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Investors label high (low) book-to-market (B/M) firms as value (growth) companies. The conventional wisdom supports that growth stocks grow faster than the value ones, creating greater shareholder value. The Purpose of this paper is to analyze how stocks of growth and value companies create value for their shareholders in Brazil, compared to the USA market. For this, the authors analyze three dimensions of return.

First, the authors perform portfolios to analyze the growth rates of shareholders’ return. Then, the authors perform regressions to study the explanatory power of the B/M in growth. The data come from Thomson Reuters Eikon database and the Brazilian Institute of Geography and Statistics. The authors select all non-financial firms with available data from 1997 to 2017.

The profitability of growth firms is higher than the value ones, in almost every year after the portfolios’ formation, with little variation. Contrary to the findings for the US market, growth companies in Brazil show higher dividend growth than value companies.

It is possible that the database does not contain complete and entirely reliable accounting data, which may partially affect the results.

The findings contradict those exposed in the USA. The implications are the inverse of the US study: the duration-based explanation could be a vital factor for the value premium in the Brazilian stock market. Also, the findings support the standard valuation techniques and help the growth rates estimation in the valuation process (top-down approach).

This study is the first to compare the profitability and dividend growth of growth/value stocks in the Brazilian market. Overall, growth stocks have considerable profitability, and dividend growth compared to value stocks.

The purpose of this paper is to investigate whether market conditions have an effect on investors’ propensity to herd in an emerging economy’s stock market. Additionally, given the lack of research on Islamic behavioral finance, the authors further investigate if the herding phenomenon is distinct in Islamic versus conventional stocks.

The authors used daily data for the period of 1995–2016 according to the herding behavior model of Chang et al. (2000), which relies on cross-sectional absolute deviation of returns.

Findings reveal the herding behavior of investors among Shariah-compliant during up and down market exits with non-linear relationship to the market return, while for conventional stocks herding behavior does not exist with linear nor nonlinear relationships during the up and down market. Furthermore, for the whole market, herding behavior only exists during upmarket with a nonlinear relationship to the market return. However, this relationship is not significant. Moreover, the results of this study are robust with respect to the effect of the Asian and global financial crisis.

The findings are useful for investors to identify which market conditions are associated with rational and irrational behavior of investors.

Most of the theoretical and empirical studies on herding behavior have focused on developed countries. Only a few studies have paid attention to the herding behavior in Islamic financial markets, particularly in the context of an emerging market such as Malaysia. This study fills this void.

The Chinese fund market has witnessed significant developments in recent years. However, although there has been a range of studies assessing fund performance in developed industries, the rapidly developing fund industry in China has received very little attention. This study aims to examine the performance of open-end securities investment funds investing in Chinese domestic equity during the period May 2003 to September 2020. Specifically, applying a non-parametric bootstrap methodology from the literature on fund performance, the authors investigate the role of skill versus luck in this rapidly evolving investment funds industry.

This study evaluates the performance of Chinese equity securities investment funds from 2003–2020 using a bootstrap methodology to distinguish skill from luck in performance. The authors consider unconditional and conditional performance models.

The bootstrap methodology incorporates non-normality in the idiosyncratic risk of fund returns, which is a major drawback in “conventional” performance statistics. The evidence does not support the existence of “genuine” skilled fund managers. In addition, it indicates that poor performance is mainly attributable to bad stock picking skills.

The authors find that the top-ranked funds with positive abnormal performance are attributed to “good luck” not “good skill” while the negative abnormal performance of bottom funds is mainly due to “bad skill.” Therefore, sensible advice for most Chinese equity investors would be against trying to “pick winners funds” among Chinese securities investment funds but it would be recommended to avoid holding “losers.” At the present time, investors should consider other types of funds, such as index/tracker funds with lower transactions. In addition, less risk-averse investors may consider Chinese hedge funds [Zhao (2012)] or exchange-traded fund [Han (2012)].

The paper makes several contributions to the literature. First, the authors examine a wide range (over 50) of risk-adjusted performance models, which account for both unconditional and conditional risk factors. The authors also control for the profitability and investment risks in Fama and French (2015). Second, the authors select the “best-fit” model across all risk-adjusted models examined and a single “best-fit” model from each of the three classes. Therefore, the bootstrap analysis, which is mainly based on the selected best-fit models, is more precise and robust. Third, the authors reduce the possibility that findings may be sample-period specific or may be a survivor (upward) biased. Fourth, the authors consider further analysis based on sub-periods and compare fund performance in different market conditions to provide more implications to investors and practitioners. Fifth, the authors carry out extensive robustness checks and show that the findings are robust in relation to different minimum fund histories and serial correlation and heteroscedasticity adjustments. Sixth, the authors use higher frequency weekly data to improve statistical estimation.

