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Worried abut the “AI bubble,” and especially how it could affect Nvidia (NVDA stock)? Chip Stock Investors Nick and Kasey explain what’s really happening, the real reason big tech is spending so much on Nvidia, and a financial metric to follow the cycle. They conclude this video with a discussion on stocks that can act as an “NVDA stock hedge.”
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Content in this video is for general information or entertainment only and is not specific or individual investment advice. Forecasts and information presented may not develop as predicted and there is no guarantee any strategies presented will be successful. All investing involves risk, and you could lose some or all of your principal.
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Chapters:
00:00 Introduction to Hyperscalers and CapEx Spending
00:08 Understanding the NVIDIA Cycle
01:13 Cash Reserves and CapEx of Major Companies
02:21 Key Metrics for Evaluating Hyperscaler Spending
02:43 Detailed Analysis of Google and Meta
05:10 The Importance of CapEx to Operating Cash Flow
07:10 Quotes from Alphabet and Meta CFOs
11:46 The Perfect NVIDIA Stock Hedge
12:31 Future Outlook for AI and Semiconductor Markets
Nick and Kasey own shares of Nvidia, Alphabet and Meta.
Public Disclosure: A Bond Account is a self-directed brokerage account with Public Investing, member FINRA/SIPC. Deposits into this account are used to purchase 10 investment-grade and high-yield bonds. The [6.9%] yield is the average annualized yield to maturity (YTM) across all ten bonds in the Bond Account, before fees, as of [8/28/2024]. A bond’s yield is a function of its market price, which can fluctuate; therefore a bond’s YTM is “locked in” when the bond is purchased. Your yield at time of purchase may be different from the yield shown here. The “locked in” YTM is not guaranteed; you may receive less than the YTM of the bonds in the Bond Account if you sell any of the bonds before maturity, or if the issuer calls or defaults on the bond. Public Investing charges a markup on each bond trade. See our Fee Schedule. (https://public.com/disclosures/fee-schedule)
Bond Accounts are not recommendations of individual bonds or default allocations. The bonds in the Bond Account have not been selected based on your needs or risk profile. You should evaluate each bond before investing in a Bond Account. The bonds in your Bond Account will not be rebalanced and allocations will not be updated, except for Corporate Actions.
Fractional Bonds also carry additional risks including that they are only available on Public and cannot be transferred to other brokerages. Read more about the risks associated with fixed income (https://public.com/disclosures/fixed-income-disclosure) and fractional bonds (https://public.com/disclosures/apex-fractional-bond-disclosure). See Bond Account Disclosures (https://public.com/disclosures/bond-account) to learn more.
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35 comments
Also me: Buying Spotify and Palantir.
Two companies from Japan I like are SCREEN Holdings and Disco Corp. Have you looked into those?
Best regards from Austria
As I can not aford to buy all good companies
Thanks for a reply
If it’s top line you need to think about the phase in, the phase out of the old, and any cannibilization. If it’s not a distinct product you need to allocate the bundle.
COS if it’s hardware you need to estimate the internal costing efforts and the external cost to build.
With R&D you need time tracking tools, or software coding tracking tools and need to assume the front end has been set up. You need to pass that info and to your FP&A team and have them log it into their system of record to track cumulative investment.
You need an allocation methodology for direct S&M and G&A.
It just gets really complicated and you need a lot of experience and people to execute all of which no public company is ever going to disclose to you.
Much better to assess your original thesis without the investment and your new thesis in terms of revenue growth, margin expansion, operating leverage or operating cash flow.
For operating cash flow it might make sense to include the amortization of the hardware as an add back because if you aren’t using free cash flow you don’t consider the investment.
You only have to look at the power of the latest models to see how fast this field is evolving. With each more powerful, more reliable model that's released, there's a corresponding increase in applicability. I expect further significant advances over the coming months, with the upcoming launch of GPT-NEXT, followed by Orion, likely over the next 1-4 months and I do not see this process slowing down yet.
Basically, what I'm saying is that we're VERY early in the game yet. As these models becoming increasingly useful, their adoption will increase. Every more advanced model will come with more use cases and more businesses being forced to use the technology in order to remain competitive.
I can't see how this won't have a significant effect on the cyclical nature of the semiconductor industry.
Ps. Even your sponsors for videos are quality and thoughtfully selected.
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