Hey, everyone. I'm starting a series on

risk management, because that's my area

of expertise after 12 years of

experience working at Goldman Sachs. And

in this video, I will cover how I

identify warning signs before major

market declines, how I hedge my

portfolio, how I prepare for volatility,

and most importantly, how I protect

capital when the market environment

starts to change. Now, look at this.

This is really interesting. Look at my

YouTube views. Now, look at the market.

These are two separate charts. However,

you will see that they look very

similar. Now, I want to overlay YouTube

views over the stock market, and you'll

see something very interesting. You will

see that there's a huge correlation, or

basically, whenever my YouTube views go

down, that the stock market also goes

down. I'm launching an indicator that

can help investors predict when the

market is likely to crash before it

crashes. This indicator will connect the

following three criteria. The first is a

speculation and sentiment score. This

looks at things like YouTube views,

retail investor attention, and Google

Trends, option activity, and other

measures of investor enthusiasm. The

idea is simple. When everyone becomes

extremely bullish and speculation starts

accelerating, complacency may be

building. The second is a market health

score. Here, I'll look beneath the major

indexes at things like market breadth,

how many stocks are trading above their

200-day moving average, small cap

performance, credit spreads, volatility,

and whether fewer stocks are actually

participating in the rally. And third is

a macro and liquidity score. This looks

at the bigger economic picture,

financial conditions, credit markets,

earnings revisions, liquidity, interest

rates, and other signs that the

environment supporting stocks may be

weakening. So, let's focus in this video

on how I spot market crashes before it

may happen. This is only part one of the

series, and today we're focusing on

detection, how I identify when the

market risk is starting to build. In

part two, I'll show you exactly how I

prepare and adjust my portfolio when

these warning signs appear. Then in part

three, I'll break down how I actually

hedge and protect my portfolio if the

risk of a major decline becomes much

higher. If you want access to my full

market risk scorecard including live

updates to my YouTube views and

sentiment indicator, you can now find it

in description below. It's only in this

specific video. Now, the goal is simple.

Identifying when market risk is building

early so you have more time to prepare

before potential dangerous market

conditions develop. My market warning

score will be from one to 10 and higher

score that a crash is more likely to

happen in the near term. Let's start

with why this is even reliable to begin

with. For that, we need to understand

how retail attention matters. So,

markets aren't driven purely by

earnings, revenue, or economic data.

They're driven by people and people are

emotional. Fear and greed can push

prices much further in either direction

than fundamentals alone might suggest.

Think about what happens during a strong

bull market. Stocks are starting to go

up, investors start making money, and

suddenly people who weren't paying

attention market six months ago are now

becoming interested. And now there's

more people rushing to the market to buy

up stocks because they think that it's

easy money. They see their friends

making money, they see stocks constantly

appearing on social media, and they

start searching for stocks to buy,

watching investing videos, opening up

brokerage accounts, and sometimes taking

significantly more risk or investing

money that they would not have even

invested in the first place. And that is

where FOMO starts to become important.

When markets have already gone up

substantially, investors often become

even more confident, unfortunately, and

that is precisely when prices are

becoming more expensive. Instead of

asking how much could I lose, people

start asking how much more money can I

make. That behavior is exactly what my

indicator is looking to measure. You can

look at Google search activity, you can

look at options activity, you can look

at retail trading volumes, you can look

at social media engagement. And in my

case, I have another data set that I've

been watching for years, our very own

YouTube channel. When hundreds of

thousands of retail investors suddenly

become much more interested in the stock

market content, I think that's really

worth paying attention to. It doesn't

mean that YouTube views predict a crash

alone. If my views double tomorrow,

obviously I'm not going to be selling my

portfolio because I think the market's

overvalued based off of my views alone.

Instead, it is a data point and a piece

of information that has really strangely

been very accurate in a backtest result.

When I had backtested my YouTube data

versus when markets were going down,

they were correlated at 0.79%

and we'll talk about what correlation

means later on in this video. So,

imagine that S&P 500 is still making new

highs. From the outside, everything

looks good, but underneath the surface,

fewer stocks are participating in the

rally. Small caps are weakening, credit

conditions are deteriorating, and

volatility is starting to behave

differently. Earnings expectations are

being revised lower. Meanwhile,

investors and specifically retail

investors are more bullish than ever.

