Journal of Risk and Financial Management

This paper analyses the relationship between household debt and income inequality in South Africa for the period 1980–2021. We use two measures of inequality and estimate a vector error correction model (VECM) which includes household debt, inequality, and other macroeconomic variables. To test the robustness of our results, single equation models are used, which estimate household debt as a function of inequality and macroeconomic factors. We employ two measures of inequality, namely Gini coefficient and ratio of top and bottom income earners’ proportion of income. Furthermore, we use both household debt as a percentage of disposable income and household debt service costs as dependent variables in single equation regressions. The study finds a negative and significant relationship between household debt and income inequality in the long run, which contradicts the Rajan hypothesis in the South African case. Rather, we find that inequality in South Africa creates a bias in debt allocation towards high-income earners, whose incomes can easily absorb the extra debt (reduced ratio of debt to disposable income). There are therefore no socio-equity considerations in South African credit markets. We find growth in gross domestic product (GDP) per capita also has a moderating effect on the relationship between household debt and income inequality. High GDP per capita growth in the presence of high inequality reduces the impact of inequality on household debt and vice-versa. All other control variables take expected signs. These results are robust to changes in the inequality or household debt measures. Full article

This article has examined the effect of the duration of membership in the World Trade Organization (WTO) on the submission of trademarks by countries’ residents. The analysis used an unbalanced sample of 124 countries (including developed and developing countries) and, primarily, the binominal regression approach supplemented by the generalized method of moments estimator, which was utilized for the robustness check. Results have shown that the effect of the duration of WTO membership on trademarks works through the channel of trade costs. This effect is positive for less developed economies and negative for relatively advanced economies. These findings reflect the fact that as countries spend more time as WTO members, they experience a higher submission of patents in relation to trademarks, especially if they enjoy an improvement in their real per capita income (and export complex products). Furthermore, countries that receive higher Aid for Trade flows (which help to reduce trade costs) experience yet a higher number of trademark applications, but to a lesser extent than patent filings. Full article

This study was conducted to assess the effects of security incidents on the stock prices of firms in Korea. A content analysis of news coverage articles about security incidents was performed. The research questions (RQs) of the current study were as follows: RQ1: this study evaluated whether the news coverage of a security incident can influence an investor’s decision to buy or sell a stock; and RQ2: the study also analyzed whether the type of industry, the amount of damage caused by the incident, and the specific security incident itself would affect how investors assessed a stock’s value. The results of the study indicate the following: (1) news coverage articles about security incidents have a significant effect on stock prices; and (2) the degree of such an effect varies depending on the tone, theme, and category of the news coverage. A more negative tone was associated with a decrease in stock prices. Less negative and neutral tones were associated with an increase in stock prices. In particular, a neutral tone was associated with an increase in stock prices, which was commonly seen in most of the firms experiencing security incidents. Furthermore, the number of news coverage articles about security incidents had no relationship to variations in stock prices. In firms experiencing security incidents, variations in stock prices varied depending on the types of industry, the types of damages, and the type of incident. In conclusion, the current study used an event study and a content analysis of news coverage articles about security incidents to assess their effects on the stock prices of firms. Further studies are warranted to establish the feasibility of this approach in a real-world setting. Full article

The COVID-19 pandemic has had a substantial and far-reaching impact on global economic growth, extending its effects to Indonesia as well. Various sectors have witnessed a decline in stock returns as a consequence. Interestingly, the telecommunications sector has bucked this trend by experiencing an increase in stock returns, defying the negative implications of the pandemic. The relationship between returns and risk is inherently intertwined, necessitating a meticulous risk assessment. In response to this need, the Value at Risk (VaR) method has emerged as a rapidly growing and widely adopted risk measurement tool. Among the techniques employed for VaR estimation, the Monte Carlo simulation stands out due to its flexibility and comprehensiveness in accommodating factors such as time variance, volatility, returns, fat tails, and extreme scenarios. The Gumbel copula method, known for its heightened sensitivity to high-risk events, is utilized for VaR estimation on abnormal stock returns. This study aims to quantify the Value at Risk by leveraging the estimated Gumbel copula parameter for the return on the shares of PT. Indosat Ooredoo Hutchison Tbk, and PT. Smartfren Telecom Tbk during the COVID-19 pandemic. At a 90% confidence level, the VaR is determined to be 7.6%. Notably, this estimate closely aligns with the actual values, underscoring the reliability of the VaR estimation conducted using the Gumbel copula parameter estimator. Therefore, this model serves as a robust reference, particularly suitable when dealing with investment return data that deviate from the normal distribution, while considering the unique stock return characteristics within each dataset. Full article

