BREAKING: Three NEW DEALS Will Send Nvidia Stock SOARING SOON
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- Опубликовано: 22 апр 2024
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Nvidia Stock News (NVDA)
China is currently doing everything in its power to not be dependent on foreign chip manufacturers or even chip equipment manufacturers. The country is trying to create the technology itself, especially after the sanctions the U.S. put on China last October, as well as the new regulations that forbid American chip companies from selling to China.
Disclaimer: This is not licensed financial advice, we are just sharing our thoughts for your fun and entertainment.
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Overall, 51% of traders think this year would favor stocks, mutual funds, and other equity-based investments, despite Treasury yields and other safer cash-like investments paying big. I’m looking for opportunities in the market that could fetch me $1m ahead of retirement by 2025
Although the stock market is continuing rallying, there is a risk of reversals in the key indexes, sectors, and top stocks in particular. I advise you to consult a broker or financial counselor for advice.
Having an investment adviser is the best way to go about the market right now, especially for near retirees, I've been in touch with a coach for awhile now mostly cause I lack the depth knowledge and mental fortitude to deal with these recurring market conditions, I nettd over $220K during this dip, that made it clear there's more to the market that we avg joes don't know.
Please can you leave the information of your investment advisor here? I'm in dire need of one.
There are a handful of experts in the field. I've experimented with a few over the past years, but I've stuck with ‘’ Jennifer Lea Jenson” for about five aiyears now, and her performance has been consistently impressive. She’s quite known in her field, look-her up.
Thank you! I checked out Alicia Ann Jordan's credentials on her website and it seems quite good! Hopefully, she's taking in fresh applicants because I sent her an email.
Just remember everyone that NVIDIA's Q1 earnings are less then 4 weeks away and they should be BLOWOUT! NVIDIA has guided the market that they should be $24 Billion which means that they'll probably be closer to $26 Billion. On top of that the Gross Margins will be 76% with Net Margins of 55%, which means that PROFIT for Q1 should be over $13 Billion! (as an example, AMD's net profit is 10%). Every single chip that NVIDIA is currently manufactured is already sold (for the next year) so the money pipeline is just pouring in. ON TOP OF THAT, it is very likely that a split will happen soon.
Excellent points!
So what will the price range for NVDA stock be you think?
@@Rapha187 I wish I had a crystal ball, but the forward growth should be excellent. It appears that NVIDIA has brushed off Friday's 10% drop and we have almost made up all of that in the last two days. My price target for EOY is $1,200.
@@jeffrose5622 thanks for replying bro, I really hope so
If it splits, how quickly will the split value likely rise back to current value?
Buy and hold
So basically we're going to keep this economy going for as long as we can until it literally hits the ground and starts combusting in to flames, this will not be a depression this will be a nightmare financially for everyone because right now when the inflation spikes up like a rocket and the dollar detaches itself from normal levels we're going to be just like Zimbabwe or Germany with wheelbarrows of money for bread. I personally feel like we have maybe 4 to 5 years of somewhat economic transactions with money and debt but after 2030 I think that's when everything will falter and hit the skids. I would buy Bitcoin and buy hard assets like gold /silver as a store of value while also actively trading...The only wild card for us investors is to actively engage the market by trading, we always over complicate things when we speculate. It's not about guessing the market's next move; it's about playing it smart and steady during trading...managed to grow a nest egg of around 100k to a decent 432k in the space of a few months... I'm especially grateful to Kelvin Hurdle, whose deep expertise and traditional trading acumen have been invaluable in this challenging, ever-evolving financial landscape....
He mostly interacts on Telegrams, using the user-name..
@KelvinHurdle..
Bitcoin's role as a store of value and its potential for future growth make it an attractive investment option. BTC trading can be a thrilling way to participate in this digital asset's journey.
Been looking for someone trustworthy to listen to for a while, and I'm delighted I came across your comment
He delves into technical, fundamental, and sentiment analysis, providing a holistic view of the market.
It will split this year!!!!! 3or4 quarter!!!🎉🎉🎉Especially if it goes over 1000 DOLLARS!!!
Kramer called the Bounce......😂😂😂😂😂
Simple minds will go straight to supply! If you’re an owner of NVDA…you’re an owner of a product that is limited by supply! Demand is going to allow you to grow in wealth due to the limit?
OK when your thumbnail picture is JIM KRAMER, it immediately tells me......"Don't watch this video"! THANKS!
