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Fintech: Recent Advancements in Modern Techniques, Methods and Real-World Solutions

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 9352

Special Issue Editors


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Guest Editor
Department of Operations and Information Management, Aston Business School, Aston University, Birmingham B4 7ET, UK
Interests: fintech; data science; Internet of Things; cloud/fog/edge computing and security with risk
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institute for Future Transport and Cities, Coventry University, Priory St, Coventry CV1 5FB, UK
Interests: Big Data Analytics, Internet of Things (IoT), Information Retrieval, Computer Vision, Artificial Intelligence and Energy Efficient Communication Protocols

Special Issue Information

Dear Colleagues,

Finance Technology (FinTech) is an advanced business model that adopts emerging technology to improve efficiency and manage risk in the finance field. These new technologies, such as Blockchain, Machine Learning, Big Data, and Cloud Computing, positively contribute to reform the process of the traditional finance industry and provide an optimal paradigm for finance enterprises. Meanwhile, there are several emerging companies focused on supplying fintech services, which fascinate investors with optimistic expectations about the firms' valuation and a promising future. The scientific procedure of appraising the effectiveness and practicability of FinTech has a crucial role because it could lead to a guideline for understanding and further improving the development of financial technologies.

Nowadays, the compositions of FinTech have been consistently increasing and a growing number of financial scenarios require the intervention of these advanced technologies in order to cut down costs and increase output. This Special Issue aims to seek original contributions demonstrating the significant advancements and innovations of FinTech, the successful implementation for new technologies in the finance industry, and effective valuation theories conducted in FinTech enterprises.

This Special Issue is focused on but not limited to the following topics:

  • Financial modeling, financial process modeling, and financial risk analysis for FinTech
  • Risk management and control for FinTech
  • Algorithms, software engineering, and development for FinTech
  • System design and implementation for FinTech
  • Testing (software engineering; penetration; product development) for FinTech
  • Proofs-of-concept for FinTech
  • Risk Modeling, business process modeling, and analytics for FinTech
  • Trust and privacy for FinTech
  • Quantitative analysis and regression for FinTech
  • Case studies for FinTech
 
For general queries, you can contact [email protected].

 

Prof. Dr. Victor Chang
Prof. Rahat Iqbal
Guest Editors

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • finance technology
  • company valuation
  • blockchain
  • machine learning
  • risk management

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Published Papers (1 paper)

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Research

22 pages, 758 KiB  
Article
Empirical Research on the Fama-French Three-Factor Model and a Sentiment-Related Four-Factor Model in the Chinese Blockchain Industry
by Ziyang Ji, Victor Chang, Hao Lan, Ching-Hsien Robert Hsu and Raul Valverde
Sustainability 2020, 12(12), 5170; https://doi.org/10.3390/su12125170 - 24 Jun 2020
Cited by 18 | Viewed by 7999
Abstract
As one of the most significant components of financial technology (FinTech), blockchain technology arouses the interests of numerous investors in China, and the number of companies engaged in this field rises rapidly. The emotion of investors has an effect on stock returns, which [...] Read more.
As one of the most significant components of financial technology (FinTech), blockchain technology arouses the interests of numerous investors in China, and the number of companies engaged in this field rises rapidly. The emotion of investors has an effect on stock returns, which is a hot topic in behavioral finance. Blockchain is an essential part of FinTech, and with the fast development of this technology, investors’ sentiment varies as well. The online information that directly reflects investors’ mood could be utilized for mining and quantifying to construct a sentiment index. For a better understanding of how well some factors adequately explain the return of stocks related to blockchain companies in the Chinese stock market, the Fama-French three-factor model (FFTFM) will be introduced in this paper. Furthermore, sentiment could be a new independent variable to enhance the explanatory power of the FFTFM. A comparison between those two models reveals that the sentiment factor could raise the explanatory power. The results also indicate that the Chinses blockchain industry does not own the size effect and book-to-market effect. Full article
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