Social media sentiment and stock market volatility
This article review critically examines Boris Andreev, Georgios Sermpinis, and Charalampos Stasinakis’s research on social media sentiment, specifically from Reddit’s r/WallStreetBets (WSB), as a predictor of stock market volatility. Structured with a summary, analysis, and evaluation, this article review example highlights the authors’ innovative use of WSB sentiment data, applying machine learning models like Random Forest and Neural Networks. The paper writer also assesses the study’s limitations, noting its reliance on WSB data and its challenges in forecasting extreme market shifts. This review concludes that while WSB sentiment offers insight, it alone is insufficient for high-volatility predictions.
* The sample essays are for browsing purposes only and are not to be submitted as original work to avoid issues with plagiarism.
Academic level:
Graduate
Type of paper:
Article review
Discipline:
Investing and financial markets
Citation:
APA
Pages:
3 (852 words)
Spacing:
Double
* The sample essays are for browsing purposes only and are not to be submitted as original work to avoid issues with plagiarism.