Pub Date : 2024-11-01DOI: 10.1016/j.najef.2024.102308
Yi Zhang , Long Zhou , Zhidong Liu , Baoxiu Wu
This study examines volatility contagion between the US and five BRICS stock markets during the COVID-19 pandemic and the Russo-Ukrainian crisis. We first use the Markov-switching dynamic regression method to endogenously identify various phases of market evolution. Then, we employ a dynamic conditional correlation process to uncover time-varying volatility spillovers relying on the implied volatility induced by daily changes in the investigated markets. Empirical results indicate that market spillover during the two crises presents quite different scenarios. The US has a more significant and persistent contagion effect on the BRICS markets during COVID-19. However, only a short-lived and pulse-like market response is detected in the initial stage of the Russo-Ukrainian crisis, and the volatility interdependency structures do not follow a specific pattern across all implied volatility pairs.
{"title":"Spillover of fear among the US and BRICS equity markets during the COVID-19 crisis and the Russo-Ukrainian conflict","authors":"Yi Zhang , Long Zhou , Zhidong Liu , Baoxiu Wu","doi":"10.1016/j.najef.2024.102308","DOIUrl":"10.1016/j.najef.2024.102308","url":null,"abstract":"<div><div>This study examines volatility contagion between the US and five BRICS stock markets during the COVID-19 pandemic and the Russo-Ukrainian crisis. We first use the Markov-switching dynamic regression method to endogenously identify various phases of market evolution. Then, we employ a dynamic conditional correlation process to uncover time-varying volatility spillovers relying on the implied volatility induced by daily changes in the investigated markets. Empirical results indicate that market spillover during the two crises presents quite different scenarios. The US has a more significant and persistent contagion effect on the BRICS markets during COVID-19. However, only a short-lived and pulse-like market response is detected in the initial stage of the Russo-Ukrainian crisis, and the volatility interdependency structures do not follow a specific pattern across all implied volatility pairs.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102308"},"PeriodicalIF":3.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-31DOI: 10.1016/j.najef.2024.102305
Chuanhui Liu , Zhongyuan Sheng , Xuetong Hu , Chunxiao Tian
This study, utilizing Chinese listed companies from 2007 to 2022, reveals that enterprises can improve their digital transformation strategies by learning from the digital technologies of industry-leading companies. By free-riding on technology adoption, enterprises can reduce their R&D investments in implementing digital transformation projects, as existing digital technologies can be copied and improved for their own use. Furthermore, we find that firms with stronger research capabilities are more efficient at learning from leading firms’ digital technologies. Better digital technologies not only optimize a firm’s strategic plan for digital transformation but also enhance the actual implementation of such projects. This enhancement is achieved by easing financing constraints and diversifying the upstream chain. Our findings are robust to alternative variable measures and endogeneity tests. Overall, we highlight the technological spillovers of digital technology innovations by leading firms, facilitating a deeper digital transformation of other firms through various governance channels.
{"title":"Hand in hand or left behind: The dual impact of leading firms’ digital technologies on industry digital transformation","authors":"Chuanhui Liu , Zhongyuan Sheng , Xuetong Hu , Chunxiao Tian","doi":"10.1016/j.najef.2024.102305","DOIUrl":"10.1016/j.najef.2024.102305","url":null,"abstract":"<div><div>This study, utilizing Chinese listed companies from 2007 to 2022, reveals that enterprises can improve their digital transformation strategies by learning from the digital technologies of industry-leading companies. By free-riding on technology adoption, enterprises can reduce their R&D investments in implementing digital transformation projects, as existing digital technologies can be copied and improved for their own use. Furthermore, we find that firms with stronger research capabilities are more efficient at learning from leading firms’ digital technologies. Better digital technologies not only optimize a firm’s strategic plan for digital transformation but also enhance the actual implementation of such projects. This enhancement is achieved by easing financing constraints and diversifying the upstream chain. Our findings are robust to alternative variable measures and endogeneity tests. Overall, we highlight the technological spillovers of digital technology innovations by leading firms, facilitating a deeper digital transformation of other firms through various governance channels.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102305"},"PeriodicalIF":3.8,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-26DOI: 10.1016/j.najef.2024.102304
Yunzhong Li , Chengfang Ye , Mingxi Li , Wai Yan Shum , Fujun Lai
FinTech has been extensively applied in China in the context of high-quality development. This study quantifies the level of FinTech development in various Chinese cities based on the number of FinTech companies present, investigating the impact and mechanisms of regional FinTech development on enterprises’ Total Factor Productivity (TFP). The results indicate that FinTech significantly enhances enterprises’ TFP. This conclusion remains valid after a series of robustness tests. Mechanism analysis reveals that FinTech contributes to this improvement by enhancing credit availability of enterprises, increasing financing accessibility for businesses, reducing financing costs, alleviating financing constraints, and fostering technological innovation within enterprises. Heterogeneity analysis shows that this positive effect is more pronounced in highly competitive firms, non-financial background firms and regions with more favorable business environments. Overall, our findings demonstrate a positive impact of FinTech on enterprises’ TFP, providing new insights into its beneficial effects.
