The impact of Twitter-based sentiment on US sectoral returns
<p dir="ltr">This paper scrutinizes the effect of Twitter-based sentiment on US sectoral returns using data from between 21 June 2010 and 13 April 2020. We apply causality in quantiles as a non-parametric measure, followed by a rolling window wavelet correlation. The former measures...
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| مؤلفون آخرون: | , , |
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2023
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| _version_ | 1864513541608833024 |
|---|---|
| author | Rami Zeitun (17075215) |
| author2 | Mobeen Ur Rehman (15282575) Nasir Ahmad (821439) Xuan Vinh Vo (15353934) |
| author2_role | author author author |
| author_facet | Rami Zeitun (17075215) Mobeen Ur Rehman (15282575) Nasir Ahmad (821439) Xuan Vinh Vo (15353934) |
| author_role | author |
| dc.creator.none.fl_str_mv | Rami Zeitun (17075215) Mobeen Ur Rehman (15282575) Nasir Ahmad (821439) Xuan Vinh Vo (15353934) |
| dc.date.none.fl_str_mv | 2023-01-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.najef.2022.101847 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/The_impact_of_Twitter-based_sentiment_on_US_sectoral_returns/24501133 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Commerce, management, tourism and services Banking, finance and investment Economics Econometrics Information and computing sciences Human-centred computing US sectoral returns Investor sentiments S&P 500 Causality Wavelet correlation |
| dc.title.none.fl_str_mv | The impact of Twitter-based sentiment on US sectoral returns |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">This paper scrutinizes the effect of Twitter-based sentiment on US sectoral returns using data from between 21 June 2010 and 13 April 2020. We apply causality in quantiles as a non-parametric measure, followed by a rolling window wavelet correlation. The former measures the manifestation of causality directed from Twitter-based sentiment towards US sectoral returns, whereas the latter measures the correlation of returns across decomposed series that correspond to different time horizons. Our results highlight symmetric changes in US sectoral returns that vary across different sectors. The healthcare, communications, materials, consumer discretionary, energy, staples, and information technology sectors are more sensitive to changes in Twitter-based sentiment across all quantiles. Our findings from the rolling window wavelet correlation point to low correlation values for all decomposed series (i.e., long-, medium-, and short-run). Our findings have value for investors in the US sectoral market because they may be helpful for constructing and rebalancing portfolios based on varying levels of correlation across different quantile distributions and investment periods.</p><h2>Other Information</h2><p dir="ltr">Published in: The North American Journal of Economics and Finance<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.najef.2022.101847" target="_blank">https://dx.doi.org/10.1016/j.najef.2022.101847</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_7711416c6d16b411bb06c4c026eb2294 |
| identifier_str_mv | 10.1016/j.najef.2022.101847 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24501133 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The impact of Twitter-based sentiment on US sectoral returnsRami Zeitun (17075215)Mobeen Ur Rehman (15282575)Nasir Ahmad (821439)Xuan Vinh Vo (15353934)Commerce, management, tourism and servicesBanking, finance and investmentEconomicsEconometricsInformation and computing sciencesHuman-centred computingUS sectoral returnsInvestor sentimentsS&P 500CausalityWavelet correlation<p dir="ltr">This paper scrutinizes the effect of Twitter-based sentiment on US sectoral returns using data from between 21 June 2010 and 13 April 2020. We apply causality in quantiles as a non-parametric measure, followed by a rolling window wavelet correlation. The former measures the manifestation of causality directed from Twitter-based sentiment towards US sectoral returns, whereas the latter measures the correlation of returns across decomposed series that correspond to different time horizons. Our results highlight symmetric changes in US sectoral returns that vary across different sectors. The healthcare, communications, materials, consumer discretionary, energy, staples, and information technology sectors are more sensitive to changes in Twitter-based sentiment across all quantiles. Our findings from the rolling window wavelet correlation point to low correlation values for all decomposed series (i.e., long-, medium-, and short-run). Our findings have value for investors in the US sectoral market because they may be helpful for constructing and rebalancing portfolios based on varying levels of correlation across different quantile distributions and investment periods.</p><h2>Other Information</h2><p dir="ltr">Published in: The North American Journal of Economics and Finance<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.najef.2022.101847" target="_blank">https://dx.doi.org/10.1016/j.najef.2022.101847</a></p>2023-01-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.najef.2022.101847https://figshare.com/articles/journal_contribution/The_impact_of_Twitter-based_sentiment_on_US_sectoral_returns/24501133CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/245011332023-01-01T00:00:00Z |
| spellingShingle | The impact of Twitter-based sentiment on US sectoral returns Rami Zeitun (17075215) Commerce, management, tourism and services Banking, finance and investment Economics Econometrics Information and computing sciences Human-centred computing US sectoral returns Investor sentiments S&P 500 Causality Wavelet correlation |
| status_str | publishedVersion |
| title | The impact of Twitter-based sentiment on US sectoral returns |
| title_full | The impact of Twitter-based sentiment on US sectoral returns |
| title_fullStr | The impact of Twitter-based sentiment on US sectoral returns |
| title_full_unstemmed | The impact of Twitter-based sentiment on US sectoral returns |
| title_short | The impact of Twitter-based sentiment on US sectoral returns |
| title_sort | The impact of Twitter-based sentiment on US sectoral returns |
| topic | Commerce, management, tourism and services Banking, finance and investment Economics Econometrics Information and computing sciences Human-centred computing US sectoral returns Investor sentiments S&P 500 Causality Wavelet correlation |