Template-Type: ReDIF-Article 1.0
Author-Name: Timcy Sachdeva
Author-X-Name-First: Timcy
Author-X-Name-Last: Sachdeva
Title: Estimating bitcoin and traded asset classes volatility using GARCH model
Abstract:
Bitcoin is the world's first cryptocurrency which has largest market capitalization. The study aims to analyze the risk measures for the bitcoin and comparing with tradable asset classes that include the Standard and Poor's BSE 500, USD, Euro, GBP and the Gold future prices. The study uses the GARCH models to identify the components of world economies that bitcoin is sensitive too as against variables that impact the global financial prudence. The empirical results of the study reveal that against dollar and euro exchange rates bitcoin returns are more sensitive. Bitcoin can be used together with gold to diversify or eliminate explicit market risks. The study presents reasonable justification over the development and relationship between bitcoin and different traded assets that pose new challenges before the global investors. The implication of this paper for the strategic policy makers shows the sensitivity among tradeable assets.
Journal: Int. J. of Electronic Finance
Pages: 131-144
Issue: 3
Volume: 10
Year: 2021
Keywords: bitcoin; BTC; traded asset classes; volatility; hedging; GARCH model; FinTech; gold.
File-URL: http://www.inderscience.com/link.php?id=115637
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:3:p:131-144

Template-Type: ReDIF-Article 1.0
Author-Name: Faheem Masoodi
Author-X-Name-First: Faheem
Author-X-Name-Last: Masoodi
Author-Name: Bilal Ahmed Pandow
Author-X-Name-First: Bilal Ahmed
Author-X-Name-Last: Pandow
Title: Internet of things: financial perspective and its associated security concerns
Abstract:
The internet of things (IoT) has expanded at a very rapid rate over the last decade and revolutionised much of internet and devices technologies. Though much of transformation was driven by IoT, however, its implementation, security issues and other associated aspects still remain a matter of concern. The literature on the financial aspect of IoT is very scarce and this paper aims to fill this void and provide financial perspectives on IoT. The analysis of IoT banking and financial services industry is projected to expand from $249.5 million to USD2.03 billion by 2023: eight-time rise or a compound annual growth rate (CAGR) of around 52%. Furthermore, it was noted that the financial results of selected IoT firms had seen decent development over the past many years. In addition, there are several mergers and acquisitions in the IoT market, culminating in USD75.44 billion increase in the sector. One of the major challenges in IoT implementation in the financial industry is security and privacy. The inherent vulnerabilities in IoT devices can be exploited by the attacker, which makes it increasingly onerous for financial services firms to safeguard the system against phishing, data breaches, ransomware and other attacks.
Journal: Int. J. of Electronic Finance
Pages: 145-158
Issue: 3
Volume: 10
Year: 2021
Keywords: internet; security; internet of things; IoT; finance.
File-URL: http://www.inderscience.com/link.php?id=115644
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:3:p:145-158

Template-Type: ReDIF-Article 1.0
Author-Name: Bhoomika Trehan
Author-X-Name-First: Bhoomika
Author-X-Name-Last: Trehan
Author-Name: Amit Kumar Sinha
Author-X-Name-First: Amit Kumar
Author-X-Name-Last: Sinha
Title: A study of confirmation bias among online investors in virtual communities
Abstract:
The purpose of this study is to investigate the existence of confirmation bias among online investors participating in virtual communities. It further examines the factors such as perceived knowledge, investment experience, and gender that influence the confirmation bias. In the virtual communities, two types of participants were identified 'knowledge seekers' and 'knowledge contributors'. An online survey was conducted using structured questionnaire and the data was analysed with the application of relevant statistical tools. Investment-related virtual communities were found to be a great source of stock market-related news and investment ideas. The findings indicate that online investors exhibit confirmation bias as they join virtual communities to seek information that confirms their previous beliefs and opinions. The data was collected from online chat rooms where online investors interact and discuss investment trades. As many investors invest online without taking financial advice and guidance, their investment choices depend on their instinct and knowledge. Therefore, this study is of immense importance for both investors and investment advisors.
Journal: Int. J. of Electronic Finance
Pages: 159-179
Issue: 3
Volume: 10
Year: 2021
Keywords: behavioural biases; confirmation bias; decision-making process; gender; investment experience; online investors; overconfidence; perceived knowledge; psychology; virtual communities.
File-URL: http://www.inderscience.com/link.php?id=115647
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:3:p:159-179

