Application of Mathematical Methods to Economics, Management, Finance and Social Problems II

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 14697

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ISCTE – Instituto Universitário de Lisboa, 1649-004 Lisboa, Portugal
Interests: mathematics; statistics; stochastic processes—queues and applied probabilities; game theory; application of quantitative methods to economics; management; finance; and social problems
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Due to the great success of the first Special Issue on this theme thanks to the many researchers who contributed, we now propose a new similar Special Issue and invite researchers on the area to submit their work.

The world is facing considerable challenges, contributing science to the new stages of human evolution. The Special Issue intends to offer new insights and contribute to the the context of the social, financial, and economic change in this arena.

Our proposal welcomes all kind of articles that may bring interesting contributions to the fields approached by the issue.

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Keywords

  • quantitative methods
  • qualitative methods
  • big data
  • game theory
  • chaos theory
  • decision-making
  • dynamic systems
  • information systems
  • statistics
  • economics
  • finance
  • management
  • tourism

Published Papers (8 papers)

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Research

21 pages, 6233 KiB  
Article
A Novel Deterministic Probabilistic Forecasting Framework for Gold Price with a New Pandemic Index Based on Quantile Regression Deep Learning and Multi-Objective Optimization
by Yan Wang and Tong Lin
Mathematics 2024, 12(1), 29; https://doi.org/10.3390/math12010029 - 22 Dec 2023
Viewed by 947
Abstract
The significance of precise gold price forecasting is accentuated by its financial attributes, mirroring global economic conditions, market uncertainties, and investor risk aversion. However, predicting the gold price is challenging due to its inherent volatility, influenced by multiple factors, such as COVID-19, financial [...] Read more.
The significance of precise gold price forecasting is accentuated by its financial attributes, mirroring global economic conditions, market uncertainties, and investor risk aversion. However, predicting the gold price is challenging due to its inherent volatility, influenced by multiple factors, such as COVID-19, financial crises, geopolitical issues, and fluctuations in other metals and energy prices. These complexities often lead to non-stationary time series, rendering traditional time series modeling methods inadequate. Our paper presents a multi-objective optimization algorithm that refines the interval prediction framework with quantile regression deep learning in response to this issue. This framework comprehensively responds to gold’s financial market dynamics and uncertainties with a screening process of various factors, including pandemic-related indices, geopolitical indices, the US dollar index, and prices of various commodities. The quantile regression deep-learning models optimized by multi-objective optimization algorithms deliver robust, interpretable, and highly accurate predictions for handling non-linear relationships and complex data structures and enhance the overall predictive performance. The results demonstrate that the QRBiLSTM model, optimized using the MOALO algorithm, delivers excellent forecasting performance. The composite indicator AIS reaches −15.6240 and −11.5581 at 90% and 95% confidence levels, respectively. This underscores the model’s high forecasting accuracy and its potential to provide valuable insights for assessing future trends in gold prices. The deterministic and probabilistic forecasting framework for gold prices captures the market dynamics with the new pandemic index and comprehensively sets a new benchmark for predictive modeling in volatile market commodities like gold. Full article
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21 pages, 8511 KiB  
Article
Regulating the Big Data-Based Discriminatory Pricing in Platform Retailing: A Tripartite Evolutionary Game Theory Analysis
by Shandong Mou, Kexin Zhong and Yamin Ma
Mathematics 2023, 11(11), 2579; https://doi.org/10.3390/math11112579 - 05 Jun 2023
Cited by 2 | Viewed by 1316
Abstract
Nowadays, with the rapid development of the platform economy, Big Data-based Discriminatory Pricing (BDDP) has become a common phenomenon in which big data and algorithms are applied to excessively seize consumer surplus and thus damage the rights and interests of consumers. This work [...] Read more.
