Will Mark Zuckerberg Become The Wealthiest Person In The World It's gone 12 months or so since Meta Platforms shareholders reached their breaking point in Q4'22 as the Tech giant's financial results in those times were following an increasingly questionable rebrand, from Facebook into Meta.
In October, 2022 Altimeter Capital Chairman and CEO Brad Gerstner said in an open letter to the Company that Meta has too many employees and is moving too slowly to maintain investor confidence.
A Meta shareholder wrote an open letter to CEO Mark Zuckerberg, saying he's basically "not happy". The investor criticized the brand's $100 billion-plus Metaverse experiment, saying such wild investments "into an unknown future are disproportionate and appalling even by Silicon Valley standards."
Investor recommended a plan to bring a "Mojo" back to the company.
👉 It included cutting personnel costs by 20% and limiting the company's costly investment in Metaverse technology to no more than $5 billion a year.
👉 Further, Meta must restore the trust of investors, employees and the tech community to attract, inspire and retain the best people in the world, - Gerstner wrote in the letter.
👉 In short, Meta needs to get fit and focused.
The letter was the latest sign that Meta investors were beginning to significantly express doubts about the company's financial results. Meta shares were down more than 61% in 2022.
Meta changed its company name to better focus on virtual reality hardware and software, and is spending $10 billion a year on the technology.
“However, people were confused about what the Metaverse even means,” Gerstner wrote.
"If the company had invested $1-2 billion a year in this project, this confusion might not even be an issue."
Ultimately, Gerstner says, Meta has too many people and spends too much on capital expenditures. If Meta could control those costs, it could double its free cash flow and improve its share price, he said.
He said a 20 percent cut in employee costs would return Meta to the level of staffing it had last year, and said the company can't spend money like before because the cost of capital and interest rates have risen recently.
“We believe the recommendations outlined above will result in a leaner, more productive and more focused company — a company that regains its confidence and momentum,” Gerstner resulted his letter.
I have to say also, there were a lot of important questions to Meta activity abroad the United States, in addition to the dismal financial performance in 2022. Saying this, I mean that the activities of Meta Platforms Inc, including Facebook and Instagram products, were recognized as extremist and were banned in the Russian Federation under the local court decision, and Meta stocks were uncompromisingly delisted from both Russian trading boards, well known as Moscow Stock Exchange MOEX:MOEX and Saint Petersburg Stock Exchange MOEX:SPBE .
In conclusion the rehabilitation path was the one and only - Meta Gotta Have a Mojo!
NOWADAYS
In nowadays Meta Platforms Inc. NASDAQ:META is the # 1 over the all S&P500 SP:SPX components with 205 percent yearly performance in this time, as Meta stocks were not simply gained, but tripled the price over the past 12 months.
Meta reported Q3'23 earnings after the closing bell October 25, 2023 that beat analysts' revenue and profit estimates.
The beat was driven by a continued rebound in Meta's advertising business following a sharp slowdown throughout 2022. Meta's guidance on its 2023 and 2024 expenses also hit the sweet spot for investors, as it signaled that it can balance its "year of efficiency" cost cutting efforts while it continues to invest in the Metaverse and Artificial intelligence (AI).
According to Forbes Real-Time Billionaire Index Mark Zuckerberg is the 6th richest person in the world today with its $120.0 wealth as of today while Tesla CEO Elon Musk is yet number one in the world with $241.1B wealth.
Key facts about Mark Zuckerberg
* Mark Zuckerberg started Facebook at Harvard in 2004 at the age of 19 for students to match names with photos of classmates.
* He took Facebook public in May 2012; he now owns about 13% of the company's stock, according to the company's 2023 proxy statement.
* Facebook changed its name to Meta Platforms in November 2021 in a sign it was shifting the company's focus to the metaverse.
* In December 2015, Zuckerberg and his wife, Priscilla Chan, pledged to give away 99% of their Meta stake over their lifetimes.
* Mark Zuckerberg born in White Plains, New York in 1984, and in this time 39-years old Mark Zuckerberg is the youngest one over the top 30 richest persons in the world.
In conclusion, Will Mark Zuckerberg become the wealthiest person in the world!?
Perhaps, Yes. He can.
The main technical graph undoubtedly says Meta Inc stocks NASDAQ:META are on the runway to triple the price once again.
=========
Dedicated to my beloved newborn son, Mark 💖
AI
PALANTIR Sell signal at the top of the 15-month Channel Up.Palantir (PLTR) gave us a solid buy signal 3 months ago (June 24, see chart below) as it respected the recurring bottom sequences within the 15-month Channel Up:
Right now the price has been consolidating after a direct hit at the top (Higher Highs trend-line) of the Channel Up. The 1D RSI got overbought and started pulling-back on a standard Bearish Divergence, a formation which three time within this pattern turned-out to be a solid sell signal.
