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Nvidia

A Negative Month at these Levels Could Signal NVDA Down to $196We are at a point where NVDA is trading at a Macro Monthly Bearish ABCD PCZ and all the Oscillators are sitting in overbought zones. If NVDA sees a negative monthly candle at these levels, it is very likely that these Oscillators will begin to come down again and signal Potential Bearish Action ahead; if we get such a signal at these levels, then I would typically aim for it to go back down to the level of C of the ABCD as a Minimum Target; but given how high this is and how profitable even a 61.8% retrace would be, I will opt to target the 61.8% retrace instead down at $196.32 as it nicely fits into my typical 3:1 risk to reward requirement.
NASDAQ:NVDAShort
by RizeSenpai
8
SPX/ES - An Analysis Of The 'JPM Collar'Over the last two quarters, financial social media has cared a lot about the "JPM Collar," a series of very large options trades that JP Morgan uses in one of the funds it offers its clients. The theory for speculators is that the JPM collar will be used to constrict the market within a certain range. But as for how that plays out, it's hard for a trader to anticipate, especially amid the daily chop. The levels are on the chart and you can reference them yourself. Below is a print of monthly bars, which is easier to see since I have to compress the TradingView chart to make the bars work: If you're not familiar options, the general idea is this: These options blocks expire September 29 JPM will lose a lot of money if price is over 4,665 or starts to approach 4,665, especially if it happens right away JPM will lose a lot of money if price goes under 3,550, especially if it happens right away JPM will lose a lot of money if price goes under 4,215, especially if it happens right away But a nuance of being long 4,215 calls is that if price is significantly over 4,215 by September, they will make a lot of money on their calls. Geopolitical Risks Before we begin, I'll warn you, as I do in every post, that the geopolitical situation is tense. NATO is at war with the Russian Federation inside of Ukraine and the International Rules Based Order is always talking about "de-risking, but not decoupling" from Mainland China under President Xi Jinping. The risk for markets is, short of a situation where a tectonic/geothermal event surprises everyone and causes the crash of crashes, is that Xi gets up one night and throws away the Chinese Communist Party. Since Beijing business hours are New York night, you'll wake up to quite the gap down that will be hard to recover from, for the Chinese Communist Party and former Chairman Jiang Zemin and its cronies are guilty of the 24-year-long persecution and genocide against Falun Dafa's 100 million practitioners. The Call The most most notable thing about price action is as June closed, range equilibrium between the June high and the October low is exactly 4,000.00 points. Something else I stumbled upon when preparing for this post is that when comparing the Dow, Nasdaq, and SPX futures monthly bars, the three have completely converged. This is the first time since the **2022 top** that this has happened. You can see it on the weekly as well There used to be quite the delta, which allowed for stock picking and trading. If you ask me, what three memelines coming together all at once means is that the markets reached peak overbought, and genuine "overbought" isn't something you can see with an indicator. The daily shows this really only manifested in June. There are some problems with more uppy, as I explain in my calls below on the VIX, which needs to go up so that whales can go back to collecting free money selling volatility: VIX - The 72-Handle Prelude (But note that under the current conditions being summer and we're not that bearish right now, we may only see VIX 50) And the fact that the Nasdaq is just so far away from its trendline that going more parabolic is hard to believe. Nasdaq NQ - A Fundamental and Technical Warning Signal I don't normally call exact areas, but I put a white box with a dolphin because I think price is going there, and will do so fast, like, mid-August fast. That box means 3,778~. This means JPM will be green on out of the money calls, red on its own calls, and red on the 3,550 puts. But JPM doesn't lose money to begin with because they're hedged and will be compensating for the drawdown in other ways, like the alpha they'll generate from going big block long in the dumps under 4,000. The other advantage is it will trap bears who think it's finally the apocalypse they've long been awaiting for the ponzi to go to zero, and they'll buy puts and buy puts even though the iVol is insane from VIX being over 50. Once the craziness is done, the markets will recover, and whoever sold will probably by trapped. So, be careful out there. Wall Street's best laid plans can be blown to pieces in an hour by Heaven, for men are no better than mice in this boundless Cosmos.
CME_MINI:ES1!
by LordWrymouth
6
NVDA - MyMI Option Plays - CallsNVDA has outperformed outperformance in it's definition. This Titan has broken into a higher price range channel (top level of the orange channels) and is showing the potential to be headed back to $500. The most recent breakout in this week's trading sessions shows that there is still money on the sideline waiting to be injected in the markets and that we have much higher to go. This has taken us bullish in all of our current open trades. We are not currently in NVDA but we are patiently awaiting a re-entry that's a little more favorable for a longer-term call option and share hold.
NASDAQ:NVDALong
by MyMIWallet
UPDATE: Nvidia on track to its target of $562.33As mentioned before, there was a large Cup and Handle that formed on the price chart. We then had the price break up and out of the brim level, showing intense demand and buying. We also have 7>21>200 MA - Bullish and RSI>50 (Bull zone). The first anticipated target we set was a medium term one to $562.33 Nvidia continues to make higher highs and all time highs. And this will continue as long as people are feeling bullish and confident with the current AI, Machine learning, deep learning and quantum computing developments on the rise. ABOUT THE COMPANY Founding: Nvidia Corporation was founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem. Headquarters: The company is headquartered in Santa Clara, California, USA, in the heart of Silicon Valley. GPU Pioneer: Nvidia is credited with inventing the Graphics Processing Unit (GPU) in 1999, revolutionizing the gaming industry by allowing for more complex visuals and 3 Industries: While Nvidia is best known for its impact on video games, its GPUs are also used in areas like artificial intelligence, high performance computing, data centers, automotive technology, and more. GeForce: One of Nvidia's most well-known product lines is the GeForce series, which are GPUs designed for consumers, primarily for gaming and video editing. Tegra Processors: Nvidia also produces Tegra mobile processors for smartphones and tablets, as well as vehicle navigation and entertainment systems. AI & Deep Learning: Nvidia has made significant contributions to the fields of AI and deep learning, with their GPU architectures being used to accelerate these tasks.
