{"title":"Do US sectoral contagion and news-based economic policy uncertainty cause fear or greed behavior in Bitcoin investors?","authors":"Umaid A. Sheikh , Muhammad Tahir Suleman","doi":"10.1016/j.najef.2025.102429","DOIUrl":"10.1016/j.najef.2025.102429","url":null,"abstract":"<div><div>We explore whether spillover of shocks between U.S. sectoral stocks, Dynamic Conditional Correlations (DCCs) and U.S. Economic Policy Uncertainty (U.S. EPU) increase Bitcoin investors’ fear and greed Sentiment Indices (BSI) by using the daily time series data from 1st February 2018 towards 1st February 2025. Initially, we explore the overall and frequency domain short- and long-term spillover of shocks between 11 major U.S. sectoral stock returns by using the time and frequency domain Generalized Vector Auto-regression approach. For further robustness, we also extract the DCCs using the DCC-GARCH-t copula approach between 55 pairs of U.S. sectoral stock returns and regress BSI on these DCCs and U.S.EPU with a series of quantile regression models. For portfolio optimization, this study also examines the hedging effectiveness (HE) of different US sectors under high vs low U.S. EPU regimes based on the hedge ratios. Findings present the consistent adverse effect of overall and frequency domain short- and long-term U.S. sectoral stock returns’ total connectedness indices on the BSI. However, the long-term spillover of shocks between U.S. sectors increases Bitcoin investors’ fear (higher selling behavior) with more magnitude than the short-term investment horizon. Furthermore, a series of quantile regressions further reinforce this adverse effect, and DCCs between all 55 pairs of U.S. sectors increase the extreme fear of Bitcoin investors. This study provides concrete recommendations for investors to exercise caution in Bitcoin trading when the shock spillover mechanism between U.S. sectors is stronger.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102429"},"PeriodicalIF":3.8,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863979","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":"A hybrid model for intraday volatility prediction in Bitcoin markets","authors":"Prakash Raj, Koushik Bera, N. Selvaraju","doi":"10.1016/j.najef.2025.102426","DOIUrl":"10.1016/j.najef.2025.102426","url":null,"abstract":"<div><div>Volatility modeling in cryptocurrencies poses unprecedented challenges due to extreme price fluctuation, 24/7 trading cycles, and decentralized and speculative environments. This article presents a novel hybrid BEMD-REGARCH model by integrating the bivariate empirical mode decomposition (BEMD) with the realized exponential generalized autoregressive conditional heteroscedasticity (REGARCH) model to estimate the volatility of cryptocurrencies. The highlights include the use of intraday hourly returns and realized variance, and the model forecasts intraday 1-<span><math><mrow><mi>h</mi><mi>o</mi><mi>u</mi><mi>r</mi></mrow></math></span>-ahead volatility. Testing the hybrid model on various datasets ensures robustness, and the model yields superior volatility forecasting gains over the traditional REGARCH model on various performance metrics. In addition, BEMD trumps EMD by scoring lower forecasting errors than the EMD-GARCH model. In summary, applying BEMD to the REGARCH model enhances its forecasting performance.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102426"},"PeriodicalIF":3.8,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800647","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 valuation of variance swaps with psychological barriers in the underlying dynamics","authors":"Shiyu Song , Yiming Jiang","doi":"10.1016/j.najef.2025.102422","DOIUrl":"10.1016/j.najef.2025.102422","url":null,"abstract":"<div><div>This paper focuses on the valuation problem of variance swaps when there exist psychological barriers in the underlying price dynamics. Specifically, the volatility of the proposed model will shift from one regime to another once the psychological barrier is crossed by the underlying asset price. To obtain the variance swap rate, two approaches are provided: The first is to consider the Laplace transform of the process related to the swap rate and then invert it numerically, while the second is to find the explicit pricing formula for variance swaps in terms of integrals by using the trivariate density associated with the skew Brownian motion through a measure change. Numerical results in the end reveal the nonnegligible impact of psychological barriers on swap rates.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102422"},"PeriodicalIF":3.8,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777619","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":"Effect of digital finance on household financial asset allocation: a social psychology perspective","authors":"Jing Yang , Jianxun Shi , Ling Xu","doi":"10.1016/j.najef.2025.102427","DOIUrl":"10.1016/j.najef.2025.102427","url":null,"abstract":"<div><div>Over the past decade, digital finance has rapidly advanced, attracting significant attention due to its profound economic implications. Additionally, its development deeply affects social psychology and household behavior. This study examines the influence of digital finance on household financial asset allocation from a social psychological perspective, exploring how technological progress and economic transitions alter human behavior. Utilizing the China Household Finance Survey (CHFS) data from 2015, 2017, and 2019, combined with county-level digital finance data, empirical results show digital finance significantly promotes household participation in financial markets. This increased participation fosters a higher allocation toward risky financial assets, particularly equities, thereby enhancing portfolio diversification. From a psychological standpoint, such effects emerge as digital finance elevates individuals’ interest in and awareness of economic and financial matters, reshapes risk perceptions, and strengthens social interactions. Heterogeneity analysis further reveals that while the positive effects are somewhat weaker in rural and agriculturally registered households, they are significantly more pronounced in households characterized by higher education levels, greater average age, substantial assets, and entrepreneurial activities. Consequently, this research provides policymakers valuable insights into employing digital finance strategically to optimize household asset allocation and mitigate financial risks by shaping psychological and behavioral tendencies.