Adel Hassan A. Gadhi, Shelton Peiris, David E. Allen
This paper examines the predictive ability of volatility in time series and investigates the effect of tradition learning methods blending with the Wasserstein generative adversarial network with gradient penalty (WGAN-GP). Using Brent crude oil returns price volatility and environmental temperature for the city of Sydney in Australia, we have shown that the corresponding forecasts have improved when combined with WGAN-GP models (i.e., ANN-(WGAN-GP), LSTM-ANN-(WGAN-GP) and BLSTM-ANN (WGAN-GP)). As a result, we conclude that incorporating with WGAN-GP will’ significantly improve the capabilities of volatility forecasting in standard econometric models and deep learning techniques.
{"title":"Improving Volatility Forecasting: A Study through Hybrid Deep Learning Methods with WGAN","authors":"Adel Hassan A. Gadhi, Shelton Peiris, David E. Allen","doi":"10.3390/jrfm17090380","DOIUrl":"https://doi.org/10.3390/jrfm17090380","url":null,"abstract":"This paper examines the predictive ability of volatility in time series and investigates the effect of tradition learning methods blending with the Wasserstein generative adversarial network with gradient penalty (WGAN-GP). Using Brent crude oil returns price volatility and environmental temperature for the city of Sydney in Australia, we have shown that the corresponding forecasts have improved when combined with WGAN-GP models (i.e., ANN-(WGAN-GP), LSTM-ANN-(WGAN-GP) and BLSTM-ANN (WGAN-GP)). As a result, we conclude that incorporating with WGAN-GP will’ significantly improve the capabilities of volatility forecasting in standard econometric models and deep learning techniques.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We evolved our past Portfolio Yield Reactive (PYR) model to provide a competitive system with infiltration of categorical information and fundamentals into advanced higher-order moments that support more objective portfolio selection aided by intelligent computing. The system of the PYR model searches for hidden corporate performance prototypes in big data from accounting and financial statements. The PYR model restricts malicious patterns, such as hoaxes, noise, and manipulation, incorporated into a novel optimal portfolio selection method.
{"title":"Optimal Investments in the Portfolio Yield Reactive (PYR) Model","authors":"Nikolaos Loukeris, Iordanis Eleftheriadis","doi":"10.3390/jrfm17080376","DOIUrl":"https://doi.org/10.3390/jrfm17080376","url":null,"abstract":"We evolved our past Portfolio Yield Reactive (PYR) model to provide a competitive system with infiltration of categorical information and fundamentals into advanced higher-order moments that support more objective portfolio selection aided by intelligent computing. The system of the PYR model searches for hidden corporate performance prototypes in big data from accounting and financial statements. The PYR model restricts malicious patterns, such as hoaxes, noise, and manipulation, incorporated into a novel optimal portfolio selection method.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nawaf N. Hamadneh, Jamil J. Jaber, Saratha Sathasivam
This paper examines the volatility risk in the KSA stock market (Tadawul), with a specific focus on predicting volatility using the logarithm of the standard deviation of stock market prices (LSCP) as the output variable. To enhance volatility prediction, it proposes the combined use of the dynamic evolving neural fuzzy inference system (DENFIS) and the nonlinear spectral model, maximum overlapping discrete wavelet transform (MODWT). This study utilizes a dataset comprising 4609 observations and investigates the inputs of lag 1 of the close stock price (LCP), the natural logarithm of oil price (Loil), the natural logarithm of cost of living (LCL), and the interbank rate (IB), determined through autocorrelation (AC), partial autocorrelation (PAC), correlation, and Granger causality tests. Regression analysis reveals significant effects of variables on LSCP: LCP has a negative effect, and Loil has a positive effect in the ordinary least square (OLS) model, while LCL and IB have positive effects in the fixed effect model and negative effects in the random effect model. The MODWT-Haar-DENFIS model was developed as we found that the model has the potential to be an effective model for stock market forecasting. The results provide valuable insights for investors and policymakers, aiding in risk management, investment decisions, and the development of measures to mitigate stock market volatility.