NASDAQ:NVDALong
by Timonrosso
1
Nvidia -> Slowing Down And Now?Hello Traders and Investors , my name is Philip and today I will provide a free and educational multi-timeframe technical analysis of Nvidia 💪 Looking at the monthly timeframe you can see that after Nvidia retested previous support and the 0.786 fibonacci retracement at the $110 level, there was a solid rally towards the upside. Also on the weekly timeframe you can see that we had a juicy inverted head and shoulders reversal pattern and I pointed out all the reasons why I do expect the upcoming pump of roughly 120% towards the upside. Looking at the daily timeframe now you can see that Nvidia is a little bit overextended is also slowing down with momentum so there might be the possibility that we will see a short term correction after Nvidia actually breaks the current uptrend line. Keep in mind: Don't get caught up in short term moves and always look at the long term picture; building wealth is a marathon and not a quick sprint 📈 Thank you for watching and I will see you tomorrow! My previous analysis of this asset:
NASDAQ:NVDAShort
by basictradingtv
62
Why the Nasdaq may not capture the full growth potential of AIThe start of 2023 has marked the return of tech growth stocks alongside the surge of generative artificial intelligence (AI) and large language models (LLMs). The biggest tech companies in the world have benefitted from the buzz created by ChatGPT and rapidly rising enthusiasm around AI in general. Nvidia, a leading semiconductor company seen as one of the main AI beneficiaries, has advanced the most within the Nasdaq-100 and even joined the trillion-dollar market cap club just weeks ago. The year-to-date rally of ‘Big Tech’, led by Nvidia, has resulted in a strong return differential of 22.33%1 between the widely followed tech gauge (the Nasdaq-100) and the broad equity exposure (the S&P 500). The top 10 holdings in the Nasdaq-100 by contribution to return (CTR) have jointly posted 30.45% year-to-date, representing more than 82% of the total index return. This advance of the top Nasdaq-100 holdings, capitalising on the buzz around AI, is begging the question from investors whether allocation to the Nasdaq-100 already offers good exposure to the long-term investment potential associated with the AI megatrend. To answer this question, we have to take a step back and think of the concept of megatrends and benchmarks in the portfolio construction process. Benchmarks are usually viewed by investors as a core allocation, while thematic investing is being used as a return enhancement play that benefits from the evolution of various megatrends. In the case of the Nasdaq-100, we can point to several arguments why a thematic strategy focused on the AI theme might be a better option if an investor’s goal is to benefit from the long-term growth potential offered by AI. 1. The AI space represents a wide variety of areas that can achieve wider adoption and success at various points in the future. A targeted AI strategy can build exposure to the theme and its evolving trends through a diversified basket of more pure-play companies involved in various AI activities. In turn, the Nasdaq-100 will tap into the space only through a handful of companies that would offer a less comprehensive and less pure exposure to the theme. 2. A targeted AI strategy has the potential to capture the mega caps of tomorrow early on and with a meaningful weight within the portfolio. Investing in AI through the Nasdaq-100 might be seen by investors as a safe way to avoid losers and focus on more successful AI companies that made it into the benchmark. However, this approach does not allow investors to reap the return potential associated with exciting smaller companies early on. After all, the growth potential driving the returns in the tech space is highest for smaller and younger companies. Investing Tesla and Nvidia (the latest two companies that managed to hit a $1 trillion market cap) in them 3 months after they went public would have resulted in much higher annualised returns in comparison to returns after they joined the Nasdaq-100. In addition, it took both companies around 2-3 years to join the tech benchmark and, after they did, their starting weights were only 0.40%-0.50%. In contrast, thematic strategies might invest in companies shortly after their IPO (initial public offering) dates and might allocate a more meaningful weight to them. 3. A satellite thematic exposure can improve the risk-adjusted portfolio returns through increased diversification. The concept of diversification was first formalised by H. Markowitz as early as in 1952. However, in practice, it’s not feasible to hold all stocks in the investable universe and investors stick to broad benchmarks to build their market exposure. In this situation, thematic investing represents a novel way to split the universe of investable companies and identify promising opportunities aligned with megatrends shaping our future. Relatively low overlap of thematic strategies with broad benchmarks is what makes them particularly attractive for a satellite exposure. Trying to kill two birds with one stone (that is, building a core tech exposure and capturing the potential of the AI theme) by using the Nasdaq-100 could backfire. It could deteriorate diversification and risk-adjusted returns for two reasons: 1) Sticking just to AI companies within the Nasdaq-100 narrows down the return drivers associated with the AI megatrend; 2) Investors increase idiosyncratic risks in their portfolios associated with the biggest tech companies, most likely captured in some other portfolio allocations, for example, the S&P 500. Thematic strategies specifically focused on AI might represent a better option for investors seeking to benefit from the long-term growth potential associated with the megatrend in contrast to the theme exposure offered through the Nasdaq-100. When selecting the specific AI strategy it’s important to understand how each strategy captures the space and to align it with investor’s beliefs about the future development of the megatrend. Diversification benefits and potential return drivers associated with the theme are yet other important considerations that help to govern the strategy selection process. Sources 1 As of 27 June 2023. This material is prepared by WisdomTree and its affiliates and is not intended to be relied upon as a forecast, research or investment advice, and is not a recommendation, offer or solicitation to buy or sell any securities or to adopt any investment strategy. The opinions expressed are as of the date of production and may change as subsequent conditions vary. The information and opinions contained in this material are derived from proprietary and non-proprietary sources. As such, no warranty of accuracy or reliability is given and no responsibility arising in any other way for errors and omissions (including responsibility to any person by reason of negligence) is accepted by WisdomTree, nor any affiliate, nor any of their officers, employees or agents. Reliance upon information in this material is at the sole discretion of the reader. Past performance is not a reliable indicator of future performance.
NASDAQ:NDX
by aneekaguptaWTE
NVIDIA - Momentum but need to 'slow down' before continuationNVIDIA is a renowned technology company known for its cutting-edge advancements in areas like artificial intelligence, gaming, and high-performance computing. With a strong track record of innovation and a leading position in its industry, NVIDIA has established itself as a standout company. Since October 2022, NVIDIA shares have been on an upward trajectory, and during that time plenty of opportunities (that I all missed!) in buying at breakout points from a solid base and also from a pullback and B. Looking ahead, there is an anticipation of NVIDIA's stock continuing its upward momentum next week. The missed daily pivot on Friday suggests a potential continuation of buyer's control. Having said that, I do hope the bullish momentum come to a 'halt' when it testing the all time high at $440.27 and then start to make a solid pullback and perhaps form a base above the moving averages, before the stock makes new all time high throughout the year.
