November 26, 2025 • 14 mins
Do fundamentals or narratives drive market valuations? That is the question so many are wrestling with in today’s 24/7 algo-based platforms and AI-driven mediascape.
Ben Hunt is founder of Perscient, a firm that studies how narratives and stories shape markets, investing, and social behavior through the lens of information theory, game theory, and unstructured data analysis. His work analyzes the language, story arcs, and viral spread of explanations in media
Each week, “At the Money” discusses an important topic in money management. From portfolio construction to taxes and cutting down on fees, join Barry Ritholtz to learn the best ways to put your money to work.
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Episode Transcript
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Speaker 1 (00:09):
Investors have long been taught that fundamentals drive stock prices,
revenue growth, profits. As Benjamin Graham taught us, in the
short run, the market is a voting machine. But in
the long run it's a weighing machine. But what if
it isn't? What if narratives are driving market valuations. I'm
(00:32):
Barry Riddolets and on today's edition of At the Money,
we're going to discuss how to identify when market narratives
overtake fundamentals. To help us unpack all of this and
what it means for your portfolio, let's bring in Ben
Hunt of Percion. Ben's firm studies narratives and the stories
(00:53):
that shape markets, investing, and social behavior through the lens
of information theory. So Ben, let's start with a definition.
How do you define a narrative in the context of
markets and investing.
Speaker 2 (01:08):
It's a simple definition. A narrative is an answer to
the question why why did the market go up today?
Why should you buy the stock? Why should you sell
this stock? Why should you vote for this person? Any
answer to the question why is a narrative? Well?
Speaker 1 (01:28):
Sad you distinguish between something like data, which I arguably
comes with a storyline attached to it, and just a
straight up Hey, bitcoin is millennium or digital goals? Like,
how do you define the difference between this? I guess
this stock is cheap with a pe of nine? Is
(01:49):
a narrative?
Speaker 2 (01:50):
Yeah, well why is? Why is a pe of nine cheap? Right?
Or why is a pe of three cheap or fifteen cheap?
These are all stories. Any any valuation, any multiple, any
meaning that you attached to numbers, it's a story. It's
a It's an answer to the question why why do
(02:12):
I call it cheap? Why do I think you should
buy it? Why is this interesting? Those are all why
questions and the answer Those are all narratives.
Speaker 1 (02:22):
So how do you identify any particular narrative that may
be driving a particular stock or asset class or the
overall market? What what tools do you use to help
discern that?
Speaker 2 (02:38):
Well, let me start by saying what I don't care about.
So what I don't care about is truth or accuracy.
I mean, it sounds crazy, but.
Speaker 1 (02:47):
Not at all because you're trying to figure out what
the crowd believes, whether it's true or not. Well, if
it affects their behavior, it matters.
Speaker 2 (02:55):
It matters. Right, So I've I've given up on trying
to figure out what reality is. What I'm trying to
figure out is how is reality being presented? How is
it being presented to us? So what I'm looking for
are elements of presentation. I'm looking for word choice. I'm
(03:16):
looking for how loud is it being presented to you,
how frequently it's being presented to you. But most of all, Barry,
I'm looking for a concept that you talk about in
network math, and it's called density, And I'm looking for
how the language is connected to other words. In fact,
(03:37):
those are the measurements you use in network math. Those
are where they we talk about betweenness, we talk about
connectedness and centrality. Those are the measurements. Because I'm looking
at the presentation, not at the reality.
Speaker 1 (03:53):
So how do you measure density? You hinted at some
of it, how loud it is, how repetitive it is.
How do you tell when a specific narrative is beginning
to exert influence over prices?
Speaker 2 (04:08):
Yeah? So, Bob Sheller wrote a pretty good book a
couple of years back called Narrative Economics, And the takeaway
from that book is that you should think about and
understand narratives in exactly the same way you think about
and you understand disease. I mean, you use the same measurements.
