Using quarterly data from 2019Q1 to 2020Q3, this study aims to examine the impact of COVID-19 on intellectual capital (IC) performance of banks operating in China and Pakistan. Based on the data of 34 Chinese and 41 Pakistani banks, this study applies the fixed effect method to examine this relationship, and the value added intellectual coefficient (VAIC) model is used to measure IC performance. The study shows a negative but insignificant influence of COVID-19 on IC performance of the banking sector in both countries. Likewise, the findings exhibit that IC components show resilience against COVID-19 and are slightly influenced by this crisis. The results are also consistent in robustness check. The cross-country comparison suggests that the performance of IC components in the Pakistani banking sector is higher compared to China. This is the first study that examines the impact of COVID-19 on IC performance of banks, and it might provide insights regarding the influence of crises such as COVID-19 on IC performance of banks in emerging economies.
{"title":"Assessing intellectual capital performance of banks during COVID-19: Evidence from China and Pakistan","authors":"Jian Xu, M. Haris, M. Irfan","doi":"10.3934/qfe.2023017","DOIUrl":"https://doi.org/10.3934/qfe.2023017","url":null,"abstract":"Using quarterly data from 2019Q1 to 2020Q3, this study aims to examine the impact of COVID-19 on intellectual capital (IC) performance of banks operating in China and Pakistan. Based on the data of 34 Chinese and 41 Pakistani banks, this study applies the fixed effect method to examine this relationship, and the value added intellectual coefficient (VAIC) model is used to measure IC performance. The study shows a negative but insignificant influence of COVID-19 on IC performance of the banking sector in both countries. Likewise, the findings exhibit that IC components show resilience against COVID-19 and are slightly influenced by this crisis. The results are also consistent in robustness check. The cross-country comparison suggests that the performance of IC components in the Pakistani banking sector is higher compared to China. This is the first study that examines the impact of COVID-19 on IC performance of banks, and it might provide insights regarding the influence of crises such as COVID-19 on IC performance of banks in emerging economies.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231783","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}
A. Mabrouk, Sabrine Arfaoui, Mohamed Essaied Hamrita
Systematic risk is one of the well-known indices involved in the market situation study. One of the disadvantages of scientific studies of market indices is the lack of involving extreme changes such as embargos and other crises in the model. The present paper attempts to study the impact of the embargo on systematic risk using wavelets as a mathematical-statistical tool. The proposed mathematical model was applied to the case of the Golf Council Countries (GCC) market, with the Qatar case as an example of an embargoed country. The time series applied corresponds to the Qatar stock exchange index active trade over the period January 01, 2017, to December 31, 2021, which was characterized by the main GCC embargo period against Qatar. The findings in the present work permit understanding the impact of such a crisis on the market and allow a good description of the behavior of the market during the embargo, which makes a good basis for managers, policymakers, and investors.
{"title":"Wavelet-based systematic risk estimation for GCC stock markets and impact of the embargo on the Qatar case","authors":"A. Mabrouk, Sabrine Arfaoui, Mohamed Essaied Hamrita","doi":"10.3934/qfe.2023015","DOIUrl":"https://doi.org/10.3934/qfe.2023015","url":null,"abstract":"Systematic risk is one of the well-known indices involved in the market situation study. One of the disadvantages of scientific studies of market indices is the lack of involving extreme changes such as embargos and other crises in the model. The present paper attempts to study the impact of the embargo on systematic risk using wavelets as a mathematical-statistical tool. The proposed mathematical model was applied to the case of the Golf Council Countries (GCC) market, with the Qatar case as an example of an embargoed country. The time series applied corresponds to the Qatar stock exchange index active trade over the period January 01, 2017, to December 31, 2021, which was characterized by the main GCC embargo period against Qatar. The findings in the present work permit understanding the impact of such a crisis on the market and allow a good description of the behavior of the market during the embargo, which makes a good basis for managers, policymakers, and investors.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231206","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}
Given the competitiveness of a market-making environment, the ability to speedily quote option prices consistent with an ever-changing market environment is essential. Thus, the smallest acceleration or improvement over traditional pricing methods is crucial to avoid arbitrage. We propose a method for accelerating the pricing of American options to near-instantaneous using a feed-forward neural network. This neural network is trained over the chosen (e.g., Heston) stochastic volatility specification. Such an approach facilitates parameter interpretability, as generally required by the regulators, and establishes our method in the area of eXplainable Artificial Intelligence (XAI) for finance. We show that the proposed deep explainable pricer induces a speed-accuracy trade-off compared to the typical Monte Carlo or Partial Differential Equation-based pricing methods. Moreover, the proposed approach allows for pricing derivatives with path-dependent and more complex payoffs and is, given the sufficient accuracy of computation and its tractable nature, applicable in a market-making environment.
