'Sell in May and Go Away' Just Won't Go Away

Andrade, Sandro C.; Chhaochharia, Vidhi; Fuerst, Michael E.

doi:10.2139/ssrn.2115197

Cited by 12 publications

(15 citation statements)

References 18 publications

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“…Finally, several workers have warned of the dangers of data mining (Sullivan et al, ; Andrade et al, ). Our analysis to discover a possible periodic term requires no fitting procedure and we have kept our out‐of‐sample tests as simple as possible.…”

Section: Discussionmentioning

confidence: 99%

“…This possibility was considered further (Witte, ) and after careful study of outliers it was found that the results of Bouman and Jacobsen () are still marginally statistically significant. More recently, Andrade et al () find that the ‘sell in May’ effect persists in out‐of‐sample tests in all 37 countries studied. Returns on a basket of NYSE and American Stock Exchange (AMEX) listed stocks tend to be high or low in certain months (Heston and Sadka, ) and a regression analysis indicates a yearly periodicity that has persisted for 20 years.…”

Section: Introductionmentioning

confidence: 91%

“…Unusually large returns on New York Stock Exchange (NYSE) listed stocks have been observed during the month of January (Rozeff and Kinney, ). Larger returns have been noted during the months October to May as compared to June to September (Hirsch, ; Bouman and Jacobsen, ; Doeswijk, ; Lucey and Zhao, ; Haggard and Witte, ; Andrade et al, ) for US and overseas large‐cap stocks.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Forecasting Ability of a Periodic Component Extracted from Large‐Cap Index Time Series

O’Shea

2016

Journal of Forecasting

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We develop a method to extract periodic variations in a time series that are hidden in large non‐periodic and stochastic variations. This method relies on folding the time series many times and allows direct visualization of a hidden periodic component without resorting to any fitting procedure. Applying this method to several large‐cap stock time series in Europe, Japan and the USA yields a component with periodicity of 1 year. Out‐of‐sample tests on these large‐cap time series indicate that this periodic component is able to forecast long‐term (decade) behavior for large‐cap time series. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

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Forecasting Ability of a Periodic Component Extracted from Large‐Cap Index Time Series

O’Shea

2016

Journal of Forecasting

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“…The debate continues today. For example, Andrade et al (2013) report that in an out-ofsample period (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012), all countries contained in the Bouman and Jacobsen (2002) study still performed better in November-April than during the rest of the year. Jacobsen and Zhang (2014) expanded the sample of Bouman and Jacobsen (2002) to include data from 109 countries.…”

Section: Halloween Effectmentioning

confidence: 99%

Seasonal anomalies in the market for American depository receipts

Lobão

2019

JEFAS

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Purpose The literature provides extensive evidence for seasonality in stock market returns, but is almost non-existent concerning the potential seasonality in American depository receipts (ADRs). To fill this gap, this paper aims to examine a number of seasonal effects in the market for ADRs. Design/methodology/approach The paper examines four ADRs for the period from April 1999 to March 2017 to look for signs of eight important seasonal anomalies. The authors follow the standard methodology of using dummy variables for the time period of interest to capture excess returns. For comparison, the same analysis on two US stock market indices is conducted. Findings The results show the presence of a highly significant pre-holiday effect in all return series, which does not seem to be justified by risk. Moreover, turn-of-the-month effects, monthly effects and day-of-the-week effects were detected in some of the ADRs. The seasonality patterns under analysis tended to be stronger in emerging market-based ADRs. Research limitations/implications Overall, the results show that significant seasonal patterns were present in the price dynamics of ADRs. Moreover, the findings lend support to the idea that emerging markets are less efficient than developed stock markets. Originality/value This is the most comprehensive study to date for indication of seasonal anomalies in the market for ADRs. The authors use an extensive sample that includes recent significant financial events such as the 2007/2008 financial crisis and consider ADRs with different characteristics, which allows to draw comparisons between the differential price dynamics arising in developed market-based ADRs and in the ADRs whose underlying securities are traded in emerging markets.

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“…Beside these investment strategies that are founded in economic fundamentals, there is also empirical evidence that profitable seasonal anomalies exist. For example, Andrade, Chhaochharia, and Fuerst (), Haug and Hirschey (), and Jacobsen and Zhang () all provide evidence of superior trading strategies based on calendar effects. The explanations of such effects are distinct.…”

Section: Introductionmentioning

confidence: 99%

Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?

Dichtl¹

2019

Rev Financ Econ

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Determining whether investment strategies exist that provide higher (risk‐adjusted) returns than buying and holding the S&P 500 stock market index is not only highly relevant for finance theory, but also for the asset management industry. This study conducts a comprehensive test using realistic investment strategies based on monthly seasonalities, technical indicators, and fundamental factors (over 4,100 strategies in total). To assess statistical significance, we use Hansen's data‐snooping‐resistant SPA test. The results show that only investment strategies trying to exploit underreaction and overreaction effects with technical indicators dominate the buy‐and‐hold strategy in some simulation setups. These investment strategies are clearly superior to the strategies based on seasonalities and fundamental factors. Given that underreaction and overreaction effects are mainly justified with cognitive biases, our results support the economic relevance of behavioral finance insights.

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'Sell in May and Go Away' Just Won't Go Away

Cited by 12 publications

References 18 publications

Forecasting Ability of a Periodic Component Extracted from Large‐Cap Index Time Series

Forecasting Ability of a Periodic Component Extracted from Large‐Cap Index Time Series

Seasonal anomalies in the market for American depository receipts

Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?

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