The research paper explores the value of information content incorporated in the first-time going concern opinion from the perspective of investors. The signaling effects of the auditors’ opinion with going concern remark issued to financially distressed companies are of a great value in case the auditor statements deliver new information content which has not been incorporated in the previously disclosed financial information. Otherwise a going concern audit opinion remains not relevant for the purpose of investors’ decision making. If the going concern audit opinion adds new information content, we gain an ability to detect a stock market reaction to the relevant public announcement. The paper examines the Australian stock market reaction to public announcements of going concern audit opinion in a short term period for the sample of the 29 first-time going concern listed companies during the 2007 to 2009 years observation period. High sample criteria are determined in order to avoid contamination effects of other price sensitive information. The impact of both the preliminary financial report and the final annual report is examined by means of the parametric and non-parametric tests aligned with the event study methodology. Consistent with previous studies in Australia, no significant financial market reaction to the final going concern audit opinion announcements inherent to the Australian environment has been found. We document that the more negative impact on the market reaction is caused by the preliminary financial report rather than the final report, which contains an audit opinion note. Correspondently, the audit opinions with going concern qualification do not add new information content for the Australian stock market participants, who base their expectations on the previously disclosed financial information.

I investigate how career concerns influence banking analysts’ forecasts and find that banking analysts issue relatively more optimistic forecasts early in the year and more pessimistic forecasts later in the year for banks who could be their future employers. This pattern is not observed when the same analysts forecast earnings for banks with no equity research departments. Using the Global Settlement as an exogenous shock on career concerns, I show that this forecast pattern is pronounced after the Settlement. Moreover, I find that analysts benefit from this behaviour as analysts that are more biased in their forecasts towards potential future employers are more likely to move to a higher reputation bank. Textual analysis of analyst reports is also valuable due to the private information and analysis conveyed in the text. Second paper therefore examines analyst reports with consistent and conflicting signals in terms of qualitative and quantitative outputs. I find that investors react more strongly when the sentiment and earnings forecast bias are consistent. Interestingly, when the tone of report text does not coincide with the earnings forecast, investors place greater weight on the text rather than the EPS forecasts. I also find that consistent reports with both optimistic sentiment and forecast bias have a strong positive market reaction but they are low in forecast accuracy. Markedly, forecasts with pessimistic sentiment have higher accuracy than those of optimistic sentiment. Hence, pessimistic sentiment is a good indicator of the quality of forecast reports. Finally, in my last paper, I explore whether there is any association between firm-specific investor sentiment and the subsequent tone of firms' quarterly reports. Firm-specific investor sentiment is measured using the methodology from Aboody et al. (2016), which proxies for market confidence relating to a specific firm. Given the potential cost-benefit trade-off in the reporting strategy, I argue and find different responses from managers in their 10-Qs in terms of their investor sentiment. I focus on the tone of optimism, readability and the proportion of uncertain words in the 10-Q filings. For firms with extremely high levels of investor sentiment, managers tend to be more conservative by using less optimistic words to avoid future disappointment. In comparison, in firms with extremely pessimistic investor sentiment, managers tend to use more optimistic and easy to understand language, and minimize their proportion of uncertainty in their 10-Q filings. By doing so, perhaps they are trying to alter their investor sentiment.

Issuers’ credit ratings change by one or more notches when credit rating agencies provide new ratings. Unique to the literature, I study the influences affecting multi notch versus single notch rating upgrades and downgrades. For Standard & Poors data, I show that rating changes with multiple notches provide more information to the market than single notch rating changes. Consistent with prior literature on the business cycle, I show that investors value good news rating changes (upgrades) more in bad times (recession) and that investors value bad news rating changes (downgrades) more in good times (expansion). I model and test probit models using variables capturing the characteristics of the previous issuer’s credit rating, liquidity, solvency, profitability, and growth opportunity to determine the classification of single notch versus multi notch rating changes. The determinants of multi notch versus single notch rating changes for upgrades and downgrades differ. Business cycle influences are evident. Firms that have multi notch rating upgrades and downgrades have significantly different probit variables vis-à-vis firms that have single notch rating upgrades and downgrades. The important characteristics for determining multiple notch upgrades are a firm’s prior rating change, prior rating, cash flow, total assets and market value. The important characteristics for determining multiple notch downgrades are a firm’s prior rating change, prior rating, current ratio, interest coverage, total debt, operating margin, market to book ratio, capital expenditure, total assets, market value, and market beta. The variables that differ for multi notch upgrades in recessions are cash flow, net income, operating margin, market to book ratio, total assets, and retained earnings. The variables that differ for multi notch downgrades in expansions are a firm’s prior rating change, current ratio, interest coverage ratio, debt ratio, total debt, capital expenditure and market beta. The power of the explanatory tests improves when the stage of the business cycle is considered. Results are robust to consideration of rating changes across rating categories, changes from probit to logit, alternative specifications of accounting variables, lags and leads of recessions and expansions timing, Fama and French industry adjustments, and winsorization levels of variables.