Template-Type: ReDIF-Article 1.0
Author-Name: G. Naresh
Author-X-Name-First: G.
Author-X-Name-Last: Naresh
Author-Name: S. Ananda
Author-X-Name-First: S.
Author-X-Name-Last: Ananda
Title: Bitcoin prices and rupee-dollar exchange rates during COVID-19
Abstract:
Bitcoin is the primary cryptocurrency in the world that can be stored and traded through the internet. Digital contracts and cryptocurrencies created on blockchains have now been used in exchanging instruments on the networks and are available online readily. This paper's main objective is to investigate the causal relationship between bitcoin prices and rupee-US dollar exchange during COVID-19. The study used the Granger causality model to study the price behaviour of bitcoin and the rupee-dollar exchange rate. The study found an unidirectional Granger causality existed, where the rupee-US dollar exchange rate affected the bitcoin price in the Indian market during COVID-19. The bitcoins are widely considered as an investment asset in Indian markets, and the rupee-dollar exchange rate has a significant impact on the bitcoin prices.
Journal: Int. J. of Electronic Finance
Pages: 180-190
Issue: 3
Volume: 10
Year: 2021
Keywords: bitcoin; cryptocurrency; fiat currency; crypto assets; exchange rate; stock exchange; investment; portfolio; COVID-19; causality; bitcoin prices; rupee-dollar exchange rate; Granger causality.
File-URL: http://www.inderscience.com/link.php?id=115661
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:3:p:180-190

Template-Type: ReDIF-Article 1.0
Author-Name: Ashutosh Upadhyay
Author-X-Name-First: Ashutosh
Author-X-Name-Last: Upadhyay
Author-Name: Kalluru Siva Reddy
Author-X-Name-First: Kalluru Siva
Author-X-Name-Last: Reddy
Title: Digital financial inclusion - demand side vs. supply side approach
Abstract:
This paper explores the measurement of digital financial inclusion (DFI) in India by analysing the parameters such as per capita bank accounts, cards, retail payment systems, internet and broadband connections from both the supply side and demand side data. We observe substantial gaps in the level of DFI brought out by these two datasets, with the supply side seeming to overestimate the level of digital financial inclusion. We also propose a theoretical model for equilibrium in demand and supply sides of DFI. Supply of DFI is divided into two components of 'autonomous' and 'induced' supply. We find that demand for and (induced) supply of DFI is directly proportional to the income level of users and the incentives provided for the usage of DFI products/services. For a sustainable model of DFI, both the demand and supply sides should balance and complement each other, and supply-side infrastructure should be available and scalable, to meet a higher level of demand for DFI.
Journal: Int. J. of Electronic Finance
Pages: 191-210
Issue: 3
Volume: 10
Year: 2021
Keywords: payment systems; digital financial inclusion; DFI; demand side; supply side; central bank policies; income; incentives.
File-URL: http://www.inderscience.com/link.php?id=115664
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:3:p:191-210

Template-Type: ReDIF-Article 1.0
Author-Name: Kanokkarn Snae Namahoot
Author-X-Name-First: Kanokkarn Snae
Author-X-Name-Last: Namahoot
Author-Name: Viphasiri Jantasri
Author-X-Name-First: Viphasiri
Author-X-Name-Last: Jantasri
Title: Forecasting the stock exchange of Thailand using data mining techniques
Abstract:
The stock price index movement is regarded as a challenging task of financial time-series prediction. An accurate forecasting of stock price movement may yield profits for investors. Due to the complexity of stock market data, predicting it is very difficult. This study attempted to develop three efficient predictive models and compared their performances in the daily stock exchange market of Thailand (SET). These models are based on three classification techniques: the uses of linear regression, decision trees, and artificial neural networks (ANN). Thirteen technical indicators were selected as inputs for the proposed models. Three comprehensive parameter settings in the experiments were performed. Experimental results showed that average performance of the ANN model (89.79%) was found to be significantly better than that of the linear regression (89.74%) and decision tree models (88.07%). Consequentially, this research demonstrates rule extraction as a post-processing technique for improving prediction accuracy and for explaining the logic to financial decision makers.
Journal: Int. J. of Electronic Finance
Pages: 211-231
Issue: 4
Volume: 10
Year: 2021
Keywords: data mining; linear regression; neural networks; decision tree; scaled conjugate gradient; SCG; stock exchange; Thailand; artificial neural networks; ANN; Stock Exchange of Thailand; SET.
File-URL: http://www.inderscience.com/link.php?id=119777
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:4:p:211-231

Template-Type: ReDIF-Article 1.0
Author-Name: Sahar Loukil
Author-X-Name-First: Sahar
Author-X-Name-Last: Loukil
Author-Name: Mouna Aloui
Author-X-Name-First: Mouna
Author-X-Name-Last: Aloui
Author-Name: Ahmed Jeribi
Author-X-Name-First: Ahmed
Author-X-Name-Last: Jeribi
Author-Name: Anis Jarboui
Author-X-Name-First: Anis
Author-X-Name-Last: Jarboui
Title: Are digital assets backstops for GCC stock markets in COVID-19-led financial crisis?
Abstract:
This study examines the safe haven properties of top five crypto-currencies, oil and gold for the five gulf cooperation council countries in view of COVID-19 period through a nonlinear and asymmetric framework NARDL methodology to uncover short- and long-run asymmetries. Using daily data from January 2019 to April 2020, we find that Bitcoin and Ethereum are safe haven assets for GCC in instability; Bitcoin is a safe haven for Oman, Saudi Arabia and Abu Dhabi. Ethereum is a safe haven for Bahrain, Kuwait and Qatar. Further, for Kuwait, Qatar, Saudi Arabia and Abu Dhabi, oil is a safe haven asset in mitigated period. We also notice that the strategies of hiding differ interestingly for all countries except for Saudi Arabia that does not significantly change its strategies. Thus, portfolio managers may consider few eligible crypto-currencies and oil for their inclusion into the portfolio to hedge risk. While, speculators acting in both stock and crypto market may go for a spread strategy. Our research is useful for portfolio managers and financial advisors looking for the best of crypto's, gold and oil to hedge shocks in stock market indices.
Journal: Int. J. of Electronic Finance
Pages: 232-259
Issue: 4
Volume: 10
Year: 2021
Keywords: cointegration; asymmetry; nonlinearity; GCC; stock market; oil; gold; crypto-currencies.
File-URL: http://www.inderscience.com/link.php?id=119782
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:4:p:232-259

