WEBVTT - Roblox Shares Fall on Daily Active Users, Bookings Miss 

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<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news. You're listening to the

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<v Speaker 2>One of the big movers in the marketplace today is Roadblocks.

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<v Speaker 2>The game company stock is down eleven percent. It was

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<v Speaker 2>down more than twenty percent early in the trading day.

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<v Speaker 2>Bookings missed outlook a little bit softer than expected. Let's

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<v Speaker 2>get some details on now we can do that. The

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<v Speaker 2>man Deep singing, he's a senior technology channels for Bloomberg Intelligence.

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<v Speaker 2>Man Deep Talk, describe what Roadblocks does, and then what's

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<v Speaker 2>happening with the stock today.

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<v Speaker 3>I mean, this is a platform think fit as a

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<v Speaker 3>Bold garden where you can play any user generated game

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<v Speaker 3>as well as you know, the Triple A titles and

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<v Speaker 3>all sorts of game content hosted inside Roadblocks platform where

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<v Speaker 3>multiple users can play the game. And it's been quite popular,

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<v Speaker 3>you know, with that demographic, the nine to seventeen eighteen

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<v Speaker 3>year old.

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<v Speaker 4>It's a great way to entice somebody to do their homework.

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<v Speaker 4>It really is.

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<v Speaker 5>Yeah, the use cases beyond gaming.

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<v Speaker 4>You spent twenty minutes doing this, you know, after you

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<v Speaker 4>do your homework or whatever.

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<v Speaker 3>Yeah, and so I think again user growth of twenty

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<v Speaker 3>percent plus and anytime you see a company missing on

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<v Speaker 3>user growth, the reaction is pretty strong. Now, if you remember,

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<v Speaker 3>there was a report from Hindenberg talking about how the

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<v Speaker 3>user and engagement metrics are inflated, so pretty much the

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<v Speaker 3>company has been you know, doing the cleanup post that report,

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<v Speaker 3>even though they didn't really acknowledge, you know, there were

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<v Speaker 3>a large number of users.

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<v Speaker 4>Were they faking those numbers. They're just so difficult too.

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<v Speaker 3>With online platforms, is it's so hard to figure out exactly,

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<v Speaker 3>you know, what's bought activity and where are the user

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<v Speaker 3>metrics inflated or engagement And there's always scope to you know,

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<v Speaker 3>clean up and have real users being reflected on the platform.

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<v Speaker 3>In the case of roadblocks, brand safety is a big

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<v Speaker 3>aspect because you know, we were talking about kids using

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<v Speaker 3>the platform. So they've really, I think done a lot

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<v Speaker 3>since that short thesis from Hindenburg, and that's partly the

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<v Speaker 3>reason why they missed in terms of the user and

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<v Speaker 3>engagement metrics. But they called out Eastern Europe being weak

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<v Speaker 3>and Turkey being weak. To me, this is really the

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<v Speaker 3>quarter where the impact was the most obvious, and then

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<v Speaker 3>it will gradually get better because they've cleaned up.

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<v Speaker 2>So it seems like at least the partial vindication for

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<v Speaker 2>the Hindenburg research.

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<v Speaker 3>Well, I could make the case even for you know,

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<v Speaker 3>a platform like snap where you may have they have

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<v Speaker 3>shown hundred million daily active users every quarter. Now do

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<v Speaker 3>they really have one hundred million or is it more

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<v Speaker 3>ninety seven million because three million are just captured in

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<v Speaker 3>their metrics. So no one has a consistent approach to.

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<v Speaker 2>A third party like a Nielsen for TV ratings.

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<v Speaker 5>There's no third party to airfact, there is no third party.

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<v Speaker 5>It's the company that's giving you the metrics.

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<v Speaker 3>And I don't think there is like a consistent approach

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<v Speaker 3>that every company uses in terms of giving out their

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<v Speaker 3>daily active usercount.

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<v Speaker 4>Beyond the daily active users, what are the other important metrics.

