Pub Date : 2024-03-19DOI: 10.1108/jrf-12-2023-0310
Raul Gómez-Martínez, María Luisa Medrano-García
PurposeCorporate diversity encompasses the different talents, knowledge, cultures, experiences and values of its employees. This diversity is reflected in multiple characteristics, such as race, age, gender, social class, religion, sexual orientation, ethnicity, culture and disability. The objective of this study is to identify if diversity is a value driver.Design/methodology/approachWe take the diversity score from the Diversity Leaders Index 2023 published by Financial Times (FT) and Statista; this will be our independent variable in linear regression models whose objective variables are relevant fundamental indicators of the Euro Stoxx 50 companies. It is, therefore, a cross-sectional sample with financial data taken as of the current date. We have 37 Euro Stoxx 50 components included in the diversity ranking.FindingsThe results indicate that diversity is not a value driver for trading volume, for its revenue, or for systematic risk measured by the beta parameter. However, it is observed, in a confidence interval of 90%, that the most diverse companies are larger (according to their market capitalization). In addition, the most diverse companies are more profitable [return on assets (ROA)] and valued by the market [price to earnings ratio (PER)] in a confidence interval of 95%.Originality/valueThese results indicate that companies should promote corporate diversity as a management strategy, as it is observed that more diverse companies are more profitable and valued by the market. This study provides a quantitative vision in the context of homogeneous companies such as the Euro Stoxx 50 Index on the aspects in which diversity is a value driver.
{"title":"Diversity as value driver in Euro Stoxx 50 companies","authors":"Raul Gómez-Martínez, María Luisa Medrano-García","doi":"10.1108/jrf-12-2023-0310","DOIUrl":"https://doi.org/10.1108/jrf-12-2023-0310","url":null,"abstract":"PurposeCorporate diversity encompasses the different talents, knowledge, cultures, experiences and values of its employees. This diversity is reflected in multiple characteristics, such as race, age, gender, social class, religion, sexual orientation, ethnicity, culture and disability. The objective of this study is to identify if diversity is a value driver.Design/methodology/approachWe take the diversity score from the Diversity Leaders Index 2023 published by Financial Times (FT) and Statista; this will be our independent variable in linear regression models whose objective variables are relevant fundamental indicators of the Euro Stoxx 50 companies. It is, therefore, a cross-sectional sample with financial data taken as of the current date. We have 37 Euro Stoxx 50 components included in the diversity ranking.FindingsThe results indicate that diversity is not a value driver for trading volume, for its revenue, or for systematic risk measured by the beta parameter. However, it is observed, in a confidence interval of 90%, that the most diverse companies are larger (according to their market capitalization). In addition, the most diverse companies are more profitable [return on assets (ROA)] and valued by the market [price to earnings ratio (PER)] in a confidence interval of 95%.Originality/valueThese results indicate that companies should promote corporate diversity as a management strategy, as it is observed that more diverse companies are more profitable and valued by the market. This study provides a quantitative vision in the context of homogeneous companies such as the Euro Stoxx 50 Index on the aspects in which diversity is a value driver.","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140228978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1108/jrf-05-2023-0124
Julien Dhima, Catherine Bruneau
PurposeThis study aims to demonstrate and measure the impact of liquidity shocks on a bank’s solvency, especially when the bank does not hold sufficient liquid assets.Design/methodology/approachThe proposed model is an extension of Merton’s (1974) model. It assesses the bank’s probability of default over one or two (short) periods relative to liquidity shocks. The shock scenarios are materialised by different net demands for the withdrawal of funds (NDWF) and may lead the bank to sell illiquid assets at a depreciated value. We consider the possibility of second-round effects at the beginning of the second period by introducing the probability of their occurrence. This probability depends on the proportion of illiquid assets put up for sale following the initial shock in different dependency scenarios.FindingsWe observe a positive relationship between the initial NDWF and the bank’s probability of default (particularly over the second period, which is conditional on the second-round effects). However, this relationship is not linear, and a significant proportion of liquid assets makes it possible to attenuate or even eliminate the effects of shock scenarios on bank solvency.Practical implicationsThe proposed model enables banks to determine the necessary level of liquid assets, allowing them to resist (i.e. remain solvent) different liquidity shock scenarios for both periods (including eventual second-round effects) under the assumptions considered. Therefore, it can contribute to complementing or improving current internal liquidity adequacy assessment processes (ILAAPs).Originality/valueThe proposed microprudential approach consists of measuring the impact of liquidity risk on a bank’s solvency, complementing the current prudential framework in which these two topics are treated separately. It also complements the existing literature, in which the impact of liquidity risk on solvency risk has not been sufficiently studied. Finally, our model allows banks to manage liquidity using a solvency approach.
