Pub Date : 2025-01-01DOI: 10.1016/j.najef.2024.102349
Yu-En Lin , Yu-Xin Xu , Bo Yu , Keith S.K. Lam
This study investigates the compensation peer effect of investments and the moderate effect of outcome uncertainty on the compensation peer effect in the US stock markets. We document two new findings. Our results suggest a significant positive relation between firms’ own and compensation peers’ investments and a significant negative moderate effect of the outcome uncertainty on the relation. In addition, we also find that the moderate effect is more pronounced in the low information accuracy groups, suggesting that the inaccurate information disclosure of compensation peers’ investments is the main cause of the negative moderate effect. Our results remain sound after various robustness and endogenous tests.
{"title":"The impact of outcome uncertainty on corporate investment compensation peer effects","authors":"Yu-En Lin , Yu-Xin Xu , Bo Yu , Keith S.K. Lam","doi":"10.1016/j.najef.2024.102349","DOIUrl":"10.1016/j.najef.2024.102349","url":null,"abstract":"<div><div>This study investigates the compensation peer effect of investments and the moderate effect of outcome uncertainty on the compensation peer effect in the US stock markets. We document two new findings. Our results suggest a significant positive relation between firms’ own and compensation peers’ investments and a significant negative moderate effect of the outcome uncertainty on the relation. In addition, we also find that the moderate effect is more pronounced in the low information accuracy groups, suggesting that the inaccurate information disclosure of compensation peers’ investments is the main cause of the negative moderate effect. Our results remain sound after various robustness and endogenous tests.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102349"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103401","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 : 2025-01-01DOI: 10.1016/j.najef.2025.102369
Abbas Valadkhani , Barry O'Mahony
This paper investigates the relationship between market broadening and future volatility in the U.S. using monthly data from May 2003 to July 2024. Market broadening is measured by the price returns of two exchange-traded funds (ETFs): the S&P 500 Equal Weight ETF (RSP) and the Russell 2000 Equal Weight ETF (IWM). We employ an Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model to ensure the conditional variance remains positive, even when ETF returns are negative. Our findings support an inverted-U hypothesis, suggesting that market gains were more widely dispersed until 2014 but have since become concentrated among mega-cap stocks. More importantly, the results indicate that broadening market participation significantly reduces future volatility. This effect is consistent regardless of whether market broadening is measured using RSP or IWM. Our estimated time-varying GARCH series exhibit strong co-movements and co-jumpings with the VIX index, accurately capturing most of its turning points and critical events. This study offers practical insights into market behavior, investment strategies, and the risks of gains mainly driven by mega-cap companies, especially for market-cap ETF investors, without the need to analyze individual stocks or use hard-to-get data.
{"title":"Market broadening and future volatility: A study of Russell 2000 and S&P 500 equal weight ETFs","authors":"Abbas Valadkhani , Barry O'Mahony","doi":"10.1016/j.najef.2025.102369","DOIUrl":"10.1016/j.najef.2025.102369","url":null,"abstract":"<div><div>This paper investigates the relationship between market broadening and future volatility in the U.S. using monthly data from May 2003 to July 2024. Market broadening is measured by the price returns of two exchange-traded funds (ETFs): the S&P 500 Equal Weight ETF (RSP) and the Russell 2000 Equal Weight ETF (IWM). We employ an Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model to ensure the conditional variance remains positive, even when ETF returns are negative. Our findings support an inverted-U hypothesis, suggesting that market gains were more widely dispersed until 2014 but have since become concentrated among mega-cap stocks. More importantly, the results indicate that broadening market participation significantly reduces future volatility. This effect is consistent regardless of whether market broadening is measured using RSP or IWM. Our estimated time-varying GARCH series exhibit strong co-movements and co-jumpings with the VIX index, accurately capturing most of its turning points and critical events. This study offers practical insights into market behavior, investment strategies, and the risks of gains mainly driven by mega-cap companies, especially for market-cap ETF investors, without the need to analyze individual stocks or use hard-to-get data.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102369"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.najef.2024.102317
Yan Chen , Qiong Luo , Feipeng Zhang
The Regional Comprehensive Economic Partnership (RCEP) has brought both opportunities and new challenges to the Asia-Pacific financial markets. To analyze the spillover effects of stock market risk among RCEP countries, this paper constructs a comprehensive framework for systemic risk management encompassing three aspects: risk measurement, connectivity analysis and identification of influential factors. Specifically, we apply the CoES as a risk measurement metric to construct a tail risk network. Based on risk decomposition in sliding windows, we examine the hierarchical propagation pathways, intensities and evolution mechanisms of systemic risk in RCEP stock markets across four levels (system, group, country and institution). Subsequently, we use a tail-event driven dynamic network quantile regression (TEDNQR) model to explore the influence of network topology, node heterogeneity, and common factors on stock price changes across different quantile levels. Finally, we employ robustness analysis based on goodness-of-fit and DM test to validate the reliability of our methodology and conclusions. The empirical results indicate that both the risk performance and the influential factors of RCEP stock markets exhibit time-varying and tail characteristics. Overall, simultaneous network effects significantly and positively impact stock movements, playing a dominant role among all factors.