The dashed Channel Up gives us a short-term Target on its bottom, which is where the 1D MA50 (blue trend-line) is trading at and is the short-term Support. That is our Target currently (Target 1 = 34.50).
If and only if, we close a 1D candle below the 1D MA50, we will open a new sell, as it will be a bearish break-out signal. In that case, we will target a potential near contact with the 1D MA200 (orange trend-line), which is the long-term Support and where the remarkable buy entries of August 05 and January 31 were provided (Target 2 = 29.50).
Keep in mind that the most optimal buy entry for the long-term (since May 2023) has been given by the 1D RSI and more specifically when it hits its Support Zone. We will continue to place buy long-term buys accordingly.
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Day 2 AI Analyzing my trading ideasThe following chart is not very different from the first except I wanted to focus on a smaller timeframe initially I wanted to focus on the 4h timeframe but the big picture wouldn’t be as clear. I started off sending a picture of the 4h chart to AI and asking if it recognized any patterns, of which it mentioned 3 patterns a Head and shoulders, a rising wedge, and a symmetrical triangle. The rising wedge we talked about yesterday. So I decided to go for the head and shoulders (in this case an inverted HAS) after drawing the HAS on the chart myself I sent a new picture of it to AI and asked what it saw (the yellow price lines were added before posting to highlight the possible target AI suggested. Below is the description I got, keep in mind AI is not to be used as a trading tool by any means, but I like to play with the fact that it takes my emotions away from trading. Disclaimer again, I’m no professional and this is not trading advice. This is what AI said about my chart.
Let’s break down the analysis again with this correct interpretation.
### Key Observations:
1. **Inverse Head and Shoulders Formation**:
- The **left shoulder** forms around early June, the **head** dips lower in mid-July, and the **right shoulder** forms in September.
- This pattern suggests that after a downtrend, there’s potential for a bullish reversal.
2. **Neckline**:
- The **dotted green line** (around $65,000) appears to act as the **neckline** of the pattern. This is a key resistance level that, once broken, would confirm the bullish reversal.
### Possible Outcomes:
- **Bullish Scenario**:
- If the price breaks **above the neckline** (around $65,000), it would confirm the Inverse Head and Shoulders pattern, signaling a potential upward movement.
- To estimate the potential target, measure the distance between the **head** and the **neckline**. The head dips to around **$50,000**, and the neckline is at **$65,000**, which gives a difference of **$15,000**.
- Adding that difference to the breakout point at **$65,000** suggests a potential upward target of around **$80,000**.
- **Bearish Scenario**:
- If the price fails to break the neckline and instead reverses back down, the key support levels to watch would be the **right shoulder level**, which is around **$55,000**, and the **$50,000** level at the head.
- A breakdown below these levels could invalidate the bullish reversal, leading to further downside pressure.
### Conclusion:
The **Inverse Head and Shoulders** is a classic bullish reversal pattern. If the price breaks above the **$65,000 neckline**, we could see Bitcoin target **$80,000** based on the pattern's projected move. However, failure to break the neckline would mean the pattern is not yet confirmed, and we might see the price retest support around **$55,000** or **$50,000**.
The TradingView Show: Interest Rates and AI with TradeStationJoin us for our newest episode with David Russell , Head of Market Strategy at TradeStation . We’ll dive into the current market landscape, covering all of the following topics for traders:
1. Market Trends: We’ll provide detailed insights into major stocks and bullish market trends, focusing on META, NVDA, and the evolving landscape of Chinese stocks. Discover how hedge fund managers are navigating these markets and uncover other significant movements you might be missing.
2. Index Review and Interest Rates: Our analysis will dive into macro trends affecting the SPX and NDX, exploring the importance of major indexes. We’ll discuss how rising interest rates are influencing market behavior and the broader economic implications for investors.
3. Commodities: Get the latest updates on oil, especially in light of recent production cuts that are impacting prices globally. We’ll also discuss gold and silver prices, examining why gold has achieved an all-time high while silver remains undervalued and what that means for future trends.
4. Cryptocurrency: Take a closer look at Bitcoin’s recent performance. We’ll explore whether it is on the verge of forming a significant new trend and what factors are driving its volatility in today’s market.
5. Housing Market: Analyze current trends in the housing market and what lies ahead, especially as they relate to rising interest rates, advancements in AI, and productivity improvements. This segment will provide essential insights for anyone interested in real estate investments.
And much more! We encourage you to ask questions and share your feedback in the comments. Now, some important links for you to explore and read:
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Pegasystems (PEGA) AnalysisCompany Overview: Pegasystems NASDAQ:PEGA is strategically positioned to leverage the increasing demand for AI-powered customer service solutions. By incorporating advanced technologies such as natural language processing and chatbots, PEGA is enhancing user experiences and streamlining customer interactions.