{"title":"Estimating Volatility of Saudi Stock Market Using Hybrid Dynamic Evolving Neural Fuzzy Inference System Models","authors":"Nawaf N. Hamadneh, Jamil J. Jaber, Saratha Sathasivam","doi":"10.3390/jrfm17080377","DOIUrl":"https://doi.org/10.3390/jrfm17080377","url":null,"abstract":"This paper examines the volatility risk in the KSA stock market (Tadawul), with a specific focus on predicting volatility using the logarithm of the standard deviation of stock market prices (LSCP) as the output variable. To enhance volatility prediction, it proposes the combined use of the dynamic evolving neural fuzzy inference system (DENFIS) and the nonlinear spectral model, maximum overlapping discrete wavelet transform (MODWT). This study utilizes a dataset comprising 4609 observations and investigates the inputs of lag 1 of the close stock price (LCP), the natural logarithm of oil price (Loil), the natural logarithm of cost of living (LCL), and the interbank rate (IB), determined through autocorrelation (AC), partial autocorrelation (PAC), correlation, and Granger causality tests. Regression analysis reveals significant effects of variables on LSCP: LCP has a negative effect, and Loil has a positive effect in the ordinary least square (OLS) model, while LCL and IB have positive effects in the fixed effect model and negative effects in the random effect model. The MODWT-Haar-DENFIS model was developed as we found that the model has the potential to be an effective model for stock market forecasting. The results provide valuable insights for investors and policymakers, aiding in risk management, investment decisions, and the development of measures to mitigate stock market volatility.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The increasing wave of protectionism in various corners of the world with the use of seemingly attractive but economically misleading slogans (shortening supply chains, onshoring, reshoring, nearshoring, friend-shoring, reindustrialization, and ending/correcting ‘hyperglobalization’, etc.) creates a serious challenge to the global trading system and global economic development. Trade and financial transactions have also become victims of the increasing number of geopolitical conflicts and tensions, both ‘hot’ and ‘cold’. Before it becomes too late, i.e., before the current trade tensions go too far and create the hardly reversible spiral of trade and financial wars, retaliations, etc., it is desirable to reflect on what can be lost due to protectionism. This essay analyzes four areas that have benefited from global economic integration since the 1980s (economic growth, poverty eradication, reduction in global economic inequalities, and disinflation) and may suffer from its reversal. It also discusses potential remedies that may help stop a protectionist drift.
{"title":"The Risk of Protectionism: What Can Be Lost?","authors":"Marek Dabrowski","doi":"10.3390/jrfm17080374","DOIUrl":"https://doi.org/10.3390/jrfm17080374","url":null,"abstract":"The increasing wave of protectionism in various corners of the world with the use of seemingly attractive but economically misleading slogans (shortening supply chains, onshoring, reshoring, nearshoring, friend-shoring, reindustrialization, and ending/correcting ‘hyperglobalization’, etc.) creates a serious challenge to the global trading system and global economic development. Trade and financial transactions have also become victims of the increasing number of geopolitical conflicts and tensions, both ‘hot’ and ‘cold’. Before it becomes too late, i.e., before the current trade tensions go too far and create the hardly reversible spiral of trade and financial wars, retaliations, etc., it is desirable to reflect on what can be lost due to protectionism. This essay analyzes four areas that have benefited from global economic integration since the 1980s (economic growth, poverty eradication, reduction in global economic inequalities, and disinflation) and may suffer from its reversal. It also discusses potential remedies that may help stop a protectionist drift.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"174 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jason R. Bailey, W. Brent Lindquist, Svetlozar T. Rachev
Using data from 2000 through 2022, we analyze the predictive capability of the annual numbers of new home constructions and four available environmental, social, and governance (ESG) factors on the average annual price of homes sold in eight major U.S. cities. We contrast the predictive capability of a P-spline generalized additive model (GAM) against a strictly linear version of the commonly used generalized linear model (GLM). As the data for the annual price and predictor variables constitute non-stationary time series, we transform each time series appropriately to produce stationary series for use in the GAMs and GLMs in order to avoid spurious correlations in the analysis. While arithmetic returns or first differences are adequate transformations for the predictor variables, we utilize the series of innovations obtained from AR(q)-ARCH(1) fits for the average price response variable. Based on the GAM results, we find that the influence of ESG factors varies markedly by city and reflects geographic diversity. Notably, the presence of air conditioning emerges as a strong factor. Despite limitations on the length of available time series, this study represents a pivotal step toward integrating ESG considerations into predictive time series models for real estates.
