Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
2.8
Journals
JRFM
Special Issues
Financial Technologies (Fintech) in Finance and Economics
share announcement

Financial Technologies (Fintech) in Finance and Economics

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Financial Technology and Innovation".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 15042

Special Issue Editor

Dr. Xianrong (Shawn) Zheng

E-Mail Website
Guest Editor
Information Technology & Decision Sciences Department, Old Dominion University, Norfolk, VA 23529, USA
Interests: AI; cloud computing; FinTech
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on “Financial Technologies (Fintech) in Finance and Economics”. Financial technology (Fintech) is one of the most disruptive innovations in IT and finance. Fintech will reshape how the financial services industry is structured and the provisions it offers. It will have transformative impact on financial sectors, including banking, insurance, investments, securities, etc. Fintech nurtures new business models, products, and services, aiming to improve the efficiency of the financial services industry through modern IT. Artificial intelligence (AI), machine learning (ML), deep learning, big data, cloud computing, and blockchain play key roles in fintech.

This Special Issue calls for papers on emerging information technologies in finance and economics. It welcomes research articles that present novel theory, algorithms, systems, and applications of financial information technologies, and encourages submissions from multiple disciplines, including statistics, computer science, information systems, finance, etc. Topics of interest include, but are not limited to, AI in finance, ML in finance, big data in finance, cloud computing in finance, algorithmic trading, smart trading strategies, robo-advisors, blockchain, cryptocurrency, token economics, digital economics, etc.

Dr. Xianrong (Shawn) Zheng
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • financial technologies (Fintech)
  • data science
  • algorithmic trading
  • robo-advisors
  • blockchain
  • cryptocurrency
  • token economics
  • digital economics

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 663 KiB  
Article
Bank Crisis Boosts Bitcoin Price
by Danilo Petti and Ivan Sergio
J. Risk Financial Manag. 2024, 17(4), 134; https://doi.org/10.3390/jrfm17040134 - 22 Mar 2024
Viewed by 910
Abstract
Bitcoin (BTC) represents an emerging asset class, offering investors an alternative avenue for diversification across various units of exchange. The recent global banking crisis of 9 March 2023 has provided an opportunity to reflect on how Bitcoin’s perception as a speculative asset may [...] Read more.
Bitcoin (BTC) represents an emerging asset class, offering investors an alternative avenue for diversification across various units of exchange. The recent global banking crisis of 9 March 2023 has provided an opportunity to reflect on how Bitcoin’s perception as a speculative asset may be evolving. This paper analyzes the volatility behavior of BTC in comparison to gold and the traditional financial market using GARCH models. Additionally, we have developed and incorporated a bank index within our volatility analysis framework, aiming to isolate the impact of financial crises while minimizing idiosyncratic risk. The aim of this work is to understand Bitcoin’s perception among investors and, more importantly, to determine whether BTC can be considered a new asset class. Our findings show that in terms of volatility and price, BTC and gold have responded in very similar ways. Counterintuitively, the financial market seems not to have experienced high volatility and significant price swings in response to the March 9th crisis. This suggests a consumer tendency to seek refuge in both Bitcoin and gold. Full article
(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)
►▼ Show Figures

Figure 1

20 pages, 1251 KiB  
Article
FinTech and Financial Inclusion: Exploring the Mediating Role of Digital Financial Literacy and the Moderating Influence of Perceived Regulatory Support
by Muhammed Basid Amnas, Murugesan Selvam and Satyanarayana Parayitam
J. Risk Financial Manag. 2024, 17(3), 108; https://doi.org/10.3390/jrfm17030108 - 07 Mar 2024
Viewed by 2493
Abstract
Exploring the potential of financial technology (FinTech) to promote financial inclusion is the aim of this research. This study concentrated on understanding why people use FinTech and how it affects their access to financial services by taking into account the mediating role of [...] Read more.
Exploring the potential of financial technology (FinTech) to promote financial inclusion is the aim of this research. This study concentrated on understanding why people use FinTech and how it affects their access to financial services by taking into account the mediating role of digital financial literacy and the moderating effect of perceived regulatory support. This study used partial least squares structural equation modeling (PLS-SEM) for testing the research model by collecting data from 608 FinTech users in India. The results revealed the role of trust, service quality, and perceived security are essential in promoting the utilization of FinTech services. This study also demonstrated that FinTech positively impacts financial inclusion, making it easier for individuals to get into formal financial services. Furthermore, digital financial literacy emerged as an important mediator between FinTech use and financial inclusion. The research also confirmed that perceived regulatory support has a significant moderation influence on the relationship between FinTech and financial inclusion. This research would contribute to advancing theoretical frameworks and offer practical advice for policymakers and FinTech companies to make financial services more inclusive. Full article
(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)
►▼ Show Figures

