When working with stock market data for strategy / analysis purposes, I am well aware that I have to distinguish between unadjusted and adjusted prices.
I understand that historical adjusted prices will be re-adjusted whenever a new event (dividend, split) took place; hence the adjusted close data for any given historical date is a function of that day's close level and any corporate action since then until today. I.e.: the adjusted price some historical date varies with calender time of observing the time series.
Hence, adjusted price data cannot be meaningfully stored in an append only fashion, i.e. I cannot load new adjusted price data into my database, but I have to re-create (as in: obtain and store) the whole adjusted price time series each day; or at least on each date where a corporate event took place.
This creates a little bit of a challenge for me: Obviously, downloading the whole time series of adjusted prices on each trading date is quite consuming in terms of data, traffic (and cost) and I am wondering whether it is feasible / economical to:
- re-build the adjusted price series internally (as in: in my database) with each new date, or
- to reload a full adjusted historical close time series at a lower frequency, optimally at or around capital action dates. I.e. by appending un-adjusted prices daily as usual, but then recreating the full adjusted price series only once per month / quarter / year.
I have not found any thoughts on this in this forum - and I'd be very happy to get ideas, hints, or to discuss possible approaches to this. Thanks in advance.