This paper aims to document the impact of product market competition on the value of analyst coverage.
Design/methodology/approach
This paper uses variety of estimation techniques (panel regression as well as the quantile regression approaches) and the data for nonfinancial firms from India to document the impact of product market competition on the value of analyst coverage during the period between 2001 and 2018.
Findings
The findings show that the value of analyst coverage is an increasing function of product market competition. The authors argue that better information environment associated with firms operating in industries with high competition improves the quality of research done by analysts, thereby increasing the value of analyst coverage. The study results are consistent across different subsample and remain quantitatively the same when the authors use alternate estimation procedures.
Originality/value
The paper provides evidence regarding the role played by product market competition – a publicly available measure – on the value of research produced by analysts within the context of emerging markets.
{"title":"Does competition in product markets affect the value of analyst coverage? Evidence from an emerging market","authors":"Omar Farooq, Fatimazahra Bendriouch, Harit Satt, Saad Archane","doi":"10.1108/rbf-08-2021-0148","DOIUrl":"https://doi.org/10.1108/rbf-08-2021-0148","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This paper aims to document the impact of product market competition on the value of analyst coverage.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>This paper uses variety of estimation techniques (panel regression as well as the quantile regression approaches) and the data for nonfinancial firms from India to document the impact of product market competition on the value of analyst coverage during the period between 2001 and 2018.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The findings show that the value of analyst coverage is an increasing function of product market competition. The authors argue that better information environment associated with firms operating in industries with high competition improves the quality of research done by analysts, thereby increasing the value of analyst coverage. The study results are consistent across different subsample and remain quantitatively the same when the authors use alternate estimation procedures.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The paper provides evidence regarding the role played by product market competition – a publicly available measure – on the value of research produced by analysts within the context of emerging markets.</p><!--/ Abstract__block -->","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"8 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139084536","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 : 2022-01-10DOI: 10.1108/rbf-06-2021-0119
Ricky Cooper, W. Currie, J. Seddon, Ben Van Vliet
PurposeThis paper investigates the strategic behavior of algorithmic trading firms from an innovation economics perspective. The authors seek to uncover the sources of competitive advantage these firms develop to make markets inefficient for them and enable their survival.Design/methodology/approachFirst, the authors review expected capability, a quantitative behavioral model of the sustainable, or reliable, profits that lead to survival. Second, they present qualitative data gathered from semi-structured interviews with industry professionals as well as from the academic and industry literatures. They categorize this data into first-order concepts and themes of opportunity-, advantage- and meta-seeking behaviors. Associating the observed sources of competitive advantages with the components of the expected capability model allows us to describe the economic rationale these firms have for developing those sources and explain how they survive.FindingsThe data reveals ten sources of competitive advantages, which the authors label according to known ones in the strategic management literature. We find that, due to the dynamically complex environments and their bounded resources, these firms seek heuristic compromise among these ten, which leads to satisficing. Their application of innovation methodology that prescribes iterative ex post hypothesis testing appears to quell internal conflict among groups and promote organizational survival. The authors believe their results shed light on the behavior and motivations of algorithmic market actors, but also of innovative firms more generally.Originality/valueBased upon their review of the literature, this is the first paper to provide such a complete explanation of the strategic behavior of algorithmic trading firms.