Nowadays, with the rapid development of the platform economy, Big Data-based Discriminatory Pricing (BDDP) has become a common phenomenon in which big data and algorithms are applied to excessively seize consumer surplus and thus damage the rights and interests of consumers. This work aims to explore the equilibrium strategies of the consumers, the government, and the service platform and discuss factors affecting the BDDP practice of the service platforms. This study constructs a tripartite evolutionary game model among consumers, service platforms, and the government. Two evolutionary equilibrium strategies are derived and validated using simulation. Numerical experiments are conducted using MATLAB to reveal players’ evolutionary stability strategies under various settings. The study shows that (1) the strategies of the government and the platform always influence each other, (2) a reasonable adjustment of tax rate helps regulate the platform’s behavior, and (3) the proportion of consumers who switch the platform after they realize themselves suffering BDDP is an important factor influencing platform’s strategy. This study lastly summarizes the managerial insights for dealing with the platform’s BDDP behavior and safeguarding consumers’ rights from the perspectives of macro-regulation and privacy data protection. The conclusions of this study can help promote the high-quality development of the platform economy. Full article
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31 pages, 5872 KiB  
Article
Evolutionary Game Analysis of SME Social Responsibility Performance under Public Health Emergencies
by Nan Xie, Yezi Tong and Haitao He
Mathematics 2023, 11(8), 1802; https://doi.org/10.3390/math11081802 - 10 Apr 2023
Viewed by 842
Abstract
Performing corporate social responsibility is the only way to adapt to sustainable economic and social development and is also the inevitable choice to enhance the core competitiveness of enterprises. At the beginning of 2020, the rapid spread of the COVID-19 epidemic made SMEs [...] Read more.
Performing corporate social responsibility is the only way to adapt to sustainable economic and social development and is also the inevitable choice to enhance the core competitiveness of enterprises. At the beginning of 2020, the rapid spread of the COVID-19 epidemic made SMEs face a survival crisis. Therefore, SMEs need to continue to shoulder their social responsibilities in this special period. In view of this, this paper, with the COVID-19 outbreak as the background, constructed the evolution of the government regulatory agency, SME, and consumer evolutionary game model. This paper studies the strategy choice of three subjects in the process of fulfilling social responsibility before and after public health emergencies and analyzes the influence of dynamic incentive and punishment measures, cash, and inventory on the performance of SMEs’ social responsibility using MATLAB. The results show that the government regulatory agencies play a guiding role in the enterprise responsibility process and need to provide appropriate liquidity for SMEs; SMEs should actively participate in social responsibility activities, optimize internal governance, and prepare enough cash for a crisis; consumers need to develop responsible consumer market, expand the responsible consumption scale, and help SMEs share the difficulties. Full article
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21 pages, 1771 KiB  
Article
A Novel Black-Litterman Model with Time-Varying Covariance for Optimal Asset Allocation of Pension Funds
by Yuqin Sun, Yungao Wu and Gejirifu De
Mathematics 2023, 11(6), 1476; https://doi.org/10.3390/math11061476 - 17 Mar 2023
Cited by 2 | Viewed by 1449
Abstract
The allocation of pension funds has important theoretical value and practical significance, which improves the level of pension investment income, achieves the maintenance and appreciation of pension funds, and resolves the pension payment risk caused by population aging. The asset allocation of pension [...] Read more.
