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Ich habe 70 Charts analysiert, um festzustellen, ob wir CRASHEN oder STEIGEN! (Deep Dive Analyse) — Transcript

by CoinCheck TV by Furkan Yildirim · 5,796 words · 933 segments · language en · Watch on YouTube

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0:00The entire Wall Street is currently
0:01arguing about a single question. Are we
0:03experiencing 1998 or 2000 right now, and
0:05the answer determines whether we see
0:07another doubling or a crash of nearly 80
0:09percent, because Thursday's crash is
0:11reminiscent of both years. In 1998, the
0:14market collapsed in a very similar way.
0:16After that, however, the Nasdaq more
0:18than doubled again by March 2000. In the
0:20year 2000, the bubble finally burst. The
0:22Nasdaq lost 78 percent and took 15 years
0:25to reach its old high again.
0:28So, is this 1998 and another doubling is
0:30coming before the burst, or is it 2000
0:32and the bubble is bursting right now?
0:34And anyone who overlays today's
0:36semiconductor index with that of 1999
0:38and 2000 sees this disturbing pattern,
0:40but that is only one argument, and
0:42Thursday's crash is truly significant.
0:44We lost 2.3 trillion US dollars in the
0:46Nasdaq alone, more than ever before, and
0:48according to textbook statistics, such a
0:51day should actually only occur every
0:538,000 years.
0:54That is why we will go through point by
0:56point today what speaks for 1998 and
0:58what speaks for 2000.
1:00At the end, you will get my answer and
1:02three indicators by which you can
1:03recognize for yourselves in which
1:04direction things are heading, and I will
1:06show you what also happened with Bitcoin
1:07on Thursday, because that was also
1:09unique.
1:10That is exactly what we will talk about
1:12, and for that, I spent the entire
1:13weekend working through 70 charts and 10
1:15analyses from Goldman Sachs, Nomura, JP
1:17Morgan, Bank of America, and others. Not
1:19just for this video, but also for myself
1:21, because I wanted to know where we
1:22stand right now and what I can derive
1:24from it for myself, and that is exactly
1:25what I will show you here in this video
1:26. I have visually reprocessed all the
1:28charts for you here with AI so that you
1:30can understand them even better. If you
1:32out there can derive value from this—
1:34you know the drill—feel free to leave a
1:35thumbs up under the video here, feel
1:36free to share the video as often as
1:38possible, and feel free to write a
1:39comment.
1:40And if you are new here and don't want
1:41to miss any further deep dives on the
1:43macro market, the financial market,
1:44Bitcoin, and more: feel free to
1:45subscribe and activate the bell for free
1:46, then you won't miss anything anymore,
1:48as I said.
1:49Let's start with the raw numbers from
1:51Thursday. You all noticed the crash. The
1:53Nasdaq 100 lost 6.36 percent.
1:56That was the worst day since March 16th
1:58. March 2020, that is, since the corona
2:00crash.
2:01The S&P 500 lost 4.36%, the most since
2:04the tariff shock in April 2020.
2:08The Nasdaq 100 alone lost around 2.3
2:10trillion US dollars in market value on
2:12this day.
2:14According to Bloomberg, this is the
2:16largest daily loss in the index's
2:17history, and Goldman Sachs has also
2:19recalculated it, especially
2:21statistically, regarding how rare such a
2:23day is.
2:24Anyone who participates in every single
2:26trading day on the stock market would
2:28technically have to wait 8,000 years on
2:29average to experience such a crash just
2:31once.
2:33And yet, we have already seen such a day
2:35several times this year, so extreme days
2:37are becoming the rule, which shows that
2:39textbook statistics simply no longer fit
2:41this market, and it wasn't the only
2:42extreme value on that day.
2:45The semiconductor ETF SMH has lost
2:47around 20%in five days.
2:50It last lost that much in March 2020,
2:52also during the Corona crash.
2:54The semiconductor index SOX also fell by
2:5712%in a single day.
2:59That was also its worst day since 2020,
3:02and if we go further, we will see, for
3:04example, that Nvidia, the second-largest
3:06company in the world, had a realized
3:08volatility of 100 over five days.
3:11Translated, that means the stock
3:12fluctuated by more than 6%per day on
3:14average, basically like a small shitcoin
3:17or an altcoin in the crypto market that
3:19also swings very violently.
3:21On Thursday alone, Nvidia fell by 9.3%.