NASDAQ:NVDALong
by sufiansaid
6
What does real estate have to do with AI?To shed some light on the potential of artificial intelligence (AI), and discuss the role of the supporting infrastructure enabling this boom, we were delighted to leverage the expertise of Eric Rothman, Portfolio Manager, Real Estate Securities with CenterSquare. CenterSquare is a dedicated real estate investment manager, with around $14 billion under management, and Eric has been with the company for 17 years. Before we explore the Nvidia story and the relationship between AI, data centres, and ‘new economy real estate’, let’s define what that latter phrase means. New economy real estate is supporting technological advancements, like AI What is ‘new economy real estate’? Eric noted that there is so much beyond the traditional ‘4 foodgroups’ of real estate: 1) retail 2) office 3) residential 4) industrial When CenterSquare defines the ‘new economy real estate’ space, Eric noted that the larger components include data centres, cell phone towers, and warehouses dedicated to new economy logistics—things like ecommerce fulfillment. This is far from traditional, industrial real estate. Some of the smaller segments include life sciences, cold storage, and office space that is uniquely tailored to technology tenants, typically located in specific cities with focused pools of technology talent. Such cities might be Seattle, San Francisco or New York. These types of ‘real estate’, most notably data centres, are vital to support growing technologies like AI. The Nvidia story—$1 trillion to be spent? There has been a huge amount of excitement and discussion around Nvidia as the stock has enjoyed overnight success on the coattails of the AI boom. ‘$1 trillion’ is a big number (and a nice headline), but it’s very difficult to forecast where generative AI will take us. Some people say it is like inventing the wheel or the personal computer. This is a big claim, and only time will tell. If people are thinking about ‘data centre REITs’ as an investment, they have to understand that data centres just fulfil the provision of power, cooling, and connectivity. The data centre REITs do not actually own the computers. The tenants invest in the computers. One thing that is absolutely true, however, is that as an owner, you love to see the tenants putting money into the space that they are renting. Why? This makes it less likely they are going to leave. Therefore, a greater investment in AI technology and computing power may be a positive signal for the supporting real estate (like data centres). Eric’s conclusion, whether thinking about the impact of generative AI on data centre REITs or cell phone tower REITs, was that the move in share prices hasn’t reflected where we could be going yet. Connectivity and data centres will be vital components for artificial intelligence, but it’s not yet clear how or when investors are going to reflect that in the real estate prices. Eric noted that investors frequently forget about the buildings until later in a cycle or a trend. Greater computing power = greater energy consumption? Another aspect that we discussed was energy usage. Eric estimated that newer AI-focused semiconductors draw more power, not just a little bit more power but a step change in power consumption. A chart from the ‘Decadal Plan for Semiconductors’, a research report by Semiconductor Research Corporation allows us to compare compute energy to the world's energy production. A critical point to keep in mind is that ‘something has to give’; simply continuing to add computational capacity without thinking of efficiency or energy resources will eventually hit a wall. However, if history is any guide, we should expect that, as demand and investment in computational resources increases, there will be the potential for gains in efficiency, improved model design, and even different energy resources that may not yet exist today. Since many investors may be less familiar with cell phone towers, Eric made sure to mention just how strong of a business model he believes this to be. Now, it’s true that these REITs have not performed well in the past 18-months, but we are right in the middle of the current 5G rollout. Tenants have long leases, there is lots of demand, and there are even consumer price index (CPI) escalators that increase the rent to be collected. Conclusion: a different way to think about real estate It was great to be able to spend some time speaking with Eric and to learn about what’s happening both in the broader real estate market as well as in the more specific, new economy, ‘tech-focused’ market. The full discussion is accessible on behind the markets podcast This material is prepared by WisdomTree and its affiliates and is not intended to be relied upon as a forecast, research or investment advice, and is not a recommendation, offer or solicitation to buy or sell any securities or to adopt any investment strategy. The opinions expressed are as of the date of production and may change as subsequent conditions vary. The information and opinions contained in this material are derived from proprietary and non-proprietary sources. As such, no warranty of accuracy or reliability is given and no responsibility arising in any other way for errors and omissions (including responsibility to any person by reason of negligence) is accepted by WisdomTree, nor any affiliate, nor any of their officers, employees or agents. Reliance upon information in this material is at the sole discretion of the reader. Past performance is not a reliable indicator of future performance.
SPARKS:AIX
by aneekaguptaWTE
1
Oh no! A Classic WTF Animal is that pattern!I've detected the "WTF Animal" is that pattern in NVIDIA. Is it a dinosaur? A dog? An elephant? Something from out of this world? The "WTF Animal" is that pattern has been around for years now, but only now am I just sharing it. The animal I see is a dinosaur, but I also see how it could be a llama or a gazelle of sorts. Perhaps I need to draw it again. I don't have a position in NVIDIA at the moment, but it is a fascinating company to watch as AI takes the center stage in everything we do. I'll wait around for a trade, but for now I am neutral and just watching. Sometimes it's the best thing you can do: just watch. Sit on your hands. I've never made a good trade that is forced and not planned. Many of you can probably relate. Also, never trade because you think have to. The thing is, currently NVIDIA has all of these characteristics - people think they have to get in on the AI hype. That's not true. I must thank the "WTF Animal" is that pattern, because at the end of the day, the confusing chart and drawing, helps me pass time rather than rushing a trade! This pattern is usually detected when a chart looks so outlandish yet interesting, bullish but also bearish, confusing but also intriguing, that all one can see is a strange animal of sorts. Next time you think you're going to rush a trade, just remember the "WTF Animal" is that pattern. It'll save you from taking a trade you never wanted to take in the first place. Before placing that uncertain trade, first go ahead and draw the animal you see. But remember: this is not an easy pattern to spot.
