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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Bloomberg Business

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Speaker 1: Wait inside from the reporters and editors who bring you

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Speaker 1: America's most trusted business magazine, plus global business, finance and

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Speaker 1: tech news. The Bloomberg Business Week podcast with Carol Messer

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Speaker 1: and Tim Stenebeck from Bloomberg Radio.

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Speaker 2: One other name that is on our radar and stock

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Speaker 2: shares of Alphabet down about two point three percent. It's

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Speaker 2: been on our mind all this week. You remember on

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Speaker 2: Monday the stock dropped about four and a half percent

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Speaker 2: amid renewed fears about Google's AI offerings, and that after

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Speaker 2: a research note from Milius research analyst Ben Wrightss, who

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Speaker 2: noted that problems with AI tools may fuel the perception

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Speaker 2: that Google is an unreliable source for AI his words,

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Speaker 2: and create an opening for competitors. Ben Writs is also

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Speaker 2: specifically highlighting the possibility of users growing concerned.

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Speaker 3: About Google's bias.

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Speaker 2: Our Ed Ludlows Booth with Ben Rightsis earlier this week

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Speaker 2: about his note and concerns on Google's AI strategy.

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Speaker 3: Check it out.

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Speaker 4: You want to make sure they don't have a bud

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Speaker 4: light moment, and we're not sure yet. I don't want

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Speaker 4: to weigh in on the merits of what they did

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Speaker 4: or the debate. It's just real simple. When you alienate

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Speaker 4: a part of the population and they believe that you

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Speaker 4: may not be a source of truth, that's not good

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Speaker 4: for business in their business.

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Speaker 5: That was Ben rightsis speaking to our own ed Ludlow

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Speaker 5: earlier this week, Alphabet CEO Sunder Pachai responding to the

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Speaker 5: concerns as stock is now done nearly six percent so

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Speaker 5: far this week. Thunder Pachai is saying in an email

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Speaker 5: to employees, quote, we have been arguing that search behavior

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Speaker 5: is about to change with new AI infused futures. This,

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Speaker 5: once intigestion is changed by itself, creates opportunities for competitors,

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Speaker 5: but even have a meaningful portion of user growth. Continued

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Speaker 5: about Google's hallucinations and bias. Excuse me? That was from

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Speaker 5: rightsis I should say under Pachaise say, no AI is perfect,

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Speaker 5: especially as this submerging stage of the industry's development, But

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Speaker 5: we know the bar is high for us and we'll

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Speaker 5: keep at it for however long it takes.

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Speaker 2: This has been and we're just trying to keep track

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Speaker 2: of it because there's been a back and forth going

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Speaker 2: on all week here, So let's get to it. We

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Speaker 2: knew we had to get to the bottom of the

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Speaker 2: concerns and what is going on in Alphabet and its

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Speaker 2: key Google unit. So with us is the co host

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Speaker 2: of Bloomberg Technology and BTV Ed Ludlow. He's in our

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Speaker 2: San Francisco bureau, and also with us as Bloomberg News

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Speaker 2: Technology reporter, Davey Alba in New York City.

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Speaker 3: And I want to start with you.

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Speaker 2: At the heart of this is Gemini, formerly barred Google's

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Speaker 2: flagship AI products. Step back for us, the criticism from

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Speaker 2: the analyst, the chief concerns. You talked with him, and

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Speaker 2: then let's get into Sondar Pachai's response.

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Speaker 6: Sure, and by the way, not just Tim, you know,

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Speaker 6: I speaking to a lot of people that the investor

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Speaker 6: concern is right that Gemini is the poster for Google

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Speaker 6: and it's public facing AI tools and competence. But the

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Speaker 6: deeper concern is that that AI technology is going to

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Speaker 6: spread and underpin all of the things we know Google

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Speaker 6: for search, YouTube in the long run, and those are

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Speaker 6: the bread and butter businesses. And that's a concern, right,

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Speaker 6: It's an issue of trust and what I find extraordinary

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Speaker 6: about this story. I applaud you and commend you guys

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Speaker 6: for being so thorough on explaining what happened. But investors

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Speaker 6: do have short memories. If you go back to exactly

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Speaker 6: one year ago, what happened. Google released Barred and in

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Speaker 6: that demonstration video, it was asked about the Hubble telescope.

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Speaker 6: You may remember, I believe I came on the show

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Speaker 6: with you and talked about it, and it gave an

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Speaker 6: incorrect answer, and what played out was downward pressure on

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Speaker 6: the stock significant We're seeing the same thing play out

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Speaker 6: this week. Trust has been damaged and that's hurting the shehes.

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Speaker 5: And ed what do you make of Sunder Pitcha's response

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Speaker 5: the way he tried to handle this yesterday at the company.

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Speaker 6: Yeah, I mean it's a pretty direct and frank admission.

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Speaker 6: You know that. Verbatim, he said that the answers given

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Speaker 6: by the text and image generation side of Gemini insulted

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Speaker 6: and offended people, and it was unacceptable. What I'm interested

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Speaker 6: to hear from Davey is that he said they've got

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Speaker 6: teams out working around this on this around the clock, right, Well,

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Speaker 6: how do you fix it?

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Speaker 3: Well?

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Speaker 7: And let's so.

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Speaker 2: Davey come on in your story with with your Bloomberg colleagues,

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Speaker 2: digs into internally what's been going on at Google, specifically

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Speaker 2: around its ambitious AI strategy. I mean, February was supposed

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Speaker 2: to be a pretty good month from them, but it

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Speaker 2: hasn't played out. Tell us what's been going on behind

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Speaker 2: the scenes.

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Speaker 8: Yeah, you know, you're right. February was supposed to be

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Speaker 8: a banner month for Google and it's AI products. It

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Speaker 8: released a bunch of updates, including some impressive new upgrades

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Speaker 8: to Gemini, an open source model called Gemma, and you know,

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Speaker 8: more context windows so you can kind of querry the

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Speaker 8: AI for longer text and video. But you know, this

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Speaker 8: controversy has been playing out all week, and our reporting

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Speaker 8: found that the way Google rolled out this technology included

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Speaker 8: a technical fix that would transform the crop that you

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Speaker 8: would actually send to Google and kind of force some

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Speaker 8: outputs that would try to mitigate the inherent biases of AI,

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Speaker 8: given that it's trained on such a corpus of data

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Speaker 8: that does preference you know, sort of Western images and stereotypes,

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Speaker 8: and and so Google basically over corrected in releasing Gemini.

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Speaker 8: And now you know the company is trying to work

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Speaker 8: hard to fix it. But I in my opinion, this

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Speaker 8: is going to be a long journey for them. They

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Speaker 8: will have to really take a look at how they

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Speaker 8: built this product from the ground up and try to

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Speaker 8: see what fixes they can make to the fundamental product

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Speaker 8: rather than kind of a band aid fix that they

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Speaker 8: rolled out.

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Speaker 5: Well, I want to throw it back to ed just

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Speaker 5: for a second here to help contextualize where Gemini is

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Speaker 5: slash was when it comes to lms that are out there,

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Speaker 5: like where does it compare to open ais and other

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Speaker 5: ones that meta platforms perhaps are working on, and either

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Speaker 5: ones from other companies as well.

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Speaker 6: Well, Look, I would I think Davey would agree that

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Speaker 6: the way Alphabet and Google Alphabet, the parirent of Google,

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Speaker 6: have rolled out first Barred and now Gemini the kind

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Speaker 6: of all encompassing generative AI tool, has been more careful

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Speaker 6: and in different stages than others have rolled out their chatbots.