3:25Goldman tracks its own baskets of stocks
3:27for individual AI themes.
3:2913 of them had their largest daily loss
3:32since the launch of ChatGPT in November
3:352022.
3:36At the very top are optical networks
3:39with -15.26%and memory chips here with
3:42-15.2%.
3:44Goldman’s broad US AI basket also had
3:47its worst day since March 2020.
3:50What is interesting is what didn't fall
3:52; for example, Apple only fell by 1.5%
3:54because they don't have a major
3:56commitment to the AI theme.
3:58The S&P 500 only has a 60%correlation
4:00with its own equal-weighted index, so
4:02the old mantra of "diversify widely and
4:04you'll be on the safe side" no longer
4:06applies.
4:08That simply doesn't work in this market
4:09anymore.
4:11What really occupied my thoughts while
4:12looking at all the data is that a day
4:14like this isn't happening for the first
4:16time.
4:17As mentioned, investors traded 11.23
4:20million put options on the CBOE on
4:23Thursday. A put is basically an
4:25insurance policy against falling prices
4:28. That is the highest figure in the
4:30history of the exchange. The old record
4:32was 10.22 million on April 4.
4:352025, at the height of the tariff panic
4:38.
4:38And if we take another step forward here
4:41to the next chart, you will see an
4:43interesting statistic there as well.
4:46The ten biggest days, these ten biggest
4:48put days, where bets on falling prices
4:51were extremely heavy, all occurred
4:53either this year or last year.
4:55And these statistics go back 30 years.
4:57Of course, put options are traded more
5:00generally than in the past, but the fact
5:02that the ten biggest days for this
5:04insurance against falling prices fall
5:06exactly on these two years is, I believe
5:08, no coincidence and says something
5:10about this market.
5:12Moving on, if you look at Goldman’s
5:15panic index for volatility on a scale of
5:180 to 10, it rose to 9.57 on Thursday,
5:20clearly in the panic zone.
5:23Goldman’s volatility desk writes that
5:26this is the greatest panic we have seen
5:28in a very long time. The VIX, the
5:31volatility index on Wall Street, rose by
5:3470%in a single day.
5:36The VXN, the fear barometer for the
5:39Nasdaq, saw its biggest daily jump since
5:42March 2020. And yet, the whole situation
5:45looks almost harmless in the S&P 500,
5:46you have to say, right? The S&P 500 is
5:49currently just 6.3%below its high. Since
5:522009, the average correction has been
5:557.6%. So, at the index level, everything
5:57still looks very normal. It is also
5:59already the third correction of more
6:02than 5%this year. Beneath the surface,
6:04however, it looks completely different,
6:05right? The Nasdaq 100 is now 14.7%below
6:08its record from the 6th of October.
6:1159 out of 100 stocks in the Nasdaq are
6:14already in a bear market, meaning more
6:16than 20%below their high. The
6:18semiconductor index is around 38%below
6:20its high.
6:22So the index hides how much damage is
6:24really prevailing on the surface, and
6:25that will become important later,
6:27especially when we talk about the Fed.
6:29But why did this happen right now? The
6:32trigger, I believe, is also clear. The
6:34US midterm elections were held on
6:35Tuesday. The Democrats won both houses
6:37of Congress, in addition to several
6:39governorships. The market was still
6:41celebrating that on Wednesday. On
6:42Thursday, the bill came due because of a
6:45topic that many have underestimated so
6:47far: data centers. People in the US do
6:50not want data centers in their own
6:52backyards.
6:53In an election poll, 76%of respondents
6:55rejected a new data center in their
6:57community, and this resistance is
6:59currently growing very rapidly.
7:02In September, 24%were strongly against
7:04it, in August it was 61%, and now
7:06politics is also coming into play. If
7:09you look at this, including an analysis
7:11from Goldman Sachs, around 45%of planned
7:13data center capacity in the US is in
7:15states where a construction moratorium
7:18could be looming after the election.
7:20Texas alone accounts for 26.7%of that.
7:23The new governor there wants to halt
7:25construction until new laws are, uh, in
7:27place.
7:28The legislative period in Texas runs
7:30until the end of 2027.
7:32The logic behind it is simple, right?
7:35So, if the construction of data centers
7:37slows down drastically, it impacts
7:39growth expectations, making them
7:41increasingly unrealistic, which is why
7:43the market sold off everything tied to
7:45this expansion on Thursday, right?