{"title":"Regional FinTech development and total factor productivity among firms: Evidence from China","authors":"Yunzhong Li , Chengfang Ye , Mingxi Li , Wai Yan Shum , Fujun Lai","doi":"10.1016/j.najef.2024.102304","DOIUrl":"10.1016/j.najef.2024.102304","url":null,"abstract":"<div><div>FinTech has been extensively applied in China in the context of high-quality development. This study quantifies the level of FinTech development in various Chinese cities based on the number of FinTech companies present, investigating the impact and mechanisms of regional FinTech development on enterprises’ Total Factor Productivity (TFP). The results indicate that FinTech significantly enhances enterprises’ TFP. This conclusion remains valid after a series of robustness tests. Mechanism analysis reveals that FinTech contributes to this improvement by enhancing credit availability of enterprises, increasing financing accessibility for businesses, reducing financing costs, alleviating financing constraints, and fostering technological innovation within enterprises. Heterogeneity analysis shows that this positive effect is more pronounced in highly competitive firms, non-financial background firms and regions with more favorable business environments. Overall, our findings demonstrate a positive impact of FinTech on enterprises’ TFP, providing new insights into its beneficial effects.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102304"},"PeriodicalIF":3.8,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.najef.2024.102302
Ziqing Wu, Leyi Chen
In the era of high-quality economic development, oil price uncertainty (OVX) and the total factor productivity (TFP) of corporations are pivotal issues for both policymakers and scholars. This study leverages the implied volatility of oil prices and financial data from Chinese listed industrial companies spanning 2010 to 2022 to investigate the influence of OVX on firms’ TFP and the underlying mechanisms. The findings reveal that OVX substantially dampens firms’ TFP, with corporate leverage and financialization identified as key channels through which this impact occurs. Further heterogeneity analysis indicates that the negative impact of OVX on TFP is particularly pronounced in firms operating in industries with low concentration and among small and medium-sized enterprises (SMEs). The extension analysis suggests a threshold effect in the relationship between OVX and corporate TFP, with the suppressive effect of OVX on TFP intensifying as the level of corporate financialization increases. Consequently, it is imperative for policymakers to closely monitor oil price fluctuations and implement timely strategies to mitigate the risks associated with OVX.