That is a type of divergence that I am

looking for. Markets are extremely

emotional. When everything is going up,

investors tend to believe the good

environment will continue. They also

completely give up and you can see

videos of mine that usually would get 5x

the views that don't get any more

attention. That's how I know when the

bottom is near. All right, here's what

I'm seeing with YouTube views and why

this matters for investors. So, check

out my YouTube views which have been

steadily going down and check out QQQ,

which is basically the Nasdaq. This is

the ETF for the Nasdaq. Very, very

similar. And actually plot of them on

the same chart here with today, all the

days in July and now it's July 30th as

I'm recording this video. So, for the

month of July, I have basically taken my

views every single day, okay, and I have

taken the close price of QQQ. Of course,

on the weekends and on the holiday it

was closed. So, I have taken these two

numbers and I have ran a correlation.

I'm going to explain correlation in a

moment or I will soon in this video. And

you can see that surprisingly, this is

very shocking data, the correlation is

.86 for the views that I'm getting as

well as the market coming down. And I

plotted here as well. This actually

makes pretty logical sense. This means

that essentially when investor

enthusiasm, which I'm defining as one of

the data points in my indicator as my

YouTube views, which you can track as

well in my indicator that I have, is

that when people are searching for

option trading topics, stock market

topics, investing topics, which is what

I cover on this channel, and when that

search volume goes down, the stock

market is also going down. That

correlation is pretty clear. And what

I've seen recently is I've made a video

which is 54 minutes long, 4.7 thousand

less views. I made another video here, 1

hour and 27 minutes. Now, these videos

are typically I'm getting double or

triple or even quadruple the amount of

views when the market is hot. As soon as

I have a video that's not performing

well, that actually tells me some

important information,

which is that investors are not that

excited about the market because they're

feeling fearful. It's actually a very

important metric within my indicator

because this has been historically, on a

back test, extremely useful information.

Now, I want to show you a little bit

more about correlation and what

correlation actually looks like. So,

here is Nvidia stock and I'm going to

use Nvidia stock and compare it to AMD

stock so you can understand what

correlation does to your portfolio and

how to diversify better against stocks

that are correlated, which means that

they're going to fall down together. So,

here's Nvidia stock, okay, it's at $190

per share. We have a simple chart here,

okay? Pretty straightforward. Now, you

can also see correl here, which stands

for correlation 14 days, and I can

change this number and play around with

it. But we're just going to use 14 days

for now. Okay, so I'm going to add a

comparison. The comparison I'm going to

add is AMD. So, when I go into AMD right

down, you can see here on the chart that

of course they're very different, okay?

Over the last 6 months, they're very

different. Let me do 1 month here. Over

the last 3 months, as you can see here,

although the stocks are moving pretty

differently, and one stock's up 27%

whereas it's down 9% over the last 3

months, the correlation here is actually

.9, meaning similar to the chart that we

have seen earlier, that there is a very

strong relationship between these two

stocks moving together. Now, what I want

to do is pull up an AI stock, Nvidea,

ticker symbol NVDA, and I want to

compare it to another AI stock because I

want to show you how dangerous it is to

have multiple AI stocks. You can see

here, I am using NVDA and IREN, and they

have a correlation of .92, even stronger

relationship than AMD and Nvidia, which

anything over .75 is already a very

strong relationship. .92 basically means

you're practically owning the same

stock. So, if you have multiple stocks

in your portfolio, but they're in the

same sector, or specifically they're

tied to AI, you are not as diversified

as you think. The market is really

connected, which is why this data that I

have of my YouTube views and the QQQ

close price is also surprisingly

extremely correlated. So, whenever I

spend multiple thousands of dollars to

create awesome content on YouTube and

nobody subscribes or watches it, it

doesn't make me bitter, it doesn't make

me upset, it just makes me realize that

the investors who are very enthusiastic

in the market are now being very

fearful, it's actually a good indicator

that the market is likely to pull back

or have poor future performance. Let's

get into the next chapter of my

detection series and discuss

correlation. You might think you're

diversified because you own 15 or 20

different stocks. You have watched other

videos about diversifying and protecting

yourself, but if most of these companies

are exposed the same underlying risk

factors, your portfolio may be much more

concentrated than it actually looks.

