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The Future and Sustainability of Financial Markets

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 23991

Special Issue Editor


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Guest Editor
College of Economics, Sungkyunkwan University, Seoul 03063, Korea
Interests: financial economics

Special Issue Information

Dear Colleagues,

In the era of the 4th Industrial revolution, global and local financial markets are experiencing significant changes and innovations. Both the academic community and financial industry are confronting great challenges. Researchers have started to focus on interdisciplinary studies and market experts consider sustainable finance by applying new technology to financial markets. Existing financial theories examine the issues of asset pricing, market microstructure, and corporate finance using the classical economic frameworks and methodologies. The majority of empirical finance studies test the theories using the developed market dataset and mainboard market data. To expand our knowledge on the new trends of finance, we need to focus on the recent innovations on fintech and artificial intelligence. We also need to expand research to emerging markets, small/start-up firms, and big data. Motivated by these demands and new trends of financial research, we are inviting papers for this Special Issue, “The Future and Sustainability of Financial Markets”. Topics of the papers may include (but are not limited to) interdisciplinary studies on fintech, big data, block-chain, machine-learning applications for finance, cryptocurrency, crowdfunding, sustainable finance, small and start-up companies, emerging and transitional economies, and emerging financial markets. We encourage you to submit not only purely academic papers but also practical papers with policy implications.

Prof. Doojin Ryu
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. 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

  • fintech
  • big data
  • block-chain
  • machine-learning applications for finance
  • cryptocurrency
  • crowdfunding
  • sustainable finance
  • small and start-up companies
  • emerging and transitional economies
  • emerging financial markets

Published Papers (8 papers)