{"title":"Hedonic Models Incorporating Environmental, Social, and Governance Factors for Time Series of Average Annual Home Prices","authors":"Jason R. Bailey, W. Brent Lindquist, Svetlozar T. Rachev","doi":"10.3390/jrfm17080375","DOIUrl":"https://doi.org/10.3390/jrfm17080375","url":null,"abstract":"Using data from 2000 through 2022, we analyze the predictive capability of the annual numbers of new home constructions and four available environmental, social, and governance (ESG) factors on the average annual price of homes sold in eight major U.S. cities. We contrast the predictive capability of a P-spline generalized additive model (GAM) against a strictly linear version of the commonly used generalized linear model (GLM). As the data for the annual price and predictor variables constitute non-stationary time series, we transform each time series appropriately to produce stationary series for use in the GAMs and GLMs in order to avoid spurious correlations in the analysis. While arithmetic returns or first differences are adequate transformations for the predictor variables, we utilize the series of innovations obtained from AR(q)-ARCH(1) fits for the average price response variable. Based on the GAM results, we find that the influence of ESG factors varies markedly by city and reflects geographic diversity. Notably, the presence of air conditioning emerges as a strong factor. Despite limitations on the length of available time series, this study represents a pivotal step toward integrating ESG considerations into predictive time series models for real estates.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bernardette Naa Hoffman, Johnson Okeniyi, Sunday Eneojo Samuel
This study examines factors influencing Ghanaian banks’ compliance with anti-money laundering (AML) legislation. Drawing upon institutional, compliance, and dynamic capability theories, the study identifies the interplay of organisational, regulatory, and employee factors influencing compliance outcomes. A mixed methods approach was used to collect data from 23 universal banks, 9 local and 14 foreign, in Ghana, focusing on experienced managers and employees in risk, legal, operations, compliance, and business development departments. The findings show that employee characteristics like due diligence and moral involvement have a positive relationship with compliance with AML regulations; however, contrary to expectations, effective AML/CFT programs did not significantly impact banks’ adherence to these regulations. The association between moral engagement, an innovative culture, and AML compliance is weakened by normative power and an innovative culture acting as negative moderators. This study contributes empirical evidence to the literature on AML compliance in emerging markets and offers practical implications for policymakers, regulators, and banking professionals seeking to boost regulatory effectiveness and mitigate financial crime risks. This study provides a foundation for targeted interventions and strategic initiatives aimed at strengthening the AML regulatory landscape in Ghana and other countries.
