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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.

In this paper, the authors examine the interconnectedness of four blockchain exchange-traded funds (ETFs) with other financial markets, such as stocks and cryptocurrencies.

A multivariate dynamic conditional correlation model is used to model the relationship of blockchain ETFs with equity and cryptocurrency markets. Risk-minimizing hedge ratios are calculated following the methods used in studies by Kroner and Sultan (1993) and Sadorsky (2012).

The empirical results show a high degree of correlation of blockchain ETF returns with returns of the NASDAQ Composite Index, while the level of comovement with Bitcoin is relatively low.

The results imply that blockchain ETFs may be suitable for hedging purposes in a portfolio holding Bitcoin. Furthermore, investing in blockchain ETFs appears similar to investing in NASDAQ.

To the best of the authors’ knowledge, no studies have investigated the dynamic relationship of blockchain ETFs and other financial assets.

This paper investigates the impact of financial technology innovation on bank performance. Using a large sample of FinTech mergers and acquisitions (M&A) deals by major and regional US banks as well as artificial intelligence (AI) patent applications and grants by banks from 2010 to 2022, their impact on bank return on assets (ROA) and return on equity (ROE) is explored.

System GMM estimators created for dynamic panel models are employed to evaluate the impact of a bank’s acquisitions of technology-oriented, AI and FinTech corporations and the filing of technology-oriented patents on profitability.

A positive association between the number of FinTech M&A deals and bank performance is documented; however, none of the patent variables (grant, filing or publication) appear to have a significant effect.

A large sample of FinTech M&A deals and patents by US major and regional banks is used to study the impact on bank performance. A comprehensive empirical analysis is performed while controlling for bank size and other bank characteristics.

The purpose of this paper is to consider two global real estate periods (2000‐2006 and 2007‐2008) that will probably be recorded in history as the most significant periods in terms of a surge and then an eventual downturn in the real estate prices and returns. The paper aims to offer investment strategies in the real estate sector and pinpoint the optimum momentum strategies that provide the maximum returns in the real estate investment trusts (REITs) markets of seven countries.

Within an iterative framework, a two‐step procedure was employed. The first step drew upon an established momentum approach. The second step, however, departed from it and employed an evolutionary (genetic) algorithm to optimize the investment strategies that could be pursued.

The findings suggest that momentum effects have been present during the 2000‐2008 periods. However, in contrast with prior studies, momentum portfolio returns are statistically insignificant during the boom years, but are highly significant during the downturn periods. These findings are attributed to the heterogeneous returns during these periods.

Profitable REITs momentum investment is not uniform across the countries considered. Taking long positions in the winners and short positions in the losers during the boom periods in the real estate market may not necessarily be an optimum strategy. Since the profitability of the investment strategy during the downturn is driven by short positions, the practical implementation of such strategy will be limited if short sales constraints are imposed.

The paper employs a unique and novel approach for the first time in the field of real estate investment. It introduces genetic algorithm into the momentum literature. This approach pinpoints the optimum profitability of the momentum/persistence strategies that could be pursued.

The purpose of this paper is to examine the relationship between naked short selling and accounting irregularities that cause a firm to issue a restatement.

Using the level of abnormal fails-to-deliver as a proxy for naked short selling, the paper looks for evidence of increased naked short selling in anticipation of, as well as in response to these announcements.

Larger firms and firms with a higher percentage of institutional ownership experience greater levels of fails prior to the announcement day, while smaller firms are more likely to be targets of naked short sellers after the announcement. The paper also finds that more transparent announcements are associated with more abnormal fails.

This paper is the first research to study the relation between naked short selling and accounting restatements.