Japan replaces China.... and more. I figure $1000 for earnings... and revalue after that. All these "deals" can only lead to increased revenue and increased margins. $1200 is quite doable over the next 12 months. But thats just my opinion.
I agree 'cranky'!
PLTR 🌙🚀
nvda $8000 by2030
LETS GO!!!!!!!
😮 ACHR, SABR, PERI …
I like keep it simple, Altria tobacco 4life
Jim always calls it wrong
Why does everyone on Yahoo Finance pronounce NVDIA incorrectly?
Well, why do you spell it incorrectly?
@@rdpaik good point
I pronounce it.... B E N F R A N K L I N
@@crankybuzzard6867 -- Internet winner!! Yes!!!
If you want more viewership, remove Jim Kramer
Strong BUY. Still early innings. NVIDIA is the dominant leader in AI and the preferred technology partner globally. Even w new competition on the horizon, NVIDIA is far ahead of the competition. 85% market share. 76% margin. Unrivaled demand for new Blackwell chip. Demand far exceeds production for Blackwell through to 2025 and beyond. No competitor has anything close to Blackwell. And forward P/E is about 33 (cheap for a high growth stock). Buy this stock and wait. You will be rewarded
Problem is that NVDA is addicted to the datacenter, their mobile offerings are terrible. Inference needs to happen at the edge (mobile) and training will not have the same amount of demand as time goes on. NVDA is a major bet on aggregation of resources (compute) but this is cyclical as we have seen dozens of major shifts in this industry. Remember when Citrix aggregated desktops with VDI and then it imploded because VDI has a problem with latency? AI Inference in the datacenter has the same problem with latency. AAPL and Samsung are the best buys for AI now that we are transitioning from training to inference. Cheers and good luck!
@@ZTK-RC You make some interesting points. I do think data centres are where it's going. And that is not mutually exclusive to mobile. And you are right and wrong about training. I agree that there will be less demand for some areas of training like LLM -as it will be done. But AI has many areas to train on. Infinite. Have we cure every disease yet? Have we solved energy? What about food and agriculture? Space exploration. Biotech. It's endless. AI is the genie out of the bottle. It's like Bill Gates saying 1981--640K of memory should be enough for anybody. He underestimated the future. I respect your opinion tho.
@@ZTK-RC Due to your edits--my reply was auto deleted. i'm too lazy to retype it all again. You make some smart comments. But I think you are in correct. I would love to debate it w you. There is no way i would say AAPL is a best buy for AI. The key to AI is data--and Apple does not have enough. This is why they bailed on autonomous driving tech. They lacked the data that Tesla had and the vast accumulation of corner cases. If you don't have the data--you can not lead. Simple as that. Apple will have to buy it or license data. They have deep pockets --but they are far behind in the AI race. Again, I respect your opinion. I appreciate your smart commentary
@@popcornl8208 Great post!
@@ZTK-RC IDK, I've been working in ML since the mid 70's (speech recognition algorithm development, including hardware and embedded software), and on to biomedical signal and image processing, mission critical and hard realtime embedded classifiers. I'm still working on several healthcare applications. There were over 33,000 ML papers published last year. The largest deep networks (even as I never believed in backprop, especially for deeper networks) now: "The largest models typically have 100 billion parameters, requiring 200 gigabytes to load, which places them outside the range of most consumer electronics." When I started out in speech recognition, I collected my own in house database of > 18,000 utterances, which was larger than the first public domain database for speech (TI-20). Datasets have continuously grown in size ever since. Later, I worked with the MIT-BIH arrythmia database (> 112,000 beats from 47 patients) -- larger than TI-20, but tiny compared to datasets that have come later, and what we surely have now that are proprietary. The ability of deep networks (no matter how they're trained) to absorb data, and the amount of data yet to be collected, is very likely to keep growing for quite some time yet. Now I'm no fan of deep networks and backprop -- I think they're inefficient. I published the first large margin / soft margin perceptron training algorithm, used in a constructive network of hidden units based on a combination of radial basis functions and hyperplanes (more efficient in terms of their classification power), along with what be called a version of a mixture of experts model, and an algorithm very close to AdaBoost (prior to Freund and Schapire, as brilliant as those guys are). Those are techniques I believe to be more efficient in both training and classification, but may very well not scale up to the demands of the datasets that exist now (I don't consider that as an issue since I still work with much smaller, more esoteric datasets). In any case saying that we're out of the woods in terms of training, and now just in the realm of running these networks seems to me kinda like that famous quote