7:48That much is clear. But that is only
7:50half the story. The other half is the
7:52money. Very important, I already spoke
7:54about that on October 6th. October,
7:56spoken. In a deep-dive video, insiders
7:58know more. Uh, bets on AI bankruptcies
8:00are rising, where we looked at default
8:02insurance.
8:04By the way, that was exactly the high of
8:06the Nasdaq 100 and the intermediate high
8:08of the semiconductor index, so the
8:09timing fit quite well there.
8:12The big cloud corporations—if you look
8:15at it, just a reminder—the so-called
8:17hyperscalers have already issued 296
8:18billion dollars in bonds this year.
8:21Goldman had expected 250 billion for the
8:24entire year.
8:25That is around 9%of all investment-grade
8:27corporate bonds worldwide.
8:29In total, AI-related bonds this year
8:32stand at 687 billion dollars. And if you
8:35look at the data, you can clearly see
8:37that the credit market is currently
8:38getting even more nervous.
8:40A CDS is basically credit default
8:41insurance against insolvency, if one can
8:44no longer service loans, if a debtor can
8:46no longer pay back the funds.
8:49Goldman's basket for CDS on AI data
8:51center firms rose above 500 basis points
8:54on Thursday, a record.
8:57The bonds of CoreWeave, for example, one
8:59of the biggest or large AI cloud
9:00providers, are trading at a spread of
9:02over 12 percentage points above
9:03government bonds.
9:05The problem is simply that every quarter
9:08a permit is missing is another quarter
9:10of interest payments on a half-finished
9:12data center.
9:14The list of postponed or canceled IPOs
9:15and financings in the data center sector
9:17has been growing since September.
9:20We have just received a fresh report
9:22that Microsoft has canceled a data
9:24center with Oracle, for example.
9:27On Thursday, Bloomberg even reported
9:29that the bank ING wants to offload a
9:30credit package for data centers worth
9:32500 million dollars.
9:34Even at Goldman, where they are leaning
9:36more toward the 1998 scenario, they call
9:38the scale of spending and the
9:40uncertainty regarding returns an
9:42uncomfortable parallel to 2000, but
9:44large investments on credit existed in
9:46both years.
9:47That is, we must clearly state, it is
9:49not an indication that just because
9:50everything is running on borrowed money
9:52, it somehow points to the year 2000 and
9:53thus to a bursting of the bubble.
9:55We already had large investments on
9:57borrowed money back in 1998. That is
10:00very clear, or very important to note
10:01there.
10:02So, using this argument to say, hey,
10:04everything is running on credit, that’s
10:06why I’m getting out of the market now,
10:07that can be dangerous in the sense that
10:09you then miss the entire remaining rally
10:11because, as I said, major investments
10:13essentially started in 1996, or before
10:14the dot-com bubble.
10:16The essential difference was only made
10:18by the credit market. Starting in 2000,
10:20no more money was injected.
10:22Exactly, that is the open question today
10:24, and we will come back to that at the
10:26end of the video, how you can recognize
10:27it for yourself, because at the end of
10:29the day, it's all about when the flow of
10:30money is stopped.
10:32The question remains why such a
10:34political topic triggers a day that,
10:36statistically, should only occur every
10:388,000 days, and the answer lies, in
10:40principle, in the structure of the
10:41market. This is called the shrinking
10:43denominator. More than half of all
10:45stocks today are held passively, that is
10:48, via index funds and ETFs that buy
10:50stocks regardless of what they cost.
10:53A large part of daily trading comes from
10:55systematic strategies, index adjustments
10:58, and ETFs, and fast active funds
11:00operate with high leverage, meaning
11:02tight risk limits and very similar risk
11:05models when compared side by side.
11:08This means that with a shrinking
11:09denominator, a uniformly acting group
11:11can trigger daily movements that,
11:13according to standard statistics, hardly
11:15ever occur. Translated, this means that
11:17when one fund reaches its loss limit,
11:19they all do, and on the other side,
11:21there are only passive funds that don't
11:23care about the price and programs that
11:25sell simply because the price is falling
11:27. On Thursday, you could see that happen
11:29live.
11:31ETFs accounted for 32%of the total
11:33trading volume, the most since June, and
11:35almost no one was looking at individual
11:37stocks, right?
11:38Everyone sold the index, and then the
11:41programs took over; leveraged ETFs have
11:44to reset their leverage every evening.
11:46If prices fall sharply, they have to
11:48sell at the close of trading.
