Predictability of stock market returns: Evidence from Eurozone's banking sectors

This paper analyzes the in-, and out-of sample, predictability of the stock market returns from Eurozone’s banking sectors, arising from bank-specific ratios and macroeconomic variables, using panel estimation techniques. In order to do that, I set an unbalanced panel of 116 banks returns, from April, 1991, to March, 2013, to constitute equal-weighted country-sorted portfolios representative of the Austrian, Belgian, Finish, French, German, Greek, Irish, Italian, Portuguese and Spanish banking sectors. I find that both earnings per share (EPS) and the ratio of total loans to total assets have in-sample predictive power over the portfolios’ monthly returns whereas, regarding the cross-section of annual returns, only EPS retain significant explanatory power. Nevertheless, the sign associated with the impact of EPS is contrarian to the results of past literature. When looking at inter-yearly horizon returns, I document in-sample predictive power arising from the ratios of provisions to net interest income, and non-interest income to net income. Regarding the out-of-sample performance of the proposed models, I find that these would only beat the portfolios’ historical mean on the month following the disclosure of year-end financial statements. Still, the evidence found is not statistically significant. Finally, in a last attempt to find significant evidence of predictability of monthly and annual returns, I use Fama and French 3-Factor and Carhart models to describe the cross-section of returns. Although in-sample the factors can significantly track Eurozone’s banking sectors’ stock market returns, they do not beat the portfolios’ historical mean when forecasting returns.

Reporting cash flow evidence from campanies listed in the Euronext Lisbon

Based on the 2013 and 2014 consolidated statements of cash flows of companies listed in Euronext Lisbon, this Work Project analyses the cash flow disclosures, namely if they are in accordance with International Accounting Standards 7, specifically the format, the choice of classification interests, dividends paid and received and the composition of cash and cash equivalents. Additionally, quality of income ratio is analyzed due to its importance for users of financial statements. The results show evidence of uniformity and consistency in the use of the direct method for reporting operational activities in both years, but there are some differences regarding the disclosure of interests and dividends, paid and received, respectively.

Portraying the Portuguese Foundation Sector

Foundations’ importance in the actual economy has been increasingly recognized. This work project assesses the impact of the new legal framework in the foundations’ financial reporting and offers a financial statement analysis of the Portuguese foundational sector. It unveils links between financial performance and characteristics of foundations, and profiles foundations in three clusters, each with different approaches to disclosure, volunteer workforce, and taxes. It is concluded that foundations are not respecting the benefits trusted to them, calling for a tighter control to their financial reporting, and that even though that slowly, the sector is expected to continue growing.

Graph usage in annual reports, evidence from Norwegian listed companies

As investors and other users of annual reports often focus their attention on graphs, it is important that they portray accurate and reliable information. However, previous studies show that graphs often distort information and mislead users. This study analyses graph usage in annual reports from the 52 most traded Norwegian companies. The findings suggest that Norwegian companies commonly use graphs, and that the graph distortions, presentational enhancement and measurement distortion, are present. No evidence of selectivity was found. This study recommends development of guidelines for graphical disclosure, and advises preparers and users of annual reports to be aware of misleading graphs.