Detecting and Analysing Possible Outliers in Global Stock Market Returns
We employ a Boxplot method for detecting and analyzing outlying daily returns of 14 international stock market indices sampled from around the world. The main objective of the paper is to provide an extensive analysis of the main characteristics, features and effects of the detected outlier returns....
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Taylor & Francis Group
2022-12-01
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| Series: | Cogent Economics & Finance |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23322039.2022.2066762 |
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| author | Ali A. Shehadeh Sadam M. Alwadi Mohammad I. Almaharmeh |
| author_facet | Ali A. Shehadeh Sadam M. Alwadi Mohammad I. Almaharmeh |
| author_sort | Ali A. Shehadeh |
| collection | DOAJ |
| description | We employ a Boxplot method for detecting and analyzing outlying daily returns of 14 international stock market indices sampled from around the world. The main objective of the paper is to provide an extensive analysis of the main characteristics, features and effects of the detected outlier returns. The results show that from about 4–10% of observations constitute outlying returns with an average of 6%. Conservatively, about 1.4% of return series are extreme outliers. Negative outliers are found more frequent, influential, severe and transmissible. The bulk of detected outliers are found to be in the magnitude of three standard deviations. Also, outliers tend to cluster together, both within individual return series over time and across stock markets. We find a sequential pattern in outlier occurrence within individual return series, and a concurrent pattern across stock markets. Moreover, adjusting for outlying returns leads to a decrease in standard deviation, negative skewness and kurtosis by about 18%, 74% and 69% on average, respectively. We do not find consistent evidence that advanced and well-developed stock markets have less frequent and/or sever outliers. Overall, the results and analysis of the paper provide important considerations about international stock market returns which are relevant to stock investment, portfolio and risk management. The results show that the best (worst) outlying returns which represent about only 1% of the return observations have an enormous effect on the stock return performance and realization. |
| format | Article |
| id | doaj-art-4f60cdbc323c41a6a64197e5011da3de |
| institution | DOAJ |
| issn | 2332-2039 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Economics & Finance |
| spelling | doaj-art-4f60cdbc323c41a6a64197e5011da3de2025-08-20T03:12:56ZengTaylor & Francis GroupCogent Economics & Finance2332-20392022-12-0110110.1080/23322039.2022.2066762Detecting and Analysing Possible Outliers in Global Stock Market ReturnsAli A. Shehadeh0Sadam M. Alwadi1Mohammad I. Almaharmeh2Department of Finance, The University of Jordan/Aqaba, Aqaba, JordanDepartment of Finance, The University of Jordan/Aqaba, Aqaba, JordanDepartment of Accounting , The University of Jordan/Aqaba, Aqaba, JordanWe employ a Boxplot method for detecting and analyzing outlying daily returns of 14 international stock market indices sampled from around the world. The main objective of the paper is to provide an extensive analysis of the main characteristics, features and effects of the detected outlier returns. The results show that from about 4–10% of observations constitute outlying returns with an average of 6%. Conservatively, about 1.4% of return series are extreme outliers. Negative outliers are found more frequent, influential, severe and transmissible. The bulk of detected outliers are found to be in the magnitude of three standard deviations. Also, outliers tend to cluster together, both within individual return series over time and across stock markets. We find a sequential pattern in outlier occurrence within individual return series, and a concurrent pattern across stock markets. Moreover, adjusting for outlying returns leads to a decrease in standard deviation, negative skewness and kurtosis by about 18%, 74% and 69% on average, respectively. We do not find consistent evidence that advanced and well-developed stock markets have less frequent and/or sever outliers. Overall, the results and analysis of the paper provide important considerations about international stock market returns which are relevant to stock investment, portfolio and risk management. The results show that the best (worst) outlying returns which represent about only 1% of the return observations have an enormous effect on the stock return performance and realization.https://www.tandfonline.com/doi/10.1080/23322039.2022.2066762Outliersoutliers in stock returnsBoxplotstock investmentinternational stock marketsdaily stock market returns |
| spellingShingle | Ali A. Shehadeh Sadam M. Alwadi Mohammad I. Almaharmeh Detecting and Analysing Possible Outliers in Global Stock Market Returns Cogent Economics & Finance Outliers outliers in stock returns Boxplot stock investment international stock markets daily stock market returns |
| title | Detecting and Analysing Possible Outliers in Global Stock Market Returns |
| title_full | Detecting and Analysing Possible Outliers in Global Stock Market Returns |
| title_fullStr | Detecting and Analysing Possible Outliers in Global Stock Market Returns |
| title_full_unstemmed | Detecting and Analysing Possible Outliers in Global Stock Market Returns |
| title_short | Detecting and Analysing Possible Outliers in Global Stock Market Returns |
| title_sort | detecting and analysing possible outliers in global stock market returns |
| topic | Outliers outliers in stock returns Boxplot stock investment international stock markets daily stock market returns |
| url | https://www.tandfonline.com/doi/10.1080/23322039.2022.2066762 |
| work_keys_str_mv | AT aliashehadeh detectingandanalysingpossibleoutliersinglobalstockmarketreturns AT sadammalwadi detectingandanalysingpossibleoutliersinglobalstockmarketreturns AT mohammadialmaharmeh detectingandanalysingpossibleoutliersinglobalstockmarketreturns |