NASDAQ:NVDA
by scheplick
18
Nvidia will be necessary to step out of the relatively high triaNvidia will be necessary to step out of the relatively high triangle This chart shows the weekly candle chart of Nvidia shares over the past year. The graph overlays the high and low points of November 2021 and October 2022, along with the corresponding golden section. As shown in the figure, the high points of Nvidia shares last week and this week were suppressed by 1.382 of the golden section in the figure! Nvidia's stock has accelerated since the middle of May 2023, and obviously the bull momentum has been released! In the future, it will be necessary to step out of the relatively high triangle and organize it before continuing to exert upward force!
NASDAQ:NVDA
by Think_More
Ninja Talks EP 22: 500 Followers!First off thanks for 500 followers, seems people like my Ninja Talks, so I'll keep um coming. In today's episode I want to talk about two types of anger traders go through in the market, one makes you win and one makes you lose. * Anger Numero Uno The first is pure rage, complete emotionality and it's what the majority of traders even seasoned pros know very well. In poker this would be called "tilting", in trading it's the same shiz it's just the catalyst appears different, they see cards we see candlesticks. Anyway back to the rage, quick story; many-o-moons ago I tilted and blew up my entire trading account (which was basically my entire net worth at the time), I screamed and rubbed my face so aggressively I dislocated my jaw! It's still not 100% aligned years later. This is the brutality of giving into the 1st anger, it takes no prisoners and will at any moment dash your emotional AND physical well being 1000mph at the wall until you learn to master it. * Which brings me to the second Anger. The second Anger, if verbalised, would sound something like "That's it! Let's fuc🤬ING go!", it's a "game on" mentality, not tilted but ready - you understand you're down, but your not giving up - you remain calm but awake. I'll give you an example, back in the day I had an MMA fight after not training for two years. Completely out of shape I took the fight on one week's notice lost 15lbs and jumped in there underweight, depleted, injured and weirdly stupidly confident. Round one begins and I'm tired after just 1 minute, the "gentlemen" across from me realising this proceeds to plod forward and tee off on my baldy head and skinny legs, but then something happened - my mind snapped out of it and basically said "Enough! Let's fu🤬ING go!" - I walked forward angry but calm saw his incoming kick grabbed it mid air, diverted it to my right and threw a rear high kick slapping the "gentleman's" temple "CRACKKKK!!!" and down he went, the fight was over just like that. Here's the thing... Understanding the difference between these two angers are a defining factor between winning and losing in the financial markets, yet very few learn from their outputs and instead point the finger outwardly at others, don't be that guy and instead learn to channel anger into determinative action. Make sense Ninja? Channeling rage (especially as a man) is one of our most potent potentialities, but it must be intentful and purposeful and preferably positive if we want to capture it's true essence. Meditate on this Ninja. I'll see you in the next ep! Follow for more.
NASDAQ:NVDAEducation
by NinjaTradingServices
2
Simple Pattern Targets for NVidiaWe had a head and shoulders that made a 1.5x measured move down, where it created an inverted HS that saw a 1x measured move up to resistance. Sitting at resistance now, if we don't soon see a push through it, we could move back down towards the support area marked on the chart. As long as that support area holds (or the neckline below it), we should see a visit back to our previous ATH, possibly a double-top with a slightly higher or slightly lower high. However, if DXY continues to remain below 105ish, it could see a new ATH instead.
NASDAQ:NVDA
by dudebruhwhoa
Mitigate Nvidia risk with a value-chain exposure to AIThe recent earnings announcement from Nvidia was historic. It’s not often that a firm shifts revenue guidance for an upcoming quarter from $7 billion to $11 billion. Nvidia’s total market capitalisation touched $1 trillion, something very few companies ever achieve1. An overzealous valuation? Professor Aswath Damodaran of New York University2, well known for his work on valuation, has said he cannot rationalise a $1 trillion valuation. Damodaran estimates Nvidia has a roughly 80% share of the artificial intelligence (AI) semiconductor market, which is around $25 billion today. Using bullish assumptions, which may not prove accurate, he looks to see growth in the AI semiconductor market to reach $350 billion within a decade. If Nvidia captured 100% future market share (a bold assumption), Damodaran’s valuation still resides about 20% below current prices. Nvidia is essentially a hardware company. One can see them try to ramp up software, but that is not the main driver. Other companies that achieved the $1 trillion market capitalisation level have software companies with network effects that draw vast numbers of end users into ecosystems. These software businesses have many ways to earn revenue from new products and services. Professor Damodaran’s valuations do not necessarily lead to share prices that immediately decline—but it may be difficult to keep the return momentum coming with equal fervor. Nvidia’s products do not operate in a vacuum WisdomTree spends a lot of time focusing on the AI megatrend. Nvidia’s products do not exist in a standalone fashion, as they are plugged into cabinets containing other hardware functioning in concert. If the AI semiconductor market grows, as many now expect, a lot of companies will benefit. Nvidia cannot, by itself, manufacture its semiconductors end-to-end. Taiwan Semiconductor Manufacturing Co. (TSMC) is responsible for this part of the puzzle. There is a whole semiconductor value chain, and each element captures a different-sized slice of the economic value pie. There are a range of companies associated with ‘generative AI’ over the period from the release of ChatGPT. Alphabet, Meta and Microsoft represent companies developing large language models (LLMs) to allow users to directly access generative AI. Meta was beaten down in 2022, due to disappointment with the firm’s metaverse efforts, but AI and cost cutting is helping them in 2023. Alphabet and Microsoft are at the centre of the generative AI battleground. Microsoft, so far, is winning on the cloud computing battle front with its Azure platform, whereas Alphabet’s Google is going to be very difficult to fend off in the internet search space. It’s interesting to compare Nvidia to Samsung and SK Hynix. Running AI models, especially large AI models, requires memory, and Samsung and SK Hynix are in the memory chip space. Excitement, at least in recent years, fluctuated in waves across the broad semiconductors market. Right