Sanshao Peng, Catherine Prentice, Syed Shams and Tapan Sarker
Given the cryptocurrency market boom in recent years, this study aims to identify the factors influencing cryptocurrency pricing and the major gaps for future research.
Abstract
Purpose
Given the cryptocurrency market boom in recent years, this study aims to identify the factors influencing cryptocurrency pricing and the major gaps for future research.
Design/methodology/approach
A systematic literature review was undertaken. Three databases, Scopus, Web of Science and EBSCOhost, were used for this review. The final analysis comprised 88 articles that met the eligibility criteria.
Findings
The influential factors were identified and categorized as supply and demand, technology, economics, market volatility, investors’ attributes and social media. This review provides a comprehensive and consolidated view of cryptocurrency pricing and maps the significant influential factors.
Originality/value
This paper is the first to systematically and comprehensively review the relevant literature on cryptocurrency to identify the factors of pricing fluctuation. This research contributes to cryptocurrency research as well as to consumer behaviors and marketing discipline in broad.
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Rajesh Mohnot, Arindam Banerjee, Hanane Ballaj and Tapan Sarker
The aim of this research is to re-examine the dynamic linkages between macroeconomic variables and the stock market indices in Malaysia following some transformational changes in…
Abstract
Purpose
The aim of this research is to re-examine the dynamic linkages between macroeconomic variables and the stock market indices in Malaysia following some transformational changes in the policies and the exchange rate regime.
Design/methodology/approach
Using monthly data points for all the economic variables and the stock market index (KLCI Index), the authors applied vector autoregression (VAR) model to examine the relationship. The authors also used impulse response function (IRF) in order to explore the effect of one-unit shock in “X” on “Y” under the VAR environment.
Findings
The authors' study finds a significant relationship between all the macroeconomic variables and the stock market index of Malaysia. The cointegration results indicate a long-term relationship, whereas the vector autoregressive-based impulse response analysis suggests that the Malaysian stock index (KLCI) responds negatively to the money supply, inflation and producer price index (PPI). However, the authors' results indicate a positive response from the stock index to the exchange rate.
Research limitations/implications
The authors' study's results are based on selected macroeconomic variables and the VAR model. Researchers may find other variables and methods more useful and may provide findings accordingly.
Practical implications
Since the results are quite asymmetric, it would be interesting for the market players, policymakers and regulators to consider the findings and explore appropriate opportunities.
Originality/value
While the relationship between macroeconomic variables and stock market indices has been widely examined, a significant gap in the literature remains concerning the role of exchange rate variable on the stock market in an emerging economy context.
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Md. Bokhtiar Hasan, Mustafa Raza Rabbani, Tapan Sarker, Tanzila Akter and Shaikh Masrick Hasan
This study aims to examine the effect of risk disclosure (RD) on commercial banks’ credit rating (CR) in the context of Bangladesh. It also explores the factors influencing RD in…
Abstract
Purpose
This study aims to examine the effect of risk disclosure (RD) on commercial banks’ credit rating (CR) in the context of Bangladesh. It also explores the factors influencing RD in both Islamic and conventional banks.
Design/methodology/approach
The sample includes 200 bank-year observations consisting of 20 commercial banks (15 conventional and 5 Islamic banks) from 2010 to 2019. The sample is further segregated into Islamic and conventional banks. Ordered logit and random effect ordinary least square models are used to analyze the data. Furthermore, the two-stage least squares approach is used to perform a robustness test.
Findings
This study shows that RD significantly positively impacts CR, with a stronger effect in Islamic banks than in conventional banks. This study also finds that banks’ age and leverage negatively influence CRs. Moreover, banks’ size and total capital have a positive and negative influence on CRs, respectively. This study also shows that the age of Islamic and conventional banks positively and negatively influences the RD scores, respectively. In contrast, the RD score of conventional banks is positively impacted by bank size.
Practical implications
By examining which variables substantially impact RD and, hence, CR scores, bank stakeholders may make better financing, investment and other policy decisions. Investors may choose stocks with a high level of RD in the annual reports as the earlier studies imply that higher RD enhances CR.
Originality/value
Only a few studies have examined the relationship between RD and CRs, while, to the best of the authors’ knowledge, this study is the maiden attempt in the Bangladesh context. This study also compares the link between Islamic and conventional banks.
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Jitender Kumar, Vinki Rani, Garima Rani and Tapan Sarker
The current study aims to identify the impact of financial literacy, financial risk-tolerance, financial socialization, financial stress, socio-demographic factors and financial…
Abstract
Purpose
The current study aims to identify the impact of financial literacy, financial risk-tolerance, financial socialization, financial stress, socio-demographic factors and financial behavior on the individual financial wellbeing residing in India's National Capital Region (NCR) region. Understanding financial wellbeing is crucial as it helps individuals understand personal finance better and develop a more favorable financial attitude. The information can depict individuals' financial skills, knowledge and attitudes toward achieving financial wellbeing in emerging economies.
Design/methodology/approach
Through self-administered survey questionnaires, data are obtained using convenience sampling from 420 (394) respondents regarding individual financial wellbeing levels in India. The survey responses were collected between May 2022 and July 2022. The authors use the “partial least squares structural equation modeling” (PLS-SEM) technique to test the research hypotheses.
Findings
The present study's outcome confirms that five determinants, such as financial literacy, financial risk-tolerance, financial socialization, financial stress and socio-demographic factors, significantly influence the financial behavior of individuals. Further, financial behavior, financial literacy, financial risk-tolerance and financial socialization significantly influence financial wellbeing. However, financial stress and socio-demographic factors have statistically insignificant impacts on financial wellbeing.