Template-Type: ReDIF-Article 1.0
Author-Name: Nathan Keeton
Author-X-Name-First: Nathan
Author-X-Name-Last: Keeton
Author-Name: June Wei
Author-X-Name-First: June
Author-X-Name-Last: Wei
Title: Development of a framework for GPS-based mobile shopping systems
Abstract:
This paper aims at developing a user-friendly mobile framework to guide mobile shopping via the guided position system (GPS) technology. Specifically, it first studied usability features that are crucial to mobile shopping via GPS by developing a framework with integrated user-friendly features. Second, 23 data flows are mapped and identified based on the framework to illustrate how to integrate these usability features into development. Third, the system analysis is performed based on both dynamic modelling (using data flow diagramming) and static modelling (using entity-relation diagramming). Fourth, the system design including database design and user interface design are performed. Finally, a prototype is developed with usability testing. This study concludes that the mobile shopping guided by GPS with usability emphasis is crucial to develop the efficient mobile shopping systems.
Journal: Int. J. of Electronic Finance
Pages: 270-284
Issue: 4
Volume: 10
Year: 2021
Keywords: guided position system; GPS; data flow diagram; guided mobile shopping.
File-URL: http://www.inderscience.com/link.php?id=119784
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:4:p:270-284

Template-Type: ReDIF-Article 1.0
Author-Name: S. Mahalakshmi
Author-X-Name-First: S.
Author-X-Name-Last: Mahalakshmi
Author-Name: S. Thiyagarajan
Author-X-Name-First: S.
Author-X-Name-Last: Thiyagarajan
Author-Name: G. Naresh
Author-X-Name-First: G.
Author-X-Name-Last: Naresh
Title: Financialisation of agricultural commodity and its trading during COVID-19 pandemic
Abstract:
The establishment of regularised trading exchanges for agricultural commodities attracted every market participant to benefit from their trade. The pandemic has created massive chaos in every asset class, and agri-commodities are no exception. However, the pandemic also taught lessons for the global traders to focus on food produce. Therefore, this paper intends to look at agricultural commodity trading behaviour during this COVID-19 pandemic by looking at the movement of the trade in the agri-futures index and other asset classes, including equity, exchange rates, bullion prices, etc. The results show that all the selected asset classes except the exchange rate are influencing Agridex. In addition, the Agridex returns are influenced by the severity of COVID-19 cases. Therefore, the policymakers should keep this in mind and work to prevent the price rise to an uncontrollable extent because this can lead to stagflation.
Journal: Int. J. of Electronic Finance
Pages: 260-269
Issue: 4
Volume: 10
Year: 2021
Keywords: agricultural futures index; commodity; futures; assets; volatility; COVID-19.
File-URL: http://www.inderscience.com/link.php?id=119785
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:4:p:260-269

Template-Type: ReDIF-Article 1.0
Author-Name: Jason Lim Chiu
Author-X-Name-First: Jason Lim
Author-X-Name-Last: Chiu
Author-Name: Karl Manuel Amistoso Gonzales
Author-X-Name-First: Karl Manuel Amistoso
Author-X-Name-Last: Gonzales
Author-Name: Cyril Mae Estipona Lopez
Author-X-Name-First: Cyril Mae Estipona
Author-X-Name-Last: Lopez
Title: The effects of acculturation on expatriate workers' motivation and intention to stay
Abstract:
With the rising demand for globalisation, many organisations are now enforcing different strategies and measurements to maintain their competitive advantage in the international market. Expatriation has become a global trend due to the continuous demand for talents, skills, and knowledge worldwide and other reasons due to financial needs. This study aims to identify the effects of the four acculturation strategies on the expatriate workers' assimilation, integration, separation, and marginalisation, and their impact on the motivation and intention to stay of the expatriate workers in their organisation. Alderfer's ERG theory of motivation was used to support this study as motivation can simultaneously reach multiple levels of need. The hayes process macro was applied to determine the relationship between the variables of this research paper. The research findings showed that expatriate workers whose acculturation is more on assimilation and marginalisation strategy have higher motivation and intention to stay in the organisation.
Journal: Int. J. of Electronic Finance
Pages: 285-305
Issue: 4
Volume: 10
Year: 2021
Keywords: acculturation strategies; expatriate workers; motivation; intention to stay.
File-URL: http://www.inderscience.com/link.php?id=119786
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Handle: RePEc:ids:ijelfi:v:10:y:2021:i:4:p:285-305