Leveraging Social Media Sentiment for Predictive Algorithmic Trading Strategies
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908477785374720 |
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| author | Goyal, Gatik Phadke, Sharvil Sharma, Arnav Qin, Huifang |
| author_facet | Goyal, Gatik Phadke, Sharvil Sharma, Arnav Qin, Huifang |
| contents | This study investigates how social media sentiment derived from Reddit comments can be used to enhance investment decisions in a way that offers higher returns with lower risk. Using BERTweet we analyzed over 2 million Reddit comments from the subreddit r/wallstreetbets and developed a Sentiment Volume Change (SVC) metric combining sentiment and comment volume changes, which showed significantly improved correlation with next-day returns compared to sentiment alone. We then implemented two different investment strategies that relied solely on SVC to make decisions. Back testing these strategies over four years (2020-2023) our strategies significantly outperformed a comparable buy-and-hold (B&H) strategy in a bull market, achieving 70% higher returns in 2023 and 84.4% higher returns in 2021 while also mitigating losses by 4% in a declining market in 2022. Our results confirm that comment sentiment and volume data derived from Reddit can be effective in predicting short-term stock price movements and sentiment-powered strategies can offer superior risk-adjusted returns as compared to the market, implying that social media sentiment can potentially be a valuable investment tool. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_02089 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Leveraging Social Media Sentiment for Predictive Algorithmic Trading Strategies Goyal, Gatik Phadke, Sharvil Sharma, Arnav Qin, Huifang Social and Information Networks This study investigates how social media sentiment derived from Reddit comments can be used to enhance investment decisions in a way that offers higher returns with lower risk. Using BERTweet we analyzed over 2 million Reddit comments from the subreddit r/wallstreetbets and developed a Sentiment Volume Change (SVC) metric combining sentiment and comment volume changes, which showed significantly improved correlation with next-day returns compared to sentiment alone. We then implemented two different investment strategies that relied solely on SVC to make decisions. Back testing these strategies over four years (2020-2023) our strategies significantly outperformed a comparable buy-and-hold (B&H) strategy in a bull market, achieving 70% higher returns in 2023 and 84.4% higher returns in 2021 while also mitigating losses by 4% in a declining market in 2022. Our results confirm that comment sentiment and volume data derived from Reddit can be effective in predicting short-term stock price movements and sentiment-powered strategies can offer superior risk-adjusted returns as compared to the market, implying that social media sentiment can potentially be a valuable investment tool. |
| title | Leveraging Social Media Sentiment for Predictive Algorithmic Trading Strategies |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2508.02089 |