National cultures significantly explain cross-country differences in the relation between asset growth and stock returns. Motivated by the notion that managers in individualistic and low uncertainty-avoiding cultures have a higher tendency to overinvest, this study aims to show that the negative relation between asset growth and stock returns is stronger in countries with such cultural features. Once the researchers control for cultural dimensions, proxies associated with the q-theory, limits-to-arbitrage, corporate governance, investor protection and accounting quality provide no incremental power for the relation between asset growth and stock returns across countries. Evidence of this study highlights the importance of the overinvestment hypothesis in explaining the asset growth anomaly around the world.

The purpose of this paper is to consider the economic information content within several popular stock market factors and to the extent to which their movements are both explained by economic variables and can explain future output growth.

Using US stock portfolios from 1964 to 2019, the authors undertake three related exercises: whether a set of common factors contain independent predictive ability for stock returns, what economic and market variables explain movements in the factors and whether stock market factors have predictive power for future output growth.

The results show that several of the considered factors do not contain independent information for stock returns. Further, most of these factors are neither explained by economic conditions nor they provide any predictive power for future output growth. Thus, they appear to contain very little economic content. However, the results suggest that the impact of these factors is more prominent with higher macroeconomic risk (contractionary regime).

The stock market factors are more likely to reflect existing market conditions and exhibit a weaker relation with economic conditions and do not act as a window on future behavior.

Fama and French three-factor model still have better explanations for stock returns and economic information more than any other models.

This paper contributes to the literature by examining whether a selection of factors provides unique information when modelling stock returns data. It also investigates what variables can predict movements in the stock market factors. Third, it examines whether the factors exhibit a link with subsequent economic output. This should establish whether the stock market factors contain useful information for stock returns and the macroeconomy or whether the significance of the factor is a result of chance. The results in this paper should advance our understanding of asset price movement and the links between the macroeconomy and financial markets and, thus, be of interest to academics, investors and policy-makers.

The authors analyse a growth model to explain how economic fluctuations are primarily driven by productive capacities (i.e. capacity utilization driven by innovations and know-how) and productive inefficiencies.

This study’s methodology consists of the combination of the economic growth model, à la Solow–Swan, with a sigmoidal production function (in capital), which may explain growth, poverty traps or fluctuations depending on the relative levels of inefficiencies, productive capacities or lack of know-how.

The authors show that economies may experience economic growth, poverty traps and/or fluctuations (i.e. cycles). Economic growth is reached when an economy experiences both a low level of inefficiencies and a high level of productive capacities while an economy falls into a poverty trap when there is a high level of inefficiencies in production. Instead, the economy gets in cycles when there is a large level of the lack of know-how and low levels of productive capacity.

The authors conclude that more capital per capita (greater savings and investment) and greater productive capacity (with less lack of know-how) are the economic policy keys for an economy being on the path of sustained economic growth.

The purpose of this study is to examine herd behaviour under different market conditions, examine the potential impact of the firm size and stock characteristics on this relationship, and explore how herding affects market prices in the German market.

The authors apply a method that does not rely on theoretical models, thus eliminating the biases inherent in their application. This technique is based on the assumption that macro herding manifests itself in the synchronicity (comovement) of stock returns.

The study’s findings show that herding is more pronounced in down markets and is more pronounced when market returns reach extreme levels. Additionally, the authors have found that there is stronger herding among large companies compared to small companies, and that stock characteristics considered have no effect on the degree of macro herding. Results also suggest that the contemporaneous market-wide information drives macro herding and that macro herding facilitates the incorporation of market-wide information into prices.

The study’s results strongly support the idea of directional asymmetry, which holds that stocks react quickly to negative macroeconomic news while small stocks react slowly to positive macroeconomic news. Additionally, the study’s results suggest that the contemporaneous market-wide information drives macro herding and that macro herding facilitates the rapid incorporation of market-wide information into prices.

