{"title":"The economic value of Bitcoin: A volatility timing perspective with portfolio rebalancing","authors":"Jui-Cheng Hung , Hung-Chun Liu , J. Jimmy Yang","doi":"10.1016/j.najef.2024.102260","DOIUrl":"10.1016/j.najef.2024.102260","url":null,"abstract":"<div><p>We investigate the economic value of adding Bitcoin, instead of Gold, to a traditional portfolio from the perspective of a volatility timing framework. Using futures data, we find that Bitcoin adds more value than Gold does to the portfolio during periods of dovish monetary policy. However, during periods of rapid rate hikes, Bitcoin destroys value while Gold offers safe haven and diversification benefits. Rebalancing strategies matter when considering adding alternative assets to a stock–bond portfolio in the presence of transaction costs. This study is timely given the macroeconomic environment of rate hikes and the downturn of cryptocurrencies.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102260"},"PeriodicalIF":3.8,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998268","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}
Daniel O. Beltran , Vihar M. Dalal , Mohammad R. Jahan-Parvar , Fiona A. Paine
{"title":"Optimizing composite early warning indicators","authors":"Daniel O. Beltran , Vihar M. Dalal , Mohammad R. Jahan-Parvar , Fiona A. Paine","doi":"10.1016/j.najef.2024.102250","DOIUrl":"10.1016/j.najef.2024.102250","url":null,"abstract":"<div><p>Research on predicting financial crises has produced various composite early warning indicators (EWIs) using macroeconomic and financial time-series. Much of the focus has been on identifying the best leading indicators for financial crises (e.g., credit-to-GDP ratios, financial asset prices, etc.). This paper instead focuses on how to optimally extract and combine signals from multiple cyclical indicators. We find that when combining multiple indicators into a composite EWI, jointly optimizing the indicators improves performance relative to optimizing individually and combining their signals. The performance of our jointly optimized EWIs is robust to the key modelling choices inherent in their design including the trend-cycle decomposition method and the preference for false positives over false negatives.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102250"},"PeriodicalIF":3.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947997","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}
{"title":"Network measurement and influence mechanism of dynamic risk contagion among global stock markets: Based on time-varying spillover index and complex network method","authors":"Bo Yu , Haiqin Ouyang , Chao Guan , Binzhao Lin","doi":"10.1016/j.najef.2024.102258","DOIUrl":"10.1016/j.najef.2024.102258","url":null,"abstract":"<div><p>From a global and dynamic perspective, this paper conducts the network measurement of risk contagion among global stock markets by employing time-varying spillover index and complex network method. Furthermore, this paper investigates the influence mechanism of dynamic risk contagion, combining multiple factors such as financial opening, international trade, and cross-border capital flow. The results show that: (1) There exists a strong risk contagion effect among global stock markets, especially for developed countries, which have obvious time-varying characteristics in both direction and intensity. (2) The risk contagion effect is also highly event-dependent, which shows a rapid upward trend during extreme risk events such as the financial crisis and the COVID-19 epidemic. (3) Different economic and financial development situations lead to different risk contagion effects, and the ranking of countries with stronger risk effects remains at a stable level, which can prompt important risk events. (4) International trade, cross-border capital flow, financial market volatility, investor sentiment, and the US monetary policy are key influence mechanisms of dynamic risk contagion. However, financial opening and economic fundamentals are not statistically significant, which is contrary to our intuition.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102258"},"PeriodicalIF":3.8,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141963619","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}
{"title":"Does climate change matter for bank profitability? Evidence from China","authors":"Chien-Chiang Lee , Xiaoli Zhang , Chi-Chuan Lee","doi":"10.1016/j.najef.2024.102257","DOIUrl":"10.1016/j.najef.2024.102257","url":null,"abstract":"<div><p>Using panel data from 87 China’s banks from 2011 to 2022, this research investigates whether and how climate change affects bank profitability. It is discovered that the improvement of bank profitability is severely hampered by climate change. The main ways that climate change affects bank profitability are by causing financial losses to bank creditors, changing the likelihood of defaults and the quality of bank credit assets. Energy conservation and carbon reduction, the implementation of green financial policies, and ensuring that banks have enough capital are all factors that can help mitigate the negative effects of climate change on bank profitability. In addition, climate change has a greater negative effect on the profitability of small-sized banks, regional banks, and banks with lower levels of liquidity. In conclusion, this study offers forward-looking suggestions for banks to reduce risks from climate change, which is critical for encouraging low-carbon and green development and averting systemic financial risks. It also offers theoretical references for Chinese banks to develop customized policies and strategies to address these risks.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102257"},"PeriodicalIF":3.8,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141963003","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}
