E7: NVIDIA AI BUBBLE - We Can't Stay Quiet Any Longer

Funding Awesome
3 Mar 202455:45

Summary

TLDRThe video script features an insightful discussion between Larry Tentarelli and Alex, examining whether the current market conditions constitute an AI bubble akin to the dot-com bubble of 2000. Larry, a seasoned investor with firsthand experience during the dot-com era, meticulously analyzes various data points, including stock price movements, valuations, IPO activity, and profitability. Through comprehensive comparisons and historical context, he presents a compelling argument that the current market dynamics, driven by AI and technological advancements, do not mirror the speculative frenzy of the past. Instead, he highlights the robust fundamentals, defensible technology, and high-quality earnings underpinning companies like NVIDIA, suggesting a sustainable trajectory rather than a fleeting bubble.

Takeaways

  • đŦ The current tech market conditions are being compared to the dot-com bubble of 2000, but the data shows significant differences that suggest it is not a true bubble scenario.
  • đĻ The NASDAQ 100 index has only risen 3x in the past 5 years, compared to a 12x rise during the dot-com bubble, indicating a much slower and more sustainable growth.
  • đ¸ The current NASDAQ P/E ratio is 42, which is only a quarter of the 175 P/E ratio during the dot-com bubble peak, suggesting more reasonable valuations today.
  • đĻ There were 20+ stocks that rose over 900% during the dot-com bubble, while today's top performers like NVIDIA have seen much slower growth in comparison.
  • đ° The IPO frenzy during the dot-com bubble was unprecedented, with an average 70% first-day return and 165 IPOs doubling on their first day, which is not being observed in today's market.
  • đĢ NVIDIA's earnings and revenue growth have outpaced its stock price growth, indicating that its valuation is supported by strong fundamentals rather than speculative mania.
  • đ¤ The customer base for tech companies today, such as NVIDIA, consists of well-established, cash-rich companies, unlike the dot-com era when many customers were undercapitalized startups.
  • đ´ The top 10 companies in the NASDAQ 100 today have 12x higher revenues than the top 10 companies during the dot-com bubble peak, reflecting the maturity and profitability of today's tech giants.
  • đĩ Profitability and cash flow generation are a major focus for today's tech leaders, in contrast with the dot-com era's emphasis on potential and unfulfilled promises.
  • đĨ While market corrections are always possible, the data suggests that the current tech market conditions are fundamentally different from the speculative dot-com bubble environment of 2000.

Q & A

  • What is the main topic being discussed in the video?

    -The main topic being discussed is whether the current AI and tech stock market rally can be considered a bubble similar to the dotcom bubble of the early 2000s.

  • Who is the guest being interviewed, and what qualifies him to speak on this topic?

    -The guest being interviewed is Larry Tentarelli, who has over 25 years of experience in the financial markets, including working as a licensed broker at Merrill Lynch during the dotcom bubble. He has extensively researched and analyzed the current market conditions and historical data to compare the two market environments.

  • What are some key differences between the current AI stock rally and the dotcom bubble that the guest highlights?

    -Some key differences highlighted include: 1) The magnitude of the NASDAQ 100 index gains (12x during dotcom vs. 3x now), 2) Valuations (NASDAQ P/E of 175 then vs. 42 now), 3) Number of parabolic stocks (20+ then vs. very few now), 4) IPO activity (over 440 IPOs in 1999 with massive first-day pops vs. much lower IPO activity now), and 5) Profitability of leading companies (many unprofitable then vs. highly profitable now).

  • How does the guest compare Nvidia's performance and financials to Cisco's during the dotcom bubble?

    -The guest compares Nvidia's net income of $29.7 billion in fiscal 2024 to Cisco's best year of $2.6 billion net income in fiscal 2000. He also notes that if Nvidia traded at Cisco's peak P/E ratio of 196, it would have a market cap of $5.8 trillion, about twice as big as Microsoft currently.

  • What is the significance of the quality of customers for companies like Nvidia compared to during the dotcom bubble?

    -During the dotcom bubble, many of the customers for companies like Cisco were unprofitable, venture capital-backed startups that eventually went out of business. In contrast, Nvidia's customers today are financially stable, major tech companies like Meta, Tesla, and Google, who are unlikely to go out of business anytime soon.

  • How does the guest respond to concerns that the current AI stock rally is a bubble?