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Speaker 6: You know, they did it with limited beta access at first,

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Speaker 6: opening it up to a wider audience. I do think

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Speaker 6: it's important tim to remember kind of what happened to

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Speaker 6: set this all off, which is basically Gemini was asked

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Speaker 6: what was worse, Hitler or Elon Musk and that's a

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Speaker 6: very layman's and short answer. But the response that the

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Speaker 6: Gemini bot gave was it's hard to say, and so

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Speaker 6: that is what spurred the debate online. The problem being

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Speaker 6: the root of your question is we are twelve months

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Speaker 6: on from the general release and so that's worrying, right,

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Speaker 6: because if you go back in history, Google is at

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Speaker 6: the advent of the R and D that went into

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Speaker 6: early AI. Fast forward to the first twelve months of commercialization,

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Speaker 6: and that response on that specific question has got a

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Speaker 6: lot of people saying, well, how on earth could Google,

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Speaker 6: of all companies, allowed it to get to this stage, right.

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Speaker 2: And you know, Davey considering that Google you right, you

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Speaker 2: guys write in your story that's on the bloomberd today

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Speaker 2: that Google pioneered some of the techniques that.

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Speaker 3: Are today at the heart of the AI boom.

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Speaker 2: So it's kind of ironic, But come on in on

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Speaker 2: some of what we just heard from ed in terms

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Speaker 2: of what's been going on and what they're finding out

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Speaker 2: some of the issues.

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Speaker 8: Yeah, you know, this is a problem for all large

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Speaker 8: scale AI systems, not just Google. This is something that

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Speaker 8: open AI faces and you know metas LM faces. The

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Speaker 8: fact is that these AI systems are trained on all

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Speaker 8: of the Internet's data basically, and if you think about

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Speaker 8: what's on the Internet, a lot of it is kind

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Speaker 8: of garbage. And so the way that the AI mirrors

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Speaker 8: what it's trained on is a huge problem and one

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Speaker 8: that these companies don't have a an elegant fix for.

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Speaker 8: So it ads right. Google has been absolutely way more

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Speaker 8: careful than some of its other peers in rolling out

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Speaker 8: its products. It usually does so in experimental stages first,

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Speaker 8: But the problem is that there is no other way

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Speaker 8: to train these AI systems, and so so when you

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Speaker 8: have this fundamental issue of the AI kind of being problematic,

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Speaker 8: what they can do is apply sort of hard coded

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Speaker 8: fixes on it, technical fixes, and in this case, our

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Speaker 8: reporting found, you know, they may have gone a little

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Speaker 8: too far, which is how you get these absurd answers

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Speaker 8: of like who is worse Elon Musker or Hitler, And

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Speaker 8: it's like, oh, waffling, like we can't say one way

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Speaker 8: or the other.

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Speaker 2: So guys, we got about a minute left and let

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Speaker 2: me go to you first, So how should we And

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Speaker 2: I'm thinking about the Bloomberg audience of investors trying to say, well,

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Speaker 2: wait a minute, is.

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Speaker 3: This a really big issue.

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Speaker 2: This is just part of a bigger, broader story as

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Speaker 2: we wait our way through this new world of AI, Like,

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Speaker 2: what is it?

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Speaker 7: Yeah, it's hard for me to answer.

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Speaker 6: I'll go with investors vote with their feet, right, And

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Speaker 6: the negative share reaction this week was not as severe

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Speaker 6: as the negative reaction one year ago in that example

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Speaker 6: of Bard making a mistake. You just have to continue

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Speaker 6: to see how investors interpret the get picture. How does

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Speaker 6: Gemini Gemini relate to its core businesses and either improve

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Speaker 6: them or cause more concern?

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Speaker 2: Davie saving twenty five seconds for you your thoughts forward,

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Speaker 2: you know, as you continue to report this out.

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Speaker 8: Yeah, I'm curious to see what fixes Google will have

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Speaker 8: going forward. The CEO of DeepMind, Demissabis, had just said

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Speaker 8: this week that he intends for this feature to go

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Speaker 8: back online within the next couple of weeks. And I

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Speaker 8: think if they don't have anything more than kind of

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Speaker 8: the band aid fix that we saw, then you know what,

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Speaker 8: investors will probably take note and vote accordingly.

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Speaker 2: Investors not shy when there's any kind of AI angle

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Speaker 2: that that disappoints guys.

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Speaker 3: This is exactly what we wanted to do.

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Speaker 2: A deep dive on this which has been over the

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Speaker 2: news throughout the week, co host to Bloomberg Technology Ed Ludlow,

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Speaker 2: and of course our thanks to Bloomberg News tech reporter

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Speaker 2: Davy Alba.

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Speaker 1: You're listening to the Bloomberg Business Week podcast Can't Just

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Speaker 1: Look five weekday afternoons from two to five pm Eastern

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Speaker 1: a Bloomberg Business app or want us Live on YouTube.

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Speaker 2: Well shares of the power generation company energ Energy hitting

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Speaker 2: a record high today inter day before dropping back this

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Speaker 2: following its latest quarterly update, the company reaffirming its twenty

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Speaker 2: twenty four guidance and an upbeat forecast for twenty twenty

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Speaker 2: four adjusted EBITA. So we continue to get some news

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Speaker 2: and earnings reports, including on some of the energy names.

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Speaker 5: Yeah, and it's important to follow, of course, because Bloomberg

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Speaker 5: News recently reported how the US power grid is struggling

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Speaker 5: to maintain an even flow of electricity and putting homes

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Speaker 5: at risk. It was a big take a couple of

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Speaker 5: weeks ago. We covered it here on the program. So

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Speaker 5: with more on some of the trend shaping the electricity

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Speaker 5: sector as an investment play, We're joined by Timothy Kramer,

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Speaker 5: the CEO at CNIC Funds. It's home to the cnic

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Speaker 5: ice US Carbon Neutral Power Futures Index ETF, which has

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Speaker 5: about four million dollars in assets in the fund. That's,

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Speaker 5: according to Bloomberg, down about twelve percent since the beginning

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Speaker 5: training in May of last year, down about four percent

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Speaker 5: year to date. Tim joins us from Houston. Tim, good

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Speaker 5: to have you on the program today. Talk a little

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Speaker 5: bit about who this is for. Carol and I did

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Speaker 5: some digging in the Bloomberg terminal and it was it

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Speaker 5: was a bit tough to make sense of what exactly

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Speaker 5: is in the ETF and what it tracks, So give

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Speaker 5: us the details here, sure.

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Speaker 9: So what's in the ETF is electricity future So ICE

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Speaker 9: the Intercontinental Exchange has the futures listed. So just like

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Speaker 9: you've got crude oil futures, goal futures, et cetera, you've

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Speaker 9: got these futures on electricity. And so what the index

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Speaker 9: then the ETF has in it is it takes an

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Speaker 9: average of six of the major power trading hubs in

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Speaker 9: the US and it takes those futures and then it

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Speaker 9: weights them according to what the electricity consumption is in

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Speaker 9: the US.

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Speaker 3: So who is this for? I'm curious about you.

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Speaker 2: Guys have about a little bit more than four million

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Speaker 2: dollars in assets under management.

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Speaker 3: Who do you target with this?

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Speaker 8: Who?

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Speaker 2: What kind of exposure is an investor looking for by

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Speaker 2: tapping into this ETF?

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Speaker 9: Sure, So electricity is the most consumed commodity in the

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Speaker 9: US on a retail notional basis, but up until now

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Speaker 9: it hasn't been in any ETF, any index, any mutual fund, nothing.

