Pub Date : 2025-01-01DOI: 10.1016/j.intfin.2024.102086
Matthew Greenwood-Nimmo , Daan Steenkamp , Rossouw van Jaarsveld
We develop a network model capturing the dynamic interactions among foreign exchange (FX) returns and realized risk measures for 20 developed market (DM) and emerging market (EM) currencies. We show that DM currencies are more integrated within the network than EM currencies on average and tend to become more dependent on external conditions over time. Spillovers between DMs and EMs evolve more rapidly than spillovers within DMs and within EMs and are a major contributor to overall spillover dynamics. Auxiliary regressions reveal that the net DM-to-EM spillover comoves with global factors known to drive EM capital flows.
{"title":"Risk and return spillovers among developed and emerging market currencies","authors":"Matthew Greenwood-Nimmo , Daan Steenkamp , Rossouw van Jaarsveld","doi":"10.1016/j.intfin.2024.102086","DOIUrl":"10.1016/j.intfin.2024.102086","url":null,"abstract":"<div><div>We develop a network model capturing the dynamic interactions among foreign exchange (FX) returns and realized risk measures for 20 developed market (DM) and emerging market (EM) currencies. We show that DM currencies are more integrated within the network than EM currencies on average and tend to become more dependent on external conditions over time. Spillovers between DMs and EMs evolve more rapidly than spillovers within DMs and within EMs and are a major contributor to overall spillover dynamics. Auxiliary regressions reveal that the net DM-to-EM spillover comoves with global factors known to drive EM capital flows.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"98 ","pages":"Article 102086"},"PeriodicalIF":5.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143101851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study examines the directional return predictability between the technology sector of U.S. stock market and three major cryptocurrencies (Bitcoin, Ethereum, and Dogecoin). Using daily data from August 7, 2015, to February 8, 2024, and the cross-quantilogram approach in both static and dynamic settings, the results reveal significant positive predictability in the stock market–cryptocurrency nexus. The technology sector, semiconductors subsector, and Nvidia Corporation exert predictive power over cryptocurrency returns and vice versa across several quantiles and lags. When controlling for the impact of other financial variables, namely, U.S. dollar and U.S. treasury markets, the return predictability holds, especially for the two largest cryptocurrencies, Bitcoin and Ethereum, which reflects their importance and tighter connections with the U.S. technology sector. A trading strategy based on the results of the cross-quantilograms outperforms a benchmark strategy (i.e., always long position in either stocks or cryptocurrency), which underlines the practical implications of our main findings, particularly in terms of the significant return interactions between U.S. technology/semiconductors stocks and large cryptocurrencies.
{"title":"Tech titans and crypto giants: Mutual returns predictability and trading strategy implications","authors":"Elie Bouri , Amin Sokhanvar , Harald Kinateder , Serhan Çiftçioğlu","doi":"10.1016/j.intfin.2024.102109","DOIUrl":"10.1016/j.intfin.2024.102109","url":null,"abstract":"<div><div>This study examines the directional return predictability between the technology sector of U.S. stock market and three major cryptocurrencies (Bitcoin, Ethereum, and Dogecoin). Using daily data from August 7, 2015, to February 8, 2024, and the cross-quantilogram approach in both static and dynamic settings, the results reveal significant positive predictability in the stock market–cryptocurrency nexus. The technology sector, semiconductors subsector, and Nvidia Corporation exert predictive power over cryptocurrency returns and vice versa across several quantiles and lags. When controlling for the impact of other financial variables, namely, U.S. dollar and U.S. treasury markets, the return predictability holds, especially for the two largest cryptocurrencies, Bitcoin and Ethereum, which reflects their importance and tighter connections with the U.S. technology sector. A trading strategy based on the results of the cross-quantilograms outperforms a benchmark strategy (i.e., always long position in either stocks or cryptocurrency), which underlines the practical implications of our main findings, particularly in terms of the significant return interactions between U.S. technology/semiconductors stocks and large cryptocurrencies.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"99 ","pages":"Article 102109"},"PeriodicalIF":5.4,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-12-24DOI: 10.1016/j.intfin.2024.102106
Yunhan Zhang, Zhixin Liu, Hao Jin
This paper develops a two-country dynamic general equilibrium model with a range of fiscal policy instruments and external policies. We employ this model to examine the transmission mechanisms of fiscal consolidation and evaluate both the domestic and spillover effects of various fiscal consolidation strategies. In particular, we focus on how exchange rate regimes and financial openness influence these effects. Our findings are as follows. Firstly, a reduction in government investment significantly harms economic growth, while a reduction in transfer payments worsens income inequality. Additionally, a rise in corporate social security taxes has the most pronounced negative impact on the labor market. Secondly, the reforms of the exchange rate regime and financial account policy contribute to creating more favorable conditions for fiscal rebalancing. Lastly, China’s 2021 fiscal consolidation hit the domestic economy negatively both in the short and long term. However, it had a positive spillover effect in the short term, with a negative effect in the long term. Moreover, relative to the actual consolidation measure, the labor market-friendly and growth-friendly scenarios lead to less declines in employment and output, whereas the social-friendly scenario results in a lower domestic Gini coefficient and is preferred from a welfare perspective.
