Pub Date : 2026-02-01Epub Date: 2025-11-26DOI: 10.1016/j.ribaf.2025.103233
Tomasz Kaczmarek , Ender Demir , Wael Rouatbi , Adam Zaremba
We examine sovereign bond market reactions to the U.S. ”reciprocal” tariff announcement on April 2, 2025, using daily returns from 61 countries. Government bond prices rose following the announcement, consistent with a flight-to-safety response amid heightened global uncertainty. Cross-country variation reflects three main drivers: tariff exposure, fiscal fundamentals, and export orientation. Bonds from countries facing higher tariffs experience stronger gains, but this effect weakens for sovereigns with poor credit quality or high unemployment. Moreover, bonds issued by net exporters underperform, suggesting that investor concerns center on structural vulnerabilities rather than general trade openness. Overall, the results highlight the selective nature of the flight-to-safety dynamic during episodes of rising protectionism.
{"title":"Protectionism and safe-haven demand: Sovereign bond reactions to the 2025 U.S. tariff announcement","authors":"Tomasz Kaczmarek , Ender Demir , Wael Rouatbi , Adam Zaremba","doi":"10.1016/j.ribaf.2025.103233","DOIUrl":"10.1016/j.ribaf.2025.103233","url":null,"abstract":"<div><div>We examine sovereign bond market reactions to the U.S. ”reciprocal” tariff announcement on April 2, 2025, using daily returns from 61 countries. Government bond prices rose following the announcement, consistent with a flight-to-safety response amid heightened global uncertainty. Cross-country variation reflects three main drivers: tariff exposure, fiscal fundamentals, and export orientation. Bonds from countries facing higher tariffs experience stronger gains, but this effect weakens for sovereigns with poor credit quality or high unemployment. Moreover, bonds issued by net exporters underperform, suggesting that investor concerns center on structural vulnerabilities rather than general trade openness. Overall, the results highlight the selective nature of the flight-to-safety dynamic during episodes of rising protectionism.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103233"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-15DOI: 10.1016/j.ribaf.2025.103253
Ziqi Li , Zhihao Cai , Ho-Chuan Huang
This study examines the impact of CFO-CEO co-option on controlling shareholders’ equity pledging in Chinese A-share listed firms from 2003 to 2022. Findings indicate a significant positive relationship, as co-opted CFOs – those appointed after the CEO’s tenure begins – tend to align with CEO interests, facilitating higher pledge levels to meet short-term liquidity needs. Gender and tenure moderate this effect: female CFOs, despite being risk-averse, exhibit stronger influences due to compliance pressures, while newly appointed CFOs are more susceptible to CEO influence. External governance mechanisms, such as Big Four audits and concentrated market environments, mitigate this impact, whereas high information asymmetry exacerbates it. Additionally, financing constraints serve as a mediating mechanism, as co-opted CFOs heighten financial pressures, leading to increased equity pledging. These findings highlight governance risks associated with CFO co-option and provide policy insights for mitigating financial instability in emerging markets.