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Speaker 9: So right now, if you take a look, modern portfolio

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Speaker 9: theory says that you should have somewhere between five and

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Speaker 9: fifteen percent of your aun allocated to commodities, and that's

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Speaker 9: for portfolio diversification and for inflation protection. So if you

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Speaker 9: take a look, pensions and endowments typically have about three

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Speaker 9: percent right now allocation, and there's like over eight hundred

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Speaker 9: billion dollars tied with the Bloomberg Commodity Index and other

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Speaker 9: other commodity indexes. So this is geared towards a few

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Speaker 9: different types of audiences. The first would be we'll say

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Speaker 9: model portfolio. So if you take a look, a lot

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Speaker 9: of the major platforms have been pushing a sixty forty portfolio,

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Speaker 9: so sixty percent equity forty percent debt, and now they're

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Speaker 9: trying to find tune that a bit, and so they're

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Speaker 9: pushing like a sixty thirty five to five with the

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Speaker 9: five being commodities. And so if you look back over

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Speaker 9: the past three, five and seven years, on an absolute

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Speaker 9: basis and on a risk adjusted basis, the sixty thirty

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Speaker 9: five to five has been beating the sixty forty. But

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Speaker 9: if you do a sixty thirty five three to two,

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Speaker 9: three in commods and two in electricity, it beats everything

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Speaker 9: on an absolute and a risk adjusted basis. So we

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Speaker 9: think a model portfolio for investors would make sense. And

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Speaker 9: then for the pensions and endowments, this gives you inflation

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Speaker 9: protection because CPI is two point five percent electricity month

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Speaker 9: in and month out right, and this person the index

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Speaker 9: is eighty percent related to inflation.

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Speaker 5: I saw Carol furiously writing down every number you just

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Speaker 5: mentioned that, Timothy, Hey, So I do have to ask though,

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Speaker 5: in terms of exposure to commodities. There are lot of

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Speaker 5: different ways to get exposure to commodities. So somebody watching

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Speaker 5: could be saying, okay, well, you know, I could buy

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Speaker 5: this etf or I could buy I could buy crude

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Speaker 5: I could buy natural gas, I could buy coal. These

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Speaker 5: are all things that are used in the US to

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Speaker 5: generate power. Why not just go directly to the source

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Speaker 5: in terms of how that power is generator? I mean

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Speaker 5: they could buy equity, you know, equity in companies that

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Speaker 5: are solar companies.

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Speaker 9: So in terms of going to the actual source, we'll

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Speaker 9: go with what the occrude natural gas that you mentioned first.

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Speaker 9: The US has a stated goal of being eighty five

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Speaker 9: percent renewable generation by twenty thirty and one hundred percent

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Speaker 9: carbon free by twenty thirty five, and so you're seeing

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Speaker 9: less and less reliance on fossil fuels and more on

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Speaker 9: other types of generation, and that creates a number of problems.

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Speaker 9: And so you get direct exposure to the electricity as

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Speaker 9: a commodity with this particular product. That's the first thing.

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Speaker 9: And then if you do the equities, well, you know,

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Speaker 9: you don't know if they'd hedge their exposure or not,

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Speaker 9: and they can have accounting irregularities and they got to

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Speaker 9: cover management and overhead. So you're not really getting the

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Speaker 9: clean direct exposure to the commodity itself as if you

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Speaker 9: as if you played the index or the ETI talk to.

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Speaker 2: Us about flows over four million in assets under management.

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Speaker 2: What kind of flows have you seen in and out

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Speaker 2: as of late?

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Speaker 9: So right now, we've got interest from some of the

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Speaker 9: platforms and from family offices, and we have seen some

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Speaker 9: people that have been treading this in terms of their

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Speaker 9: view on natural gas and or absolute price levels on commodities.

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Speaker 9: And I will point out that what happens is we

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Speaker 9: had probably the warmest winter January February of twenty four

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Speaker 9: that you know, we've ever had, and so that's kind

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Speaker 9: of depressed the price of this a little bit. And

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Speaker 9: so that was due to winel Nino phenomena. But we

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Speaker 9: are looking now for this summer for law Nina to

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Speaker 9: be a very hot and very dry summer. So we're

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Speaker 9: seeing interest in this pickback up for people that are

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Speaker 9: looking to try to profit or participate on that.

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Speaker 2: So Tim, is that it like you in terms of participation,

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Speaker 2: you're kind of relying on the weather in terms of

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Speaker 2: interest into the ETF. I'm just curious about what's the

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Speaker 2: strategy for getting AUM a little bit higher here?

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Speaker 9: Sure, So to get the AUM hire, we're having conversations

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Speaker 9: with the exact same pensions and endowments that we talked

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Speaker 9: about and we're also having the conversations with some of

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Speaker 9: the platforms about getting onto the model portfolios and getting

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Speaker 9: this more available to some of the retail investors.

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Speaker 5: Interested in your thoughts just on infrastructure and on the grid,

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Speaker 5: since you're so involved in this space, Tim, I mean,

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Speaker 5: there's been so much reporting, especially in your home state

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Speaker 5: in Texas after that grid failure a couple of years

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Speaker 5: ago during that really huge cold snap in the are

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Speaker 5: US grids up to snuff to handle increasing power consumption

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Speaker 5: as we do shift and start using more and more electricity.

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Speaker 9: The short answer is no. The easy way to describe

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Speaker 9: that is there's an article that came out the other

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Speaker 9: day that talks about completion rate, and so approximately eight

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Speaker 9: point seven percent of everything that goes into the development

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Speaker 9: queue gets built. So there's a lot of things that

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Speaker 9: are trying to get built as we're going towards that

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Speaker 9: one hundred percent renewable, but it's very difficult to get

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Speaker 9: them permitted and it takes a longer period of time

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Speaker 9: to do it. It's up from between two to three

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Speaker 9: years and now it ranges between four and seven years.

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Speaker 9: So the fact that it's difficult to get the stuff

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Speaker 9: permitted and it is taking longer to build. You need

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Speaker 9: to combine that with the fact that's you've got higher

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Speaker 9: expenses and so you know, higher interest rates, higher labor costs,

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Speaker 9: and things like that just make it more prohibitively expensive

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Speaker 9: to get the grid to where it needs to be

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Speaker 9: for the stability factor that you're referencing.

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Speaker 3: I am curious when you look at the electricity market.

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Speaker 2: I mean, we talk a lot about AI right and

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Speaker 2: machine learning and the amount of power that's going to

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Speaker 2: be needed. We talked about the autonomous vehicles, the amount

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Speaker 2: of power needed just inside the vehicle to make it

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Speaker 2: all happen if it's autonomous. In terms of the fundamentals,

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Speaker 2: the factors, the macro factors, what do you see tim

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Speaker 2: as the biggest factors impacting demand raising it over the

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Speaker 2: next couple of years.

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Speaker 9: You nailed it right. So a couple of sound bites

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Speaker 9: will be a Google search takes one wat of power,

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Speaker 9: an AI search takes one hundred wants and it takes

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Speaker 9: one thousand watts to train that. So the AI right

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Speaker 9: there tells you kind of what the demand is. You

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Speaker 9: guys talk about bitcoin. You've got it scrolling across your

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Speaker 9: screens and so when you look at bitcoin, forty percent

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Speaker 9: of all bitcoin in the world is mined in the

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Speaker 9: US and seventy percent of bitcoin's expense is electricity. And

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Speaker 9: then just the proliferation of data centers, the electricity demand

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Speaker 9: due to data centers alone for data centers should be

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Speaker 9: growing at about ten percent a year through like twenty thirty.

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Speaker 9: So just for what you talked about technology reasons, just

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Speaker 9: a massive name that we think is understated.

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Speaker 2: Biggest risk though to this strategy for you and just

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Speaker 2: got about twenty seconds here, sure.

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Speaker 9: I mean the biggest risk is we think from a

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Speaker 9: long term fundamental play that this looks good. The biggest

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Speaker 9: risk is just short term if we don't get you know,

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Speaker 9: demand due to weather. Yeah, I can depress prices a

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Speaker 9: little bit, but other than that, from a long term perspective,

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Speaker 9: we did all.

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Speaker 3: Right, got it?

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Speaker 2: Run tim great to get some time. Timothy Kramer our

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Speaker 2: CEFCN I S Funds.

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Speaker 1: You're listening to the Bloomberg Business Week podcast. Listen live

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Speaker 1: each weekdays starting at two pm Eastern on Apple car

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Speaker 1: Play and ANDROYD Auto with the Bloomberg Business ad. You

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00:19:39,480 --> 00:19:42,760
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Speaker 1: New York station. Just say Alexa play Bloomberg eleven thirty.