{"title":"Competitive advantage in algorithmic trading: a behavioral innovation economics approach","authors":"Ricky Cooper, W. Currie, J. Seddon, Ben Van Vliet","doi":"10.1108/rbf-06-2021-0119","DOIUrl":"https://doi.org/10.1108/rbf-06-2021-0119","url":null,"abstract":"PurposeThis paper investigates the strategic behavior of algorithmic trading firms from an innovation economics perspective. The authors seek to uncover the sources of competitive advantage these firms develop to make markets inefficient for them and enable their survival.Design/methodology/approachFirst, the authors review expected capability, a quantitative behavioral model of the sustainable, or reliable, profits that lead to survival. Second, they present qualitative data gathered from semi-structured interviews with industry professionals as well as from the academic and industry literatures. They categorize this data into first-order concepts and themes of opportunity-, advantage- and meta-seeking behaviors. Associating the observed sources of competitive advantages with the components of the expected capability model allows us to describe the economic rationale these firms have for developing those sources and explain how they survive.FindingsThe data reveals ten sources of competitive advantages, which the authors label according to known ones in the strategic management literature. We find that, due to the dynamically complex environments and their bounded resources, these firms seek heuristic compromise among these ten, which leads to satisficing. Their application of innovation methodology that prescribes iterative ex post hypothesis testing appears to quell internal conflict among groups and promote organizational survival. The authors believe their results shed light on the behavior and motivations of algorithmic market actors, but also of innovative firms more generally.Originality/valueBased upon their review of the literature, this is the first paper to provide such a complete explanation of the strategic behavior of algorithmic trading firms.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"52 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79537557","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 : 2022-01-07DOI: 10.1108/rbf-05-2021-0088
Todd Feldman, Shuming Liu
Purpose
The author proposes an update to the mean variance (MV) framework that replaces a constant risk aversion parameter using a dynamic risk aversion indicator. The contribution to the literature is made through making the static risk aversion parameter operational using an indicator of market sentiment. Results suggest that Sharpe ratios improve when the author replaces the traditional risk aversion parameter with a dynamic sentiment indicator from the behavioral finance literature when allocating between a risky portfolio and a risk-free asset. However, results are mixed when using the behavioral framework to allocate between two risky assets.
Design/methodology/approach
The author includes a dynamic risk aversion parameter in the mean variance framework and back test using the traditional and updated behavioral mean variance (BMV) framework to see which framework leads to better performance.
Findings
The author finds that the behavioral framework provides superior performance when allocating between a risky and risk-free asset; however, it under performs when allocating between risky assets.
Research limitations/implications
The research is based on back testing; therefore, it cannot be concluded that this strategy will perform well in real-time circumstances.
Practical implications
Portfolio managers may use this strategy to optimize the allocation between a risky portfolio and a risk-free asset.
Social implications
An improved allocation between risk-free and risky assets that could lead to less leverage in the market.
Originality/value
The study is the first to use such a sentiment indicator in the traditional MV framework and show the math.
{"title":"A new behavioral finance mean variance framework","authors":"Todd Feldman, Shuming Liu","doi":"10.1108/rbf-05-2021-0088","DOIUrl":"https://doi.org/10.1108/rbf-05-2021-0088","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>The author proposes an update to the mean variance (MV) framework that replaces a constant risk aversion parameter using a dynamic risk aversion indicator. The contribution to the literature is made through making the static risk aversion parameter operational using an indicator of market sentiment. Results suggest that Sharpe ratios improve when the author replaces the traditional risk aversion parameter with a dynamic sentiment indicator from the behavioral finance literature when allocating between a risky portfolio and a risk-free asset. However, results are mixed when using the behavioral framework to allocate between two risky assets.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The author includes a dynamic risk aversion parameter in the mean variance framework and back test using the traditional and updated behavioral mean variance (BMV) framework to see which framework leads to better performance.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The author finds that the behavioral framework provides superior performance when allocating between a risky and risk-free asset; however, it under performs when allocating between risky assets.</p><!--/ Abstract__block -->\u0000<h3>Research limitations/implications</h3>\u0000<p>The research is based on back testing; therefore, it cannot be concluded that this strategy will perform well in real-time circumstances.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>Portfolio managers may use this strategy to optimize the allocation between a risky portfolio and a risk-free asset.</p><!--/ Abstract__block -->\u0000<h3>Social implications</h3>\u0000<p>An improved allocation between risk-free and risky assets that could lead to less leverage in the market.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The study is the first to use such a sentiment indicator in the traditional MV framework and show the math.</p><!--/ Abstract__block -->","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"103 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139084098","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 : 2022-01-04DOI: 10.1108/rbf-10-2021-0211
Chaiyuth Padungsaksawasdi, Sirimon Treepongkaruna, P. Jiraporn
PurposeThe paper aims to investigate the effect of uncertain times on LGBT-supportive corporate policies, exploiting a novel text-based measure of economic policy uncertainty (EPU) that was recently constructed by Baker et al. (2016). LGBT-supportive policies have attracted a great deal of attention in the media lately. There is also a rapidly growing area of the literature that addresses LGBT-supportive policies specifically.Design/methodology/approachThe authors execute a regression analysis and several other robustness checks including propensity score matching (PSM) and an instrumental-variable analysis to mitigate endogeneity.FindingsThe authors' results show that companies significantly raise their investments in LGBT-supportive policies in times of greater uncertainty, reinforcing the risk mitigation view where LGBT-supportive policies create moral capital with an insurance-like effect that mitigates adverse consequences during uncertain times. The effect of EPU on LGBT-supportive policies is above and beyond its effect on corporate social responsibility (CSR) in general.Originality/valueThe authors' study is the first to explore the effect of uncertain times on LGBT-supportive corporate policies. The authors contribute to a crucial area of the literature that examines how firms respond to EPU. In addition, the authors enrich the literature on LGBT-friendly policies by showing that EPU is one of the significant determinants of LGBT-friendly policies.