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102427"},"PeriodicalIF":3.8,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816090","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}
Kai Jiang , Baogui Xin , Ernesto D.R. Santibanez Gonzalez
{"title":"Can industrial intelligence promote net-zero development? An analysis of resource dependence","authors":"Kai Jiang , Baogui Xin , Ernesto D.R. Santibanez Gonzalez","doi":"10.1016/j.najef.2025.102425","DOIUrl":"10.1016/j.najef.2025.102425","url":null,"abstract":"<div><div>The increasing prevalence of artificial intelligence (AI) has triggered intense debates on the impact of industrial intelligence on economic changes including the Solow paradox. How does industrial intelligence affect resource dependence and net-zero development? To shed some light on this question, we combine the grounded theory and dynamic stochastic general equilibrium (DSGE) model to explore what is the possible impact of industrial intelligence on resource dependence and net-zero development. Our results indicate that: (i) Intelligent technological progress enables net-zero development by boosting total factor productivity (TFP), promoting the labor market dynamic evolution, and accelerating intelligence. (ii) However, there is a significant rebound effect associated with intelligent technological progress. It will aggravate resource dependence if the industry pays too much attention to the intelligent transformation of the end link, such as intelligent resource exploitation. (iii) The government can implement resource tax policies to alleviate the resource-environment issues caused by industrial intelligence, which is conducive to stabilizing the macro economy, reducing resource dependence and promoting net-zero development. The findings enrich the technological progress theory and provide guidance for building an intelligent-friendly, resource-saving and net-zero society.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102425"},"PeriodicalIF":3.8,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800648","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":"Analytically pricing crude oil options under a jump-diffusion model with stochastic liquidity risk and convenience yield","authors":"Sha Lin , Meiling Chen , Xin-Jiang He","doi":"10.1016/j.najef.2025.102424","DOIUrl":"10.1016/j.najef.2025.102424","url":null,"abstract":"<div><div>This study investigates the pricing issue of European crude oil options in a market with imperfect liquidity. We adopt a jump-diffusion model incorporating stochastic convenience yield to simulate crude oil price evolution, adjusted for the impacts of stochastic liquidity risk. A risk-neutral measure is established based on the Feynman-Kac theorem, followed by the presentation of a closed-form formula for determining the fair delivery price of the crude oil futures contract. This further give rise to an analytical price of the crude oil options. Novel formula’s correctness is verified by numerical tests that compare the analytical answer with Monte Carlo simulation. In conclusion, an empirical analysis is carried out to validate the proposed model using the crude oil options data available on the Shanghai International Energy Exchange (INE). The findings are contrasted to a benchmark model with constant liquidity, demonstrating the relevance of introducing stochastic liquidity into crude oil option pricing.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102424"},"PeriodicalIF":3.8,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767862","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":"Long-term forecasting in asset pricing: Machine learning models’ sensitivity to macroeconomic shifts and firm-specific factors","authors":"Yihe Qian , Yang Zhang","doi":"10.1016/j.najef.2025.102423","DOIUrl":"10.1016/j.najef.2025.102423","url":null,"abstract":"<div><div>This study investigates the long-term forecasting capabilities of five prominent machine learning models—decision tree, random forest, gradient boosted regression trees, support vector machines, and neural networks—within the domain of asset pricing. Applying these models to S&P 500 constituent stocks from 2000 to 2023, we examine their predictive performance over extended horizons. Our findings indicate that Gradient Boosting and Random Forest models stand out for their superior performance, though their predictive accuracy exhibits sensitivity to the prevailing economic stability. Furthermore, these models show enhanced effectiveness in forecasting returns for larger companies, with their performance demonstrating significant variation across different industry sectors. A notable decline in accuracy with the increase in forecasting horizons underscores the challenges inherent in long-term financial prediction. Our results highlight the substantial impact of macroeconomic factors, particularly Consumer Sentiment and Net Exports, whose influences fluctuate over time. Practically, machine learning models, especially Gradient Boosting and Random Forest, are shown to consistently surpass the benchmark S&P 500 index in portfolio construction scenarios. We show the importance of economic stability, firm size, and industry sector context, providing novel insights for the strategic application of machine learning in asset pricing and the formulation of investment strategies suited to diverse market conditions.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102423"},"PeriodicalIF":3.8,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682605","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}