{"title":"The domestic and spillover effects of fiscal consolidation: The role of fiscal instruments, exchange rate regimes, and capital controls","authors":"Yunhan Zhang, Zhixin Liu, Hao Jin","doi":"10.1016/j.intfin.2024.102106","DOIUrl":"10.1016/j.intfin.2024.102106","url":null,"abstract":"<div><div>This paper develops a two-country dynamic general equilibrium model with a range of fiscal policy instruments and external policies. We employ this model to examine the transmission mechanisms of fiscal consolidation and evaluate both the domestic and spillover effects of various fiscal consolidation strategies. In particular, we focus on how exchange rate regimes and financial openness influence these effects. Our findings are as follows. Firstly, a reduction in government investment significantly harms economic growth, while a reduction in transfer payments worsens income inequality. Additionally, a rise in corporate social security taxes has the most pronounced negative impact on the labor market. Secondly, the reforms of the exchange rate regime and financial account policy contribute to creating more favorable conditions for fiscal rebalancing. Lastly, China’s 2021 fiscal consolidation hit the domestic economy negatively both in the short and long term. However, it had a positive spillover effect in the short term, with a negative effect in the long term. Moreover, relative to the actual consolidation measure, the labor market-friendly and growth-friendly scenarios lead to less declines in employment and output, whereas the social-friendly scenario results in a lower domestic Gini coefficient and is preferred from a welfare perspective.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"99 ","pages":"Article 102106"},"PeriodicalIF":5.4,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183695","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 : 2024-12-22DOI: 10.1016/j.intfin.2024.102104
Muhammad Suhail Rizwan , Ghufran Ahmad , Anum Qureshi
Central Bank Digital Currency (CBDC) is an emerging Financial Technology (FinTech) area. Several countries are involved in CBDC development at different stages and a few are already in the launching stage. We use the autoregressive distributed lag approach to explore the association between CBDC-related news and systemic risk in the short and long run by employing dynamic panel heterogeneity analysis. The results show that CBDC-related news has a significant negative association with systemic risk in the long run, indicating a positive reception by the global financial sector. Extended analysis shows that the long-run negative association is consistent across different income levels and geographical regions. However, countries in the advanced stages of CBDC development show a significant positive association between CBDC-related news and systemic risk warranting the utmost care in implementing CBDC initiatives.