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Speaker 2: Yes, indeed, folks, he is in from the West Coast,

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Speaker 2: in from the state of California. He's also in charge

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Speaker 2: of investing for the largest teachers retirement systems, second largest

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Speaker 2: public pension here in the United States, which provides benefits

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Speaker 2: to California nearly did we say, one million public school

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Speaker 2: educators in their families. We're talking about the California State

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Speaker 2: Teachers Retirement System also known as COLSTERS, which by the way,

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Speaker 2: is also the largest educator only pension fund in the world,

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Speaker 2: and as of the end of last month, the investment

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Speaker 2: portfolio had more than three hundred and twenty five billion

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Speaker 2: in assets under management.

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Speaker 3: That's a nice little amount too many.

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Speaker 5: What of responsibility, I'd say, Chris Allman is who we're

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Speaker 5: talking about. He's chief investment officer of cal STIRS. He's

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Speaker 5: back with us here in the Bloomberg Interactive Brokers studios.

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Speaker 5: So Chris, it's good to see you. We're going to

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Speaker 5: talk about your future plans in a second. But you

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Speaker 5: shared with us an incredible stat just moments ago that

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Speaker 5: California teachers live longer than any other profession in California, which.

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Speaker 7: Is sort of any profession in the USA, any actroy

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Speaker 7: table think about it, that makes you talk about California.

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Speaker 7: They're all college educated, they're typically non smokers. They live

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Speaker 7: in California, so they have healthier lifestyles, eating habits, and

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Speaker 7: they're seventy two percent women and live longer than men.

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Speaker 7: So we have over four hundred teachers that are retired

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Speaker 7: over one hundred.

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Speaker 5: Years old, which I mean right, yeah, that means they're

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Speaker 5: dipping into their pension plans for longer than Oh yeah.

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Speaker 7: Longevity is a big challenge for me.

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Speaker 5: That's so interesting to hear. I mean, and what was

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Speaker 5: the stat about the teachers over one hundred?

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Speaker 7: Four hundred more? I think right now we're about four

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Speaker 7: hundred and fifty teachers that are over one hundred years old.

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Speaker 7: We write them a happy birthday card. At one hundred,

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Speaker 7: I kind of cringe a little bit because it's like, wow,

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Speaker 7: you know, we got a card back from a teacher

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Speaker 7: that was one hundred, very legible, writing thrilled about her

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Speaker 7: daughter that was eighty, her granddaughter that was sixty, and

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Speaker 7: telling us that our great guyanddaughter was a teacher and

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Speaker 7: thinking about retiring.

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Speaker 3: I think I'm going to move to California and become

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Speaker 3: a teacher.

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Speaker 7: It's too late now, Yeah, you gotta start when you're young.

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Speaker 2: So let's talk about though the investment environment, something we

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Speaker 2: always like to do. You guys have to you know,

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Speaker 2: guarantee that they're going to be the money there for

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Speaker 2: those who tap into this fund and this retirement fund.

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Speaker 2: How do you continue to think about it in today's environment,

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Speaker 2: and what's the smartest strategy and how first doesn't shift

439
00:22:05,000 --> 00:22:08,399
Speaker 2: Chris based on you know, we're day to day the

440
00:22:08,480 --> 00:22:10,040
Speaker 2: gyrations we obsess over it.

441
00:22:10,400 --> 00:22:13,040
Speaker 3: You've got to think longer term, bigger, broader to make.

442
00:22:12,920 --> 00:22:16,280
Speaker 7: Sure you're at Bloomberg because of the focused capital and

443
00:22:16,320 --> 00:22:18,439
Speaker 7: the long term. A conference that we're part of in

444
00:22:18,480 --> 00:22:20,560
Speaker 7: a group that we're really trying to help. The key

445
00:22:20,640 --> 00:22:22,760
Speaker 7: is to think long term. So I've got a thirty

446
00:22:22,800 --> 00:22:25,920
Speaker 7: year horizon. I think long term. We make I always

447
00:22:25,920 --> 00:22:27,879
Speaker 7: say we're a giant cruise ship out on the ocean.

448
00:22:28,160 --> 00:22:30,040
Speaker 7: We're not going to ever go to port. We're always

449
00:22:30,080 --> 00:22:33,320
Speaker 7: out in rough weather or smooth weather, and what we're

450
00:22:33,359 --> 00:22:36,000
Speaker 7: doing is making subtle course corrections. So I'm listening to

451
00:22:36,040 --> 00:22:39,760
Speaker 7: you guys every day on my car to work back home.

452
00:22:39,840 --> 00:22:43,160
Speaker 7: I'm a diehard listener to Bloomberg Radio, and I am

453
00:22:43,520 --> 00:22:46,480
Speaker 7: paying attention to the nuances in the market, but I

454
00:22:46,520 --> 00:22:51,359
Speaker 7: am not making giant corrections to that portfolio. It's long term.

455
00:22:51,400 --> 00:22:54,480
Speaker 7: You've got to have a thought that it's a marathon,

456
00:22:54,560 --> 00:22:56,879
Speaker 7: and every year is just one pace in a marathon

457
00:22:56,920 --> 00:22:58,240
Speaker 7: when you're a mile in a marathon.

458
00:22:58,359 --> 00:22:58,840
Speaker 1: So when you.

459
00:22:58,880 --> 00:23:02,320
Speaker 2: Listen to either conversations from the investor from the investing

460
00:23:02,320 --> 00:23:04,040
Speaker 2: space or when you listen to Bloomberg, what is it

461
00:23:04,040 --> 00:23:06,160
Speaker 2: that makes you sit up a little straight and say, oh,

462
00:23:06,440 --> 00:23:09,000
Speaker 2: that's an interesting trend or that's something significant that could

463
00:23:09,040 --> 00:23:11,000
Speaker 2: be a longer term investment play.

464
00:23:11,200 --> 00:23:13,520
Speaker 7: Carol, the old adage of don't fight the Fed. I'm

465
00:23:13,560 --> 00:23:16,440
Speaker 7: listening to what the Fed's saying today, what Jim Williams,

466
00:23:16,440 --> 00:23:18,639
Speaker 7: who's from Sacramento is saying, you know what, the New

467
00:23:18,720 --> 00:23:22,160
Speaker 7: York Fed. Listening to them first and foremost and paying

468
00:23:22,160 --> 00:23:26,000
Speaker 7: attention to their directions, but then the other overall trends

469
00:23:26,080 --> 00:23:28,919
Speaker 7: within the US market and the global markets, because it's

470
00:23:28,960 --> 00:23:30,640
Speaker 7: not just the US Central Bank we have to pay

471
00:23:30,680 --> 00:23:31,280
Speaker 7: attention to.

472
00:23:31,400 --> 00:23:33,400
Speaker 3: But global central bankers there Oh yeah.

473
00:23:33,320 --> 00:23:37,040
Speaker 7: No, because it we are a truly global portfolio. We

474
00:23:37,080 --> 00:23:39,480
Speaker 7: have a home country bias to the USA. It's over

475
00:23:39,520 --> 00:23:42,119
Speaker 7: half of the market and it's about seventy five percent

476
00:23:42,160 --> 00:23:45,439
Speaker 7: of our portfolio. But it still is interest rates first.

477
00:23:45,520 --> 00:23:50,080
Speaker 7: And you're really listening to whether people are greedy or fearful.

478
00:23:50,440 --> 00:23:53,000
Speaker 7: And the old Warren Buffett adage is still true. If

479
00:23:53,040 --> 00:23:55,959
Speaker 7: people are fearful, then that's time to be greedy. If

480
00:23:56,000 --> 00:23:59,520
Speaker 7: they're greedy like now, it's time to be a little fearful.