{"title":"Does oil price uncertainty affect corporate total factor productivity? Evidence from China","authors":"Ziqing Wu, Leyi Chen","doi":"10.1016/j.najef.2024.102302","DOIUrl":"10.1016/j.najef.2024.102302","url":null,"abstract":"<div><div>In the era of high-quality economic development, oil price uncertainty (OVX) and the total factor productivity (TFP) of corporations are pivotal issues for both policymakers and scholars. This study leverages the implied volatility of oil prices and financial data from Chinese listed industrial companies spanning 2010 to 2022 to investigate the influence of OVX on firms’ TFP and the underlying mechanisms. The findings reveal that OVX substantially dampens firms’ TFP, with corporate leverage and financialization identified as key channels through which this impact occurs. Further heterogeneity analysis indicates that the negative impact of OVX on TFP is particularly pronounced in firms operating in industries with low concentration and among small and medium-sized enterprises (SMEs). The extension analysis suggests a threshold effect in the relationship between OVX and corporate TFP, with the suppressive effect of OVX on TFP intensifying as the level of corporate financialization increases. Consequently, it is imperative for policymakers to closely monitor oil price fluctuations and implement timely strategies to mitigate the risks associated with OVX.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102302"},"PeriodicalIF":3.8,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.najef.2024.102303
Renzhong Li , Chen Fei , Weiyin Fei
Blockchain-based token platform economy is a new branch of digital platform economics. Constructing a continuous time dynamic model of token platform economy, this paper analyzes what kind of ESG policy is appropriate for the government, meanwhile the token platform participants (developers, users and speculators) make optimal investments and decisions under ESG policy. Simulation result shows neutral ESG policy is optimal. Based on the given neutral ESG policy, we have done the research on ESG investment and decision strategies for platform participants. Our research shows that the tokens selling rate and efforts of green platform (ESG score greater than 0) developers are lower than the ones of brown platform (ESG score less than 0). Consequently, when developers’ token retention is about half of the initial amount, users should invest more brown tokens. Speculators should invest brown tokens for developers’ high token retention. Green token investments of speculators and users are needed in other cases. Next, the impact of the government’s three ESG policies on the maturity or termination of the platform also been analyzed. An important conclusion occurred: the government’s aggressive or conservative ESG policy cannot make the development of the green platform better; Therefore, we suggest a neutral ESG policy which means that the government could adopt high tax incentive and high tax burden on the green and brown platform while it is not necessary to implement the extra subsidy and punishment policy on the green and brown platform.
{"title":"Impact of government’s support policy on decision-making of platform participants under ESG","authors":"Renzhong Li , Chen Fei , Weiyin Fei","doi":"10.1016/j.najef.2024.102303","DOIUrl":"10.1016/j.najef.2024.102303","url":null,"abstract":"<div><div>Blockchain-based token platform economy is a new branch of digital platform economics. Constructing a continuous time dynamic model of token platform economy, this paper analyzes what kind of ESG policy is appropriate for the government, meanwhile the token platform participants (developers, users and speculators) make optimal investments and decisions under ESG policy. Simulation result shows neutral ESG policy is optimal. Based on the given neutral ESG policy, we have done the research on ESG investment and decision strategies for platform participants. Our research shows that the tokens selling rate and efforts of green platform (ESG score greater than 0) developers are lower than the ones of brown platform (ESG score less than 0). Consequently, when developers’ token retention is about half of the initial amount, users should invest more brown tokens. Speculators should invest brown tokens for developers’ high token retention. Green token investments of speculators and users are needed in other cases. Next, the impact of the government’s three ESG policies on the maturity or termination of the platform also been analyzed. An important conclusion occurred: the government’s aggressive or conservative ESG policy cannot make the development of the green platform better; Therefore, we suggest a neutral ESG policy which means that the government could adopt high tax incentive and high tax burden on the green and brown platform while it is not necessary to implement the extra subsidy and punishment policy on the green and brown platform.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102303"},"PeriodicalIF":3.8,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.najef.2024.102301
Yantao Ling , Yan Han , Qingzhong Ren , Jing Xu , Mengqiu Cao , Xing Gao
There is no ‘one size fits all’ product strategy for the ‘green’ market. Although prior studies have explored the influence of consumer environmental awareness on decisions pertaining to green production, further investigation is required regarding the impact of consumer willingness to pay (WTP) on green technology choices and product design, and the ongoing debate about the environmental consequences of both firm and consumer behaviour. This study aims to explore strategies adopted by an enterprise intending to introduce a green product. Utilising optimisation methodology, we investigate the strategies employed for introducing green products, considering pivotal factors such as consumers’ WTP, variable costs, the research costs associated with green technology, and the constraints imposed by the level of green technology. Our research investigates the strategies for introducing, and the optimal pricing of, green products, outlining the impact of the aforementioned factors on the market penetration of green products and company profits. Additionally, this research further explores the impact of consumers’ WTP and enterprises’ use of eco-friendly materials on environmental quality. The results indicate that the strategies for launching green products and the impact of eco-friendly materials on environmental quality depend on the enterprise’s technological parameters and consumers’ WTP. The findings suggest that the market penetration rate of green products increases in line with consumers’ WTP and the level of greenness of products, while higher research costs will decrease the penetration rate of green products. This research contributes to the field of green innovation by showcasing how enterprises make decisions about production and green technology innovation.