    -The guest acknowledges that stocks can go down at any time, but based on his analysis of historical data and current market conditions, he does not see any evidence that the current AI stock rally meets the criteria of a bubble comparable to the dotcom bubble of 2000.

  • What lessons did the guest learn from his experience during the dotcom bubble?

    -One key lesson the guest learned was the importance of using technical analysis and strict risk management techniques, such as selling stocks when they break below the 200-day moving average, to avoid significant losses during market downturns.

  • What role does the quality of earnings play in the guest's analysis?

    -The guest emphasizes the high quality of earnings for leading AI and tech companies today, with many generating significant cash flow and even paying dividends, in contrast to the mostly unprofitable dotcom companies of the early 2000s.

  • How does the guest respond to concerns about high valuations for companies like Nvidia?

    -The guest notes that while Nvidia's stock has risen significantly, its earnings growth has outpaced its stock price gains, resulting in a lower P/E ratio compared to the start of its current rally. This is in contrast to the dotcom bubble, where stock prices rose much faster than earnings.

  • What is the guest's overall conclusion about the current AI stock market environment?

    -The guest's overall conclusion is that, based on his extensive analysis and first-hand experience, the current AI stock market rally does not exhibit the characteristics of a bubble comparable to the dotcom bubble of the early 2000s, and he expects the rally to continue for longer than most people anticipate.

Outlines

00:00

🗣️ Introduction and Background

The speaker, Alex, introduces his friend Larry Tentarelli to discuss whether we are currently in an AI bubble, similar to the dot-com bubble in the late 1990s. Larry shares his background as a licensed broker at Merrill Lynch from 1998 to 2003, experiencing the dot-com bubble firsthand. He explains how he decided to study what happened and develop a technical trading process to avoid similar mistakes.

05:00

📈 NASDAQ 100 Performance Comparison

Larry compares the NASDAQ 100 performance between the dot-com bubble period (1995-2000) and the current AI bubble period (2018-2024). He highlights that the NASDAQ 100 went up 12x during the dot-com bubble but has only gone up 3x in the current period, suggesting a much smaller move. He also notes that the current NASDAQ 100 level is only 8% above the 2021 highs, which doesn't indicate a bubble.

10:06

💰 Parabolic Stock Movements

Larry discusses the parabolic stock movements witnessed during the dot-com bubble, with stocks like Qualcomm rising 2,619% in 1999 alone and 20 tech stocks rising by 900% or more. He contrasts this with the current market, where only a few stocks, mostly biotechs, have seen such massive gains, and the top performers like Nvidia don't come close to the dot-com bubble levels.

15:07

🚀 IPO Frenzy Comparison

The discussion turns to the IPO frenzy during the dot-com bubble, where the average first-day return for internet IPOs was 266% in 1999, compared to 59% for non-internet IPOs. Larry shares examples of IPOs that doubled or more on their first day, with the top 10 averaging a 500% first-day return. He contrasts this with the current market, where he couldn't find any IPOs that doubled on the first day in 2023.

20:10

🤯 Speculative Frenzy and Valuations

Larry discusses the speculative frenzy during the dot-com bubble, citing examples of companies like Corvis, which raised $1 billion in an IPO but had no sales and a $27.6 billion market cap. He compares this to the current market, where he doesn't see anything close to that level of speculation or unrealistic valuations.

25:13

🆚 Nvidia vs. Cisco Comparison

Larry compares Nvidia's performance and profitability with Cisco during the dot-com bubble peak. He highlights that Nvidia made $29.7 billion in net income last year, 11 times more than Cisco's best year in 2000. Furthermore, Nvidia made more money in 20 days last quarter than Cisco did in their entire best year, suggesting a significant difference in profitability and performance.

30:16

💹 Earnings Growth and Valuations

The discussion focuses on Nvidia's earnings growth and valuations. Larry points out that Nvidia's stock price has not risen as fast as its earnings growth, with earnings per share up 764% in the past year while the stock is up only 230%. He argues that this is the opposite of what would be expected in a real bubble, where stock prices would rise faster than earnings growth.

35:17

🏦 Revenue and Earnings Comparison

Larry compares the revenues and earnings of the top 10 NASDAQ 100 companies during the dot-com bubble peak in March 2000 with the current top 10. He highlights that the current top 10 companies have total revenues of $1.8 trillion, 12 times greater than the $148 billion total in 2000, while the NASDAQ 100 price is only up 3.7 times. This disparity suggests that the current market is not overvalued compared to the dot-com bubble.

