Signs of Seasonality
One of the members of our Customer Success team was wondering about the difficulty of getting client attention at the end of August. We ran an analysis to try and answer the question, “how active are our clients by month?” We used price target updates, logins, and trades per month as a proxy for investor activity.
August was definitely the softest month, but clients weren’t as “checked out” as we expected. We hypothesized that the peak periods would be during earnings season and troughs will be after earnings. Here’s the rub, they’re in the same month. The end of second-quarter earnings season and the before school vacation season are in the same month.
To remedy this fact, we created periods starting on the 15th of each month (i.e. August 15th to September 15th). This allows us to catch each earnings season as its own isolated period. Here are the results:
There is clear seasonality. The post Q2 earnings season is 2.5 standard deviations from the norm. I suspect that if we broke this down into two-week tranches, we would have seen even more pronounced deviation from August 15th to August 31st.
As expected, the Post Earnings Season cohort’s activity was light at 0.7 standard deviations below normal activity, while the During Earnings cohort was busy (+0.8).
One of my favorite parts of working at Alpha Theory is that we have a long series of robust, structured data that allows us to ask and answer interesting questions. If you would like to be able to do the same, the first step is collecting and maintaining well-structured data. Then you can ask interesting questions like “what season do we make our most money?”, “who is the best forecaster on my team?”, “how often do stocks go below our risk targets?”, etc.
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