{"title":"Dynamic credit risk transmissions among global major industries: Evidence from the TVP-VAR spillover approach","authors":"Seo-Yeon Lim , Sun-Yong Choi","doi":"10.1016/j.najef.2024.102251","DOIUrl":"10.1016/j.najef.2024.102251","url":null,"abstract":"<div><p>We examine the dynamics of credit risk connectedness by analyzing credit default spreads in four major sectors (banks, transportation, manufacturing, electricity) across three global regions (Asia, Europe, North America) using the TVP-VAR spillover methodology from 2007 to 2024. We have identified significant findings regarding credit risk spillovers among them. First, there are consistently high levels of credit risk spillovers between sectors, indicating underlying economic factors influencing the transmission of credit risk shocks. Second, notable regional findings include a substantial increase in credit risk connectedness for Asian banks during the global financial crisis (GFC). European manufacturing sectors also displayed significantly high connectedness levels during both the GFC and the COVID-19, while North American banks saw a notable surge due to the collapse of Silicon Valley Banks (SVB) in March 2023. In addition, during the RU-war, the electricity and manufacturing sectors in Europe had high CDS connectedness. Lastly, a distinct observation emerged concerning the Asian transportation sector. These findings have practical implications for policymakers and portfolio managers. For instance, they can help policymakers assess the effectiveness of their policies by revealing global industry credit risk interconnections. Additionally, the dynamic credit risk linkages provide strategies for hedging credit risk.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102251"},"PeriodicalIF":3.8,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141947996","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}
{"title":"The threshold effect of political connection on the green innovation of businesses: Evidence from China","authors":"Doudou Chen , Tao Bu","doi":"10.1016/j.najef.2024.102255","DOIUrl":"10.1016/j.najef.2024.102255","url":null,"abstract":"<div><p>It is increasingly accepted that green innovation plays a crucial role in the new development pattern. Despite the government’s efforts to promote green innovation in China, the efficiency of such initiatives is still inadequate. Therefore, it is essential to investigate how political connection affect the green innovation process of businesses, so as to better guide the government’s role, stimulate green innovation in businesses, and ultimately support sustainable economic and social progress. Drawing on the data of A-share listed companies in China from 2010 to 2020, this article empirically examines the influence and mechanism of political connection on green innovation of enterprises. The findings indicate that political connection can reduce the financing constraints for businesses, however, it can also stimulate the motivation for rent-seeking, which means that resources are used to meet government expectations or satisfy management’s private desires, thus crowding out innovation resources and eventually having a negative effect on innovation. Evidence suggests that the influence of political connection on green innovation in companies has a limit based on resource investment and allocation decisions. When resource investment reaches a certain point, green innovation can be significantly enhanced; however, if the resources allocated for social responsibility reach a particular threshold, political connection can adversely affect green innovation. This article proposes that strengthening both internal and external governance can mitigate the agency problems of executives and reduce the negative impact of political connections on green innovation within businesses. By delving deeper into the relationship between political connections and green innovation, this article offers new insights and policy recommendations aimed at fostering green innovation in enterprises.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102255"},"PeriodicalIF":3.8,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141985413","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}
Qu Yang , Yuanyuan Yu , Dongsheng Dai , Qian He , Yu Lin
{"title":"Can hybrid model improve the forecasting performance of stock price index amid COVID-19? Contextual evidence from the MEEMD-LSTM-MLP approach","authors":"Qu Yang , Yuanyuan Yu , Dongsheng Dai , Qian He , Yu Lin","doi":"10.1016/j.najef.2024.102252","DOIUrl":"10.1016/j.najef.2024.102252","url":null,"abstract":"<div><p>The sudden eruption of COVID-19 has inflicted tremendous damage to the worldwide economy, and stock markets have become violently volatile due to its negative impact. Therefore, accurate forecasting of stock price index has been playing an essential role in maintaining national economic security and formulating related policies. In this paper, a novel decomposition-ensemble model is proposed to predict the highly fluctuating stock price index. To begin with, the modified ensemble empirical mode decomposition (MEEMD) method is adopted to decompose the original stock price index into subsequences with different frequencies. Then, the last high-frequency subsequence and other