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Very cool work here. This is a pretty epic post, so please do not take this the wrong way.

I was under the impression that FB Prophet was optimal for significantly seasonal time series data.

Honestly given the fickle nature of these kind of growth patterns beyond the very near term, an ARIMA with a flat vol or a simple eyeball extrapolation in my experience as a quant would likely generate just as reasonable/reliable results.

While I understand this is likely intended as a standalone project, it would be interesting to run a comparison of ARIMA vs FB Prophet on out of sample trending Github tools/file types, as well as the general performance of these predictions beyond a one year time frame (especially vs the reported confidence intervals in Prophet).

I am not that familiar with how Prophet works, so I am absolutely open to being humbled and corrected. I have a project myself that has a varying seasonal component and I am looking forward to diving into Prophet for a deeper understanding. I am attempting to model an Asian 2 asset spread option with a volume weighted average index price setting mechanism where the underlying exhibits seasonality in the volume traded over the trading time window. I am currently running a Monte Carlo on the valuation with a simple average settlement assumption, as opposed to a volume weighted average assumption, and I was thinking Prophet could help.

Does anyone have experience in financial time series analysis and option valuation who would care to chime in?

Also, what is everyone's thoughts on using prophet non seasonal vol clustering times series?

Hey, I posted the notebook by the OP. Thank you for your feedback! You're correct in saying that FB Prophet is for forecasting time series with strong seasonal effects. FB Prophet was the model used in the original script I found & the main point here was simply to make the notebook more readable on kyso, which has quite a few non-technical readers. I've worked a lot with ARIMAs before for financial/economic data and I like the idea of comparing the results between the two, and maybe even extend the time frame. So 1. I think that'll be my next project and 2. if your project is public I'd love to give it a read when published.

Did you try running the forecast with a log ceiling to control for the trajectory a bit? Or would that only be a concern of yours if you had to forecast past a couple of years? I find that when I use Prophet to forecast down to the day I end up creating initial forecasts with heavy log ceilings to prevent unreasonable estimates of the future and then end up removing the ceiling once enough history is established to provide a resaonable baseline.

Ah okay. Great work with plotly on visualization then. This is a great skill to have and something I need to work on. I’ve added Kyso to my favorite list. I look forward to your future posts.

I will likely publish something on my project using stale data given I work in a trading environment. The theory should be the same though. One of these days I’d like to actually write a solid white paper level research study and get published! One can dream!

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