{"title":"The governance nexus: The impact of CFO-CEO collusion on controlling shareholders’ equity pledging","authors":"Ziqi Li , Zhihao Cai , Ho-Chuan Huang","doi":"10.1016/j.ribaf.2025.103253","DOIUrl":"10.1016/j.ribaf.2025.103253","url":null,"abstract":"<div><div>This study examines the impact of CFO-CEO co-option on controlling shareholders’ equity pledging in Chinese A-share listed firms from 2003 to 2022. Findings indicate a significant positive relationship, as co-opted CFOs – those appointed after the CEO’s tenure begins – tend to align with CEO interests, facilitating higher pledge levels to meet short-term liquidity needs. Gender and tenure moderate this effect: female CFOs, despite being risk-averse, exhibit stronger influences due to compliance pressures, while newly appointed CFOs are more susceptible to CEO influence. External governance mechanisms, such as Big Four audits and concentrated market environments, mitigate this impact, whereas high information asymmetry exacerbates it. Additionally, financing constraints serve as a mediating mechanism, as co-opted CFOs heighten financial pressures, leading to increased equity pledging. These findings highlight governance risks associated with CFO co-option and provide policy insights for mitigating financial instability in emerging markets.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103253"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-11-24DOI: 10.1016/j.ribaf.2025.103227
Lihong Cao , Xuanning Zhu , Yi Li
This paper examines how firm digitalization influences bank loans and debt maturity using data from Chinese-listed firms from 2009 to 2021. By employing machine learning and large language models to measure digitalization, we find that digitalization significantly increases both the scale of bank loans and the proportion of long-term loans. The effect of digitalization is stronger for credit and guaranteed loans than for collateral loans, indicating that digitalization reduces the collateral requirements in lending. Mechanism analysis reveals that digitalization enhances firms’ access to bank lending by improving information transparency, financial stability and corporate reputation. The positive effect is stronger for firms without credit ratings, highlighting digitalization’s role in reducing information asymmetry. Additionally, the effects are more pronounced in regions with advanced banking systems and marketization, for firms in traditional industries and firms under competitive pressure. Our findings highlight digitalization’s critical role in improving firms’ credit market competitiveness and advocate for government policies to facilitate firm digitalization. It offers actionable insights for firms in bank-dominated economies globally to alleviate financial constraints through technological development.
{"title":"Firm digitalization and bank lending: Evidence from China","authors":"Lihong Cao , Xuanning Zhu , Yi Li","doi":"10.1016/j.ribaf.2025.103227","DOIUrl":"10.1016/j.ribaf.2025.103227","url":null,"abstract":"<div><div>This paper examines how firm digitalization influences bank loans and debt maturity using data from Chinese-listed firms from 2009 to 2021. By employing machine learning and large language models to measure digitalization, we find that digitalization significantly increases both the scale of bank loans and the proportion of long-term loans. The effect of digitalization is stronger for credit and guaranteed loans than for collateral loans, indicating that digitalization reduces the collateral requirements in lending. Mechanism analysis reveals that digitalization enhances firms’ access to bank lending by improving information transparency, financial stability and corporate reputation. The positive effect is stronger for firms without credit ratings, highlighting digitalization’s role in reducing information asymmetry. Additionally, the effects are more pronounced in regions with advanced banking systems and marketization, for firms in traditional industries and firms under competitive pressure. Our findings highlight digitalization’s critical role in improving firms’ credit market competitiveness and advocate for government policies to facilitate firm digitalization. It offers actionable insights for firms in bank-dominated economies globally to alleviate financial constraints through technological development.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103227"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-11-26DOI: 10.1016/j.ribaf.2025.103232
Dexiang Mei , Xiaotao Li
Against the backdrop of economic globalization, the outbreak of numerous transnational emergencies (such as geopolitical wars, trade frictions, and political conflicts) has affected the Chinese financial market and introduced significant uncertainties (e.g., monetary policy, political risk, and geopolitical risk). In addition, the stock market is a complex, nonlinear, and dynamic system. Therefore, the least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA) techniques are used to construct a comprehensive uncertainty index for the Chinese stock market. Neural networks (a gated recurrent unit (GRU), long short-term memory (LSTM), and bidirectional long short-term memory (BiLSTM)) are embedded into a generalized autoaggressive conditional heteroskedasticity-mixed-data sampling (GARCH-MIDAS) model to construct an integrated model. The empirical results show that the newly constructed uncertainty factor provided effective information for predicting Chinese stock market volatility, and that the model's predictive ability integrated model's predictive ability is significantly better than that of the traditional model both statistical and economical. A robustness test confirms these conclusions. Therefore, understanding the volatility rules and structural characteristics of the financial market plays a vital role in accurately predicting volatility and preventing financial risk.