{"title":"Impact of specific liquidity shocks on the bank's solvency","authors":"Julien Dhima, Catherine Bruneau","doi":"10.1108/jrf-05-2023-0124","DOIUrl":"https://doi.org/10.1108/jrf-05-2023-0124","url":null,"abstract":"PurposeThis study aims to demonstrate and measure the impact of liquidity shocks on a bank’s solvency, especially when the bank does not hold sufficient liquid assets.Design/methodology/approachThe proposed model is an extension of Merton’s (1974) model. It assesses the bank’s probability of default over one or two (short) periods relative to liquidity shocks. The shock scenarios are materialised by different net demands for the withdrawal of funds (NDWF) and may lead the bank to sell illiquid assets at a depreciated value. We consider the possibility of second-round effects at the beginning of the second period by introducing the probability of their occurrence. This probability depends on the proportion of illiquid assets put up for sale following the initial shock in different dependency scenarios.FindingsWe observe a positive relationship between the initial NDWF and the bank’s probability of default (particularly over the second period, which is conditional on the second-round effects). However, this relationship is not linear, and a significant proportion of liquid assets makes it possible to attenuate or even eliminate the effects of shock scenarios on bank solvency.Practical implicationsThe proposed model enables banks to determine the necessary level of liquid assets, allowing them to resist (i.e. remain solvent) different liquidity shock scenarios for both periods (including eventual second-round effects) under the assumptions considered. Therefore, it can contribute to complementing or improving current internal liquidity adequacy assessment processes (ILAAPs).Originality/valueThe proposed microprudential approach consists of measuring the impact of liquidity risk on a bank’s solvency, complementing the current prudential framework in which these two topics are treated separately. It also complements the existing literature, in which the impact of liquidity risk on solvency risk has not been sufficiently studied. Finally, our model allows banks to manage liquidity using a solvency approach.","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140426312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.1108/jrf-10-2023-0261
D. Beju, Maria Ciupac-Ulici, V. Bresfelean
PurposeThis paper aims to investigate the impact of political stability on corruption by drawing upon a sample encompassing both developed and developing European and Asian countries.Design/methodology/approachThe dataset, sourced from the Refinitiv database, spans from July 2014 to May 2022. Panel data techniques, specifically pooled estimation and dynamic panel data [generalized method of moments (GMM)] are employed. The analysis encompasses both fixed and random effects models to capture country-specific cross-sectional effects. To validate our findings, we perform a robustness test by including in the investigation four control variables, namely poverty, type of governance, economic freedom and inflation. To test heterogeneity, the dataset is further divided into two distinct subsamples based on the countries’ locations.FindingsEmpirical findings substantiate that political stability (viewed as the risk of government destabilization) has a positive and significant impact on corruption in all analyzed samples of European and Asian countries, though some differences are observed in various subsamples. When we take into account the control variables, these analysis results are robust.Research limitations/implicationsThis research provided a panel data analysis with GMM, while other empirical methodologies could also be used, like the difference-in-difference approach. However, our results should be validated by extending the time and the sample to a worldwide sample and using alternative measures of corruption and political stability. Moreover, our focus was on a linear and unidirectional relationship between the considered variables, but it would be interesting to test in our further research a non-linear and bidirectional correlation between them. Furthermore, we have introduced in the robustness test only four economic variables, but to consolidate our findings, we plan to include socioeconomic and demographic variables in future studies.Practical implicationsThese outcomes imply that authorities should be aware of the necessity of implementing anti-corruption policies designed to establish effective agencies and enforcement