This study explores the housing distribution effect of the Housing Provident Fund(HPF)system on households.Utilizing data from the China Household Finance Survey conducted in 2013,2015,2017,and 2019,this study empiric...This study explores the housing distribution effect of the Housing Provident Fund(HPF)system on households.Utilizing data from the China Household Finance Survey conducted in 2013,2015,2017,and 2019,this study empirically investigates this effect from two dimensions:the impact of HPF payments on household income and housing loan behavior,and the impact on the Gini coefficient of housing assets within the group.The results indicate that the HPF payment does not significantly impact household income levels.Instead,it increases their likelihood of obtaining housing loans,particularly for middle-income households.Additionally,for any group of families,the HPF payment decreased the housing Gini coefficient among households by approximately 0.11 units.This study may be the first to provide the most direct empirical evidence on the extent of HPF’s impact on housing inequality within a group.It also questions the inference in the literature that“HPF will aggravate housing inequality within the group.”Based on this study’s findings,we expect that housing inequality will continue to be alleviated with continued HPF implementation.In particular,this effect will be more significant if the credit support for lowincome families to purchase houses through the HPF can be further enhanced.展开更多
This study assesses the portfolio concentration of socially responsible investment(SRI)pension funds,which may be subject to a potentially limited asset universe and have a higher concentration and lower performance t...This study assesses the portfolio concentration of socially responsible investment(SRI)pension funds,which may be subject to a potentially limited asset universe and have a higher concentration and lower performance than conventional funds.Nonetheless,in contrast to previous studies on SRI funds,this study considers the informationadvantage theory,positing that skilled managers should increase their concentration in assets in which they possess valuable information,departing from optimization models to achieve outperformance.This study first compares actual fund concentration with concentration obtained from several traditional and modern portfolio optimization techniques(minimum variance,global minimum variance,optimal portfolio,naïve diversification,risk parity,and reward-to-risk timing)to understand whether SRI pension funds concentrate portfolios and deviate from optimization model solutions.Unlike previous studies,the actual fund assets are considered in the optimization models to take into account the real investment profiles of SRI funds.The results indicate that SRI pension funds are less concentrated than conventional funds,and SRI and conventional pension funds largely diversify their portfolios,presenting lower concentration than portfolios formed with the optimization models.Furthermore,concentration strategies positively influence performance in SRI and conventional funds,revealing the use of information advantage.However,SRI and conventional fund managers present poor skills(picking,timing,and trading)to exploit information advantages due to overconfidence issues,which affect performance with concentration strategies.This situation may be modified if SRI funds follow modern optimization models and conventional funds follow traditional optimization models,improving managers’performance and skills.展开更多
Purpose:To explore how different types of research funding affect research papers,with implications for optimizing funding policies and promoting sustainable research development.Design/methodology/approach:We used so...Purpose:To explore how different types of research funding affect research papers,with implications for optimizing funding policies and promoting sustainable research development.Design/methodology/approach:We used social network analysis and citation analysis to compare the influence of funded and non-funded papers,as well as among different funding types.Multidimensional scaling and cohesive subgroup analysis revealed thematic differences.Findings:Funded papers do not always show higher academic influence than non-funded ones,but multifunded papers perform better than single-funded ones.Papers funded by international institutions and HKMT have a greater impact on the international academic community.Funded papers emphasize innovation and interdisciplinarity;non-funded papers focus more on classical theory application.Research limitations:This study used only the WoS Core Collection,potentially missing other funding sources.Practical implications:The findings inform the refinement of funding policies and support strategies that encourage impactful and innovative research.Originality/value:This study offers a multi-level empirical analysis of how funding shapes research influence and thematic trends.展开更多
Pension fund must consider some significant issues when making renewable energy project investment decisions.It is necessary to determine the most important factors and prioritize the indicators.Accordingly,the purpos...Pension fund must consider some significant issues when making renewable energy project investment decisions.It is necessary to determine the most important factors and prioritize the indicators.Accordingly,the purpose of this study is to conduct a priority analysis of the determinants of investment in renewable energy projects by pension funds.This study constructs a novel fuzzy decision-making model.First,five indicators for this process are weighted using an entropy methodology based on sine trigonometric Pythagorean fuzzy sets.The CRITIC methodology is also considered to make a comparative evaluation.Second,five different clean energy investment alternatives for pension funds are ranked using the RATGOS methodology.Similarly,this ranking analysis