11:50On Thursday, that amounted to 48.6
11:53billion dollars, the second-highest
11:55value ever recorded, and if we continue
11:57here, then we also have the funds with
12:00volatility control.
12:02These funds determine how many shares
12:04they hold based on how much the market
12:06fluctuates.
12:07If volatility rises, they have to sell.
12:09In just one week, they dumped 117
12:11billion dollars in stocks, and then
12:13there are the market makers, right? They
12:16are constantly hedging themselves
12:17through options positions as well.
12:20When they have negative gamma, they have
12:22to sell into falling prices and buy into
12:24rising ones.
12:25That was around 7 billion more on top
12:28for every percent the S&P 500 falls, and
12:31the next wave is already lined up.
12:34Trend-following funds, the so-called
12:36CTAs, turned short on the Nasdaq when
12:39the index fell below 27,600 points.
12:42Below 26,800 points, their position
12:45drops back to the level of April 2025,
12:47which is when we had the, uh, tariff
12:50shock.
12:51The Nasdaq 100 closed at 26,630 on
12:55Thursday.
12:57In a weak scenario, Goldman expects
12:59another 7.5 billion dollars in sales for
13:02the S&P 500 alone over the next, uh, few
13:04days.
13:06We'll have to wait and see; we'll take a
13:08look at the, uh, statistics on that in a
13:10moment.
13:10If you look at the irony of the day, on
13:13Wednesday, when prices rose after the
13:15election, in the middle of that
13:17post-election relief rally, many
13:19investors sold their hedges. On Thursday
13:21, everyone wanted that exact same hedge
13:24back.
13:25With 6.2 million contracts, there was a
13:27new record for index puts.
13:30Three of the five biggest index put days
13:32of all time have occurred in the last
13:33three weeks, so there we also have a
13:35very stark extreme.
13:37At the same time, short selling on US
13:39ETFs rose by 7%, the sharpest increase
13:41since March. It's like a homeowner—if
13:44you translate it simply—a homeowner sold
13:46, uh, or canceled their fire insurance
13:48on Wednesday, and then on Thursday, the
13:50house just burns down, right? So that’s
13:52how quickly it can happen.
13:54And for our comparison between 1998 and
13:562000, this is also important because we
13:58essentially had market mechanics here,
14:00forced selling, and partly fundamental
14:02developments.
14:04It was exactly the same in 1998.
14:06Back then, the hedge fund LTCM got into
14:08trouble with massive leverage after
14:10Russia stopped servicing its debt.
14:13The markets collapsed, but the economy
14:15kept running. I'll tell you the whole
14:17story in more detail in a moment.
14:19What we have heard so far with these
14:21market mechanics is a clear argument for
14:22why there was such heavy selling,
14:24fitting for 1998.
14:25Now you might think the hedge funds beat
14:27the market down. The answer surprised me
14:29somewhat as well. The panic we saw
14:31earlier was in the options market and in
14:33trading the index as a whole.
14:36For individual stocks, it looked
14:37different. According to Goldman Prime,
14:39the department that manages hedge funds
14:41, the funds there did not sell in a
14:43panic.
14:44The bottom line: hedge funds, where a
14:46manager personally decides on every
14:48stock, were simply not the main drivers
14:50of this sell-off.
14:52Nevertheless, the tech funds were hit
14:54the hardest, losing 4.1%in a single day
14:57.
14:58Before the AI sell-off in the summer,
15:00they were still up around 24%for the
15:01year.
15:02Now they are roughly at zero. The entire
15:05AI gain for the year is gone, and if
15:06you're at zero eight weeks before the
15:08end of the year, you're obviously going
15:10to take less risk, right?
15:12These funds just want to survive until
15:14next year, and the question then is, who
15:16was selling besides all the algorithms?
15:19Above all, retail investors. There are
15:21clear statistics on this, too.
15:23On Thursday, retail investors sold a net
15:26$ 338 million in individual US stocks.
15:30There were only two days with higher
15:31volumes, back in March 2020 during the
15:33Corona crash.
15:34And of the ten largest sell-off days
15:36since 2020, seven occurred in 2024,
15:38which is another indication—if it still
15:40wasn't clear—that we are in very extreme
15:43times.
15:45At JP Morgan, retail sales had already
15:47reached around $ 1.3 billion by midday,
15:50primarily in large tech stocks,
15:52semiconductors, and leveraged ETFs.