structures for combating systemic corruption, to improve the political environment and the quality of institutions and to apply coherent economic strategies to accelerate economic growth because higher political stability and sustainable development determine a decrease in levels of corruption.Social implicationsAt the microeconomic level, the survival of organizations may be in danger from new types of corruption and money laundering. Therefore, in order to prevent financial harm, the top businesses worldwide should respond to instances of corruption through strengthened supervisory procedures. This calls for the creation of a mechanism inside the code of conduct where correct reporting of suspected situations of corruption would have a prompt procedure to be notified of. To avoid corruption in operational procedures, na
{"title":"Political stability and corruption nexus: an international perspective on European and Asian countries","authors":"D. Beju, Maria Ciupac-Ulici, V. Bresfelean","doi":"10.1108/jrf-10-2023-0261","DOIUrl":"https://doi.org/10.1108/jrf-10-2023-0261","url":null,"abstract":"PurposeThis paper aims to investigate the impact of political stability on corruption by drawing upon a sample encompassing both developed and developing European and Asian countries.Design/methodology/approachThe dataset, sourced from the Refinitiv database, spans from July 2014 to May 2022. Panel data techniques, specifically pooled estimation and dynamic panel data [generalized method of moments (GMM)] are employed. The analysis encompasses both fixed and random effects models to capture country-specific cross-sectional effects. To validate our findings, we perform a robustness test by including in the investigation four control variables, namely poverty, type of governance, economic freedom and inflation. To test heterogeneity, the dataset is further divided into two distinct subsamples based on the countries’ locations.FindingsEmpirical findings substantiate that political stability (viewed as the risk of government destabilization) has a positive and significant impact on corruption in all analyzed samples of European and Asian countries, though some differences are observed in various subsamples. When we take into account the control variables, these analysis results are robust.Research limitations/implicationsThis research provided a panel data analysis with GMM, while other empirical methodologies could also be used, like the difference-in-difference approach. However, our results should be validated by extending the time and the sample to a worldwide sample and using alternative measures of corruption and political stability. Moreover, our focus was on a linear and unidirectional relationship between the considered variables, but it would be interesting to test in our further research a non-linear and bidirectional correlation between them. Furthermore, we have introduced in the robustness test only four economic variables, but to consolidate our findings, we plan to include socioeconomic and demographic variables in future studies.Practical implicationsThese outcomes imply that authorities should be aware of the necessity of implementing anti-corruption policies designed to establish effective agencies and enforcement structures for combating systemic corruption, to improve the political environment and the quality of institutions and to apply coherent economic strategies to accelerate economic growth because higher political stability and sustainable development determine a decrease in levels of corruption.Social implicationsAt the microeconomic level, the survival of organizations may be in danger from new types of corruption and money laundering. Therefore, in order to prevent financial harm, the top businesses worldwide should respond to instances of corruption through strengthened supervisory procedures. This calls for the creation of a mechanism inside the code of conduct where correct reporting of suspected situations of corruption would have a prompt procedure to be notified of. To avoid corruption in operational procedures, na","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140425979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-21DOI: 10.1108/jrf-04-2023-0096
Shuifeng Hong, Yimin Luo, Mengya Li, Duoping Yang
PurposeThis paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.Design/methodology/approachWith daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.FindingsThe empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.Originality/valueThe MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.