{"title":"Accelerated American option pricing with deep neural networks","authors":"David Anderson, Urban Ulrych","doi":"10.3934/qfe.2023011","DOIUrl":"https://doi.org/10.3934/qfe.2023011","url":null,"abstract":"Given the competitiveness of a market-making environment, the ability to speedily quote option prices consistent with an ever-changing market environment is essential. Thus, the smallest acceleration or improvement over traditional pricing methods is crucial to avoid arbitrage. We propose a method for accelerating the pricing of American options to near-instantaneous using a feed-forward neural network. This neural network is trained over the chosen (e.g., Heston) stochastic volatility specification. Such an approach facilitates parameter interpretability, as generally required by the regulators, and establishes our method in the area of eXplainable Artificial Intelligence (XAI) for finance. We show that the proposed deep explainable pricer induces a speed-accuracy trade-off compared to the typical Monte Carlo or Partial Differential Equation-based pricing methods. Moreover, the proposed approach allows for pricing derivatives with path-dependent and more complex payoffs and is, given the sufficient accuracy of computation and its tractable nature, applicable in a market-making environment.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231461","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}
This study aimed to investigate the risk-return relationship, provided volatility feedback was taken into account, in the South African market. Volatility feedback, a stronger measure of volatility, was treated as an important source of asymmetry in the investigation of the risk-return relationship. This study analyzed the JSE ALSI excess returns and realized variance for the sample period from 15 October 2009 to 15 October 2019. This study modelled the novel and robust Bayesian approach in a parametric and nonparametric framework. A parametric model has modelling assumptions, such as normality, and a finite sample space. A nonparametric approach relaxes modelling assumptions and allows for an infinite sample space; thus, taking into account every possible asymmetric risk-return relationship. Given that South Africa is an emerging market, which is subject to higher levels of volatility, the presence of volatility feedback was expected to be more pronounced. However, contrary to expectations, the test results from both the parametric and nonparametric Bayesian model showed that volatility feedback had an insignificant effect in the South African market. The risk-return relationship was then investigated free from empirical distortions that resulted from volatility feedback. The parametric Bayesian model found a positive risk-return relationship, in line with traditional theoretical expectations. However, the nonparametric Bayesian model found no relationship between risk and return, in line with early South African studies. Since the nonparametric Bayesian approach is more robust than the parametric Bayesian approach, this study concluded that there is no risk-return relationship. Therefore, investors can include South Africa in their investment portfolio with higher risk countries in order to spread their risk and derive diversification benefits. In addition, risk averse investors can find a safe environment within the South African market and earn a return in accordance to their risk tolerance.
{"title":"The risk-return relationship and volatility feedback in South Africa: a comparative analysis of the parametric and nonparametric Bayesian approach","authors":"Nitesha Dwarika","doi":"10.3934/qfe.2023007","DOIUrl":"https://doi.org/10.3934/qfe.2023007","url":null,"abstract":"This study aimed to investigate the risk-return relationship, provided volatility feedback was taken into account, in the South African market. Volatility feedback, a stronger measure of volatility, was treated as an important source of asymmetry in the investigation of the risk-return relationship. This study analyzed the JSE ALSI excess returns and realized variance for the sample period from 15 October 2009 to 15 October 2019. This study modelled the novel and robust Bayesian approach in a parametric and nonparametric framework. A parametric model has modelling assumptions, such as normality, and a finite sample space. A nonparametric approach relaxes modelling assumptions and allows for an infinite sample space; thus, taking into account every possible asymmetric risk-return relationship. Given that South Africa is an emerging market, which is subject to higher levels of volatility, the presence of volatility feedback was expected to be more pronounced. However, contrary to expectations, the test results from both the parametric and nonparametric Bayesian model showed that volatility feedback had an insignificant effect in the South African market. The risk-return relationship was then investigated free from empirical distortions that resulted from volatility feedback. The parametric Bayesian model found a positive risk-return relationship, in line with traditional theoretical expectations. However, the nonparametric Bayesian model found no relationship between risk and return, in line with early South African studies. Since the nonparametric Bayesian approach is more robust than the parametric Bayesian approach, this study concluded that there is no risk-return relationship. Therefore, investors can include South Africa in their investment portfolio with higher risk countries in order to spread their risk and derive diversification benefits. In addition, risk averse investors can find a safe environment within the South African market and earn a return in accordance to their risk tolerance.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231495","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}