15:56A trader at JP Morgan summarizes the
15:58sentiment—I’ve pulled out a quote here.
16:00It feels like retail investors have
16:03finally given up on the AI trade.
16:05There is also an important observation
16:07to be made here. After the sell-off in
16:09July, retail investors continued selling
16:11for days, even as the market was already
16:13recovering. So keep an eye on whether
16:15large institutional investors are now
16:17coming back into the market.
16:19Only that will sustain a real recovery,
16:20not retail investors who are just
16:22blowing back and forth like leaves in
16:24the wind, right? That is exactly what we
16:26keep seeing in the crypto market as well
16:28. And one more detail that many people
16:30really underestimate, in my opinion, is
16:32what retail investors are still buying,
16:35especially leveraged ETFs like the SOXL
16:37, which tracks the semiconductor index
16:39with triple leverage. The semiconductor
16:41index itself is still significantly
16:43above its April level. The leveraged one
16:45, on the other hand, has already fallen
16:46back to its April level.
16:49This is because the leverage eats up all
16:51the gains, and as I said, we see this
16:53time and again with these leveraged
16:55products, which are very popular with
16:57retail investors and where people just
16:59jump in because they get greedy, right?
17:03And then we move on to the next step,
17:05when we look at this globally: in Asia,
17:07the emergency brake is currently being
17:09pulled.
17:10Before we get to the big question of
17:12whether we are experiencing 1998 or 2000
17:14, it’s worth taking a look at Asia,
17:16because the state is now intervening
17:18there. Until recently, Taiwan was the
17:21last market that had hardly been
17:23affected by the AI sell-off.
17:25The Taiwan ETF EWT has now closed below
17:27its 200-day moving average for the first
17:29time since April 2023.
17:31It has only been this oversold a few
17:33times in the last 10 years.
17:35On Friday, the Taiex fell by 4.51%.
17:39For the week, it was 12.19%.
17:42According to Bloomberg, it was the
17:44weakest week since 2001, and that is
17:45when the state stepped in.
17:47They have a stabilization fund, and the
17:49state has now authorized its deployment
17:51.
17:52The fund has now released 500 billion
17:54Taiwan dollars, or about 15.3 billion US
17:56dollars, and is authorized to use it to
17:58buy stocks.
18:00So, the market is now being actively
18:01supported here.
18:04In terms of total volume, if you look at
18:06the sell-offs, it is probably not on a
18:08scale where you can say it's enough, but
18:10it is certainly an indication that the
18:13state, in this case Taiwan, is stepping
18:15in and saying we have crashed so hard
18:17that we must intervene now.
18:19In South Korea, it looked similar on
18:22Friday. The Kospi lost 8.76%after the
18:25opening, and trading was automatically
18:27suspended. In the end, it stood at a
18:29loss of around 6%.
18:31The government is now suspending for
18:32three months the requirement that
18:34brokers must demand a fixed minimum
18:35margin for securities loans.
18:37This is the first time since July 2022.
18:40The goal is clear: retail investors who
18:42bought on credit should not be
18:43liquidated, meaning they should not be
18:45forced into panic selling.
18:47By the way, Korea was already a leading
18:49indicator for AI trading, and the
18:51semiconductor index there, the SOX, has
18:52now caught up with the Kospi on the way
18:54down.
18:56And Japan, the Nikkei, also fell 6%and
19:00is now 20%below its recent high, which
19:03technically puts it in a bear market.
19:07So Asia is intervening with everything
19:09they have: sovereign wealth funds,
19:11short-selling curbs, and relaxed lending
19:13rules.
19:14You only do that when things are really
19:16on fire, and the AI sector is definitely
19:18on fire right now, and that is the big
19:20difference compared to the US, it must
19:22be said.
19:23There, the central bank is usually the
19:24fire department during a crash, and the
19:26Fed can lower interest rates to support
19:28the market.
19:28But this time, the exact opposite is
19:30happening, right?
19:31We’ve had interest rate hikes in
19:33September, now another pause, and the
19:35next hike is already priced in for
19:37December, which brings us to the big
19:38question: Is this 1998 or is it 2000?
19:41Let’s take a closer look at both years
19:43in detail to evaluate the similarities
19:46and differences, so we can then answer
19:48where we currently stand or what exactly
19:50matters right now, as that is our
19:52benchmark. 1998, what happened there in
19:54Russia, uh, in Russia? In the summer,
19:57Russia stated that they could or would
19:59no longer pay their debts.