{"title":"Time–frequency correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets","authors":"Shuifeng Hong, Yimin Luo, Mengya Li, Duoping Yang","doi":"10.1108/jrf-04-2023-0096","DOIUrl":"https://doi.org/10.1108/jrf-04-2023-0096","url":null,"abstract":"PurposeThis paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.Design/methodology/approachWith daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.FindingsThe empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.Originality/valueThe MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140442508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-19DOI: 10.1108/jrf-09-2023-0241
Tauqeer Saleem, Ussama Yaqub, Salma Zaman
PurposeThe present study distinguishes itself by pioneering an innovative framework that integrates key elements of prospect theory and the fundamental principles of electronic word of mouth (EWOM) to forecast Bitcoin/USD price fluctuations using Twitter sentiment analysis.Design/methodology/approachWe utilized Twitter data as our primary data source. We meticulously collected a dataset consisting of over 3 million tweets spanning a nine-year period, from 2013 to 2022, covering a total of 3,215 days with an average daily tweet count of 1,000. The tweets were identified by utilizing the “bitcoin” and/or “btc” keywords through the snscrape python library. Diverging from conventional approaches, we introduce four distinct variables, encompassing normalized positive and negative sentiment scores as well as sentiment variance. These refinements markedly enhance sentiment analysis within the sphere of financial risk management.FindingsOur findings highlight the substantial impact of negative sentiments in driving Bitcoin price declines, in contrast to the role of positive sentiments in facilitating price upswings. These results underscore the critical importance of continuous, real-time monitoring of negative sentiment shifts within the cryptocurrency market.Practical implicationsOur study holds substantial significance for both risk managers and investors, providing a crucial tool for well-informed decision-making in the cryptocurrency market. The implications drawn from our study hold notable relevance for financial risk management.Originality/valueWe present an innovative framework combining prospect theory and core principles of EWOM to predict Bitcoin price fluctuations through analysis of Twitter sentiment. Unlike conventional methods, we incorporate distinct positive and negative sentiment scores instead of relying solely on a single compound score. Notably, our pioneering sentiment analysis framework dissects sentiment into separate positive and negative components, advancing our comprehension of market sentiment dynamics. Furthermore, it equips financial institutions and investors with a more detailed and actionable insight into the risks associated not only with Bitcoin but also with other assets influenced by sentiment-driven market dynamics.
{"title":"Twitter sentiment analysis and bitcoin price forecasting: implications for financial risk management","authors":"Tauqeer Saleem, Ussama Yaqub, Salma Zaman","doi":"10.1108/jrf-09-2023-0241","DOIUrl":"https://doi.org/10.1108/jrf-09-2023-0241","url":null,"abstract":"PurposeThe present study distinguishes itself by pioneering an innovative framework that integrates key elements of prospect theory and the fundamental principles of electronic word of mouth (EWOM) to forecast Bitcoin/USD price fluctuations using Twitter sentiment analysis.Design/methodology/approachWe utilized Twitter data as our primary data source. We meticulously collected a dataset consisting of over 3 million tweets spanning a nine-year period, from 2013 to 2022, covering a total of 3,215 days with an average daily tweet count of 1,000. The tweets were identified by utilizing the “bitcoin” and/or “btc” keywords through the snscrape python library. Diverging from conventional approaches, we introduce four distinct variables, encompassing normalized positive and negative sentiment scores as well as sentiment variance. These refinements markedly enhance sentiment analysis within the sphere of financial risk management.FindingsOur findings highlight the substantial impact of negative sentiments in driving Bitcoin price declines, in contrast to the role of positive sentiments in facilitating price upswings. These results underscore the critical importance of continuous, real-time monitoring of negative sentiment shifts within the cryptocurrency market.Practical implicationsOur study holds substantial significance for both risk managers and investors, providing a crucial tool for well-informed decision-making in the cryptocurrency market. The implications drawn from our study hold notable relevance for financial risk management.Originality/valueWe present an innovative framework combining prospect theory and core principles of EWOM to predict Bitcoin price fluctuations through analysis of Twitter sentiment. Unlike conventional methods, we incorporate distinct positive and negative sentiment scores instead of relying solely on a single compound score. Notably, our pioneering sentiment analysis framework dissects sentiment into separate positive and negative components, advancing our comprehension of market sentiment dynamics. Furthermore, it equips financial institutions and investors with a more detailed and actionable insight into the risks associated not only with Bitcoin but also with other assets influenced by sentiment-driven market dynamics.","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-16DOI: 10.1108/jrf-10-2023-0252
