Model-independent overlays - the ultimate goal?
OK. We’re going to “geek out” on you a bit here. There’s been a lot of buzz recently about model-independent overlays when it comes to collecting and organizing data for feeds into aggregate trending models. As in any good system the separation of data from the mechanism for manipulating the data is key although in certain instances there is cohesion that can’t be completely avoided.
However, there can be sets of overlays that can be tied to specific instances of data organization and theoretically the data modeling can be optimized in such a way to maximize the number of potential overlays within certain overlay constraints. However, once again, the data and the overlays can’t be totally decoupled. That’s not hard to grasp from a “common sense” perspective, but as it turns out it’s quite difficult to prove conclusively.
Once again the time-factor is non-trivial in relation to the coupling/decoupling of data/overlay connections (also known as “n-realms”). Of course when dealing with any type of data collection that is derived from or has a bearing on specific markets and sub-markets naturally the element of time will be an important factor. But what’s surprising is the WAY in which time is a factor when manipulating data/overlay connections.