(04:32):
You remember when we were talking about COVID, it was
are not right? How fast does it spread? How quickly
does it spread? What is the medium in which it
can spread most easily? It's exactly the same thing here, bear,
It's exactly the same thing. We're really using exactly the
same math as you would use to try to understand
(04:54):
epidemiology and the spread of a virus. So what we're
looking at, though, instead of the atmosphere or waste water,
we're looking at the words. We're looking at all the
words that are out there in terms of text, of
what's being written, what's being said. This is all unstructured data,
(05:18):
and we're looking for the presence of certain ideas, clusters
of words that spread through that medium of media in
exactly the same way that a virus spreads through the
air or through the water. If you're a financial advisor
or you're a market person of any sort and somebody
(05:38):
comes up to say, yeah, why the why the market
go up today? And you could say, well, there are
a hundred different reasons, but basically it was just variants.
You know, it's just it's just it's just random. It's
just a random walk. But it went up today. So
someone will look like people hate that answer because it's
(05:59):
a crappy story. It's just it's a it's just true.
Speaker 1 (06:02):
But it's not competitive exactly.
Speaker 2 (06:04):
It's not truthy, right, it doesn't it doesn't connect with you.
I said, well, that's disappointing. I want a story. So
the stories that are basically there to fill the time. Uh,
and these are these are typically examples where I call
(06:25):
them descriptive narratives. They're they're answering the question why, but
they're describing why something happened.
Speaker 1 (06:35):
Always after the fact, never in advance.
Speaker 2 (06:37):
Always after the fact. That's exactly right, Barry. So what
you'll find is that I don't know, it's earning season,
and who comes out first with earnings financials, right, and so, uh,
you know City and Goldman, Sacks, whoever. They'll report some
good earnings, the stocks will go up, and afterwards, Kramer
(06:59):
and everyone else, it's got to tell you why. And
they'll say, oh, I'm bullish on financials, and they'll give
you a reason. And that the half life for that
sort of narrative. It's a week or two. I mean,
it's it. And what you want to do with that, honestly, Barry,
(07:19):
is you want to fade it. You want to look
for that to appear in your Bloomberg email in the
morning saying, oh, market experts bullish on financials because blah
blah blah. And when that drum beating gets pretty loud
when it's appearing in your morning email, I want to
(07:40):
fade it. You don't want to press it. You want
to fade it because this is just the ordinary business
of Wall Street. You've got to have an answer to why.
It's almost usually just variants or some combination of idiosyncratic stuff,
but you've got to come up with some blanket why.
And if that gets a lot of play, I want
to go the other way. Now there's a there's another
(08:02):
type of narrative though, where I want to press it.
And so that's what we call prescriptive narratives. It's not saying, oh,
the Fed is dubvish. It's saying, you know, Mohammad l
Arion will come out or I don't know, Trump will
come out and say the Fed should be dubvish. You
(08:26):
see the difference. It's not it's not describing what's already happened.
It's trying to lay the framework for what should happen.
Speaker 1 (08:36):
So so let's delve into that. What sort of tools
are you using to identify these narratives, be they descriptive
or or prescriptive. How how much lead time do you
get to analyze you know, this giant corpus of noise
and commentary and data that is produced every single day.
Speaker 2 (09:00):
Well, this is what good traders, honestly and and investors
have always done. They've they've they've always made these sort
of assessments of the news and the stories that are happening.
So this what we're trying to do is we're trying
to externalize what good traders and i'll call it short
(09:22):
term investors have always done. They've always internalized this. So
anybody can do this. You start looking for the words
that are trying to prescribe versus describe. That'll you you
can you can pick this up in whatever you do.
What we're able to do though today is because there's
(09:44):
now big data, as because there's big compute, is we
can read everything. Humans we're all limited in what we
can read, what we can pay attention to. In our
little corner of the world. What's possible today is to
read everything into animal lies exactly, this sort of word choice.
Speaker 1 (10:04):
So what sort of output do you get from your
big compute that's scraping everything, Yeah, sifting through all the language, like,
does it identify specific words? Does it identify themes? I'm
assuming artificial intelligence and big data analytics is a key
part of this. What does the output look like to you?
Speaker 2 (10:27):
Well, let me start with where it starts, because it's
not that the output comes from what you put into
it and what you want to put into it, and
this has to be human generated. Are well, what are
the ideas? What are the narratives that I care about?