Noura Metawa, S. Metawa, Maha Metawea, Ahmed El-Gayar
PurposeThis paper deeply investigates the herd behavior of the Egyptian mutual funds under changing and different conditions of the market pre- and post-events and compares the impact of asymmetric risk conditions on the herding behavior of the Egyptian mutual funds in both up and down markets.Design/methodology/approachWe test for the existence of herding for the whole period from 2003 to 2022, as well as for the pre-and post-different Egyptian uprising periods. We employ two well-known models, namely the cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD) models. Additionally, we use the quantile regression approach.FindingsWe find that the behavior of mutual funds does not change following the different political and social events. For the whole period, we find evidence of herding behavior using only the model of CSAD in down-market conditions. We generalize our finding to be evidence of the existence herding behavior in different quantiles, under only the down market in specific points’ pre, post or both given events throughout the whole series. Conversely, during the upper market, we show a full absence of herding behavior considering all different quantiles. When the market is down, managers are afraid of the condition of uncertainty, neglecting their own private information, avoid acting independently and consequently, following other mutual funds. When the market is up, managers become rational and act fully independent.Research limitations/implicationsFuture research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund performance and investor outcomes.Practical implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently.Social implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently. Future research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund p
{"title":"Asymmetry risk and herding behavior: a quantile regression study of the Egyptian mutual funds","authors":"Noura Metawa, S. Metawa, Maha Metawea, Ahmed El-Gayar","doi":"10.1108/jrf-10-2023-0252","DOIUrl":"https://doi.org/10.1108/jrf-10-2023-0252","url":null,"abstract":"PurposeThis paper deeply investigates the herd behavior of the Egyptian mutual funds under changing and different conditions of the market pre- and post-events and compares the impact of asymmetric risk conditions on the herding behavior of the Egyptian mutual funds in both up and down markets.Design/methodology/approachWe test for the existence of herding for the whole period from 2003 to 2022, as well as for the pre-and post-different Egyptian uprising periods. We employ two well-known models, namely the cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD) models. Additionally, we use the quantile regression approach.FindingsWe find that the behavior of mutual funds does not change following the different political and social events. For the whole period, we find evidence of herding behavior using only the model of CSAD in down-market conditions. We generalize our finding to be evidence of the existence herding behavior in different quantiles, under only the down market in specific points’ pre, post or both given events throughout the whole series. Conversely, during the upper market, we show a full absence of herding behavior considering all different quantiles. When the market is down, managers are afraid of the condition of uncertainty, neglecting their own private information, avoid acting independently and consequently, following other mutual funds. When the market is up, managers become rational and act fully independent.Research limitations/implicationsFuture research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund performance and investor outcomes.Practical implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently.Social implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently. Future research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund p","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139773896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-16DOI: 10.1108/jrf-10-2023-0252
Noura Metawa, S. Metawa, Maha Metawea, Ahmed El-Gayar
PurposeThis paper deeply investigates the herd behavior of the Egyptian mutual funds under changing and different conditions of the market pre- and post-events and compares the impact of asymmetric risk conditions on the herding behavior of the Egyptian mutual funds in both up and down markets.Design/methodology/approachWe test for the existence of herding for the whole period from 2003 to 2022, as well as for the pre-and post-different Egyptian uprising periods. We employ two well-known models, namely the cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD) models. Additionally, we use the quantile regression approach.FindingsWe find that the behavior of mutual funds does not change following the different political and social events. For the whole period, we find evidence of herding behavior using only the model of CSAD in down-market conditions. We generalize our finding to be evidence of the existence herding behavior in different quantiles, under only the down market in specific points’ pre, post or both given events throughout the whole series. Conversely, during the upper market, we show a full absence of herding behavior considering all different quantiles. When the market is down, managers are afraid of the condition of uncertainty, neglecting their own private information, avoid acting independently and consequently, following other mutual funds. When the market is up, managers become rational and act fully independent.Research limitations/implicationsFuture research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund performance and investor outcomes.Practical implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently.Social implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently. Future research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund p