481
00:23:59,600 --> 00:24:02,120
Speaker 5: So when can you get greedy again? When are people

482
00:24:02,160 --> 00:24:02,880
Speaker 5: going to be fearful?

483
00:24:03,760 --> 00:24:06,600
Speaker 7: That's always a tough question. You know, it's the consumer

484
00:24:06,680 --> 00:24:08,840
Speaker 7: right now is really in a bad mood. But what

485
00:24:09,000 --> 00:24:12,800
Speaker 7: surprises me. They're flying on planes. All the airports are jammed,

486
00:24:13,000 --> 00:24:16,399
Speaker 7: they're going to restaurants, they're you know, the the lower

487
00:24:16,520 --> 00:24:20,200
Speaker 7: end consumer is struggling. But we hit a soft landing.

488
00:24:20,240 --> 00:24:23,720
Speaker 7: We're doing okay, and the markets are repeating record highs.

489
00:24:23,760 --> 00:24:25,919
Speaker 5: You've you've you've said, we've landed the plane.

490
00:24:26,119 --> 00:24:27,600
Speaker 7: Yep, look at that.

491
00:24:27,840 --> 00:24:28,720
Speaker 5: We hit a soft landing.

492
00:24:28,800 --> 00:24:29,800
Speaker 3: Well it's kind of interesting.

493
00:24:29,840 --> 00:24:31,040
Speaker 5: So you think we got to call here?

494
00:24:31,160 --> 00:24:34,600
Speaker 3: Okay, okay, okay.

495
00:24:34,840 --> 00:24:38,320
Speaker 7: I said it. I said it. Apparel. Back in December,

496
00:24:38,359 --> 00:24:41,560
Speaker 7: we hit the soft landing. It's done done. Inflation is

497
00:24:41,560 --> 00:24:43,680
Speaker 7: not totally under control. It's going to jump up to

498
00:24:43,760 --> 00:24:46,480
Speaker 7: three and fours and then back to two's. We're going

499
00:24:46,560 --> 00:24:48,600
Speaker 7: to be in a higher inflation environment. But that doesn't

500
00:24:48,640 --> 00:24:50,600
Speaker 7: mean the Fed is going to ease I think, well,

501
00:24:50,680 --> 00:24:51,840
Speaker 7: does the market right?

502
00:24:51,960 --> 00:24:53,560
Speaker 3: So does the Fed even need to cut rates?

503
00:24:54,600 --> 00:24:57,159
Speaker 7: They? I think for the markets sake they need to

504
00:24:57,200 --> 00:25:00,760
Speaker 7: come off, but maybe not more than three cuts in

505
00:25:00,800 --> 00:25:03,520
Speaker 7: this year at most. They do not need to ease back.

506
00:25:03,960 --> 00:25:07,399
Speaker 7: Real interest rates are probably around three percent. That's what

507
00:25:07,440 --> 00:25:08,040
Speaker 7: the FED is say.

508
00:25:08,480 --> 00:25:11,600
Speaker 3: Off landing. You're saying to maintain that's off landing.

509
00:25:11,640 --> 00:25:14,080
Speaker 7: They're gonna have, I think, to maintain it. Yeah. The economy,

510
00:25:14,200 --> 00:25:17,520
Speaker 7: you know, we hear every week about some companies with

511
00:25:17,640 --> 00:25:21,800
Speaker 7: job cuts. Employment though in other sectors is strong. A

512
00:25:21,840 --> 00:25:25,359
Speaker 7: lot of enthusiasmopsous say about the productivity games we'll see

513
00:25:25,400 --> 00:25:29,080
Speaker 7: in an AI. Those things have to play out over time,

514
00:25:29,119 --> 00:25:32,280
Speaker 7: and the FED shouldn't rush because inflation is sticky and

515
00:25:32,320 --> 00:25:33,920
Speaker 7: it's going to be difficult to maintain.

516
00:25:34,080 --> 00:25:35,440
Speaker 5: Hey, I want to talk a little bit about how

517
00:25:35,480 --> 00:25:38,119
Speaker 5: you buy and what you buy because you have a

518
00:25:38,160 --> 00:25:41,040
Speaker 5: real passive bias in addition to a US bias. So

519
00:25:41,080 --> 00:25:44,120
Speaker 5: you said seventy five percent of the portfolio is US focused.

520
00:25:45,040 --> 00:25:47,800
Speaker 5: How much that is equities? And of those equities, what

521
00:25:47,840 --> 00:25:48,320
Speaker 5: are you buying?

522
00:25:49,359 --> 00:25:52,320
Speaker 7: The key to us is we're about forty eight percent

523
00:25:52,960 --> 00:25:56,920
Speaker 7: are global equity. Most over half of that's in the USA.

524
00:25:57,119 --> 00:25:59,680
Speaker 7: We are passive in others. We own the Russell three

525
00:25:59,680 --> 00:26:03,199
Speaker 7: thousand and index from Microsoft all the way down to

526
00:26:03,200 --> 00:26:06,080
Speaker 7: the bottom stock and we're going to hold that, so

527
00:26:06,119 --> 00:26:08,800
Speaker 7: we own the Magnificent seven. Those are amongst our top

528
00:26:09,320 --> 00:26:12,240
Speaker 7: largest holdings. But we still have fixed income, we have

529
00:26:12,359 --> 00:26:15,080
Speaker 7: real estate, we have private equity. We're broadly to versided,

530
00:26:15,119 --> 00:26:19,280
Speaker 7: we have infrastructure, we have some inflation sensitive assets. So

531
00:26:19,400 --> 00:26:22,520
Speaker 7: it's a very diverse sided portfolio, but a blend of

532
00:26:22,520 --> 00:26:23,960
Speaker 7: public and private holdings.

533
00:26:24,040 --> 00:26:24,520
Speaker 3: What's been your.

534
00:26:24,480 --> 00:26:26,560
Speaker 2: Biggest change since you kind of tend to write, set

535
00:26:26,560 --> 00:26:29,679
Speaker 2: a strategy and let it stick. You're not kind of

536
00:26:29,680 --> 00:26:31,439
Speaker 2: moving in and out every day. That's not what you

537
00:26:31,480 --> 00:26:33,840
Speaker 2: guys do. Is there anything though in the last six

538
00:26:33,880 --> 00:26:36,560
Speaker 2: to twelve months that's been something new or new.

539
00:26:38,200 --> 00:26:40,960
Speaker 3: You know, kind of just playing around with it a

540
00:26:40,960 --> 00:26:41,440
Speaker 3: little bit.

541
00:26:41,600 --> 00:26:44,280
Speaker 7: You guys have talked about private credit and the concern

542
00:26:44,359 --> 00:26:47,720
Speaker 7: about private credit. The money going in. If anything, we're

543
00:26:47,760 --> 00:26:51,359
Speaker 7: still invested, but we've slowed down. The advantage to private

544
00:26:51,400 --> 00:26:54,160
Speaker 7: credit is when rates are rising, being a variable rate,

545
00:26:54,200 --> 00:26:55,919
Speaker 7: it's going to climb with it. Well, now rates are

546
00:26:56,000 --> 00:26:57,879
Speaker 7: peaked and now they're going to start easing off, so

547
00:26:57,960 --> 00:27:01,359
Speaker 7: there's no reason to rush in a nice alternative to

548
00:27:01,440 --> 00:27:05,200
Speaker 7: general fixed income and trading bonds in this market has been.

549
00:27:05,080 --> 00:27:06,920
Speaker 3: Tough, but tempering back a little bit.

550
00:27:07,440 --> 00:27:11,119
Speaker 7: Just pacing ourselves, I think, a bit more discretionary and

551
00:27:11,160 --> 00:27:14,159
Speaker 7: paying attention. Anytime you have like this kind of an

552
00:27:14,240 --> 00:27:17,119
Speaker 7: environment where you're gonna have some stress coming up in

553
00:27:17,160 --> 00:27:20,400
Speaker 7: the year in terms of people that can't pay, then

554
00:27:20,440 --> 00:27:22,600
Speaker 7: you want to have to do your credit analysis and

555
00:27:22,640 --> 00:27:24,200
Speaker 7: pay attention to your exposures.