{"title":"Systemic risk and network effects in RCEP financial markets: Evidence from the TEDNQR model","authors":"Yan Chen , Qiong Luo , Feipeng Zhang","doi":"10.1016/j.najef.2024.102317","DOIUrl":"10.1016/j.najef.2024.102317","url":null,"abstract":"<div><div>The Regional Comprehensive Economic Partnership (RCEP) has brought both opportunities and new challenges to the Asia-Pacific financial markets. To analyze the spillover effects of stock market risk among RCEP countries, this paper constructs a comprehensive framework for systemic risk management encompassing three aspects: risk measurement, connectivity analysis and identification of influential factors. Specifically, we apply the CoES as a risk measurement metric to construct a tail risk network. Based on risk decomposition in sliding windows, we examine the hierarchical propagation pathways, intensities and evolution mechanisms of systemic risk in RCEP stock markets across four levels (system, group, country and institution). Subsequently, we use a tail-event driven dynamic network quantile regression (TEDNQR) model to explore the influence of network topology, node heterogeneity, and common factors on stock price changes across different quantile levels. Finally, we employ robustness analysis based on goodness-of-fit and DM test to validate the reliability of our methodology and conclusions. The empirical results indicate that both the risk performance and the influential factors of RCEP stock markets exhibit time-varying and tail characteristics. Overall, simultaneous network effects significantly and positively impact stock movements, playing a dominant role among all factors.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102317"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103411","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 : 2025-01-01DOI: 10.1016/j.najef.2025.102365
Chao Tang , Peimin Chen , Shu Zhang
The growing frequency of natural disasters and the impacts of climate change have caused many companies to face liquidity shortages. Consequently, how to hedge such risks has become an urgent issue for investors to consider. To construct an effective hedge tool, in this paper we mainly explore the pricing problem of catastrophe equity put options (CatEPuts) with liquidity risk. In the context of losses caused by catastrophic events, we use Markov modulated Poisson processes (MMPP) to depict its intensity. The default event of the option issuer occurring at any time before the expiration of the option and the correlation existing between the stock and the assets of the option issuer are also considered and involved in our model. Under this framework, we obtain a closed-form formula for CatEPuts with liquidity risk and default risk under MMPP by applying Escher transformation and multidimensional normality. Finally, we conduct numerical analysis. By comparing solutions with and without influencing factors, the significance of risk factors and jump diffusion processes are elucidated. It also includes sensitivity analysis to explore the impact of key parameters on the price of CatEPuts. In addition, as an application we explore some realistic cases, such as the measure of VaR. Through risk management analysis, it demonstrates that CatEPuts can effectively hedge catastrophic risks.
{"title":"Valuing catastrophe equity put options with liquidity risk, default risk and jumps","authors":"Chao Tang , Peimin Chen , Shu Zhang","doi":"10.1016/j.najef.2025.102365","DOIUrl":"10.1016/j.najef.2025.102365","url":null,"abstract":"<div><div>The growing frequency of natural disasters and the impacts of climate change have caused many companies to face liquidity shortages. Consequently, how to hedge such risks has become an urgent issue for investors to consider. To construct an effective hedge tool, in this paper we mainly explore the pricing problem of catastrophe equity put options (CatEPuts) with liquidity risk. In the context of losses caused by catastrophic events, we use Markov modulated Poisson processes (MMPP) to depict its intensity. The default event of the option issuer occurring at any time before the expiration of the option and the correlation existing between the stock and the assets of the option issuer are also considered and involved in our model. Under this framework, we obtain a closed-form formula for CatEPuts with liquidity risk and default risk under MMPP by applying Escher transformation and multidimensional normality. Finally, we conduct numerical analysis. By comparing solutions with and without influencing factors, the significance of risk factors and jump diffusion processes are elucidated. It also includes sensitivity analysis to explore the impact of key parameters on the price of CatEPuts. In addition, as an application we explore some realistic cases, such as the measure of <em>VaR</em>. Through risk management analysis, it demonstrates that CatEPuts can effectively hedge catastrophic risks.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102365"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094283","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 : 2025-01-01DOI: 10.1016/j.najef.2025.102363
Bin Gao , Mimi Qin , Jun Xie
Digital transformation empowers enterprises with new kinetic energy for high-quality development. Can digital transformation enhance the transparency of the capital market? This study constructs a digital transformation index and examines its impact on the information transparency of Chinese listed companies from the perspective of information senders. We find that digital transformation significantly enhances enterprise information transparency, and the relationship is more pronounced in non-technological enterprises, enterprises with high ownership concentration, and enterprises with high levels of intellectual property protection. Channel tests show that reducing management myopia and increasing news media supervision are possible mechanisms. Overall, our findings provide critical insights for improving the transparency construction of China’s capital market.