now, during the explosion of generative AI, graphics processing units (GPUs), where Nvidia is the leader, are all the rage. Synopsys and TSMC represent notable, necessary value-chain plays on semiconductors. Nvidia chips cannot be created in a vacuum. Synopsys provides necessary electronic design automation capabilities, whereas TSMC is among the only companies with a manufacturing process advanced enough to fabricate Nvidia’s most advanced chips. Is AI over-hyped? The Gartner Hype cycle characterises one way to view new technologies. In the short term, excitement leads to money flows. Share prices and valuations benefit. At a certain point, a realisation sets in that true success, growth, and adoption takes time, so at this point there is usually a lot of selling and a tougher return environment. Finally, there is a recognition that pessimism is also not quite appropriate as the technology is still important and still being used, so growth rates and returns then tend to be more reasonable. AI is not any one single thing. Today we think of it as ChatGPT, LLMs or generative AI, but other disciplines and functionalities are still there, they just aren’t grabbing headlines in same way. ‘Generative AI’ and ‘foundation models’ might be nearing a peak of inflated expectations. Have you been excited about self-driving vehicles recently? No? Well, that could be part of the reason why ‘autonomous vehicles’ might be near the trough of disillusionment. Computer vision, which has been around for quite some time, is making its way up the so-called ‘slope of enlightenment’. The hype cycle is not an exact science. Any discipline on this graph could generate any sort of return, positive or negative, going forward. It’s simply a tool that helps us place all of these different topics on a broader continuum. The only thing we seem to know for sure is that all of the topics do not generate the same levels of excitement or pessimism all the time. Conclusion: it’s possible to mitigate single company risk by looking across the AI ecosystem The hype cycle illustration points out that the various applications of AI are at different points of adoption, excitement, and development. No one knows the future with certainty, but we believe there is growth occurring in all of these disciplines. The world is enthralled with generative AI now, but the world was similarly excited about autonomous vehicles a few years ago. Progress is occurring, even if we are not seeing it reflected in every headline. WisdomTree has a broad-based AI index to capture these AI trends. While Nvidia’s valuation is getting stretched, according to Professor Damodaran, WisdomTree’s AI index did not change much following the Nvidia surge. The entire ecosystem of AI defined by WisdomTree is not as beholden to the moves of any single company. AI has the potential to impact every industry which is why WisdomTree built a broad-based, ecosystem-oriented approach as opposed to concentrating on any single stock. Sources 1 Source: Bloomberg. 2 Source: Hough, Jack. “Nvidia Is the New Tesla, the ‘Dean of Valuation’ Says. It’s Time to Cash Out.” Barrons. May 31, 2023.
NASDAQ:NVDA
by aneekaguptaWTE
Peeking into Super SevensIn our previous paper , we outlined how investors can use CME's Micro S&P 500 Futures to hedge beta exposure and extract pure alpha. The paper referenced that the Super Sevens stocks (Amazon, Apple, Google, Meta, Microsoft, Nvidia, and Tesla) will continue to outperform the broader S&P 500 index. Not only do these stocks benefit from passive investing and ESG investing, these firms also have solid fundamentals to back up their gargantuan valuations. Each of the firms in the Super Sevens offer unique value drivers. Each firm is a market leader in its space and has demonstrated resilient earnings capacity and solid growth potential. Still, each also has its own set of risks. Notably, with the Super Sevens the value drivers outweigh the potential risks. AMAZON VALUE DRIVERS • Blistering profits from AWS offering with dominant market share of 33%. • Market dominance in e-commerce and solid supply chain network. • Successful new categories: Kindle (publishing), Alexa (voice assistant), and Prime (video streaming). POTENTIAL RISKS • Heavy reliance on AWS for profits. Slowing growth in AWS due to slowdown in corporate IT spending. • Low profit margins in e-commerce business. Slowing growth due to lower consumer spending. • Rising competition in cloud services and e-commerce. ANALYST PRICE TARGETS • Across 54 analysts providing a 12-month price target, 42 (77%) having a strong buy rating, 7 (13%) of them have a buy rating, 4 (7%) suggest a hold, while just 1 (2%) has a strong sell rating. • Average 12-month price target stands at 137, with a maximum of 220 and a minimum of 85. TECHNICAL SIGNALS • Technical signals point to momentum deeply in favour of Amazon shares. Oscillators point to buy and Moving averages point to a strong buy. • In aggregate, technical signals point to a buy. APPLE VALUE DRIVERS • Product category definers. Dominant and still growing iPhone demand. • Solid eco-system which is extremely hard to displace. • Control over both software and hardware enables specialized tailored improvements. • Sticky services such as App store, Apple Pay, and potentially Apple BNPL. POTENTIAL RISKS • Apple is heavily reliant on external fabricators exposing it to supply-chain bottlenecks. • Heavily dependent on iPhone sales. • Rising dependence on future growth in unexplored new categories. ANALYST PRICE TARGETS • Across 42 analysts providing a 12-month price target, 22 (52%) having a strong buy rating, 6 (14%) of them have a buy rating, 13 (31%) suggest a hold, while just 1 (2%) has a strong sell rating. • Average 12-month price target stands at 187, with a maximum of 220 and a minimum of 140. TECHNICAL SIGNALS • Technical signals point to solid momentum favouring long position in Apple shares. Oscillators point to buy and Moving averages point to a strong buy. • In aggregate, technical signals point to a strong buy despite Apple trading at near its all-time-high. GOOGLE VALUE DRIVERS • Google is the dominant search engine (86% market share). • Phenomenally successful and effective ad-targeting capabilities. • Heavy investments in future innovation enabling leapfrog into new verticals such as Android, Waymo (FSD & Maps). • Successful early acquisitions such as YouTube, Android, Applied Semantics & DoubleClick (AdSense), Nest (Home Automation). POTENTIAL RISKS • Massive reliance on ad revenues via search for profits. Slowing ad spend as firms cut back on spending. • Non-trivial dependence on cloud revenue for growth exposes them. Slowing cloud revenue growth due to lower corporate IT spending. • Failure to expand into new domains such as social media, wearable tech, and gaming. ANALYST PRICE TARGETS • Across 52 analysts providing a 12-month price target, 40 (77%) having a strong buy rating, 7 (13%) of them have a buy rating, while 5 (10%) suggest a hold. None of the analysts have a sell