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Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

SUMMARY: This study examines whether the presence of high-quality auditors (Big 4 or industry specialist auditors [ISAs]) in an industry facilitates accounting information transfer among industry peers and enhances investment decisions of firms not audited by high-quality auditors (non-Big 4-ISA client firms). Consistent with the prediction of informational influence theories, we find that non-Big 4-ISA client firms that belong to an industry with a greater presence of high-quality auditors are associated with lower investment inefficiency. The effect is more pronounced for firms with less precise private information. Path analysis shows that the association between high-quality auditor presence and learning firms' investment inefficiency is explained via a direct path of source credibility and an indirect path mediated by peer firms' accounting information quality. Finally, we find that firms in industries with larger reductions in Big 4 presence following the Sarbanes-Oxley Act of 2002 incur more investment inefficiency. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: M40; M41; M42. [ABSTRACT FROM AUTHOR]

Robust Risk Quantification via Shock Propagation in Financial Networks Despite the significance of risk contagion in financial networks, uncertainties arise in interbank network structures because of limited information. To address this, proposed is a robust optimization approach to estimate worst-case default probabilities and capital requirements for a specific group of banks (e.g., systemically important financial institutions). By applying this tool, we analyze the impact of different incomplete network information structures and gain regulatory insights into gathering actionable network information. Given limited network information, we consider robust risk quantification under the Eisenberg–Noe model for financial networks. To be more specific, motivated by the fact that the structure of the interbank network is not completely known in practice, we propose a robust optimization approach to obtain worst-case default probabilities and associated capital requirements for a specific group of banks (e.g., systemically important financial institutions) under network information uncertainty. Using this tool, we analyze the effects of various incomplete network information structures on these worst-case quantities and provide regulatory insights into the collection of actionable network information. All claims are numerically illustrated using data from the European banking system. Funding: The work of D. Ahn was supported by the Hong Kong Research Grants Council, University Grants Committee [Early Career Scheme Grant 24210420]. N. Chen acknowledges funding support from the Hong Kong Research Grants Council, University Grants Committee [General Research Fund Grant 14207918 and General Research Fund Grant 14208620]. The work by K.-K. Kim was supported by the National Research Foundation of Korea [Grant NRF-2019R1A2C1003144]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2020.0722. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to investigate the role of accounting comparability as an intra-organizational factor on pricing considerations of information environment issues such as information uncertainty and information asymmetry. In this study, two criteria have been used to measure information uncertainty. Based on the standard deviation of cash flows by the matched company (MF) method, the first criterion of information uncertainty on the model presented by Larson and Risatek is based. To measure the second criterion three different indicators were used, and then factor analysis method was used to convert these indicators into a single criterion. Information asymmetry is also measured based on the two indicators of accruals quality and sales gap. Also, the expected return of shareholders has been calculated based on the 5-factor model of Fama and French, for pricing these issues. For this purpose, data related to companies listed on the Tehran Stock Exchange have been extracted, for the period 1388 to 1397 and a combined regression model has been used to test the research hypotheses. The results show that the comparability of profits and cash flows leads to changes in returns due to information uncertainty and information asymmetry.Thus, investors and users of financial information in the Iranian capital market as well as standard formulators should pay special attention to the importance of comparability of financial reports as a qualitative factor among organizations; this is because it reduces the effects of information environment interference on the decision-making of users of financial information.

Stakeholders' uncertainty about firms' value drives their urge to get information, as well as managerial disclosure choices. In this study, the authors examine whether and how an important source of uncertainty – the recent COVID-19 pandemic's effect on corporate social responsibility (CSR) disclosure – is beyond managerial and stakeholders' control. The authors develop a novel construct for daily CSR disclosure by employing computer-aided text analysis (CATA) on the press releases issued by 125 New Zealand Stock Exchange (NZX) listed from 28 February 2020 to 31 December 2020. To capture COVID-19 intensity, the authors use the growth rate of the population-adjusted cumulative sum of confirmed cases in New Zealand on a specific day. To examine the association between the COVID-19 outbreak and companies' CSR disclosure, the authors employed ordinary least squares (OLS) regression by clustering standard error at the firm level. The authors find a one standard deviation increase in the COVID-19 outbreak leads to a 28% increase in such disclosures. These results remained robust to a series of sensitivity tests and continue to hold after accounting for potential endogeneity concerns. In the channel analysis, the study demonstrates that the positive relationship between COVID-19 and CSR disclosure is more pronounced in the presence of a well-structured board (i.e. a large, more independent board and with a higher proportion of women on it). In further analysis, the authors find the documented relationship varies over the pandemic's life cycle and is moderated by government stringency response, peer CSR pressure and media coverage. This paper is the first study that contributes to the scant literature examining the impact of the COVID-19 outbreak on CSR disclosure. Prior research either investigates the relationship of the CSR-stock return during the COVID-19 market crisis or examines the relationship between corporate characteristics including the quality of financial information and the reactions of stock returns during COVID-19. The authors extend such studies by providing empirical evidence that managers respond to COVID-19 by increasing CSR disclosure.

We document strong evidence that CEO incentive compensation can predict the significance of stock price momentum through discretionary accrual and real activities manipulation. The profit of momentum strategy increases with CEO pay‐for‐performance incentive, but decreases with CEO risk‐taking incentive. It also evaluates the effects of information uncertainty on such relationship. The evidence is more significant for firms with older and longer tenured CEOs and firms with more informed traders. The relationship between the profit of momentum strategy and CEO pay‐for‐performance incentive is stronger among CEOs without the risk‐taking incentive. Our results are robust for different sub‐samples based on before and after Reg FD and Sarbanes–Oxley Act, even after controlling for the potential endogeneity. Further, our findings are consistent with the information diffusion explanation of momentum and the agency theory that incentivised CEOs tend to manipulate information by smoothing good news, concealing mildly bad news and accelerating the disclosure of extremely bad news. [ABSTRACT FROM AUTHOR]

We examine and compare the extent to which the reaction of investors to earnings announcements is influenced by a firm's governance profile and prevailing market conditions. We find that firms with better governance characteristics experience a larger initial reaction to both good and bad earnings announcements regardless of the prevailing sentiment and uncertainty conditions. However, the influence of governance is constrained to the announcement period. We demonstrate that changes in market uncertainty and/or investor sentiment are related to the post-earnings announcement drift. We also find that a major channel through which greater corporate governance influences the market response to unexpected earnings news is by lowering information uncertainty and so providing greater clarity of the implication of the news for firm value. Finally, we establish that two types of uncertainties (market and information) have very different influence on investor's response to information signals. JEL Classification: D81, G10, G14, G30, G32 [ABSTRACT FROM AUTHOR]

Firms engaging in innovative practices have patents to prevent competitive forces from eroding the resulting economic rents; however, there is limited evidence regarding the impact of innovation on risk. We shed new light on how firms' involvement in innovation activities impacts their volatility, particularly their idiosyncratic volatility. In this paper, we empirically examine the effect of innovation on idiosyncratic volatility. To do so, we empirically examine the impact of innovation, measured by patents weighted by citations and R&D expenditure, on the idiosyncratic volatility of firms. Using a large sample of 8256 US firms, we find that more innovation is associated with lower idiosyncratic volatility. We also find that information uncertainty is the channel through which innovation affects idiosyncratic risk. The results are robust for different measures of idiosyncratic volatility. These results have empirical implications for investors, managers, and firms engaging in innovation-related activities. [ABSTRACT FROM AUTHOR]

Introduction. Meaning-in-life orientations and self-reflection are important indicators of the regulation of personal meanings. In a modern rapidly changing society, individuals do not fully manage their lives due to the influence of various uncertainty factors. The COVID-19 pandemic that began in early 2020 and swept across the world is considered a global factor of uncertainty. The increased uncertainty of life associated with the pandemic is an additional stressor. This paper represents a first effort in obtaining empirical data on gender characteristics of teachers’ meaning-based regulation in the context of the coronavirus pandemic. This paper reports the results of an empirical study of differences in meaning-in-life orientations and self-reflection among teachers before and during the pandemic as different conditions of information uncertainty in their lives. Methods. The study was conducted among female teachers of secondary schools in the Rostov region in March 2017 (n = 53) and in October 2020 (n = 43), i.e. before and during the pandemic, which can be considered different conditions of information uncertainty in their lives. We used the following psychological assessment tools: (a) the Meaning-in-Life Orientations test by D. A. Leont'ev and (b) the Self-reflection Questionnaire by I. A. Stetsenko. Results. We observed an increase in all means of both tests during the pandemic, compared to the pre-pandemic values. Differences in all parameters are statistically significant (according to the Mann–Whitney U test). Discussion. Our findings indicate that the pandemic represents a surmountable stressor for the homogeneous acmeological category of female teachers surveyed in this study. Information uncertainty contributes to constructive restructuring of the processes of meaning-based regulation and psychological adaptation, which leads to an increase in the level of meaningfulness of life orientations and self-reflection among the respondents.

Due to the constant growth of cities in terms of population and territory, the volume of passenger traffic is sharply increasing. A lot of attention is paid to the study of transport infrastructure in scientific works, but the current problems of the functioning of various types of transport in large cities remain not fully covered. First of all this concerns the great uncertainty in the current information about the movement of transport and their work in the event of emergency situations. The article proposes to use the mathematical apparatus of the theory of queuing systems for the analysis of passenger traffic on urban transport. As an example, a graph of states for fixed-route taxis is constructed and ratios are obtained for evaluating the main indicators of the quality of their work. In the conditions of frequent changes in road situations and uncertainty of the conditions for obtaining information about the current situation, it is proposed to carry out traffic management using intelligent decisionmaking support tools. In this regard, it is advisable to use an approach based on fuzzy situational management. For this purpose, the article proposes an algorithm for fuzzy situational management, which is the basis of intelligent IDSS. . For an optimal transition from the current situation to a situation that meets the new operating conditions, in the sense of the selected criterion, it is proposed to use the dynamic programming method. Ref. 12, pic. 4.

• The trend factor performs significantly better following high market volatility periods. • Results remain robust under different asset price models and after controlling for various macroeconomic state variables. • Stock market volatility serves as an important time-series determinant of trend factor performance. This paper investigates how stock market volatility predicts trend factor profits. We find that the trend factor performs significantly better following high market volatility periods. From 1931 to 2022, the average monthly risk adjusted return following high volatility periods is 2.47 %, significantly higher than that following low volatility periods. We hypothesize that fundamental signals are more likely to be imprecise when the stock market is more volatile, leading investors to rely more heavily on trend signals. Consequently, the trend factor could deliver higher profits. Collectively, our paper suggests that market volatility is an important time-series determinant of trend factor performance. [ABSTRACT FROM AUTHOR]

• There is a U-shaped relationship between the performance of carbon neutrality and firm value. • The U-shaped relationship is weaker in state-owned firms and firms operating in B2C industries. • The U-shaped relationship is stronger when information uncertainty is higher. Carbon neutrality is critical in addressing the climate crisis. Using the data of Chinese listed firms from 2018 to 2022, this paper shows a significant U-shaped association between the performance of carbon neutrality and firm value. Our key findings hold after a battery of robustness tests and endogeneity concerns. The U-shaped relationship is weaker in state-owned firms and those operating in B2C industries, and stronger when information uncertainty is higher. This paper has implications for the promotion of carbon-neutral practices in enterprises and the realization of sustainable development. [ABSTRACT FROM AUTHOR]

We propose a timing momentum strategy by incorporating moving‐average signals in the price momentum and show that the proposed strategy substantially outperforms the buy‐and‐hold strategy. The performance of the timing momentum is better than that of Barroso and Santa‐Clara's (2015) constant‐volatility momentum and is identical to that of Daniel and Moskowitz's (2016) dynamic momentum. One advantage of the timing momentum is that its weights on winner and loser portfolios are lower than the other two strategies, thus leading to lower transaction costs. Further, we show that the profitability of the timing momentum is enhanced when information uncertainty is high. More importantly, the timing momentum has time‐invariant profitability across various time‐series predictors and during periods of momentum crashes. [ABSTRACT FROM AUTHOR]

This article explores instinctive frames of human decision-making in environmental and resource economics. Higher-moment asset pricing combines rational, mathematically informed economic reasoning with psychological and biological insights. Leptokurtic blindness and skewness preference combine in particularly challenging ways for carbon mitigation. At their worst, human heuristics may generate perverse decisions. Information uncertainty and the innate preference for bonds-and-bullets portfolios may impair responses to catastrophic climate change.

The physical-chemical monitoring of vast oceanic areas aims at assessing the status and evolution of the environmental resource for its exploration, protection and/or better understanding. However, the interpretation of monitoring data is affected by ocean seasonality and heterogeneity, and by the quality of sampling and characterization tools used to study the environment. All these factors contribute to the uncertainty of collected information that should be expressed in determined parameter values or trends. A trend of a studied parameter quantified by values difference is significant if the observed absolute value of the difference is larger than their expanded uncertainty. The correlation of studied parameters, useful for their interpretation, is equality affected by the mentioned sources of uncertainty. This work describes the metrologically sound evaluation of trends and correlations of physicochemical parameters of vast oceanic areas where all uncertainty sources affecting the information are considered by simulating their complex impact by the Monte Carlo Method. The described methodology was successfully used to study the impact of summer upwelling in an 800 km2 coastal area offshore two large cities in Portugal. Nutrients, conductivity, salinity and temperature trends and correlations are distinguished from system heterogeneity, sampling and sample analysis uncertainty for a 99% confidence level. [Display omitted] • Simulation of the impact of the heterogeneity, and sampling and analysis uncertainty on oceanic area characterisation. • Mean value of nutrients and fundamental oceanographic parameters from a vast oceanic area reported with uncertainty. • Evaluation of the variation of mean composition values between October 2019 and May 2018 for a 99% confidence level. • Correlations between nutrients and fundamental oceanic parameters evaluated taking information uncertainty into account. • Upwelling trends and correlations confirmed from modelled spatial variation of a vast oceanic area with uncertainty. [ABSTRACT FROM AUTHOR]

• COVID-19 pandemic had an adverse impact on the IPO market. • IPOs during the pandemic experience greater information uncertainty compared to those before the pandemic. • Increased uncertainty is mainly driven by the IPOs from the high-technology and the healthcare sectors. • IPO underpricing and post-IPO return volatility is positively associated with pandemic intensity and the associated government responses. Anecdotal evidence seems to suggest that the initial public offering (IPO) market performed remarkably well through the COVID-19 pandemic. To further understand this peculiar observation, we carry out a comprehensive analysis of IPOs during the pandemic vis-a-vis IPOs before the pandemic. Our findings imply that IPOs during the pandemic experience greater information uncertainty compared to those before the pandemic, and this greater uncertainty is mainly driven by the IPOs from the high-technology and the healthcare sectors. Furthermore, we find that an average IPO firm experiences larger underpricing and more post-IPO return volatility as the pandemic and the associated government responses increase in severity before the offering. Overall, our study indicates that the COVID-19 pandemic had an adverse impact on the IPO market. [ABSTRACT FROM AUTHOR]

Vehicle localisation is an important and challenging task in achieving autonomous driving. This work presents a box particle filter framework for vehicle self-localisation in the presence of sensor and map uncertainties. The proposed feature-refined box particle filter incorporates line features extracted from a multi-layer Light Detection And Ranging (LiDAR) sensor and information from OpenStreetMap to estimate vehicle states. A particle weight balance strategy is incorporated to account for the OpenStreetMap positional inaccuracy, which is assessed by comparing it to a high definition road map. The performance of the proposed framework is evaluated on a LiDAR dataset and compared with box particle filter variants. Experimental results show that the proposed framework achieves respectively 10% and 53% localisation performance improvement with reduced box volumes of 25% and 41%, when compared with the state-of-the-art interval analysis based box regularisation particle filter and the box particle filter. • The FRBPF is proposed to deal with OpenStreetMap and sensor data uncertainties. • A contraction algorithm is developed to reduce the volume of box particles. • Theoretical proofs about the features-refined contractions are derived. • A weight balance strategy is designed to improve the performance of FRBPF. [ABSTRACT FROM AUTHOR]