Vivek emailed me a simple question after reading yesterday’s does revenue seasonality translate to vol seasonality? post:
Why not just compute volatility from the daily returns within each calendar month instead of using a trailing 20-day window?
Um, well, eh. I don’t know. I guess just had a blind spot. I think of rolling realized vol instinctively. But for a seasonality study, it has a problem I already flagged in the post: a big earnings move in August gets recounted ~20 times as the window slides over it, smearing that vol into September.
It’s just unnecessary. So I added a section to the notebook that computes calendar-month realized vol directly: take each month’s daily log returns, compute √(mean(r²)) × √252, and you get one clean RV number per month per year without overlap.
The earnings effects and their seasonal patterns does look sharper.
A few more charts just to round it out:
The updated notebook is here: 👉 HRB Seasonality Study
Thanks again to Vivek for the feedback. Vivek was one of the senior quants at SIG when I was there. He’s also a chess genius if you’re into that.
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