Thursday, October 8, 2009

Market Reaction To Sentiment-Based Events

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In a previous posting, I described how it is possible to identify and make trading decisions based on a range of events such as earnings or earnings guidance announcements, executive appointments, analysts ratings, etc.; this with news sentiment determining the expected direction of the market. When using sentiment to decide on the expected direction of certain triggering events based on RavenPack data, a number of approaches are available. For example:


  • Using a single sentiment score allows for the simplest approach in determining whether a news item is positive or negative. For instance, a news item with a RavenPack sentiment score (0-100) above 50 is positive and below 50 is negative. However, previous studies indicate that taking a multi-classifier approach to sentiment adds value due to the diversification effect available amongst the different classifiers.
  • Using average or weighted scores allows for a simple evaluation of multi-classifier sentiment, where high (low) values could potentially be considered reflecting greater positive (negative) sentiment. Alternatively, a simple positive or negative classification can be used depending on whether the score is above or below 50 and contextually relevant to a given entity (i.e. a company). The "average" approach was applied as part of constructing market sentiment indices (factors) in the study "Construction of Market Sentiment Indices Using News Sentiment".
  • Using unique combinations of sentiment scores, which was the focus in the study: "Impact of News Sentiment on (intra-day) Abnormal Stock Returns". An advantage of such approach is that it is possible to evaluate how different combinations of sentiment classifications can impact the market potentially under different environments and for different event types. In contrast, a disadvantage is that one may end up with only a few occurrences of each "signal", thus requiring an evaluation of a larger universe of companies as part of the research and model construction phase.
  • Using a voting (consensus) mechanism could potentially create stronger confidence in correctly classifying a news item as being overall positive or negative as it relies on several sentiment analysis techniques that have to be in agreement. This approach is more restrictive than the average sentiment approach, and therefore a large number of potentially interesting signals a filtered out resulting in less signals overall but of higher quality. This approach has been applied for instance in a study by Macquarie US Equity Research: "Breaking News: How to use news sentiment to pick stocks".
In what follows, I will highlight some of the results from an event study that considers about 100 different types of events, as covered by RavenPack. As part of this study, events are considered positive or negative using a voting mechanism with at least three out of the five RavenPack sentiment scores having to be greater (less) than 50 (out of 100), and the other two scores being neutral. The company relevance score must also be 100%.

Considering the constituents of the Russell 3000, the following charts present the results of selected events (the numbers in parentheses denote the total number of events of that type and the percent of all events in the sample). Furthermore, the charts presented show the mean and median market- and sector-adjusted returns for stocks around positive and negative events.


Earnings and guidance events

Overall, earnings and revenues related events are the most common in the database, which comes as no surprise since most companies make such information available on a quarterly horizon. Considering positive and negative revenue announcements, the key results can be summarized as:

  • For positive revenue announcements (Figure 6), on average there tends to be a mild post-event upwards drift relative to the market. However, the median return actually gives a slight downwards drift.
  • For negative revenue announcements (Figure 7), the post-event drift is much stronger regardless of whether the mean or median is used. This suggests that even after negative revenue announcements, there is still substantial alpha available from shorting this category of stocks.




Analyst Ratings

The second most common category of events is those generated by sell-side analyst activity. Figures 10 and 11 show the average stock price reaction to changes in ratings by sell-side analysts.

  • On average, sell-side analysts tend to be contrarian in their ratings changes. In other words, they tend to upgrade stocks that have been underperforming, and downgrade stocks that have been outperforming. This is opposite to the conventional wisdom that sell-side analysts tend to follow recent price momentum.
  • Post-upgrade and post-downgrade drift is less clear-cut. From the perspective of the median stock, it appears that both upgrades and downgrades lead to underperformance.
  • Using average returns, post-event performance is relatively in-line with the market.





M&A activity events

Assessing the impact of M&A activity has always been challenging, because every takeover situation is a little different from the last. Figures 14 shows the case where a company announces it is acquiring another company, while Figure 15 shows what happens when a company is itself the target of a takeover. The key results can be summaries as:

  • A few outlier stocks tend to have a big impact on returns to the strategy as reflected by the big difference between the mean and the median.
  • On the day of the announcement, the price of the acquiree’s stock jumps up sharply on average. However, post-event, there is little drift on average.
  • For the acquirer, there is no post-event drift when using average returns. However, median returns tend to indicate that stocks that look for acquisitions tend to underperform before and after the event.






Other events

Ad hoc events like bankruptcies (Figure 16) tend to occur infrequently, but when they do happen, the returns are often very large. Fraud (Figure 17) is another somewhat rare event. The key results can be summaries as:

  • Following a bankruptcy announcement, the stock price plunges, but then tends to bounce back in the next five to ten trading days.
  • On average, stocks that report fraud tend already to have been underperforming before the fraud is announced. After the event, these stocks continue to underperform.