During periods of market stress,

correlations can also increase.

Investors reduce risk, institutions

reposition portfolios, leverage gets

unwound, and selling can spread across

sectors, even if that specific sector

doesn't warrant a pullback. Suddenly, it

matters a lot less that you own 20

different stocks if 17 of them are

falling together. So, before we look at

a real example, let me quickly explain

what correlation actually means. Imagine

there are two completely different

stocks, stock A and stock B. If stock A

goes up and stock B tends to go up at

the same time, and when stock A falls,

stock B tends to fall with it, those

stocks have a positive correlation.

Correlation is generally measured -1 to

+1. A correlation near +1 means the two

investments have historically moved very

closely together. You can see an example

of correlation here on the screen, which

is exactly one. It's essentially just a

straight line. Now, here is a plot of

dots with a correlation of 0.8. You can

see how these two lines are very

related, but they're not exactly equal

to each other as the dots are spread out

and there are some outliers. Now,

correlation is explaining the

relationship between two things. A

simple example of that is height and

weight. So, the chart that I'm showing

you on the screen is actually a chart of

height and weight. Taller people tend to

weigh more, so as height increases,

weight generally increases, too, but

it's not perfect, which is why the dots

wouldn't form a perfectly straight line.

For example, height and weight are

positively correlated. In one study of

more than 11,800 adults, the correlation

was about 0.55.

So, taller people tend to weigh more,

but the relationship was nowhere near

perfect. Now, here's why this matters

for risk management and what it means

for your portfolio. Imagine I split my

money equally between five different

stocks. At first, that seems

diversified, but if all five have

extremely high correlations with each

other, a major stock can push almost the

entire portfolio in the same direction.

Compare that with a portfolio containing

investments whose returns aren't as

closely correlated, and you will see a

really big difference. One position

might be falling while another is

relatively stable or even moving higher.

It doesn't mean that low correlation

eliminates risk completely. It means

that you're less dependent on one market

factor determining what to your entire

portfolio. So, when I think about

diversification, I'm not just counting

positions. I'm asking how much of my

portfolio could realistically start

moving in the same direction at the same

time. Now, imagine what's happening at

the same time. The S&P 500 is near an

all-time high, retail investors are

extremely bullish, my YouTube views and

other measures of speculation are

exploding. Individually, none of these

indicators tell me a crash is definitely

happening. That's impossible to tell,

and nobody can really predict the

market. However, together, they're

telling me something much more

interesting. I was joking with my

community that I found how to predict

the market. And again, of course, nobody

can do that. Only maybe Michael Burry

can do that, and he's done that about 10

of the last three times. If you get that

joke, you get that joke, right? Means

that he can't even predict the market,

right? But when I look closer at my own

YouTube data, I've actually gained some

confidence that combining multiple

factors, especially my enthusiasm score,

performed surprisingly well for timing.

This unusual indicator, I believe, will

be very useful for you to protect your

portfolio going forward. I also think

it's a great way to get risk

management-focused together in a small

focused community. We can see the views

that I'm getting, how enthusiastic or

how greedy or how selfish or how fearful

investors are based off of the videos

that I'm making, and we can also use

other indicators to combine to make up a

full score to try to protect ourselves,

especially before a market crash may

happen. Because by the time that

everyone already agrees that there's a

problem in the market has already

repriced significantly. And I'm looking

to be early before momentum really

catches on and it's too late. Now, you

can subscribe for part two if you're

interested. I'll be using VIX as one of

the factors to understand within your

own risk management process. So, I'll be

diving deeper into risk management

topics and depending on how many likes

and interest this video gets, then I'll

consider making the part two. Check out

my YouTube if you're interested in my

own indicator based on my own data set

for my YouTube channel, then go ahead

and check out the link in the

description. Make sure to subscribe and

if you're interested in that indicator

that follows my YouTube data, then go

ahead and check it out right now.