{"title":"Central bank digital currency and systemic risk","authors":"Muhammad Suhail Rizwan , Ghufran Ahmad , Anum Qureshi","doi":"10.1016/j.intfin.2024.102104","DOIUrl":"10.1016/j.intfin.2024.102104","url":null,"abstract":"<div><div>Central Bank Digital Currency (CBDC) is an emerging Financial Technology (FinTech) area. Several countries are involved in CBDC development at different stages and a few are already in the launching stage. We use the autoregressive distributed lag approach to explore the association between CBDC-related news and systemic risk in the short and long run by employing dynamic panel heterogeneity analysis. The results show that CBDC-related news has a significant negative association with systemic risk in the long run, indicating a positive reception by the global financial sector. Extended analysis shows that the long-run negative association is consistent across different income levels and geographical regions. However, countries in the advanced stages of CBDC development show a significant positive association between CBDC-related news and systemic risk warranting the utmost care in implementing CBDC initiatives.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"99 ","pages":"Article 102104"},"PeriodicalIF":5.4,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-12-12DOI: 10.1016/j.intfin.2024.102096
Seraina C. Anagnostopoulou , Andrianos E. Tsekrekos
We examine whether acquirers make better acquisitions when target firms’ financial statements exhibit higher comparability with those of the acquirer. We hypothesize that higher comparability between M&A bidders/targets will result in lower deal integration and information processing costs, and easier detection of any financial misreporting practices. We examine long-run deal performance and find that financial reporting comparability between acquirers/targets is positively associated with long-run deal performance and makes post-acquisition divestitures less likely, consistent with comparability resulting in more successful acquisitions. We provide evidence on how comparative accounting information between M&A counterparties influences capital allocation decisions and value creation.
{"title":"Accounting comparability between M&A bidders and targets and deal outcome","authors":"Seraina C. Anagnostopoulou , Andrianos E. Tsekrekos","doi":"10.1016/j.intfin.2024.102096","DOIUrl":"10.1016/j.intfin.2024.102096","url":null,"abstract":"<div><div>We examine whether acquirers make better acquisitions when target firms’ financial statements exhibit higher comparability with those of the acquirer. We hypothesize that higher comparability between M&A bidders/targets will result in lower deal integration and information processing costs, and easier detection of any financial misreporting practices. We examine long-run deal performance and find that financial reporting comparability between acquirers/targets is positively associated with long-run deal performance and makes post-acquisition divestitures less likely, consistent with comparability resulting in more successful acquisitions. We provide evidence on how comparative accounting information between M&A counterparties influences capital allocation decisions and value creation.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"99 ","pages":"Article 102096"},"PeriodicalIF":5.4,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183712","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 : 2024-12-04DOI: 10.1016/j.intfin.2024.102093
Niranjan Sapkota
This research explores the factors contributing to the failure of cryptocurrency exchanges by analyzing a sample of 845 exchanges. Using logit and probit models, it identifies key variables affecting cryptocurrency exchange defaults. The results show that cryptocurrency exchanges that are centralized, located in countries with high transparency indices, and offer fewer peer cryptocurrencies are more likely to default. Additionally, exchanges that impose high withdrawal fees and have no restrictions on clients from the United States are also positively associated with defaults. Moreover, the absence of referral schemes and having lower ratings each contributes marginally to defaults. Machine learning (ML) models including random forest, support vector machine, stacked ensemble confirm the robustness and high predictability of cryptocurrency exchange defaults.
{"title":"The crypto collapse chronicles: Decoding cryptocurrency exchange defaults","authors":"Niranjan Sapkota","doi":"10.1016/j.intfin.2024.102093","DOIUrl":"10.1016/j.intfin.2024.102093","url":null,"abstract":"<div><div>This research explores the factors contributing to the failure of cryptocurrency exchanges by analyzing a sample of 845 exchanges. Using logit and probit models, it identifies key variables affecting cryptocurrency exchange defaults. The results show that cryptocurrency exchanges that are centralized, located in countries with high transparency indices, and offer fewer peer cryptocurrencies are more likely to default. Additionally, exchanges that impose high withdrawal fees and have no restrictions on clients from the United States are also positively associated with defaults. Moreover, the absence of referral schemes and having lower ratings each contributes marginally to defaults. Machine learning (ML) models including random forest, support vector machine, stacked ensemble confirm the robustness and high predictability of cryptocurrency exchange defaults.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"99 ","pages":"Article 102093"},"PeriodicalIF":5.4,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-11-29DOI: 10.1016/j.intfin.2024.102084
Bogdan Dima , Ştefana Maria Dima , Roxana Ioan
Understanding the risk premium and its impact on current and expected returns is a critical research problem. The present study contributes to the investigation of risk premium decomposition over short-run periods via two key advancements. First, it presents a model that incorporates past uncertainties regarding investors’ trade outcome expectations into current predictions. This model enables a short-run decomposition of the risk premium. Second, the study examines the relationship between past volatility and current expected trading results for the Chicago Board Options Exchange Volatility Index (VIX) using daily data from January 5, 2016, to January 20, 2023. The findings indicate that current expected losses are influenced by the volatility of previously predicted unfavourable trade outcomes, underscoring the relevance of this study to portfolio management decisions. The parameter that captures this impact exhibits significant time variation. This result remains robust across various specifications of a time-varying parameter model with shrinkage. We further validate this robustness by testing different time frequencies, analysing various types of instruments and markets, and employing an alternative risk estimation method. Ultimately, the findings suggest that proactive stabilisation policies must be implemented to enhance the quality, relevance, and availability of information disseminated by financial asset issuers throughout the market.