{"title":"Forecasting of Chinese stock price using a hybrid neural network model","authors":"Dexiang Mei , Xiaotao Li","doi":"10.1016/j.ribaf.2025.103232","DOIUrl":"10.1016/j.ribaf.2025.103232","url":null,"abstract":"<div><div>Against the backdrop of economic globalization, the outbreak of numerous transnational emergencies (such as geopolitical wars, trade frictions, and political conflicts) has affected the Chinese financial market and introduced significant uncertainties (e.g., monetary policy, political risk, and geopolitical risk). In addition, the stock market is a complex, nonlinear, and dynamic system. Therefore, the least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA) techniques are used to construct a comprehensive uncertainty index for the Chinese stock market. Neural networks (a gated recurrent unit (GRU), long short-term memory (LSTM), and bidirectional long short-term memory (BiLSTM)) are embedded into a generalized autoaggressive conditional heteroskedasticity-mixed-data sampling (GARCH-MIDAS) model to construct an integrated model. The empirical results show that the newly constructed uncertainty factor provided effective information for predicting Chinese stock market volatility, and that the model's predictive ability integrated model's predictive ability is significantly better than that of the traditional model both statistical and economical. A robustness test confirms these conclusions. Therefore, understanding the volatility rules and structural characteristics of the financial market plays a vital role in accurately predicting volatility and preventing financial risk.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103232"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-24DOI: 10.1016/j.ribaf.2025.103263
Yang Hu , Chunlin Lang , Les Oxley , Yang (Greg) Hou
This paper investigates the Granger causality relationship in Bitcoin mining from environmental, sustainable, and miner’s financial perspectives for the period of February 2017 to January 2025. Using a time-varying Granger causality approach of Shi et al. (2018, 2020), we explore how the hashrate, a measure of computational power in the Bitcoin mining process, affects energy consumption, electronic waste, and miners’ revenues. Our findings reveal that an increase in hashrate leads to a significant rise in energy use and electronic waste and affects miners’ revenues. In addition, we show that mining revenue Granger causes the hashrate, suggesting economic incentives drive the network security through the hashrate. These results offer new insights for investors, policymakers, and environmental economists.
{"title":"Time-varying Granger causality in Bitcoin mining: Uncovering shifting links to environment, sustainability, and profitability","authors":"Yang Hu , Chunlin Lang , Les Oxley , Yang (Greg) Hou","doi":"10.1016/j.ribaf.2025.103263","DOIUrl":"10.1016/j.ribaf.2025.103263","url":null,"abstract":"<div><div>This paper investigates the Granger causality relationship in Bitcoin mining from environmental, sustainable, and miner’s financial perspectives for the period of February 2017 to January 2025. Using a time-varying Granger causality approach of Shi et al. (2018, 2020), we explore how the hashrate, a measure of computational power in the Bitcoin mining process, affects energy consumption, electronic waste, and miners’ revenues. Our findings reveal that an increase in hashrate leads to a significant rise in energy use and electronic waste and affects miners’ revenues. In addition, we show that mining revenue Granger causes the hashrate, suggesting economic incentives drive the network security through the hashrate. These results offer new insights for investors, policymakers, and environmental economists.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103263"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-23DOI: 10.1016/j.ribaf.2025.103260
Peilin Fu , Xuan Liu , Shuhong Wang
Green innovation (GI) is a critical pathway to sustainable development. However, the growth of GI remains sluggish and falls short of meeting the pressing demands of environmental protection and carbon mitigation. While extant literature predominantly emphasizes GI quantity, this study uncovers the structural roots of GI stagnation through the aspect of biased technological progress. Using a comprehensive panel dataset of Chinese A-share listed firms from 2010 to 2021 and employing fixed-effects and instrumental variable regression models, we find that traditional finance (TF) tends to favor non-green innovation (NGI) due to its short-term profit orientation, thus widening the gap between GI and NGI. In contrast, green finance (GF) significantly promotes the green-biased technological progress (GBTP), particularly among private enterprises (PEs), by alleviating financing constraints and information asymmetries. Furthermore, the effectiveness of GF is moderated by different types of environmental regulation and information transparency: subsidy-based environmental regulation amplifies the positive effect of GF in PEs, while cost-based regulation plays a more critical role in state-owned enterprises (SOEs). Our findings contribute to the understanding of financial policy design for promoting sustainable technological transformation and offer actionable insights for optimizing green innovation pathways across different ownership structures.