Key Catalysts:
AI-Powered Solutions: The rising interest in AI technologies provides a significant opportunity for Pegasystems to grow its client base and expand its offerings in customer service automation.
Leadership Insights: CEO Alan Trefler emphasizes the company's commitment to innovation, which is expected to attract new clients and deepen existing relationships, driving revenue growth.
Financial Goals: Pegasystems aims to achieve the "Rule of 40" by 2024, balancing revenue growth with free cash flow margin. This metric is crucial for appealing to investors looking for sustainable growth and profitability.
Investment Outlook: Bullish Outlook: We are bullish on Pegasystems above $61.00-$62.00, reflecting confidence in its strategic initiatives and market potential. Upside Potential: Our target for PEGA is set at $84.00-$86.00, driven by expected growth in AI solutions and the successful implementation of financial goals.
🚀 PEGA—Pioneering AI in Customer Service. #AI #CustomerExperience #Pegasystems
Day 1 AI analyzing my trading ideasMy first published chart, I had an idea to send my chart to AI and ask what it sees, the support lines were added to the chart a while ago by myself but still do represent good support. I’m sure a lot of people have noticed this triangle forming on the daily, so this is my first test to see if AI can see anything no one else can.
Disclaimer this is not trading advice and I am not a trading expert, just someone who loves to look at charts and read people’s ideas and thoughts. Below is the AI evaluation.
This image appears to be a Bitcoin (BTC) to US Dollar (USD) chart, most likely from a trading platform such as TradingView. Here are some key details and observations:
1. **Chart Pattern (Symmetrical Triangle)**:
- The purple triangle drawn on the chart is a common technical analysis pattern known as a "symmetrical triangle." It is formed by drawing trendlines connecting higher lows and lower highs, creating a converging triangle. This usually indicates a period of consolidation where the price is moving within a range before a breakout in either direction.
- The points labeled A, B, C, and D highlight the highs and lows within the triangle, suggesting the completion of a cycle within the pattern. Traders often wait for a breakout (either upward or downward) from this triangle pattern to enter positions.
2. **Price Levels**:
- The current price is shown as **$64,669.33**, which is a drop of **1.48%** from the previous level.
- There are significant support and resistance levels drawn with horizontal lines:
- **$48,333.61** and **$45,806.41** are key levels below the current price, likely indicating potential support zones if the price falls.
- There is also a more distant level at **$31,282.06**, which could represent a strong support zone if the price breaks downwards significantly.
3. **Timeframe**:
- The timeframe is set to **1D**, meaning that each candlestick on the chart represents one day of trading activity.
- The date axis indicates the price history from around early 2024, with the pattern extending into July 2024 and beyond.
4. **Volume**:
- The volume bars at the bottom of the chart show the level of trading activity. Higher green bars indicate higher buying interest, while red bars would indicate selling pressure (though none seem to be visible in this image).
In summary, this chart shows Bitcoin trading within a symmetrical triangle, suggesting that traders are watching for a potential breakout in either direction. A breakout above the upper trendline could lead to further price increases, while a breakdown below the lower trendline could signal a decline.
TAO Bittensor, my revenge chart after my defeat.Project description:
Bittensor ( GETTEX:TAO ) is a decentralized machine learning protocol that incentivizes users to contribute computing power and train AI models on the blockchain. By leveraging a decentralized infrastructure, Bittensor aims to create an open, permissionless network for AI development.
Type of project:
Decentralized AI and machine learning protocol.
Is it under a block?:
Yes, Bittensor operates on its own blockchain, utilizing a decentralized network to facilitate AI model training and computation. GETTEX:TAO is used as the native token to reward participants who contribute to the network.
Latest update or news:
As of July 2024, Bittensor introduced Neuron Staking, allowing participants to stake their GETTEX:TAO tokens on AI models they believe will perform well, further aligning incentives within the network and driving improvements in model quality.
Narrative:
Decentralized AI, machine learning, blockchain infrastructure, and incentive-based computation.
Why is it a good investment?
Institutional Backers and Angel Investors:
1. Multicoin Capital:
Multicoin Capital has backed Bittensor due to its innovative approach to decentralized AI, seeing it as a key player in the future of decentralized machine learning networks.
Outlier Ventures:
Outlier Ventures, a venture capital firm known for supporting Web3 and AI projects, has invested in Bittensor, recognizing the importance of decentralized AI infrastructure.
KR1:
KR1, a European blockchain investment firm, has also supported Bittensor’s vision for open, permissionless AI model training on the blockchain, seeing it as a critical step toward decentralized AI systems.