{"title":"Antecedents of Compliance with Anti-Money Laundering Regulations in the Banking Sector of Ghana","authors":"Bernardette Naa Hoffman, Johnson Okeniyi, Sunday Eneojo Samuel","doi":"10.3390/jrfm17080373","DOIUrl":"https://doi.org/10.3390/jrfm17080373","url":null,"abstract":"This study examines factors influencing Ghanaian banks’ compliance with anti-money laundering (AML) legislation. Drawing upon institutional, compliance, and dynamic capability theories, the study identifies the interplay of organisational, regulatory, and employee factors influencing compliance outcomes. A mixed methods approach was used to collect data from 23 universal banks, 9 local and 14 foreign, in Ghana, focusing on experienced managers and employees in risk, legal, operations, compliance, and business development departments. The findings show that employee characteristics like due diligence and moral involvement have a positive relationship with compliance with AML regulations; however, contrary to expectations, effective AML/CFT programs did not significantly impact banks’ adherence to these regulations. The association between moral engagement, an innovative culture, and AML compliance is weakened by normative power and an innovative culture acting as negative moderators. This study contributes empirical evidence to the literature on AML compliance in emerging markets and offers practical implications for policymakers, regulators, and banking professionals seeking to boost regulatory effectiveness and mitigate financial crime risks. This study provides a foundation for targeted interventions and strategic initiatives aimed at strengthening the AML regulatory landscape in Ghana and other countries.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"285 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohamed Nofel, Mahmoud Marzouk, Hany Elbardan, Reda Saleh, Aly Mogahed
Over the last few decades, remarkable technical advancements, including artificial intelligence, machine learning, big data, blockchain, cloud computing, and the Internet of Things, have emerged. These tools have the ability to change the accounting process. This study aims to conduct a systematic literature review on using the Internet of Things (IoT), blockchain, and eXtensible Business Reporting Language (XBRL) in a single accounting information system (AIS) to enhance the quality of digital financial reports. This paper employs a systematic literature review (SLR) methodology, specifically, by adopting the widely accepted PRISMA technique. The final sample of this study included 309 related studies from 2013 to 2023. Our findings highlight the lack of literature related to the integration of these three types of technologies within a unified AIS. This study is extremely significant because it proposes a new research stream that explores the possibility of integrating IoT, blockchain, and XBRL in a single accounting system, yielding a plethora of benefits to the accounting field. However, the potential benefits of such an integration are evident, including enhanced transparency, real-time reporting capabilities, and improved data security. Our paper’s main contribution is that it is the first paper, to the best of our knowledge, to explore the integration of these three technologies. We also identified important gaps in the research and pointed out ways for future research to somehow take a lead in exploring further how this integrated system is affecting accounting practices.
{"title":"Integrating Blockchain, IoT, and XBRL in Accounting Information Systems: A Systematic Literature Review","authors":"Mohamed Nofel, Mahmoud Marzouk, Hany Elbardan, Reda Saleh, Aly Mogahed","doi":"10.3390/jrfm17080372","DOIUrl":"https://doi.org/10.3390/jrfm17080372","url":null,"abstract":"Over the last few decades, remarkable technical advancements, including artificial intelligence, machine learning, big data, blockchain, cloud computing, and the Internet of Things, have emerged. These tools have the ability to change the accounting process. This study aims to conduct a systematic literature review on using the Internet of Things (IoT), blockchain, and eXtensible Business Reporting Language (XBRL) in a single accounting information system (AIS) to enhance the quality of digital financial reports. This paper employs a systematic literature review (SLR) methodology, specifically, by adopting the widely accepted PRISMA technique. The final sample of this study included 309 related studies from 2013 to 2023. Our findings highlight the lack of literature related to the integration of these three types of technologies within a unified AIS. This study is extremely significant because it proposes a new research stream that explores the possibility of integrating IoT, blockchain, and XBRL in a single accounting system, yielding a plethora of benefits to the accounting field. However, the potential benefits of such an integration are evident, including enhanced transparency, real-time reporting capabilities, and improved data security. Our paper’s main contribution is that it is the first paper, to the best of our knowledge, to explore the integration of these three technologies. We also identified important gaps in the research and pointed out ways for future research to somehow take a lead in exploring further how this integrated system is affecting accounting practices.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper considers the impact of the composition of the top management team on the credit default risk of the firm. Finance theory suggests that shareholders prefer higher levels of risk than the risk-averse executives managing the firm. Increasing the influence of female executives may reduce credit default risk, as female executives have been shown to be associated with lower firm risk. Alternatively, as diversity has been shown to improve the quality of group decision-making, a higher but optimal credit default risk may result. This paper uses a matched sample of 6,652 firm-year observations of publicly traded American firms over the period 2010–2020 to investigate the relationship between gender power within the top management team and credit default risk as measured by the Altman Z-score. This paper finds a convex relationship between the Altman Z-score and the influence of female executives. In other words, top management teams where power is shared between female and male executives accept higher levels of credit default risk than teams dominated by just female (or just male) executives. However, this paper also finds that an excessively high credit risk is negatively associated with the influence of female executives.
