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TCW is a leading global asset management firm with over 50 years of investment experience and a broad range of products across fixed income, equities, emerging markets, and alternative investments. In each episode of TCW Investment Perspectives, professionals from the firm share their insights on global trends and events impacting markets and the investment landscape.
Welcome to the TCW Investment Perspectives Podcast.
I'm your host, Anisha Goodly, Managing Director and Co-Head
of the Fixed Income Portfolio Specialist Team at TCW.
Emerging markets have delivered strong returns over the past
year, supported in part by the rapid rise of artificial
intelligence and its impact on global growth and investment.
But while much of the AI narrative has been focused on
the large US hyperscalers, a significant portion of the
value chain is increasingly rooted in emerging markets.
So the question is: is AI simply driving near-term performance, or is
it reshaping the long-term opportunity set across emerging markets?
Joining me today is Hiren Dasani, Chief Investment Officer
for Emerging Markets at White Oak, and Portfolio Manager
for the TCW White Oak Emerging Markets Equity Fund.
Hiren, welcome to the podcast, and thanks so much for joining today.
Hiren Dasani: Thank you, Anisha.
Good morning, everyone.
Hiren, to kick off, can you just lay out what
the AI landscape looks like in emerging markets?
Yeah, so I think before we go specific into the AI,
maybe it would be interesting to understand what
the broader emerging markets composition today is.
And that would help you to understand why EM
is benefiting a lot from the AI capex theme.
So today, if you see the top three countries by the weight in the
benchmark, Taiwan is the largest weight at about 25-26% of the benchmark.
Korea is the second largest at about 23% of the benchmark,
followed by China at about 20% of the benchmark.
This is what I'm calling about the MSCI EM benchmark weights.
And from a sector perspective, if S&P 500 has about 38-39% weight in
the information technology as a sector, emerging market index has
almost about 43-44% weight in information technology as a sector.
So, yes, both S&P and EM are heavily dominated by IT today.
And Taiwan and Korea, which are the flag bearers of this AI
theme, are the now top to largest weight in the emerging market.
So that should give you some perspective on what the AI opportunity is.
And as we go along, we can talk more about that in the detail.
When you look at AI from an emerging markets perspective, how different
does the story look versus what we're hearing in developed markets?
Yeah, so I think it will be surprising to know, or many
of the listeners that emerging markets is much more
about what we call picks and shovels trade for the AI.
So whether it is Korea or Taiwan, the two large emerging markets, they are
at the forefront of the value chain of the AI infrastructure build out.
So take any subcomponent of the data center or the server, whether it is memory,
or whether it is semiconductor foundries, whether it is cooling systems, whether
it is PCBs, I mean, you name, name the component, and it's
almost entirely, almost entirely made in Taiwan or Korea.
And not surprisingly, these two countries are the best performing
emerging markets and probably the best performing markets in
the world, year to date and over the last 12 to 18 months.
Now, obviously, end markets are still
largely driven by the US hyperscaler capex.
But the demand of the hyperscaler capex is translating into very strong
revenue growth for the companies in the emerging markets, especially in
Korea and Taiwan, who are kind of fulfilling the entire AI supply chain.
So the Pix and Shovels trade have been very successful so far in this AI boom.
And so do you feel like it's fairly concentrated within those two countries?
Or is it more broad based?
Are you seeing any emerging signs in other countries?
So obviously, you know, beyond these two countries,
China also has a very large value chain.
On some of the sub components of the AI, whether it is optical
components, whether it is robotics related components, actuators,
and many other sub components, which go into the robotics.
So whether it is Tesla's humanoid robots, whether it is any other
kind of robotic system, which is propagated by Nvidia, again,
China is playing an important role in that robotic system.
If you go beyond the Taiwan and Korea, the China AI
trade is also about the local large language models.
I'm sure people are familiar with DeepSeq and how cheap it is compared to some
of the, you know, Western large language models like Enthropic or OpenAI.
And China has demonstrated that they can develop their own LLMs.
Alibaba is now developing their own chip as well, which
can eventually compete with the Nvidia chips if, let's
say, China is not able to get the advanced AI chips.
So, yes, I mean, beyond Taiwan and Korea, China
is at the forefront of the AI trade as well.