The allocation of pension funds has important theoretical value and practical significance, which improves the level of pension investment income, achieves the maintenance and appreciation of pension funds, and resolves the pension payment risk caused by population aging. The asset allocation of pension funds is a long-term asset allocation problem. Thus, the long-term risk and return of the assets need to be estimated. The covariance matrix is usually adopted to measure the risk of the assets, while calculating the long-term covariance matrix is extremely difficult. Direct calculations suffer from the insufficiency of historical data, and indirect calculations accumulate short-term covariance, which suffers from the dynamic changes of the covariance matrix. Since the returns of main assets are highly autocorrelated, the covariance matrix of main asset returns is time-varying with dramatic dynamic changes, and the errors of indirect calculation cannot be ignored. In this paper, we propose a novel Black–Litterman model with time-varying covariance (TVC-BL) for the optimal asset allocation of pension funds to address the time-varying nature of asset returns and risks. Firstly, the return on assets (ROA) and the covariance of ROA are modeled by VARMA and GARCH, respectively. Secondly, the time-varying covariance estimation of ROA is obtained by introducing an effective transformation of the covariance matrix from short-term to long-term. Finally, the asset allocation decision of pension funds is achieved by the TVC-BL model. The results indicate that the proposed TVC-BL pension asset allocation model outperforms the traditional BL model. When the risk aversion coefficient is 1, 1.5, and 3, the Sharp ratio of pension asset allocation through the TVC-BL pension asset allocation model is 13.0%, 10.5%, and 12.8% higher than that of the traditional BL model. It helps to improve the long-term investment returns of pension funds, realize the preservation and appreciation of pension funds, and resolve the pension payment risks caused by the aging of the population. Full article
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24 pages, 1612 KiB  
Article
Consumer Acceptance and Adoption of AI Robo-Advisors in Fintech Industry
by Asrar Ahmed Sabir, Iftikhar Ahmad, Hassan Ahmad, Muhammad Rafiq, Muhammad Asghar Khan and Neelum Noreen
Mathematics 2023, 11(6), 1311; https://doi.org/10.3390/math11061311 - 08 Mar 2023
Cited by 4 | Viewed by 5408
Abstract
Artificial intelligence (AI) has provided significant help in many fields of life. This study proposed a framework that helped in understanding customers’ attitudes about the adoption of Robo-advisors. The role of the Technology Readiness Index moderated as one of the primary relationships. A [...] Read more.
Artificial intelligence (AI) has provided significant help in many fields of life. This study proposed a framework that helped in understanding customers’ attitudes about the adoption of Robo-advisors. The role of the Technology Readiness Index moderated as one of the primary relationships. A total of 208 potential users of Robo-advisor services provided the data that confirmed the validity of the model. This model provided the input for structural equation modeling and analysis of the study hypotheses. The results indicated that consumers showed positive attitudes about Robo-advisor services, with the moderating effect of Technology Readiness Index dimensions, namely, contributors and inhibitors. Perceived ease of use, perceived usefulness, and perceived convenience influenced consumers in developing positive attitudes about this service. Financial businesses can design better AI Robo-advisor services to fulfill the requirements of a wide range of consumers. This proposed framework contributes to the consumers’ understanding of behavioral intentions for the use of Robo-advisors in FinTech. Full article
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12 pages, 294 KiB  
Article
Keep It Simple: A Methodological Discussion of Wage Inequalities in the Spanish Hospitality Industry
by Francisco Sánchez-Cubo, José Mondéjar-Jiménez, Alejandro García-Pozo and Mauro Maltagliati
Mathematics 2023, 11(5), 1163; https://doi.org/10.3390/math11051163 - 27 Feb 2023
Cited by 2 | Viewed by 931
Abstract
Human capital in hospitality has been widely addressed by applying sophisticated econometric methods. However, for the Spanish case, there was a gap in the analyses as the crucial importance of collective agreements was undervalued. This paper redesigns the conceptualisation of the variables and [...] Read more.
Human capital in hospitality has been widely addressed by applying sophisticated econometric methods. However, for the Spanish case, there was a gap in the analyses as the crucial importance of collective agreements was undervalued. This paper redesigns the conceptualisation of the variables and applies a subsequent new classification to job positions, as it deals with the outliers at different levels of rigorousness. Then, linearised and quantile regressions were run for each case, obtaining an outcome of thirty values for each variable. The analyses and comparisons show the high importance of collective agreements on salaries, the noticeable low values of human capital variables, and provides additional information for the nationality and gender gaps, the latter strikingly high in upper professional categories. Overall, this paper demonstrates the importance of a proper study design to prevent advanced econometric models from falling into bias and it minimises the differences between methods. Full article