Figure 1

15 pages, 637 KiB  
Article
The Causal Relationship between FinTech, Financial Inclusion, and Income Inequality in African Economies
by Abebe Gule Girma and Fariz Huseynov
J. Risk Financial Manag. 2024, 17(1), 2; https://doi.org/10.3390/jrfm17010002 - 19 Dec 2023
Viewed by 2448
Abstract
Income inequality is one of the biggest problems affecting developing economies. Market imperfections and information asymmetry lead to lack of access to the financial system, which will exacerbate income inequality. The growing adoption of FinTech (financial technology) has altered the structure of how [...] Read more.
Income inequality is one of the biggest problems affecting developing economies. Market imperfections and information asymmetry lead to lack of access to the financial system, which will exacerbate income inequality. The growing adoption of FinTech (financial technology) has altered the structure of how financial services are delivered and makes these services accessible to underserved groups. This study explores the causal relationship between FinTech development, financial inclusion, and income inequality in a panel study of 29 African countries. We apply pooled OLS regression and structural equation models to samples from the years 2011, 2014, and 2017. The findings indicate that FinTech has a positive and statistically significant effect on financial inclusion and income inequality in African countries. The study results also demonstrate that financial inclusion plays a pivotal mediation role in the negative effect of FinTech on income inequality in African economies. Further, financial inclusion (the ability to create a bank account and borrow money) negatively and significantly affects income inequality in African countries, whereas saving shows a positive and significant impact on income inequality. Overall, our study results suggest that to reduce income inequality and increase the effectiveness of FinTech investments, policymakers in African countries should design proper policies to enhance financial inclusion and offer more accessible and equitable financial services. Full article
(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)
►▼ Show Figures

Figure 1

23 pages, 1420 KiB  
Article
Understanding the Determinants of FinTech Adoption: Integrating UTAUT2 with Trust Theoretic Model
by Muhammed Basid Amnas, Murugesan Selvam, Mariappan Raja, Sakthivel Santhoshkumar and Satyanarayana Parayitam
J. Risk Financial Manag. 2023, 16(12), 505; https://doi.org/10.3390/jrfm16120505 - 06 Dec 2023
Cited by 2 | Viewed by 2995
Abstract
Financial technology (FinTech) is transforming the financial services industry by offering innovative, convenient solutions for businesses and individuals. This study examines the factors influencing FinTech adoption, with a special focus on trust. By integrating insights from both the unified theory of acceptance and [...] Read more.
Financial technology (FinTech) is transforming the financial services industry by offering innovative, convenient solutions for businesses and individuals. This study examines the factors influencing FinTech adoption, with a special focus on trust. By integrating insights from both the unified theory of acceptance and use of technology (UTAUT2), and the trust theoretic model (TTM), this research uncovers critical determinants of FinTech adoption. Utilizing survey responses obtained from 399 participants, this research employs the partial least squares structural equation modelling method. The findings reveal that performance expectancy, effort expectancy, social influence, habit, price value, and facilitating conditions significantly influence users’ intentions to use FinTech services. In addition, the study shows that trust plays a crucial role in FinTech use, as it influences both the intentions to use and the actual use of FinTech. Surprisingly, hedonic motivation was found not to affect users’ intentions, implying that people see FinTech as a practical, rather than enjoyable, endeavor. These insights provide valuable guidance for service providers and policymakers seeking to enhance FinTech adoption and utilization while ensuring the security and trustworthiness of these digital platforms. Full article
(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)
►▼ Show Figures

