Sell-in-May-and-Go-Away in the U.S. Equity Index Futures Markets, 1993–2019

Dzhabarov, Constantine; Ziemba, William T.

doi:10.1142/9789811222634_0010

Cited by 1 publication

(4 citation statements)

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“…This result holds in both Tables 6 and 7 (baseline simulation, simulation with random draws by month, and extended holding period from October through April). The significant outperformance in ESG indices appears in small and medium capitalization ESG equity indices, which is consistent with the results of recent studies showing superior performance of monthly seasonal strategies using the Russell 2000 index, as opposed to investing in large cap indices (Dzhabarov and Ziemba, 2020).…”

Section: Trading Strategies Simulationsupporting

confidence: 90%

“…This result holds in both Tables 6 and 7 (baseline simulation, simulation with random draws by month, and extended holding period from October through April). The significant outperformance in ESG indices appears in small and medium (Dzhabarov and Ziemba, 2020). Lastly, since bid-ask spreads and commissions have been decreasing over time, we test the profitability of the trading strategies at lower transaction cost levels.…”

Section: Sell-in-may and Esg Indicesmentioning

confidence: 99%

“…Tsagkanos and Zachouris (2014) do not find a significant Halloween effect in the S&P 500 (which consists of large-cap stocks), but they do find one in the Russell 2000 (which consists of small capitalization stocks). Dzhabarov and Ziemba (2020) similarly use data from 1993 to 2019 to show that applying the Sell-in-May strategy to the Russell 2000 index produces superior returns compared to a buy-and-hold strategy.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Maberly and Pierce, 2004;Lucey and Zhao, 2008). Furthermore, a few studies have found differences in the seasonal effects of equity indices with different market capitalization, with the Sell-in-May strategy beating buy-and-hold using small capitalization equity indices (Tsagkanos and Zachouris, 2014;Dzhabarov and Ziemba, 2020). Some of the proposed explanations for the observed seasonality in returns include market behavior during summer vacation periods (Bouman and Jacobsen, 2002), temperature-based mood (Cao and Wei, 2005), depression and seasonal affective disorder (Kamstra et al, 2003), and investor optimism during the last quarter (Doeswijk, 2008).…”

Section: Introductionmentioning

confidence: 99%

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The Sell-in-May effect in ESG indices

Pavlova

Whitworth

Boyrie

2022

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PurposeThis 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.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueAlthough 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.

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Section: Trading Strategies Simulationsupporting

confidence: 90%

“…This result holds in both Tables 6 and 7 (baseline simulation, simulation with random draws by month, and extended holding period from October through April). The significant outperformance in ESG indices appears in small and medium (Dzhabarov and Ziemba, 2020). Lastly, since bid-ask spreads and commissions have been decreasing over time, we test the profitability of the trading strategies at lower transaction cost levels.…”

Section: Sell-in-may and Esg Indicesmentioning

confidence: 99%