40:18

🧑‍💼 Customer Quality and Financial Stability

An important distinction between the dot-com bubble and the current market is the quality of customers and their financial stability. During the dot-com bubble, companies like Cisco and Sun Microsystems sold to startups with limited capital, which eventually went out of business. Today, Nvidia's customers are financially stable companies like Meta, Tesla, and Amazon, reducing the risk of customer insolvency.

45:18

🔍 Personal Experiences and Lessons Learned

Larry shares his personal experiences during the dot-com bubble, including the emotional and financial toll of trading volatile stocks on margin. He discusses the lessons learned, such as implementing a technical trading process and selling stocks when they close below the 200-day moving average to protect capital. He emphasizes the importance of managing emotions and following a disciplined approach.

50:19

📊 Data and Research Process

Larry highlights the importance of conducting thorough research and relying on primary sources for data. He explains that his team pulled annual reports and financial statements directly from company websites to compile the numbers used in their analysis, ensuring accurate and reliable information.

55:22

🎬 Closing Thoughts and Summary

In closing, Larry summarizes the key points discussed, including the differences in market performance, valuations, IPO activity, earnings growth, and customer quality between the dot-com bubble and the current market. He emphasizes that while stocks can go down at any time, the data and analysis do not support the notion that the current market is in a bubble comparable to the dot-com era.

Mindmap

Keywords

💡Tech Bubble

A tech bubble, or speculative bubble, refers to a period of excessive speculation and inflated prices in technology-related stocks or assets. The script suggests that some believe the current AI/tech stock market is experiencing a bubble similar to the dot-com bubble around 2000. However, the evidence provided aims to debunk this notion.

💡Valuations

Valuations refer to the methods and metrics used to determine the fair value or worth of a company or its stock. The script compares the price-to-earnings (P/E) ratios of tech stocks during the dot-com bubble to current valuations, showing that today's valuations are much lower, indicating a lack of irrational exuberance.

💡Parabolic Stocks

Parabolic stocks refer to stocks that experience extremely rapid and unsustainable price growth, often indicative of speculative frenzy. The script contrasts the numerous stocks that saw 900% or more gains in a single year during the dot-com bubble with the relatively modest gains of current tech stocks, suggesting a more measured market environment.

💡IPO Frenzy

An IPO (Initial Public Offering) frenzy refers to a period where numerous companies, even those with little or no revenue or business plan, go public and experience huge first-day price spikes. The script highlights the extreme IPO activity during the dot-com bubble, with multiple companies doubling in price on their first trading day, compared to the relatively calm IPO market today.

💡Profitability

Profitability refers to a company's ability to generate earnings and revenue. The script emphasizes that many dot-com bubble companies had little to no profitability, relying on hype and speculation. In contrast, current tech giants like Nvidia and Microsoft are generating substantial profits, indicating a more sustainable market environment.

💡Earnings Growth

Earnings growth refers to the rate at which a company's net income or profits increase over time. The script highlights that the stock price growth of companies like Nvidia is being driven by exceptional earnings growth, rather than irrational speculation, as was the case during the dot-com bubble.

💡Market Capitalization

Market capitalization, or market cap, is the total value of a company's outstanding shares. The script compares the market caps of companies like Cisco during the dot-com bubble to current tech giants like Nvidia, illustrating that today's valuations are more aligned with actual earnings and growth potential.

💡Customer Base

The customer base refers to the companies or entities that purchase a company's products or services. The script contrasts the dot-com bubble, where many tech companies relied on financially unstable or speculative customers, with today's tech giants, which have robust, well-capitalized customers like Google, Microsoft, and Tesla.

💡Technological Moat

A technological moat refers to a company's competitive advantage or barrier to entry based on its superior technology or intellectual property. The script suggests that companies like Nvidia have a significant technological lead in areas like parallel computing and AI hardware, making it difficult for competitors to catch up quickly.

💡Generative AI

Generative AI refers to artificial intelligence systems that can generate new data, such as text, images, or audio, based on the training data they have ingested. The script positions generative AI as the next phase of the internet, driving demand for companies like Nvidia that provide the necessary hardware infrastructure.

Highlights

Larry shares his experience as a broker during the dot-com bubble, living through the massive run-up and meltdown of tech stocks.

Larry discovered technical trading and developed a process using moving averages to manage risk and avoid getting caught in bubbles.

