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The purpose of the paper is to back-test value-at-risk (VaR) models for conditional distributions belonging to a Generalized Hyperbolic (GH) family of Lévy processes – Variance Gamma, Normal Inverse Gaussian, Hyperbolic distribution and GH – and compare their risk-management features with a traditional unconditional extreme value (EV) approach using data from future contracts return data of S&P500, FTSE100, DAX, HangSeng and Nikkei 225 indices.

The authors apply tail-based and Lévy-based calibration to estimate the parameters of the models as part of the initial data analysis. While the authors utilize the peaks-over-threshold approach for generalized Pareto distribution, the conditional maximum likelihood method is followed in case of Lévy models. As the Lévy models do not have closed form expressions for VaR, the authors follow a bootstrap method to determine the VaR and the confidence intervals. Finally, for back-testing, they use both static calibration (on the entire data) and dynamic calibration (on a four-year rolling window) to test the unconditional, independence and conditional coverage hypotheses implemented with 95 and 99 per cent VaRs.

Both EV and Lévy models provide the authors with a conservative proportion of violation for VaR forecasts. A model targeting tail or fitting the entire distribution has little effect on either VaR calculation or a VaR model’s back-testing performance.

To the best of the authors’ knowledge, this is the first study to explore the back-testing performance of Lévy-based VaR models. The authors conduct various calibration and bootstrap techniques to test the unconditional, independence and conditional coverage hypotheses for the VaRs.

The purpose of this paper is to investigate the properties of net income (NI) and total comprehensive income (TCI) of listed companies in New Zealand (NZ). Four properties of TCI and NI are examined: persistence, variability, predictive ability, and value relevance. Whether the value relevance of TCI depends on its reporting location is also investigated.

A cross‐sectional research design is used with data on TCI reported by NZ listed companies in 2010 under the new disclosure requirement in IAS 1. Ordinary least squares (OLS) regressions are used with a sample of 86 firms to test for persistence, variability, and predictive ability, and 81 firms to test for value relevance of NI and TCI.

The study finds: NI is potentially more persistent than TCI and potentially explains contemporaneous stock returns better than TCI; no significant difference in the variability and predictive ability of NI and TCI; little evidence that the value relevance of TCI depends on its reporting location; other comprehensive income (OCI) has incremental ability to predict one‐year‐ahead CFO, although the incremental ability of OCI to predict one‐year‐ahead NI is not statistically significant; and OCI is not incrementally value relevant.

The findings would be of interest to securities analysts and other users in valuing firms and when earnings are used in contractual settings (e.g. management compensation). Further, the results would also be of potential interest to standard‐setters.

The literature on comprehensive income is growing. However, the authors are not aware of any study that investigates the properties of NI and TCI in accordance with the new requirement to report comprehensive income in the amended IAS 1 which came into effect in NZ on January 1, 2009. The paper adds current evidence on the properties of NI and TCI under IFRS to the international literature.

Bangladesh is an emerging economy and international audit firms operate there through affiliated local audit firms. The Bangladesh audit market can be characterized as an intensely competitive small audit market with relatively poor demand for high‐audit quality. In addition, Bangladesh has a relatively small and under developed but growing capital market that is characterized by poor corporate regulation and weak investor protection. The purpose of this paper is to examine the association between Big 4 affiliated auditors and accruals quality in Bangladesh.

Following prior literature, this paper uses both absolute discretionary accruals and signed discretionary accruals as proxies of accruals quality. The sample is 382 firm‐year observations and covers fiscal years 2000‐2003.

It was found that the association between Big 4 affiliates and accruals quality in Bangladesh depends on measures of accruals quality and accruals models used. Overall, Big 4 affiliates do not have a positive impact on accruals quality of their clients in Bangladesh.

This paper contributes to the literature on audit quality and accruals quality. The results potentially suggest that Big 4 affiliates do not have any positive impact on accruals quality of clients in an intensely competitive audit market where the demand for quality audit is poor and monitoring is lax and raise potential implications for policy makers and market participants in Bangladesh.

This study investigates the presence of herding in the Brazilian stock market between 2012 and 2020 and associates it with the volume of searches on the Google platform.

Following methodologies are used to investigate the presence of herding: the Cross-Sectional Standard Deviation of Returns (CSSD), the Cross-Sectional Absolute Deviation (CSAD) and the Cross-Sectional Deviation of Asset Betas to the Market.

Most of the models detected herding. In addition, there was a causal relationship between peaks in Google search volumes and the incidence of herding across the whole period, especially in 2015 and 2019.

This study suggests that confirmation bias influences investors' decisions to buy or sell assets.

The purpose of this paper is to examine whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia Pacific ex Japan, North America and Globe.

