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Financial Mathematics and Sustainability
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Financial Mathematics and Sustainability

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E5: Financial Mathematics".

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 9874

Special Issue Editors

Prof. Dr. José Manuel Santos-Jaén

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Guest Editor
Department of Financial Economics and Accounting, University of Murcia, Campus de Espinardo, 30100 Murcia, Spain
Interests: financial mathematics; corporate social responsibility; partial least squares structural equation modeling; gender economics studies; globalization; green economics; health economics; international business management; accounting
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. María del Carmen Valls Martínez

E-Mail Website
Guest Editor
Department of Economics and Business, University of Almería, La Cañada de San Urbano, 04120 Almería, Spain
Interests: financial mathematics; financial operations; partial least squares structural equation modeling; panel data linear regressions; logit and probit models; applied econometrics; ethical banking; gender economics studies; health economics; corporate social responsibility
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Financial mathematics focuses on applying mathematical formulas and equations to financial problems, market modeling, and data analysis. With this approach, finance professionals can better understand the performance of companies, including profitability and growth potential. These aspects are crucial to ensuring the economic sustainability of companies. That is the ability of organizations to manage the resources they have and responsibly generate profitability over the long term.

On the other hand, investors and savers are increasingly aware of sustainability issues. They want to know what activities are financed with their savings and, in many cases, invest in instruments that achieve specific social or environmental objectives. Sustainable and responsible investment (SRI) is an investment philosophy that integrates environmental, social, and governance (ESG) criteria.

Under these two premises, financial mathematics has become an indispensable ally in achieving the UN's Sustainable Development Goals (SDGs), contributing to eradicating poverty, protecting the planet, and ensuring prosperity for all.

Therefore, this Special Issue focuses on applying financial mathematics to sustainability, providing a platform for researchers to present their novel and unpublished papers with stunning results.

Dr. José Manuel Santos Jaén
Dr. María del Carmen Valls Martínez
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. Mathematics 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 2600 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 mathematics
  • sustainability
  • sustainable finance
  • green finance
  • ESG

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Published Papers (6 papers)