2. Angel Investors:
Trent McConaghy (Founder of Ocean Protocol):
While not directly invested, McConaghy has expressed strong support for decentralized AI projects like Bittensor that utilize blockchain technology to democratize access to AI resources and data.
Sandeep Nailwal (Co-founder of Polygon):
Nailwal, known for supporting decentralized infrastructure projects, has voiced interest in Bittensor’s approach to incentivizing AI model training through decentralized computation, though no confirmed direct investment.
Futuristic Use Case:
Decentralized machine learning model training:
Bittensor enables the training of AI models in a decentralized manner, allowing participants to contribute computational power and data, which is crucial for building AI models that are not dependent on centralized entities.
Incentivized AI development:
Bittensor’s tokenomics incentivize participants to stake GETTEX:TAO tokens on high-performing AI models, aligning incentives across the network and driving continuous improvements in the quality of AI outputs.
AI model sharing across industries:
Industries such as healthcare, finance, and research can benefit from Bittensor’s decentralized AI models, which allow for the sharing and optimization of AI models across sectors in a transparent and permissionless way.
Secure and transparent AI computation:
By leveraging blockchain’s security and transparency, Bittensor ensures that AI models and computations are performed in a trustless environment, reducing risks associated with centralized AI model training.
Why will it make a significant amount of profits?
Unique competitive edge:
Bittensor stands out from traditional AI platforms by decentralizing the training and development of machine learning models. This creates an open and permissionless ecosystem where anyone can contribute to AI development and be rewarded, giving it a unique position in the AI market.
Growing demand for decentralized AI models:
As the AI industry grows, the need for decentralized infrastructure that allows for transparent, secure, and scalable AI model training will increase. Bittensor’s approach of incentivizing contributors with GETTEX:TAO tokens will attract more participants and developers, driving demand for the token.
Neuron Staking and incentivization model:
Bittensor’s Neuron Staking system allows participants to earn rewards by staking GETTEX:TAO on AI models they believe will succeed. This creates a sustainable revenue model while encouraging continuous innovation in AI development.
Revenue from AI model training and computation:
Bittensor generates revenue by offering decentralized AI model training and computation services. As more businesses and developers use its infrastructure for AI model optimization, the value of GETTEX:TAO tokens will increase due to the growing demand for decentralized computation.
AIT Protocol; One Stop Shop under TAO Bittensor!Project description:
AIT Protocol is a decentralized AI infrastructure platform designed to enhance the development and deployment of AI-powered applications by leveraging blockchain technology for secure data sharing, decentralized computation, and AI-driven services.
Type of project:
AI infrastructure and decentralized computation protocol.
Is it under a block?:
Yes, AIT Protocol operates on Ethereum and other compatible blockchains, utilizing smart contracts to manage AI-driven services and secure data exchange across decentralized networks.
Latest update or news:
As of August 2024, AIT Protocol launched its AI-as-a-Service (AIaaS) feature, enabling developers to access decentralized AI models and computation resources for building and scaling AI-powered applications on the blockchain.
Narrative:
AI infrastructure, decentralized computation, AI-driven services, and blockchain-based AI applications.
Why is it a good investment?
1. Institutional Backers and Angel Investors:
Pantera Capital:
Pantera Capital has invested in AIT Protocol, recognizing its potential to bridge the gap between AI and blockchain, focusing on decentralized AI applications and services.
Framework Ventures:
Framework Ventures has also backed AIT Protocol due to its unique AI infrastructure approach, enabling decentralized computation and AI services in a secure and scalable manner.
Outlier Ventures:
Known for supporting Web3 and AI projects, Outlier Ventures has invested in AIT Protocol to push the boundaries of decentralized AI and its integration with blockchain ecosystems.
2. Angel Investors:
Ben Goertzel (Founder of SingularityNET):
While not directly confirmed, Goertzel has shown interest in projects like AIT Protocol that focus on decentralizing AI and integrating it with blockchain for secure and scalable solutions.
Chris Dixon (a16z Crypto):
Dixon, a key figure in supporting blockchain and AI convergence, has expressed support for the type of decentralized AI services that AIT Protocol aims to provide, though no direct investment has been confirmed.
Futuristic Use Case:
Decentralized AI applications:
AIT Protocol enables developers to create AI-powered dApps that leverage decentralized computation and data storage, allowing for more secure and scalable AI models that can be accessed by a global user base.
AI-driven services for enterprises:
Enterprises can use AIT Protocol’s AI-as-a-Service (AIaaS) to integrate decentralized AI models into their business operations, providing automated insights, decision-making, and process optimization while maintaining data security.
Cross-chain AI integration:
AIT Protocol is designed to operate across multiple blockchains, enabling AI models to interact with different ecosystems and provide AI-driven services across various decentralized platforms and dApps.
