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Weak-form rationality of fixed-event forecasts implies that forecast revisions should not be correlated. However, significant positive correlations between consecutive forecast revisions were found in most USDA forecasts for U.S. corn, soybeans, wheat, and cotton. This study developed a statistical procedure for correction of this inefficiency which takes into account the issue of outliers, the impact of forecast size and direction, and the stability of revision inefficiency. Findings suggest that the adjustment procedure has the highest potential for improving accuracy in corn, wheat, and cotton production forecasts.

We extend Vuong’s (1989) model-selection statistic to allow for complex survey samples. As a further extension, we use an M-estimation setting so that the tests apply to general estimation problems – such as linear and nonlinear least squares, Poisson regression and fractional response models, to name just a few – and not only to maximum likelihood settings. With stratified sampling, we show how the difference in objective functions should be weighted in order to obtain a suitable test statistic. Interestingly, the weights are needed in computing the model-selection statistic even in cases where stratification is appropriately exogenous, in which case the usual unweighted estimators for the parameters are consistent. With cluster samples and panel data, we show how to combine the weighted objective function with a cluster-robust variance estimator in order to expand the scope of the model-selection tests. A small simulation study shows that the weighted test is promising.

This study explores the “Sell-in-May” effect in environmental, social and governance (ESG) indices and compares the seasonal effects in ESG equity indices with conventional equity indices.

The authors use ordinary least squares (OLS) models and M-estimation as a robustness check, as OLS estimates may be sensitive to outliers. The authors also employ bootstrap simulations to use the data efficiently and to test whether seasonal trading strategies can produce abnormal returns.

The regression results reveal that seasonal effects in USA ESG equity indices are similar to those in conventional equity indices. Higher returns are noticeable from November through April, mainly in ESG indices including small and medium capitalization stocks. When the authors extend the Sell-in-May strategy from October through April, the authors find that the seasonal effect is significant for multiple ESG indices, even after accounting for the January effect. Bootstrap simulations show that the Sell-in-May and Extended Sell-in-May strategies appear to beat a buy-and-hold strategy on a risk-adjusted basis and that this result is stronger in medium and small capitalization ESG indices.

Although previous research has considered the effectiveness of seasonal equity trading strategies and the general performance of ESG stocks, this is the first study to specifically examine the “Sell in May” effect in ESG indices. The authors also consider an “Extended” Sell-in-May strategy where stocks are purchased one month earlier and show that the strategy produces higher returns.

This study aims to investigate the roles of intellectual capital efficiency and institutional ownership on cash holdings and their speed of adjustment.

Using a sample of 432 firm-year observations of tourism-listed companies, three measures of cash holdings are used as dependent variables and intellectual capital efficiency and institutional ownership as independent variables. The financial data is collected from the S&P Capital IQ database for the period 2015–2020. Two system-generalized methods of moment estimation are used for the robustness checks of the results.

The study provides evidence that an increase in intellectual capital efficiency in tourism firms results in lower cash holdings. The research findings also report that characteristics such as firm size, age and market-to-book value ratio are associated with cash holdings. Furthermore, institutional ownership in these firms did not affect the cash holdings. The results also confirm the existence of a target cash holding level to which the tourism firms attempt to converge. These results are robust to the alternative proxy of cash holding and endogeneity tests.

The study uses intellectual capital efficiency measured by the model proposed by Pulic. Alternative measures of intellectual capital can be included in future studies. Future research can also investigate the impact on cash holdings before and during the pandemic for tourism companies. The study is limited to the impact of institutional ownership; thus, research can be extended to consider other types of ownership.

The findings of this study indicate that tourism companies should take into account the impact of intellectual capital efficiency on their cash holding decisions. The industry uses a specific financial management strategy in light of better efficiency and possibly values the opportunity cost of holding more cash. Additionally, regulators should re-examine the role of institutional ownership in tourism firms, as it was found to have no impact on cash holdings. The regulators may need to consider other factors, such as firm size and age, when developing policies and regulations to ensure that tourism firms have adequate cash holdings.