{"title":"The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX","authors":"Bogdan Dima , Ştefana Maria Dima , Roxana Ioan","doi":"10.1016/j.intfin.2024.102084","DOIUrl":"10.1016/j.intfin.2024.102084","url":null,"abstract":"<div><div>Understanding the risk premium and its impact on current and expected returns is a critical research problem. The present study contributes to the investigation of risk premium decomposition over short-run periods via two key advancements. First, it presents a model that incorporates past uncertainties regarding investors’ trade outcome expectations into current predictions. This model enables a short-run decomposition of the risk premium. Second, the study examines the relationship between past volatility and current expected trading results for the Chicago Board Options Exchange Volatility Index (VIX) using daily data from January 5, 2016, to January 20, 2023. The findings indicate that current expected losses are influenced by the volatility of previously predicted unfavourable trade outcomes, underscoring the relevance of this study to portfolio management decisions. The parameter that captures this impact exhibits significant time variation. This result remains robust across various specifications of a time-varying parameter model with shrinkage. We further validate this robustness by testing different time frequencies, analysing various types of instruments and markets, and employing an alternative risk estimation method. Ultimately, the findings suggest that proactive stabilisation policies must be implemented to enhance the quality, relevance, and availability of information disseminated by financial asset issuers throughout the market.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"98 ","pages":"Article 102084"},"PeriodicalIF":5.4,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142745320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-11-27DOI: 10.1016/j.intfin.2024.102085
Jun Hu , Siyu Zhang , Liang Wang , Daifei Yao
This study explores how the introduction of the carbon emissions trading scheme (ETS) affects investors’ reactions to corporate earnings surprises. We propose two non-exclusive explanations, namely, the preference-based view and the uncertainty-based view, and suggest that the implementation of ETS may influence the magnitude of investor responses to corporate unexpected earnings. Consistent with the preference-based view, by utilizing China’s introduction of ETS as a quasi-natural experiment, we observe a reduction in the earnings response coefficients (ERCs) following the implementation of ETS. We validate this result by showing that the introduction of ETS prompts investors to focus on corporate carbon risk. Cross-sectional tests find that the effect of ETS on ERCs is more pronounced in firms with higher corporate carbon risk exposure, in firms whose investors exhibit greater environmental awareness, in better-developed carbon pilot markets, and in firms with greater exposure to international capital markets, while this impact is mitigated by firms’ non-financial performance. These findings highlight the importance of environmental regulation and market liberalization in influencing investors’ resource allocation.