{"title":"Does corporate digital transformation improve capital market transparency? Evidence from China","authors":"Bin Gao , Mimi Qin , Jun Xie","doi":"10.1016/j.najef.2025.102363","DOIUrl":"10.1016/j.najef.2025.102363","url":null,"abstract":"<div><div>Digital transformation empowers enterprises with new kinetic energy for high-quality development. Can digital transformation enhance the transparency of the<!--> <!-->capital market? This study constructs a digital transformation index and examines its impact on the information transparency of Chinese listed companies from the perspective of information senders. We find that digital transformation significantly enhances enterprise information transparency, and the relationship is more pronounced in non-technological enterprises, enterprises with high ownership concentration, and enterprises with high levels of intellectual property protection. Channel tests show that reducing management myopia and increasing news media supervision are possible mechanisms. Overall, our findings provide critical insights for improving the transparency construction of China’s capital market.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102363"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093986","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 : 2025-01-01DOI: 10.1016/j.najef.2025.102361
Xiao Jin , Shu-Ling Lin
Several United States banks went bankrupt in 2023, and the total scale exceeded the subprime 2008 mortgage crisis. Thus, determining how to better predict banks’ systemic risks is crucial. While past research used quantitative data and statistical methods, rarely incorporated qualitative data, and lacked research exploring the impact of public confidence on systemic risk.
This study examined 445,500 daily multimodal quantitative and qualitative data to analyze financial news. We obtained data on public confidence through finance bidirectional encoder representations from transformers (hereafter FinBERT) to explore the relationship between public confidence and systemic risk through temporal fusion transformers (TFTs). We established an early prediction model that predicts the next 5 and 20 days, achieving more accurate prediction performance than linear regression, LSTM (long short-term memory), and XGB (eXtreme gradient boosting).
Based on the model that uses the past 20 days to predict the next five days, we found that positive and negative public confidence had a greater impact on systemic risk. In comparison, neutral public confidence had a lesser effect. Macro data such as carbon dioxide emissions also impact systemic risk. By expanding the time range to 60 days to predict 20 days, we found that the most significant impact on systemic risk factors was month, negative public information, interest rate, quasi-leverage, and the GDP growth rate.
The findings indicate that public confidence deserves more attention than macro variables in preventing systemic risks in the banking industry. Negative public confidence significantly affects systemic risk, echoing the adage that Bad news has wings.
