Context Analytics (CA) leads the industry in structuring and analyzing unstructured text for sentiment analysis in financial markets. One of CA’s flagship offerings, the S-Factor feed, delivers a comprehensive suite of social sentiment metrics sourced from Twitter and Stocktwits, differentiated by platform for greater accuracy.By grouping securities into sentiment-based quintiles, we reveal a strong correlation between online mood and next-day returns.
Data Sources and Quality Controls
On Twitter, Context Analytics uses a proprietary account rating algorithm to evaluate financial relevance and credibility of each account. Only accounts that meet the algorithm’s criteria are included in the S-Factor calculations. In contrast, all accounts on Stocktwits are included, as the platform is exclusively focused on financial conversations.
Mapping Messages to Securities
Each publicly traded security is associated with a tailored topic model—a set of rules and identifiers that links messages to specific companies. Messages that match these identifiers are ingested and analyzed for sentiment, which is scored on a scale from -1.0000 to 1.0000. These individual sentiment scores and message volumes are then aggregated over a 24-hour window and compared to a 20-day historical baseline, producing a variety of sentiment factors, or S-Factors. These metrics are updated every minute.
Understanding the S-Score
One of the most widely used S-Factors is the S-Score. It represents the exponentially weighted sentimentfor a security over the past 24 hours (S), relative to its 20-day historical mean (s-mean) and 20-day historical standard deviation (s-volatility). This approach weights recent messages more heavily than older ones, capturing shifts in sentiment in near real-time. Because the metric is normalized to each security’s historical behavior, it avoids bias from message volume alone.
Research: Combining Twitter and Stocktwits Sentiment
We explored the predictive power of a blended S-Score by averaging Twitter and Stocktwits S-Scores for each security at the specified timestamps. Only securities with sentiment activity on both platforms and a share price above $5 at the previous day’s close were included. Each day, securities were sorted into quintiles based on their average S-Score prior to market close (3:40pm ET):
- Quintile 5: Top 20% (most positive sentiment)
- Quintile 1: Bottom 20% (most negative sentiment)
We then calculated daily Close-to-Close returns and cumulative returns for each quintile.
Top Quintile vs. Bottom Quintile:
- Cumulative Return: 83% vs. 12.49%
- Sharpe Ratio: 0.65 vs. 0.22
- Average S-Score: 974 vs. -1.115
- Return Spread +79.32% return
Key Findings: Sentiment Predicts Returns
The results clearly show a positive correlation between average S-Score and subsequent daily returns. Securities in the top sentiment quintile consistently outperformed those in the lower quintiles. Additionally, the bottom quintile consistently underperformed its peers.
The S-Factor feed is Context Analytics’ most established product, backed by over 10 years of historical data and a suite of 15 distinct sentiment factors. This rich dataset enables comprehensive back testing and empowers users to integrate real-time social media sentiment into financial strategies.
Interested in learning more? Reach out to us at ContactUs@ContextAnalytics-AI.com or visit www.contextanalytics-ai.com for more information.
TL;DR: Context Analytics uses social media sentiment from Twitter and Stocktwits to predict stock performance. Stocks with the highest average sentiment (S-Score) returned nearly 9x more than those with the lowest, proving that real-time online sentiment can forecast short-term market movements.
Strategy Summary: In review of the strategy and the key findings, we can summarize the results as follows:
- Sentiment Source:Twitter + Stocktwits
- Grouping:Stocks sorted into 5 quintiles by sentiment
- Top vs. Bottom Performance:
- Cumulative Return:Q5 = +111.83%, Q1 = +12.49%
- Annual Return:Q5 = +16.95%, Q1 = +6.14%
- Sharpe Ratio:Q5 = 0.65, Q1 = 0.22
- Sortino Ratio:Q5 = 1.04, Q1 = 0.34
- S-Score:Q5 = 1.974, Q1 = -1.115
Conclusion: Higher social sentiment correlates with stronger next-day stock performance.