{"title":"LGBT-supportive corporate policies, risk aversion and mitigation and economic policy uncertainty","authors":"Chaiyuth Padungsaksawasdi, Sirimon Treepongkaruna, P. Jiraporn","doi":"10.1108/rbf-10-2021-0211","DOIUrl":"https://doi.org/10.1108/rbf-10-2021-0211","url":null,"abstract":"PurposeThe paper aims to investigate the effect of uncertain times on LGBT-supportive corporate policies, exploiting a novel text-based measure of economic policy uncertainty (EPU) that was recently constructed by Baker et al. (2016). LGBT-supportive policies have attracted a great deal of attention in the media lately. There is also a rapidly growing area of the literature that addresses LGBT-supportive policies specifically.Design/methodology/approachThe authors execute a regression analysis and several other robustness checks including propensity score matching (PSM) and an instrumental-variable analysis to mitigate endogeneity.FindingsThe authors' results show that companies significantly raise their investments in LGBT-supportive policies in times of greater uncertainty, reinforcing the risk mitigation view where LGBT-supportive policies create moral capital with an insurance-like effect that mitigates adverse consequences during uncertain times. The effect of EPU on LGBT-supportive policies is above and beyond its effect on corporate social responsibility (CSR) in general.Originality/valueThe authors' study is the first to explore the effect of uncertain times on LGBT-supportive corporate policies. The authors contribute to a crucial area of the literature that examines how firms respond to EPU. In addition, the authors enrich the literature on LGBT-friendly policies by showing that EPU is one of the significant determinants of LGBT-friendly policies.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"1 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76706091","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 : 2021-12-29DOI: 10.1108/rbf-08-2021-0150
E. M. Guerra-Leal, F. Arredondo-Trapero, José Carlos Vázquez-Parra
PurposeTo analyze financial inclusion through digital banking in order to identify how digital banking is including or excluding different types of populations in an emergent economy.Design/methodology/approachChi-square statistical tests were conducted to test the relationship between demographic variables (i.e. gender, region, locality and age) with having a digital banking account, types of services and reasons for not using them. As an example of an emergent economy, the Mexican Financial Inclusion Survey database was used, which includes stratified and clustered sampling.FindingsHaving a bank account with digital banking is related to gender. Women are more excluded than men, demonstrating a gender gap in access to digital banking accounts. Moreover, having a bank account with digital banking depends on the region. In regions where digital banking is more developed, the population uses a wide variety of digital banking services, in contrast to less developed regions. About the size of the locality, the lack of financial inclusion via digital banking is more common in rural contexts or small cities, demonstrating the exclusion of this type of population.Research limitations/implicationsThis study is conducted with data from the latest Mexican Financial Inclusion Survey. Since the National Institute of Statistics and Geography (NISG) in Mexico previously conducted the study for exploratory purposes, it was not possible for the researchers to modify the variables.Practical implicationsThe results might be considered on similar emergent economies to promote financial inclusion of vulnerable groups such as women, people living in underdeveloped regions, rural areas, small cities and elders. These findings may provide criteria for both government agencies and banking institutions to make efforts focused on including these population groups that have not been financially included through digital banking.Originality/valueIdentifying the barriers that affect financial inclusion, such as gender, region, size of the city and age can help to guide efforts to achieve greater economic freedom and quality of life for diverse types of populations. Although the study is carried out in an emerging economy, the results can also shed light on how to address these forms of exclusion that occur in different types of economies. It is understood that the lack of financial inclusion is a limitation to the economic freedom and quality of life to which everyone should have access, hence the relevance of the article.