20:02This led to a major crash, and most
20:03notably, the most famous hedge fund at
20:05the time, LTCM, began to falter.
20:07They had borrowed so much money that the
20:10entire financial system was under threat
20:12. The stock market plunged by a fifth,
20:15but then the Fed intervened.
20:17They brought the major banks to the
20:19table, saved the fund, and cut interest
20:21rates several times within a few weeks.
20:23The panic subsided. As mentioned earlier
20:26, the Nasdaq subsequently more than
20:28doubled.
20:292000, a clear difference. This time, the
20:32Fed did exactly the opposite.
20:34They kept raising interest rates because
20:36they wanted to cool down the economy.
20:37In March 2000, the Nasdaq reached its
20:39peak, and then the bubble, the dot-com
20:42bubble, burst.
20:43As stated at the beginning, it lost
20:46almost 80%and took 15 years to recover.
20:50And a strategist, if you want to bring
20:53in expert opinions, notably Goldman
20:55Sachs, for example, says: "I lean toward
20:571998." His reasoning: Unlike in the year
20:592000, today's market leaders have real
21:02revenue, cash flows, and balance sheets
21:04, and a delay in building data centers
21:06does not destroy the demand for
21:08computing power.
21:10It only postpones it.
21:12Let’s go through what I consider to be
21:14the most important arguments. There are
21:16several points that are important here.
21:18First, the valuation.
21:20Nvidia is currently trading at around
21:22ten times the expected earnings for the
21:24next 24 months, as cheap as it hasn't
21:26been since 2013.
21:28Valuations in the semiconductor sector
21:30have halved since June. Cisco was
21:32trading at well over a hundred times its
21:34earnings in the year 2000. That leans
21:37more toward 1998. Second, the Fed.
21:40In 1998, the Fed cut rates, in 2000 it
21:43raised them, and today we are still in
21:45the middle of an interest rate hike
21:47cycle, with about an 80%probability
21:49right now that we will see another rate
21:51hike in December.
21:53That would suggest 2000 in this regard.
21:56Third, earnings. Traders describe the
21:59situation like this: company figures are
22:00improving, yet stocks are falling anyway
22:02. The quarterly figures, prices for
22:04memory chips, and computing power are,
22:06uh, strong. Back in 2000, many stock
22:09prices were tied to companies that had
22:11no profits at all. That speaks in favor
22:14of 1998 again. If you look further into
22:17it, uh, there is this chart here. The
22:19exaggeration, so that is the fourth
22:21point. Bank of America measures how far
22:23the semiconductor index is above or
22:25below its 200-day, uh, line.
22:27This year it was up to 74%higher; this
22:29value was only higher during the dot-com
22:32bubble, here at 111%.
22:34In the last five days, the semiconductor
22:37index has lost more than 15%against the
22:39S&P 500, lagging behind as much as it
22:42hasn't since 2002.
22:44And let's go back to the beginning here
22:46, uh, to this chart with the
22:48semiconductor index overlaid with back
22:50then, '99 to 2000. The progression
22:52matches surprisingly well, you have to
22:55say. That speaks more for 2000 here.
22:58And this perhaps results in an interim
23:00picture that is very unsatisfying for
23:02some, namely that the arguments simply
23:03balance each other out now when you look
23:05at these points, the similarities and
23:07the differences.
23:08One open question remains, of course:
23:10will the credit market continue to
23:12finance, uh, things? And if you also
23:13look at a trend line, we also see that
23:15we are hanging by a thread there. A
23:17trend line that is now being tested for
23:19the third time on the Nasdaq.
23:21What my answer to this is now, and what
23:23my interim conclusion from this entire
23:25analysis is, is that we are more likely
23:28experiencing a 1998, but without the
23:30rescue by the Fed. The valuations, the
23:32profits, and the mechanical trigger look
23:35like 1998. But the most important
23:37element of 1998 is missing, namely the
23:39Fed stepping in, and that also has a
23:42clear reason.
23:43At the index level, hardly anything has
23:45really happened yet, right? S&P 500 down
23:486.3%.
23:50The last times the Fed acted or reacted
23:52, the S&P was significantly lower or in
23:55a much sharper, yes, correction or
23:58sometimes even in a bear market.
24:01What we saw, most recently in 2022, is
24:03that they even hiked further during the
24:04correction because inflation was high,
24:06and that is naturally also a very
24:08important point.