{"title":"Can green finance promote green-biased technological progress?","authors":"Peilin Fu , Xuan Liu , Shuhong Wang","doi":"10.1016/j.ribaf.2025.103260","DOIUrl":"10.1016/j.ribaf.2025.103260","url":null,"abstract":"<div><div>Green innovation (GI) is a critical pathway to sustainable development. However, the growth of GI remains sluggish and falls short of meeting the pressing demands of environmental protection and carbon mitigation. While extant literature predominantly emphasizes GI quantity, this study uncovers the structural roots of GI stagnation through the aspect of biased technological progress. Using a comprehensive panel dataset of Chinese A-share listed firms from 2010 to 2021 and employing fixed-effects and instrumental variable regression models, we find that traditional finance (TF) tends to favor non-green innovation (NGI) due to its short-term profit orientation, thus widening the gap between GI and NGI. In contrast, green finance (GF) significantly promotes the green-biased technological progress (GBTP), particularly among private enterprises (PEs), by alleviating financing constraints and information asymmetries. Furthermore, the effectiveness of GF is moderated by different types of environmental regulation and information transparency: subsidy-based environmental regulation amplifies the positive effect of GF in PEs, while cost-based regulation plays a more critical role in state-owned enterprises (SOEs). Our findings contribute to the understanding of financial policy design for promoting sustainable technological transformation and offer actionable insights for optimizing green innovation pathways across different ownership structures.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103260"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-08DOI: 10.1016/j.ribaf.2025.103249
Genhao Li , Xiaojiao Ye , Chaochao Li , Chao Long
Informal lending has long operated outside formal financial regulation, emerging as a key source of risk in the financial system. However, its role as a potential transmission channel for climate risks has rarely been explored in existing literature. Based on a dual perspective of physical and transition risks, this study systematically examines the impact of climate risks on informal lending default and their spillover effects on the formal financial system. The results show that climate risks exhibit significant heterogeneity in their impact on informal lending default: physical risk significantly increases default risk, serving as the primary climate threat faced by informal lending; transition risk, by contrast, presents a nonlinear impact characterized by short-term inhibition and long-term promotion, which is associated with its short-term boosting effect on return on capital (ROC). The core transmission mechanism is as follows: climate risks erode ROC, exacerbate operational risks, and drive a shift in financing channels toward informal lending, thereby increasing default risk. Heterogeneity analysis reveals that the aforementioned impacts are more pronounced among individual borrowers, in eastern China, and in scenarios affected by extreme low temperatures and heavy rainfall shocks. Furthermore, this study confirms that climate risks can be transmitted to the formal financial system via the informal lending channel, exhibiting significant cross-market spillover effects. This study expands the research scope of climate risks to the informal financial sector, offering new insights into the critical function of informal lending in climate risk transmission.