{"title":"Asymmetry risk and herding behavior: a quantile regression study of the Egyptian mutual funds","authors":"Noura Metawa, S. Metawa, Maha Metawea, Ahmed El-Gayar","doi":"10.1108/jrf-10-2023-0252","DOIUrl":"https://doi.org/10.1108/jrf-10-2023-0252","url":null,"abstract":"PurposeThis paper deeply investigates the herd behavior of the Egyptian mutual funds under changing and different conditions of the market pre- and post-events and compares the impact of asymmetric risk conditions on the herding behavior of the Egyptian mutual funds in both up and down markets.Design/methodology/approachWe test for the existence of herding for the whole period from 2003 to 2022, as well as for the pre-and post-different Egyptian uprising periods. We employ two well-known models, namely the cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD) models. Additionally, we use the quantile regression approach.FindingsWe find that the behavior of mutual funds does not change following the different political and social events. For the whole period, we find evidence of herding behavior using only the model of CSAD in down-market conditions. We generalize our finding to be evidence of the existence herding behavior in different quantiles, under only the down market in specific points’ pre, post or both given events throughout the whole series. Conversely, during the upper market, we show a full absence of herding behavior considering all different quantiles. When the market is down, managers are afraid of the condition of uncertainty, neglecting their own private information, avoid acting independently and consequently, following other mutual funds. When the market is up, managers become rational and act fully independent.Research limitations/implicationsFuture research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund performance and investor outcomes.Practical implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently.Social implicationsThe study reveals that the behavior of mutual funds remains consistent despite various political and social events, suggesting a degree of resilience in their investment strategies. The research uncovers evidence of herding behavior in both high and low quantiles, but exclusively in down markets. In such conditions of market decline, fund managers appear to forsake their private information, exhibiting a tendency to follow the crowd rather than acting independently. Future research should delve deeper into the drivers of herding behavior, assess its longer-term effects, develop risk management strategies and consider regulatory measures to mitigate the potential negative impact on mutual fund p","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139833294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.1108/jrf-10-2023-0255
I. Cuceu, Decebal-Remus Florescu, V. Văidean
PurposeThis paper aims to analyze the potential variables explaining the compliance value added tax (VAT) gap, which basically represents an estimate of the unpaid VAT in the economy. A major component of compliance VAT Gap is represented by tax fraud; there exist other causes too, like insolvencies, bankruptcies, optimizations practices and maladministration. The objective of our paper is to revisit the main determinants of the VAT compliance gap for the European Union (EU)-27 member states. Using econometric modeling, our study identifies the relationship between the VAT gap and various determinants of it.Design/methodology/approachOur work focuses on the shadow economy, final consumption, VAT revenues, standard VAT rates, differences between the standard and reduced rates, economic prosperity, press freedom, political stability and others, as determinants of European VAT compliance gaps, for the 2005–2020 time interval. The methods include panel data analysis through simple and multiple regression modeling, the combinatorial approach, fixed and random effects.FindingsOur study validates the direct impact of shadow economy and the indirect impact of VAT revenues, economic prosperity and press freedom, upon VAT compliance gaps. Upon subsampling of EU member states within old and new ones, our results estimate a larger positive impact of shadow economy upon old member states, compared to new ones.Practical implicationsThe policy implications include leverage effects of governments acting upon a reduction in shadow economy phenomena and boosts of economic development, political stability and press freedom, in order to attain the contraction of compliance VAT gaps.Originality/valueOur paper sheds light in a poorly explored scientific area, that of the determinants of VAT gap, especially in relationship with financial and economic crime phenomena.