本文探讨了高层管理团队的构成对企业信用违约风险的影响。金融理论认为，与管理公司的风险规避型高管相比，股东更倾向于更高的风险水平。提高女性高管的影响力可能会降低信用违约风险，因为女性高管已被证明与较低的公司风险相关。或者，由于多样性已被证明能提高群体决策的质量，因此可能会导致较高但最优的信贷违约风险。本文使用 2010-2020 年间美国上市公司 6652 个公司年观测数据的匹配样本，研究高层管理团队中的性别权力与以 Altman Z 分数衡量的信用违约风险之间的关系。本文发现，Altman Z 分数与女性高管的影响力之间存在凸性关系。换句话说，与仅由女性（或男性）高管主导的团队相比，由女性和男性高管共享权力的高层管理团队接受的信用违约风险水平更高。不过，本文也发现，过高的信用风险与女性高管的影响力呈负相关。
{"title":"Gender Power, the Top Management Team, and Firm Credit Default Risk","authors":"Mark A. Tribbitt, Richard Walton","doi":"10.3390/jrfm17080368","DOIUrl":"https://doi.org/10.3390/jrfm17080368","url":null,"abstract":"This paper considers the impact of the composition of the top management team on the credit default risk of the firm. Finance theory suggests that shareholders prefer higher levels of risk than the risk-averse executives managing the firm. Increasing the influence of female executives may reduce credit default risk, as female executives have been shown to be associated with lower firm risk. Alternatively, as diversity has been shown to improve the quality of group decision-making, a higher but optimal credit default risk may result. This paper uses a matched sample of 6,652 firm-year observations of publicly traded American firms over the period 2010–2020 to investigate the relationship between gender power within the top management team and credit default risk as measured by the Altman Z-score. This paper finds a convex relationship between the Altman Z-score and the influence of female executives. In other words, top management teams where power is shared between female and male executives accept higher levels of credit default risk than teams dominated by just female (or just male) executives. However, this paper also finds that an excessively high credit risk is negatively associated with the influence of female executives.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Panagiotis E. Petrakis, Anna-Maria Kanzola, Ioannis Lomis
The global geopolitical landscape is characterized by the rise of new powers and a shift toward multipolarity. This study examines the impact of multipolarity on international cooperation using an iterated game theory approach, particularly the classic prisoner’s dilemma, extended to a multiplayer setting. This effort can be regarded as a preliminary study of hypothetical optimal global cooperation. The main hypothesis is that an increase in the number of large countries in the international system will lead to higher levels of cooperation. Our simulation approach confirmed this. Our findings extend to the conclusion that multipolarity, under appropriate cultural and value systems, can foster new economic development and fair competition. Furthermore, we emphasize the importance of evolving strategies and cooperative dynamics in a multipolar world, contributing to discussions on foreign economic policy integration, sustainability, and managing vulnerabilities among great powers. The study underscores the necessity of strategic frameworks and international institutions in promoting global stability and cooperation amidst the complexities of multipolarity.