Predicting trends in the stock market is becoming complex and uncertain. In response, various artificial intelligence solutions have emerged. A significant solution for predicting the trends of a stock’s volatile and chaotic nature is drawn from deep learning. The present study’s objective is to compare and predict the closing price of the NIFTY 50 index through two significant deep learning methods—long short-term memory (LSTM) and backward elimination LSTM (BE-LSTM)—using 15 years’ worth of per day data obtained from Bloomberg. This study has considered the variables of date, high, open, low, close volume, as well as the 14-period relative strength index (RSI), to predict the closing price. The results of the comparative study show that backward elimination LSTM performs better than the LSTM model for predicting the NIFTY 50 index price for the next 30 days, with an accuracy of 95%. In conclusion, the proposed model has significantly improved the prediction of the NIFTY 50 index price. Full article

In recent years, the increasing demand for digital cultural content has intensified the digitization challenges for cultural organizations. Among these difficulties, cultural organizations have been struggling to find the financial resources for digitizing their cultural heritage, as well as for storing data, developing digital skills, and implementing enhancement and management processes for their digitized materials. The financial sustainability of digitization projects has therefore been problematic, especially for small and medium organizations. In this framework, among its attempts to solve these issues, the European Union has launched the project Europeana, a digital platform uniting European digitized heritage and empowering cultural organizations through a variety of services. The aim of our research was to investigate the Europeana project to understand how it eases the financial costs of digitization for cultural organizations, and how the Europeana model could bring insights into how to improve the financial sustainability of digitization of cultural heritage. Full article

Global society’s comfort and well-established certainties have been unpredictably and foundationally undermined by the emergence of the COVID-19 virus. The announcement of the pandemic by the WHO has halted global economic activities, and the financial markets have recorded drastic losses. In this context of uncertainty and economic downturn, many traditional companies have been negatively impacted, but the biotechnology sector, which has already been growing for some years, registered high growth rates and earnings. In particular, this study focused on the two most significant biotech companies, BioNTech and Moderna, the two start-ups that first commercialized COVID-19 vaccines. The GARCH (1,1) model examines the relation of two stock prices and the volatility of derivatives markets before and after the outbreak of the pandemic. The variables used in the analysis are the U.S. technologic market index, the market volatility, and Brent future prices. The results suggest a different reaction of market volatility and Brent future prices on the return of both companies. Additionally, during the COVID-19 period, a contagion effect between both companies and the technological market was observed. Full article

We examine the complex relationship between taxes and local economies at the county level. Specifically, we explore the impacts of different types of state-level taxes, including income and payroll taxes, property and other taxes, as well as sales tax, on key economic performance indicators. Our study aims to comprehensively analyze how state-level taxation influences entrepreneurship, innovation, labor markets, and overall economic growth in local communities. The findings consistently demonstrate that taxes harm local economies, although the magnitude of the impact varies depending on the specific type of tax. Notably, a 10 percent increase in income and payroll taxes leads to a 3 percent drop in the nonfarm proprietors employment rate, 0.3 fewer patents per 1000 people, and a USD 3000 decrease in GDP per capita. A similar tax hike in sales taxes results in a 4.5 percent decline in the nonfarm employment rate and a 0.2 patent reduction per 1000 people. Property and other taxes also harm the economy: a 10 percent increase is linked to a 5.3 percent fall in the nonfarm proprietors employment rate, a 7.5 percent rise in local unemployment, and a USD 55,000 drop in regional GDP per capita. Full article