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Research

21 pages, 317 KiB  
Article
The Impact of Heterogeneous Market Sentiments on Corporate Risk-Taking and Governance
by Hangbo Liu, Xuemeng Guo and Dachen Sheng
Mathematics 2024, 12(22), 3505; https://doi.org/10.3390/math12223505 - 9 Nov 2024
Viewed by 820
Abstract
This research focuses on how market sentiment affects corporate governance in the Chinese market. The sample covers the years from 2014 to 2023. Market sentiment is estimated using a cross-sectional absolute deviation (CSAD) model, and earnings quality is used as an indicator of [...] Read more.
This research focuses on how market sentiment affects corporate governance in the Chinese market. The sample covers the years from 2014 to 2023. Market sentiment is estimated using a cross-sectional absolute deviation (CSAD) model, and earnings quality is used as an indicator of the consequences of corporate governance. Both mutual fund shareholding and the number of firm visits by mutual fund analysts are verified as effective corporate governance instruments that work well in a regular market but become ineffective when the market sentiment is high. The reason for this is that managers’ expectations change, and they may believe that disclosing good news during high-sentiment market periods significantly increases the share prices and helps them meet their performance requirements. In a high-sentiment market, an incentive contract encourages managers to take on projects with inappropriate risk or even manipulate earnings. One potential solution is to adopt venture capital firms’ high-water mark and clawback clauses to prevent managers from focusing on short-term goals rather than seeking long-term business sustainability. Full article
(This article belongs to the Special Issue Financial Mathematics and Sustainability)
17 pages, 665 KiB  
Article
Financial Literacy, Fintech, and Risky Financial Investment in Urban Households—An Analysis Based on CHFS Data
by Linsheng Chen, Jianli Bai, Shiwei Xu, Zhengrong Cheng and Jiahui Chen
Mathematics 2024, 12(21), 3393; https://doi.org/10.3390/math12213393 - 30 Oct 2024
Cited by 3 | Viewed by 1519
Abstract
In recent years, China’s financial markets have come under increasing scrutiny. In order to explore the impact of financial literacy on urban household investment in the risk financial market, this paper used the micro-data of the 2019 China Household Finance Survey (CHFS) to [...] Read more.
In recent years, China’s financial markets have come under increasing scrutiny. In order to explore the impact of financial literacy on urban household investment in the risk financial market, this paper used the micro-data of the 2019 China Household Finance Survey (CHFS) to start from two perspectives: household risk financial investment and the number of investment financial products, namely the breadth of investment. By constructing a probit model and ordered probit model for empirical analysis, the main conclusions are as follows. Benchmark regression results show that the improvement of financial literacy can significantly promote urban households to make risky financial investments and can significantly broaden the types of risky financial investments. Based on the IV-probit model and two-stage least square method, the endogeneity test using the economic and financial information attention degree as the instrumental variable showed that the model results were credible. The robustness test showed that the model results were basically correct. Furthermore, the mechanism analysis found that the use of fintech played an intermediary effect in the process of financial literacy affecting urban household risky financial investment and the amount of investment. This indicates that the improvement of financial literacy can improve the probability of using fintech, thus promoting the household risky financial investment behavior. Heterogeneity analysis based on risk attitude showed that financial literacy had a greater effect on the improvement in the risky financial investment behavior of risk-inclined families, followed by risk-neutral families, and had the least effect on risk-averse families. The research conclusions of this paper are of practical significance to solve the problems related to urban household financial market investment. Therefore, this paper puts forward some suggestions for reference, especially in terms of financial education and the digital economy. Full article
(This article belongs to the Special Issue Financial Mathematics and Sustainability)
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16 pages, 2152 KiB  
Article
A Study of GGDP Transition Impact on the Sustainable Development by Mathematical Modelling Investigation
by Nuoya Yue and Junjun Hou
Mathematics 2024, 12(19), 3005; https://doi.org/10.3390/math12193005 - 26 Sep 2024
Cited by 1 | Viewed by 1438
Abstract
GDP is a common and essential indicator for evaluating a country’s overall economy. However, environmental issues may be overlooked in the pursuit of GDP growth for some countries. It may be beneficial to adopt more sustainable criteria for assessing economic health. In this [...] Read more.
GDP is a common and essential indicator for evaluating a country’s overall economy. However, environmental issues may be overlooked in the pursuit of GDP growth for some countries. It may be beneficial to adopt more sustainable criteria for assessing economic health. In this study, green GDP (GGDP) is discussed using mathematical approaches. Multiple dataset indicators were selected for the evaluation of GGDP and its impact on climate mitigation. The k-means clustering algorithm was utilized to classify 16 countries into three distinct categories for specific analysis. The potential impact of transitioning to GGDP was investigated through changes in a quantitative parameter, the climate impact factor. Ridge regression was applied to predict the impact of switching to GGDP for the three country categories. The consequences of transitioning to GGDP on the quantified improvement of climate indicators were graphically demonstrated over time on a global scale. The entropy weight method (EWM) and TOPSIS were used to obtain the value. Countries in category 2, as divided by k-means clustering, were predicted to show a greater improvement in scores as one of the world’s largest carbon emitters, China, which belongs to category 2 countries, plays a significant role in global climate governance. A specific analysis of China was performed after obtaining the EWM-TOPSIS results. Gray relational analysis and Pearson correlation were carried out to analyze the relationships between specific indicators, followed by a prediction of CO2 emissions based on the analyzed critical indicators. Full article