{"title":"The effect of consumer willingness to pay on enterprises’ decisions about adopting low-carbon technology","authors":"Yantao Ling , Yan Han , Qingzhong Ren , Jing Xu , Mengqiu Cao , Xing Gao","doi":"10.1016/j.najef.2024.102301","DOIUrl":"10.1016/j.najef.2024.102301","url":null,"abstract":"<div><div>There is no ‘one size fits all’ product strategy for the ‘green’ market. Although prior studies have explored the influence of consumer environmental awareness on decisions pertaining to green production, further investigation is required regarding the impact of consumer willingness to pay (WTP) on green technology choices and product design, and the ongoing debate about the environmental consequences of both firm and consumer behaviour. This study aims to explore strategies adopted by an enterprise intending to introduce a green product. Utilising optimisation methodology, we investigate the strategies employed for introducing green products, considering pivotal factors such as consumers’ WTP, variable costs, the research costs associated with green technology, and the constraints imposed by the level of green technology. Our research investigates the strategies for introducing, and the optimal pricing of, green products, outlining the impact of the aforementioned factors on the market penetration of green products and company profits. Additionally, this research further explores the impact of consumers’ WTP and enterprises’ use of eco-friendly materials on environmental quality. The results indicate that the strategies for launching green products and the impact of eco-friendly materials on environmental quality depend on the enterprise’s technological parameters and consumers’ WTP. The findings suggest that the market penetration rate of green products increases in line with consumers’ WTP and the level of greenness of products, while higher research costs will decrease the penetration rate of green products. This research contributes to the field of green innovation by showcasing how enterprises make decisions about production and green technology innovation.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102301"},"PeriodicalIF":3.8,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.najef.2024.102300
Rangan Gupta , Jacobus Nel , Joshua Nielsen , Christian Pierdzioch
We study whether booms and busts in the stock market of the United States (US) drives its volatility. Given this, first, we employ the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to identify both positive and negative bubbles in the short-, medium, and long-term. We successfully detect major crashes and rallies during the weekly period from January 1973 to December 2020. Second, we utilize a nonparametric causality-in-quantiles approach to analyze the predictive impact of our bubble indicators on daily data-based weekly realized volatility (RV). This econometric framework allows us to circumvent potential misspecification due to nonlinearity and instability, rendering the results of weak causal influence derived from a linear framework invalid. The MS-LPPLS-CIs reveal strong evidence of predictability for RV over its entire conditional distribution. We observe relatively stronger impacts for the positive bubbles indicators, with our findings being robust to an alternative metric of volatility, namely squared returns, and weekly realized volatilities derived from 5 (RV5)- and 10 (RV10)-minutes interval intraday data. Furthermore, we detect evidence of predictability for RV5 and RV10 of nine other developed and emerging stock markets. In addition, we also find strong evidence of causal feedbacks from RV5 and RV10 on to the MS-LPPLS-CIs of the 10 countries considered. Finally, time-varying connectedness of the RVs of the G7 stock markets is also shown to be strongly (positively) predicted by the connectedness of the six bubbles indicators. Our findings have significant implications for investors and policymakers.
