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The book-to-market (BM) ratio differs across stocks because to differences in expected cashflows and expected returns. The central hypothesis is that the evolution of BM, in terms of past changes in price and book equity, contains information about future cashflows that can be used to improve estimates of expected returns. This article used a database of Economática to extract a sample of non-financial companies shares listed on BOVESPA and test this hypothesis. The estimated regressions were performed monthly during the period July 1996 to June 2008. Both for large and mid caps as for small caps, the results do not favor this hypothesis and show that only the most recent BM is important to predict the assets returns. Furthermore, stock issues and repurchases are also related to future cashflows and it is expected to improve estimates of expected returns. However, the results provide no evidence favoring that.

The Halloween effect relates to the notion that stock market returns tend to be higher in the period from November to April than from May to October. In this study, we analyze the robustness of this trading strategy taking into account the individual returns of stocks traded in the Brazilian stock market during the period from August 1994 to June 2014. Using standard dummy regression approach introduced by Bouman and Jacobsen (2002), our results suggest the existence of the Halloween effect in the Brazilian market, which has shown to be economically and statistically significant, with a positive sign and a slight drop trend over the past few years. In addition, when reassessing these results using the "Superior Predictive Ability Test" of Hansen (2005), we have found that an investment strategy based on the Halloween effect generates a statistically significant returns superior to a buy-and-hold strategy when the effects of data-snooping when data-snooping effects are not neglected in the stock returns series, as in Bouman and Jacobsen (2002).

In this paper, we use the information from the credit default swap market to measure the main components of the oil and gas companies spread. Using nearly 20 companies of this industry with different ratings and nearly 80 bonds, the result was that the majority of the oil and gas spread is due to the default risk. We also find that the spread component related to the non-default is strongly associated with some liquidity measures of bond markets, what suggest that liquidity has a very important role in the valuation of fixed income assets. On the other side, we do not find evidence that the non-default component of the spread is related to tax matters.

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