If you move beyond these three large markets, then the other way
to think about the indirect benefits of AI is on the commodities.
And here is where a lot of Latin American markets like Brazil,
Peru, Chile, which have large, let's say, copper mining
businesses are benefiting from the AI-related demand.
And eventually, the commodity demand is also
being driven by the AI data center CapEx.
In markets like India, we are seeing quite a few small and mid-cap companies
which are supplying to, let's say, GE Vernova, Siemens, Mitsubishi,
some of these global power equipment-related businesses.
And as these companies are supplying the transformers
and other electricity-related equipment, the value
chain is benefiting from the low-cost markets.
The low-cost manufacturing countries like India as well.
How about the bottlenecks?
Are you seeing any sort of specific bottlenecks in AI
that could impact the outlook for the next few years?
So the biggest bottleneck today most of the countries are facing
is about the electricity and the energy availability, right?
And in many of the emerging markets, the
energy infrastructure is still developing.
The electricity consumption is growing anyway without the AI at a healthy pace.
But if you put up quite a few data centers, then obviously the
incremental requirement for the electricity goes up accordingly.
We are seeing massive capex in the renewable
energy space in countries like China and India.
And over time, these countries will have cheaper way of developing
the data centers because the land cost and the construction cost
is much lower compared to, let's say, what you see in the US.
The other day I was meeting one data center company in
India and they were telling me that if you'll put up a data
center in India, the per megawatt cost is about $6 million.
Whether the same cost in a country like US will be
somewhere in the range of $12 million per megawatt.
And this is excluding the compute cost.
This is just about the bare shell data center.
So if you believe that there could be a scenario where the low cost energy and
the low cost manufacturing, the low cost data centers of emerging markets can be
used for the huge inferencing requirements of the Western economies, then there
is going to be a significant boom in the energy infrastructure as
well as in the data center CAPEX in countries like India as well.
And how dependent do you feel the AI companies
in emerging markets are on US companies?
Or how distinct are they?
So when you think about just that correlation or that portfolio construction?
So obviously in the near term, everything is hugely correlated.
Because today, if you are talking to a TSMC or a Samsung or a Hynix, the three
kind of torchbearers of the AI trade in the EM, or even some of the other
companies which are benefiting from the AI CAPEX, today, most
of their demand is coming from the US hyperscaler CAPEX.
And so if there is a view that the hyperscaler CAPEX slows down, because let's
say more questions about the return on investment of some of these hyperscalers,
then it does impact demand outlook for the EM semiconductor value chain as well.
And in the near term, they will also see some drawdown.
But in the more medium term, what is more important to see is
that these companies are, you know, still attractively valued.
Many of the picks and shovels companies we like to call them are
still reasonably valued in terms of their earnings multiples,
they are generating significant cash flows, they are
not putting up humongous CAPEX as the hyperscalers are.
So obviously, their balance sheets are very healthy.
And today they are benefiting only from the US data center demand.
But if you believe that this AI CAPEX is going to last, it's a multi-year
theme, and it will eventually percolate to the other markets as well,
then the requirement for the semiconductor value
chain is likely to continue for a long time.
Thanks, Ren.
And when you take all this back to your investment process
at White Oak, how are you underwriting this theme?
What are you looking for in companies?
So obviously, at White Oak, when we are managing the portfolios, we are not
looking to create our portfolios, which can be driven only by one theme.
We are very conscious that we want to be a balanced portfolio, which
should ideally generate outperformance on either of these outcomes,
whether the AI trade works well or AI trade does not work well.
So the way we try to construct our portfolio is that we
try to remain very neutral on a particular theme, we
don't try to take too much outsized country bets.
Our country overweights and underweights are generally
within a couple of percentages of the benchmark.
Our sector underweights and overweights are also
within a couple of percentages of the benchmark.
So yes, we are aware of the theme, but we are
also aware that the themes can change on a dime.
And we don't want our alpha outcomes to be driven entirely by one theme,
because that would not be then the balanced portfolio construction.
So yes, we are obviously benefiting from some of this AI related capex, but
we are also looking for opportunities outside of this AI theme, in the more
structural growth areas of emerging markets like consumer financial
services, healthcare and other areas where the penetration
levels are quite low in many of the emerging markets.