24:09Inflation remains at a very high level,
24:12and if we go further, generally, if you
24:14look at it currently, does that mean we
24:17are going down further now?
24:19If you look at the statistics, they
24:20actually say something different. Take a
24:22look at the 20 largest jumps of the
24:24volatility index since 1990 here.
24:27Thursday landed in third place here with
24:29plus 70%. Three months after such jumps
24:32, the S&P 500 was on average 5%higher
24:34after one year. So, these are actually
24:37Japanese-style moments where entering
24:39the market has historically and
24:40statistically paid off in most cases.
24:43And let's go even further. Since 2015,
24:45the Nasdaq has fallen by more than 5%on
24:47a single day seven times.
24:50Six times it was higher three months
24:52later, but six times it fell below the
24:54level of the crash day again within one
24:56month.
24:57So usually, there is an initial recovery
24:59after such a big crash. You can see that
25:02here in this second column. So most
25:03cases are then green. After a week,
25:06however, there is another low, where
25:08this low is tested once more. But
25:10afterwards, if you look at it after
25:12three months—which isn't exactly a
25:14long-term perspective, I find—three
25:16months, we actually see a recovery again
25:18and again.
25:20What is interesting, however, is that
25:22there is one exception, and that was in
25:232022, in the exact case where the Fed
25:25had raised interest rates, and that is,
25:27as I said, currently the case as well,
25:29and Goldman has also evaluated this for
25:30its panic index.
25:32After the 15 previous signals above 9.5
25:35, the S&P 500 was on average 4.6%higher
25:38after three months in 80%of the cases.
25:42After one month, it was only 0.68%on
25:44average.
25:45These figures come primarily from phases
25:47in which the Fed was actually helping.
25:50The turnaround must therefore come from
25:51somewhere else, and there are three
25:52indicators for this, in my view, which
25:54you can also observe yourselves in the
25:55coming weeks. The first is volatility.
25:57Volatility-controlled funds have sold
26:00117 billion dollars. Their equity
26:02allocation is now as low as it has been
26:05in only 14.6%of cases over the last
26:07three years. As soon as the fluctuation
26:09drops, as soon as the volatility index
26:11drops, they have to buy back
26:12automatically. No market can sustain a
26:15volatility of 100 at Nvidia for long. So
26:17that will not remain a normal state in
26:20my view. At some point, the market will
26:22level off again, the volatility indices
26:25will also pull back, and then these
26:27volatility-controlled funds will have to
26:29buy back. The second indicator, and this
26:31is very important and I believe many are
26:33currently underestimating it, is
26:34politics. Remember April 2025. The
26:37Nasdaq fell by more than 11%over two
26:40days because of tariffs.
26:42A few days later, Trump suspended most
26:44tariffs for 90 days, and by the end of
26:46June, the Nasdaq was at a new record,
26:48right?
26:49So that is what happened. The Fed didn't
26:51cut rates back then until September.
26:53The trigger was political, so the
26:54turnaround also came from politics.
26:57This time, the trigger is the threatened
27:00construction freeze for data centers,
27:02and the new governor of Texas is already
27:04saying herself that it’s not like they
27:06hate data centers, right?
27:08So she is already rowing back a little
27:10bit. Projects that have already been
27:11approved should just be allowed to be
27:12completed. Goldman calls this a
27:14regulatory reset and expects any
27:16potential construction freezes to be
27:18short-lived.
27:19The third indicator is the credit market
27:21, and that decides between 1998 or 2000
27:23in my view.
27:25At the moment, the fire is only burning
27:26in one corner, and that’s specifically
27:28those building data centers; they are
27:30currently paying large premiums and
27:32higher interest rates.
27:34As I said, CoreWeave, for example, is
27:36paying over 12 percentage points more
27:37than the US government. But for normal
27:39large companies, you can hardly see any
27:41of that.
27:42Back in 2000, it also only started
27:43burning in one corner. First, the
27:45telecom companies stopped getting money
27:47, then it spread. Suddenly, even healthy
27:49companies had to pay much higher
27:51interest rates.
27:52Many couldn't get any new loans at all,
27:54and in the end, the economy slipped into
27:55a recession.
27:57That is what you need to pay attention
27:58to.
28:00If normal companies suddenly have to pay
28:02significantly more interest, or if
28:04companies cancel their bonds because
28:06they can't find buyers, then the fire
28:08spreads, and 1998 becomes 2000 once the
28:10cash flow stops.