rating. • Average 12-month price target stands at 131, with a maximum of 190 and a minimum of 100. TECHNICAL SIGNALS • Technical signals point to decent momentum favouring Google shares but prices are at tiny risk of oscillating downwards. Oscillators point to neutral while Moving averages point to a strong buy. • In aggregate, technical signals point to a buy. META VALUE DRIVERS • Market monopoly on social media with high penetration across global markets on multiple platforms. • Flagship Facebook platform continues to see growth with 2.9 billion monthly active users (MAU). • Successful acquisitions have provided them with a wide suite of social media platforms – WhatsApp (2 billion MAU) and Instagram (2 billion MAU). • Successful developer tools (Graph, Hydra, React) have allowed them to build useful SDK (Software Development Kit). Potential sources of enterprise revenue from these. POTENTIAL RISKS • Increasing competition from TikTok. • Privacy concerns have a direct revenue impact e.g., Apple’s new privacy policies. • Falling market share for flagship Facebook in advanced economies. • High reliance on ad-sales. Slowing ad sales as firms cut back on spending. • Shaky bet on the Metaverse which is starting to fade. ANALYST PRICE TARGETS • Across 60 analysts providing a 12-month price target, 39 (65%) having a strong buy rating, 7 (12%) of them have a buy rating, 10 (17%) suggest a hold, 1 (2%) sell rating, and 3 (5%) has a strong sell rating. • Average 12-month price target stands at 281, with a maximum of 350 and a minimum of 100. TECHNICAL SIGNALS • Technical signals point to decent momentum favouring Meta shares. Oscillators signal neutral indicating a tiny risk of shares shedding gains while Moving averages point to a strong buy. • In aggregate, technical signals point to a buy. MICROSOFT VALUE DRIVERS • Sheer dominance of Windows (74% market share) & MS Office. • Deep roots in MS Office enables the firm to straddle across consumers & enterprise. • Diversified software offerings - cloud (Azure), gaming (Xbox), enterprise (Windows Server and SQL), search (Bing), productivity (Office), collaboration (Teams), and AI (through Open AI's ChatGPT). • Active M&A activity to acquire assets - LinkedIn, OpenAI, GitHub, Skype, Mojang, Nokia, Activision-Blizzard (Pending). • Besides Windows, Microsoft controls dev frameworks such as .Net further strengthening their grasp on SW dev. POTENTIAL RISKS • Limited success in hardware offerings unlike Apple. • Multiple major acquisitions have fizzled – Skype and Nokia. • Limited adoption in enterprise software. ANALYST PRICE TARGETS • Across 51 analysts providing a 12-month price target, 37 (73%) having a strong buy rating, 6 (12%) of them have a buy rating, 7 (14%) suggest a hold, while just 1 (2%) has a strong sell rating. • Average 12-month price target stands at 345, with a maximum of 450 and a minimum of 232. TECHNICAL SIGNALS • Technical signals point to decent momentum favouring Microsoft shares. Oscillators are at neutral while Moving averages signal a strong buy. • In aggregate, technical signals point to a strong buy. NVIDIA VALUE DRIVERS • Market dominance in discrete GPU’s (80%). • Early mover in AI hardware which gives them a lead over the competition. • Raytracing, DLSS, Neural Network cores. • Nvidia’s CUDA is the primary choice for training ML models. • Market dominance in high-growth data centre graphics hardware (95%) and super-computing hardware. • Successful enterprise partnerships – car manufacturers using Nvidia software. • Emerging tech such as AI and VR require more graphics intensive processing driving demand for Nvidia’s products. POTENTIAL RISKS • Hardware-focused business model exposes it to supply-chain risks and bottlenecks. • Extremely high P/E of 225 dependent upon expectations of future growth in AI. • Losing market share in discrete GPUs and enterprise GPUs to AMD and Intel. ANALYST PRICE TARGETS • Across 50 analysts providing a 12-month price target, 36 (72%) having a strong buy rating, 6 (12%) of them have a buy rating, 7 (14%) suggest a hold, while just 1 (2%) has a sell rating. • Average 12-month price target stands at 444, with a maximum of 600 and a minimum of 175. TECHNICAL SIGNALS • Technical signals point to solid momentum favouring long position Nvidia shares. Oscillators point to buy and Moving averages point to a strong buy. • In aggregate, technical signals point to a strong buy despite Nvidia relentless and unrivalled price ascent. TESLA VALUE DRIVERS • Early mover in EV’s with dominant market share in US (62%). • Dedicated and loyal customer base. • Vertical integration of EV value chain allows it to reduce reliance on external suppliers. • Early investment in large factories that will allow them to scale output more efficiently. • Huge and monetizable supercharger network by opening it up to other EV makers. • Subscription model for software enables revenue generation after product sale. • Long term vision has allowed Tesla to create entirely new products such as supercharger network, battery banks, home power backup and solar roofs. • Tesla’s planned Robotaxi and entry into car insurance can be hugely disruptive. POTENTIAL RISKS • Increasing competition from automobile majors as well as Chinese EV firms. • Tesla’s brand is deeply entangled with Musk’s reputation. • Dependence on government incentives to make Tesla affordable. • Continued access to battery metal minerals. • Ongoing and unresolved production scaling challenges. ANALYST PRICE TARGETS • Across 46 analysts providing a 12-month price target, 18 (39%) having a strong buy rating, 5 (11%) of them have a buy rating, 17 (37%) suggest a hold, 1 (2%) has a sell rating, and a 5 (11%) hold a strong sell rating. • Average 12-month price target stands at 201, with a maximum of 335 and a minimum of 71. TECHNICAL SIGNALS • Technical signals point to solid momentum favouring Tesla. Oscillators point to buy and Moving averages point to a strong buy. • In aggregate, technical signals point to a strong buy. SUMMARY The Super Sevens are well positioned to continue outperforming the wider market. As mentioned in our previous paper , investors can use a beta hedge to nullify the effects of the broader market (S&P 500) and extract pure alpha from the growth of the Super Sevens. MARKET DATA CME Real-time Market Data helps identify trading set-ups and express market views better. If you have futures in your trading portfolio, you can check out on CME Group data plans available that suit your trading needs www.tradingview.com DISCLAIMER This case study is for educational purposes only and does not constitute investment recommendations or advice. Nor are they used to promote any specific products, or services. Trading or investment ideas cited here are for illustration only, as an integral part of a case study to demonstrate the fundamental concepts in risk management or trading under the market scenarios being discussed. Please read the FULL DISCLAIMER the link to which is provided in our profile description.