from the guy who ran the patent office in 1899, saying that "Everything that can be invented has been invented already". It just has never seemed, even in the "AI Winter", that we were done yet in terms of new algorithms and architectures. Surely running these incredibly ginormous networks won't be done on smartphones for some time. Even if they're done "at the edge", who do you think will be providing the hardware and software development environment? At the moment, it seems that any company that can make use of AI/ML is scrambling to do so. Time to market would seem to be way more important than "saving a few bucks" by going with hardware that probably comes with a development environment that hasn't been hammered on by > 4.8 million developers (Nvidia's community of developers), nor the information sharing and the software ecosystem that has sprung up around Nvidia's hardware and the CUDA environment. Look at what happened to all the 8 and 16 bit microprocessor architectures that every semiconductor company had felt they needed to design and manufacture. They all disappeared into the smokey haze of microprocessor history, except for the (really crufty) Intel architecture, with Motorola's 68000 design hanging on as very much an also ran, and TI's superior TMS9900 (both the 68000 and 9900 very much inspired by the elegant PDP11 instruction set) never getting much traction at all. What happens is that once a particular architecture gains a foothold, for whatever reason (like IBM choosing Intel for their first PC, even though IBM also had a more laboratory oriented "personal computer" that did use the 68000), everyone converges on to that particular part, and the leader then has the resources to design the next version, and support the software development environment better than their competitors. (Now Apple did also use the 68000 in their first Macintosh's -- I bought one specifically for that reason, their processors were never out on the open market, unless I'm mistaken, nor are any of their other processors since then.) I later worked for Lucent / Agere, where the StarCore owed it's heritage to the 68000 too, but again, just a blip on the radar screen of microprocessor history. The convergence effect can also be seen in OS's. IBM chooses Microsoft DOS for the IBM PC OS , and we're saddled with a cruddy OS and it's descendants for decades, while Unix and then Linux struggle for a remote second place, despite being clearly more robust and efficient (my understanding is that Apple's OS is a Linux derivative, but I couldn't say for sure -- it sure looks that way at their command line, though). Anyway, sorry for going on about what I call "the convergence effect", but IMHO, the design of new ML network architectures is probably not slowing down, nor the size of datasets and network sizes. That, and the need for companies to bring out new products and services in the most timely fashion to be competitive, and the lack of computing power in a smartphone (I can't say about the class of machines being used for "edge computing", though) -- all combined with what I call "The Convergence Effect", would seem to have Nvidia in the leadership position for at least the next five years, but probably a decade or more. And again, being the leader means revenue to support R&D to stay ahead of the pack. The fact is that Jensen Huang and others surely at Nvidia were smart enough to recognize the potential impact of AlexNet back in 2012, and they so rightly deserve the just rewards from that vision that they are seeing today (along with all of us hodling on to our shares of NVDA until such time as the next revolution in AI/ML comes to pass). #:')
Its obvious your a promoter or just your belly up on the stock and have an interest to see others to buy it so you can sell your BAG
NOT HAPPENING !...😂
Everyone is saying 2024 nvidia to 1000 2000 even 3000+ it will be none of it but under 600 for sure.
It will go up more next month
Putting Jim Cramer on the thumbnail automatically disqualifies this video. Have a nice day.
😆😆
I'm taking all my money our of Nvidia now that Jim Crammer has told us to buy Nvidia he's jinxed the stock and it will crash horribly tomorrow.
What are you talking about? Nvidia stock will crash tomorrow? You wish! Are you a short seller of $NVDA? Good luck to you!
everytime jim cramer got excited to a particular stock, it will usually drop temporarily, I guess bcs of institution manipulation. Overall, I'm still bullish on NVIDIA for at least 2-3 years 4:24 4:24
Do it. Please. Sell all your nvidia stocks so it goes down again and I buy more
Everytime Jim Cramer got excited to a particular stock, usually there's short term drop, most likely because of institution's manipulation to buy low. I'm still bullish on Nvidia
it indeed happened 😁
y'all can say what you want about NVIDIA going higher. But the daily chart says breakdown. nvda will continue lower. let the bleeding continue.. news on stocks is always priced in and months ahead of the real world. I don't care what is coming out. the here and now daytrading technicals says nvda tank. TANK! TANK!!! TANK!!!!!! git some.. get those 4090's down to 100 bucks. true value.
Don’t believe the hype.
NVDA will crash soon.