is also made by considering TOPSIS technique to check the reliability of the results.The main contribution of this study is the creation of a new and comprehensive fuzzy decision-making model to identify the most important factors in renewable energy project investments for pension funds.The proposed model uses the RATGOS technique to rank clean energy investment alternatives for pension funds.By considering the geometrical mean in the RATGOS calculation process,criticisms related to existing ranking techniques can be overcome.The use of sine trigonometric Pythagorean fuzzy numbers provides significant benefits to the quality of the proposed decision-making model.The defuzzification process can be implemented appropriately using these sets.Therefore,this study’s findings pave the way for investors to make investment decisions under these circumstances.It is concluded that the most important criterion is risk minimization.Effective regulations are another critical issue.Furthermore,the ranking results indicate that the most suitable renewable energy alternative is green bonds.The comparative results with STPFY-TOPSIS show that the proposed model generates coherent and reliable findings.展开更多
This study examines the sustainability of China's pension funds in a context of negative population growth,analyzing how demographic shifts,economic fluctuations,and institutional flaws impact fund operations.The ...This study examines the sustainability of China's pension funds in a context of negative population growth,analyzing how demographic shifts,economic fluctuations,and institutional flaws impact fund operations.The research reveals that declining working-age populations and accelerating aging are causing imbalances in fund revenues and expenditures.Slower economic growth and inflation further erode contribution capacity and investment returns,while the drawbacks of the Pay-as-you-go system and provincial-level pooling models exacerbate regional risks.Pension funds face multiple challenges including revenue-expenditure imbalances,investment volatility,systemic design flaws,and population mobility-induced risks.The study proposes comprehensive optimization strategies encompassing population structure improvement,diversified funding channels,expenditure control,enhanced investment management,and institutional reforms.These measures aim to provide theoretical and practical references for addressing the sustainability challenges of pension funds under negative population growth.展开更多
The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions,elevating systemic risk in financial networks.Therefore,developing strategies to alleviate this risk,with a focus ...The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions,elevating systemic risk in financial networks.Therefore,developing strategies to alleviate this risk,with a focus on non-performing assets,has become a research area of interest.Supported by policies related to the Chinese insurance market,this study proposes the establishment of a non-performing assets disposal fund backed by insurance capital.This fund will invest in the non-performing assets of financial institutions with the aim of mitigating systemic risk.Using a linear threshold model,we identify an asymptotically optimal scheme for disposing of nonperforming assets.Additionally,we construct a payment model integrated with nonperforming assets,from which we derive an optimal payment and clearing strategy.Our research also proposes a robust set of criteria to assist regulators in determining whether to use the non-performing assets disposal fund.To demonstrate the efficacy of the fund in reducing systemic risk,we conduct simulations and analyze data from the Chinese interbank financial network.Through this rigorous analysis,we confirm the role of the fund in enhancing the stability of the financial system.展开更多
This study examines the causal relationship between financial technology startup venture capital(VC)financing and its deals with domestic credit provided by the banking sector and equity market movement.Despite the ri...This study examines the causal relationship between financial technology startup venture capital(VC)financing and its deals with domestic credit provided by the banking sector and equity market movement.Despite the rise of alternative finance,such as fintech venture capital(it is the fund that venture capital firms put into young,promising fintech companies so that they can help them expand and scale quickly),which is yet underexplored,borrowers still heavily rely on banks and the stock market for financing.We use panel data from 57 countries from 2010 to 2020 and an advanced econometric method called the cross-sectional autoregressive distributed lag model(CS-ARDL)to determine how the size and number of fintech equity funds dealt with by venture capital firms,banking sector credit,and stock market returns are interrelated at the global level and across regional,income,and economic levels.Our results reveal a cointegrating relationship between fintech venture capital funding and deals with bank loans and equity market returns.However,this relationship varies across the regions studied and between developed and developing economies.Our findings provide crucial guidelines for policymakers to create policies that support balanced financial development by highlighting the global interaction of equity market movements,banking credit,and fintech venture capital investment and lay the groundwork for internationally aligned policies to guarantee the optimal distribution of financial capital and improve economic stability and adaptability by illustrating how these links differ across geographical locations and economic conditions.展开更多