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Research

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15 pages, 1568 KiB  
Article
Risks in Major Cryptocurrency Markets: Modeling the Dual Long Memory Property and Structural Breaks
by Zhuhua Jiang, Walid Mensi and Seong-Min Yoon
Sustainability 2023, 15(3), 2193; https://doi.org/10.3390/su15032193 - 24 Jan 2023
Cited by 2 | Viewed by 1313
Abstract
This study estimates the effects of the dual long memory property and structural breaks on the persistence level of six major cryptocurrency markets. We apply the Bai and Perron structural break test, Inclán and Tiao’s iterated cumulative sum of squares (ICSS) algorithm, and [...] Read more.
This study estimates the effects of the dual long memory property and structural breaks on the persistence level of six major cryptocurrency markets. We apply the Bai and Perron structural break test, Inclán and Tiao’s iterated cumulative sum of squares (ICSS) algorithm, and the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model, with different distributions. The results show that long memory and structural breaks characterize the conditional volatility of cryptocurrency markets, confirming our hypothesis that ignoring structural breaks leads to an underestimation of the persistence of volatility modeling. The ARFIMA-FIGARCH model, with structural breaks and a skewed Student-t distribution, fits the cryptocurrency market’s price dynamics well. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
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16 pages, 1390 KiB  
Article
Nonlinear Influence of Financial Technology on Regional Innovation Capability: Based on the Threshold Effect Analysis of Human Capital
by Wei Han, Ping Wang, Yushi Jiang and Hao Han
Sustainability 2022, 14(2), 1007; https://doi.org/10.3390/su14021007 - 17 Jan 2022
Cited by 5 | Viewed by 1797
Abstract
According to the data of financial technology and high-tech innovation level of 17 cities in the pilot area of China Independent Innovation Demonstration Zone (Shandong Province) from 2007 to 2017, and taking human capital as the threshold variable, this paper empirically analyzes the [...] Read more.
According to the data of financial technology and high-tech innovation level of 17 cities in the pilot area of China Independent Innovation Demonstration Zone (Shandong Province) from 2007 to 2017, and taking human capital as the threshold variable, this paper empirically analyzes the nonlinear influence of financial technology development on regional innovation capability under different absorptive capacity by constructing a panel threshold regression model. The results show that: (1) Taking human capital endowment as the threshold variable, the influence mechanism of financial technology development on regional innovation capability has an inverted S-shaped double threshold effect, that is, the driving effect of financial technology development on regional innovation capability has the “optimal range” of human capital absorption capability; (2) When the endowment of human capital is less than the first threshold, there is a significant negative relationship between financial technology and regional innovation capability, and in this case, financial technology development cannot promote the improvement of regional innovation capability; (3) When the human capital endowment crosses the first threshold, there is a significant positive relationship between the development of financial science and technology and the regional innovation capability, which indicates that only when the human capital endowment can better realize R&D learning, digestion and absorption can the development of financial science and technology achieve collaborative innovation and enhance the regional innovation capability; (4) After the endowment of human capital crosses the second threshold, although there is still a positive relationship between the development of financial technology and regional innovation capability, the driving effect of financial technology has a diminishing marginal effect, which shows that the scale of technology and finance should match with human capital, and unlimited expansion of human capital investment will also lead to the imbalance of the allocation of innovation elements and reduce the efficiency of regional innovation. Based on the empirical analysis results, the paper finally puts forward policy suggestions from the aspects of differentiated development strategy, innovative talent incentive policy, and the construction of financial technology leading center. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
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16 pages, 2652 KiB  
Article
Non-Traditional Systemic Risk Contagion within the Chinese Banking Industry
by Tonmoy Choudhury, Simone Scagnelli, Jaime Yong and Zhaoyong Zhang
Sustainability 2021, 13(14), 7954; https://doi.org/10.3390/su13147954 - 16 Jul 2021
Cited by 7 | Viewed by 2021
Abstract
Systemic risk contagion is a key issue in the banking sector in maintaining financial system stability. This study is among the first few to use three different distance-to-risk measures to empirically assess the domestic interbank linkages and systemic contagion risk of the Chinese [...] Read more.
Systemic risk contagion is a key issue in the banking sector in maintaining financial system stability. This study is among the first few to use three different distance-to-risk measures to empirically assess the domestic interbank linkages and systemic contagion risk of the Chinese banking industry, by using bivariate dynamic conditional correlation GARCH model on data collected from eight prominent Chinese banks for the period 2006–2018. The results show a relatively high correlation among almost all the banks, suggesting an interconnectedness among the banks. We found evidence that the banking system is exposed to significant domestic contagion risks arising from systemic defaults. Given that Chinese markets deliver weak signals of forthcoming stress in banking sectors, new policy intervention is crucial to resolve the hidden stress in the system. The results have important policy implications and will provide scholars and policymakers further insight into the risk contagion originating from interbank networks. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
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10 pages, 710 KiB  
Article
Incentive Contracts for Sustainable Growth of Small or Medium-Sized Enterprise
by Daehyeon Park, Jinhyeong Jo and Doojin Ryu
Sustainability 2021, 13(9), 4964; https://doi.org/10.3390/su13094964 - 28 Apr 2021
Cited by 3 | Viewed by 1965
Abstract
This study analyzes incentive contracts in public procurement supply chains using a game-theoretic approach. Specifically, we compare a structure in which the host company is a large enterprise and the partner company is a small or medium-sized enterprise (SME) to a structure in [...] Read more.
This study analyzes incentive contracts in public procurement supply chains using a game-theoretic approach. Specifically, we compare a structure in which the host company is a large enterprise and the partner company is a small or medium-sized enterprise (SME) to a structure in which the host is an SME and the partner is a large enterprise. For each structure, we examine whether an incentive contract improves supply chain performance and confirm that the performance improvement effect is greater when the host company is an SME. Our analysis has several policy implications. SMEs are less likely to be selected as host companies for large-scale procurement projects, limiting their growth opportunities. Thus, to enable SMEs’ sustainable growth through large-scale procurement projects, the governments can allocate a portion of public procurement to SMEs. The introduction of incentive contracts elicits sustainable cooperation from large companies when an SME is the host company in a public procurement supply chain. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
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25 pages, 346 KiB  
Article
Do Cross-Listed Firms Have a Better Governance Structure and Lower Agency Costs? Evidence from Chinese Firms
by Dong-Soon Kim, Eunjung Yeo and Li Zhang
Sustainability 2021, 13(4), 1734; https://doi.org/10.3390/su13041734 - 5 Feb 2021
Cited by 2 | Viewed by 2185
Abstract
This study examines whether an influence from a difference in corporate governance structure exists on firms’ agency costs between Chinese companies cross-listed on the Hong Kong Stock Exchange (HKSE) and those that are domestically listed ones. We determine that, overall, companies with an [...] Read more.
This study examines whether an influence from a difference in corporate governance structure exists on firms’ agency costs between Chinese companies cross-listed on the Hong Kong Stock Exchange (HKSE) and those that are domestically listed ones. We determine that, overall, companies with an HKSE cross-listing had better corporate governance than those without. The corporate governance advantage of the HKSE cross-listed firms holds if we control for firm fixed effects and resolve the potential endogeneity problem between corporate governance and agency costs by using two-stage least square (2SLS) regression analysis with instrumental variables. Specifically, the HKSE cross-listed firms had better corporate governance in terms of board size and institutional ownership. By contrast, domestically listed firms experienced the adverse effects of institutional owner’s roles and higher board pay. The advantages of HKSE cross-listed firms may stem from the benefits of having a larger board size and the effective monitoring of the management by the institutional stockholders. Implications are drawn for the debate on cross-listing and the future challenges of Chinese firms, and a more robust monitoring is necessary for sustainable finance of their stock markets. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
16 pages, 1546 KiB  
Article
Asymmetric Dependence between Oil Prices and Maritime Freight Rates: A Time-Varying Copula Approach
by Ki-Hong Choi and Seong-Min Yoon
Sustainability 2020, 12(24), 10687; https://doi.org/10.3390/su122410687 - 21 Dec 2020
Cited by 10 | Viewed by 3186
Abstract
Changes in crude oil price affect the shipping freight market via three different channels. This study explores the dependence structure between oil prices and maritime freight rates to identify the effective channel. Therefore, it investigates the relationship between oil prices and three major [...] Read more.
Changes in crude oil price affect the shipping freight market via three different channels. This study explores the dependence structure between oil prices and maritime freight rates to identify the effective channel. Therefore, it investigates the relationship between oil prices and three major maritime freight rates; the Baltic Dry Index (BDI), the Baltic Dirty Tanker Index (BDTI), and the Baltic Clean Tanker Index (BCTI). We employ the decomposition method, not studied in the existing literature, and the copula approach which can identify the time-varying effects and asymmetry in the tail dependence structure between oil prices and freight rates. The main results of this analysis are as follows: the decomposed components display different conditional dependence patterns, and asymmetry is revealed in the upper and lower tail dependence. In the long-run, we find more dependence in extreme periods like the financial crises. In short-run fluctuations, we find the dependence increases in an economic boom. The implications of the results suggest that dependence can vary over time and may change depending on extreme events, implying that the complementary strategies should be different the long-run and short-run. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
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12 pages, 592 KiB  
Article
The Perception and Knowledge of Financial Risk of the Portuguese
by Fernando Tavares, Eulália Santos, Vasco Tavares and Vanessa Ratten
Sustainability 2020, 12(19), 8255; https://doi.org/10.3390/su12198255 - 7 Oct 2020
Cited by 8 | Viewed by 2634
Abstract
This study will help academics, researchers, and professionals to better understand how the Portuguese population perceives financial risk. Thus, the main objective of this study is to analyse and compare the perception and knowledge of financial risk by the Portuguese. The methodology used [...] Read more.
This study will help academics, researchers, and professionals to better understand how the Portuguese population perceives financial risk. Thus, the main objective of this study is to analyse and compare the perception and knowledge of financial risk by the Portuguese. The methodology used is quantitative, and the measurement instrument consists of three parts: financial risk perception, financial risk knowledge and sociodemographic characterization of the participants. The sample is composed of 830 Portuguese individuals, over 18 years old. The results demonstrate that financial risk perception is a one-dimensional measurement and that there are low levels of both perception and knowledge of financial risk. It can also be concluded that the Portuguese individuals have a higher level of financial risk perception, when compared to financial risk knowledge, and it is men who have higher levels of perception and knowledge of financial risk. Thus, this study contributes to the literature on financial risk by presenting empirical evidence and relevant conclusions, and it is therefore expected that it will help to improve the perception and knowledge of the financial risk of the Portuguese and, consequently, their financial decisions and financial well-being. Therefore, the study fills a gap, since there are no studies in Portugal that assess the perception and knowledge of financial risk of the Portuguese. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
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Review