{"title":"The determinants of compliance VAT gap","authors":"I. Cuceu, Decebal-Remus Florescu, V. Văidean","doi":"10.1108/jrf-10-2023-0255","DOIUrl":"https://doi.org/10.1108/jrf-10-2023-0255","url":null,"abstract":"PurposeThis paper aims to analyze the potential variables explaining the compliance value added tax (VAT) gap, which basically represents an estimate of the unpaid VAT in the economy. A major component of compliance VAT Gap is represented by tax fraud; there exist other causes too, like insolvencies, bankruptcies, optimizations practices and maladministration. The objective of our paper is to revisit the main determinants of the VAT compliance gap for the European Union (EU)-27 member states. Using econometric modeling, our study identifies the relationship between the VAT gap and various determinants of it.Design/methodology/approachOur work focuses on the shadow economy, final consumption, VAT revenues, standard VAT rates, differences between the standard and reduced rates, economic prosperity, press freedom, political stability and others, as determinants of European VAT compliance gaps, for the 2005–2020 time interval. The methods include panel data analysis through simple and multiple regression modeling, the combinatorial approach, fixed and random effects.FindingsOur study validates the direct impact of shadow economy and the indirect impact of VAT revenues, economic prosperity and press freedom, upon VAT compliance gaps. Upon subsampling of EU member states within old and new ones, our results estimate a larger positive impact of shadow economy upon old member states, compared to new ones.Practical implicationsThe policy implications include leverage effects of governments acting upon a reduction in shadow economy phenomena and boosts of economic development, political stability and press freedom, in order to attain the contraction of compliance VAT gaps.Originality/valueOur paper sheds light in a poorly explored scientific area, that of the determinants of VAT gap, especially in relationship with financial and economic crime phenomena.","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139840142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.1108/jrf-10-2023-0255
I. Cuceu, Decebal-Remus Florescu, V. Văidean
PurposeThis paper aims to analyze the potential variables explaining the compliance value added tax (VAT) gap, which basically represents an estimate of the unpaid VAT in the economy. A major component of compliance VAT Gap is represented by tax fraud; there exist other causes too, like insolvencies, bankruptcies, optimizations practices and maladministration. The objective of our paper is to revisit the main determinants of the VAT compliance gap for the European Union (EU)-27 member states. Using econometric modeling, our study identifies the relationship between the VAT gap and various determinants of it.Design/methodology/approachOur work focuses on the shadow economy, final consumption, VAT revenues, standard VAT rates, differences between the standard and reduced rates, economic prosperity, press freedom, political stability and others, as determinants of European VAT compliance gaps, for the 2005–2020 time interval. The methods include panel data analysis through simple and multiple regression modeling, the combinatorial approach, fixed and random effects.FindingsOur study validates the direct impact of shadow economy and the indirect impact of VAT revenues, economic prosperity and press freedom, upon VAT compliance gaps. Upon subsampling of EU member states within old and new ones, our results estimate a larger positive impact of shadow economy upon old member states, compared to new ones.Practical implicationsThe policy implications include leverage effects of governments acting upon a reduction in shadow economy phenomena and boosts of economic development, political stability and press freedom, in order to attain the contraction of compliance VAT gaps.Originality/valueOur paper sheds light in a poorly explored scientific area, that of the determinants of VAT gap, especially in relationship with financial and economic crime phenomena.