{"title":"Financial inclusion and digital banking on an emergent economy","authors":"E. M. Guerra-Leal, F. Arredondo-Trapero, José Carlos Vázquez-Parra","doi":"10.1108/rbf-08-2021-0150","DOIUrl":"https://doi.org/10.1108/rbf-08-2021-0150","url":null,"abstract":"PurposeTo analyze financial inclusion through digital banking in order to identify how digital banking is including or excluding different types of populations in an emergent economy.Design/methodology/approachChi-square statistical tests were conducted to test the relationship between demographic variables (i.e. gender, region, locality and age) with having a digital banking account, types of services and reasons for not using them. As an example of an emergent economy, the Mexican Financial Inclusion Survey database was used, which includes stratified and clustered sampling.FindingsHaving a bank account with digital banking is related to gender. Women are more excluded than men, demonstrating a gender gap in access to digital banking accounts. Moreover, having a bank account with digital banking depends on the region. In regions where digital banking is more developed, the population uses a wide variety of digital banking services, in contrast to less developed regions. About the size of the locality, the lack of financial inclusion via digital banking is more common in rural contexts or small cities, demonstrating the exclusion of this type of population.Research limitations/implicationsThis study is conducted with data from the latest Mexican Financial Inclusion Survey. Since the National Institute of Statistics and Geography (NISG) in Mexico previously conducted the study for exploratory purposes, it was not possible for the researchers to modify the variables.Practical implicationsThe results might be considered on similar emergent economies to promote financial inclusion of vulnerable groups such as women, people living in underdeveloped regions, rural areas, small cities and elders. These findings may provide criteria for both government agencies and banking institutions to make efforts focused on including these population groups that have not been financially included through digital banking.Originality/valueIdentifying the barriers that affect financial inclusion, such as gender, region, size of the city and age can help to guide efforts to achieve greater economic freedom and quality of life for diverse types of populations. Although the study is carried out in an emerging economy, the results can also shed light on how to address these forms of exclusion that occur in different types of economies. It is understood that the lack of financial inclusion is a limitation to the economic freedom and quality of life to which everyone should have access, hence the relevance of the article.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"23 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78195480","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 : 2021-12-17DOI: 10.1108/rbf-09-2021-0191
J. Brodmann, Phuvadon Wuthisatian, Rama K. Malladi
PurposeThe purpose of the paper is to analyze socially responsible investment (SRI) asset performance compared to traditional assets using the MSCI KLD 400 Index. The authors examine the required return that investors expect to maintain their holdings in SRI stock and whether SRI stocks can be used for diversification during financial crises.Design/methodology/approachThe authors examine SRI stocks' liquidity from the MSCI KLD 400 index, encompassing all environmental, social and governance (ESG) factor investments over 25 years, from 1990 until 2019. The authors test whether sorting portfolios based on their excess return, liquidity and volatility can explain the difference in SRI and non-SRI stocks' returns and then examine the global financial crisis' (GFC) impact on excess returns for SRI and non-SRI assets.FindingsThe authors find a significant difference in liquidity and volatility between SRI and non-SRI stocks and that SRI stocks perform better during financial crises. The results suggest a possible general investor preference to invest in non-SRI stocks despite our findings that SRI stocks tend to withstand financial risk better than non-SRI stocks. The authors find that long-term investors may be willing to forego short-term gains to reduce their overall risk exposure during crises.Originality/valueSRI is gaining international popularity as an alternative investment that includes ratings based on ESG factors. Previous studies provide mixed results of whether SRI stocks outperform conventional stocks. In addition, there is limited research examining the liquidity and volatility of SRI assets. The authors compare the differences between SRI and non-SRI stocks in terms of excess return, volatility and liquidity and compare the liquidity of SRI and non-SRI stocks during the financial crisis.