This study investigates the distribution and imbalances of research funding in the field of Environmental Chemistry,utilizing application and funding data fromthe National Natural Science Foundation of China(NSFC)over...This study investigates the distribution and imbalances of research funding in the field of Environmental Chemistry,utilizing application and funding data fromthe National Natural Science Foundation of China(NSFC)over the past decade.The findings reveal significant regional disparities,with Eastern regions receiving over 70%of the national funding,while the Northeast accounts for only 4%to 6.5%.Additionally,the analysis shows notable differences in funding allocation among various research institutions,with a substantial portion of funds concentrated in a few leading institutions,leading to inequities across different types and levels of organizations.The impact of applicant gender on funding disparities is relatively minor;although female applicants have a slightly lower funding rate,the concentration of funds is marginally higher among females.Furthermore,the study highlights that key projects and talent-oriented initiatives,due to their significant funding concentration,exacerbate the existing imbalances.Overall,this research provides valuable insights for optimizing funding policies and advocates for a more equitable distribution of resources in Environmental Chemistry research,addressing the identified disparities.展开更多
The Rural Revitalization Investment Fund serves as a crucial financial instrument for advancing rural revitalization and promoting common prosperity.It aims to address financing and land-use challenges faced by rural ...The Rural Revitalization Investment Fund serves as a crucial financial instrument for advancing rural revitalization and promoting common prosperity.It aims to address financing and land-use challenges faced by rural industries through financial support while fostering coordinated industrial development.The fund primarily operates through equity direct investment and the“mother fund+direct investment”model,with an increasing emphasis on combining government guidance with social capital participation.However,challenges persist,including a shortage of professional talent,insufficient institutional innovation,and weak industrial foundations in rural areas.To enhance the fund’s effectiveness,it is recommended to strengthen professional team management,clearly define its strategic positioning,implement strict supervision,innovate operational mechanisms,and prioritize environmental and social responsibility.These measures will ensure that the fund contributes to rural revitalization while promoting sustainable development and common prosperity.展开更多
This study introduces a fund recommendation system based on the ε-greedy algorithm and an incremental learning framework.This model simulates the interaction process when customers browse the web-pages of fund produc...This study introduces a fund recommendation system based on the ε-greedy algorithm and an incremental learning framework.This model simulates the interaction process when customers browse the web-pages of fund products.Customers click on their preferred fund products when visiting a fund recommendation web-page.The system collects customer click sequences to continually estimate and update their utility function.The system generates product lists using the ε-greedy algorithm,where each product on the list has the probability of 1-ε of being selected as an exploitation strategy,and the probability of ε is chosen as the exploration strategy.We perform a series of numerical tests to evaluate the estimation performance with different values of ε.展开更多
The inaugural"Belt and Road Nepal-China Buddhist Culture and Art Summit Forum"was held at the Lumbini Buddhist University in Nepal.The"Faxian-Xuanzang Scholarship Fund",jointly established by the C...The inaugural"Belt and Road Nepal-China Buddhist Culture and Art Summit Forum"was held at the Lumbini Buddhist University in Nepal.The"Faxian-Xuanzang Scholarship Fund",jointly established by the Chinese Culture Promotion Society and the Lumbini Buddhist University,was officially launched during the forum.The programme aims to support 100 Chinese and Nepali students in the next three years in conducting specialised research in such fields as Buddhist art and historical scripts.展开更多
Recently,funds and corporations have adopted environmental/social/governance(ESG)-related criteria as increasingly important criteria when evaluating investments.The ESG scores of mutual funds,which pool money from ma...Recently,funds and corporations have adopted environmental/social/governance(ESG)-related criteria as increasingly important criteria when evaluating investments.The ESG scores of mutual funds,which pool money from many individuals,are,therefore,significant as a sign of social commitment and deliver long-term results for investors deciding in which fund to invest.However,this scoring process is not transparent,and computing ESG scores requires an extensive review and monitoring of accountancy data.In this study,Machine Learning(ML)was employed to predict six ESG scores of 3192 mutual funds by comparing the performance of the models built solely using 13 variables of ESG-controversial sectorial involvement and 37 variables of financial data.In both cases,three classification and three regression algorithms were applied to the 72 simulations.The results demonstrate an acceptable fit of the Random Forest and Gradient Boosting algorithms in regression exercises(R2 values of 60–80%)and good prediction capabilities for classification(accuracies of approximately 70–80%).The models obtained similar performance when predicting ESG scores either from financial data or ESG-controversial sectorial involvement,illustrating how financial variables are good predictors of ESG scores as data on direct involvement in non-ESG funds’activities.Thus,a relationship between the financial performance of a fund and its ESG score exists and is predictable by ML,saving time and resources.展开更多
基金funded by the Humanities and Social Sciences Research Project of the Ministry of Education of China(Project No.23XJC790007).