Decentralized data sharing for AI training:
By leveraging blockchain technology, AIT Protocol allows secure, transparent data sharing for training AI models, solving critical issues related to data privacy and security in AI development.
Why will it make a significant amount of profits?
Unique competitive edge:
AIT Protocol’s focus on decentralized AI infrastructure gives it a competitive edge in both the blockchain and AI sectors, providing scalable AI solutions that are not tied to centralized entities, thus appealing to developers, enterprises, and AI enthusiasts alike.
Growing demand for AI services:
As the demand for AI-driven services continues to grow across industries, AIT Protocol’s decentralized AI infrastructure will attract more developers and enterprises looking for secure, scalable AI solutions, driving demand for NYSE:AIT tokens.
Revenue from AI-as-a-Service (AIaaS):
AIT Protocol’s AIaaS model creates a sustainable revenue stream by enabling developers and businesses to access decentralized AI models and computational power for a fee, which will drive the utility and value of the NYSE:AIT token.
Integration with Web3 and decentralized ecosystems:
As more decentralized applications and platforms seek to integrate AI capabilities, AIT Protocol will play a critical role in providing AI services across Web3 ecosystems, making it a key infrastructure player in the growing blockchain and AI intersection.
Tesla (TSLA) AnalysisCompany Overview: Tesla NASDAQ:TSLA continues to lead the electric vehicle (EV) market, and its ambitious leap into humanoid robotics with the Optimus robot could open up massive new revenue streams. CEO Elon Musk projects this venture could unlock a $200 trillion opportunity, particularly in household and manufacturing applications.
Key Catalysts:
Optimus Robot: Visionary investors like Cathie Wood of ARK Invest estimate a $12 trillion market for humanoid robotics, where Tesla aims to be at the forefront, revolutionizing industries.
Full Self-Driving (FSD): Tesla's advanced FSD technology could be licensed to other automakers, creating new revenue channels. Musk’s long-term goal of launching an autonomous ride-hailing business or robotaxi fleet offers additional upside potential, which could reshape the automotive and transportation landscape.
Expanding Market Potential: Beyond EVs, Tesla's expansion into AI-driven robotics and autonomous vehicles places it at the intersection of multiple high-growth markets.
Investment Outlook: Bullish Outlook: We are bullish on Tesla above $193.00-$195.00, signaling strong confidence in its continued leadership in both the EV and emerging robotics sectors. Upside Potential: Our target for TSLA is $360.00-$370.00, driven by the potential commercialization of humanoid robots and further advancements in autonomous driving technology.
⚡️ TSLA—Driving the Future with Innovation in EVs, AI, and Robotics. #EVs #AI #AutonomousDriving
SMCI DROPSuper Micro Computer (SMCI) is currently under scrutiny as it faces multiple probes and class-action lawsuits. These legal issues primarily stem from allegations of accounting manipulation and concerns over corporate governance. The investigation has been sparked by a report from Hindenburg Research, which raised serious questions about the company's financial reporting, including accusations of overstating sales, understating expenses, and engaging in "round-tripping" practices to inflate revenues
Meta Platforms (NASDAQ: $META) Breaks Out to New HighsMeta Platforms (NASDAQ: NASDAQ:META ) has been making waves in both the tech and stock markets as the company continues its growth trajectory with strong fundamentals and new product launches. Following a successful Connect 2024 conference, Meta's stock surged to an all-time high, driven by bullish investor sentiment around its cutting-edge innovations in AI, augmented reality (AR), and smart eyewear.
The company, led by CEO Mark Zuckerberg, is not only deepening its collaboration with EssilorLuxottica, the maker of Ray-Ban smart glasses, but it has also unveiled an array of groundbreaking products that are set to shape the future of digital interaction.
Meta’s AI & AR Push
Meta (NASDAQ: NASDAQ:META ) has been in the spotlight recently due to its heavy investments in artificial intelligence and augmented reality. The company's partnership with EssilorLuxottica for developing smart eyewear is set to evolve with potential symbolic investments from Meta, signaling their commitment to a long-term relationship. Mark Zuckerberg expressed confidence that EssilorLuxottica could transition from being the world’s premier glasses company to becoming a significant player in the technology space.
The demand for the Ray-Ban Meta smart glasses has far surpassed expectations, with sales reportedly three to five times stronger than anticipated. This surge in demand highlights Meta’s growing dominance in wearable tech and AR, especially as it continues to expand its product lineup with the unveiling of **Orion AR glasses** at the Connect 2024 event.
In addition to its hardware innovations, Meta (NASDAQ: NASDAQ:META ) is leveraging its AI infrastructure to enhance its core social media businesses—Facebook and Instagram. The introduction of AI-driven features, including partnerships with celebrities like Awkwafina, John Cena, and Judi Dench for new AI assistants, demonstrates the company’s focus on integrating advanced technology into everyday user experiences. These developments have already translated into increased advertising revenue and boosted Meta’s stock by **60%** this year alone.