To examine the herd behavior of common risk-factor portfolio investors, this paper utilizes the cross-sectional absolute deviations (CSAD) methodology, covering a daily data sampling period of July 1990 to January 2019 from Kenneth R. French-Data Library. CSAD driven by fundamental and non-fundamental information is assessed using Fama–French five-factor model.

The results do not provide evidence for herding under normal market conditions, either when reacting to fundamental information or non-fundamental information, for any region under consideration. However, Fama–French common risk-factor portfolio investors mimic the underlying risk factors in returns related to size and book-to-market value, size and operating profitability, size and investment and size and momentum of the equity stocks in European and Japanese markets during crisis period. Also, no considerable evidence is found for herding (on fundamental information) under crisis and up-market conditions except for Japan. Ancillary findings are discussed under conclusion.

Further research on new risk factors explaining stock return variation may help improve the model performance. The performance can be improved by adding new risk factors that are free from behavioral bias but significant in explaining common stock return variation. Also, it is necessary to revisit the existing common risk factors in order to understand behavioral aspects that may affect cost of capital calculations (e.g. pricing errors) and valuation of investment portfolios.

This is the first paper that examines the herd behavior (fundamental and non-fundamental) of Fama–French common risk-factor investors using five-factor model.

The study aims to use bibliometric and scientometric analysis to conduct a detailed investigation on the impact of disruptive technologies in accounting and reporting literature. To draw both academics and practitioners through accelerated research activities, the study also aims to look into the significance of these disruptive technologies, their potential and the opportunities they present for the accounting profession.

With the use of the Scopus database and a combination of accounting, reporting, auditing and technology-related keywords, 1660 research articles published between 2008 and 2023 were included in the sample. To provide graphical analysis of bibliometric data and visualize research findings such as bibliographic coupling, co-citation and keyword co-occurrence, this study used the R-biblioshiny and VOSViewer tools.

The findings demonstrate a growth in scholarly interest in the study’s area, particularly in recent years. The bibliometric analysis focuses on three key uses and applications of technology in the accounting and auditing professions: the adoption of continuous auditing and monitoring in the audit profession, the use of software tools in the audit and accounting professions and the connections between information systems and audit.

This study contributes to the literature by examining current research trends on the use of technology in the accounting and reporting professions, identifying gaps in the literature and, most importantly, proposing a research agenda for the field. This study’s data came entirely from English-language articles and reviews in the Scopus database. It also considers studies that are directly relevant to the use of technology in accounting and reporting.

The purpose of this paper is to present the Islamic stock and Sukuk market efficiency and focus on the presence of investor herding behaviour (HB) captured by Hurst exponent estimation.

The Hurst exponent was estimated with various methods. The authors studied the evolving efficiency of the “Dow Jones” indices from 1 January 2010 to 30 December 2016 using a rolling sample of the Hurst exponent. In addition, they used a time-varying parameter method based on the Hurst of delayed returns. After that, the robust Hurst method was considered. In the next step, the efficiency of the different activity types of Islamic bonds was studied using an efficiency index. Finally, the Hurst exponent estimates were applied to assess the presence of HB.

The results show that, firstly, there’s a strong correlation between the “DJIM” and “DJSI” prices and returns. Secondly, by using robust Hurst estimate, it is observed that the “DJIM” is the most efficient market. The Hurst exponent estimation results show that HB is more intensive in the Islamic stock market. These results indicate also the inexistence of this behaviour in the studied Sukuk market.

Sukuk as Islamic financial assets is recent. Their relative time series are not long enough to apply the long memory approach. Furthermore, this work can be extended to study other Islamic financial markets.

Herding affects risk-return characteristics of assets and has an impact on asset pricing models. Practitioners are interested in understanding herding and its timing as it might create profitable trading opportunities.

This work analyses the impact of Islamic principles on the financial markets and their ability to understand some behavioural biases.

This study contributes to the literature by identifying the efficiency and the presence of HB with Hurst exponent estimation in Islamic markets.

This study aims to examine whether audit partner public-client specialization and busyness impact the cost of debt.

This paper uses data from companies in Thailand for the 1998–2016 period. To measure the cost of debt, this study uses the realized interest cost, measured as the total interest expense for the one year ahead divided by the average value of total debt outstanding during that year.

The results show a positive association between the cost of debt and two measures of public-client specialization and busyness, which are the number of public clients audited by an individual audit partner in each year and the proportion of the number of public clients divided by the number of total clients in an individual audit partner’s portfolio.

In the literature, there is a lack of research on whether a higher number of public clients in an audit partner’s portfolio leads to better or worse perceived audit quality. This study extends prior literature by examining whether creditors’ perception of audit quality depends on the audit partner specialization or busyness and specifically, on the number of public clients of the auditor. The findings indicate that public-client busyness of a particular audit partner, rather than the audit partner public-client specialization, matters in the cost of debt.