556
00:27:24,480 --> 00:27:27,200
Speaker 5: So Chris, we got to talk about your your plans

557
00:27:27,200 --> 00:27:29,120
Speaker 5: because you said last month that you were stepping down

558
00:27:29,160 --> 00:27:33,840
Speaker 5: after twenty four years at Calstairs. Why now, what's next?

559
00:27:34,320 --> 00:27:38,080
Speaker 7: Hey, age, I've been there long enough time to retire,

560
00:27:38,160 --> 00:27:41,480
Speaker 7: slow down, do some bike riding, and then just do

561
00:27:41,560 --> 00:27:44,440
Speaker 7: a few other things. I have a real passion about

562
00:27:44,440 --> 00:27:47,240
Speaker 7: climate change and talking to US and non US investors

563
00:27:47,240 --> 00:27:50,760
Speaker 7: about that. I think that the energy transition we have

564
00:27:50,800 --> 00:27:54,600
Speaker 7: to go through calstirs we say fifteen years, I'm telling

565
00:27:54,600 --> 00:27:57,480
Speaker 7: people it's seven years. Twenty thirty sounds like a long time.

566
00:27:57,680 --> 00:28:00,840
Speaker 7: What the transition that we really have to move away

567
00:28:00,840 --> 00:28:08,600
Speaker 7: from hydrocarbons is our source of electricity, propulsion, manufacturing, agriculture,

568
00:28:08,640 --> 00:28:12,080
Speaker 7: and we have to find other alternative sources. We need

569
00:28:12,119 --> 00:28:15,439
Speaker 7: more energy around the whole world, and we need different energy.

570
00:28:16,240 --> 00:28:21,119
Speaker 2: I don't disagree. It's become though, a political firestorm in

571
00:28:21,200 --> 00:28:24,240
Speaker 2: terms of so I don't know. Do you think that's

572
00:28:24,280 --> 00:28:26,920
Speaker 2: going to continue to kind of slow that process down,

573
00:28:26,960 --> 00:28:28,880
Speaker 2: that shift away from fossil Oh, this is.

574
00:28:28,800 --> 00:28:31,680
Speaker 7: A hard change. Think back to when we move from

575
00:28:31,880 --> 00:28:35,600
Speaker 7: blackberries to iPhones. Everybody jumped on them. Number one. They

576
00:28:35,600 --> 00:28:39,480
Speaker 7: were a huge investment and they were free because the

577
00:28:39,520 --> 00:28:43,280
Speaker 7: telephone company embedded the cost to you. Everybody moved instantly.

578
00:28:43,720 --> 00:28:46,000
Speaker 7: This transition is not going to be free, it's not

579
00:28:46,080 --> 00:28:49,640
Speaker 7: necessarily more efficient. It's a change, and it's probably going

580
00:28:49,680 --> 00:28:52,440
Speaker 7: to be a little bit expensive, So Carol, Therefore, you're

581
00:28:52,480 --> 00:28:54,400
Speaker 7: going to see fits and starts. You're going to see

582
00:28:54,440 --> 00:28:58,800
Speaker 7: people who've devoted their life in the industry to traditional

583
00:28:58,800 --> 00:29:01,840
Speaker 7: methods hanging on onto those. We still have coal plants

584
00:29:01,840 --> 00:29:05,240
Speaker 7: around the world for goodness sake, but mother Nature is

585
00:29:05,280 --> 00:29:08,080
Speaker 7: going to teach us all a very harsh lesson right

586
00:29:08,120 --> 00:29:10,320
Speaker 7: on the TV screens. You know, there are big brush

587
00:29:10,320 --> 00:29:13,640
Speaker 7: fires in the middle of winter in Texas, and then

588
00:29:13,640 --> 00:29:17,840
Speaker 7: they're gonna have snow. And you know La had a hurricane,

589
00:29:17,960 --> 00:29:20,920
Speaker 7: an earthquake and then a fire. You know we're gonna

590
00:29:20,960 --> 00:29:21,840
Speaker 7: have these extremes.

591
00:29:22,600 --> 00:29:23,920
Speaker 2: We look forward to the work you do on that.

592
00:29:24,000 --> 00:29:25,480
Speaker 2: Come back when you want to talk more about that,

593
00:29:25,560 --> 00:29:28,560
Speaker 2: Chris Allman. We've always appreciated the conversations with you, Chief

594
00:29:28,560 --> 00:29:34,120
Speaker 2: Investment Officer of Costers joining us in studio, Chris, thank you, Mac.

595
00:29:35,800 --> 00:29:36,480
Speaker 7: A journal.

596
00:29:37,520 --> 00:29:38,480
Speaker 4: How about you let me drive?

597
00:29:39,000 --> 00:29:45,360
Speaker 6: No, no, no, no, all right, please, I'll gravels Wait, I

598
00:29:45,440 --> 00:29:46,000
Speaker 6: want to drive.

599
00:29:48,280 --> 00:29:49,160
Speaker 5: It's a good question.

600
00:29:52,960 --> 00:29:54,520
Speaker 1: This is the drive to the.

601
00:29:54,480 --> 00:29:57,400
Speaker 3: Globe, doing well by around each.

602
00:29:57,280 --> 00:30:01,200
Speaker 2: Other down on Blueberg Radio, all right, everybody well, Our

603
00:30:01,200 --> 00:30:03,479
Speaker 2: next guest says it's time to party like it's nineteen

604
00:30:03,600 --> 00:30:06,760
Speaker 2: ninety nine. That's because he says, there is quote no

605
00:30:06,920 --> 00:30:08,880
Speaker 2: doubt that twenty twenty four is shaping up to be

606
00:30:08,920 --> 00:30:11,000
Speaker 2: the best year since nineteen ninety nine.

607
00:30:11,000 --> 00:30:13,360
Speaker 3: So that'll take you a few decades back.

608
00:30:13,480 --> 00:30:16,680
Speaker 5: I went back a few decades using Bloomberg data, and

609
00:30:16,760 --> 00:30:19,080
Speaker 5: I found the Nasdaq one hundred that year was up

610
00:30:19,120 --> 00:30:22,400
Speaker 5: a cool one and two percent. But Carol, we all

611
00:30:22,400 --> 00:30:23,760
Speaker 5: know what happened after.

612
00:30:23,520 --> 00:30:26,280
Speaker 3: That, Yeah, exactly, the tech sell off in a big

613
00:30:26,360 --> 00:30:26,760
Speaker 3: the dot.

614
00:30:26,640 --> 00:30:28,320
Speaker 7: Com boom, the bubble burst.

615
00:30:28,800 --> 00:30:30,360
Speaker 2: All right, So let's get to it. Let's drive to

616
00:30:30,400 --> 00:30:33,520
Speaker 2: the clothes with Louis Navalier. He's chairman, founder and CIO

617
00:30:33,680 --> 00:30:35,600
Speaker 2: of the company that bears his name. He joins us

618
00:30:35,600 --> 00:30:36,240
Speaker 2: from Florida.

619
00:30:36,920 --> 00:30:39,080
Speaker 3: Louis, it's been a while. Nice to have you here.

620
00:30:40,320 --> 00:30:43,000
Speaker 2: You know, I'm not I say this to folks with

621
00:30:43,760 --> 00:30:47,440
Speaker 2: utmost respect because you've seen a few investment cycles.

622
00:30:47,800 --> 00:30:50,080
Speaker 3: So how do you describe the cycle that we're in?

623
00:30:50,320 --> 00:30:51,200
Speaker 3: Is there more?

624
00:30:51,360 --> 00:30:55,400
Speaker 2: We were just talking with Chris Allman talking about fear

625
00:30:55,480 --> 00:30:57,360
Speaker 2: versus greed. He thinks there's a lot of greed in

626
00:30:57,360 --> 00:30:58,000
Speaker 2: this market.