So we talked a lot about some of the mega
cap companies like TSMC, Samsung and Hynix.
Everybody knows about them as the flag bearers
of the AI trade in the emerging market.
But emerging market is not only about some of this mega cap names.
And at White Oak, we do find a lot of opportunities in the mid and small cap
names, which are outside of this kind of, you know, big headline mega cap names.
And why do we think mid and small cap are providing us more opportunities?
Because they are less efficient segments of the market.
And in general, we believe emerging markets are
less efficient compared to the developed markets.
And there is a case of active management in the emerging market.
But even within the EM, if you go down the market cap
curve, the level of market inefficiency increases.
And if you have a right kind of team, then you can
really generate a lot of alpha in the mid and small cap.
At White Oak, we have a team of more than 40 investment professionals
who are sector knowledge experts in this respective emerging markets.
And our investment process allows us to leverage this team.
So overall, EM benchmark has, let's say, close to 1400 companies,
but go down to about $500 million as a market cap cutoff.
Then you have more than 5000 companies in the emerging market.
And because we have a large investment team, because we have a process which is
collaborative between the portfolio manager and the analyst, it allows us to
cover more number of names, it allows us to
own more number of names in the portfolio.
And over time, we have realized that on a per unit of capital, which you
deploy in this mid and small cap, you can generate significantly higher alpha.
Haran, I want to pick up on what you mentioned earlier about
not necessarily concentrating portfolios in individual themes.
When you look at the overall emerging market equity
landscape, where else are you seeing opportunities?
It's a very broad kind of, you know, set
of opportunities that we are evaluating.
I'll give you a few examples.
For example, consumer, it's a structural opportunity in the emerging
markets, because in many countries, the penetration levels are quite low.
Just take cars as an example, right?
In US, you will have about 800 cars per thousand people.
In China, that number is somewhere in the range of 70 or 80.
And in India, that number is probably in the high single digit levels.
So you are seeing a significantly low penetration of cars as a category.
And that gives you a structural growth opportunity for electric
vehicles, as well as the overall kind of auto industry.
Another example I'll give you is about healthcare.
If you look at the healthcare ecosystem, whether it is hospitals, whether
it is diagnostics, whether it is low cost manufacturing of the drugs, we
are seeing significant opportunities across multiple emerging markets.
In general, we are finding more opportunities in the hospitals value chain.
We are also finding some very interesting opportunities in the
contract research and the manufacturing space in the healthcare.
So whether it is Chinese companies or whether it is Indian companies,
they are leveraging the low cost research talent availability
and they are also leveraging the low cost manufacturing ability.
You might be interested to know that almost 40% of the generic drugs which
are sold in the US in terms of volumes are produced in a country like India.
So India and China are kind of at the forefront of this healthcare,
especially on the biologics and the biosimilar opportunity.
So whether it is GLP drugs, again, the manufacturing value chain of
the GLP drugs is moving towards the emerging markets because that's
where the base chemicals and the APIs are made in a low cost manner.
So healthcare, consumer, those are some of the areas
where quite a few interesting businesses out there.
Financial services is another one.
In most of the emerging markets, you will see that the penetration of
financial services, whether it is loan to GDP ratio, whether it is mutual
fund penetration, whether it is brokerages, again, they are at maybe
20-30 years behind where the developed markets are like US, right?
So in US, the household allocation to equities as an asset class is much higher.
But in emerging markets, we see that it's a
trend which is still at the early stages.
So China, Korea, India, all these countries, we are seeing
the local retail individuals and local households kind
of putting more money in the local equity markets.
So that's the other theme which we are quite excited about.
Karen, thanks again for joining us.
AI is clearly becoming an increasingly important force across
emerging markets, and we appreciate you walking through
that sector, but also more broadly, the opportunity set.
And thanks to everyone here for listening
to the TCW Investment Perspectives podcast.
Be sure to subscribe for more insights on the forces shaping global markets.
Until next time, I'm Anisha Goodly.
Thank you for joining us today on TCW Investment Insights.
For more insights from TCW, please visit tcw.com slash insights.
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