An explorative analysis of sentiment impact on S&P 500 components returns, volatility and downside risk.
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| Title: | An explorative analysis of sentiment impact on S&P 500 components returns, volatility and downside risk. |
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| Authors: | Figà-Talamanca, Gianna1 (AUTHOR) gianna.figatalamanca@unipg.it, Patacca, Marco2 (AUTHOR) |
| Source: | Annals of Operations Research. Nov2024, Vol. 342 Issue 3, p2095-2117. 23p. |
| Subjects: | Bloomberg LP, Market sentiment, Rate of return on stocks, Value at risk, Sentiment analysis, GARCH model |
| Abstract: | The main contribution of this study is to assess whether investor sentiment, as measured through textual analysis of newspaper articles or social media posts, does have an effect on the mean returns and on the variance of financial stocks. The analysis is carried on a basket of the S &P 500 components where stock returns and volatility are modeled within the GARCH family augmented, both in the mean and the variance equation, with an exogenous variable representing the investor sentiment; the latter is measured through specific Bloomberg proprietary scores based on News or Twitter feeds. Empirical results support the hypothesis that these indicators do have a positive impact on stock prices: the Twitter based index positively affects the components returns, confirming the outcomes of existing studies, whereas the news based index has a significant impact on their volatility. We also contribute the literature by performing the same analysis across the 11 sectors of the index, evidencing that investor sentiment has a significant impact on Industrials, Health Care, Consumer Discretionary, Consumer Staples, Information Technology and Communication Services. As a further contribution, we perform an out-of-sample analysis to assess the potential effect of Bloomberg sentiment scores on downside risk measures, such as Value at Risk and Expected Shortfall. This subject is relevant to regulators in order to conceive suitable policy interventions during turmoil periods around specific market sectors or stocks. [ABSTRACT FROM AUTHOR] |
| Copyright of Annals of Operations Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 181119116 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: An explorative analysis of sentiment impact on S&P 500 components returns, volatility and downside risk. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Figà-Talamanca%2C+Gianna%22">Figà-Talamanca, Gianna</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> gianna.figatalamanca@unipg.it</i><br /><searchLink fieldCode="AR" term="%22Patacca%2C+Marco%22">Patacca, Marco</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Annals+of+Operations+Research%22">Annals of Operations Research</searchLink>. Nov2024, Vol. 342 Issue 3, p2095-2117. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Bloomberg+LP%22">Bloomberg LP</searchLink><br /><searchLink fieldCode="DE" term="%22Market+sentiment%22">Market sentiment</searchLink><br /><searchLink fieldCode="DE" term="%22Rate+of+return+on+stocks%22">Rate of return on stocks</searchLink><br /><searchLink fieldCode="DE" term="%22Value+at+risk%22">Value at risk</searchLink><br /><searchLink fieldCode="DE" term="%22Sentiment+analysis%22">Sentiment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22GARCH+model%22">GARCH model</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The main contribution of this study is to assess whether investor sentiment, as measured through textual analysis of newspaper articles or social media posts, does have an effect on the mean returns and on the variance of financial stocks. The analysis is carried on a basket of the S &P 500 components where stock returns and volatility are modeled within the GARCH family augmented, both in the mean and the variance equation, with an exogenous variable representing the investor sentiment; the latter is measured through specific Bloomberg proprietary scores based on News or Twitter feeds. Empirical results support the hypothesis that these indicators do have a positive impact on stock prices: the Twitter based index positively affects the components returns, confirming the outcomes of existing studies, whereas the news based index has a significant impact on their volatility. We also contribute the literature by performing the same analysis across the 11 sectors of the index, evidencing that investor sentiment has a significant impact on Industrials, Health Care, Consumer Discretionary, Consumer Staples, Information Technology and Communication Services. As a further contribution, we perform an out-of-sample analysis to assess the potential effect of Bloomberg sentiment scores on downside risk measures, such as Value at Risk and Expected Shortfall. This subject is relevant to regulators in order to conceive suitable policy interventions during turmoil periods around specific market sectors or stocks. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Annals of Operations Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10479-022-05129-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 2095 Subjects: – SubjectFull: Bloomberg LP Type: general – SubjectFull: Market sentiment Type: general – SubjectFull: Rate of return on stocks Type: general – SubjectFull: Value at risk Type: general – SubjectFull: Sentiment analysis Type: general – SubjectFull: GARCH model Type: general Titles: – TitleFull: An explorative analysis of sentiment impact on S&P 500 components returns, volatility and downside risk. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Figà-Talamanca, Gianna – PersonEntity: Name: NameFull: Patacca, Marco IsPartOfRelationships: – BibEntity: Dates: – D: 20 M: 11 Text: Nov2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 02545330 Numbering: – Type: volume Value: 342 – Type: issue Value: 3 Titles: – TitleFull: Annals of Operations Research Type: main |
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