This is interesting. What do you mean by fintech -- hedge funds and HFT shops, or financial technogy companies like Affirm? Could you share a few examples?
Looking at the cpp code, could you describe the prototype/pattern image? What sort of prep do you do to make it generally recognizable as the questions/answers change?
This is a nice piece of work - thanks for sharing with the community!
Some feedback: it'd be nice to see you actually quantify how accurate Prophet's forecasts are on the landing page for the project. In the Wikipedia page view example, you go as far as showing a Prophet forecast, but it'd be nice to have you take it one step further and quantify its performance. Maybe withhold some of the data you use to fit the model and see how it performs on that out of sample data. It's nice that you show qualitatively that it captures seasonality, but you make bold claims about its accuracy and the data to back those claims up is conspicuously absent. Related, it might be worth benchmarking its performance against existing automated forecasting tools.
Thanks for your reply. The ad-exchange-related jargon is foreign to me, but your explanation makes sense. Basically, the arbitrageur buys ad space on a website from a demand source (which essentially means buying a demand source tag which secures the ad space on that website) and turns around and re-sells that space which he/she just bought on a DSP. So, money is made when the cost to buy the ad space from the demand source is less than it's re-sold for on the DSP.
Is that about right? What information does the demand source tag include - is that basically a placeholder indicating you bought space for an ad on a website? I assume the arbitrageur's edge comes from finding traffic that can be bought cheaply from the demand source and sold higher on the DSP?