Hi @James, @Joakim, @Karl, your comments above are all good ones and also all touch on some of my own favorite topics too.
Regarding value, growth and our favorite Oracle of Omaha, it is interesting to note that although Warren B started very much following the ideas of his own predecessor & master, he also expanded on them over time. While he (WB) is seen as predominantly a "Value" rather than a "Growth" investor, it is interesting that, in the details, his analysis method very much takes into account expectations of Return on Owners Equity and Equity Growth over time and this is discussed nicely in Belafonte's book on Buffet.
I think the distinction between "Growth vs Value" stocks is an artificial one, and Joakim implies this as well in his comment about finding "value in growth", which is also similar to the idea of "Growth at a Reasonable Price".
As to exactly how best to do that, of course we all have somewhat different ideas and I think Ernie Chan's comment and Joakim's take on it are definitely good ones: "the key to using ML in financial time-series might NOT be to predict future prices or returns, but to choose non-price related features".
The way that ML is often used for discovering price patterns & making predictions therefrom has certainly been successful (profitable) in some cases, but is fraught with problems, especially when ML is used to data mine the difficult-to-see price patterns the soon get arbitraged away as more people discover them, and so this way (the most common way) of using ML for price patterns probably offers little of LONG-TERM value.
I'm absolutely NOT against ML, but i do just think that there are better ways to use it, as Ernie implies. It is interesting to compare the market phenomena that lead only to ephemeral profits (such as being the first to see hidden price patterns that actually have no real long-term basis) vs the phenomena that do continue to be profitable year-after-year, decade-after-decade, irrespective of how many people find them (such as trends based on delays in supply & demand - e.g. in the time it takes to bring new mines into production in response to demand for new tech metal resources, etc).
I think "ZenoTheStoic" (familiar face with a new name huh? Not the same Zeno as the one with the Paradox right?) also touches on this very well with his comment: "* Stock prices are driven in the long term by fundamentals. Cashflow is one of the most basic and important fundamentals for valuing a stock. Fundamentals don't change: cashflow will always be important and a lack of cashflow will always (eventually) sink a company if left uncorrected.*"
Maybe it is indeed " ... a point few seem to appreciate on this forum", but nevertheless i think those of us talking here certainly do get it.
An interesting question is how well can Karl's (and others of us with an interest in it) actually use ML in a better-than-usual way, such as by being applied to this all-important topic?
Cheers, all the best, from TonyM