At Context Analytics, we are the leader in unstructured financial data. In this blog, we explore how long-term sentiment signals, derived from our Quantitative News Feed, can drive powerful quantitative strategies and generate alpha. Context Analytics’ Quantitative News Feed is a predictive news sentiment tool useful for trading strategy building and risk management. By harnessing and enhancing our advanced proprietary Natural Language Processing (NLP) technology, this feed transforms how users digest and analyze financial news.
What Sets Context Analytics News Feed Apart?
Extensive Coverage: Our reach is unparalleled, with over 150,000 news articles analyzed monthly from more than 4,000 global news sources. This ensures our users gain a comprehensive, real-time view of the financial news landscape, capturing shifts in sentiment that might influence market moves.
In previous research, our focus centered on shorter-term sentiment — specifically, a 24-hour positivity ratio for companies based on news sentiment. This was calculated as the ratio of aggregate positive mentions to total indicative sentiment hits. In this study, however, we extend our approach to look at sentiment trends over a 30-day period.
Monthly Positivity Ratio
For this analysis, we calculated a monthly positivity ratio as follows:
- We examined the past 30 days of positive sentiment hits divided by total indicative sentiment hits.
- To ensure relevance, we included only articles with full (100%) relevance to a unique ticker and excluded any reposted articles.
- This monthly positivity ratio provides a score between 0 and 1, which we used to gauge longer-term sentiment.
Using this score, we implemented a strategy that rebalances monthly:
Results
Since late 2021, we’ve run this strategy across our dataset, revealing a notable correlation between higher monthly positivity ratios and longer-term returns. While nearly monotonic, the quintile results show a consistent trend: stocks with more positive sentiment generally outperform those with lower positivity scores. Quintiles 1 and 2 experienced negative returns in this period, whereas Quintile 5 and Quintile 4, comprising stocks with the highest positivity ratios, showed the strongest gains.
Our Q5-Q1 portfolio, which represents a long-short strategy between the highest and lowest quintiles, delivered robust returns. It outperformed benchmarks like the SPY on risk ratios, with a similar number of securities and an equally weighted structure. This suggests that the Quantitative News Feed’s positivity ratio can be a powerful tool for generating alpha over a more extended time horizon.
The results from this strategy demonstrate the potential for Context Analytics’ Quantitative News Feed to support long-term signal generation. By leveraging these metrics, traders and portfolio managers can refine their models and optimize risk management strategies, harnessing the power of sentiment to drive more informed decisions.
For more information on how our Quantitative News Feed can transform your trading strategies, visit us at www.contextanalytics-ai.com .