{"title":"Climate risk, informal lending default, and financial risk spillovers: A dual perspective of physical and transition risks","authors":"Genhao Li , Xiaojiao Ye , Chaochao Li , Chao Long","doi":"10.1016/j.ribaf.2025.103249","DOIUrl":"10.1016/j.ribaf.2025.103249","url":null,"abstract":"<div><div>Informal lending has long operated outside formal financial regulation, emerging as a key source of risk in the financial system. However, its role as a potential transmission channel for climate risks has rarely been explored in existing literature. Based on a dual perspective of physical and transition risks, this study systematically examines the impact of climate risks on informal lending default and their spillover effects on the formal financial system. The results show that climate risks exhibit significant heterogeneity in their impact on informal lending default: physical risk significantly increases default risk, serving as the primary climate threat faced by informal lending; transition risk, by contrast, presents a nonlinear impact characterized by short-term inhibition and long-term promotion, which is associated with its short-term boosting effect on return on capital (ROC). The core transmission mechanism is as follows: climate risks erode ROC, exacerbate operational risks, and drive a shift in financing channels toward informal lending, thereby increasing default risk. Heterogeneity analysis reveals that the aforementioned impacts are more pronounced among individual borrowers, in eastern China, and in scenarios affected by extreme low temperatures and heavy rainfall shocks. Furthermore, this study confirms that climate risks can be transmitted to the formal financial system via the informal lending channel, exhibiting significant cross-market spillover effects. This study expands the research scope of climate risks to the informal financial sector, offering new insights into the critical function of informal lending in climate risk transmission.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103249"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-05DOI: 10.1016/j.ribaf.2025.103250
Zhongyuan Li , Shuo Chen , Ruike Ye , Wenzhi Chen
The motivation for outward foreign direct investment (OFDI) has consistently been a focal point in international business research. Using data from listed Chinese firms, this study examined whether peer effects drive OFDI. We meticulously identified peer effect-driven OFDI as an enterprise engaging in OFDI in a country where other firms from the same city and industry have already invested. Our findings revealed that peer firms’ OFDI activities significantly influence focal firms’ OFDI behavior, and learning and competition mechanisms drive these peer effects. The peer effects are more pronounced among firms that are larger, older, more profitable, or state-owned. Furthermore, under the learning mechanism, firms exhibit rational OFDI behavior, favoring geographically or culturally proximate countries. In contrast, under the competition mechanism, firms exhibit irrational OFDI behavior, preferring to invest in geographically or culturally distant countries. These results offer valuable insights for policymakers seeking to guide firms toward rational OFDI.
{"title":"A dual lens examination of peer effects on OFDI: Learning and competition perspectives","authors":"Zhongyuan Li , Shuo Chen , Ruike Ye , Wenzhi Chen","doi":"10.1016/j.ribaf.2025.103250","DOIUrl":"10.1016/j.ribaf.2025.103250","url":null,"abstract":"<div><div>The motivation for outward foreign direct investment (OFDI) has consistently been a focal point in international business research. Using data from listed Chinese firms, this study examined whether peer effects drive OFDI. We meticulously identified peer effect-driven OFDI as an enterprise engaging in OFDI in a country where other firms from the same city and industry have already invested. Our findings revealed that peer firms’ OFDI activities significantly influence focal firms’ OFDI behavior, and learning and competition mechanisms drive these peer effects. The peer effects are more pronounced among firms that are larger, older, more profitable, or state-owned. Furthermore, under the learning mechanism, firms exhibit rational OFDI behavior, favoring geographically or culturally proximate countries. In contrast, under the competition mechanism, firms exhibit irrational OFDI behavior, preferring to invest in geographically or culturally distant countries. These results offer valuable insights for policymakers seeking to guide firms toward rational OFDI.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103250"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-05DOI: 10.1016/j.ribaf.2025.103248
Shuping Li , Xiaoyang Yao , Jianfeng Li
This study applies the generalized dynamic factor model (GDFM), TVP-VAR-DY framework, and pattern causality to investigate spillover effect from international commodity idiosyncratic volatility co-movements to China’s financial market risk, as well as the impact of a series of macroeconomic factors on such spillover effect. The empirical results indicate that the idiosyncratic volatility co-movements of energy, industrial metals, precious metals, soft commodities, and agricultural products all have significant spillover effects on China’s financial market risk. The influence of commodity idiosyncratic co-movements on China’s financial market risk is relatively stable under normal economic conditions but intensifies significantly during periods of deteriorating economic fundamentals. Macroeconomic factors such as international capital flows, investor sentiment, geopolitical risks, economic conditions, and international freight rates predominantly exhibit a positive causal effect on the dynamic spillover effect.
