---
title: Social Media Trading Impact
url: https://www.ml-quant.com/papers/ssrn/4827409/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4827409
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4827409
featured: 2024-05-15
citations: unknown
topic: Trading, Microstructure & Execution
---


# Social Media Trading Impact

The paper investigates the effect of presidential tweets on equity markets, revealing that market volatility increases and liquidity worsens more quickly during extended trading hours.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4827409
- Identifier: SSRN 4827409
- Released: 2021-09-10
- First featured: Quant Letter No. 49 (2024-05-15): https://www.ml-quant.com/issues/2024-05-15/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Trading, Microstructure & Execution

## Related

- [FAST: Efficient Action Tokenization for Vision-Language-Action Models](https://www.ml-quant.com/papers/arxiv/2501.09747/): A new tokenization scheme, Frequency-space Action Sequence Tokenization (FAST), has been proposed for robot actions, facilitating the training of vision-language action policies for complex and high-frequency tasks.
- [Deep Reinforcement Learning for Active High Frequency Trading](https://www.ml-quant.com/papers/arxiv/2101.07107/): A new Deep Reinforcement Learning framework has been developed for high frequency stock trading, showing potential for profitable long-term strategies.
- [Inflation and Trading](https://www.ml-quant.com/papers/ssrn/4822700/): Research indicates that investors often hold unrealistic expectations about stock returns during high inflation, and lack knowledge about inflation-hedging strategies, affecting their trading decisions.
- [Can Machine Learning Unlock New Insights into High-Frequency Trading?](https://www.ml-quant.com/papers/ssrn/4826698/): Machine learning is being used to explore the link between high-frequency trading and financial market trends, offering new ways to identify different trading strategies and their effects on market information.
- [No-arbitrage conditions and pricing from discrete-time to continuous-time strategies](https://www.ml-quant.com/papers/doi/10-1007-s10436-023-00426-1/): The paper presents a framework for continuous-time financial market models, demonstrating that no-arbitrage conditions apply in continuous time if they apply in discrete time, and super-hedging prices are the same in both times.
- [High-frequency stock market order transitions during the US-China trade war 2018: A discrete-time Markov chain analysis.](https://www.ml-quant.com/papers/doi/10-1063-5-0176892/): The research analyzes high-frequency stock market data to understand trading dynamics, revealing that similar strategies are used regardless of volatility during the 2018 USA-China trade war.