{"title":"Stock market volatility and multi-scale positive and negative bubbles","authors":"Rangan Gupta , Jacobus Nel , Joshua Nielsen , Christian Pierdzioch","doi":"10.1016/j.najef.2024.102300","DOIUrl":"10.1016/j.najef.2024.102300","url":null,"abstract":"<div><div>We study whether booms and busts in the stock market of the United States (US) drives its volatility. Given this, first, we employ the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to identify both positive and negative bubbles in the short-, medium, and long-term. We successfully detect major crashes and rallies during the weekly period from January 1973 to December 2020. Second, we utilize a nonparametric causality-in-quantiles approach to analyze the predictive impact of our bubble indicators on daily data-based weekly realized volatility (<em>RV</em>). This econometric framework allows us to circumvent potential misspecification due to nonlinearity and instability, rendering the results of weak causal influence derived from a linear framework invalid. The MS-LPPLS-CIs reveal strong evidence of predictability for <em>RV</em> over its entire conditional distribution. We observe relatively stronger impacts for the positive bubbles indicators, with our findings being robust to an alternative metric of volatility, namely squared returns, and weekly realized volatilities derived from 5 (<em>RV5</em>)- and 10 (RV10)-minutes interval intraday data. Furthermore, we detect evidence of predictability for <em>RV5</em> and <em>RV10</em> of nine other developed and emerging stock markets. In addition, we also find strong evidence of causal feedbacks from <em>RV5</em> and <em>RV10</em> on to the MS-LPPLS-CIs of the 10 countries considered. Finally, time-varying connectedness of the <em>RV</em>s of the G7 stock markets is also shown to be strongly (positively) predicted by the connectedness of the six bubbles indicators. Our findings have significant implications for investors and policymakers.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102300"},"PeriodicalIF":3.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to provide a systematic inquiry into the return spillover dynamics between a network of Indian sectoral indices during the pre- and post-pandemic periods. To analyze the same, this paper uses the asymmetric time-varying parameter vector autoregressions (TVP-VAR) framework. Furthermore, in the spirit of Broadstock et al. (2020), we perform dynamic portfolio exercises based on common hedging techniques and the minimum connectedness portfolio approach to determine what better captures asymmetry. Our daily dataset includes 12 sectoral stocks spanning from January 01, 2017, to May 5, 2023. The findings reveal that negative connectedness dominates throughout the sample period, demonstrating that profit-maximizing agents and risk-averse investors are more likely to react negatively to news. We also show that in the network, the average net transmitters are the banking and other financial service sectors, whereas the net receivers are the information technology, pharmaceutical, and fast-moving consumer goods sectors throughout the period under consideration. Our results show that the minimum connectedness portfolio (MCoP) approach is a very useful method based on Sharpe ratios, as it is either the first or second most profitable among these three competing methods. These results, therefore, yield valuable insights for policymakers and investors.
{"title":"Unveiling asymmetric return spillovers with portfolio implications among Indian stock sectors during Covid-19 pandemic","authors":"Aswini Kumar Mishra, Kamesh Anand K, Akhil Venkatasai Kappagantula","doi":"10.1016/j.najef.2024.102297","DOIUrl":"10.1016/j.najef.2024.102297","url":null,"abstract":"<div><div>This paper aims to provide a systematic inquiry into the return spillover dynamics between a network of Indian sectoral indices during the pre- and post-pandemic periods. To analyze the same, this paper uses the asymmetric time-varying parameter vector autoregressions (TVP-VAR) framework. Furthermore, in the spirit of Broadstock et al. (2020), we perform dynamic portfolio exercises based on common hedging techniques and the minimum connectedness portfolio approach to determine what better captures asymmetry. Our daily dataset includes 12 sectoral stocks spanning from January 01, 2017, to May 5, 2023. The findings reveal that negative connectedness dominates throughout the sample period, demonstrating that profit-maximizing agents and risk-averse investors are more likely to react negatively to news. We also show that in the network, the average net transmitters are the banking and other financial service sectors, whereas the net receivers are the information technology, pharmaceutical, and fast-moving consumer goods sectors throughout the period under consideration. Our results show that the minimum connectedness portfolio (MCoP) approach is a very useful method based on Sharpe ratios, as it is either the first or second most profitable among these three competing methods. These results, therefore, yield valuable insights for policymakers and investors.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102297"},"PeriodicalIF":3.8,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1016/j.najef.2024.102295
Limin Wen , Junxue Li , Jiliang Sheng , Yi Zhang
This paper establishes an active portfolio model that considers corporate Environmental, Social, and Governance (ESG) ratings, examining the impact of ESG information on portfolio performance. Based on the exponential utility function, the paper incorporates ESG scores and ESG risk (uncertainty factors) into active portfolio management and derives the analytical solution of the model. Theoretical findings indicate that ESG risk adjusts the optimal portfolio, helping to mitigate losses due to ESG divergence. The paper conducts empirical research using ESG ratings from three well-known rating agencies and the CSI300 index. The empirical results demonstrate that ESG preferences enhance the ESG quality of the portfolio. Consistent with theoretical predictions, reliance on a single ESG rating may lead to adverse outcomes, especially when the selected rating agency’s standards deviate from market norms. In contrast, portfolios that include ESG uncertainty exhibit higher stability and lower loss risk, showing good robustness across different stages and industries.