During the dot-com bubble, there were 20 stocks that went up 900% or more in a single year, compared to only 2 stocks today.

In 1999, there were 117 IPOs that doubled on their first day of trading, whereas Larry couldn't find a single one in 2023.

A fiber optics company called Corvis achieved a $27.6 billion market cap with no sales, highlighting the extreme speculation during the dot-com bubble.

Nvidia's net income in fiscal year 2024 was $29.7 billion, 11 times more than Cisco's best year in fiscal 2000 ($2.6 billion).

If Nvidia traded at Cisco's peak PE ratio of 196, Nvidia would have a $5.8 trillion market cap, nearly twice as big as Microsoft.

Nvidia's earnings per share grew 764% in the past 12 months, far outpacing its stock price increase of 230%.

The top 10 NASDAQ stocks today have 12 times higher revenue ($1.8 trillion) than the top 10 in 2000 ($148 billion), but the index price is only up 3.7x.

Unlike the dot-com era, today's leading companies like Microsoft, Apple, and Meta are highly profitable and stable customers for Nvidia's GPUs.

Entire countries and tech giants like Apple are committing to building AI infrastructure, providing a massive market for Nvidia.

Larry emphasizes the importance of analyzing data directly from company sources, as his team did by pulling financial reports from corporate websites.

Larry highlights the key differences between today's market and the dot-com bubble, including valuations, stock price moves, IPO activity, and customer quality.

While not saying stocks can't go down, Larry argues the data shows the current market does not resemble the speculative frenzy of the dot-com bubble.

Larry advises staying open-minded but relying on objective data and analysis rather than emotional reactions when assessing potential bubbles.