{"title":"The liquidity, performance and investor preference of socially responsible investments","authors":"J. Brodmann, Phuvadon Wuthisatian, Rama K. Malladi","doi":"10.1108/rbf-09-2021-0191","DOIUrl":"https://doi.org/10.1108/rbf-09-2021-0191","url":null,"abstract":"PurposeThe purpose of the paper is to analyze socially responsible investment (SRI) asset performance compared to traditional assets using the MSCI KLD 400 Index. The authors examine the required return that investors expect to maintain their holdings in SRI stock and whether SRI stocks can be used for diversification during financial crises.Design/methodology/approachThe authors examine SRI stocks' liquidity from the MSCI KLD 400 index, encompassing all environmental, social and governance (ESG) factor investments over 25 years, from 1990 until 2019. The authors test whether sorting portfolios based on their excess return, liquidity and volatility can explain the difference in SRI and non-SRI stocks' returns and then examine the global financial crisis' (GFC) impact on excess returns for SRI and non-SRI assets.FindingsThe authors find a significant difference in liquidity and volatility between SRI and non-SRI stocks and that SRI stocks perform better during financial crises. The results suggest a possible general investor preference to invest in non-SRI stocks despite our findings that SRI stocks tend to withstand financial risk better than non-SRI stocks. The authors find that long-term investors may be willing to forego short-term gains to reduce their overall risk exposure during crises.Originality/valueSRI is gaining international popularity as an alternative investment that includes ratings based on ESG factors. Previous studies provide mixed results of whether SRI stocks outperform conventional stocks. In addition, there is limited research examining the liquidity and volatility of SRI assets. The authors compare the differences between SRI and non-SRI stocks in terms of excess return, volatility and liquidity and compare the liquidity of SRI and non-SRI stocks during the financial crisis.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"63 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78819700","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 : 2021-12-01DOI: 10.1108/rbf-03-2021-0051
Akanksha Goel, Shailesh Rastogi
PurposeThe purpose of the study is to identify certain behavioural and psychological traits of the borrowers which have the tendency to predict the credit risk of the borrowers. And the second objective is to draw a conceptual model that reveals the impact of those traits on credit default.Design/methodology/approachThe study has adopted a systematic Literature Review approach to identify those behavioural and psychological traits of borrowers that reflect on the tendency to predict the credit default of borrowers.FindingsThe findings of this study have revealed that there are some non-financial factors, which can be looked into while granting a loan to a borrower. The identified factors can be used to develop a subjective credit scoring model that can quantify and verify the soft information (character and reliability) of debtors. Further, a behavioural credit scoring model will help in easing the assessment of those borrowers, who do not have an appropriate credit history and reliable financial statements.Practical implicationsThe proposed model would help banks and financial institutions to evaluate those borrowers who lack substantial financial information. Further, a subjective credit scoring model would help to evaluate the credit worthiness of such borrowers who do not have any credit history. The model would also reduce the biasness of subjective scoring and would reduce the financial constraints of borrowers.Originality/valueBy reviewing the literature, it has been observed that there are very few studies that have exclusively considered the behavioural and psychological factors in credit scoring. Several studies have linked the psychological constructs with debts, but very few researchers have considered it while constructing a behavioural scoring model. Thus, it can be inferred that this area of behavioural finance is still unexplored and needs attention of researchers worldwide. In addition, most of the studies are carried out in European, African and American regions but are almost non-existent in the Asian markets.
{"title":"Understanding the impact of borrowers' behavioural and psychological traits on credit default: review and conceptual model","authors":"Akanksha Goel, Shailesh Rastogi","doi":"10.1108/rbf-03-2021-0051","DOIUrl":"https://doi.org/10.1108/rbf-03-2021-0051","url":null,"abstract":"PurposeThe purpose of the study is to identify certain behavioural and psychological traits of the borrowers which have the tendency to predict the credit risk of the borrowers. And the second objective is to draw a conceptual model that reveals the impact of those traits on credit default.Design/methodology/approachThe study has adopted a systematic Literature Review approach to identify those behavioural and psychological traits of borrowers that reflect on the tendency to predict the credit default of borrowers.FindingsThe findings of this study have revealed that there are some non-financial factors, which can be looked into while granting a loan to a borrower. The identified factors can be used to develop a subjective credit scoring model that can quantify and verify the soft information (character and reliability) of debtors. Further, a behavioural credit scoring model will help in easing the assessment of those borrowers, who do not have an appropriate credit history and reliable financial statements.Practical implicationsThe proposed model would help banks and financial institutions to evaluate those borrowers who lack substantial financial information. Further, a subjective credit scoring model would help to evaluate the credit worthiness of such borrowers who do not have any credit history. The model would also reduce the biasness of subjective scoring and would reduce the financial constraints of borrowers.Originality/valueBy reviewing the literature, it has been observed that there are very few studies that have exclusively considered the behavioural and psychological factors in credit scoring. Several studies have linked the psychological constructs with debts, but very few researchers have considered it while constructing a behavioural scoring model. Thus, it can be inferred that this area of behavioural finance is still unexplored and needs attention of researchers worldwide. In addition, most of the studies are carried out in European, African and American regions but are almost non-existent in the Asian markets.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"7 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75186673","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}
PurposeThis study aims to examine the relationship between pandemic sentiment (PS) and stock market returns in an emerging order-driven stock market like India.Design/methodology/approachThis study uses nonlinear causality and wavelet coherence techniques to analyze the sentiment-returns nexus. The analysis is conducted on the full sample period from January to December 2020 and further extended to two subperiods from January to June and July to December to investigate whether the associations between sentiment and market returns persist even several months after the outbreak.FindingsThis study constructs two novel measures of PS: one using Google Search Volume Intensity and the other using Textual Analysis of newspaper headlines. The empirical findings suggest a high degree of interrelationship between PS and stock returns in all time-frequency domains across the full sample period. This interrelationship is found to be further heightened during the initial months of the crisis but reduces significantly during the later months. This could be because a considerable amount of uncertainty regarding the crisis is already accounted for and priced into the markets in the initial months.Originality/valueThe ongoing coronavirus pandemic has resulted in sharp volatility and frequent crashes in the global equity indices. This study is an endeavor to shed light on the ongoing debate on the COVID-19 pandemic, investors’ sentiment and stock market behavior.