文摘This study explores the housing distribution effect of the Housing Provident Fund(HPF)system on households.Utilizing data from the China Household Finance Survey conducted in 2013,2015,2017,and 2019,this study empirically investigates this effect from two dimensions:the impact of HPF payments on household income and housing loan behavior,and the impact on the Gini coefficient of housing assets within the group.The results indicate that the HPF payment does not significantly impact household income levels.Instead,it increases their likelihood of obtaining housing loans,particularly for middle-income households.Additionally,for any group of families,the HPF payment decreased the housing Gini coefficient among households by approximately 0.11 units.This study may be the first to provide the most direct empirical evidence on the extent of HPF’s impact on housing inequality within a group.It also questions the inference in the literature that“HPF will aggravate housing inequality within the group.”Based on this study’s findings,we expect that housing inequality will continue to be alleviated with continued HPF implementation.In particular,this effect will be more significant if the credit support for lowincome families to purchase houses through the HPF can be further enhanced.
基金supported by Government of Aragon[Grant S38_20R]Ibercaja and University of Zaragoza[Grants JIUZ-2021-SOC-03 and JIUZ2022-CSJ-24]Ministerio de Ciencia e Innovación and FEDER[PID2022-136818NB-100].
文摘This study assesses the portfolio concentration of socially responsible investment(SRI)pension funds,which may be subject to a potentially limited asset universe and have a higher concentration and lower performance than conventional funds.Nonetheless,in contrast to previous studies on SRI funds,this study considers the informationadvantage theory,positing that skilled managers should increase their concentration in assets in which they possess valuable information,departing from optimization models to achieve outperformance.This study first compares actual fund concentration with concentration obtained from several traditional and modern portfolio optimization techniques(minimum variance,global minimum variance,optimal portfolio,naïve diversification,risk parity,and reward-to-risk timing)to understand whether SRI pension funds concentrate portfolios and deviate from optimization model solutions.Unlike previous studies,the actual fund assets are considered in the optimization models to take into account the real investment profiles of SRI funds.The results indicate that SRI pension funds are less concentrated than conventional funds,and SRI and conventional pension funds largely diversify their portfolios,presenting lower concentration than portfolios formed with the optimization models.Furthermore,concentration strategies positively influence performance in SRI and conventional funds,revealing the use of information advantage.However,SRI and conventional fund managers present poor skills(picking,timing,and trading)to exploit information advantages due to overconfidence issues,which affect performance with concentration strategies.This situation may be modified if SRI funds follow modern optimization models and conventional funds follow traditional optimization models,improving managers’performance and skills.
基金supported by the National Natural Science Foundation of China(Grant No.72304169)Natural Science Foundation of Shandong Province(Grant No.ZR2023QG113)+1 种基金Youth Innovation Teams in Higher Education Institutions of Shandong Province(Grant No.2023RW007)the Fundamental Research Funds of Shandong University(Grant No.23RWZX29).
文摘Purpose:To explore how different types of research funding affect research papers,with implications for optimizing funding policies and promoting sustainable research development.Design/methodology/approach:We used social network analysis and citation analysis to compare the influence of funded and non-funded papers,as well as among different funding types.Multidimensional scaling and cohesive subgroup analysis revealed thematic differences.Findings:Funded papers do not always show higher academic influence than non-funded ones,but multifunded papers perform better than single-funded ones.Papers funded by international institutions and HKMT have a greater impact on the international academic community.Funded papers emphasize innovation and interdisciplinarity;non-funded papers focus more on classical theory application.Research limitations:This study used only the WoS Core Collection,potentially missing other funding sources.Practical implications:The findings inform the refinement of funding policies and support strategies that encourage impactful and innovative research.Originality/value:This study offers a multi-level empirical analysis of how funding shapes research influence and thematic trends.