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<v Speaker 5>That engagement also was like kind of a slight.

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<v Speaker 4>Message and radio it's time spent listening. Is that this

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<v Speaker 4>sort of the same thing.

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<v Speaker 3>Yeah, So again I look at you know, what they

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<v Speaker 3>are doing on the AI side. They are looking to

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<v Speaker 3>develop their own foundational model. So think of it as

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<v Speaker 3>you know what the LLLM companies are doing. It's a

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<v Speaker 3>walled garden where they will create all of tools to

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<v Speaker 3>enable more content. It's similar to YouTube in some sense.

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<v Speaker 3>YouTube has got a lot of video content, Roadblocks has

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<v Speaker 3>got a lot of gaming content and other things for

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<v Speaker 3>that demographic. So net I mean, this seems to be

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<v Speaker 3>justified reaction because they missed on their numbers, But has

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<v Speaker 3>a thesis really changed because they're losing share?

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<v Speaker 6>I don't think so real quick.

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<v Speaker 4>Have the safety concerns as a parent have they been

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<v Speaker 4>fully addressed?

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<v Speaker 3>That's what they're trying to address, and that's why you

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<v Speaker 3>know they missed on these metrics. So they're using a

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<v Speaker 3>combination of AI tools as well as just focusing more

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<v Speaker 3>on brand safety because they want to ramp up ADS.

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<v Speaker 5>And the way you ramp up ADS is you.

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<v Speaker 3>Want to make guarantee the advertisers that it's a safe

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<v Speaker 3>platform to advertise on.

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<v Speaker 6>Man Deep Seeing, thank you so much. We appreciate that.

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<v Speaker 6>Man Deep Seeing.

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<v Speaker 2>Senior technology channels for Bloomberg Intelligence. Join us here on

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<v Speaker 2>a bloomerg interactive broker studio.

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<v Speaker 1>You're listening to the Bloomberg Intelligence podcast. Catch us live

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<v Speaker 1>weekdays ten am Eastern on Apple coarcklay and Android Auto

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<v Speaker 1>with the Bloomberg Business app. Listen on demand wherever you

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<v Speaker 1>get your podcasts, or watch us live on YouTube.

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<v Speaker 2>Right next, guest, nice exposure to technology. And one of

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<v Speaker 2>my questions is is technology going to continue to lead

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<v Speaker 2>this market?

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<v Speaker 6>Hire have a little bit of a hiccup so far

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<v Speaker 6>in it.

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<v Speaker 4>Was the only sector to decline in the month of

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<v Speaker 4>January exactly, and it's.

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<v Speaker 6>Just kind of underperforming here.

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<v Speaker 2>So Nancy Tangler John's She's the CEO and CIO of

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<v Speaker 2>Laffer Tangler Investments based in Get this right now. She's

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<v Speaker 2>calling from Scottsdale, Arizona. One of my all time favorite.

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<v Speaker 4>Play there is snow, snow and ice on the.

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<v Speaker 6>Ground, snow as Royal Palms Hotel is my go to place.

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<v Speaker 2>They love me there lots of good stuff to do

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<v Speaker 2>out there, exactly. Nancy, thanks so much for joining us here.

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<v Speaker 2>Deep Seek was a story a couple of weeks ago.

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<v Speaker 2>We've now kind of forgotten about it, but I think

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<v Speaker 2>that costs a lot of tech investors to kind of

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<v Speaker 2>maybe rethink a little bit their AI trade. Here, how

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<v Speaker 2>did you kind of view that news and did it

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<v Speaker 2>kind of change in anyway your view of big tech.

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<v Speaker 7>Well, Paul and John, I'm dressed in sympathy for you

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<v Speaker 7>this morning in a down vest because it is actually cold.

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<v Speaker 6>Here to find cold, Nancy, Well, not really cold yet.

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<v Speaker 4>I was going to whip out my violins.