(This article belongs to the Special Issue Financial Mathematics and Sustainability)
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21 pages, 902 KiB  
Article
Assessing the Impact of Environmental Technology on CO2 Emissions in Saudi Arabia: A Quantile-Based NARDL Approach
by Md. Saiful Islam, Anis ur Rehman and Imran Khan
Mathematics 2024, 12(15), 2352; https://doi.org/10.3390/math12152352 - 27 Jul 2024
Cited by 2 | Viewed by 1373
Abstract
Climatic change and environmental degradation have become a worldwide discourse. Green innovation is commonly viewed as a means of lowering environmental pollution in the era of climate change. Considering this, the primary purpose of this study is to investigate the effects of environmental [...] Read more.
Climatic change and environmental degradation have become a worldwide discourse. Green innovation is commonly viewed as a means of lowering environmental pollution in the era of climate change. Considering this, the primary purpose of this study is to investigate the effects of environmental technology (ET) on CO2 emissions by controlling Saudi Arabia’s ICT use, energy use, energy intensity, and financial development. It uses a quantile-based multiple-threshold “nonlinear autoregressive distributed lag (NARDL)” estimation utilizing data from 1990 to 2020. It also conducts the ARDL and NARDL estimation techniques simultaneously for comparative outcomes. The Toda–Yamamoto (T-Y) causality assessment also crosschecks the primary multiple-threshold NARDL estimates. The outcomes reveal that ET promotes environmental pollution due to its low scale compared to the Kingdom’s technological base. ICT improves environmental quality, and energy consumption deteriorates it. All three estimation techniques confirm these findings. The multiple-threshold NARDL estimation appears robust and reveals damaging impacts of energy intensity and financial development on emissions. The T-Y causality assessment also authenticates the primary estimation outcomes. The outcomes have important implications for policymakers to focus on enhancing patents for ET, raising ICT diffusion, reducing energy intensity through generating more renewable energies, expanding financial support for ICT and green investments, and ensuring a sustainable environment. Full article
(This article belongs to the Special Issue Financial Mathematics and Sustainability)
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20 pages, 668 KiB  
Article
Bankruptcy Prediction for Sustainability of Businesses: The Application of Graph Theoretical Modeling
by Jarmila Horváthová, Martina Mokrišová  and Martin Bača
Mathematics 2023, 11(24), 4966; https://doi.org/10.3390/math11244966 - 15 Dec 2023
Cited by 2 | Viewed by 2319
Abstract
Various methods are used when building bankruptcy prediction models. New sophisticated methods that are already used in other scientific fields can also be applied in this area. Graph theory provides a powerful framework for analyzing and visualizing complex systems, making it a valuable [...] Read more.
Various methods are used when building bankruptcy prediction models. New sophisticated methods that are already used in other scientific fields can also be applied in this area. Graph theory provides a powerful framework for analyzing and visualizing complex systems, making it a valuable tool for assessing the sustainability and financial health of businesses. The motivation for the research was the interest in the application of this method rarely applied in predicting the bankruptcy of companies. The paper aims to propose an improved dynamic bankruptcy prediction model based on graph theoretical modelling. The dynamic model considering the causality relation between financial features was built for the period 2015–2021. Financial features entering the model were selected with the use of Domain knowledge approach. When building the model, the weights of partial permanents were proposed to determine their impact on the final permanent and the algorithm for the optimalisation of these weights was established to obtain the best performing model. The outcome of the paper is the improved dynamic graph theoretical model with a good classification accuracy. The developed model is applicable in the field of bankruptcy prediction and is an equivalent sophisticated alternative to already established models. Full article
(This article belongs to the Special Issue Financial Mathematics and Sustainability)
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12 pages, 569 KiB  
Article
The Ordered Weighted Average Sector Liquid Return Index: A Method for Determining Financial Recovery from Sectoral Debt
by Salvador Linares-Mustarós, Maria Àngels Farreras-Noguer, Joan Carles Ferrer-Comalat and José M. Merigó
Mathematics 2023, 11(23), 4839; https://doi.org/10.3390/math11234839 - 30 Nov 2023
Viewed by 1120
Abstract
The primary aim of this article is to demonstrate that using the average of ratios as a representative value for measuring the health of a sector does not constitute a valid procedure. After mathematically demonstrating this objective, the article will then focus on [...] Read more.
The primary aim of this article is to demonstrate that using the average of ratios as a representative value for measuring the health of a sector does not constitute a valid procedure. After mathematically demonstrating this objective, the article will then focus on introducing a new index for estimating the potential debt return value for a sector or group of companies. Next, the article details the start of the process for creating a new index to improve investors’ understanding of the risk associated with a sector or a group of companies meeting short-term obligations based on assigned probabilities of future sales. Given that said value is intended to represent an indicator of expected liquid solvency, its construction will take treasury tensions into account. An Ordered Weighted Average type of aggregation function is used to aggregate the magnitudes in this scenario. Consequently, the second objective of the present work is the creation of this index, which provides an initial estimate of how much money can be recovered from a sector’s debt. Full article
(This article belongs to the Special Issue Financial Mathematics and Sustainability)
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