Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market
The primary objective of this paper is to empirically examine the nature and statistical significance of the news effect on conditional volatility of unpredictable components of stock returns. Daily stock return data of 12 local and multinational companies on Dhaka Stock Exchange Ltd., Bangladesh, f...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2022-10-01
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| Series: | SAGE Open |
| Online Access: | https://doi.org/10.1177/21582440221127157 |
| _version_ | 1811181710009696256 |
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| author | Shekar Bose Hafizur Rahman |
| author_facet | Shekar Bose Hafizur Rahman |
| author_sort | Shekar Bose |
| collection | DOAJ |
| description | The primary objective of this paper is to empirically examine the nature and statistical significance of the news effect on conditional volatility of unpredictable components of stock returns. Daily stock return data of 12 local and multinational companies on Dhaka Stock Exchange Ltd., Bangladesh, for the period 1990 to 2011 were used in this study. The likelihood of asymmetric effects of news on conditional volatility was tested using a set of diagnostics under the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) framework. The results fail to reject the null hypothesis of symmetric effects, thereby suggesting that the conditional volatility of unpredictable components of stock returns is affected equally by positive and negative news. The robustness of the results was further checked by using three widely used asymmetric models, namely exponential GARCH (EGARCH), Glosten, Jagannathan & Runkle (GJR)-GARCH, and a partially non-parametric Autoregressive Conditional Heteroscedastic (PNP-ARCH) models. Yet again, the results do not provide any evidence of significant asymmetric effects in the volatility process. In addition, the descriptive results confirm the stylized facts of unpredictable return series such as non-normal distribution, time variant conditional volatility, and persistence in return volatility. Collectively these findings, perhaps, indicate the adequacy of the GARCH (1,1) model in representing the data generating process. A number of regulatory and behavioral factors that are anticipated to be accountable for the absence of asymmetric news effects are underlined. Finally, some policy implications of the results and possible extensions of the present paper are also conveyed. JEL codes: G10, G12, G14 |
| first_indexed | 2024-04-11T09:22:04Z |
| format | Article |
| id | doaj.art-ffd6efb064de45afad966e9a322548e0 |
| institution | Directory Open Access Journal |
| issn | 2158-2440 |
| language | English |
| last_indexed | 2024-04-11T09:22:04Z |
| publishDate | 2022-10-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | SAGE Open |
| spelling | doaj.art-ffd6efb064de45afad966e9a322548e02022-12-22T04:32:11ZengSAGE PublishingSAGE Open2158-24402022-10-011210.1177/21582440221127157Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock MarketShekar Bose0Hafizur Rahman1Independent Researcher, Brisbane City, QLD, AustraliaThompson Rivers University, Kamloops, BC, CanadaThe primary objective of this paper is to empirically examine the nature and statistical significance of the news effect on conditional volatility of unpredictable components of stock returns. Daily stock return data of 12 local and multinational companies on Dhaka Stock Exchange Ltd., Bangladesh, for the period 1990 to 2011 were used in this study. The likelihood of asymmetric effects of news on conditional volatility was tested using a set of diagnostics under the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) framework. The results fail to reject the null hypothesis of symmetric effects, thereby suggesting that the conditional volatility of unpredictable components of stock returns is affected equally by positive and negative news. The robustness of the results was further checked by using three widely used asymmetric models, namely exponential GARCH (EGARCH), Glosten, Jagannathan & Runkle (GJR)-GARCH, and a partially non-parametric Autoregressive Conditional Heteroscedastic (PNP-ARCH) models. Yet again, the results do not provide any evidence of significant asymmetric effects in the volatility process. In addition, the descriptive results confirm the stylized facts of unpredictable return series such as non-normal distribution, time variant conditional volatility, and persistence in return volatility. Collectively these findings, perhaps, indicate the adequacy of the GARCH (1,1) model in representing the data generating process. A number of regulatory and behavioral factors that are anticipated to be accountable for the absence of asymmetric news effects are underlined. Finally, some policy implications of the results and possible extensions of the present paper are also conveyed. JEL codes: G10, G12, G14https://doi.org/10.1177/21582440221127157 |
| spellingShingle | Shekar Bose Hafizur Rahman Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market SAGE Open |
| title | Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market |
| title_full | Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market |
| title_fullStr | Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market |
| title_full_unstemmed | Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market |
| title_short | Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market |
| title_sort | are news effects necessarily asymmetric evidence from bangladesh stock market |
| url | https://doi.org/10.1177/21582440221127157 |
| work_keys_str_mv | AT shekarbose arenewseffectsnecessarilyasymmetricevidencefrombangladeshstockmarket AT hafizurrahman arenewseffectsnecessarilyasymmetricevidencefrombangladeshstockmarket |