627
00:30:58,040 --> 00:30:58,960
Speaker 3: How do you see it.

628
00:31:00,280 --> 00:31:02,800
Speaker 10: Well, there's a lot agreed because they AI stocks are

629
00:31:02,840 --> 00:31:06,600
Speaker 10: ten percent of global market capitalization, but the two leading

630
00:31:06,640 --> 00:31:09,960
Speaker 10: hardware AI stocks have over two hundred percent sales growth,

631
00:31:10,440 --> 00:31:13,760
Speaker 10: So that's justified in my opinion. I mean, the software

632
00:31:13,760 --> 00:31:16,880
Speaker 10: has ways to catch up and to be monetized. But

633
00:31:17,480 --> 00:31:21,440
Speaker 10: you know, Nvidia's super microcomputer are worth their capitalizations and

634
00:31:21,520 --> 00:31:23,680
Speaker 10: they do not trade it very high multiples. When you

635
00:31:23,720 --> 00:31:27,760
Speaker 10: look out to fiscal twenty twenty five, I mean super

636
00:31:27,800 --> 00:31:32,640
Speaker 10: micros under eighteen times forecasts earnings. Nivida is a little higher,

637
00:31:32,640 --> 00:31:33,800
Speaker 10: but it's it's a monopoly.

638
00:31:34,040 --> 00:31:36,080
Speaker 2: These are all these are all names that you would

639
00:31:36,120 --> 00:31:38,240
Speaker 2: own it by. I'm kind of obsessed with super Micro too.

640
00:31:38,240 --> 00:31:39,680
Speaker 2: I mean the stacks up one hundred and eighty nine

641
00:31:39,680 --> 00:31:41,360
Speaker 2: percent this year. It's not kind of a name that

642
00:31:41,400 --> 00:31:43,440
Speaker 2: we talk about a lot, but we are talking a

643
00:31:43,480 --> 00:31:46,600
Speaker 2: lot about it because of its significance, it's gains, its moves,

644
00:31:46,840 --> 00:31:50,040
Speaker 2: and it's fundamentals. But these are names you've owned, owned

645
00:31:50,080 --> 00:31:52,520
Speaker 2: for a long time, or just been piling money into it.

646
00:31:52,520 --> 00:31:56,440
Speaker 10: As of late, those are our two largest holdings. Navidia

647
00:31:56,440 --> 00:31:58,840
Speaker 10: I've had for over five years. It's my second time

648
00:31:58,920 --> 00:32:02,680
Speaker 10: back in Navidia, dig it out temporarily. Super Micro we've

649
00:32:02,680 --> 00:32:06,480
Speaker 10: had for over two years, and our biggest holdings after

650
00:32:06,520 --> 00:32:10,280
Speaker 10: that would be Nova nor disc Eli, Lilly the weight

651
00:32:10,320 --> 00:32:14,000
Speaker 10: loss drugs. Those are capturing a lot of market share.

652
00:32:14,160 --> 00:32:16,480
Speaker 10: I will admit that even though we're seeing a lot

653
00:32:16,480 --> 00:32:19,160
Speaker 10: of breath in small caps since an early January effect

654
00:32:19,200 --> 00:32:24,200
Speaker 10: late last year that it's still narrow. My opinion is

655
00:32:24,440 --> 00:32:27,680
Speaker 10: only three of the seven of the Magnificent seven had

656
00:32:27,800 --> 00:32:31,760
Speaker 10: really spectacular results and money is now moving and super

657
00:32:31,760 --> 00:32:34,200
Speaker 10: Micro's beneficiary of that, and so it was a Nova

658
00:32:34,240 --> 00:32:35,360
Speaker 10: Noor disc in Lily.

659
00:32:36,360 --> 00:32:38,920
Speaker 5: Talk to us a little bit about areas that you've

660
00:32:38,920 --> 00:32:40,800
Speaker 5: missed in recent years, because you're in a pretty good

661
00:32:40,800 --> 00:32:43,920
Speaker 5: position having owned in video, super Micro, Nova nor Disc

662
00:32:43,960 --> 00:32:47,200
Speaker 5: and Eli Lilly, what were some missteps in recent years

663
00:32:47,200 --> 00:32:48,200
Speaker 5: if you could go back in time.

664
00:32:49,240 --> 00:32:52,320
Speaker 10: Meta. I missed Meta because it's a high beta stock

665
00:32:53,240 --> 00:32:56,120
Speaker 10: and it went higher on short covering. And the way

666
00:32:56,200 --> 00:32:59,040
Speaker 10: my system works is we look for high alpha, low deviation,

667
00:32:59,760 --> 00:33:01,880
Speaker 10: So anytime we get a high bay of stock, it

668
00:33:01,920 --> 00:33:04,480
Speaker 10: doesn't quite fit our model. So there will be some

669
00:33:04,520 --> 00:33:09,040
Speaker 10: extraordinary stocks running that we will miss, you know, I'll

670
00:33:09,040 --> 00:33:11,360
Speaker 10: be honest with you. Google is hard to figure out

671
00:33:11,520 --> 00:33:16,360
Speaker 10: because the guidance is poor. Amazon's a little easier to

672
00:33:16,400 --> 00:33:19,280
Speaker 10: figure out. Lately it's mostly cloud computing. But the retail

673
00:33:19,560 --> 00:33:21,920
Speaker 10: society is finally going to make some money, we think,

674
00:33:22,520 --> 00:33:26,960
Speaker 10: And but you know, Meta is the big one we missed.

675
00:33:27,280 --> 00:33:28,120
Speaker 3: Do you like it now?

676
00:33:30,160 --> 00:33:33,360
Speaker 10: It ranks high on our quant criteria, but my fundamental criteria,

677
00:33:33,360 --> 00:33:36,240
Speaker 10: I'm not too crazy about it. The texts are funny.

678
00:33:36,400 --> 00:33:38,320
Speaker 10: You know, the more people they lay off, the more

679
00:33:38,360 --> 00:33:42,440
Speaker 10: the stocks rally. And you already have googling of people.

680
00:33:42,160 --> 00:33:45,760
Speaker 3: Because the year or years of what is it efficiency.

681
00:33:47,240 --> 00:33:50,440
Speaker 7: Yeah, so you got Apple with the Apple car today.

682
00:33:50,600 --> 00:33:56,240
Speaker 10: Of course you broke that news yesterday. You've got Amazon

683
00:33:56,520 --> 00:33:59,320
Speaker 10: becoming more efficient a lot of their delivery. They're trying

684
00:33:59,320 --> 00:34:02,320
Speaker 10: to sub out because it's not cost effective to have

685
00:34:02,360 --> 00:34:04,680
Speaker 10: a tube of toothpaste delivered to your house, so they

686
00:34:04,920 --> 00:34:08,520
Speaker 10: they're figuring that one out. But yeah, the meta is

687
00:34:08,600 --> 00:34:12,200
Speaker 10: laying off people. So maybe it is the AI revolution.

688
00:34:12,360 --> 00:34:15,200
Speaker 10: Maybe they will they will just be a company and

689
00:34:15,360 --> 00:34:18,719
Speaker 10: with some drune, some robots. You know, we'll find out.

690
00:34:18,880 --> 00:34:22,440
Speaker 10: But you know that we're not near that bubble that

691
00:34:22,480 --> 00:34:24,880
Speaker 10: we had in March of two thousand, that was pretty

692
00:34:24,880 --> 00:34:29,080
Speaker 10: bad back then. I don't have a multiple problem. You know.