{"title":"The determinants of compliance VAT gap","authors":"I. Cuceu, Decebal-Remus Florescu, V. Văidean","doi":"10.1108/jrf-10-2023-0255","DOIUrl":"https://doi.org/10.1108/jrf-10-2023-0255","url":null,"abstract":"PurposeThis paper aims to analyze the potential variables explaining the compliance value added tax (VAT) gap, which basically represents an estimate of the unpaid VAT in the economy. A major component of compliance VAT Gap is represented by tax fraud; there exist other causes too, like insolvencies, bankruptcies, optimizations practices and maladministration. The objective of our paper is to revisit the main determinants of the VAT compliance gap for the European Union (EU)-27 member states. Using econometric modeling, our study identifies the relationship between the VAT gap and various determinants of it.Design/methodology/approachOur work focuses on the shadow economy, final consumption, VAT revenues, standard VAT rates, differences between the standard and reduced rates, economic prosperity, press freedom, political stability and others, as determinants of European VAT compliance gaps, for the 2005–2020 time interval. The methods include panel data analysis through simple and multiple regression modeling, the combinatorial approach, fixed and random effects.FindingsOur study validates the direct impact of shadow economy and the indirect impact of VAT revenues, economic prosperity and press freedom, upon VAT compliance gaps. Upon subsampling of EU member states within old and new ones, our results estimate a larger positive impact of shadow economy upon old member states, compared to new ones.Practical implicationsThe policy implications include leverage effects of governments acting upon a reduction in shadow economy phenomena and boosts of economic development, political stability and press freedom, in order to attain the contraction of compliance VAT gaps.Originality/valueOur paper sheds light in a poorly explored scientific area, that of the determinants of VAT gap, especially in relationship with financial and economic crime phenomena.","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.1108/jrf-06-2023-0133
E. Fedorova, Polina Iasakova
PurposeThis paper aims to investigate the impact of climate change news on the dynamics of US stock indices.Design/methodology/approachThe empirical basis of the study was 3,209 news articles. Sentiment analysis was performed by a pre-trained bidirectional FinBERT neural network. Thematic modeling is based on the neural network, BERTopic.FindingsThe results show that news sentiment can influence the dynamics of stock indices. In addition, five main news topics (finance and politics natural disasters and consequences industrial sector and Innovations activism and culture coronavirus pandemic) were identified, which showed a significant impact on the financial market.Originality/valueFirst, we extend the theoretical concepts. This study applies signaling theory and overreaction theory to the US stock market in the context of climate change. Second, in addition to the news sentiment, the impact of major news topics on US stock market returns is examined. Third, we examine the impact of sentimental and thematic news variables on US stock market indicators of economic sectors. Previous works reveal the impact of climate change news on specific sectors of the economy. This paper includes stock indices of the economic sectors most related to the topic of climate change. Fourth, the research methodology consists of modern algorithms. An advanced textual analysis method for sentiment classification is applied: a pre-trained bidirectional FinBERT neural network. Modern thematic modeling is carried out using a model based on the neural network, BERTopic. The most extensive topics are “finance and politics of climate change” and “natural disasters and consequences.”
{"title":"The impact of climate change news on the US stock market","authors":"E. Fedorova, Polina Iasakova","doi":"10.1108/jrf-06-2023-0133","DOIUrl":"https://doi.org/10.1108/jrf-06-2023-0133","url":null,"abstract":"PurposeThis paper aims to investigate the impact of climate change news on the dynamics of US stock indices.Design/methodology/approachThe empirical basis of the study was 3,209 news articles. Sentiment analysis was performed by a pre-trained bidirectional FinBERT neural network. Thematic modeling is based on the neural network, BERTopic.FindingsThe results show that news sentiment can influence the dynamics of stock indices. In addition, five main news topics (finance and politics natural disasters and consequences industrial sector and Innovations activism and culture coronavirus pandemic) were identified, which showed a significant impact on the financial market.Originality/valueFirst, we extend the theoretical concepts. This study applies signaling theory and overreaction theory to the US stock market in the context of climate change. Second, in addition to the news sentiment, the impact of major news topics on US stock market returns is examined. Third, we examine the impact of sentimental and thematic news variables on US stock market indicators of economic sectors. Previous works reveal the impact of climate change news on specific sectors of the economy. This paper includes stock indices of the economic sectors most related to the topic of climate change. Fourth, the research methodology consists of modern algorithms. An advanced textual analysis method for sentiment classification is applied: a pre-trained bidirectional FinBERT neural network. Modern thematic modeling is carried out using a model based on the neural network, BERTopic. The most extensive topics are “finance and politics of climate change” and “natural disasters and consequences.”","PeriodicalId":22869,"journal":{"name":"The Journal of Risk Finance","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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