Transcripts

00:00

so no matter where we turn everybody

00:02

seems to think that we are in aom style

00:05

Tech bubble I think that this is a

00:07

bubble and I don't use that term lightly

00:09

we're now you know deeply into into

00:12

bubble territory we are living through

00:14

just a massive AI bubble So eventually

00:17

that suggests that there's going to be a

00:19

reckoning so what I decided to do for

00:21

this special episode of funding awesome

00:23

is bring in my good friend Larry

00:24

tentarelli and talk about whether we are

00:27

or are not really in an AI bubble the

00:30

stock market your time is valuable so

00:32

let's dive right into it Larry I think

00:34

the first question everyone is going to

00:35

have is what the heck qualifies you to

00:38

tell us if we're in a bubble right now

00:40

sure Hello Alex thank you for having me

00:42

on I started in the market in

00:46

1998 so I'm going on year number 26 now

00:49

I was a series 7 licens broker with

00:52

maril Lynch

00:54

1998 to 2003 so I actively traded right

00:59

through through the run up and then the

01:02

run down in the NASDAQ 100 back then so

01:06

I lived through the do bubble on a

01:10

professional basis and on a daily basis

01:13

I made a lot of money I lost a lot of

01:15

money but what I decided to do after the

01:19

NASDAQ melted down in

01:22

2201 I decided to really study what

01:25

happened and commit myself to be sure

01:28

that that didn't happen to me again

01:30

about last May is when I really started

01:33

to see the the bubble talk start to show

01:36

up on Twitter there was already talk it

01:38

was an AI bubble it was a tech bubble

01:41

I'd say about 90% of the posts that I

01:45

saw were very bearish I've got a

01:47

subscription-based website it's a

01:49

research website called bluechip

01:51

daily.com our subscribers include hedge

01:55

fund managers portfolio managers

01:58

research analysts Financial uh

02:01

journalist and Retail investors some of

02:04

our commentary has been featured on CNBC

02:08

Barons Bloomberg Reuters and a few other

02:12

sources I've been posting for 11 years

02:15

since January 2013 and and we've been

02:18

fortunate I've developed a follower base

02:20

of over 90,000 people and I said to

02:23

people I don't think that this is a

02:25

bubble whatsoever and I think that this

02:28

is going to continue a lot longer than

02:31

most people think and now here we are 10

02:34

months later and I think the same thing

02:37

I don't see a bubble whatsoever based on

02:40

my prior experience living through the

02:42

dotc bubble we did the research and

02:44

compiled the hard data and we're going

02:47

to compare all of the numbers from that

02:50

bubble in March 2000 versus all of the

02:53

numbers today and I think that when your

02:56

viewers get done with this video they'll

02:58

probably come to the same same

03:00

conclusion that there there's nothing

03:01

today that looks anything like the

03:04

bubble in 2000 so we have somebody who's

03:08

not only lived through it but invested

03:10

through it on the way up and way down

03:12

professionally who's seen all the

03:14

emotions tied up with the bubble of 2000

03:17

and who's pulled all the cold hard data

03:19

and compared it then versus now this

03:22

Nvidia Le AI bubble to see if there

03:25

really is a pattern here I'm super

03:27

excited for it let's dive right into it

03:29

here's what I see we're going to talk

03:31

about six reasons why we are not in a

03:35

tech bubble so first thing NASDAQ 100

03:38

1995 to 2000 over a fiveyear period it

03:42

went up

03:44

12x whoa yeah and we're wait till you

03:47

see these charts NASDAQ 100 this 5year

03:50

period 2018 to 2024 we're up 3x so 3x is

03:55

a good return but it's definitely not

03:58

12x number two valuations the NASDAQ

04:01

Composite PE in March 2000 was

04:06

175 the current NASDAQ PE today is 42 so

04:10

if we just look at valuations the

04:13

valuation today for the NASDAQ is 76%

04:17

lower than it was in 2000 we're going to

04:19

talk about some parabolic stocks we're

04:22

going to look at IPO activity and then

04:24

the big comparison that that I've heard

04:27

for over a year now is a lot of people

04:29

like to compare Nvidia to Cisco and they

04:32

say that you know Nvidia today is Cisco

04:35

back in 2000 nowhere near close we're

04:38

going to go through the math and then

04:39

we're going to talk about profitability

04:41

so I want to get started with these

04:43

charts I said that not only do I think

04:46

that this is not a bubble I said but I

04:49

think that this is probably going to go

04:50

on much longer than most people think

04:54

because these Cycles generally don't end

04:56

after a few months it's one thing to

04:58

have an opinion

05:00

but the numbers really tell the story so

05:03

this is a NASDAQ 100 chart

05:06

1995 to 2000 and if we take a look in

05:09

the bottom leftand corner we can see

05:11

1995

05:14

37996 the so we'll call it 400 for

05:17

simple math over five years we went from

05:21

400 to the peak

05:26

4,816 this was March 10th of 2000

05:30

so from 400 to 4,800 that's a

05:34

12x

05:36

run in five years and three months so

05:41

what I wanted to do is let's take a look

05:43

at today's NASDAQ 100 let's take the

05:47

same fiveyear look back period and see

05:51

how do we compare so this is 2018 to

05:55

2024 what I want to do just to be fair

05:58

is I want to take the very lowest number

06:01

that I can find so we can compare the

06:04

run so from

06:06

5800 to

06:08

17962 that's a 3X run now 3x is nice

06:14

over five years but keep in mind

06:18

95 to

06:20

2000 12x run so if huge difference yeah

06:25

so if if we were at the same level today

06:29

that the bubble Top in 2012 X the NASDAQ

06:33

100 would need to trade for 70,000 right

06:38

now yeah very different from where it is

06:41

today and Alex here's another

06:42

interesting thing if if we take a look

06:44

at the nasac 100 today so we're just

06:47

under

06:48

18,000 right now if we look at the peak

06:51

in

06:52

2021 we can see the the peak in 2021 was

06:58

16764 so so we are less than

07:02

8% above the highs in 2021 and I just

07:06

think it's difficult to call something a

07:10

bubble when it's only 8%

07:13

7% over the prior high does that make

07:16

sense that does and it's also important

07:18

to understand like how much time has

07:20

passed since that prior high for

07:22

earnings to catch up to these valuations

07:25

right so it took well over a year to

07:27

reach a new high and in that time these

07:29

companies have been growing they've been

07:31

adding more to their bottom line they've

07:33

been adding more customers right right

07:37

Apple's making more money Microsoft is

07:40

making more money all these companies

07:42

are are making more money as as the

07:45

prices going up on the NASDAQ 100 and if

07:47

we go back to that chart for a second

07:50

you can see from

07:51

[Music]

