Stock News as a predictor of Returns

1. Stock News As a Predictor Of Returns www.infotrie.com

2. News as a predictor of Returns This presentation looks at stock returns of large cap Financial Services companies listed across major stock exchanges around globe and weigh its performance against the market news indicators as calculated by Infotrie. For the purpose of our analysis we have considered News Sentiment Data provided by Infotrie within the time period (1 Jan, 2013 – 19, May, 2014) and have assessed equities from NASDAQ, NYSE, Tokyo Stock Exchange and Paris Stock Exchange. In this presentationwe also attempt at establishing a deeper understanding of how news trends work, specifically we will look at how Infotrie’sBuzz Index can be a significant indicator of stock returns trend over look back periods of 1,2 and 3 months. Before we start looking at a detailed stock wise analysis we would like to mention certain key points and coin certain hypothesis that the reader can later observe in this paper.

3. News as a predictor of Returns • Buzz scores are nothing but normalized values of news volume over the past 7 days in the range 0 through 10, in simpler words the reader may consider it to be rate of change of news volume over past 7 days. • Inference: Buzz scores may not good immediate indicators when considering wider look-back windows, they positively forecast a trend in returns, specifically a downward trend. • Hypothesis: They represent the decay or rise in news volume thus reflecting the market’s interest or indifference. Interest helps a stock rise and indifference does the opposite. • Sentiment: Ranges from 0 to 10. Values above 5 deemed as bullish while lower values are bearish indicators. • News Volume: The higher, the more in-the-news a company is. We correlated the Prices with Periodic Buzz, Volumes and Sentiment to pick up those with significant relationships (>40%). These companies will then be further analysed to determine if our hypothesis were true. In our research, we analysed 16 companies but in the interest of being succinct, will only discuss 3 in this post. The full report will be available upon request.

4. News as a predictor of Returns • Buzz scores are nothing but normalized values of news volume over the past 7 days in the range 0 through 10, in simpler words the reader may consider it to be rate of change of news volume over past 7 days. • Inference: Buzz scores may not good immediate indicators when considering wider look-back windows, they positively forecast a trend in returns, specifically a downward trend. • Hypothesis: They represent the decay or rise in news volume thus reflecting the market’s interest or indifference. Interest helps a stock rise and indifference does the opposite. • Sentiment: Ranges from 0 to 10. Values above 5 deemed as bullish while lower values are bearish indicators. • News Volume: The higher, the more in-the-news a company is. We correlated the Prices with Periodic Buzz, Volumes and Sentiment to pick up those with significant relationships (>40%). These companies will then be further analysed to determine if our hypothesis were true. In our research, we analysed 16 companies but in the interest of being succinct, will only discuss 3 in this post. The full report will be available upon request.

5. 1.    Berkshire Hathaway Inc. (BRK) [NYSE] The table above gives us an idea that BRK is “in the news” firm with a relatively bullish sentiment and a low buzz score implying a relatively stable news volume. Our correlation analysis suggest that we can observe that most significant indicator to be Buzz index over weekly and monthly intervals. Let’s see:

7. Fig 2: Weekly and biweekly returns v/s respective buzz momentum From Fig 2 we can observe value of returns having a healthy correlation with buzz scores as calculated and we can specifically point out that decay in buzz score are significantly related falling returns.

8. 3: Monthly returns v/s SMA_60 and Buzz_60 From the above figure we can say the buzz momentum follows a pattern similar but more precise than the pattern in Fig 2 thus strengthening our hypothesis.

9. 2.    American Express Company (AXP) [NYSE] Essentially AXP has a bullish average sentiment with significant news volume. While at first glance it seems similar to Berkshire Hathaway (BRK), AXP is more volatile and has a positive correlation between simple moving averages (SMA) of Price and periodic Time values (unlike BRK). Thus, we find this worth observing.

10. Fig 6: Returns_90, Buzz_90 and SMA_90 Figure 6 reflects of a decay scenario where decaying value of Buzz_90 relates to a steep decay in returns. We believe the steep decay has more to do with volatility rather than the magnitude of decay of buzz.

11. 3. Capital One Finance (COF) [NYSE] COF offers a rather contradictory picture to our hypothesis. In this scenario, Buzz_90 is negatively correlated to 90-day returns. The most significant indicator was the 90-day volume, which also had a negative correlation to returns. From figure 7 below, we can conclude that this appears to be a non-causal relationship from the following figure.

12. Fig 7: Returns_90 and NewsVolume_90

13. Conclusion If we consider company’s data samples to be a probabilistic hypothesis testing mechanism, our initial hypothesis regarding Buzz scores holds true 11 times out of 16. Empirically we also saw that returns (60-90 days) for equities with a large news volume are more significantly correlated to the decaying Buzz values over 60-90 day look back windows while those with marginal or negligible news volume were related to upward as well as downward buzz trend. One may have also noticed a marginal correlation between sentiment scores and returns over small periods (up to 2 weeks) which is consistent with SMA values reflecting generic correlations over small intervals of time.

14. Contact Us InfoTrie Financial Solutions Pte Ltd Address - 37th Floor, Singapore Land Tower, 50 Raffles Place, Singapore 048623 Phone - +65 6570 0631 Email - contact@infotrie.com Website - www.infotrie.com www.finsents.com