{"title":"Adapting to Multipolarity: Insights from Iterated Game Theory Simulations—A Preliminary Study on Hypothetical Optimal Global Cooperation","authors":"Panagiotis E. Petrakis, Anna-Maria Kanzola, Ioannis Lomis","doi":"10.3390/jrfm17080370","DOIUrl":"https://doi.org/10.3390/jrfm17080370","url":null,"abstract":"The global geopolitical landscape is characterized by the rise of new powers and a shift toward multipolarity. This study examines the impact of multipolarity on international cooperation using an iterated game theory approach, particularly the classic prisoner’s dilemma, extended to a multiplayer setting. This effort can be regarded as a preliminary study of hypothetical optimal global cooperation. The main hypothesis is that an increase in the number of large countries in the international system will lead to higher levels of cooperation. Our simulation approach confirmed this. Our findings extend to the conclusion that multipolarity, under appropriate cultural and value systems, can foster new economic development and fair competition. Furthermore, we emphasize the importance of evolving strategies and cooperative dynamics in a multipolar world, contributing to discussions on foreign economic policy integration, sustainability, and managing vulnerabilities among great powers. The study underscores the necessity of strategic frameworks and international institutions in promoting global stability and cooperation amidst the complexities of multipolarity.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study assessed the accounting-based variables and value-based management (VBM) variables that jointly affect firm value and performance. The study applied the causality test and variance decomposition to determine the variability of the variables, and further empirically employed fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) techniques to justify the results. Data covering 356 industries were purposively sampled to arrive at 61 companies spanning 2011–2020. Overall, the causality test found no relationship between economic value added and market value added but only found unidirectional causality from shareholder returns to MVA, EVA to shareholder returns, ROA to MVA, ROE to MVA, EVA to MVA, MVA to EVA, ROE to ROA, EVA to ROA, and EVA to ROE. A very strong bidirectional causality relationship was found between return on asset and shareholder return as a measure of company performance. Further results from the forecast error of the variance decomposition showed that shareholder returns are explained only by its own shock, contributing 45.38 percent in the long run, while the remaining variables, namely market value added, return on asset, return on equity, and economic value added, contribute about 35.96%, 14.06%, 4.08%, and 0.51%, respectively, to predicting the future values of shareholder return. This confirms the relationships between the variables from the short run to the long run. Additionally, results from the FMOL and DOL revealed that all accounting variables and VBM are good approaches for evaluating company performance as the empirical result from ROA, ROE, and EVA revealed positive and significant relationships. This confirms that a combination of both variables would produce a better evaluation as the accounting variables and VBM variables jointly relate to shareholder returns. This study serves as a guide to companies’ management and boards of directors in having better ways to evaluate company performance. Consequently, it is recommended that managers select combinations of accounting and VBM variables that suit their operations and jointly apply them in the performance evaluation of the company. This will be useful in providing both the relative and incremental performance information needed for diverse decision-making.
{"title":"Evaluating the Relationship between Accounting Variables, Value-Based Management Variables, and Shareholder Returns: An Empirical Approach","authors":"Oji Okpusa Oke, Kola Benson Ajeigbe","doi":"10.3390/jrfm17080371","DOIUrl":"https://doi.org/10.3390/jrfm17080371","url":null,"abstract":"This study assessed the accounting-based variables and value-based management (VBM) variables that jointly affect firm value and performance. The study applied the causality test and variance decomposition to determine the variability of the variables, and further empirically employed fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) techniques to justify the results. Data covering 356 industries were purposively sampled to arrive at 61 companies spanning 2011–2020. Overall, the causality test found no relationship between economic value added and market value added but only found unidirectional causality from shareholder returns to MVA, EVA to shareholder returns, ROA to MVA, ROE to MVA, EVA to MVA, MVA to EVA, ROE to ROA, EVA to ROA, and EVA to ROE. A very strong bidirectional causality relationship was found between return on asset and shareholder return as a measure of company performance. Further results from the forecast error of the variance decomposition showed that shareholder returns are explained only by its own shock, contributing 45.38 percent in the long run, while the remaining variables, namely market value added, return on asset, return on equity, and economic value added, contribute about 35.96%, 14.06%, 4.08%, and 0.51%, respectively, to predicting the future values of shareholder return. This confirms the relationships between the variables from the short run to the long run. Additionally, results from the FMOL and DOL revealed that all accounting variables and VBM are good approaches for evaluating company performance as the empirical result from ROA, ROE, and EVA revealed positive and significant relationships. This confirms that a combination of both variables would produce a better evaluation as the accounting variables and VBM variables jointly relate to shareholder returns. This study serves as a guide to companies’ management and boards of directors in having better ways to evaluate company performance. Consequently, it is recommended that managers select combinations of accounting and VBM variables that suit their operations and jointly apply them in the performance evaluation of the company. This will be useful in providing both the relative and incremental performance information needed for diverse decision-making.","PeriodicalId":47226,"journal":{"name":"Journal of Risk and Financial Management","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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