Crypto-currency: Is the future dark or bright?

Javed, Mohd; Husain, Rehan; Azam, Mohammad Khalid

doi:10.1080/02522667.2019.1641894

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…Zarifis and Cheng (2022) have proposed that the presence of risk, whether in the realm of Fintech or e-commerce, has a positive influence on their demand, noting a similarity in the nature of risks within both domains. Building upon this, Xie et al (2021) have contended that perceived risk stands as one of the most Religious OrientaƟon critical factors that can exert a negative impact on Fintech adoption (Yousuf Javed et al, 2019). Lee and Allaway (2002) have posited that technology garners acceptance among individuals when they possess a clear understanding of its use and feel in control of their needs in its context.…”

Section: Perceived Risk and Adoption Of Islamic Fintechmentioning

confidence: 99%

Exploring the moderating role of religious orientation on Islamic Fintech adoption

Alsmadi

2024

IMEFM

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Purpose This paper aims to delve into the factors influencing the adoption of Islamic Fintech and investigates the potential impact of Religious Orientation. Design/methodology/approach The study uses a questionnaire to collect data from 291 Jordanians, using Structural Equation Model – Partial Least Squares (SEM-PLS) to evaluate the research model and test hypotheses. Findings The outcomes of the Smart PLS path analysis revealed that several factors significantly influence the adoption of Islamic Fintech. Notably, perceived risk, financial literacy, trust and convenience were identified as pivotal determinants in shaping individuals' decisions to adopt Islamic Fintech. Additionally, the study unveils the noteworthy role of religious orientation as a moderator, impacting the relationship between perceived risk, financial literacy, trust and convenience concerning the adoption of Islamic Fintech. Originality/value This study contributes fresh insights to the existing literature concerning the adoption of Islamic Fintech, enhancing the understanding of the key drivers in this domain. Furthermore, it emphasizes the practical implications of religious orientation in shaping individuals' attitudes and behaviors pertaining to Islamic Fintech adoption.

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Section: Perceived Risk and Adoption Of Islamic Fintechmentioning

confidence: 99%

Exploring the moderating role of religious orientation on Islamic Fintech adoption

Alsmadi

2024

IMEFM

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“…The ADF trial involves regressing the time series on its lagged values and possibly on the differenced series. The test statistic is then computed, and its p-value is compared to the chosen significance level (Yousuf Javed et al, 2019). The ADF test uses various statistical software packages like Python (with libraries like StatsModels), R, or specialised econometrics software.…”

Section: Augmented Dickey-fuller (Adf) Testmentioning

confidence: 99%

A comparative analysis of Silverkite and inter-dependent deep learning models for bitcoin price prediction

Tripathy,

Nayak,

Prusty

2024

Front. Blockchain

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These days, there is a lot of demand for cryptocurrencies, and investors are essentially investing in them. The fact that there are already over 6,000 cryptocurrencies in use worldwide because of this, investors with regular incomes put money into promising cryptocurrencies that have low market values. Accurate pricing forecasting is necessary to build profitable trading strategies because of the unique characteristics and volatility of cryptocurrencies. For consistent forecasting accuracy in an unknown price range, a variation point detection technique is employed. Due to its bidirectional nature, a Bi-LSTM appropriate for recording long-term dependencies in data that is sequential. Accurate forecasting in the cryptocurrency space depends on identifying these connections, since values are subject to change over time due to a variety of causes. In this work, we employ four deep learning-based models that are LSTM, FB-Prophet, LSTM-GRU and Bidirectional-LSTM(Bi-LSTM) and these four models are compared with Silverkite. Silverkite is the main algorithm of the Python library Graykite by LinkedIn. Using historical bitcoin data from 2012 to 2021, we utilized to analyse the models’ mean absolute error (MAE) and root mean square error (RMSE). The Bi-LSTM model performs better than others, with a mean absolute error (MAE) of 0.633 and a root mean square error (RMSE) of 0.815. The conclusion has significant ramifications for bitcoin investors and industry experts.

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“…Regulation from the RBI would mean that individuals' trust is being extended to a market which is being looked over and is also of use to the individuals. The Government of India along with the RBI must make information and general awareness about cryptocurrency available to the public (Javed, et. al, 2019) 12 .…”

Section: Implications For the Reserve Bank Of Indiamentioning

confidence: 99%

An Opinion-based research on Cryptocurrency and it's functioning in India.

Dhond,

Gangakhedkarr,

Siddanagowder

2023

IJOES

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This paper aims to analyse the crypto market in India from the viewpoint of consumers who could potentially trade in these markets and extend the extent of their behaviour to the importance of a regulatory body within the economy. The central idea of this paper is to estimate the importance of a central bank in the minds of people and how it affects their trust on a currency which is unregulated. This forms the first tier of the paper In order to get insight into the more technical dynamics of cryptocurrencies, the paper then studies cryptocurrency from the point of view of experts who explain the different dimensions of the crypto markets. This forms the second tier of the paper. The paper aims to analyse from the surveys conducted and the available literature, the nature of the crypto market in India with a more reporting approach than a problem-solving model. The research is based on primary data collected by means of surveys and structured interviews. These are termed as the two tiers in the paper. Using quantitative statistical analysis to find the common trend of the sample and a descriptive approach for the analysis of the interviews, the paper examines how the two tiers behave single-handedly and their dynamic when they interact.

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Crypto-currency: Is the future dark or bright?

Cited by 6 publications

References 8 publications

Exploring the moderating role of religious orientation on Islamic Fintech adoption

Exploring the moderating role of religious orientation on Islamic Fintech adoption

A comparative analysis of Silverkite and inter-dependent deep learning models for bitcoin price prediction

An Opinion-based research on Cryptocurrency and it's functioning in India.

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