We investigated the stock return risk associated with the various types of dividend decisions announced by New Zealand firms during the COVID-19 pandemic in 2020. The sample includes a group of firms that initially announced cash dividends but a number of days later made announcements cancelling their payments. Using multinomial logistic regression analysis, we found that higher pre-pandemic payout policy significantly increased the likelihood of a cancellation, an omission or an increase decision. Higher growth and higher profitability reduced the probability of an omission and a reduction decision, respectively. Moreover, higher stock return volatility increased the likelihood of an omission, a reduction or an increase decision. Further event study analysis revealed that investors reacted more feverishly to the announcements of cancellation decisions than any other types of dividend decisions. Moreover, we report strong evidence of negative abnormal returns around the cancellation announcements followed by positive post-announcement price reversals, a pattern that is not observed for the omission announcements. This paper contributes to the literature by studying a cancellation sample and reveals, for the first time, significant shareholder risk associated with cancellation decisions, which was not observed for omission decisions. We alert managers to carefully weigh the costs and benefits of breaking a promise of dividend payout. Full article

This study explores fiscal consolidations’ impact on non-performing loans (NPLs) in highly indebted countries (HICs) following the global financial crisis (GFC) and subsequent sovereign debt crisis. A dynamic panel data estimator was applied to obtain the unbiased estimator due to NPLs’ time persistence. The findings reveal that fiscal consolidation measures increase NPLs since they limit the household and business loan-serving capacity. Extended analysis categorises fiscal consolidation episodes into (1) the fiscal consolidation weak form (FCWE) and (2) the fiscal consolidation strong form (FCSE). The extended analysis results reveal that the FCWE and FCSE improve NPLs by 1.55% and 31.10%, respectively. The weak-to-strong form transition of the fiscal consolidation analysis resulted in improving NPLs by 28.55 percentage points. NPL definition challenges, the potential influence of loan restructuring and regulatory restrictions, and implications for policymakers and financial institutions in managing NPLs in highly indebted economies were explored. Investigating the potentially different effects of both forms of fiscal consolidation (FCWE and FCSE) on NPLs in countries with different definitions of NPLs, including a comparison study between different definitions, was identified as an implication for future research. Finally, future studies should examine how restrictions on IFRS 9 may affect the FCWE and NPL as well as FCSE and NPL associations. Full article

The futures contracts were introduced to act as hedging instruments and ensure the price discovery (referred to as PD hereafter) mechanism for the underlying securities. If the price movement of a futures contract leads the price movement of the underlying securities in the spot market, this confirms the existence of price discovery in the market. This study undertakes an in-depth analysis of past research in order to find research trends and directions for the future in the field of price discovery. The bibliometric analysis technique is used to analyse the existing literature. The study considers the 1431 documents collected from the Scopus database for the period of 1982–2021 to conduct the descriptive and network analysis of search results. The study identifies three key clusters, i.e., the foundation of the price discovery process (Cluster 1), the econometric tools and techniques to assess the price discovery process (Cluster 2), and price discovery under different market conditions and constraints (Cluster 3). After an in-depth content analysis of these clusters, the study provides suggestions for future research in the field of price discovery. The study is the first of its type to conduct an in-depth analysis of the literature of price discovery since inception, and provides directions for future research in the field. Full article

This article deals with the identification of a superior forecasting method for market liquidity using a calibrated Heston model for the bid/ask price path simulation instead of a standard Brownian motion, as well as a compound Poisson process and inverse transform sampling for the generation of the bid/ask volume distribution. We show that the simulated trading volumes converge to one single value, which can be used as a liquidity estimator, and find that the calibrated Heston model as well as the inverse transform sampling are superior to both the use of standard Brownian motion and compound Poisson process. Full article

This research investigates the role of the large, medium, and small market cap portfolios in returns during the COVID-19 pandemic, around the ‘lockdown’ policy in March 2020 based on the Norwegian market. The main results suggest that during the event window, the medium and small portfolios are impacted more negatively than the large. During the before-event days, the large portfolio is slightly negatively affected, but it tends to be better after the event. The medium and small portfolios are not adversely affected during before the event, but they are considerably negatively affected after the event. The small portfolio is affected more severely negatively than the medium. The small portfolio is the most volatile of the three during the event window. In addition, there are opportunities to earn extremely positive abnormal returns (from 2.5%) after the event by holding the small and medium portfolios, but not for the large. It seems that more opportunities to earn extremely positive abnormal returns for the small portfolio than the medium. Full article