Robert Adrian Grecu , Alexandru Adrian Cramer , Daniel Traian Pele , Stefan Lessmann
{"title":"The link between energy prices and stock markets in European Union countries","authors":"Robert Adrian Grecu , Alexandru Adrian Cramer , Daniel Traian Pele , Stefan Lessmann","doi":"10.1016/j.najef.2025.102420","DOIUrl":"10.1016/j.najef.2025.102420","url":null,"abstract":"<div><div>The paper examines the relationship between the energy sector and the stock market, specifically analyzing how fluctuations in energy prices, such as oil and gas, influence the returns of major European stock indices. The analysis is conducted at the level of European Union (EU) countries, considering both individual country-specific dynamics and group-level effects based on various criteria, such as geographical region and industrial development.</div><div>Although EU countries share several common economic characteristics, the findings indicate that the impact of energy prices on stock markets varies significantly across states. Additionally, the results highlight that energy price dynamics affect countries with the highest levels of industrial production differently compared to the rest of the EU.</div><div>From a quantitative perspective, the study explores both the co-movement between variables and the effects of various economic shocks. Furthermore, it examines the dynamic linkages between energy and stock markets by employing models such as the Dynamic Conditional Correlation (DCC) model, the Time-Varying Parameter Vector Autoregressive (TVP-VAR) model, and the Markov-Switching model to capture regime-dependent changes in the relationship between energy prices and stock market returns.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102420"},"PeriodicalIF":3.8,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682608","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}
Aziz Ullah , Kang-Lin Peng , Chih-Chiang Lu , Ying Jin
{"title":"Impacts of geographical conflicts on risk tango between oil and equity markets: An empirical evidence from oil-importing and exporting nations","authors":"Aziz Ullah , Kang-Lin Peng , Chih-Chiang Lu , Ying Jin","doi":"10.1016/j.najef.2025.102419","DOIUrl":"10.1016/j.najef.2025.102419","url":null,"abstract":"<div><div>This study investigates the impact of the Russia-Ukraine conflict and the Israel-Palestine dispute on the risk tango between West Texas Intermediate (WTI) and Brent oil returns on oil-importing and exporting equity markets. The Findings are as follows:</div><div>Firstly, the current conditional volatility in these markets relies heavily on volatility caused by geographical conflicts. Secondly, the time-varying co-movement shows that WTI has countercyclical behaviour with India and the US in the long run. At the same time, Brent exhibits contrasting cyclical with Japan and countercyclical relationships with the USA and India. Thirdly, our NET plots visualize the fluctuation amid Russia-Ukraine and Israeli-Palestine tension and similar co-movement trends witnessed in wavelet analysis. Lastly, it reveals that geopolitical tension has widespread implications for regional economies. Furthermore, the portfolio weights recommend that investors diversify and apportion more than 50% to oil assets. However, Brent offers superior cheap hedging, particularly for oil exporting, while WTI is more cost-effective for oil-importing economies.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102419"},"PeriodicalIF":3.8,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682606","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}
Yuanling Li , Zhongyi Xiao , Fei Shen , Hanbing Zou , Weiping Li
{"title":"Financing the firm or fueling risk? how share-pledged loans for corporate use shape corporate performance","authors":"Yuanling Li , Zhongyi Xiao , Fei Shen , Hanbing Zou , Weiping Li","doi":"10.1016/j.najef.2025.102421","DOIUrl":"10.1016/j.najef.2025.102421","url":null,"abstract":"<div><div>This paper investigates the effects of controlling shareholders’ share pledges on the performance of Chinese publicly listed companies between 2009 and 2022. Utilizing a triple difference-in-difference approach, we explore how the act of controlling shareholders pledging their shares and reinvesting the proceeds into the firm impacts both short-term accounting outcomes and long-term firm value. Our findings show that while such pledges tend to enhance short-term accounting performance, as measured by return on equity (<em>ROE</em>), they correlate with a reduction in the firm’s long-term value, as reflected by <em>TobinQ</em>. This trend persists even when alternative proxies for <em>ROE</em> and <em>TobinQ</em> are used, and remains robust across different sample sets and when employing propensity score matching. Furthermore, we observe that these effects are more pronounced in firms where controlling shareholders exhibit a significant gap between cash flow rights and voting rights, or where tunneling activities are prevalent, or corporates with lower analysts following. Our study contributes to the literature on share pledging and reinforces the agency theory framework regarding the actions of controlling shareholders.</div></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"78 ","pages":"Article 102421"},"PeriodicalIF":3.8,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143641758","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}