Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets
A trite yet fundamental question in economics is: What causes large asset price fluctuations? A 10-fold rise in the price of GameStop equity, between January 22, 2021, and January 28, 2021, demonstrated that herding behavior among retail investors is an important contributing factor. This article pr...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
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Portfolio Management Research
2024
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| _version_ | 1826314483193085952 |
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| author | Semenova, V Gorduza, D Wildi, W Dong, X Zohren, S |
| author_facet | Semenova, V Gorduza, D Wildi, W Dong, X Zohren, S |
| author_sort | Semenova, V |
| collection | OXFORD |
| description | A trite yet fundamental question in economics is: What causes large asset price fluctuations? A 10-fold rise in the price of GameStop equity, between January 22, 2021, and January 28, 2021, demonstrated that herding behavior among retail investors is an important contributing factor. This article presents a data-driven guide to the forum that started the hype: WallStreetBets (WSB). The article’s initial experiments decompose the forum using a large language topic model and network tools. The topic model describes the evolution of the forum over time and shows the persistence of certain topics (such as the market/S&P 500 discussion) and the sporadic interest in others, such as COVID-19 or crude oil. The authors use network analysis to decompose the landscape of retail investors into clusters based on their posting and discussion habits; several large, correlated asset discussion clusters emerge, surrounded by smaller, niche ones. A second set of experiments assesses the impact that WSB discussions have had on the market. The authors show that forum activity has a Granger causal relationship with the returns of several assets, some of which are now commonly classified as meme stocks, while others have gone under the radar. The article extracts a set of short-term trade signals from posts and long-term (monthly and weekly) trade signals from forum dynamics and considers their predictive power at different time horizons. In addition to the analysis, the article presents the dataset, as well as an interactive dashboard, in order to promote further research. |
| first_indexed | 2024-09-25T04:33:11Z |
| format | Journal article |
| id | oxford-uuid:427a1dc8-7021-4029-9dca-4afaec3437ef |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:33:11Z |
| publishDate | 2024 |
| publisher | Portfolio Management Research |
| record_format | dspace |
| spelling | oxford-uuid:427a1dc8-7021-4029-9dca-4afaec3437ef2024-09-06T13:23:24ZWisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBetsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:427a1dc8-7021-4029-9dca-4afaec3437efEnglishSymplectic ElementsPortfolio Management Research2024Semenova, VGorduza, DWildi, WDong, XZohren, SA trite yet fundamental question in economics is: What causes large asset price fluctuations? A 10-fold rise in the price of GameStop equity, between January 22, 2021, and January 28, 2021, demonstrated that herding behavior among retail investors is an important contributing factor. This article presents a data-driven guide to the forum that started the hype: WallStreetBets (WSB). The article’s initial experiments decompose the forum using a large language topic model and network tools. The topic model describes the evolution of the forum over time and shows the persistence of certain topics (such as the market/S&P 500 discussion) and the sporadic interest in others, such as COVID-19 or crude oil. The authors use network analysis to decompose the landscape of retail investors into clusters based on their posting and discussion habits; several large, correlated asset discussion clusters emerge, surrounded by smaller, niche ones. A second set of experiments assesses the impact that WSB discussions have had on the market. The authors show that forum activity has a Granger causal relationship with the returns of several assets, some of which are now commonly classified as meme stocks, while others have gone under the radar. The article extracts a set of short-term trade signals from posts and long-term (monthly and weekly) trade signals from forum dynamics and considers their predictive power at different time horizons. In addition to the analysis, the article presents the dataset, as well as an interactive dashboard, in order to promote further research. |
| spellingShingle | Semenova, V Gorduza, D Wildi, W Dong, X Zohren, S Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets |
| title | Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets |
| title_full | Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets |
| title_fullStr | Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets |
| title_full_unstemmed | Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets |
| title_short | Wisdom of the crowds or ignorance of the masses? A data-driven guide to WallStreetBets |
| title_sort | wisdom of the crowds or ignorance of the masses a data driven guide to wallstreetbets |
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