Here's why that's important, Barry, because let's say you're a
(10:47):
value investor. You've got a vision, you know, you've got
a view on a stock, and like all value investors,
you think the market has not recognized the story about
this stuff that I think is really important. So what
you're looking for is not how loud is that story
(11:09):
right now? That story is dormant. You're looking for that
story to start being told. So you can't start this
from asking AI, Hey, AI, what are the prominent stories
right now, because it can only tell you what's being
spread right then and there. What I find the way
(11:31):
to really make money with narratives is to say, what
narrative is dormant today? I want to see when it
starts to get discovered. Is that discovery phase when the
market quote unquote wakes up to a story that you've
been looking for the market to wake up to. That's
(11:52):
how I find you can most reliably make money from
narrative investments.
Speaker 1 (12:00):
So I get the sense we're still in the early
days of narrative investing as a key strategy, at least
in terms of using AI and big data. What do
you see developing in this space? What's the narrative about
narrative investing?
Speaker 2 (12:21):
Barry? This is, like I say, this is an old idea.
So if you if you go back and kind of
look at your Wall Street history, or if you talk
to kind of traders today, what they're always looking at
is the news that comes along, and they're trying to say, hey,
do I fade that you know? Is that story worn out?
(12:41):
Is it is that? Is it topping over? Or does
this story have legs? Is this the start of its spread?
Like a virus. So it's an old idea. What's possible
today is to quantify it. What's possible today is to
external life what good traders have internalized in the past.
(13:04):
So it's not that it's you know, inventing cold fusion
or really doing anything that's new in the world. What
it is able to do, though, is to make that
sort of analysis, to look at not what reality is,
but how reality is being presented, and make it available
(13:25):
over a much wider scope, not over just that little
area that the good trader really knows a lot about,
and make it available over a lot more publications and
things that are being written because humans can't read everything. Really,
I think it's a way of I hate to call
it democratizing investing. I really hate that idea, but it
(13:48):
really is a notion of creating a new instrument so
every investor can understand, well, what are the stories that
are being told about the world today.
Speaker 1 (14:00):
Wrap up technology has enabled us to read much more
than we were capable of reading as individuals. In fact,
the machines can read everything, and we can use those
machines to identify dormant narratives that might lead to increases
in either a particular stock or asset class or market
(14:25):
fair statement.
Speaker 2 (14:27):
Very fair. What you're looking for is what's new, what's changed,
because when the narrative changes, that changes behavior.
Speaker 1 (14:37):
Fascinating stuff. I'm Barry Riddtolts. This is Bloomberg's at the Money,
Investors have long been taught that fundamentals drive stock prices,
revenue growth, profits. As Benjamin Graham taught us, in the
short run, the market is a voting machine. But in
the long run it's a weighing machine. But what if
it isn't? What if narratives are driving market valuations. I'm
(00:32):
Barry Riddolets and on today's edition of At the Money,
we're going to discuss how to identify when market narratives
overtake fundamentals. To help us unpack all of this and
what it means for your portfolio, let's bring in Ben
Hunt of Percion. Ben's firm studies narratives and the stories
(00:53):
that shape markets, investing, and social behavior through the lens
of information theory. So Ben, let's start with a definition.
How do you define a narrative in the context of
markets and investing.
Speaker 2 (01:08):
It's a simple definition. A narrative is an answer to
the question why why did the market go up today?
Why should you buy the stock? Why should you sell
this stock? Why should you vote for this person? Any
answer to the question why is a narrative? Well?
Speaker 1 (01:28):
Sad you distinguish between something like data, which I arguably
comes with a storyline attached to it, and just a
straight up Hey, bitcoin is millennium or digital goals? Like,
how do you define the difference between this? I guess
this stock is cheap with a pe of nine? Is
(01:49):
a narrative?
Speaker 2 (01:50):
Yeah, well why is? Why is a pe of nine cheap? Right?
Or why is a pe of three cheap or fifteen cheap?
These are all stories. Any any valuation, any multiple, any
meaning that you attached to numbers, it's a story. It's
a It's an answer to the question why why do
(02:12):
I call it cheap? Why do I think you should
buy it? Why is this interesting? Those are all why
questions and the answer Those are all narratives.
Speaker 1 (02:22):
So how do you identify any particular narrative that may
be driving a particular stock or asset class or the
overall market? What what tools do you use to help
discern that?