07:53

1999 to 2000 this was maybe 15 months

07:58

the NASDAQ 100 just it more than doubled

08:01

so if the prior Peak was 2500 you're up

08:05

at 4,800 I mean just imagine if if the

08:08

NASDAQ 100 today doubled in a 12- month

08:12

period that's that's what a bubble feels

08:14

like yeah yeah completely different

08:16

exactly right exactly right so the the

08:20

first Viewpoint 12x versus 3x we're

08:24

we're just really not anywhere close as

08:27

far as the actual move in the market

08:29

market so the second thing I want to

08:32

take a look at valuation so we're going

08:34

to compare NASDAQ Composite March

08:37

2000 versus the same thing NASDAQ

08:41

Composite today the NASDAQ Composite PE

08:45

in March 2000 was

08:48

175 the current NASDAQ PE today is 42 so

08:52

once again if we're talking apples to

08:55

apples we are

08:57

1/4 of the valuation in the NASDAQ

09:02

today versus at the top in 2000 so just

09:06

to give you an idea if if we were at the

09:09

same level the NASDAQ today would need

09:12

to be at 64,000 and right now it's at

09:15

16,000 the

09:17

NASDAQ 100 would need to be at least

09:21

four or five times higher than it is

09:22

today exactly right four times higher

09:25

four times higher than it is today right

09:27

and by valuations the PE

09:29

we're still another factor of four off

09:31

right right so whether we're going by

09:34

Price or by Price divided by earnings so

09:37

far we are nowhere near the.com bubble

09:40

levels of 2000 right yeah big difference

09:44

here now here's the the next thing the

09:46

next point that I wanted to look at

09:48

because everybody I think by now is

09:50

familiar with super micro smci it's gone

09:54

on a really strong run it's been a very

09:56

strong stock but Alex here's what I can

09:59

tell you in in 988 99 we had 20 super

10:05

micros and I'll tell you what I mean

10:07

this is from The New York Times and what

10:10

this shows this talks about

10:12

1999 Qualcomm Rose

10:16

2,619 per so it went

10:19

26x just in 1999 and and wait till you

10:23

see some of these charts that I'm going

10:26

to show you 12 other stocks went up at

10:29

least

10:31

1,000% and a further seven issues went

10:34

up at least 900% so you had 20 stocks

10:38

that went up

10:40

900% or more in one year that is massive

10:45

it's that's nuts are these stocks like

10:48

from all over the place or are these

10:50

like All Tech like what kind of stock

10:52

okay were all Tech and we'll take a look

10:54

but they were all Tech they were all

10:57

internet related so this is from CNET

11:01

and this shows if we look here top tech

11:03

stocks for1

11:05

1999 Qualcomm

11:08

26x broad Vision went,

11:11

1400% veras sign I think they might

11:14

still be around that that was up almost

11:17

1200% arm Holdings I wonder if that's

11:20

the same arm it is yeah arm's been

11:22

public like several times it's been

11:25

public then went private then got

11:26

acquired then public again okay yeah I

11:29

think it's the same arm yeah so that was

11:31

up

11:31

1,00% all of these stocks were Tech

11:36

related internet related some type of

11:39

Doom but keep in mind super micro today

11:43

that's the the home run hitter super

11:46

micro over the past year would barely

11:50

crack this top 10 lineup okay so what

11:54

about the other stocks like Nvidia and

11:56

every other stock that people are

11:58

associating with this so-called AI

12:00

bubble so in Nvidia over the past year

12:04

nvidia's up about

12:06

245 per so it wouldn't even be close to

12:09

any of these stocks that's an

12:11

interesting fact the comments that I see

12:12

a lot are this is an Nvidia Le bubble

12:15

and sort of what you're saying is NVIDIA

12:17

doesn't even meet the criteria to have

12:19

this be called a bubble if we're

12:20

comparing it to 2000 right Nvidia really

12:24

wouldn't even be a blip on the screen

12:27

back then so here here's what I mean by

12:29

parabolic stocks this is micro strategy

12:32

and this is the same micro strategy

12:34

that's still around right now this stock

12:37

went

12:39

45x in a 12-month period 45x so

12:44

400% in a 12-month period correct so if

12:46

you put $1,000 into it in the middle of

12:50

99 your investment was worth

12:53

$45,000 less than a year later that is

12:56

insane yeah if you put if you got lucky

12:59

and you put 10 grand into it you had

13:02

450,000 so we're we're talking about

13:05

what super micro going going 10x micro

13:08

strategy went 45x

13:11

Qualcomm went

13:13

4200 in 18 months so if we take a look

13:18

in 98 October it was trading at a $150

13:22

in change

13:24

$65. 39 at the peak so this is a 40

13:29

2 100% run your your 1,000 would turn

13:34

into 42,000 in 18 months and and Alex