Technical Outlook: NASDAQ:META Breaks Key Levels with Room to Run
Meta stock (NASDAQ: NASDAQ:META ) has been on a strong upward trend, breaking out of a five-month ascending triangle earlier this month. This breakout, combined with above-average trading volume, signals strong bullish momentum as the stock continues to climb. Meta shares surged to a record high of $576.88 on Wednesday and are up 1.55% in premarket trading on Thursday, currently sitting at $568.31.
The Relative Strength Index (RSI), a key indicator of stock momentum, has entered overbought territory at 73, signaling that the stock’s upward movement may face some short-term resistance. A pullback could be expected in the near term, but overall, the long-term outlook remains positive as Meta's innovations and product launches continue to drive investor interest.
Key Levels to Watch: Support and Resistance
Investors should keep an eye on the $545 level, which previously served as a resistance point and could now act as a key support level. A potential pullback to this zone would present a buying opportunity for traders who prefer to enter after corrections rather than chase breakouts.
Moreover, the unfilled gap-up pattern from January 2024 is worth noting. This gap could act as a magnet for price action in the event of a correction, providing another possible entry point for investors looking to capitalize on Meta’s long-term growth potential.
Conclusion: Meta’s Bright Future in AI and AR
Meta’s continued dominance in both the AI and AR spaces positions it for significant growth in the coming years. The company’s investments in cutting-edge technologies like smart eyewear, AI-driven social media features, and AR glasses are already paying off, as evidenced by its record stock performance and stronger-than-expected product demand.
Technically, the stock remains in a rising trend pattern, with room to reach the projected price targets of $700 and $790. However, with the RSI in overbought territory, a near-term pullback may be imminent. Investors should watch for buying opportunities near support levels like $545, which could provide an attractive entry point for those looking to ride the wave of Meta’s tech-driven momentum.
A Chartist POV – A2Z Cust2Mate Solutions Corp (NASDAQ: AZ) Collection phase begun. Following the positive momentum in the US market last week, we see AZ showcased a positive buying momentum. We observed larger trading volume being done in last Friday, potentially indicating the entry of institutional investors. We will continue to observe this company, with our short term TP level remains as $1.00.
Copper Supported by the Fed’s Jumbo CutAfter May’s record peak, copper prices slumped as demand optimism went away due to US and China economic fears, EV adoption slowdown and AI euphoria giving way to skepticism. However, copper staged a rebound, as China has been stepping up its effort to prop the economy, while AI optimism returned recently lifting tech and chip-making sectors. Furthermore US recession fears were quelled after the Fed slashed rates by a jumbo 0.5% last week and pointed to aggressive easing ahead, in what could be a boon for the property sectors where copper is used heavily.
These forces have helped the non-ferrous metal regain control above the EMA200, providing the launch pad for reclaiming the 4.500 handle. This would bring the summer high in the spotlight (4.700), although this level has a higher degree of difficulty.
On the other hand, the Fed’s frontloading creates risk of renewed inflation pressures that could lead to a shallower easing path, while China economic problems persist and the real estate sector remains in distress. Copper starts the current week on the back foot, unable to capitalize on its recent bounce. This sustains risk of sub-EMA200 moves that would pause the momentum, but the downside contains many buffers and prolonged weakness does not look easy, technically nor fundamentally.
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Past Performance is not an indicator of future results.
AI ANALYSIS (6H)AI seems to be inside a large diametric.
It now appears to be inside wave D or inside part of wave E and can react to the red box and reject downwards.
We are looking for sell/short positions in the supply range.
Closing a daily candle above the invalidation level will violate the analysis.
For risk management, please don't forget stop loss and capital management
Comment if you have any questions
Thank You
Meta and Spotify Criticize EU’s AI Decisions Stock up 3.53%On Thursday, Meta (NASDAQ: NASDAQ:META ), along with Spotify and several other tech companies, voiced strong criticisms against the European Union’s approach to data privacy and artificial intelligence (AI) regulation. In an open letter, these firms, along with researchers and industry bodies, claimed that the EU's decision-making has become "fragmented and inconsistent," warning that Europe risks falling behind in the global AI race.
The Regulatory Clash: Meta and GDPR Tensions
Meta (NASDAQ: NASDAQ:META ), which owns Facebook, Instagram, and WhatsApp, has been at the center of data privacy controversies in Europe, especially under the General Data Protection Regulation (GDPR). Recently, Meta (NASDAQ: NASDAQ:META ) halted its plans to collect data from European users to train its AI models due to pressure from privacy regulators. This followed a record-breaking fine of over one billion euros for breaching privacy rules.