Speaker 2 (02:38):
Well, let me start by saying what I don't care about.
So what I don't care about is truth or accuracy.
I mean, it sounds crazy, but.
Speaker 1 (02:47):
Not at all because you're trying to figure out what
the crowd believes, whether it's true or not. Well, if
it affects their behavior, it matters.
Speaker 2 (02:55):
It matters. Right, So I've I've given up on trying
to figure out what reality is. What I'm trying to
figure out is how is reality being presented? How is
it being presented to us? So what I'm looking for
are elements of presentation. I'm looking for word choice. I'm
(03:16):
looking for how loud is it being presented to you,
how frequently it's being presented to you. But most of all, Barry,
I'm looking for a concept that you talk about in
network math, and it's called density, And I'm looking for
how the language is connected to other words. In fact,
(03:37):
those are the measurements you use in network math. Those
are where they we talk about betweenness, we talk about
connectedness and centrality. Those are the measurements. Because I'm looking
at the presentation, not at the reality.
Speaker 1 (03:53):
So how do you measure density? You hinted at some
of it, how loud it is, how repetitive it is.
How do you tell when a specific narrative is beginning
to exert influence over prices?
Speaker 2 (04:08):
Yeah? So, Bob Sheller wrote a pretty good book a
couple of years back called Narrative Economics, And the takeaway
from that book is that you should think about and
understand narratives in exactly the same way you think about
and you understand disease. I mean, you use the same measurements.
(04:32):
You remember when we were talking about COVID, it was
are not right? How fast does it spread? How quickly
does it spread? What is the medium in which it
can spread most easily? It's exactly the same thing here, bear,
It's exactly the same thing. We're really using exactly the
same math as you would use to try to understand
(04:54):
epidemiology and the spread of a virus. So what we're
looking at, though, instead of the atmosphere or waste water,
we're looking at the words. We're looking at all the
words that are out there in terms of text, of
what's being written, what's being said. This is all unstructured data,
(05:18):
and we're looking for the presence of certain ideas, clusters
of words that spread through that medium of media in
exactly the same way that a virus spreads through the
air or through the water. If you're a financial advisor
or you're a market person of any sort and somebody
(05:38):
comes up to say, yeah, why the why the market
go up today? And you could say, well, there are
a hundred different reasons, but basically it was just variants.
You know, it's just it's just it's just random. It's
just a random walk. But it went up today. So
someone will look like people hate that answer because it's
(05:59):
a crappy story. It's just it's a it's just true.
Speaker 1 (06:02):
But it's not competitive exactly.
Speaker 2 (06:04):
It's not truthy, right, it doesn't it doesn't connect with you.
I said, well, that's disappointing. I want a story. So
the stories that are basically there to fill the time. Uh,
and these are these are typically examples where I call
(06:25):
them descriptive narratives. They're they're answering the question why, but
they're describing why something happened.
Speaker 1 (06:35):
Always after the fact, never in advance.
Speaker 2 (06:37):
Always after the fact. That's exactly right, Barry. So what
you'll find is that I don't know, it's earning season,
and who comes out first with earnings financials, right, and so, uh,
you know City and Goldman, Sacks, whoever. They'll report some
good earnings, the stocks will go up, and afterwards, Kramer
(06:59):
and everyone else, it's got to tell you why. And
they'll say, oh, I'm bullish on financials, and they'll give
you a reason. And that the half life for that
sort of narrative. It's a week or two. I mean,
it's it. And what you want to do with that, honestly, Barry,
(07:19):
is you want to fade it. You want to look
for that to appear in your Bloomberg email in the
morning saying, oh, market experts bullish on financials because blah
blah blah. And when that drum beating gets pretty loud
when it's appearing in your morning email, I want to
(07:40):
fade it. You don't want to press it. You want
to fade it because this is just the ordinary business
of Wall Street. You've got to have an answer to why.
It's almost usually just variants or some combination of idiosyncratic stuff,
but you've got to come up with some blanket why.
And if that gets a lot of play, I want
to go the other way. Now there's a there's another
(08:02):
type of narrative though, where I want to press it.