Originality/value
The present study is exclusive in which an effort is being made to acquire relative importance on financial behavior and an individual's financial wellbeing. The present paper will help the government, financial services providers, and policymakers in offering innovative economic schemes and designing policies that may enhance the financial wellbeing of individuals. Finally, this article provides the road map for future research in this field.
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Attiya Waris and Laila Abdul Latif
The article aims to rely on the global wealth chains theory to study the effect of tax amnesty on anti-money laundering (AML) in Bangladesh. This theory is an analytical framework…
Abstract
Purpose
The article aims to rely on the global wealth chains theory to study the effect of tax amnesty on anti-money laundering (AML) in Bangladesh. This theory is an analytical framework intended to identify how wealth is repackaged and disguised to move it out of spheres of state oversight, regulation and taxation. It introduces the law on AML in Bangladesh, pointing out the revised Financial Action Task Force (FATF) recommendation that has expanded the scope of money laundering predicate offences to cover both indirect and direct tax crimes and smuggling in relation to customs and excise duties and taxes.
Design/methodology/approach
Interviews in Bangladesh and desk research.
Findings
There are some gaps in the scope of the offence, the coverage of predicate offences and the types of property covered by the money laundering offence. There is also an absence of financial penalties available to effectively sanction legal persons. The current money laundering offences are derived from the ordinance issued in 2008 by the caretaker government (2006-2008). The current act contains detailed definitions of money laundering and property and a list of predicate offences and sanctions for the offence. However, there are some gaps in the physical elements of the offence, and the range of its predicate offences remains too narrow. Adding tax evasion to its list of predicate offences will, given the history of money laundering in Bangladesh, aid in combating illegal transfer of assets abroad and recovery of the same and abolish tax amnesty.
Originality/value
There is no paper that has analysed the linkages between money laundering and taxation in developing countries, especially Bangladesh.
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Mentoring is an intense relationship between a senior experienced individual who is the mentor and a less experienced individual who is the protégé. Mentors provide counselling…
Abstract
Mentoring is an intense relationship between a senior experienced individual who is the mentor and a less experienced individual who is the protégé. Mentors provide counselling, guidance, advice, support and feedback for the protégé's personal and professional development. With the well-being of the family as the central issue in family firms, mentoring is often seen to be akin to a parent–child relationship. In Bangladesh, paternalistic and informal parental mentoring is the norm for grooming children both morally and professionally. Using six caselets of large family firms of Bangladesh, this chapter provides insight into the paternalistic style of mentoring, and also the generational differences in mentoring between the firm's owner and his successor.
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Hind Dheyaa Abdulrasool and Khawla Radi Athab Al-Shimmery
Implementing the 17 Sustainable Development Goals (SDGs) unarguably demands huge financial investments. However, the United Nations has acknowledged the huge financial gap…
Abstract
Implementing the 17 Sustainable Development Goals (SDGs) unarguably demands huge financial investments. However, the United Nations has acknowledged the huge financial gap militating against the implementation of the SDGs worldwide, leading experts to question the possibility of complete implementation of the goals by their terminal dateline of 2030. While the bulk of the finance currently outlaid on the SDGs comes from traditional sources including foreign direct investments (FDIs), there is the need to focus more attention on developing and exploiting impact investments that are more suitable for financing development programmes and projects. In this chapter, the SDG implementation profiles of the 12 Arab West Asia countries concerning the five most targeted SDGs were evaluated and sustainable finance issues were discussed. Secondary data were retrieved from World Bank's DataBank. The data were descriptively analyzed. Based on the profiles generated, debt relief is put forward as a possible impact investment mechanism suitable for funding the SDGs. Specifically, this chapter recommends that outright cancellation of debts based on the debt-for-SGD swap could serve as some of the impact investments needed to boost the global drive for a developed, peaceful, and just world.
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The study aims to identify the areas of flood susceptibility and to categorize the Gangarampur sub-division into various flood susceptibility zones. It also aspires to evaluate…
Abstract
Purpose
The study aims to identify the areas of flood susceptibility and to categorize the Gangarampur sub-division into various flood susceptibility zones. It also aspires to evaluate the efficacy of integrating Geographic Information Systems (GIS) with Artificial Neural Networks (ANN) for flood susceptibility analysis.
Design/methodology/approach
The factors contributing to floods such as rainfall, geomorphology, geo-hazard, elevation, stream density, land use and land cover, slope, distance from roads, Normalized Difference Water Index (NDWI) and distance from rivers were analyzed for flood susceptibility analysis. The use of the ANN model helps to construct the flood susceptibility map of the study area. For validating the outcome, the Receiver Operating Characteristic (ROC) is employed.
Findings
The results indicated that proximity to rivers, rainfall deviation, land use and land cover are the most significant factors influencing flood occurrence in the study area. The ANN model demonstrated a prediction accuracy of 85%, validating its effectiveness for flood susceptibility analysis.
Originality/value
The research offers a novel approach by integrating Geographic Information Systems (GIS) with Artificial Neural Networks (ANN) for flood susceptibility analysis in the Gangarampur sub-division. By identifying key factors such as proximity to rivers, rainfall deviation and land use, the study achieves 85% prediction accuracy, showing the effectiveness of ANN in flood risk mapping. These findings provide critical insights for planners to devise targeted flood mitigation strategies.