subsequences are predicted through multilayer perceptron (MLP) and long short-term memory (LSTM), respectively. Finally, the prediction outcomes of different model subsequences are reconstructed into the ultimate prediction results by utilizing the integration method. Compared with the contrast models, the MEEMD-LSTM-MLP model proposed in our paper not only demonstrates significant advantages in multi-step forecasting for both emerging and developed markets, but also achieves excellent prediction performance amidst the severe market fluctuations triggered by COVID-19. Furthermore, the application of the MEEMD-LSTM-MLP model is extended to financial time series with different data characteristics and market types, which further proves its high applicability and reliability. Therefore, the conducted hybrid MEEMD-LSTM-MLP model is an effective and stable multi-step forecasting tool to provide valuable intelligent technical support for governments and enterprises in complex economic conditions.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102252"},"PeriodicalIF":3.8,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950452","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}
{"title":"The impact of MD&A digital transformation information disclosure on stock price synchronicity in China","authors":"Jinwen Guo , Jiangjiao Duan","doi":"10.1016/j.najef.2024.102253","DOIUrl":"10.1016/j.najef.2024.102253","url":null,"abstract":"<div><p>With the continuous development of the global digital economy, digital transformation has become an important path for enterprises. The management discussion and analysis (MD&A) section of listed companies’ annual reports has progressively incorporated detailed information on their ongoing digital transformation efforts, reflecting the growing significance of this trend in corporate reporting. This paper uses data from 2011 to 2022 of A-share listed companies in China to investigate whether and how the MD&A digital transformation information affects the stock price synchronicity. The frequency of keywords related to digital transformation within the MD&A section of the annual report is analyzed and measured to quantify digital transformation information. The results show that digital transformation information in MD&A can significantly reduce stock price synchronicity. Further mechanism tests show that analyst and media act as information intermediaries to disseminate more firm-specific information to the market. In addition, heterogeneity tests show that this effect is mainly reflected in state-owned companies and larger companies. These findings provide valuable insights for policymakers, investors, and regulators in planning regulations.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102253"},"PeriodicalIF":3.8,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141961658","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}
{"title":"Diversification value of green Bonds: Fresh evidence from China","authors":"You Zhou , Lichao Lin , Ziling Huang","doi":"10.1016/j.najef.2024.102254","DOIUrl":"10.1016/j.najef.2024.102254","url":null,"abstract":"<div><p>This study conducts a comprehensive analysis of the static correlation between the Chinese green bond market and key capital markets-including the stock, money, foreign exchange, and gold markets—using daily data spanning from 2013 to 2022. Utilizing maximum likelihood estimation methods, our findings indicate that the Student’s t Copula model is the most suitable for capturing these relationships, revealing a relatively low static correlation among these markets. Furthermore, for dynamic dependence analysis and cross-validation, the Student’s t-GAS Copula model is applied, which corroborates the initial findings. Consequently, this suggests that the Chinese green bond market could become one of the potentially diversification options for investing in the Chinese financial landscape.</p><p>Abbreviations: ICMA, International Capital Market Association; GB, green bonds; CB, China Bond Government Bond Total Return Index; HS300, CSI 300 Index; DR7, 7-day interbank pledged repo rate; CNY, Onshore RMB to USD exchange rate; AU95, AU9995 gold price.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102254"},"PeriodicalIF":3.8,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141961659","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}
{"title":"Risk spillovers among oil, gold, stock, and foreign exchange markets: Evidence from G20 economies","authors":"Zixin Liu , Jun Hu , Shuguang Zhang , Zhipeng He","doi":"10.1016/j.najef.2024.102249","DOIUrl":"10.1016/j.najef.2024.102249","url":null,"abstract":"<div><p>This paper investigates the tail risk spillover effects among the stock and foreign exchange markets of G20 economies, as well as the oil and gold markets by constructing a tail event driven network. Adjacency matrices indicate time-varying connectedness between network nodes. The systemic risk decomposition results highlight the predominant contribution of stock markets to the aggregate risk level, while oil, gold, and specific currencies such as JPY, USD, and CNY contribute to diversifying systemic risk. Moreover, tail event driven network quantile regression analysis demonstrates the asymmetry and market heterogeneity of risk spillover effects. Our findings have instructive implications for financial regulators and institutional investors.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102249"},"PeriodicalIF":3.8,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141864982","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}