{"title":"COVID-19 pandemic sentiment and stock market behavior: evidence from an emerging market","authors":"Byomakesh Debata, Kshitish Ghate, Jayashree Renganathan","doi":"10.1108/rbf-05-2021-0083","DOIUrl":"https://doi.org/10.1108/rbf-05-2021-0083","url":null,"abstract":"PurposeThis study aims to examine the relationship between pandemic sentiment (PS) and stock market returns in an emerging order-driven stock market like India.Design/methodology/approachThis study uses nonlinear causality and wavelet coherence techniques to analyze the sentiment-returns nexus. The analysis is conducted on the full sample period from January to December 2020 and further extended to two subperiods from January to June and July to December to investigate whether the associations between sentiment and market returns persist even several months after the outbreak.FindingsThis study constructs two novel measures of PS: one using Google Search Volume Intensity and the other using Textual Analysis of newspaper headlines. The empirical findings suggest a high degree of interrelationship between PS and stock returns in all time-frequency domains across the full sample period. This interrelationship is found to be further heightened during the initial months of the crisis but reduces significantly during the later months. This could be because a considerable amount of uncertainty regarding the crisis is already accounted for and priced into the markets in the initial months.Originality/valueThe ongoing coronavirus pandemic has resulted in sharp volatility and frequent crashes in the global equity indices. This study is an endeavor to shed light on the ongoing debate on the COVID-19 pandemic, investors’ sentiment and stock market behavior.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"23 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83539873","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 : 2021-11-19DOI: 10.1108/rbf-05-2021-0092
Kamran Quddus, Ashok Banerjee
PurposeThrough a portfolio choice model, the study empirically examines the influence of the heuristic simplification through peak-end rule (PER) and the associated neglect of the duration of the experience. The portfolio strategy adopted involves optimizing portfolios to capture the impact of heuristic-driven investors' experience of good and bad states. The study attempts to validate PER in an empirical context and is expected to generate trading rules, which would exploit pricing errors emerging out of the use of heuristics by investors.Design/methodology/approachThe empirical approach adopted in the study primarily examines returns to portfolios sorted according to various hedonic evaluation rules. Behavioral portfolios are constructed using hedonic experiences as conditioning variables.FindingsThe results imply that there is continued investor demand for such assets in the short run. An equal weight portfolio based on a three-month hedonic evaluation earns an average monthly return of 2.77% over the next 12 months.Originality/valueThe authors’ study may perhaps be the first attempt to use the peak-end heuristic in portfolio construction.
