Analysts’ Earnings Forecasts and Discretionary Financial Reporting Practices

Analysts’ Earnings Forecasts and Discretionary Financial Reporting Practices
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ANALYSTS’ EARNING FORECASTS AND DICRETIONARY OR MANDATORY FINANCIAL REPORTING
Introduction
Earnings management is the use of various accounting techniques to produce financial statements that provide an overview of the firm's financial position. Earnings forecasts are based on the expectations of the firm's growth and profitability. Financial analysts form an integral part of the firm and the capital market by building financial models that estimate and provide prospective costs and revenues. Therefore, analysts' forecasts are important because they contribute to the valuation models of investors. Most analysts incorporate the top-down factors such as the macroeconomic factors, currencies, and economic growth rates to influence a firm's corporate growth (Hass et al, 2018, 151). The accuracy and other properties of analysts’ earnings forecasts have impacts on the financial reports. Therefore, high skilled and qualified auditors can manage to improve or reduce the efficiency of earnings forecasts based on the usefulness of the client's decisions. Financial reporting practices are accepted and standard rules that specify how firms must report and maintain their accounts and other transactions that have economic impacts. There are relationships between the properties of analysts' earnings forecasts and the firms' mandatory and discretionary financial reporting practices.
Ordinarily, financial reporting in an organization is critical because auditors may use their experience and skills in helping in forecasting future earnings, and this may help in promoting forecast accuracy. Additionally, the higher quality auditors are successful in constraining the attempts of their clients to manage the earnings that are ideal in meeting the consensus forecasting ongoing prior to the reporting period. It is critical to comprehend that the information available to analysts may affect the complexity and forecast accuracy. This literature will examine and evaluate financial reporting practices that are associated with bias among the analysts, measures that analysts may apply in reducing the implications of the weak financial reporting they offer and will also examine the impacts of corporate governance mechanism in the association between the forecasts offered by the analysts and the company’s financial reporting practices.
1 Properties of Analysts' Forecasts
Analysts gather information on the firm's formal communication channels. However, they are not limited to earnings conference calls, financial disclosures, and financial news items. Analysts are responsible for supplementing these formal channels with investors, the firm's management team, and brokerage clients. Some firms use Analysts' forecasts in stock price forecasts, long-term, and short-term forecasts. Therefore, analysts produce information about firms in various ways (Kothari et al. 2016, p. 195). These are buy and sell recommendations, issuing earnings, and growth forecasts. They also focus on the target prices that manifest collectively as an analyst report. Forces of demand and supply shape the properties of analysts' outputs and stock recommendations in an industry. The realization of earnings reports provides an accurate benchmark where the accuracy, biasness, and timeliness of analysts are studied. However, the accuracy and biasness of analysts' forecasts have received considerable attention in empirical research in earnings management. The quality of analysts’ forecasts are determined by the personal skills and competence of the analysts, corporate management of the firm and the effectiveness of financial reporting practices.
2 Analysts' Forecasts and Financial Reporting Practices
Accuracy refers to the absolute differences between the realization of output and the analysts' forecasts, while bias is the marked difference that is found between the two. The accuracy and bias of forecast is a function of the complexity of the task involved, the skills or competency of the analyst, and the individual incentives that face the analyst. In most cases, complexity tends to undermine accuracy, while competency or skills enhances accuracy in financial reporting (Choi et al. 2020, p.191). It is essential to understand the time-series and cross-sectional variations in analysts' forecasts accuracy and bias because the information of the forecasts depends on the extent to which the information is precise. The bias or accuracy of analysts' forecasts will ultimately affect the market prices and researchers' inferences. For instance, when market participants identify predictable variation in analyst accuracy, the market prices will end up responding positively or strongly to credible forecasts (Wu, Y. and Wilson, M., 2016, p. 167). Financial analysts' forecasts can be used as an essential factor when deliberating policymakers or regulators.
1 Accrual Earning management
Accrual earnings management occur when managers use the valuation and the structuring transactions so as to change financial statements. Eventually, this valuation influences contractual agreement and misleading of the firm’s economic performance. Therefore, accrual earnings management has an accrual reverse in the period after manipulation. An increase in the profits results into a decrease in profits in the next period. Furthermore, a decrease in current profits generated through accrual method will eventually result into an increase in profits in the next period (Darmawan et al. 2019, p. 9). Accruals can be either non-discretionary or discretionary accruals. Non-discretionary accruals are those that are determined by the normal economic conditions of the firm while discretionary accruals are not regulated on the bases of manager’s choice policy. They are assumed to be the result of manager’s opportunism.
2 Real Earning management
Managers can take action through real earnings management to obtain the desired target on profitability. Real earnings deviates from the normal operations of the firm. Furthermore, it is carried out to mislead stakeholders to behave in a manner that shows that the reporting objectives have been fulfilled in normal operations. The real earnings management has advantage over the accrual earnings management which is not easily detected by auditors or regulators and it is easier to achieve the set targets (Darmawan et al. 2019, p. 10). However, the disadvantage associated with real earnings management is that the worse impact is as a result of firm’s future cash flow. Thus, the manipulation must be anticipated by stakeholders because it puts the survival of the firm in danger.
3. Detection of earning management
There are various techniques analysts use to ensure financial reports are of high quality. The metrics used in the detection of earning management are based on the variance of the change in net income, the ratio of the variance of the changes in the net income and the variance detected in the cash flows. Furthermore, it shows the relationship between accruals and cash flows (Shahzad, 2016 p.3). In the U.S exchanges, the Generally Accepted Accounting Principles (GAAP) provide a better opportunity for non-US firms to engage in earning management that allows smoothening. Furthermore, the International Financial Reporting Standards (IFRS) is used as an alternative for GAAP in financial reporting and earning management.
3 Understanding Earnings Managemen...