Book-to-Market Ratio, return on equity and Brazilian Stock Returns

Abstract

Purpose This study aims to analyze the influence of future expectations of the book-to-market ratio (B/M) and return on equity (ROE) in explaining the Brazilian capital market returns. Design/methodology/approach The study analyzed the explanatory power of risk-factor approach variables such as beta, size, B/M ratio, momentum and liquidity. Findings The results show that future expectations of the B/M ratio and ROE, when combined with proxies for risk factors, were able to explain part of the variations of Brazilian stock returns. With respect to risk factors approach variables, the authors verified the existence of size and B/M effects and a liquidity premium in the Brazilian capital market, during the period analyzed. Research limitations/implications This research was limited to the non-financial companies with shares traded at Brasil, Bolsa and Balcão, from January 1, 1995 to June 30, 2015. This way, the conclusions reached are limited to the sample used herein. Practical implications The evidences herein presented can also contribute to establishing investment strategies, considering that the B/M ratio may be calculated through accounting information announced by companies. Besides, using historical data enable investors, in a specific year, to calculate the predictor variables for the B/M ratio and ROE in the next year, which enhance the explanatory power of the current B/M, when combined in the form of an aggregate predictor variable for stock returns. Originality/value The main contribution of this study to the literature is to demonstrate how the expected future B/M ratio and ROE may improve the explanatory capacity of the stock return, when compared with the variables traditionally studied in the literature.

The relevance of earning‐to‐price and ROE predictability for explaining Shenzhen stock exchange (SZSE), returns in China: A dynamic panel data approach

“…Under the static approach, the ROEF was consistent with the expected result, and its coefficient was significant at the 5% level in DKSE and PCSE. It does, however, have a higher coefficient value (0.0032) at the 1% level in sys‐GMM, which is consistent with the findings of (Clubb & Naffi, 2007), (Skogsvik & Skogsvik, 2010), and (Cordeiro & André, 2018). By incorporating forecasted ROE (in addition to E/P), we can control cross‐sectional firm variation in current E/P caused by differences in short‐term fundamental analysis expectations for SZSE market returns.…”

“…Aggregate predictor (FRM) and control variables were implemented with the same result as individual predictor and control variables testing. However, the combined technique produces more efficient results than either the fundamental or risk‐based approach alone, as the coefficient of determination (R 2 ) remains higher at 0.643 compared to the value in Table 7, which is consistent with the findings of (Clubb & Naffi, 2007; Cordeiro da Cunha Araújo & André Veras Machado, 2018). These findings support the author's hypothesis that the aggregate predicted variable (FRM) with EPF and ROEF could fully explain a portion of the variation in SZSE returns.…”

“…By incorporating forecasted ROE (in addition to E/P), we can control cross‐sectional firm variation in current E/P caused by differences in short‐term fundamental analysis expectations for SZSE market returns. Additionally, the coefficient of determination of 0.0190 was deficient compared to (Clubb & Naffi, 2007) R 2 of 0.0932 and (Cordeiro & André, 2018) R 2 of 0.0287. The lagged stock return (L.RE) was also significant at the 1% level with a positive coefficient (0.0309), allowing us to overcome the issue of the weak instrument by inducing an internal instrument to deal with the endogeneity issue, resulting in unbiased and reliable findings (Verbeek, 2008).…”

“…They demonstrated that by including forecasted ROE (in addition to BM), they could control cross‐sectional firm variation in current BM, which is caused by differences in short‐term fundamental analysis expectations for UK market returns. Additionally, Cordeiro and André (2018) replicate Clubb and Naffi (2007) work on the Brazilian stock market and find that BM was insignificant in explaining stock variation in the Brazilian market when viewed through the FV perspective but became statistically significant when combined with a risk proxy variable in a combined valuation approach. They substantiate that BM and its predicted variable are more useful for controlling stock return variation.…”

The Impact of Fundamental Factors on the Share Price of Micro-Sized Nasdaq Listed Technology Companies

“…Globally, a large number of empirical pieces of evidence have shown that the fundamental factors have a significant effect on the stock price (Nautiyal & Kavidayal, 2018). Numerous studies have used these financial ratios, such as leverage ratio, return on equity, current ratio, debt to equity ratio, earning per share, return on asset, operating cash flows, net profit margin, firm size, and total assets turnover, to evaluate their impact on the share price (Araújo & Machado, 2018;Chasmi & Fadaee, 2016;Gautam, 2017;Khan et al, 2019;Medyawati & Yunanto, 2020;Milošević-Avdalović, 2018;Ramadianto & Fuadati, 2019;Vijayakumar, 2010). However, there have not been many conclusive results provided by the previous studies conducted to determine the relationship between these variables and share price (Saleh, 2015).…”