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<v Speaker 6>Plan well, listen.

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<v Speaker 7>I think there was a couple of things with the

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<v Speaker 7>Deep Seak announcement. Remember on the Friday before we had

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<v Speaker 7>Projects Stargate where the President had Larry Ellison, Sam Maltman,

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<v Speaker 7>and Masassan in the White House announcing a five hundred

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<v Speaker 7>billion dollar investment in AI and whether or not it's

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<v Speaker 7>going to be five billion dollars. We could talk about

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<v Speaker 7>that all for quite some time, but it generated enthusiasm.

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<v Speaker 7>And then the next Monday we had the story break

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<v Speaker 7>that Deep Seak had developed a more efficient AI model

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<v Speaker 7>for a five point six million I don't think that's correct,

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<v Speaker 7>and I think there was timing involved, And then we

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<v Speaker 7>had Ali Baba come out. What we know is that

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<v Speaker 7>the system is not as reliable, it's censored, it crashed.

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<v Speaker 7>And we also know that at Dagos, where this was

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<v Speaker 7>being talked about and for months before Deep Seek that

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<v Speaker 7>is that they allegedly have fifty thousand h one in

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<v Speaker 7>Vidio chips, which costs forty thousand dollars each. So I

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<v Speaker 7>think the whole thing is a bit suspect, but good

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<v Speaker 7>for the overall AI market because what we know from

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<v Speaker 7>Jevon's rule is that what you will see is the

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<v Speaker 7>cheaper technology gets, the more the usage and the use

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<v Speaker 7>case demand goes up. And we're seeing that across all

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<v Speaker 7>sectors in earnings reports for the last nine months and

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<v Speaker 7>also this most recent.

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<v Speaker 4>Quarter, Nancy, what do we learn from the earnings reports

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<v Speaker 4>so far? I mean they're kind of backward looking, I

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<v Speaker 4>guess more specifically the earnings calls that we've had.

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<v Speaker 7>Yeah, John, No, you're absolutely right. So it is backward

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<v Speaker 7>looking when you look at earnings beats. But what we

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<v Speaker 7>listen to is the guidance, and what we're hearing is

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<v Speaker 7>pretty optimistic. So if I'm going to look at my

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<v Speaker 7>notes just a little bit, because we cover a lot

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<v Speaker 7>of companies, but we're hearing things from companies as diverse

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<v Speaker 7>as next Era Energy, raytheon Xylum water treatment company, and

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<v Speaker 7>pro Logis, for example. So old economy companies that are

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<v Speaker 7>benefiting from the usage of AIRE in their well in

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<v Speaker 7>their businesses and then the margin improvement is showing up

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<v Speaker 7>in margins and we're getting guidance that's pretty optimistic. And

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<v Speaker 7>so you see that in the markets. What we also

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<v Speaker 7>see is volatility because we have Trump two point zero

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<v Speaker 7>and we know from Trump one point oh that volatility

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<v Speaker 7>will be with us. He's going to make bold statements,

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<v Speaker 7>some of which will come through, many of which won't,

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<v Speaker 7>but it'll rile the markets, and it'll rile the algos

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<v Speaker 7>and the short term traders. As an investor, it's great

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<v Speaker 7>news for me because we're Volatility is the friend of

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<v Speaker 7>the long term investor.

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<v Speaker 6>Names.

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<v Speaker 2>I'm looking at your twelve Best Ideas portfolio, very very

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<v Speaker 2>heavily weighted with the big tech names everybody knows Spotify, Amazon, Broadcom,

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<v Speaker 2>Microsoft and the like. Talk to us about your thesis

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<v Speaker 2>there behind that portfolio.