Figure 1

22 pages, 11557 KiB  
Article
A Hybrid Deep Learning Approach for Crude Oil Price Prediction
by Hind Aldabagh, Xianrong Zheng and Ravi Mukkamala
J. Risk Financial Manag. 2023, 16(12), 503; https://doi.org/10.3390/jrfm16120503 - 06 Dec 2023
Viewed by 1606
Abstract
Crude oil is one of the world’s most important commodities. Its price can affect the global economy, as well as the economies of importing and exporting countries. As a result, forecasting the price of crude oil is essential for investors. However, crude oil [...] Read more.
Crude oil is one of the world’s most important commodities. Its price can affect the global economy, as well as the economies of importing and exporting countries. As a result, forecasting the price of crude oil is essential for investors. However, crude oil price tends to fluctuate considerably during significant world events, such as the COVID-19 pandemic and geopolitical conflicts. In this paper, we propose a deep learning model for forecasting the crude oil price of one-step and multi-step ahead. The model extracts important features that impact crude oil prices and uses them to predict future prices. The prediction model combines convolutional neural networks (CNN) with long short-term memory networks (LSTM). We compared our one-step CNN–LSTM model with other LSTM models, the CNN model, support vector machine (SVM), and the autoregressive integrated moving average (ARIMA) model. Also, we compared our multi-step CNN–LSTM model with LSTM, CNN, and the time series encoder–decoder model. Extensive experiments were conducted using short-, medium-, and long-term price data of one, five, and ten years, respectively. In terms of accuracy, the proposed model outperformed existing models in both one-step and multi-step predictions. Full article
(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)
►▼ Show Figures

Figure 1

24 pages, 569 KiB  
Article
Derivative of Reduced Cumulative Distribution Function and Applications
by Kevin Maritato and Stan Uryasev
J. Risk Financial Manag. 2023, 16(10), 450; https://doi.org/10.3390/jrfm16100450 - 18 Oct 2023
Viewed by 1609
Abstract
The reduced cumulative distribution function (rCDF) is the maximal lower bound for the cumulative distribution function (CDF). It is equivalent to the inverse of the conditional value at risk (CVaR), or one minus the buffered probability of exceedance (bPOE). This paper introduces the [...] Read more.
The reduced cumulative distribution function (rCDF) is the maximal lower bound for the cumulative distribution function (CDF). It is equivalent to the inverse of the conditional value at risk (CVaR), or one minus the buffered probability of exceedance (bPOE). This paper introduces the reduced probability density function (rPDF), the derivative of rCDF. We first explore the relation between rCDF and other risk measures. Then we describe three means of calculating rPDF for a distribution, depending on what is known about the distribution. For functions with a closed-form formula for bPOE, we derive closed-form formulae for rPDF. Further, we describe formulae for rPDF based on a numerical bPOE when there is a closed-form formula for CVaR but no closed-form formula for bPOE. Finally, we give a method for numerically calculating rPDF for an empirical distribution, and compare the results with other methods for known distributions. We conducted a case study and used rPDF for sensitivity analysis and parameter estimation with a method similar to the maximum likelihood method. Full article
(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)
►▼ Show Figures

Figure 1

32 pages, 469 KiB  
Article
The Future of Insurance Intermediation in the Age of the Digital Platform Economy
by Lukas Stricker, Joël Wagner and Angela Zeier Röschmann
J. Risk Financial Manag. 2023, 16(9), 381; https://doi.org/10.3390/jrfm16090381 - 25 Aug 2023
Viewed by 2116
Abstract
Today most insurance is sold by over a million brokers and independent agents acting as intermediaries between the insurance companies and their customers. Digitalization and changing customer behavior have fostered the development of insurtech businesses, and, more recently, multi-sided platforms are emerging as [...] Read more.
Today most insurance is sold by over a million brokers and independent agents acting as intermediaries between the insurance companies and their customers. Digitalization and changing customer behavior have fostered the development of insurtech businesses, and, more recently, multi-sided platforms are emerging as new market forms for insurance intermediation. This paper aims to provide a better understanding of how the emergence of the platform economy, with a market dominated by multi-sided platforms, will potentially impact insurance intermediation in the future. Using inductive content analysis on the results of a systematic literature review of the body of research on insurance intermediation, we identify the key functional roles fulfilled by insurance intermediaries. Applying these roles to a literature review on multi-sided platforms allows us to compare how different market forms and players embody the functional roles of intermediaries. Our findings suggest that multi-sided platforms are better able to perform certain roles in terms of agility, scale and scope, and we discuss the future role of platforms in insurance intermediation. Full article
(This article belongs to the Special Issue Financial Technologies (Fintech) in Finance and Economics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop