Effect of Fair Value Based on IFRS 13 on the Qualitative Characteristics of Accounting Information

The aim of the study to investigate the effect and relationship between accounting of fair value according to the standard of (IFRS13) and the qualitative characteristics of accounting information. The fair value made a good contribution in the field of accounting thought because it faced the deficiency in the principle of historical cost, which was subjected to many criticisms. The researcher designed a questionnaire, where the number of the valid questionnaires was 135. The sample was distributed according to demographic variables (academic achievement, educational qualification, and years of experience). The researcher found through statistical analysis that there is a positive significant relation between the standard of fair value (IFRS13) and the qualitative characteristics of the accounting information. Also, there is an effect of IFRS13 on qualitative characteristics.

Effect of Fair Value based on IFRS 13 on the Qualitative Characteristics of Accounting Information

The aim of the study to investigate the effect and relationship between accounting of fair value according to the standard of (IFRS13) and the qualitative characteristics of accounting information. The fair value made a good contribution in the field of accounting thought because it faced the deficiency in the principle of historical cost, which was subjected to many criticisms. The researcher designed a questionnaire, where the number of the valid questionnaires was 135. The sample was distributed according to demographic variables (academic achievement, educational qualification, and years of experience). The researcher found through statistical analysis that there is a positive significant relation between the standard of fair value (IFRS13) and the qualitative characteristics of the accounting information. Also, there is an effect of IFRS13 on qualitative characteristics.

Unregulated Corporate Financial Disclosure and Analysts’ Forecast Properties: The Case of Embedded Value Reporting by Life Insurers

This paper investigates the association between life insurers’ voluntary disclosure of embedded value (EV), an unregulated market-driven fair value measure, and analyst forecast accuracy and dispersion. EV is an estimate of the present value of future net cash flows from in-force life insurance business. Advocates of this disclosure believe that EV is a better measure of economic performance than traditional GAAP measures. Others argue that corporate management has discretion in estimating and reporting EV. Further, analysts may have access to information that allows the development of possibly more accurate estimation metrics in the absence of EV disclosure. It is then an empirical issue to determine whether EV disclosure has any incremental effect on analysts’ forecast properties. Using a multi-country setting, we find that EV disclosure is positively associated with analysts’ earnings forecast accuracy and negatively related to forecast dispersion. This result is consistent with the alternative hypothesis that disclosure of EV provides a richer information set that enriches analysts’ forecasts beyond their own in-house developed surrogates. As guidance for insurance accounting and disclosure evolves, our findings support the value of continuing to provide EV information to the public.

Research on Clothing Image Database Retrieval Algorithm Based on Wavelet Transform

Aiming at the problems of low image data retrieval accuracy and slow retrieval speed in the existing image database retrieval algorithms, this paper designs a clothing image database retrieval algorithm based on wavelet transform. Firstly, it represents the color consistency vector of clothing image, reflects the composition and distribution of image color through color histogram, quantifies the visual features of clothing image, aggregates them into a fixed size representation vector, and uses the Fair Value (FV) model to complete the collection of clothing image data. Then, the size of the clothing image is adjusted by using the size transformation technology, and the clothing pattern is divided into four moments with the same size. On this basis, the clothing image is discretized with the help of Hu invariant moment to complete the preprocessing of clothing image data. Finally, the generating function of wavelet transform is determined, and a cluster of functions is obtained through translation and expansion. The wavelet filter is decomposed into basic modules, and then, the wavelet transform is studied step by step. The clothing image data are regarded as a signal, split, predicted, and updated and input into the wavelet model, and the retrieval research of clothing image database is completed. The experimental results show that the design of the retrieval algorithm is reasonable, the retrieval data accuracy is high, and the retrieval speed is fast.

The localised accounting environment in the implementation of fair value accounting in Indonesia

Purpose This case study aims to investigate the role of actors in the implementation of fair value standards in an emerging country, Indonesia. Design/methodology/approach This study uses semi-structured interviews with important actors within the local accounting profession, standard setting and regulatory environment, to analyse fair value accounting implementation. This study also incorporates information from press releases and newspapers, to provide a more comprehensive picture of fair value implementation. Findings First, professionals undertake routine actions, cultivate interests and strategically navigate their environment during the process of fair value standard implementation. Second, the role of appraisers becomes more prominent during this process. Third, government involvement is significant in ensuring the successful implementation of global accounting standards. Research limitations/implications First, differing localised contexts, including communities and actors, may shape how an emerging country undertakes the diffusion and implementation of global standards, which in turn can also lead to institutional change. Second, government involvement is crucial in supporting the implementation of global accounting standards within emerging economies. Third, implementing market-based measurements within emerging economies characterised by a lack of an active and liquid market may present challenges. Practical implications Third, implementing market-based measurements within emerging economies characterised by a lack of an active and liquid market may present challenges. Originality/value This study applies the concept of Institutional Work within Institutional Theory to explain how fair value standards are implemented within a localised emerging economy characterised by unique actor roles and goal-directed action.

The Influence of Cognitive Biases and Financial Factors on Forecast Accuracy of Analysts

The objective of this study was to jointly analyze the importance of cognitive and financial factors in the accuracy of profit forecasting by analysts. Data from publicly traded Brazilian companies in 2019 were obtained. We used text analysis to assess the cognitive biases from the qualitative reports of analysts. Further, we analyzed the data using statistical regression learning methods and statistical classification learning methods, such as Multiple Linear Regression (MRL), k-dependence Bayesian (k-DB), and Random Forest (RF). The Bayesian inference and classification methods allow an expansion of the research line, especially in the area of machine learning, which can benefit from the examples of factors addressed in this research. The results indicated that, among cognitive biases, optimism had a negative relationship with forecasting accuracy while anchoring bias had a positive relationship. Commonality, to a lesser extent, also had a positive relationship with the analyst’s accuracy. Among financial factors, the most important aspects in the accuracy of analysts were volatility, indebtedness, and profitability. Age of the company, fair value, American Depositary Receipts (ADRs), performance, and loss were still important but on a smaller scale. The results of the RF models showed a greater explanatory power. This research sheds light on the cognitive as well as financial aspects that influence the analyst’s accuracy, jointly using text analysis and machine learning methods, capable of improving the explanatory power of predictive models, together with the use of training models followed by testing.

Is It Possible to Monetarily Quantify the Emotional Value Transferred by Companies and Organizations? An Emotional Accounting Proposal

Social accounting focuses on value transactions between organizations and their stakeholders; both market ones, where the value perceived by the different stakeholders is identified, and non-markets ones, where transactions are monetized at their fair value. There was long awareness of an emotional value translation, linked to the transfer of different products, services, remunerations, and incentives, regardless of whether they were market or non-market. Yet that emotional value seemed to be anchored in the field of psychology and managed to elude economic science. This study seeks to identify emotional value with consumer surplus and, by extension, of the other stakeholders in a value transfer process. This proposal allows the emotional value to be anchored in the micro-economy and allows it to be objectively calculated using a regression involving three elements: the market price, the fair value interval, and a perceived satisfaction score by the different stakeholders in the form of significant sampling. The result obtained not only allows Social Accounting to be complemented with emotional value, but it also facilitates its incorporation in the strategy to optimize the emotional value. Furthermore, it enables a quantification of the perceived subjective utility, which opens up a research path where some possible lines are clearly identified.