Ayodele Idowu, Obaika M. Ohikhuare, Munem Ahmad Chowdhury
This study investigated the effect of Industrialization on carbon emissions through energy consumption for a panel of eight Organization of the Petroleum Exporting Countries (OPEC) and nine High Industrialised Countries over the period 1985 to 2020; the study employs the first generation and second-generation Unit root tests. The study further adopts the use of the Panel Autoregressive Distributed Lag Model, and Common Correlated Effect pooled mean group to estimate the parameters of the model for OPEC countries and High Industrialised Countries, respectively. In addition, the Dumitrescu-Hurlin Granger causality test is conducted to infer the direction of causality among the variables. The causality test result reveals that, in OPEC, energy consumed during industrial activity is not enough to cause carbon emission and carbon emission does not cause industrialisation to interact with energy consumption. Also, for highly industrialised countries, interaction of energy consumption and industrialization causes carbon emission, but carbon emission does not cause the interaction of energy consumption and industrialization. The estimated model shows that the interactive effect of Industrialization and energy consumption has no significant influence on carbon emissions in OPEC countries in the short and long run. In contrast, foreign direct investment and economic growth have a positive and significant effect on carbon emissions in the short run. However, for highly industrialised countries the study found that the interactive effect of energy industrialization and energy consumption has a positive and significant effect on carbon emissions in the short run. It is apparent from the study that energy consumption for industrial activities, particularly in highly industrialised countries, causes carbon emission and such policy makers should formulate policy that necessitate the use of green energy for industrial activities to improve environmental quality.
本研究调查了工业化对碳排放的影响，通过能源消费的八个石油输出国组织(欧佩克)和九个高工业化国家的小组在1985年至2020年期间;本研究采用第一代和第二代单位根检验。本研究进一步采用Panel Autoregressive Distributed Lag Model和Common correlation Effect pooled mean group分别对OPEC国家和高工业化国家的模型参数进行估计。此外，通过dumitrescui - hurlin Granger因果检验来推断变量之间的因果关系方向。因果关系检验结果表明，在欧佩克国家，工业活动中消耗的能源不足以引起碳排放，碳排放不会导致工业化与能源消耗相互作用。同样，对于高度工业化的国家，能源消费与工业化的相互作用导致了碳排放，但碳排放并没有导致能源消费与工业化的相互作用。估算模型表明，工业化和能源消费的交互效应在短期和长期对欧佩克国家的碳排放没有显著影响。相比之下，外国直接投资和经济增长在短期内对碳排放有显著的正向影响。然而，对于高度工业化的国家，研究发现能源工业化和能源消费的交互效应在短期内对碳排放具有显著的正向影响。从研究中可以明显看出，工业活动的能源消耗，特别是在高度工业化的国家，导致碳排放，这些决策者应该制定政策，使工业活动必须使用绿色能源，以改善环境质量。
{"title":"Does industrialization trigger carbon emissions through energy consumption? Evidence from OPEC countries and high industrialised countries","authors":"Ayodele Idowu, Obaika M. Ohikhuare, Munem Ahmad Chowdhury","doi":"10.3934/qfe.2023009","DOIUrl":"https://doi.org/10.3934/qfe.2023009","url":null,"abstract":"This study investigated the effect of Industrialization on carbon emissions through energy consumption for a panel of eight Organization of the Petroleum Exporting Countries (OPEC) and nine High Industrialised Countries over the period 1985 to 2020; the study employs the first generation and second-generation Unit root tests. The study further adopts the use of the Panel Autoregressive Distributed Lag Model, and Common Correlated Effect pooled mean group to estimate the parameters of the model for OPEC countries and High Industrialised Countries, respectively. In addition, the Dumitrescu-Hurlin Granger causality test is conducted to infer the direction of causality among the variables. The causality test result reveals that, in OPEC, energy consumed during industrial activity is not enough to cause carbon emission and carbon emission does not cause industrialisation to interact with energy consumption. Also, for highly industrialised countries, interaction of energy consumption and industrialization causes carbon emission, but carbon emission does not cause the interaction of energy consumption and industrialization. The estimated model shows that the interactive effect of Industrialization and energy consumption has no significant influence on carbon emissions in OPEC countries in the short and long run. In contrast, foreign direct investment and economic growth have a positive and significant effect on carbon emissions in the short run. However, for highly industrialised countries the study found that the interactive effect of energy industrialization and energy consumption has a positive and significant effect on carbon emissions in the short run. It is apparent from the study that energy consumption for industrial activities, particularly in highly industrialised countries, causes carbon emission and such policy makers should formulate policy that necessitate the use of green energy for industrial activities to improve environmental quality.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231301","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}
We examine the relation between stock market returns and inflation expectations using data for 20 advanced countries. Evidence reveals that a negative relation presents in each of 18 countries; the exceptions are Brazil and Russia. The uncertainty hypothesis is established via evidence that U.S. inflation positively increases equity market volatility (EMV), which has a negative impact on U.S. and global stock returns. Evidence leads to the conclusion that both expected domestic inflation and EMV have adverse impacts on stock returns. The model is robust with different formations of inflation expectations and whether the test equations are examined using nominal or real stock returns.