文摘Pension fund must consider some significant issues when making renewable energy project investment decisions.It is necessary to determine the most important factors and prioritize the indicators.Accordingly,the purpose of this study is to conduct a priority analysis of the determinants of investment in renewable energy projects by pension funds.This study constructs a novel fuzzy decision-making model.First,five indicators for this process are weighted using an entropy methodology based on sine trigonometric Pythagorean fuzzy sets.The CRITIC methodology is also considered to make a comparative evaluation.Second,five different clean energy investment alternatives for pension funds are ranked using the RATGOS methodology.Similarly,this ranking analysis is also made by considering TOPSIS technique to check the reliability of the results.The main contribution of this study is the creation of a new and comprehensive fuzzy decision-making model to identify the most important factors in renewable energy project investments for pension funds.The proposed model uses the RATGOS technique to rank clean energy investment alternatives for pension funds.By considering the geometrical mean in the RATGOS calculation process,criticisms related to existing ranking techniques can be overcome.The use of sine trigonometric Pythagorean fuzzy numbers provides significant benefits to the quality of the proposed decision-making model.The defuzzification process can be implemented appropriately using these sets.Therefore,this study’s findings pave the way for investors to make investment decisions under these circumstances.It is concluded that the most important criterion is risk minimization.Effective regulations are another critical issue.Furthermore,the ranking results indicate that the most suitable renewable energy alternative is green bonds.The comparative results with STPFY-TOPSIS show that the proposed model generates coherent and reliable findings.
文摘This study examines the sustainability of China's pension funds in a context of negative population growth,analyzing how demographic shifts,economic fluctuations,and institutional flaws impact fund operations.The research reveals that declining working-age populations and accelerating aging are causing imbalances in fund revenues and expenditures.Slower economic growth and inflation further erode contribution capacity and investment returns,while the drawbacks of the Pay-as-you-go system and provincial-level pooling models exacerbate regional risks.Pension funds face multiple challenges including revenue-expenditure imbalances,investment volatility,systemic design flaws,and population mobility-induced risks.The study proposes comprehensive optimization strategies encompassing population structure improvement,diversified funding channels,expenditure control,enhanced investment management,and institutional reforms.These measures aim to provide theoretical and practical references for addressing the sustainability challenges of pension funds under negative population growth.
基金supported by the National Social Science Fund of China(No.22BTJ027).
文摘The COVID-19 pandemic precipitated a surge in the non-performing assets held by financial institutions,elevating systemic risk in financial networks.Therefore,developing strategies to alleviate this risk,with a focus on non-performing assets,has become a research area of interest.Supported by policies related to the Chinese insurance market,this study proposes the establishment of a non-performing assets disposal fund backed by insurance capital.This fund will invest in the non-performing assets of financial institutions with the aim of mitigating systemic risk.Using a linear threshold model,we identify an asymptotically optimal scheme for disposing of nonperforming assets.Additionally,we construct a payment model integrated with nonperforming assets,from which we derive an optimal payment and clearing strategy.Our research also proposes a robust set of criteria to assist regulators in determining whether to use the non-performing assets disposal fund.To demonstrate the efficacy of the fund in reducing systemic risk,we conduct simulations and analyze data from the Chinese interbank financial network.Through this rigorous analysis,we confirm the role of the fund in enhancing the stability of the financial system.
基金financially supported by Doctoral Fellowship of the University Grants Commission,Bangladesh.
文摘This study examines the causal relationship between financial technology startup venture capital(VC)financing and its deals with domestic credit provided by the banking sector and equity market movement.Despite the rise of alternative finance,such as fintech venture capital(it is the fund that venture capital firms put into young,promising fintech companies so that they can help them expand and scale quickly),which is yet underexplored,borrowers still heavily rely on banks and the stock market for financing.We use panel data from 57 countries from 2010 to 2020 and an advanced econometric method called the cross-sectional autoregressive distributed lag model(CS-ARDL)to determine how the size and number of fintech equity funds dealt with by venture capital firms,banking sector credit,and stock market returns are interrelated at the global level and across regional,income,and economic levels.Our results reveal a cointegrating relationship between fintech venture capital funding and deals with bank loans and equity market returns.However,this relationship varies across the regions studied and between developed and developing economies.Our findings provide crucial guidelines for policymakers to create policies that support balanced financial development by highlighting the global interaction of equity market movements,banking credit,and fintech venture capital investment and lay the groundwork for internationally aligned policies to guarantee the optimal distribution of financial capital and improve economic stability and adaptability by illustrating how these links differ across geographical locations and economic conditions.
