In this blog post, we explore the commodities markets and delve into the role of sentiment analysis...
Context Analytics’ Quantitative News Feed is a powerful tool for quantitative strategies and alpha generation, offering predictive news sentiment. One of its biggest advantages compared to other vendors is its expansive universe. We process over 3,000 articles covering more than 1,500 unique securities from over 300 distinct news sources daily. Our entire library spans over 4,000 robust news sources worldwide, covering more than 4,500 unique securities. This extensive coverage allows us to gauge which companies receive more news attention compared to others.
The purpose of this research is to explore the effect of prolonged news attention on subsequent intermediate market performance.
Methodology
Our research focused exclusively on the S&P 500 constituents, examining the volume of articles about each. We developed a metric to represent the relative article volume for each constituent on a weekly basis. Here’s how we did it:
- Daily Volume Sum: We calculated the number of articles for each ticker, assigning a value of zero to tickers with no news.
- Two-Week Summation: We computed a rolling 14-day summation of this volume sum to capture the previous two weeks' article volume.
- Standardization: The two-week sum was standardized over the previous two months, adjusted for market days. For example, if the last market day was a Friday, we compared the two-week sum against the previous eight Fridays' two-week sums.
- Standardized Volume Score: From this data, we created a standardized score to inform our trading strategy.
Trading Strategy
Our trading strategy involved the following steps:
- Entry/Exit Point: We entered positions at the close on the last trading day of the week and exited the last trading day of the following week.
- Quintile Bucketing: Each week, we placed S&P 500 constituents into quintiles based on their Standardized Volume Score, provided they had more than five articles in the previous two weeks.
- Equal-Weighted Positions: We took equal-weighted positions for each quintile and held them for one week.
- Weekly Rebalancing: We rebalanced the quintiles every week, compounding our returns over time.
- Baseline Comparison: We compare performance with the RSP (S&P 500 Equal Weighted) ETF to provide an apples-to-apples comparison for the equal weight strategy.
Results and Insights
We consistently average significant coverage for 475 out of 500 S&P 500 constituents on a weekly basis. Our analysis revealed a clear correlation between news mentions and subsequent weekly market performance:
- Higher Returns with More Mentions: Constituents in the top quintile, representing those with the highest news mentions relative to their history, generally exhibited better weekly returns.
- Monotonic Spread: There was a monotonic spread across the quintiles, with higher quintiles outperforming the lower ones.
- Improved Risk Measures: Both returns and risk measures improved as the quintile increased.
- Comparison with RSP Index: The top quintiles outperformed the equally weighted S&P 500 (RSP), while the lower quintiles underperformed.
Conclusion
Our findings suggest a correlation between news mentions and subsequent market performance on a weekly basis. Context Analytics’ Quantitative News Feed empowers users to monitor trending securities in the news, providing a valuable tool for enhancing financial strategies. For more information on the Quantitative News Feed visit www.contextanalytics-ai.com or click the link below!