25 pages, 2178 KiB  
Article
Dynamic Volatility Spillover Effects and Portfolio Strategies among Crude Oil, Gold, and Chinese Electricity Companies
by Guannan Wang, Juan Meng and Bin Mo
Mathematics 2023, 11(4), 910; https://doi.org/10.3390/math11040910 - 10 Feb 2023
Cited by 2 | Viewed by 1400
Abstract
This paper examines the dynamic relationships and the volatility spillover effects among crude oil, gold, and Chinese electricity companies’ stock prices, from 2 December 2008 to 25 July 2022. By estimating the dynamic conditional correlation (DCC) model, we identify the time-varying correlation between [...] Read more.
This paper examines the dynamic relationships and the volatility spillover effects among crude oil, gold, and Chinese electricity companies’ stock prices, from 2 December 2008 to 25 July 2022. By estimating the dynamic conditional correlation (DCC) model, we identify the time-varying correlation between crude oil, gold, and Chinese electricity stocks. Then, we use the time-varying parameter VAR model (TVP-VAR) to analyze the total and net volatility spillover effects. In addition, we compare the hedge ratio strategy and the portfolio weights strategy, as well as the corresponding hedging effectiveness among the crude oil, gold, and Chinese electricity companies. Considering the impact of the extreme events, we also extend the examination to the special period analysis of two crises, the Chinese stock market crash in 2015 and the COVID-19 pandemic in 2020. The results indicate that significant volatility spillover effects exist among crude oil, gold, and Chinese electricity companies’ stock volatility, and the total spillover effects show a sharp increase under the impact of the crisis. On average, gold is a much cheaper hedging tool than crude oil, whereas these two commodity assets remain net volatility receivers during the whole period and the crisis. However, it is worth noting that for specific assets, the impact of the crisis on spillover effects depends on the characteristics of crisis events and the assets analyzed. Additionally, most optimal weight strategies provide better hedging effectiveness than hedging strategies from the perspective of hedging effectiveness. Full article
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22 pages, 1713 KiB  
Article
Are State-Owned Enterprises Really Ineffective? An Empirical Study Based on Stochastic Frontier Analysis
by Chao Liu, Jiaye Lu, Ding Li, Mengyao Jia and Kunru Han
Mathematics 2023, 11(3), 657; https://doi.org/10.3390/math11030657 - 28 Jan 2023
Cited by 1 | Viewed by 1234
Abstract
Technical efficiency (TE) and total factor productivity (TFP) are important criteria to ensure the enhancement of the quality and efficiency of state-owned enterprises (SOEs) and function as important indicators to assess the quality of their accomplishments. The purpose of this study is to [...] Read more.
Technical efficiency (TE) and total factor productivity (TFP) are important criteria to ensure the enhancement of the quality and efficiency of state-owned enterprises (SOEs) and function as important indicators to assess the quality of their accomplishments. The purpose of this study is to explore whether the efficiency of SOEs is higher or lower than that of private enterprises. Transcendental logarithmic production function and stochastic frontier analysis (SFA) are used to assess the TE and TFP of listed central SOEs, local SOEs, and private enterprises, the data of which were taken from 2006–2020. The results show that the sampled private enterprises had the highest average TE during the study period, followed by the central and local SOEs. The private enterprises also had the highest average TFP growth rate, followed by the local and central SOEs. The TFP decompositions show that the TE change (TEC) and technical change (TC) indices of the SOEs were lower than those of the private enterprises. The TC, TEC, and scale change (SC) are limiting the TFP growth rates of the SOEs in labor-intensive industries. The SC of the SOEs has changed less than that of private enterprises in the sampled capital-intensive industries. Northern and southern China had the highest rates of TE and TFP growth. Indeed, this paper measures and decomposes TFP, and analyzes the efficiency of SOEs and private enterprises in different industries and regions in an international context. Full article
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