth-led exports hypotheses in both the short and long run. However, the study finds evidence supporting the imports-led growth hypothesis in the short term and the growth-led imports hypothesis in the long term. Overall, this paper finds no evidence in favor of the notion that foreign trade supports the economic growth of Nepal in the long run. The research findings may have important implications for policymakers in Nepal. The paper contributes to trade and economic growth literature by investigating the relationship between exports, imports, capital, and gross domestic products in a small economy such as Nepal, where exports make a minimal and imports make an extensive contribution to gross domestic products by using cointegration and the vector error correction model. Full article

The nature of the relation between stock returns and the three monetary variables of interest rates (bond yields), inflation and money supply growth, while oft studied, is one that remains unclear. We argue that the nature of the relation changes over time, and this variation is largely driven by shocks, with a change in risk associated with each variable shifting the pattern of behaviour. We show a change in the correlation between each of the three variables with stock returns. Notably, a predominantly negative correlation with bond yields and inflation becomes positive, while the opposite is true for money supply growth. The shift begins with the bursting of the dotcom bubble but is exacerbated by the financial crisis. Results of predictive regressions for stock returns also indicate a switch in behaviour. Predominantly negative predictive power switches temporarily to positive around economic shocks. This suggests that higher yields, inflation and money growth typically depress returns but support the market during periods of stress. However, after the financial crisis, higher inflation and money growth exhibit persistent positive predictive power and suggest a change in the risk perception of higher values. Full article

The article researches the features of the synergy of the social functions of the state and the housing mortgage loan (HML) in order to develop a tool that allows determining guidelines and directions for strengthening the effectiveness of collaboration between the state and the private sector represented by commercial banks in solving the most important social problem—providing housing to the population. The authors show that the use of the proposed assessment tool by state structures and commercial banks increases the effectiveness of solutions to the housing problem in the country and enhances the synergetic effect of a comprehensive increase in the standard of living of the population when synchronizing actions. The main purpose of the research was to develop an algorithm that determines the key factors influencing the number of issued HML. The object of the study is the Russian HML market on the example of three federal districts. The developed algorithm is based on the use of statistical analysis methods ANOVA, mutual regression and recursive feature elimination. The approbation of the results obtained on three subjects of the Russian Federation allowed us to obtain a set of significant factors of influence, taking into account regional peculiarities. Full article