13:37

I've got to tell you I was in these

13:39

stocks I used to I used to trade these

13:41

stocks and every single day just imagine

13:43

if you had a stock today that went up

13:47

4200 per in an 18month period I can't

13:51

imag yeah I'm I'm living in the wrong

13:53

time man yeah listen the here's the good

13:56

news the good news is that I had some

13:58

qualcom on the way up the bad news is I

14:01

also had some qualcom on the way down

14:04

and I thought it would be a good idea to

14:06

buy the dip now keep in mind I just

14:09

started in the business I think at the

14:12

time I was 29 years old and I didn't

14:15

really know anything about anything but

14:18

when I got started so I started right

14:20

about here everything just went up and

14:23

we were conditioned just by the dip just

14:25

by the dip because it's going to keep

14:27

going up so once things started to go

14:29

down we just kept buying the dip and we

14:32

bought it all the way down and and it

14:34

cost a lot of money which by the way is

14:36

still largely the message that most

14:39

retail investors get today so I'm glad

14:41

you're sharing that because that is

14:43

something that I think is really

14:45

powerful to hear right and the best way

14:48

to get better as an investor is to hear

14:50

that and understand that you need to

14:52

adjust your own strategy accordingly you

14:55

know so I'd love to hear a little bit

14:57

maybe for a couple minutes just just

14:59

what did you learn since then what are

15:00

you doing differently now big big

15:02

difference great question so I started

15:04

to trade here made a lot of money gave

15:06

it all back and and once you blow up

15:09

your trading account which is what I did

15:12

I had no more money left to trade so

15:15

this was back in 2002 so I I took a

15:19

break from trading for a couple of

15:21

months and then I sat down and and I

15:24

wanted to figure out just where it went

15:27

wrong because

15:29

it wasn't Alex it wasn't just me it

15:32

wasn't just the the people that I worked

15:35

with it was everyone maril Lynch Janice

15:39

had a fund called the Janice 20 fund

15:41

they might still have it right now maril

15:44

Lynch rolled out a product called the

15:45

focus 20 it was a u and it was just

15:49

basically 20 tech stocks you know norell

15:51

and Cisco and these things lost 8090

15:54

cents on the dollar so it wasn't just

15:57

new investors it was wasn't just the

15:59

retail investor so what I decided to do

16:02

I wanted to figure

16:04

out what could I do again so that I

16:07

would feel safe investing my money again

16:10

and not go through the same thing so I I

16:13

eventually discovered technical trading

16:16

I've got a technical process that I

16:18

follow that I've worked on for over the

16:20

past 22 years right now that I'm very

16:22

proficient with it I use moving averages

16:25

quite a bit and the key thing is no

16:27

matter how good a stock is if I'm

16:30

holding a stock and it closes below the

16:33

200 day moving average then I sell the

16:36

stock I can always buy it back if it

16:39

goes back up I looked at these charts

16:42

like Cisco and and JDs unase and Intel

16:45

and what I found is if the only thing

16:48

that I did was just sell those stocks

16:53

when they broke the 200 day moving

16:55

average and I didn't buy anything and I

16:57

didn't buy them I didn't try to found

16:59

the bottom I realized if I did that I

17:02

would have probably saved 50% 60% of my

17:06

capital and that's that's why I use

17:08

right now a 100% technical process sure

17:12

no that's that's super interesting yeah

17:14

so getting back to you know the dot

17:17

bubble versus the AI bubble let's talk

17:19

about some of these parabolic stocks

17:21

yeah let's take a look at today so we

17:23

had a quick one JDS unase Alex this was

17:26

just 3818 months I shouldn't even be

17:29

bringing this one to the table it only

17:31

went up 38 fold but here here's where we

17:34

are today so I took this information

17:37

from finviz and what I wanted to do to

17:40

to be because keep in mind I want to be

17:43

100% objective I don't want to cherry

17:45

pick I want to just take Apples to

17:47

Apples so I went into the screener and I

17:51

went for the loow hanging fruit so

17:53

there's

17:55

2,370 stocks in this fin viz database

17:59

over 1 billion market cap so I took

18:02

stocks that were $1

18:04

billion market cap or higher and I took

18:08

the top 20 performers so over the past

18:12

12 months here's the top 20 performers

18:15

so here's super micro up

18:19

1,7% over the trailing 12 months the

18:22

only stock that's ahead of that is a

18:25

very small biotechnology stock $1.4

18:29

billion market cap but keep in mind this