The company, along with other tech giants, has delayed the release of AI products in the European market, seeking clarity on legal and regulatory frameworks. For instance, Meta delayed the launch of its Twitter alternative, Threads, in the EU, while Google has also held back on AI tool rollouts in the region.
The open letter signed by Meta, Spotify, and others calls for "harmonized, consistent, quick, and clear decisions" from data privacy regulators to enable European data to be used in AI training. The companies argue that without a coherent regulatory framework, the EU could lose its competitive edge in the global AI landscape, falling behind regions like the U.S. and China, which have been advancing rapidly in the field.
Meta’s AI Ambitions and Strategic Moves
Meta’s criticisms of the EU regulations come at a time when the company is heavily investing in AI technologies to enhance its social media platforms and introduce new products. AI is at the heart of Meta’s push toward the metaverse and other cutting-edge innovations. The company’s reluctance to release certain AI products in Europe is a direct result of the regulatory uncertainty, which hampers its ability to fully capitalize on its technological advancements.
With the EU’s AI Act coming into force this year, it aims to curb potential abuses in AI usage, but this stringent regulation may slow down innovation and delay product launches in the region. Meta and other tech giants believe that clearer rules will help unlock the potential of AI while protecting user privacy.
Technical Outlook: A Bullish Meta Stock Poised for Continued Growth
From a technical perspective, Meta’s stock ( NASDAQ:META ) has been on a stellar upward trend since November 2022, and it doesn't show signs of slowing down. As of the time of writing, the stock is up 3.66% and has entered overbought territory with an RSI (Relative Strength Index) of 70.54. This indicates that the stock may be poised for a temporary cool-off.
The stock's rise has been bolstered by broader market optimism, including the recent decision by the Federal Reserve to cut interest rates. This move is expected to benefit the tech sector, with Meta standing to gain significantly. With lower borrowing costs, tech companies like Meta (NASDAQ: NASDAQ:META ) can continue their aggressive expansion into AI and metaverse-related technologies.
Meta’s stock (NASDAQ: NASDAQ:META ) also exhibits a gap-up pattern that hasn’t been filled, suggesting a potential correction or consolidation period. Additionally, the stock has been consolidating since February 2024, indicating a potential bullish continuation pattern. However, with the RSI in overbought territory, investors should watch for a short-term pullback to cool off the stock before resuming its upward trajectory.
Meta’s AI Potential Amid Regulatory Uncertainty
Meta (NASDAQ: NASDAQ:META ) is navigating a complex regulatory environment in the EU while continuing to make strides in AI and technological innovation. Despite the challenges posed by GDPR and the AI Act, Meta remains well-positioned for long-term growth, with its stock reflecting strong momentum. However, short-term volatility due to regulatory decisions and technical factors may present buying opportunities for investors. As Meta (NASDAQ: NASDAQ:META ) continues to push the envelope in AI and the metaverse, the company’s future success will largely depend on its ability to navigate these regulatory waters while maintaining its innovation edge.
The Sleeping Giant Gearing Up for Its Next MoveEthereum, often said to be the destined "Nasdaq of Blockchains", has been quietly preparing for its next big move.
Known for snoozing until it catches up, Ethereum is now front and center with the recent approval of an Ethereum ETF. This development adds yet another pillar of strength to its already powerful ecosystem, making Ethereum’s rise inevitable.
WHOEVER CROSSES OUT ETHEREUM IS GRAVELY MISTAKEN.
While Solana and other competitors are trying to close the gap, Ethereum holds undeniable advantages that make it the leader in blockchain security and decentralization. Crypto is all about safety, and Ethereum’s proven resilience and robust infrastructure offer just that.
💡 Ethereum vs Solana:
Security: Ethereum’s Proof of Stake (PoS) is more battle-tested than Solana’s hybrid model, offering greater decentralization.
Developer Network: Ethereum has the largest development ecosystem, meaning quicker solutions, better scalability, and broader dApp integration.
DeFi and NFTs: Ethereum dominates both DeFi and NFT markets, further cementing its role as the go-to blockchain for real-world utility.
Solana may be faster, but it has faced network issues, while Ethereum’s network remains consistently more secure and widely adopted. Whoever bets against Ethereum is missing the big picture.
📊 Technical Outlook:
Support: $1,180
Resistance: $4,881 (mid-term), $6,443 (Primary Target)
Ethereum is currently consolidating near support, but a move toward $6,443 could be in the cards as we see broader adoption and the ETF driving institutional investment.
🔥 Why Now is the Time to Buy: With Ethereum ETF approval, mainstream adoption is likely to surge, making Ethereum an even stronger bet in the crypto space. If Ethereum’s rise itself doesn’t excite you, the fact that Ethereum-built projects like CRGPT are also poised for success gives investors multiple ways to benefit from the blockchain’s growing power.
