Flávio Leonel de Carvalho

The relationship between earnings quality and the probability of efficient investment decisions in Latin America

Increased conflicts of interest between managers and shareholders may result from information asymmetry. However, the literature has demonstrated that high-quality accounting information can reduce both the probability of information asymmetry and the problems created therein. In this context, few studies have analysed the impact of earnings quality on investment decisions, particularly in less-developed economies. Thus, this study aims to verify whether the earnings quality of Latin American companies affects the probability of efficient investment decisions, over-investments, and the probability of under-investment. For this purpose, a logit model was used, and data from the companies of seven Latin American countries were analysed. The results indicate that poor earnings quality reduces the probability of efficient investment decisions and increases the probability of under-investment. Thus, our primary conclusion is that there is evidence that high-quality accounting information influences the investment decisions of companies in Latin America.

Portfolio optimization using Mean Absolute Deviation (MAD) and Conditional Value-at-Risk (CVaR)

This paper investigates the efficiency of traditional portfolio optimization models when the returns of financial assets are highly volatile, e.g., in financial crises periods. We also develop alternative optimization models that combine the mean absolute deviation (MAD) and the conditional value at risk (CVaR), attempting to mitigate inefficient, low return and/or high-risk, portfolios. Three methodologies for estimating the probability of the asset’s historical returns are also compared. By using historical data on the Brazilian stock market between 2004 and 2013, we analyze the efficiency of the proposed approaches. Our results show that the traditional models provide portfolios with higher returns, but our propose model are able to generate lower risk portfolios, which might be more attractive in volatile markets. In addition, we find that models that do not use equiprobable scenarios produce better results in terms of return and risk.