{"title":"Understanding heuristics-based financial decision-making using behavioral portfolio strategies","authors":"Kamran Quddus, Ashok Banerjee","doi":"10.1108/rbf-05-2021-0092","DOIUrl":"https://doi.org/10.1108/rbf-05-2021-0092","url":null,"abstract":"PurposeThrough a portfolio choice model, the study empirically examines the influence of the heuristic simplification through peak-end rule (PER) and the associated neglect of the duration of the experience. The portfolio strategy adopted involves optimizing portfolios to capture the impact of heuristic-driven investors' experience of good and bad states. The study attempts to validate PER in an empirical context and is expected to generate trading rules, which would exploit pricing errors emerging out of the use of heuristics by investors.Design/methodology/approachThe empirical approach adopted in the study primarily examines returns to portfolios sorted according to various hedonic evaluation rules. Behavioral portfolios are constructed using hedonic experiences as conditioning variables.FindingsThe results imply that there is continued investor demand for such assets in the short run. An equal weight portfolio based on a three-month hedonic evaluation earns an average monthly return of 2.77% over the next 12 months.Originality/valueThe authors’ study may perhaps be the first attempt to use the peak-end heuristic in portfolio construction.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"1 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83750067","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 : 2021-11-15DOI: 10.1108/rbf-04-2020-0077
Metin Argan, Guven Sevil, Abdullah Yalaman, Viktor Manahov
PurposeThe purpose of the research is to gain an understanding about how stock market investors impact various behavioural personality traits in various consumer groups with differing levels of motivation and capacity to absorb emerging stock market data.Design/methodology/approachThe research has used structural equation modelling (SEM) to test the validity of the theoretical model.FindingsThe current paper is the first study that uses stock market data from an emerging economy to examine the relationship between stock market investment and different behavioural patterns such as stock market attachment, trust, satisfaction and loyalty. The authors observe the presence of direct positive relationships between stock market investment and different behavioural personality traits. Moreover, the authors also observe that stock market attachment can be seen as an intermediary variable between stock investment involvement and satisfaction. The empirical findings also suggest the presence of indirect relationships between stock investment involvement and satisfaction and between stock market attachment and loyalty. The authors find that the indirect relationship between stock market attachment and loyalty occurs when the level of satisfaction is higher. Therefore, satisfaction appears to facilitate the relationship between stock market attachment and loyalty.Research limitations/implicationsOne major limitation of the study is data availability. More specifically, the study was conducted with customers of eight different banks in the province of Eskisehir, Turkey. From the 250 questionnaires distributed, 173 were returned, yielding a response rate of 69.2%.Practical implicationsBy identifying the trait characteristics of segments of stock market participants relative to their propensity to invest in stocks, it is possible to tailor messages that influence people to invest for the long term.Originality/valueThe paper deploys stock market data from an emerging economy to investigate the relationship between stock market investment and different surface traits such as stock market attachment, trust, satisfaction and loyalty. To the best of the authors' knowledge the current paper is the first such study.
{"title":"Stock market investment and different behavioural patterns: an exploratory study","authors":"Metin Argan, Guven Sevil, Abdullah Yalaman, Viktor Manahov","doi":"10.1108/rbf-04-2020-0077","DOIUrl":"https://doi.org/10.1108/rbf-04-2020-0077","url":null,"abstract":"PurposeThe purpose of the research is to gain an understanding about how stock market investors impact various behavioural personality traits in various consumer groups with differing levels of motivation and capacity to absorb emerging stock market data.Design/methodology/approachThe research has used structural equation modelling (SEM) to test the validity of the theoretical model.FindingsThe current paper is the first study that uses stock market data from an emerging economy to examine the relationship between stock market investment and different behavioural patterns such as stock market attachment, trust, satisfaction and loyalty. The authors observe the presence of direct positive relationships between stock market investment and different behavioural personality traits. Moreover, the authors also observe that stock market attachment can be seen as an intermediary variable between stock investment involvement and satisfaction. The empirical findings also suggest the presence of indirect relationships between stock investment involvement and satisfaction and between stock market attachment and loyalty. The authors find that the indirect relationship between stock market attachment and loyalty occurs when the level of satisfaction is higher. Therefore, satisfaction appears to facilitate the relationship between stock market attachment and loyalty.Research limitations/implicationsOne major limitation of the study is data availability. More specifically, the study was conducted with customers of eight different banks in the province of Eskisehir, Turkey. From the 250 questionnaires distributed, 173 were returned, yielding a response rate of 69.2%.Practical implicationsBy identifying the trait characteristics of segments of stock market participants relative to their propensity to invest in stocks, it is possible to tailor messages that influence people to invest for the long term.Originality/valueThe paper deploys stock market data from an emerging economy to investigate the relationship between stock market investment and different surface traits such as stock market attachment, trust, satisfaction and loyalty. To the best of the authors' knowledge the current paper is the first such study.","PeriodicalId":44559,"journal":{"name":"Review of Behavioral Finance","volume":"40 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89713998","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号