693
00:34:29,120 --> 00:34:32,840
Speaker 10: My average multiple in large cap is barely eighteen times

694
00:34:33,360 --> 00:34:35,320
Speaker 10: this year's estimate earnings, and I got a lot of

695
00:34:35,320 --> 00:34:38,160
Speaker 10: earnings growth. A small cap it's well under ten times

696
00:34:38,160 --> 00:34:41,719
Speaker 10: this year's estimate earnings with even more earnings growth, So

697
00:34:41,920 --> 00:34:44,560
Speaker 10: I don't really have a multiple problem or evaluation problem

698
00:34:44,560 --> 00:34:47,120
Speaker 10: at this time. Obviously we would like the FED to

699
00:34:47,719 --> 00:34:48,600
Speaker 10: start putting rates.

700
00:34:48,719 --> 00:34:50,560
Speaker 2: Is that why you think it's time to party like

701
00:34:50,600 --> 00:34:52,840
Speaker 2: it's nineteen ninety nine, because you don't have a problem,

702
00:34:52,840 --> 00:34:55,400
Speaker 2: whether it's large caps or small caps Louis with the

703
00:34:55,480 --> 00:34:58,520
Speaker 2: valuations that are out there and the multiples.

704
00:34:58,800 --> 00:35:00,920
Speaker 10: I think the main reason is we have very easy

705
00:35:01,000 --> 00:35:03,920
Speaker 10: year of year comparisons on the next two quarters, and

706
00:35:03,960 --> 00:35:07,440
Speaker 10: we just had easier comparisons in the fourth quarter, and

707
00:35:07,480 --> 00:35:10,040
Speaker 10: you saw, you know, seventy six percent of the stocks it'sant

708
00:35:10,080 --> 00:35:14,640
Speaker 10: be beat the average surprises seven percent, I believe where

709
00:35:14,760 --> 00:35:18,680
Speaker 10: the video is a grand finale, and so we got

710
00:35:18,680 --> 00:35:20,799
Speaker 10: two more cores of good earnings. We got the FED

711
00:35:20,880 --> 00:35:23,680
Speaker 10: joining the party, and let's face it, in a presidential

712
00:35:23,680 --> 00:35:26,120
Speaker 10: election cycle, we tend to rally going into the election

713
00:35:26,640 --> 00:35:29,520
Speaker 10: because we will be promised everything and anything. You know,

714
00:35:30,680 --> 00:35:33,439
Speaker 10: there's now student loan relief. I thought the court ruled

715
00:35:33,440 --> 00:35:34,840
Speaker 10: you couldn't do that, but they're going to get do

716
00:35:34,880 --> 00:35:37,160
Speaker 10: it anyway. So you know, they're gonna tell us what

717
00:35:37,200 --> 00:35:40,640
Speaker 10: we what we want to hear, and that helps both

718
00:35:40,640 --> 00:35:43,879
Speaker 10: investor in consumer confidence and the US is so much

719
00:35:43,920 --> 00:35:46,120
Speaker 10: better shape than the rest of the world. We're food

720
00:35:46,120 --> 00:35:51,440
Speaker 10: and energy independent, and we got a strong currency, and

721
00:35:51,480 --> 00:35:56,200
Speaker 10: we're an oasis for foreign capital. So the only thing

722
00:35:56,239 --> 00:35:58,080
Speaker 10: to go wrong is, I guess if our definity gets

723
00:35:58,120 --> 00:36:00,400
Speaker 10: too big. I mean, the leading candidates are both going

724
00:36:00,440 --> 00:36:02,640
Speaker 10: to make the devisit big, So that's going to be

725
00:36:02,680 --> 00:36:03,480
Speaker 10: interesting to watch.

726
00:36:03,920 --> 00:36:06,879
Speaker 5: So louis, where would you put new money to work

727
00:36:06,960 --> 00:36:10,600
Speaker 5: right now? Given that, arguably people would say, okay, parts

728
00:36:10,640 --> 00:36:12,480
Speaker 5: of the market are high, though you argue that you

729
00:36:12,520 --> 00:36:14,319
Speaker 5: know the tech names that you're in or not high.

730
00:36:15,200 --> 00:36:17,719
Speaker 10: That sounds standing question. Well, earning season is over, so

731
00:36:17,840 --> 00:36:20,239
Speaker 10: I go on every earning season locked and loaded, and

732
00:36:21,000 --> 00:36:24,400
Speaker 10: I want to buy stocks on dips now because I

733
00:36:24,400 --> 00:36:27,280
Speaker 10: don't have really news to drive my stocks to mid April.

734
00:36:28,400 --> 00:36:31,080
Speaker 10: But I am buying stocks where analysts are upgrading and

735
00:36:31,160 --> 00:36:33,719
Speaker 10: raising their estimates, and if the ounces start to cut,

736
00:36:33,760 --> 00:36:35,520
Speaker 10: I'll get out of their way because I can't fight

737
00:36:35,560 --> 00:36:39,319
Speaker 10: with the ans community. But what happens after earning season. We

738
00:36:39,400 --> 00:36:43,280
Speaker 10: have a lot of mean reversion going on, and Citadella

739
00:36:43,440 --> 00:36:46,160
Speaker 10: is pretty good at their mean reversion trading. So my

740
00:36:46,320 --> 00:36:49,000
Speaker 10: view of the world is we have four months where

741
00:36:49,040 --> 00:36:51,520
Speaker 10: the markets are efficient when earnings are coming out. That's

742
00:36:51,560 --> 00:36:54,080
Speaker 10: earning season, and the other eight months we have mean reversion,

743
00:36:54,440 --> 00:36:56,360
Speaker 10: So I just want to sell in the strength and

744
00:36:56,360 --> 00:36:59,360
Speaker 10: buy in dips. I am bullish on energy going in

745
00:36:59,440 --> 00:37:02,680
Speaker 10: through some we should get a seasonal surge just from

746
00:37:03,120 --> 00:37:04,800
Speaker 10: the fact there's more people in North hemisphere in the

747
00:37:04,840 --> 00:37:07,919
Speaker 10: Southern hemisphere. But if there's any hint that Trump might

748
00:37:07,960 --> 00:37:11,720
Speaker 10: become president, probably will exit most of my energy stocks

749
00:37:11,760 --> 00:37:13,960
Speaker 10: by September because you know he'll drill, dro drill and

750
00:37:14,080 --> 00:37:14,960
Speaker 10: prices could fall.

751
00:37:15,520 --> 00:37:19,160
Speaker 2: Interesting, interesting, broad macro. Does it matter that much to

752
00:37:19,200 --> 00:37:21,040
Speaker 2: you who is in the White House? Just got about

753
00:37:21,040 --> 00:37:23,720
Speaker 2: thirty seconds left here. You mentioned energy specifically for Trump,

754
00:37:23,719 --> 00:37:25,399
Speaker 2: but more broadly it doesn't matter to.

755
00:37:25,360 --> 00:37:29,000
Speaker 10: You, no, because what makes America great is our states

756
00:37:29,040 --> 00:37:32,319
Speaker 10: compete with each other, period and as long as we

757
00:37:32,400 --> 00:37:34,480
Speaker 10: have the states trying to steal business from each other,

758
00:37:34,880 --> 00:37:37,360
Speaker 10: business will be good and America will prosper. And we

759
00:37:37,440 --> 00:37:39,320
Speaker 10: have so much better demographics as well.

760
00:37:39,640 --> 00:37:42,000
Speaker 2: All right, Really great to get some time with you, Louis.

761
00:37:42,040 --> 00:37:42,719
Speaker 3: Thank you so much.

762
00:37:42,800 --> 00:37:46,480
Speaker 2: Louis Navalier, who's chairman, founder in CIO of Navalier and Associates,

763
00:37:46,520 --> 00:37:50,040
Speaker 2: joining us from Florida on this Wednesday.

764
00:37:50,640 --> 00:37:55,279
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765
00:37:55,440 --> 00:37:58,640
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766
00:37:58,719 --> 00:38:02,120
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767
00:38:02,160 --> 00:38:05,480
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768
00:38:05,520 --> 00:38:08,400
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769
00:38:08,440 --> 00:38:11,360
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