NASDAQ:AAPLLong
by mintdotfinance
35
The environmental impact of AI: a case studyIn our previous blog, Will AI workloads consume all the world’s energy?, we looked at the relationship between increasing processing power and an increase in energy demand, and what this means for artificial intelligence (AI) from an environmental standpoint. In this latest blog, we aim to further illuminate this discussion with a case study of the world’s biggest large language model (LLM), BLOOM. Case study on environmental impact: BLOOM An accurate estimate of the environmental impact of an LLM being run is far from a simple exercise. One must understand, first, that there is a general ‘model life cycle.’ Broadly, the model life cycle could be thought of as three phases1: Inference: This is the phase when a given model is said to be ‘up-and-running.’ If one is thinking of Google’s machine translation system, for example, inference is happening when the system is providing translations for users. The energy usage for any single request is small, but if the overall system is processing 100 billion words per day, the overall energy usage could still be quite large. Training: This is the phase when the parameters of a model have been set and the system is exposed to data from which it is able to learn such that outputs in the inference phase are judged to be ‘accurate’. There are cases where the greenhouse gas emissions impact for training large, cutting-edge models can be comparable to the lifetime emissions of a car. Model development: This is the phase when developers and researchers are seeking to build the model and will tend to experiment with all sorts of different options. It is easier to measure the impact of training a finished model that becomes public, as opposed to seeking to measure the impact of the research and development process, which might have included many different paths prior to getting to the finished model that the public actually sees. Therefore, the BLOOM case study focuses on the impact from training the model. BLOOM is trained on 1.6 terabytes of data in 46 natural languages and 13 programming languages. Note, at the time of the study, Nvidia did not disclose the carbon intensity of this specific chip, so the researchers needed to compile data from a close approximate equivalent setup. It’s an important detail to keep in mind, in that an accurate depiction of the carbon impact of training a single model requires a lot of information and, if certain data along the way is not disclosed, there must be more and more estimates and approximations (which will impact the final data). If AI workloads are always increasing, does that mean carbon emissions are also always increasing2? Considering all data centres, data transmission networks, and connected devices, it is estimated that there were about 700 million tonnes of carbon dioxide equivalent in 2020, roughly 1.4% of global emissions. About two-thirds of the emissions came from operational energy use. Even if 1.4% is not yet a significant number relative to the world’s total, growth in this area can be fast. Currently, it is not possible to know exactly how much of this 700 million tonne total comes directly from AI and machine learning. One possible assumption to make, to come to a figure, is that AI and machine learning workloads were occurring almost entirely in hyperscale data centres. These specific data centres contributed roughly 0.1% to 0.2% of greenhouse gas emissions. Some of the world’s largest firms directly disclose certain statistics to show that they are environmentally conscious. Meta Platforms represents a case in point. If we consider its specific activities: Overall data centre energy use was increasing 40% per year from 2016. Overall training activity in machine learning was growing roughly 150% per year. Overall inference activity was growing 105% per year. But Meta Platforms’ overall greenhouse gas emissions footprint was down 90% from 2016 due to its renewable energy purchases. The bottom line is, if companies just increased their compute usage to develop, train and run models—increasing these activities all the time—then it would make sense to surmise that their greenhouse gas emissions would always be rising. However, the world’s biggest companies want to be seen as ‘environmentally conscious’, and they frequently buy renewable energy and even carbon credits. This makes the total picture less clear; whilst there is more AI and it may be more energy intensive in certain respects, if more and more of the energy is coming from renewable sources, then the environmental impact may not increase at anywhere near the same rate. Conclusion—a fruitful area for ongoing analysis One of the interesting areas for future analysis will be to gauge the impact of internet search with generative AI versus the current, more standard search process. There are estimates that the carbon footprint of generative AI search could be four or five times higher, but looking solely at this one datapoint could be misleading. For instance, if generative AI search actually saves time or reduces the overall number of searches, in the long run, more efficient generative AI search may help the picture more than it hurts3. Just as we are currently learning how and where generative AI will help businesses, we are constantly learning more about the environmental impacts. Sources 1 Source: Kaack et al. “Aligning artificial intelligence with climate change mitigation.” Nature Climate Change. Volume 12, June 2022. 2 Source: Kaack et al., June 2022. 3 Source: Saenko, Kate. “Is generative AI bad for the environment? A computer scientist explains the carbon footprint of ChatGPT and its cousins.” The Conversation. 23 May 2023.
SPARKS:AIX
by aneekaguptaWTE
Harvesting Alpha with Beta HedgingImagine this. Dark skies, earth tremors and thunder roars. Shelter is top priority. Size matters in a crisis. When the tsunami strikes and lightning splits the sky, investors shudder in fear; But the super seven stand tall, shielding investors from the fury. Dramatic metaphors aside, we truly live in unprecedented times. Risk lurks everywhere. List is endless. Unstable geopolitics. Sticky inflation. Recession expectations. Unprecedented deepening of yield curve inversion. Unfinished regional banking crisis. Weak manufacturing. Tightening financial conditions. Extremely divisive global politics, to just name a few. Despite severe headwinds, US equity markets are roaring. YTD, S&P is up +15% and Nasdaq is up +32%. At the start of 2023, the consensus was for US equities to be in doldrums dragged down by recession. Halfway through the year, markets are at the cusp of one of the best first half for US equity markets in twenty years. This is among the narrowest and top-heavy rally ever. Only a sliver of stocks - precisely seven of them - defines this optimism. This paper will refer to these as the Super Sevens. These are the biggest members of the S&P 500 index. Super Sevens are Amazon, Apple, Google, Meta, Microsoft, Nvidia, and Tesla. This paper argues that the Super Sevens will deliver above market returns in the short term as investors seek safe haven from a vast array of macro risks. The paper articulates a case study to demonstrate the use of beta hedging to extract alpha from holding long positions in Super Sevens and hedging them against sharp reversals using CME Micro E-Mini S&P 500 index futures ("CME Micro S&P 500 Futures"). THE RISE AND RISE OF SUPER SEVENS Super Sevens have an outsized impact as S&P 500 is a market weighted index. Merely five of these seven form 25% of the S&P 500 market capitalisation. At $2.9 trillion in market capitalisation, Apple is greater than all of UK’s top 100 listed companies put together. If that