{"title":"The impact of co-movements in international commodity idiosyncratic volatility on China’s financial market risk","authors":"Shuping Li , Xiaoyang Yao , Jianfeng Li","doi":"10.1016/j.ribaf.2025.103248","DOIUrl":"10.1016/j.ribaf.2025.103248","url":null,"abstract":"<div><div>This study applies the generalized dynamic factor model (GDFM), TVP-VAR-DY framework, and pattern causality to investigate spillover effect from international commodity idiosyncratic volatility co-movements to China’s financial market risk, as well as the impact of a series of macroeconomic factors on such spillover effect. The empirical results indicate that the idiosyncratic volatility co-movements of energy, industrial metals, precious metals, soft commodities, and agricultural products all have significant spillover effects on China’s financial market risk. The influence of commodity idiosyncratic co-movements on China’s financial market risk is relatively stable under normal economic conditions but intensifies significantly during periods of deteriorating economic fundamentals. Macroeconomic factors such as international capital flows, investor sentiment, geopolitical risks, economic conditions, and international freight rates predominantly exhibit a positive causal effect on the dynamic spillover effect.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103248"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-11-30DOI: 10.1016/j.ribaf.2025.103231
Jin-Gyu Jeong , Suk-Joon Byun , Donghoon Kim
This study employs a chart image-based convolutional neural network (CNN) to predict stock returns in the Korean stock market, following Jiang et al. (2023). We transform historical price and volume data into chart images and utilize CNN to extract predictive patterns. Our findings demonstrate that the CNN-based models outperform traditional benchmarks, particularly for short-term return forecasts. Additional double-sort and panel logistic regression analyses with firm characteristic variables, buy-sell imbalance analysis of investor groups, and subsample tests confirm the robustness of CNN-based predictors. This study represents the first application of a chart image-based deep learning model to the Korean stock market, providing new insights into the potential of deep learning models for stock return forecasting in emerging markets.
本研究采用基于图表图像的卷积神经网络（CNN）来预测韩国股市的股票收益，借鉴Jiang et al.（2023）。我们将历史价格和成交量数据转换为图表图像，并利用CNN提取预测模式。我们的研究结果表明，基于cnn的模型优于传统基准，特别是在短期回报预测方面。额外的双排序和面板逻辑回归分析与公司特征变量，投资者群体的买卖不平衡分析，和子样本检验证实了cnn基于预测的稳健性。该研究首次将基于图表图像的深度学习模型应用于韩国股票市场，为深度学习模型在新兴市场股票收益预测中的潜力提供了新的见解。
{"title":"Forecasting returns using image-based convolutional neural networks: Evidence from Korea","authors":"Jin-Gyu Jeong , Suk-Joon Byun , Donghoon Kim","doi":"10.1016/j.ribaf.2025.103231","DOIUrl":"10.1016/j.ribaf.2025.103231","url":null,"abstract":"<div><div>This study employs a chart image-based convolutional neural network (CNN) to predict stock returns in the Korean stock market, following Jiang et al. (2023). We transform historical price and volume data into chart images and utilize CNN to extract predictive patterns. Our findings demonstrate that the CNN-based models outperform traditional benchmarks, particularly for short-term return forecasts. Additional double-sort and panel logistic regression analyses with firm characteristic variables, buy-sell imbalance analysis of investor groups, and subsample tests confirm the robustness of CNN-based predictors. This study represents the first application of a chart image-based deep learning model to the Korean stock market, providing new insights into the potential of deep learning models for stock return forecasting in emerging markets.</div></div>","PeriodicalId":51430,"journal":{"name":"Research in International Business and Finance","volume":"82 ","pages":"Article 103231"},"PeriodicalIF":6.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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