This research will examine the impact of the adoption of financial technology on conventional banks’ financial performances. The research will place emphasis on the listed commercial banks at Amman Stock Exchange—ASE, using financial data for the period 2012–2020. The main study tool was a questionnaire that focuses on three main dimensions: financial inclusion—(FI), alternative payment methods—(APMs) and automation—(Auto). A total of 115 questionnaires were distributed to all commercial banks listed at Amman Stock Exchange—ASE. Multivariate regression analysis was employed to test the impact of the FinTech dimension as a proxy for independent variables on Jordanian commercial bank’s financial performance as a proxy for dependent variables. Based on the analysis results, the study concludes that all three FinTech dimensions: FI, APMs and Auto. reflected a positive significant impact on Jordanian commercial bank’s financial performance indicators (total deposit, total loans and net profit margin). Therefore, banks in general should invest more and more into financial technology tools and applications, in order to recruit potential clients and retain their current clients, to be able to sustain under fierce competition within the banking sector. Full article

Using daily closing price observations between November 2017 and February 2023, this paper documents how the shocks of a cryptocurrency ETF resonate with ETFs representing traditional asset classes in terms of price and volatility. We find price transmission from the cryptocurrency ETF into the ETFs of several currencies, small-cap equities, and inflation. Risk propagation from the cryptocurrency ETF flows toward ETFs constituted of equities of various sizes, oil prices, high-yield corporate bonds, and inflation. There is scant evidence of transmission from ETFs with underlying conventional assets into the cryptocurrency ETF. The findings bear implications for low-cost risk management strategies. Full article

Despite the shift to private sector-driven affordable housing in Nigeria for decades, the housing deficit has continued to increase to the disadvantage of low-income families. This paper explores the enabling strategies for stimulating private-driven affordable housing in Nigeria. A case study of the Millard Fuller Foundation projects was undertaken, and semi-structured interviews were administered to 12 residents of the estates and the developer to explore their experience and highlight the considerations for designing appropriate strategies. The data generated were analysed using thematic analysis with the support of Nvivo. This study identifies four major components of construction costs—land, design, materials, and finance—that policy improvement can target to stimulate private investment. It shows that developers are likely to adopt practices that will reduce these costs with repercussions for end-users. Mindful of this, and the concern to make returns on investment, strategies should aim to harmonise both developers’ interest and that of the end-users through widespread infrastructural development to make land available in all locations, and an incremental owner-building approach so that end-users can take decisions for their housing. Furthermore, access to National Housing Fund (NHF) mortgages should be enhanced by recognising supplementary incomes in the loan origination procedures. Full article

In this paper, I propose a tracking error approach using the P/E ratio equation to approximate the CAPE Ratio. After accounting for the recent structural changes in the composition and valuation of the S&P 500 index, along with a persistently low interest rate environment over the last three decades, I show that the average CAPE Ratio had increases over time. Relying solely on historical CAPE averages to forecast equity returns may therefore prove unreliable. The findings in this paper indicate that investors should incorporate multiple factors, including required return and expected earnings growth, when forming capital allocation decisions across asset classes. Rotating out of the equity market simply because the CAPE Ratio shows that the equity market is too expensive might not produce the desire outcome investors hope for. Full article

Due to rapid technological advancements and intense competition, organizations must find new ways to do business. As a result, changes in an organization’s structures, systems, and strategies are now a pre-requisite to survive the competition. Involving employees in strategic change programmes will harness ideas that enhance competitive advantage and organizational performance. The purpose of this study is to inform industry executives, especially in insurance companies, that employees are crucial resources that must be valued for their contribution to the survival of the organization. A total of 115 respondents were surveyed using a 5-point Likert scale questionnaire in a quantitative research approach. This study employed the multiple regression method to test the effect of five employee involvement constructs on organizational performance using IBM SPSS V28 software. All five constructs, that is, participation in decision-making, teamwork, communication, creativity, and innovation, significantly affected the performance of insurance companies in Zimbabwe. This study’s findings will convince top managerial leaders of the insurance industry to acknowledge and appreciate the importance of involving employees in strategic change programmes. Furthermore, industry regulatory authorities can promote policies and practices that involve employees in decision-making. Full article