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<v Speaker 7>Yeah, So we run a growth strategy pall, and then

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<v Speaker 7>we also run a dividend growth strategy, which is more

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<v Speaker 7>value and we always pull from there our twelve best

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<v Speaker 7>ideas because there was a study done decades ago that

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<v Speaker 7>said optimal diversification is twelve names, and we have found

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<v Speaker 7>that to be true over the years. That portfolio has

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<v Speaker 7>done better than everything else. So we look for the

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<v Speaker 7>companies that are generating earning's growth at a reasonable not

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<v Speaker 7>a cheap, but a reasonable valuation. In determining that, we

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<v Speaker 7>look at relative price to sales ratio, So what am

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<v Speaker 7>I paying for a future unit of sales and then

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<v Speaker 7>the price earnings to growth ratio, And these are the

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<v Speaker 7>names that we have confidence in.

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<v Speaker 6>In fact, it has shown up in the performance.

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<v Speaker 7>So I think it's also got a heavy exposure to

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<v Speaker 7>consumer discretionary, modest exposure to industrials via Uber, and then

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<v Speaker 7>some one healthcare name, and I think one financial Goldman Sachs.

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<v Speaker 4>I learned from Paul this morning that there's high dispersion

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<v Speaker 4>in the market. I want to answer for a detailed

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<v Speaker 4>explanation of that. But does are we all writing the

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<v Speaker 4>same our investors all writing the same wave.

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<v Speaker 7>Well to some extent, you know, and that's driven by

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<v Speaker 7>the ETFs. John, So you know, when you see a

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<v Speaker 7>big sell off in a stock like Apple, a lot

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<v Speaker 7>of times that's because retail investors or financial advisors are

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<v Speaker 7>exiting ETFs, many of which own Apple, So you have

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<v Speaker 7>to keep that in mind. But what we're looking at

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<v Speaker 7>is an analogy to the nineteen nineties, and I think

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<v Speaker 7>we're in the early years of this anal Internet as

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<v Speaker 7>a technology was super cool, but we were measuring eyeballs.

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<v Speaker 7>I wasn't but analysts for eyeballs on a website. This

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<v Speaker 7>technology is much more robust. And you've heard John Chambers,

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<v Speaker 7>who was the CEO of the poster child of overvalued

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<v Speaker 7>stocks in the nineties, say that generative AI and AI

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<v Speaker 7>computing is more powerful than cloud computing and the Internet combined.

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<v Speaker 7>So in some periods of time it makes sense to

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<v Speaker 7>be part of the consensus as long as you're not

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<v Speaker 7>buying companies with multiples of one hundred times peak earnings,

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<v Speaker 7>which is what people were paying for Cisco in the day.

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<v Speaker 7>And the buyers of the infrastructure are the hyperscalers who

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<v Speaker 7>have robust balance sheets.

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<v Speaker 6>Many of them were.

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<v Speaker 7>Spending fifty sixty seventy five billion dollars this year in capex,

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<v Speaker 7>but they're still generating fifty sixty seventy five billion dollars

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<v Speaker 7>in pre cash flow, so these are really sustainable, strong company.

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<v Speaker 6>Nancy, thank you so much for joining us. Really appreciate it.

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<v Speaker 2>Nancy Tangler's CEO and chief investment office Laffer Tangler Investments,

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<v Speaker 2>and oh, by the way, forecast at high for Scotts Sale,

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<v Speaker 2>Arizona today seventy eight degrees.

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<v Speaker 6>So there you go.

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<v Speaker 4>That's tough.

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<v Speaker 6>Is they have a nice golf tournament there.

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<v Speaker 2>The PGA is there in Scotts Sale this week in

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<v Speaker 2>Phoenix area, so they're gonna have been good weather.

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<v Speaker 1>You're listening to the Bloomberg Intelligence Podcast. Catch us live

0:12:20.240 --> 0:12:23.640
<v Speaker 1>weekdays at ten am Eastern on Applecarplay and Android Auto

0:12:23.760 --> 0:12:26.800
<v Speaker 1>with the Bloomberg Business App. Listen on demand wherever you

0:12:26.840 --> 0:12:29.840
<v Speaker 1>get your podcasts, or watch us live on YouTube.

