This study investigates whether the relation between the financial reporting opacity measured by the OPAQUE measure of Hutton et al. (2009) and analyst’s earnings forecast errors measured as forecasting accuracy and bias. In particular, we test a measure of financial reporting opacity for individual firms based on an indicator of earnings management in the prior three-year moving sum of the absolute value of annual discretionary accruals as developed by Hutton et al. (2009) and standard deviation of discretionary accruals as suggested by Jeon and Park (2016). In additional analysis, we first partition the sample into KOSPI and KOSDAQ samples and test whether the relation between financial reporting opacity and analyst’s earnings forecast errors is different for market type. Furthermore, we separate the sample into Big 4 auditor and non-Big 4 auditor samples and test whether the relation between financial reporting opacity and analyst’s earnings forecast errors is different for audit quality (i.e., high audit quality versus low audit quality samples). Moreover, we divided the sample into pre-IFRS period and post-IFRS period and test whether the relation between financial reporting opacity and analyst’s earnings forecast errors has changed since the adoption of IFRS. In our tests, we further consider the empirical link between financial reporting opacity and analyst’s earnings forecast errors. Thus, our approach differs from the existing literature with a one-year value of discretionary accruals (hereafter DA) to capture the earnings management. This is, we use a three-year moving sum (other than a one-year value) to capture the multiyear effects of earnings management and because the moving sum is more likely to reflect an underlying policy of the firm to manage earnings (e.g., Hutton et al., 2009; Jeon and Park, 2017). In the study, we expect analysts’ earnings forecasts inaccurate and to be optimistically biased when financial reporting opacity is increasing. For analysis, our empirical tests employ two firm-level proxies of financial reporting opacity, that is, accrual-based measure of opacity. The first proxy of this study is the measure of opacity in financial reports (hereafter OPAQUE1) as developed by Hutton et al. (2009). We use OPAQUE1 is the measure of financial reporting opacity of Hutton et al. (2009) based on earnings management, calculated as the prior threeyear moving sum of the absolute value of annual discretionary accruals. Following Hutton et al. (2009), discretionary accruals are measured using the modified Jones model by Dechow et al. (1995). The second proxy of this study is the measure of financial reports opacity (hereafter OPAQUE2) as suggested by Jeon and Park (2016), which is the standard deviation of annual discretionary accruals, which is calculated over years t-2 through t. We use a three-year moving sum of absolute value of discretionary accruals or standard deviation of discretionary accruals (instead of a one-year value) to capture the multi-year effects of earnings management. Therefore, these measure intends to capture both the abnormally high accruals in the year of overstatement and the subsequent reversal of prior accrual overstatements. For example, Dechow et al. (1996) show that firms subjected to enforcement actions by the SEC generally manipulate reported earnings from one to three years before being detected and the overstated accruals of these firms typically reverse fairly quickly. Our sample covers KOSPI and KOSDAQ listed firms in Korean Stock Exchange Market based on the variable of interest from 2001 to 2015 (based on the dependent variable from 2002 to 2016), thus we use 9,677 firm-year observations. Our main findings are as follows. First, after including for several control variables that affect analyst’ earnings forecast errors, we find that a significantly positive association between analyst’ earnings forecast error and financial reporting opacity (both OPAQUE1 and OPAQUE2 proxies), consistent with our predictions. This result implies that firms with higher OPAQUE is associated with less accurate analyst’ earnings forecasts, and more optimistically biased forecasts. Whereas, we find no evidence that a significantly positive association between analyst’ earnings forecast error and the discretionary accruals (DA) of a one-year value. Second, we demonstrate that our measure of financial reporting opacity reliably predicts both analyst’ earnings forecasting accuracy and bias. This is, our results are robust to a variety of sensitivity checks such as an alternative specification. For examples, when we classify sample into KOSPI versus KOSDAQ listed firms, when we divided sample into Big 4 auditors versus non-Big 4 auditors, and when we partition the sample into pre- and post-IFRS adoption period, there are a positive and significant relation between analyst’ forecast error and financial reporting opacity, regardless of KOSPI versus KOSDAQ samples, or Big 4 auditors versus non-Big 4 auditors samples, and pre-IFRS period versus post-IFRS period. Therefore, our conclusions are not sensitive to market type, audit quality, and according to before and during IFRS adoption period, we find similar results. Overall, these empirical evidence suggests that the financial analyst perceive financial reporting opacity as a information risk-increasing factor. Using two proxies for financial reporting opacity, we provide novel evidence that analyst’ earnings forecast error increases significantly with financial reporting opacity, which is constructed as the multi-year effects of discretionary accruals. Whereas analyst’ earnings forecast error not increases significantly with the level of discretionary accruals in the short-run. Thus, we confirm that our firm-specific measure of financial reporting opacity (both OPAQUE1 and OPAQUE2), which prior three-year moving sum or standard deviation of annual discretionary accruals compared with the level of discretionary accruals in the one-year is a reliable predicator of information uncertainty as well as provide more information about the underlying policy of earnings management of the firm. Therefore, the results of this study may provide useful information to academics as well as investors and regulatory bodies that higher financial reporting opacity are associated with less accurate analyst’ earnings forecasts, and also more optimistically biased forecasts. Furthermore, considering the importance of analyst role in decision making of investors on the stock market, our results suggests that there is a problem with the accuracy of analyst’s earnings forecast, i.e., firms with more opaque financial reports. In addition to providing the first empirical examination of the factors that connect financial reporting opacity to analyst’s earnings forecast errors, the results have implications for earnings management and analyst’s forecast errors studies in prior research.