{"title":"Active portfolio management in the face of ESG uncertainty: An agile framework for adaptive investment strategies","authors":"Limin Wen , Junxue Li , Jiliang Sheng , Yi Zhang","doi":"10.1016/j.najef.2024.102295","DOIUrl":"10.1016/j.najef.2024.102295","url":null,"abstract":"<div><div>This paper establishes an active portfolio model that considers corporate Environmental, Social, and Governance (ESG) ratings, examining the impact of ESG information on portfolio performance. Based on the exponential utility function, the paper incorporates ESG scores and ESG risk (uncertainty factors) into active portfolio management and derives the analytical solution of the model. Theoretical findings indicate that ESG risk adjusts the optimal portfolio, helping to mitigate losses due to ESG divergence. The paper conducts empirical research using ESG ratings from three well-known rating agencies and the CSI300 index. The empirical results demonstrate that ESG preferences enhance the ESG quality of the portfolio. Consistent with theoretical predictions, reliance on a single ESG rating may lead to adverse outcomes, especially when the selected rating agency’s standards deviate from market norms. In contrast, portfolios that include ESG uncertainty exhibit higher stability and lower loss risk, showing good robustness across different stages and industries.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102295"},"PeriodicalIF":3.8,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-12DOI: 10.1016/j.najef.2024.102298
Jinfang Li
We present a dynamic asset pricing model combining individual investor sentiment, higher order expectations with learning. In the basic model, the forward-looking expectation of individual investors is distorted by individual sentiment and higher order expectations, so prices react more sluggishly to changes in fundamentals of the asset. We find that investor sentiment plays a significant role in the effect of higher order expectations on asset pricing. Investor sentiment not only makes the price tightly anchor to the initial price, but also increases the sentiment drift of the price. Higher order expectations exhibit inertia, therefore aggravating the anchor to the initial price. With the increase of the order, more and more investor sentiment is integrated into the prices, amplifying the bias of pubic signal relative to fundamentals. When individual sentiment investors learn valuable public information through price system in the long term, the information component of the equilibrium price increases, thus drawing the asset price back toward the rational expected value. The model could offer a partial explanation to the inertia and drift in the price path.
{"title":"Higher order expectations, learning, and sentiment pricing dynamics","authors":"Jinfang Li","doi":"10.1016/j.najef.2024.102298","DOIUrl":"10.1016/j.najef.2024.102298","url":null,"abstract":"<div><div>We present a dynamic asset pricing model combining individual investor sentiment, higher order expectations with learning. In the basic model, the forward-looking expectation of individual investors is distorted by individual sentiment and higher order expectations, so prices react more sluggishly to changes in fundamentals of the asset. We find that investor sentiment plays a significant role in the effect of higher order expectations on asset pricing. Investor sentiment not only makes the price tightly anchor to the initial price, but also increases the sentiment drift of the price. Higher order expectations exhibit inertia, therefore aggravating the anchor to the initial price. With the increase of the order, more and more investor sentiment is integrated into the prices, amplifying the bias of pubic signal relative to fundamentals. When individual sentiment investors learn valuable public information through price system in the long term, the information component of the equilibrium price increases, thus drawing the asset price back toward the rational expected value. The model could offer a partial explanation to the inertia and drift in the price path.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102298"},"PeriodicalIF":3.8,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142698311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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