were not enough, Apple's market capitalisation alone is greater than the aggregate market capitalisation of all the firms in the Russell 2000 index. Nvidia has been soaring on hopes of AI driven productivity gains. On blow out revenue guidance, it has rallied $640 billion in market cap YTD. That increment alone is larger than the combined market cap of JP Morgan & Bank of America the two largest banks in the US. The heatmap summarises analyst targets & technical signals on pathway for prices ahead: In part 2 of this paper, Mint will cover the detailed analyst price forecasts, technical signals and summary narratives covering value drives and intrinsic risk factors. WHAT DRIVES INVESTOR CONCENTRATION INTO THE SUPER SEVENS? As reported in the Financial Times last week, two broad market trends appear to have fed into this investor concentration. First, Passive investing. When funds merely deliver the performance of an index by replicating its composition, the higher the index weights, the more these passive funds buy into these names. Second, ESG investing. Rising push towards ESG has forced investment into tech and away from carbon-heavy sectors such as energy. Collectively, this has resulted in all types of investors – active, passive, momentum, ESG- all going after the same names. Question is, what happens now? Will the broader market catch up with the Super Sevens? Or will the Super Sevens suffer a sharp pullback? That depends on the broader US economy. Will it have a hard landing, soft landing, or no landing at all? Given market expectations of (a) resilient earnings capacity, and (b) solid growth potential among Super Sevens, we expect that in the near to mid-term the Super Sevens will continue to outperform the broader market. In ordinary times, investors could have simply established long positions in Super Sevens and wait to reap their harvests. However, we live in unprecedented times. WE LIVE IN TRULY UNPRECEDENTED TIMES Risks abound but no signs of it in equity markets. Historically, geopolitical instability, tightening financial conditions, and a deeply inverted curve could have led to crushing returns in the US equity markets. Not this time though. Peak concentration As mentioned earlier, bullishness in equity markets can be vastly attributed to just the Super Sevens. These seven have delivered crushing returns rising between 40% and 192% YTD. The S&P 500 index is market cap weighted. Super Sevens represent the largest companies in the index by market cap and their stellar performance has an outsized impact on the index. Is this a bull run or a bear market clouded by over optimism among Super Sevens? Deeply inverted yield curve In simple words, it costs far more to borrow for the near term (2 year) relative to the borrowing for long term (10-year). The US Treasury yield curves have been inverted for more than a year now. The difference between the 2-Year and 10-Year treasuries is at its widest level since the early 1980s. Inversion in yield curve has historically been a credible signal of recession ahead. When bonds with near term duration yield higher rates than those with longer-dated expiries, this precedes trouble in the economy. Recession. What recession? This period might go into the record books for the most long-awaited recession that is yet to come. For the last 12 months, experts have been calling for recession to show up in 3 months. While manufacturing sector seems feeble, labour market remains solid. Corporate balance sheets are robust. Consumer finances and consumer confidence are in good health. The VIX remains sanguine while the only fear indicator that appears unsettled is the MOVE index which indicates volatility in the bond markets. After having spiked earlier in the year, the MOVE is starting to soften as well. BETA HEDGING FOR PURE ALPHA In times of turbulence, risk management is not an afterthought but a necessity. Hedge delivers the edge. When there are ample arguments to be made for bullish and bearish markets, taking a directional position can be precarious. This paper posits Super Sevens holdings be hedged with CME Micro S&P 500 Futures. Hedging single stocks is nuanced. The stocks and the index do not always move in tandem. A given stock may be more volatile or less volatile relative to the benchmark. Beta is the sensitivity of the stock price relative to a benchmark. Beta is computed from daily returns over a defined historical period. Stocks with high Beta move a lot more than the underlying index. Stocks that move narrowly relative to its underlying benchmark exhibits low Beta. Beta hedging involves adjusting the notional value of a stock price based on its beta. Using beta-adjusted notional, hedging then involves taking an offsetting position in an index derivative contract to match the notional value. TradingView publishes beta values computed based on daily returns over the last 12 months. The following table illustrates the beta-adjusted notional for the Super Sevens based on the last traded prices as of close of market on June 16th. Beta hedging using CME Micro S&P 500 Futures enables investors to precisely scale their portfolio exposures to the index. A small contract size enables investors to manage risks with finer granularity. CME allows conversion of micro futures into a classic E-mini futures position, and vice versa. Round the clock liquidity combined with tight spreads and sizeable open interest across the two front contract months, investors can enter and exit the market at ease. BETA-HEDGED TRADE SET UP In unprecedented times like today, markets may continue to rally or come crashing. To harness pure alpha, this paper posits a spread with long positions in Super Sevens hedged by a short position in CME Micro S&P 500 Futures expiring in September 2023. This trade set-up gains when (a) Super Sevens rise faster than the S&P 500, or (b) Super Sevens suffers drop in value but falls lesser relative to S&P 500, or (c) Super Sevens gain while S&P 500 falls. This trade setup loses when (a) Super Seven falls faster than S&P 500, or (b) S&P 500 rises faster than Super Seven, or (c) S&P 500 rises while Super Sevens pullback Each CME Micro S&P 500 Futures has a multiplier of USD 5. The September contract settled on June 16th at 4453.75 implying a notional value of USD 22,269 (4453.75 * USD 5). Effective beta hedge requires that notional of the hedging trade is equivalent to the beta-adjusted notional value of single stock. Given the beta-adjusted notional value of USD 2,561 for single shares in Super Sevens and the notional value for each lot of CME Micro S&P 500 Futures at USD 22,269, the spread trade requires: a. A long position in 26 shares each across all the Super Sevens translating to a beta-adjusted notional of USD 66,576. b. Hedged by a short position with 3 lots of CME Micro S&P 500 Futures which provides a notional exposure of USD 66,807. The following table illustrates the hypothetical P&L of this spread trade under various scenarios: MARKET DATA CME Real-time Market Data helps identify trading set-ups and express market views better. If you have futures in your trading portfolio, you can check out on CME Group data plans available that suit your trading needs www.tradingview.com DISCLAIMER This case study is for educational purposes only and does not constitute investment recommendations or advice. Nor are they used to promote any specific products, or services. Trading or investment ideas cited here are for illustration only, as an integral part of a case study to demonstrate the fundamental concepts in risk management or trading under the market scenarios being discussed. Please read the FULL DISCLAIMER the link to which is provided in our profile description.
NASDAQ:AAPLLong
by mintdotfinance
3