Sector shift question

Posting the same question on Saul’s and NPI…

Right now, both TMF boards are predominantly riding the wave Cloud/AI tech stocks… but that hasn’t always been the case… nor will it always be the case. There always exceptions, NKTR is widely followed on both boards… but predominantly it’s a Cloud/AI wave from what I see.

Two questions… in trying to learn how to fish for myself…

  1. How did you identify this was the wave to ride in advance of the rest of world?
  2. How do you know to switch to another wave?

Just seeking to understand… I see phenomenal deep dives on stocks… I’m not capable of that myself yet… but trying to learn. But if I were to do a deep dive, and try to fish for myself… I feel like I want to understand “where to fish”… so what led people to this sector now? and what will lead people to the next sector after this?

Hope that makes sense.




This is an excellent question, one I’m thinking about right now.

To me, its all about revenue growth with margin improvement. So if we see signs of revenue slow down in the sector, the businesses are going to take a hit (unless the margins start to improve as quickly as the revenue growth slow down).

As far a new sector, again, to me its about revenue growth. So I want to find some sectors where I see the revenue starting to accelerate, or maintain high growth. I haven’t found a good way to search for that yet.

One sector that is happening is personal healthcare: Abiomed, Illumina,Align,etc. I own Align and a small position in Illumina, the growth rates are accelerating.



1) How did you identify this was the wave to ride in advance of the rest of world?

Mark, to try to answer this question, I don’t know that anyone necessarily identified this as the wave to ride; I could be wrong, but I think it was more a function of identifying companies that were growing quickly, increasing revenue quickly, increasing margins,etc. It just turned out that many of these companies are Cloud/AI tech stocks.

I say this because, little more than a year or so ago…maybe a bit longer ago…some of the fast-growing companies discussed on this Board were Skechers, LGIH, Casey’s General Store, etc…not many stocks at all in the Cloud/AI tech space. So, at least speaking for myself, I go where the fast-growing companies are.

Hope that helps.


This is the Internet, so I wouldn’t put too much stock into what you read here. I see a lot of posts where people say they bought near a bottom or sold near a top “a couple of days ago.” It may or may not be true – who knows. Be skeptical.

Plus, a lot of stocks here are just Motley Fool picks. Very rarely do you see a stock discussed that hasn’t been picked by a Fool paid service.

As for NKTR, it is getting crushed. However, even though it was/is a darling, I doubt we’ll see it affect the ports here as people will have either “gotten out just in time” or “averaged down below the current price.”

it is interesting how in many cases some get in and out just at the right time.

There may be some way to feel the pulse of the market and go with it and that’s maybe what they are doing? However like anything else, it does not always work.
It is interesting to see the confidence in the case of NKTR: buying on its way down throughout the day because of an understanding of ‘miscommunication or misinterpretation of the data’.

In many cases some just play the bounce but I don’t know in this is a case like that. I don’t follow NKTR. Even for the businesses I follow I have no idea in the short term if a fall is a short term opportunity or not. I don’t understand how a 3 days rule is invoked before getting in. Sometimes it goes back right up and sometimes it sideways for a while or falls further. To me in the short term it s a toss but if there is really a case of misinterpreted data then there might be some reasons for a quick snap back. I get a sense that is the idea floating around now for NKTR.

At any rate I need much more time before I can think of anything in any amount of confidence about any stock. Even then I am wrong often.


1 Like