{"title":"Stock returns and inflation expectations: Evidence from 20 major countries","authors":"Thomas C. Chiang","doi":"10.3934/qfe.2023027","DOIUrl":"https://doi.org/10.3934/qfe.2023027","url":null,"abstract":"<abstract> <p>We examine the relation between stock market returns and inflation expectations using data for 20 advanced countries. Evidence reveals that a negative relation presents in each of 18 countries; the exceptions are Brazil and Russia. The uncertainty hypothesis is established via evidence that U.S. inflation positively increases equity market volatility (EMV), which has a negative impact on U.S. and global stock returns. Evidence leads to the conclusion that both expected domestic inflation and EMV have adverse impacts on stock returns. The model is robust with different formations of inflation expectations and whether the test equations are examined using nominal or real stock returns.</p> </abstract>","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135156688","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}
Effective development of digital finance is vital to closing the regional economic disparities. This study aims at investigating the efficiency of digital finance development in China and its implications for closing regional economic disparities. Using the stochastic frontier model, we estimate the development efficiency of digital finance in 31 provinces in China from 2011 to 2020, and reveal their characteristics of temporal evolution and spatial distribution. The results show that the efficiency of digital finance development in each province shows a tendency to increase quickly first and then slowly decline. The provinces with a higher level of digital finance development always have higher development efficiency at the beginning of the sample period, which then declines rapidly after reaching the maximum, and even less than the national average value at the end of the period, with significant regional disparities observed. The provinces with a higher level of digital finance development always have higher development efficiency at the beginning of the sample period, which then declines rapidly after reaching the maximum, and even less than the national average value at the end of the period. The imbalance of development efficiency among different provinces is increasing, and the potential for development efficiency in the central and western regions is relatively greater. These findings have important implications for promoting high-quality economic development and common prosperity in China. In the future, we should continually prevent the development efficiency of digital finance to decline rapidly in all provinces (especially in the eastern region), and strive constantly to bridge the gap of development efficiency among different province, so as to provide a better surrounding for promoting high-quality economic development and common prosperity.
{"title":"Measuring provincial digital finance development efficiency based on stochastic frontier model","authors":"Guang Liu, Hong Yi, Haonan Liang","doi":"10.3934/qfe.2023021","DOIUrl":"https://doi.org/10.3934/qfe.2023021","url":null,"abstract":"Effective development of digital finance is vital to closing the regional economic disparities. This study aims at investigating the efficiency of digital finance development in China and its implications for closing regional economic disparities. Using the stochastic frontier model, we estimate the development efficiency of digital finance in 31 provinces in China from 2011 to 2020, and reveal their characteristics of temporal evolution and spatial distribution. The results show that the efficiency of digital finance development in each province shows a tendency to increase quickly first and then slowly decline. The provinces with a higher level of digital finance development always have higher development efficiency at the beginning of the sample period, which then declines rapidly after reaching the maximum, and even less than the national average value at the end of the period, with significant regional disparities observed. The provinces with a higher level of digital finance development always have higher development efficiency at the beginning of the sample period, which then declines rapidly after reaching the maximum, and even less than the national average value at the end of the period. The imbalance of development efficiency among different provinces is increasing, and the potential for development efficiency in the central and western regions is relatively greater. These findings have important implications for promoting high-quality economic development and common prosperity in China. In the future, we should continually prevent the development efficiency of digital finance to decline rapidly in all provinces (especially in the eastern region), and strive constantly to bridge the gap of development efficiency among different province, so as to provide a better surrounding for promoting high-quality economic development and common prosperity.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"274 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231733","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}
We investigate market crashes and downturns through the lens of persistent homology and persistence landscape norms. Using individual stock price data from Yahoo! Finance, we find that the variation in the persistence landscape norm as well as other measures of persistence exhibit a marked increase followed by a decline prior to historic incidents. We show that basic descriptions of persistent homology may be useful in addition to more sophisticated tools like the persistence landscape norm.