This study adds to the body of knowledge on the factors that influence cash management and ideal cash levels for the tourism industry. The examination of the effect of intellectual capital on cash holdings is a novel contribution, filling a gap in the existing literature. The findings on the speed of adjustment towards optimal cash holdings also provide support for the trade-off theory.

The authors evaluate the Sell in May effect in the Canadian context to comprehensively explore the Sell in May effect as well as its interactions with the size effect and risk and with multiple indices.

The authors use ordinary least squares (OLS) regressions to examine the Sell in May effect and Huber M-estimation to handle potential outliers. They also use the generalized autoregressive conditional heteroskedasticity (GARCH) models to explore the role of risk in the Sell in May effect.

The results demonstrate that the Sell in May effect is present in all three main Canadian stock market indices. More telling, the anomaly is strongest in small cap indices and in indices that give equal weighting to small and large cap stocks. They do not find that the effect is driven by risk.

While several papers have explored the Sell in May phenomenon in several countries, little scholarly attention has been paid to this effect in Canada and to its interaction with the size effect. The authors contribute to the literature by examining of the interactions between Sell in May and the size effect in Canada. They examine the Sell in May effect using CFMRC value-weighted and equally weighted indices of all Canadian companies. They also incorporate in their analysis the role of risk.

The purpose of this study is to scrutinize the effects of entropy generation and nonlinear mixed convection on the boundary layer flow of second grade fluid induced by stretching sheets. Heat transfer effects are accounted in view of viscous dissipation and nonlinear thermal radiation.

Optimal homotopic asymptotic method procedure is adopted to obtain the analytical solution of nonlinear ordinary differential equations.

It has been noticed that Hartmann and Brinkman number has reverse characteristics against entropy generation and Bejan number.

To the best of the authors’ knowledge, no such analysis has been reported to date.

Congress passed the Stop Trading on Congressional Knowledge (STOCK) Act of 2012, vesting the Securities and Exchange Commission with the clear legal authority to prosecute members of Congress (politicians) if they engage in insider trading. This paper aims to investigate whether members of Congress are informed traders even before they get elected to Congress, and thus helps assess whether the STOCK Act was a necessary piece of legislation.

This study compares the performance of politicians’ portfolios before and after they are elected to Congress using data from the 2004-2010 period. The authors use an event-study method to construct transactions-based calendar-time portfolios and use standard asset pricing models including capital asset pricing model (CAPM) to determine whether these portfolios earn abnormal returns (i.e. outperform the market).

The authors find weak and inconsistent evidence of abnormal returns in politicians’ portfolios that precede their election. They also find that it takes two consecutive terms in Congress for members to start making informed trades that earn themselves abnormal returns. However, these abnormal returns only accrue to those who serve on powerful committees.

The results in this paper provide support for the STOCK Act of 2012 by showing that members of Congress become informed traders while they serve in Congress. However, these results do not imply any wrongdoing for members of Congress, because the paper uses the pre-STOCK Act data (2004-2010 period).

This study is the first academic work that compares politicians’ portfolios before and after they get elected.

This study aims to investigate the day-of-the-week (DoW) effect in globally listed private equity (LPE) markets using daily data covering the period 2004–2021.

To investigate the existence of the DoW effect in globally LPE markets, ordinary least squares regression, generalised autoregressive conditional heteroscedasticity (GARCH) regression and robust regressions are used. In addition, robustness audits are conducted by subdividing the sampling period into two sub-periods: pre-financial and post-financial crisis.

Limited statistically significant evidence is found for the DoW effect. By taking time-varying volatility into account, a statistically significant DoW effect can be observed, indicating that the DoW effect is driven by time-varying volatility. Economic significance is captured through visual inspection of average daily returns, which illustrate that Monday returns are lower than the other weekdays.

The results have important implications on whether to adopt a DoW strategy for investors in LPE. The findings show that higher returns on selected days of the week for certain indices are possible.

To the best of the author’s knowledge, this paper provides the first study to examine the DoW effect for globally LPE markets by using LPX indices and contributes valuable insights on this growing asset class.