{"title":"An early prediction model on systemic risk under global risk: Using FinBERT and temporal fusion transformer to multimodal data fusion framework","authors":"Xiao Jin , Shu-Ling Lin","doi":"10.1016/j.najef.2025.102361","DOIUrl":"10.1016/j.najef.2025.102361","url":null,"abstract":"<div><div>Several United States banks went bankrupt in 2023, and the total scale exceeded the subprime 2008 mortgage crisis. Thus, determining how to better predict banks’ systemic risks is crucial. While past research used quantitative data and statistical methods, rarely incorporated qualitative data, and lacked research exploring the impact of public confidence on systemic risk.</div><div>This study examined 445,500 daily multimodal quantitative and qualitative data to analyze financial news. We obtained data on public confidence through finance bidirectional encoder representations from transformers (hereafter FinBERT) to explore the relationship between public confidence and systemic risk through temporal fusion transformers (TFTs). We established an early prediction model that predicts the next 5 and 20 days, achieving more accurate prediction performance than <em>linear regression</em>, <em>LSTM</em> (long short-term memory), and <em>XGB</em> (eXtreme gradient boosting).</div><div>Based on the model that uses the past 20 days to predict the next five days, we found that positive and negative public confidence had a greater impact on systemic risk. In comparison, neutral public confidence had a lesser effect. Macro data such as carbon dioxide emissions also impact systemic risk. By expanding the time range to 60 days to predict 20 days, we found that the most significant impact on systemic risk factors was month, negative public information, interest rate, quasi-leverage, and the GDP growth rate.</div><div>The findings indicate that public confidence deserves more attention than macro variables in preventing systemic risks in the banking industry. Negative public confidence significantly affects systemic risk, echoing the adage that <em>Bad news has wings</em>.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102361"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094285","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 : 2025-01-01DOI: 10.1016/j.najef.2024.102343
Yu-fan Wan , Ming-hui Wang , Feng-lin Wu
We investigate the impact of climate policy uncertainty shocks on stock market stability in both developed and emerging G20 economies. Using the network connectedness framework developed by Diebold and Yılmaz (2014), we quantify the risk spillover effects of climate policy uncertainty across various economics. Then, we employ the minimum spanning tree method to identify key risk transmission chains and analyze the changes after the implementation of the Paris Agreement. Our findings indicate that economies with robust financial systems exhibit stronger resilience to climate policy uncertainty shocks, while emerging markets show greater connectedness fluctuations and longer recovery periods after these shocks. Economies with weaker financial systems suffer more severe adverse effects. Furthermore, stable financial systems are becoming key nodes in the risk transmission network post the Paris Agreement, reflecting structural changes in global financial markets in response to climate policy shocks. Our research contributes to the growing literature of how climate policy uncertainty shock affects financial stability through complex networks analysis.
{"title":"Greater fragility, greater exposure: A network-based analysis of climate policy uncertainty shocks and G20 stock markets stability","authors":"Yu-fan Wan , Ming-hui Wang , Feng-lin Wu","doi":"10.1016/j.najef.2024.102343","DOIUrl":"10.1016/j.najef.2024.102343","url":null,"abstract":"<div><div>We investigate the impact of climate policy uncertainty shocks on stock market stability in both developed and emerging G20 economies. Using the network connectedness framework developed by Diebold and Yılmaz (2014), we quantify the risk spillover effects of climate policy uncertainty across various economics. Then, we employ the minimum spanning tree method to identify key risk transmission chains and analyze the changes after the implementation of the Paris Agreement. Our findings indicate that economies with robust financial systems exhibit stronger resilience to climate policy uncertainty shocks, while emerging markets show greater connectedness fluctuations and longer recovery periods after these shocks. Economies with weaker financial systems suffer more severe adverse effects. Furthermore, stable financial systems are becoming key nodes in the risk transmission network post the Paris Agreement, reflecting structural changes in global financial markets in response to climate policy shocks. Our research contributes to the growing literature of how climate policy uncertainty shock affects financial stability through complex networks analysis.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102343"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094372","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 : 2025-01-01DOI: 10.1016/j.najef.2024.102347
Wei-Peng Chen , Chih-Chiang Wu , Withz Aimable
This study examines the liquidity spillovers in the cryptocurrency market during times of uncertainty. The empirical results show that liquidity spillovers are lower than both return and volatility spillovers, and liquidity spillovers increase noticeably during times of market shocks. Ethereum is the dominant transmitter of liquidity spillovers, followed by Bitcoin. We also find that heightened crude oil volatility, stock volatility, and economic policy uncertainty contribute to more significant liquidity spillovers within cryptocurrency markets. Moreover, increased volatility in exchange rates, crude oil, gold, and stock markets and economic policy uncertainty would enhance Ethereum’s role as a transmitter of liquidity shocks in the cryptocurrency market. These findings are relevant for investors and regulators to manage risks and uncertainties in the cryptocurrency market.