0:12:30.440 --> 0:12:32.120
<v Speaker 2>All right, let's talk to these markets here. Let's talk

0:12:32.160 --> 0:12:34.840
<v Speaker 2>tech technology in these markets. This technology is still a

0:12:35.000 --> 0:12:38.319
<v Speaker 2>leader for these equity markets as it has been forever.

0:12:38.440 --> 0:12:41.040
<v Speaker 6>Shana Cisel joint says. She's the president and CEO.

0:12:40.880 --> 0:12:45.320
<v Speaker 2>Of Bondrin Capital Management, joining us here. Shana, you know,

0:12:45.360 --> 0:12:47.400
<v Speaker 2>a couple of weeks ago, it seems like a lifetime ago.

0:12:47.480 --> 0:12:51.240
<v Speaker 2>There's this thing we all learned about deep seek, and

0:12:51.320 --> 0:12:53.840
<v Speaker 2>I know you guys spend a lot of time thinking

0:12:53.840 --> 0:12:57.560
<v Speaker 2>about investing in technology broadly defined. How did you guys

0:12:58.200 --> 0:13:00.960
<v Speaker 2>think about this deep seek and what may mean for

0:13:01.160 --> 0:13:02.480
<v Speaker 2>technology investing?

0:13:03.760 --> 0:13:07.480
<v Speaker 8>So my general rule of thumb with any kind of

0:13:07.520 --> 0:13:12.960
<v Speaker 8>news is if it makes me have a very visceral

0:13:13.040 --> 0:13:17.720
<v Speaker 8>response that I should step back and read, and so

0:13:17.840 --> 0:13:20.360
<v Speaker 8>that was my initial response. The market, however, does not

0:13:20.600 --> 0:13:26.160
<v Speaker 8>have the focus and the ability to necessarily do that,

0:13:26.320 --> 0:13:30.240
<v Speaker 8>so it freaks out. As I learned more, I became

0:13:30.480 --> 0:13:33.679
<v Speaker 8>less concerned about the deep seek threat and what that

0:13:33.760 --> 0:13:37.360
<v Speaker 8>means for China as a competitor in the AI space.

0:13:38.200 --> 0:13:40.080
<v Speaker 8>There's a number of things that stood out to me

0:13:40.559 --> 0:13:44.200
<v Speaker 8>that made me think, like, Okay, this is no different

0:13:44.280 --> 0:13:48.040
<v Speaker 8>than any time a Chinese company knocks off a American

0:13:48.600 --> 0:13:53.040
<v Speaker 8>shoe brand or anything else. It's very similar, But there's

0:13:53.160 --> 0:13:55.400
<v Speaker 8>more of a concern here. If we thought TikTok was

0:13:55.440 --> 0:13:58.680
<v Speaker 8>a concern from national security perspective, this is an even

0:13:58.720 --> 0:14:02.199
<v Speaker 8>greater concern with its connection to the CCP through their app.

0:14:02.679 --> 0:14:06.679
<v Speaker 8>So while there's definitely some interesting aspects of the open

0:14:06.720 --> 0:14:10.079
<v Speaker 8>source code that can be used by Amazon or anybody

0:14:10.840 --> 0:14:15.640
<v Speaker 8>to leverage the actual app itself and the things that

0:14:15.920 --> 0:14:18.480
<v Speaker 8>related to that, I'm less concerned about in terms of

0:14:18.520 --> 0:14:21.120
<v Speaker 8>what it means for the US companies in the tech space.

0:14:22.280 --> 0:14:24.440
<v Speaker 5>This shouldn't be a surprise. It was always the.

0:14:24.440 --> 0:14:28.760
<v Speaker 8>Greatest risk to technology companies in the US was having

0:14:28.800 --> 0:14:32.600
<v Speaker 8>somebody disrupt the market. But I think it's a bit

0:14:32.640 --> 0:14:36.520
<v Speaker 8>overblown and quite frankly, I think we've been complaining about

0:14:36.600 --> 0:14:41.520
<v Speaker 8>valuations forever and this solved our problem pretty quickly.

