Audit report forecast: an application of nonlinear grey Bernoulli model

Abstract

Purpose-The widespread application of traditional grey model (GM) in different academic fields such as electrical engineering, education, mechanical engineering and agriculture provided the authors with an incentive to conduct the present empirical research in an accounting field, in particular, auditing practice. In this regard, the purpose of this paper is to employ the nonlinear type of the original GM to forecast the drastically changed data on audit reports, primarily due to the fact that the linear nature of GM is unable to forecast nonlinear data precisely. In essence, this paper adds value to the strand of audit report literature by examining the impact of different financial ratios on auditors' opinion and then forecasting audit reports by employing GMs. Design/methodology/approach-The grey forecasting model is known as a system containing uncertain information presented by grey numbers, equations and matrices. The grey forecasting model is employed by using a differential equation in an uncertain system with limited data set which is suitable for smoothing discrete data. In addition, the analyses are conducted by applying a sample of top 50 listed companies on the Tehran Stock Exchange during 2011-2016. Findings-The findings suggest that audit reports are most influenced by the current ratio and conversely, least influenced by the ratio of working capital turnover. Moreover, the authors argue that the Nash nonlinear grey Bernoulli model is more precise than the nonlinear grey Bernoulli model and GM in forecasting audit reports. Originality/value-The current study may give more strength to stakeholders in order to analyse and forecast audit report.

Auditor's report, auditor's size and value relevance of accounting information

“…Auditing practice is considered as one of the fundamental parts of corporate liability regime. In this regard, the fulfillment of corporate liability function is primarily dependent on authentic and reliable information examined by an external and independent auditor (Salehi and Dehnavi, 2018). Audit regulations and guidance require the existence of audit opinion in an audit report.…”

Research on Audit Opinion Prediction of Listed Companies Based on Sparse Principal Component Analysis and Kernel Fuzzy Clustering Algorithm

“…Heng-Shu [15] took the financial indicators of listed companies as variables and introduced Takagi-Sugeno fuzzy neural network to construct the prediction model of audit opinions. Salehi and Dehnavi [16] applied the grey model to predict audit reports and found that the Nash nonlinear grey Bernoulli model had the best prediction effect. Yao and pan et al [17] adopted stepping-regression and principal component analysis (PCA) to reduce the dimension of company characteristics and used six machine learning methods to identify fraudulent activities in financial statements of Chinese listed companies.…”

A New Conformable Fractional-Order Time-Delay Grey Bernoulli Model with the Arithmetic Optimization Algorithm and Its Application in Rural Regional Economy

“…In addition, data enhancement and discretization measures can efectively improve the prediction performance of the model. To promote the development of grey system theory, this paper develops a new grey prediction model with a time-delay polynomial based [6] NGM (1, 1, k, c) A linear function is used instead of the constant as the grey action in the traditional grey model Qian et al [7] GM (1, 1, t α ) A grey prediction model with a power term with hyperparameter α as grey action Wei et al [8] GMP (1, 1, N) A model is developed by using polynomial as the grey action of the grey model Liu et al [9] PTGM (1, 1, α) Combination of GMP (1, 1, N) and GM (1, 1, t α ) Saxena [10] OFOPGM A new data-driven grey prediction model using the time item with two hyperparameters as the action Wu et al [11] NGBM (1, 1, k, c) A NGM (1, 1, k, c) model with nonlinear Bernoulli operators Liu et al [12] NGBM (1, 1, N) A GMP (1, 1, N) model with nonlinear Bernoulli operators Ma and Liu [13] TDPGM (1, 1) A grey model with the function called time-delayed polynomial as the grey action Ma et al [14] FTDGM A model is developed by using fractional time delayed term as the grey action of the grey model Xiang et al [15] HTGM (1, 1) A prediction algorithm using hyperbolic time delayed polynomial as grey action Salehi and Dehnavi [16] NGBM ( [20] Hybrid model A combination of GM (1, 1) and VAR (1) Zhou et al [21] Hybrid model A combination of GM (1, 1) and ARIMA Saxena [2] IOGM Grey forecasting models based on internal optimization Optimization based on data enhancement methods Wu et al [22] FGM (1, 1)…”