{"title":"Cryptocurrency market spillover in times of uncertainty","authors":"Wei-Peng Chen , Chih-Chiang Wu , Withz Aimable","doi":"10.1016/j.najef.2024.102347","DOIUrl":"10.1016/j.najef.2024.102347","url":null,"abstract":"<div><div>This study examines the liquidity spillovers in the cryptocurrency market during times of uncertainty. The empirical results show that liquidity spillovers are lower than both return and volatility spillovers, and liquidity spillovers increase noticeably during times of market shocks. Ethereum is the dominant transmitter of liquidity spillovers, followed by Bitcoin. We also find that heightened crude oil volatility, stock volatility, and economic policy uncertainty contribute to more significant liquidity spillovers within cryptocurrency markets. Moreover, increased volatility in exchange rates, crude oil, gold, and stock markets and economic policy uncertainty would enhance Ethereum’s role as a transmitter of liquidity shocks in the cryptocurrency market. These findings are relevant for investors and regulators to manage risks and uncertainties in the cryptocurrency market.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102347"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094376","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 : 2025-01-01DOI: 10.1016/j.najef.2024.102345
Shaobo Long , Ning Xue , Yuan Zhang
This study investigates the impact of economic policy uncertainty (EPU) on macro price divergence in China. We use the time-varying parameter vector auto regressive model with latent thresholds (LT-TVP-VAR) to examine the nonlinear causality relationship. Our findings suggest when the EPU rises, the demand of investment would decline more significantly than consumption, which exacerbates the divergence between CPI and PPI. While the heterogeneous elasticity of demand and supply for different consumer goods further contributes to the CPI internal divergence between food and non-food prices. Furthermore, macro price divergence responds negatively to international commodity prices and money supply rising. The responds in short term are more significant compared with the medium and long interval. It suggests that policymakers should stabilize policy expectations and reduce the adverse effects of EPU shocks by increasing policy transparency, thereby mitigating macro price volatility.
{"title":"The divergence of China’s prices under economic policy uncertainty shock: A time-varying perspective","authors":"Shaobo Long , Ning Xue , Yuan Zhang","doi":"10.1016/j.najef.2024.102345","DOIUrl":"10.1016/j.najef.2024.102345","url":null,"abstract":"<div><div>This study investigates the impact of economic policy uncertainty (EPU) on macro price divergence in China. We use the time-varying parameter vector auto regressive model with latent thresholds (LT-TVP-VAR) to examine the nonlinear causality relationship. Our findings suggest when the EPU rises, the demand of investment would decline more significantly than consumption, which exacerbates the divergence between CPI and PPI. While the heterogeneous elasticity of demand and supply for different consumer goods further contributes to the CPI internal divergence between food and non-food prices. Furthermore, macro price divergence responds negatively to international commodity prices and money supply rising. The responds in short term are more significant compared with the medium and long interval. It suggests that policymakers should stabilize policy expectations and reduce the adverse effects of EPU shocks by increasing policy transparency, thereby mitigating macro price volatility.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102345"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094378","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 : 2025-01-01DOI: 10.1016/j.najef.2024.102354
Hao Wu , Yuan Huang
The carbon, energy, and metal markets are intricately interconnected, and clarifying their relationships is crucial for promoting sustainable development. This paper explores the risk transmission mechanism of carbon, energy and metal markets, as well as portfolio diversification. The quantile frequency framework and portfolio strategy are employed. Our empirical results indicate that the spillover effect is particularly pronounced in bearish and bullish markets. The connectedness of the carbon-energy-metal system is time-varying and cyclical, with short-term effects dominating. Moreover, the metal markets, especially copper, possesses greater explanatory power, and the carbon market is becoming increasingly connected with other markets in the post-COVID-19 period. In addition, the state of market dependence suggests that energy and metals can provide a better hedge against carbon in the medium and long term. Investors are recommended to hold more metals in their portfolios rather than carbon and energy, and to adjust portfolio allocations and hedge positions in response to market situations. Overall, these findings are of great significance for investors building diversified investment and for policymakers monitoring risk contagion.
{"title":"Identifying risk transmission in carbon, energy and metal markets: Evidence from a novel quantile frequency connectedness approach","authors":"Hao Wu , Yuan Huang","doi":"10.1016/j.najef.2024.102354","DOIUrl":"10.1016/j.najef.2024.102354","url":null,"abstract":"<div><div>The carbon, energy, and metal markets are intricately interconnected, and clarifying their relationships is crucial for promoting sustainable development. This paper explores the risk transmission mechanism of carbon, energy and metal markets, as well as portfolio diversification. The quantile frequency framework and portfolio strategy are employed. Our empirical results indicate that the spillover effect is particularly pronounced in bearish and bullish markets. The connectedness of the carbon-energy-metal system is time-varying and cyclical, with short-term effects dominating. Moreover, the metal markets, especially copper, possesses greater explanatory power, and the carbon market is becoming increasingly connected with other markets in the post-COVID-19 period. In addition, the state of market dependence suggests that energy and metals can provide a better hedge against carbon in the medium and long term. Investors are recommended to hold more metals in their portfolios rather than carbon and energy, and to adjust portfolio allocations and hedge positions in response to market situations. Overall, these findings are of great significance for investors building diversified investment and for policymakers monitoring risk contagion.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"76 ","pages":"Article 102354"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143094379","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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