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11 pages, 246 KiB  
Review
Corporate Default Predictions Using Machine Learning: Literature Review
by Hyeongjun Kim, Hoon Cho and Doojin Ryu
Sustainability 2020, 12(16), 6325; https://doi.org/10.3390/su12166325 - 6 Aug 2020
Cited by 39 | Viewed by 7738
Abstract
Corporate default predictions play an essential role in each sector of the economy, as highlighted by the global financial crisis and the increase in credit risk. This study reviews the corporate default prediction literature from the perspectives of financial engineering and machine learning. [...] Read more.
Corporate default predictions play an essential role in each sector of the economy, as highlighted by the global financial crisis and the increase in credit risk. This study reviews the corporate default prediction literature from the perspectives of financial engineering and machine learning. We define three generations of statistical models: discriminant analyses, binary response models, and hazard models. In addition, we introduce three representative machine learning methodologies: support vector machines, decision trees, and artificial neural network algorithms. For both the statistical models and machine learning methodologies, we identify the key studies used in corporate default prediction. By comparing these methods with findings from the interdisciplinary literature, our review suggests some new tasks in the field of machine learning for predicting corporate defaults. First, a corporate default prediction model should be a multi-period model in which future outcomes are affected by past decisions. Second, the stock price and the corporate value determined by the stock market are important factors to use in default predictions. Finally, a corporate default prediction model should be able to suggest the cause of default. Full article
(This article belongs to the Special Issue The Future and Sustainability of Financial Markets)
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