28:12That is the deciding factor in my view.
28:14If it stays limited to the data centers
28:17, then it’s more like 1998. And above
28:19everything stands the interest rate path
28:20. So, an interest rate hike in December
28:21is priced in. The next important dates
28:23are the 10th. November inflation data,
28:25the 9th. December, the next interest
28:27rate decision. But not everything will
28:28be decided there; it depends on the
28:30coming months.
28:31Is inflation cooling down, or are we
28:33really seeing a continued steep rate
28:35path where further hikes are priced in?
28:38Many assume that this will be the last
28:40rate hike because the market can't
28:42handle any more than that, and
28:43accordingly, it will depend on that.
28:46My personal opinion is, as I said, 1998
28:49is more likely, and I will take every
28:51chance to keep investing and further
28:53reduce my cash position.
28:56I already did that this past week, in
28:58the week where the crash happened, or a
29:00day before, I bought Alphabet shares for
29:02example, I anticipated six weeks of ETF
29:04savings plan installments, and invested
29:06manually once more. I last did that in
29:09April 2025, and if it continues to go
29:12down—which is what the statistics
29:14suggest might happen, that the lows
29:17might be tested again in the traditional
29:19market—then I will naturally buy more.
29:22With Bitcoin, as I promised you, it is
29:24only the second time that Bitcoin fell
29:27less than the Nasdaq when the Nasdaq
29:29dropped more than 5%.
29:31The other time was here on the 16th.
29:34March, so the Corona crash. That was
29:36actually a very good entry point, wasn't
29:37it?
29:38We shouldn't forget that, and if we go
29:41further here, um, Bitcoin stocks
29:42naturally fell twice as hard, which I
29:44think is no surprise, and Bitcoin was a
29:47year ahead.
29:48That is also one reason why Bitcoin is
29:50currently holding up a bit better. The
29:52Nasdaq, by the way, hit its all-time
29:54high exactly one year after Bitcoin. On
29:56the 6th. October we had our all-time
29:58high, and since then, Bitcoin has been
30:00underperforming, and then the selling
30:02pressure is naturally a bit reduced. So
30:04let’s summarize.
30:05Thursday was statistically an 8,000-
30:07year event, but such days are occurring
30:09more and more frequently in this market
30:10because the machine produces them that
30:12way, because the market is currently
30:13structured like this.
30:15Valuations and earnings speak for 1998;
30:18the Fed speaks for 2000. My answer is
30:20more like 1998, but without the Fed
30:22rescue because it’s simply too early.
30:26In my view, there is still room to the
30:28downside before the Fed can or must
30:30react, but overall the earnings are
30:32definitely there, so my answer is 1998,
30:34and whether it shifts will be shown by
30:37volatility, politics, and especially the
30:39credit market.
30:41I already showed you that on October 6th
30:42.
30:43That is nothing—it shouldn't be anything
30:45new to you, what I’m telling you here
30:47regarding the credit market, but I will
30:49of course keep you updated in the coming
30:52weeks and always share these
30:53developments with you.
30:56Feel free to write in the comments what
30:58you think—is this a good chance to add
30:59to positions, or are we really seeing a
31:01dot-com bubble like in 2000?
31:03What do you make of the situation?
31:06With Bitcoin, you know anyway that I
31:08only buy when we are in the value zone,
31:10unless something tax-related changes or
31:12for whatever other reason, then I will
31:15let you know, but currently, it is not
31:17my plan to actively buy spot.
31:20In the traditional market, I became
31:21active, and I will of course continue to
31:23update you on that. Feel free to leave a
31:25comment to wrap things up, and as I said
31:26, give this topic a thumbs up.
31:29Also check out the video description,
31:31where you'll find my partners, including
31:33OKX, where you can spot trade, trade
31:35pre-IPOs for OpenAI and Anthropic, trade
31:37futures, and currently secure VIP status
31:39, which lets you get things like over 4
31:41%cashback on the OKX card.
31:44You can find all that and more in the
31:46video description, as well as the Grid
31:48Bot tool, which you can get for free.
31:50You’ll also find the tutorial here,
31:52which shows you the more than 700,000
31:53trading bots I simulated there. And I
31:55hope this video was able to provide some
31:57good value for you here. If so, feel
31:58free to leave a thumbs up at the end,
31:59otherwise, I'll see you again in the
32:01next update. Bye-bye.

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