0:14:41.880 --> 0:14:44.520
<v Speaker 4>All right, let's move to treasury yields. I heard the

0:14:44.920 --> 0:14:48.720
<v Speaker 4>new treasure secretary say yesterday that he's kind of focused

0:14:48.720 --> 0:14:52.720
<v Speaker 4>on the tenure and bringing that down. Now, I'm kind

0:14:52.760 --> 0:14:54.520
<v Speaker 4>of a student of history, and I have to go

0:14:54.600 --> 0:14:58.200
<v Speaker 4>back to the early sixties and beyond right up to

0:14:58.240 --> 0:15:03.120
<v Speaker 4>present day. The ten here seems to follow economic activity.

0:15:03.400 --> 0:15:05.240
<v Speaker 4>And if you want to bring the ten year lower,

0:15:05.320 --> 0:15:09.560
<v Speaker 4>a sure way to do it is to lessen economic growth.

0:15:10.640 --> 0:15:12.080
<v Speaker 4>I'm sure it doesn't want to do that.

0:15:13.200 --> 0:15:16.400
<v Speaker 8>Yeah, that's the conundrum here, right, You want to bring

0:15:16.520 --> 0:15:19.360
<v Speaker 8>rates down, but you know, at the end of the day,

0:15:19.720 --> 0:15:23.000
<v Speaker 8>there is correlation there between the strength of the economy

0:15:23.040 --> 0:15:25.160
<v Speaker 8>and the interst rate environment and the yield curve and

0:15:25.160 --> 0:15:28.000
<v Speaker 8>how the yeld curve behaves. You know, the FED doesn't

0:15:28.040 --> 0:15:31.760
<v Speaker 8>have the power things it has to control that. I mean,

0:15:31.800 --> 0:15:35.560
<v Speaker 8>we've seen that in recent months with the FED cutting

0:15:35.720 --> 0:15:41.280
<v Speaker 8>and yet the yield curve not behaving like rates have

0:15:41.320 --> 0:15:44.360
<v Speaker 8>been cut. In fact, it's to be expected, right, because

0:15:44.760 --> 0:15:46.720
<v Speaker 8>you want to get out of an inverted yield curve,

0:15:46.720 --> 0:15:49.640
<v Speaker 8>which requires the longer end to go up even in

0:15:49.680 --> 0:15:53.240
<v Speaker 8>a cutting cycle. But I think that the problem here

0:15:53.280 --> 0:15:56.760
<v Speaker 8>and what they're trying to kind of fix, is related

0:15:56.800 --> 0:16:00.560
<v Speaker 8>to mortgage rates in the housing market, and I don't

0:16:00.600 --> 0:16:04.080
<v Speaker 8>know that there's an easy fix to that. But I

0:16:04.120 --> 0:16:06.800
<v Speaker 8>am concerned that there's this belief that if they just

0:16:06.840 --> 0:16:09.680
<v Speaker 8>cut rates enough, they can fix this problem, because I

0:16:09.680 --> 0:16:14.120
<v Speaker 8>think it's not that black and white, and there's a

0:16:14.320 --> 0:16:18.200
<v Speaker 8>high probability of a potential mistake being made if they

0:16:18.240 --> 0:16:21.440
<v Speaker 8>go in with policy decisions thinking that it is that easy.

0:16:22.160 --> 0:16:22.320
<v Speaker 7>Chan.

0:16:22.400 --> 0:16:25.600
<v Speaker 2>I know you work with your clients talking about alternative investments. Here,

0:16:26.480 --> 0:16:29.480
<v Speaker 2>where do you see the greatest opportunity in alternatives here?

0:16:29.560 --> 0:16:32.480
<v Speaker 2>Private equity, private credit, hedge funds.