And so that's what we call prescriptive narratives. It's not saying, oh,
the Fed is dubvish. It's saying, you know, Mohammad l
Arion will come out or I don't know, Trump will
come out and say the Fed should be dubvish. You
(08:26):
see the difference. It's not it's not describing what's already happened.
It's trying to lay the framework for what should happen.
Speaker 1 (08:36):
So so let's delve into that. What sort of tools
are you using to identify these narratives, be they descriptive
or or prescriptive. How how much lead time do you
get to analyze you know, this giant corpus of noise
and commentary and data that is produced every single day.
Speaker 2 (09:00):
Well, this is what good traders, honestly and and investors
have always done. They've they've they've always made these sort
of assessments of the news and the stories that are happening.
So this what we're trying to do is we're trying
to externalize what good traders and i'll call it short
(09:22):
term investors have always done. They've always internalized this. So
anybody can do this. You start looking for the words
that are trying to prescribe versus describe. That'll you you
can you can pick this up in whatever you do.
What we're able to do though today is because there's
(09:44):
now big data, as because there's big compute, is we
can read everything. Humans we're all limited in what we
can read, what we can pay attention to. In our
little corner of the world. What's possible today is to
read everything into animal lies exactly, this sort of word choice.
Speaker 1 (10:04):
So what sort of output do you get from your
big compute that's scraping everything, Yeah, sifting through all the language, like,
does it identify specific words? Does it identify themes? I'm
assuming artificial intelligence and big data analytics is a key
part of this. What does the output look like to you?
Speaker 2 (10:27):
Well, let me start with where it starts, because it's
not that the output comes from what you put into
it and what you want to put into it, and
this has to be human generated. Are well, what are
the ideas? What are the narratives that I care about?
Here's why that's important, Barry, because let's say you're a
(10:47):
value investor. You've got a vision, you know, you've got
a view on a stock, and like all value investors,
you think the market has not recognized the story about
this stuff that I think is really important. So what
you're looking for is not how loud is that story
(11:09):
right now? That story is dormant. You're looking for that
story to start being told. So you can't start this
from asking AI, Hey, AI, what are the prominent stories
right now, because it can only tell you what's being
spread right then and there. What I find the way
(11:31):
to really make money with narratives is to say, what
narrative is dormant today? I want to see when it
starts to get discovered. Is that discovery phase when the
market quote unquote wakes up to a story that you've
been looking for the market to wake up to. That's
(11:52):
how I find you can most reliably make money from
narrative investments.
Speaker 1 (12:00):
So I get the sense we're still in the early
days of narrative investing as a key strategy, at least
in terms of using AI and big data. What do
you see developing in this space? What's the narrative about
narrative investing?
Speaker 2 (12:21):
Barry? This is, like I say, this is an old idea.
So if you if you go back and kind of
look at your Wall Street history, or if you talk
to kind of traders today, what they're always looking at
is the news that comes along, and they're trying to say, hey,
do I fade that you know? Is that story worn out?
(12:41):
Is it is that? Is it topping over? Or does
this story have legs? Is this the start of its spread?
Like a virus. So it's an old idea. What's possible
today is to quantify it. What's possible today is to
external life what good traders have internalized in the past.
(13:04):
So it's not that it's you know, inventing cold fusion
or really doing anything that's new in the world. What
it is able to do, though, is to make that
sort of analysis, to look at not what reality is,
but how reality is being presented, and make it available
(13:25):
over a much wider scope, not over just that little
area that the good trader really knows a lot about,
and make it available over a lot more publications and
things that are being written because humans can't read everything. Really,
I think it's a way of I hate to call
it democratizing investing. I really hate that idea, but it
(13:48):
really is a notion of creating a new instrument so
every investor can understand, well, what are the stories that
are being told about the world today.
Speaker 1 (14:00):
Wrap up technology has enabled us to read much more
than we were capable of reading as individuals. In fact,
the machines can read everything, and we can use those
machines to identify dormant narratives that might lead to increases
in either a particular stock or asset class or market
(14:25):
fair statement.
Speaker 2 (14:27):
Very fair. What you're looking for is what's new, what's changed,
because when the narrative changes, that changes behavior.
Speaker 1 (14:37):
Fascinating stuff. I'm Barry Riddtolts. This is Bloomberg's at the Money,
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