To the best of the researchers’ knowledge, this is the first study that examines macro herding for a major financial market using a herding measure based on the co-movement of returns that does not rely on theoretical models.

The purpose of this paper is to investigate whether sentiment and mood, which are distinct theoretical concepts, can also be distinguished empirically.

Using a sample of German small-cap stocks and linear techniques, the effect of sentiment and mood on short-term abnormal stock return following earnings announcements is tested separately.

Mood tends to be a positive factor in predicting short-term abnormal stock return, as its biologically based impact uniformly affects the risk aversion of all market participants. Notably, negative mood influences stock return significantly negatively. Sentiment is no factor, however, as its cognitively based impact affects only unsophisticated investors, namely, their cash-flow expectations.

As the sample is restricted to small-cap stocks from a single stock market and only two proxies of sentiment and mood, respectively, are used, the findings should be generalized with caution. Future research might investigate other markets and employ different proxies of sentiment and mood.

Market participants should be aware of the different effect of sentiment and mood on stock return and adjust investment strategies accordingly.

As sophisticated investors are likely to profit from the irrational behavior of unsophisticated investors, who are prone to sentiment, the financial literacy of retail investors should be enhanced.

This paper is unique in distinguishing between sentiment and mood, both theoretically and empirically. Such distinction was largely ignored by related past research.

This paper aims to revisit the relationship between intangible capital and labour productivity growth using the largest, up-to-date macro database (2000–2015) available to corroborate the econometric findings of earlier work and to generate novel econometric evidence by accounting for times of crisis (2008–2013) and economic recovery (2014–2015).

To achieve these aims, this paper employs a cross-country growth accounting econometric estimation approach using the largest, up-to-date database available encompassing 16 EU countries over the period 2000–2015. The paper accounts for times of crisis (2008–2013) and of economic recovery (2014–2015). It separately estimates the contribution of three distinct dimensions of intangible capital: (1) computerized information, (2) innovative property and (3) economic competencies.

First, when accounting for intangibles, the paper finds that these intangibles have become the dominant source of labour productivity growth in the EU, explaining up to 66 percent of growth. Second, when accounting for times of crisis (2008–2013), in contrast to tangible capital, the paper detects a solid positive relationship between intangibles and labour productivity growth. Third, when accounting for the economic recovery (2014–2015), the paper finds a highly significant and remarkably strong relationship between intangible capital and labour productivity growth.

This paper corroborates the importance of intangibles for labour productivity growth and thereby underlines the necessity to incorporate intangibles into today's national accounting frameworks in order to correctly depict the levels of capital investment being made in European economies. These levels are significantly higher than those currently reflected in the official statistics.

Recognizing the severity of COVID-19 on the US economy, the authors investigate the behavior of US-listed firms towards leverage speed of adjustment (SOA) during the pandemic. While prior evidence (based on an international study) shows that firm leverage increased during the pandemic leading to a higher SOA toward leverage ratios, leverage for US firms during the same period reduced drastically. Yet there is a dearth of empirical studies on the behavior of US-listed firms' SOA during the pandemic. The authors fill this void.

The study includes US-listed non-financial and non-utility firms for the period 2015Q1-2021Q4, covering a total sample of 45,213 firm-quarter observations. The authors’ empirical strategy is based on the generalized method of moments (GMM) and firm-fixed effect methodology, controlling for firm- and quarter-fixed effects.

Three main findings are established: (1) while the SOA toward book target increased during the pandemic, SOA toward market target increased significantly only for less valued and cash-constrained firms; (2) firms in states most impacted by the pandemic adjusted faster towards target ratio; and (3) while the emergence of the pandemic and the overall firm-level risk increased (decreased) the deviation from book (market) target, firm-level risk partially mediated the effect of the pandemic on how far firms deviated from target ratio.

This study enhances our understanding of leverage adjustment during the crisis and shows that risk avoidance motive and the market value of firms are key determinants of convergence rate during the crisis and further demonstrates that market leverage is more sensitive to market dynamics. As such, caution must be taken when dealing with and interpreting market leverage SOA.

Although prior evidence based on international study provides insights into how firms behave toward their leverage ratios because of the pandemic, little is known about how US firms react to the pandemic in terms of the target ratios, particularly (1) since the USA is one of the severely affected countries and (2) firms in the USA reduced their leverage ratios as against what prior evidence shows. The authors provide evidence to explain how and why US firms reacted toward their SOA during the pandemic.