{"id":81425,"date":"2021-03-26T10:15:22","date_gmt":"2021-03-26T14:15:22","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=81425"},"modified":"2024-05-15T10:29:45","modified_gmt":"2024-05-15T14:29:45","slug":"does-social-media-sentiment-matter-in-the-pricing-of-u-s-stocks","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/does-social-media-sentiment-matter-in-the-pricing-of-u-s-stocks\/","title":{"rendered":"Does Social Media Sentiment Matter in the Pricing of U.S. Stocks?"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong><em>Excerpt<\/em><\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Although the models cannot entirely capture the reality, they are essential in the analysis and problem solving, and the same could be said about asset pricing models. These models had a long journey from the CAPM model to the most recent Fama French five-factor model. However, the asset pricing models still rely on fundamentals, and as we see in the practice every day, the financial markets or investors are not always rational, and prices tend to deviate from their fundamental values. Past research has already suggested that the assets are driven by both the fundamentals and sentiment. The novel research of Koeppel (2021) continues in the exploration of the hypothesis mentioned above and connects the sentiment with the factors in Fama\u00b4s and French\u00b4s methodology. The most interesting result of the research is the construction of the sentiment risk factor based on the direct search-based sentiment indicators. The data are sourced by the MarketPsych that analyze information flowing on social media. For comparison, public news is not a source of such exploitable sentiment indicator.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The sentiment score extracted from social media can be exploited to augment the Fama French five factors model. Based on the results, this addition seems to be justified. Adding the sentiment to the pure fundamental model explains more variation and reduce the alphas (intercepts). Moreover, the factor is unrelated to the well-known and established risk factors utilized in the previous asset pricing models, including the momentum.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Authors:<\/strong>&nbsp;Christian Koeppel<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Title:&nbsp;<\/strong>Does Social Media Sentiment Matter in the Pricing of U.S. Stocks?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Link<\/strong>:&nbsp;<a href=\"https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3771788\">https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3771788<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Abstract:<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This paper applies a recently developed social media-based sentiment proxy for the construction of a new risk factor for sentiment-augmented asset pricing models on U.S. equities. Accounting for endogeneity, autocorrelation and heteroskedasticity in a GMM framework, we \ufb01nd that the inclusion of sentiment signi\ufb01cantly improves the performance of the \ufb01ve-factor model from Fama and French (2015, 2017) for di \ufb00 erent industry and style portfolios like size, value, pro\ufb01tability, investment. The sentiment risk premium provides the missing component in the behavioral asset pricing theory of Shefrin and Belotti (2008) and (partially) resolves the pricing puzzles of small extreme growth, small extreme investment stocks and small stocks that invest heavily despite low pro\ufb01tability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Visit Quantpedia to read the full article: <a href=\"https:\/\/quantpedia.com\/does-social-media-sentiment-matter-in-the-pricing-of-u-s-stocks\/\">https:\/\/quantpedia.com\/does-social-media-sentiment-matter-in-the-pricing-of-u-s-stocks\/<\/a><\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#f9eb90\">Past performance is not necessarily indicative of future results.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This article delivers insight on how sentiment score extracted from social media might be exploited to augment the Fama French five factors model. <\/p>\n","protected":false},"author":186,"featured_media":46636,"comment_status":"closed","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[339,338,341,351,344],"tags":[9446,4922,8522,7879,494,1038,3913],"contributors-categories":[13662],"class_list":["post-81425","post","type-post","status-publish","format-standard","has-post-thumbnail","category-data-science","category-ibkr-quant-news","category-quant-development","category-quant-europe","category-quant-regions","tag-capm-model","tag-econometrics","tag-fama-and-french","tag-fama-french","tag-quant","tag-sentiment-analysis","tag-social-media","contributors-categories-quantpedia"],"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.8) - 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