{"title":"Topological variability in financial markets","authors":"Aaron D. Valdivia","doi":"10.3934/qfe.2023019","DOIUrl":"https://doi.org/10.3934/qfe.2023019","url":null,"abstract":"We investigate market crashes and downturns through the lens of persistent homology and persistence landscape norms. Using individual stock price data from Yahoo! Finance, we find that the variation in the persistence landscape norm as well as other measures of persistence exhibit a marked increase followed by a decline prior to historic incidents. We show that basic descriptions of persistent homology may be useful in addition to more sophisticated tools like the persistence landscape norm.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231994","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}
Tânia Menezes Montenegro, Pedro Meira, Sónia Silva
The costs and benefits of mandatory auditor rotation (audit firm rotation and partner rotation) are far from being conclusive. This paper helps fill this gap in the literature by examining the relationship between mandatory auditor rotation and firms' stock market performance in the Portuguese context. Using a sample of listed companies in Portugal from 2009 to 2020, the main finding indicates that mandatory audit firm rotation is positively and significantly related to the firm's market performance. The evidence gathered suggests investors perceive mandatory audit firm rotation as a mechanism for improving audit quality. Controlling for the engagement partner rotation, we do not find that the rotation rule has a positive effect on firms' market performance. The net benefits of the mandatory audit rotation rule seem to be driven by the mandatory change of the audit firm, with improvements in market perceptions of earnings. Robustness tests suggest that the signal and significance of the association of firms' market performance and mandatory audit firm rotation holds in the presence of corporate governance mechanisms. Also, the audit experience of the departing and incoming partners does not interact with the relationship between mandatory partner rotation and firms' market performance.
{"title":"The investors' prospects on mandatory auditor rotation: evidence from Euronext Lisbon","authors":"Tânia Menezes Montenegro, Pedro Meira, Sónia Silva","doi":"10.3934/qfe.2023022","DOIUrl":"https://doi.org/10.3934/qfe.2023022","url":null,"abstract":"<abstract> <p>The costs and benefits of mandatory auditor rotation (audit firm rotation and partner rotation) are far from being conclusive. This paper helps fill this gap in the literature by examining the relationship between mandatory auditor rotation and firms' stock market performance in the Portuguese context. Using a sample of listed companies in Portugal from 2009 to 2020, the main finding indicates that mandatory audit firm rotation is positively and significantly related to the firm's market performance. The evidence gathered suggests investors perceive mandatory audit firm rotation as a mechanism for improving audit quality. Controlling for the engagement partner rotation, we do not find that the rotation rule has a positive effect on firms' market performance. The net benefits of the mandatory audit rotation rule seem to be driven by the mandatory change of the audit firm, with improvements in market perceptions of earnings. Robustness tests suggest that the signal and significance of the association of firms' market performance and mandatory audit firm rotation holds in the presence of corporate governance mechanisms. Also, the audit experience of the departing and incoming partners does not interact with the relationship between mandatory partner rotation and firms' market performance.</p> </abstract>","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135445766","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}
This study examines the relationship between market volatility conditions and the weekend effect on size and profitability anomalies in the U.S. stock market. The study uses the ICSS model to divide the sample into high- and low-volatility periods. Empirical results indicate that the weekend effect of size and profitability anomalies is significant in low-volatility states and insignificant in high-volatility conditions, and it is consistent across different measures of stock market volatility and subsamples. Additionally, we identify the intra-week patterns of log returns on the VIX index as the driver of the weekend effect on profitability and size anomalies. Our study not only extends the understanding of the weekend effect of long-short anomalies but also provides new evidence on the effectiveness of volatility management in factor investing. It also has important implications for investors, who should consider improving their factor investment strategies based on our results.
{"title":"Volatility conditions and the weekend effect of long-short anomalies: Evidence from the US stock market","authors":"Wenhui Li, N. Nor, Hisham M, Feng Min","doi":"10.3934/qfe.2023016","DOIUrl":"https://doi.org/10.3934/qfe.2023016","url":null,"abstract":"This study examines the relationship between market volatility conditions and the weekend effect on size and profitability anomalies in the U.S. stock market. The study uses the ICSS model to divide the sample into high- and low-volatility periods. Empirical results indicate that the weekend effect of size and profitability anomalies is significant in low-volatility states and insignificant in high-volatility conditions, and it is consistent across different measures of stock market volatility and subsamples. Additionally, we identify the intra-week patterns of log returns on the VIX index as the driver of the weekend effect on profitability and size anomalies. Our study not only extends the understanding of the weekend effect of long-short anomalies but also provides new evidence on the effectiveness of volatility management in factor investing. It also has important implications for investors, who should consider improving their factor investment strategies based on our results.","PeriodicalId":45226,"journal":{"name":"Quantitative Finance and Economics","volume":"1 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70231647","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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