0:16:33.320 --> 0:16:34.880
<v Speaker 6>Where are you spending most of your time these days?

0:16:35.520 --> 0:16:39.720
<v Speaker 8>So more hedge fund like strategies, private equity, private credit

0:16:39.760 --> 0:16:42.200
<v Speaker 8>are kind of sensitive to the interest rate environment and

0:16:42.280 --> 0:16:47.040
<v Speaker 8>also sensitive to public market betas in the hedge fund world,

0:16:47.200 --> 0:16:50.880
<v Speaker 8>especially if you believe that there's going to be increased volatility.

0:16:51.120 --> 0:16:55.440
<v Speaker 8>Hedge funds and hedge fund like strategies are great diversifiers. So,

0:16:55.520 --> 0:17:00.680
<v Speaker 8>for example, last week, there's a ETF PTL, the ADF

0:17:01.240 --> 0:17:05.480
<v Speaker 8>us Anti Beta fund long low beta short high beta

0:17:05.560 --> 0:17:09.879
<v Speaker 8>that that product did remarkably well when we had the

0:17:09.920 --> 0:17:14.720
<v Speaker 8>big deep seek threat threat sell off, And that's exactly

0:17:14.760 --> 0:17:17.840
<v Speaker 8>what you want and those types of products, and that's

0:17:17.880 --> 0:17:21.439
<v Speaker 8>what hedge fund like strategies can do is provide you

0:17:21.560 --> 0:17:26.959
<v Speaker 8>that downside protection when the market is under significant stress.

0:17:27.000 --> 0:17:30.200
<v Speaker 8>Managed futures is another example, like a CTA et F.

0:17:31.040 --> 0:17:33.000
<v Speaker 8>And then when you move into the hedge fund space

0:17:33.040 --> 0:17:37.280
<v Speaker 8>where they can use leverage more as a tool, you

0:17:37.320 --> 0:17:40.200
<v Speaker 8>can get even greater benefit as a diversifier and as

0:17:40.200 --> 0:17:43.400
<v Speaker 8>a downside protector. But it's not sexy and people get

0:17:43.880 --> 0:17:46.919
<v Speaker 8>forget that, like these aren't meant to outperform the market.

0:17:46.960 --> 0:17:49.200
<v Speaker 8>There they serve a purpose in your portfolio.

0:17:49.680 --> 0:17:51.320
<v Speaker 5>I like to think of it as.

0:17:51.400 --> 0:17:54.080
<v Speaker 8>Like home insurance, like you hope you never have to

0:17:54.160 --> 0:17:56.520
<v Speaker 8>use it, but it's you would never not have it

0:17:57.359 --> 0:18:00.800
<v Speaker 8>because you need to be able to manage the risk.

0:18:00.880 --> 0:18:03.320
<v Speaker 8>And that's exactly how I see those types of strategies.

0:18:03.760 --> 0:18:06.000
<v Speaker 8>This year, I think is the year where these types

0:18:06.040 --> 0:18:10.480
<v Speaker 8>of strategies are really going to show their worth because

0:18:10.480 --> 0:18:12.040
<v Speaker 8>I think the markets are going to be quite polatile.

0:18:12.760 --> 0:18:14.959
<v Speaker 2>Shana, thank you so much for joining us. Always appreciate

0:18:15.000 --> 0:18:17.440
<v Speaker 2>getting a few minutes of your time. Shana Sissel, president

0:18:17.480 --> 0:18:21.320
<v Speaker 2>and CEO of a Bondrion Capital Management, joining us, you're

0:18:21.320 --> 0:18:22.440
<v Speaker 2>talking about the broader market.

0:18:22.880 --> 0:18:27.600
<v Speaker 1>This is the Bloomberg Intelligence Podcast, available on Apple, Spotify,

0:18:27.800 --> 0:18:31.720
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0:18:31.960 --> 0:18:35.240
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0:18:35.320 --> 0:18:39.199
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0:18:39.240 --> 0:18:42.520
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