基金supported by the Major Project of Philosophy and Social Science Research of Jiangsu(No.2019SJZDA073).
文摘This study investigates the distribution and imbalances of research funding in the field of Environmental Chemistry,utilizing application and funding data fromthe National Natural Science Foundation of China(NSFC)over the past decade.The findings reveal significant regional disparities,with Eastern regions receiving over 70%of the national funding,while the Northeast accounts for only 4%to 6.5%.Additionally,the analysis shows notable differences in funding allocation among various research institutions,with a substantial portion of funds concentrated in a few leading institutions,leading to inequities across different types and levels of organizations.The impact of applicant gender on funding disparities is relatively minor;although female applicants have a slightly lower funding rate,the concentration of funds is marginally higher among females.Furthermore,the study highlights that key projects and talent-oriented initiatives,due to their significant funding concentration,exacerbate the existing imbalances.Overall,this research provides valuable insights for optimizing funding policies and advocates for a more equitable distribution of resources in Environmental Chemistry research,addressing the identified disparities.
文摘The Rural Revitalization Investment Fund serves as a crucial financial instrument for advancing rural revitalization and promoting common prosperity.It aims to address financing and land-use challenges faced by rural industries through financial support while fostering coordinated industrial development.The fund primarily operates through equity direct investment and the“mother fund+direct investment”model,with an increasing emphasis on combining government guidance with social capital participation.However,challenges persist,including a shortage of professional talent,insufficient institutional innovation,and weak industrial foundations in rural areas.To enhance the fund’s effectiveness,it is recommended to strengthen professional team management,clearly define its strategic positioning,implement strict supervision,innovate operational mechanisms,and prioritize environmental and social responsibility.These measures will ensure that the fund contributes to rural revitalization while promoting sustainable development and common prosperity.
基金This research was supported by National Key R&D Program of China under No.2022YFA1004000National Natural Science Foundation of China under No.11991023 and 12371324.
文摘This study introduces a fund recommendation system based on the ε-greedy algorithm and an incremental learning framework.This model simulates the interaction process when customers browse the web-pages of fund products.Customers click on their preferred fund products when visiting a fund recommendation web-page.The system collects customer click sequences to continually estimate and update their utility function.The system generates product lists using the ε-greedy algorithm,where each product on the list has the probability of 1-ε of being selected as an exploitation strategy,and the probability of ε is chosen as the exploration strategy.We perform a series of numerical tests to evaluate the estimation performance with different values of ε.
文摘The inaugural"Belt and Road Nepal-China Buddhist Culture and Art Summit Forum"was held at the Lumbini Buddhist University in Nepal.The"Faxian-Xuanzang Scholarship Fund",jointly established by the Chinese Culture Promotion Society and the Lumbini Buddhist University,was officially launched during the forum.The programme aims to support 100 Chinese and Nepali students in the next three years in conducting specialised research in such fields as Buddhist art and historical scripts.
文摘Recently,funds and corporations have adopted environmental/social/governance(ESG)-related criteria as increasingly important criteria when evaluating investments.The ESG scores of mutual funds,which pool money from many individuals,are,therefore,significant as a sign of social commitment and deliver long-term results for investors deciding in which fund to invest.However,this scoring process is not transparent,and computing ESG scores requires an extensive review and monitoring of accountancy data.In this study,Machine Learning(ML)was employed to predict six ESG scores of 3192 mutual funds by comparing the performance of the models built solely using 13 variables of ESG-controversial sectorial involvement and 37 variables of financial data.In both cases,three classification and three regression algorithms were applied to the 72 simulations.The results demonstrate an acceptable fit of the Random Forest and Gradient Boosting algorithms in regression exercises(R2 values of 60–80%)and good prediction capabilities for classification(accuracies of approximately 70–80%).The models obtained similar performance when predicting ESG scores either from financial data or ESG-controversial sectorial involvement,illustrating how financial variables are good predictors of ESG scores as data on direct involvement in non-ESG funds’activities.Thus,a relationship between the financial performance of a fund and its ESG score exists and is predictable by ML,saving time and resources.