{"title":"Carbon emission trading scheme, investors’ attention, and earnings response coefficients","authors":"Jun Hu , Siyu Zhang , Liang Wang , Daifei Yao","doi":"10.1016/j.intfin.2024.102085","DOIUrl":"10.1016/j.intfin.2024.102085","url":null,"abstract":"<div><div>This study explores how the introduction of the carbon emissions trading scheme (ETS) affects investors’ reactions to corporate earnings surprises. We propose two non-exclusive explanations, namely, the preference-based view and the uncertainty-based view, and suggest that the implementation of ETS may influence the magnitude of investor responses to corporate unexpected earnings. Consistent with the preference-based view, by utilizing China’s introduction of ETS as a quasi-natural experiment, we observe a reduction in the earnings response coefficients (ERCs) following the implementation of ETS. We validate this result by showing that the introduction of ETS prompts investors to focus on corporate carbon risk. Cross-sectional tests find that the effect of ETS on ERCs is more pronounced in firms with higher corporate carbon risk exposure, in firms whose investors exhibit greater environmental awareness, in better-developed carbon pilot markets, and in firms with greater exposure to international capital markets, while this impact is mitigated by firms’ non-financial performance. These findings highlight the importance of environmental regulation and market liberalization in influencing investors’ resource allocation.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102085"},"PeriodicalIF":5.4,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142719882","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 : 2024-11-25DOI: 10.1016/j.intfin.2024.102083
Carmela D’Avino
This paper examines whether global banks’ liquidity reallocations via internal capital markets are driven by the locational activity patterns of their foreign branches. Using aggregated data of foreign branches of US global banks located in 52 countries, we advance evidence of a picking order that favors locations where branches are more heavily engaged in lending activities. Specifically, we find that internal liquidity support to branches in host countries with prominent local lending activities is especially significant during a contraction in local deposits.
In jurisdictions where branches have higher shares of market-based activities and off-balance sheet exposures, we do not observe a significant increase in internal liquidity support following local funding contractions.
{"title":"Global banks and the picking order in internal capital markets: Do locational activity patterns matter?","authors":"Carmela D’Avino","doi":"10.1016/j.intfin.2024.102083","DOIUrl":"10.1016/j.intfin.2024.102083","url":null,"abstract":"<div><div>This paper examines whether global banks’ liquidity reallocations via internal capital markets are driven by the locational activity patterns of their foreign branches. Using aggregated data of foreign branches of US global banks located in 52 countries, we advance evidence of a picking order that favors locations where branches are more heavily engaged in lending activities. Specifically, we find that internal liquidity support to branches in host countries with prominent local lending activities is especially significant during a contraction in local deposits.</div><div>In jurisdictions where branches have higher shares of market-based activities and off-balance sheet exposures, we do not observe a significant increase in internal liquidity support following local funding contractions.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102083"},"PeriodicalIF":5.4,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700683","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 : 2024-11-22DOI: 10.1016/j.intfin.2024.102082
Erdinc Akyildirim , Thomas Conlon , Shaen Corbet , Yang (Greg) Hou
Increasing levels of digitisation make firms more susceptible to cyberattacks and privacy violations. In this paper, we quantify the impact of cybercrime on company stock returns using a large international sample. On the day after the cyber event, stock returns are found to decrease by -0.24%, but the effect reverses in about two weeks. The magnitude of the decrease in the stock market is greatest for companies that have experienced reoccurring events and for breaches deemed to be most severe. We show that the extent of the stock market decline cannot be explained by national institutional and macroeconomic factors, and is related to company-specific characteristics, including size, volatility, credit ranking and asset volatility. The empirical results highlight important policy and regulatory issues, not least the need for cyber risk disclosure requirements.
{"title":"HACKED: Understanding the stock market response to cyberattacks","authors":"Erdinc Akyildirim , Thomas Conlon , Shaen Corbet , Yang (Greg) Hou","doi":"10.1016/j.intfin.2024.102082","DOIUrl":"10.1016/j.intfin.2024.102082","url":null,"abstract":"<div><div>Increasing levels of digitisation make firms more susceptible to cyberattacks and privacy violations. In this paper, we quantify the impact of cybercrime on company stock returns using a large international sample. On the day after the cyber event, stock returns are found to decrease by -0.24%, but the effect reverses in about two weeks. The magnitude of the decrease in the stock market is greatest for companies that have experienced reoccurring events and for breaches deemed to be most severe. We show that the extent of the stock market decline cannot be explained by national institutional and macroeconomic factors, and is related to company-specific characteristics, including size, volatility, credit ranking and asset volatility. The empirical results highlight important policy and regulatory issues, not least the need for cyber risk disclosure requirements.</div></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":"97 ","pages":"Article 102082"},"PeriodicalIF":5.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142700682","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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