⚠️ Final Thoughts:
Ethereum is the backbone of decentralized applications and smart contracts. Its growing importance in the crypto space means investors who get in now could see massive returns. Don’t sleep on Ethereum—it may snooze, but when it wakes, it surges. Combine that with Ethereum-based projects like CRGPT, and you’ve got a powerful investment strategy in the making.
🚀 Next Stop: $6,443 and Beyond
🔮 The future is bright for Ethereum and the Ethereum ecosystem, and you can be part of it.
10,364$ would be the price of Ethereum when in the future it meets today's Bitcoin marketcap. (when and if but to me is just a matter of 'when'!)
One Love,
The FXPROFESSOR 💙
Such a rise still feels boring for you?
Consider AI-powered project built and quoted on Ethereum like CRGPT
CryptoGPT: Unleashing AI in Crypto Trading CryptoGPT is gearing up for the release of its revolutionary Global Platform of Trading (GPT) , offering a unique opportunity for early investors to benefit from a market cap of just $350K, with $35M—a potential 100x return- seem like a reasonable first target for an AI project so well purposed for Crypto trading.
Ethereum & CRGPT:
As CRGPT is quoted on Ethereum, the potential rise of Ethereum could fuel AI gains.
Ethereum's strong network and ecosystem, backed by a fresh ETF approval mean investors can benefit from both Ethereum’s climb and CRGPT’s rapid expansion. At this stage both ETH and CRGPT seem like a potential bargain.
This could be an ideal moment to consider buying Ethereum and leveraging it within one of the most promising AI + Crypto projects on the market.
Key Milestones & Vision:
AI-Driven Trading: Seamless integration with exchanges like Binance as well as Metamask
New Team & Enhanced Vision: After overcoming early challenges, a revitalized team is pushing the project forward.
Platform Launch Imminent: Backed by cutting-edge AI to scale the trading experience.
Low Market Cap
At this low market cap, CRGPT seems massively undervalued. As the platform launches, the deflationary tokenomics (buyback & burn) will decrease supply and increase demand, pushing up token value. Trading is rewarded in this ecosystem and holding CRGPT unlocks AI tools for trading into the new age.
🌟 Why CRGPT is Set to Thrive:
Deflationary Model: Token burn will reduce supply while demand surges.
Real-World Utility: Premium features, rewards, and AI-driven tools.
My personal $35M first Target: A highly achievable milestone, which means 100x potential for early adopters.
Before the Platform and new website Launch:
The rise of Ethereum combined with CRGPT’s launch makes this potential a perfect time to enter the market, with upside potential from both, a new AI platform and website coming up and knowing the previous success of the price reaching almost 2$ ATHs.
To all who believe in AI, blockchain, and the next wave of crypto innovation, this could be our moment to make the best out of a promising AI project built on Ethereum.
One Love,
The FXPROFESSOR 💙
Oracle Corporation | ORCL & Ai If there is one person that you can compare it with Tony Stark aka IRON MAN is Larry Ellison
the ruthless entrepreneur who is born to win and be the number 1. Since the close of trading Friday, Ellison’s net worth has pumped 8 billion dollar to reach $ 206 billion
Oracle’s stock has reached new highs following its earnings report last week, which exceeded expectations and raised its revenue forecast for fiscal 2026.
Orcl have risen 20% this month and If this upward trend holds, it would mark their best performance since October 2022, when the stock jumped 28%, and the second best month since October 2002, nearly two decades ago.
The company’s stock success is partly driven by its involvement in the booming artificial intelligence sector. Ellison, Oracle’s founder since 1977, mentioned in last week’s earnings call that the company is building data centers to meet the growing demand for generative AI.
“We are literally building the smallest, most portable, most affordable cloud data centers all the way up to 200 megawatt data centers, ideal for training very large language models and keeping them up to date,” Larry said during the call
also he recently mentioned that Elon Musk and I ‘begged’ Jensen Huang for GPUs over dinner!We need you to take more of our money please!! It went ok. I mean, it worked!
Oracle also announced last week a partnership with Amazon’s cloud computing division to run its database services on dedicated hardware. Over the past year, it has formed similar alliances with Microsoft and Google, two other major cloud infrastructure providers
Oracle's cloud services are a key driver of their success, with revenue from this division growing 21% year over year, reaching $5.6 billion in quarterly earnings
Oracle is becoming a crucial provider, acting like a foundational layer for AI-focused companies. Their database systems are now critical to supporting businesses like OpenAI, AWS, and Google Cloud in building the infrastructure for future AI advancements. Despite AWS and Google Cloud being direct competitors, Oracle’s software remains essential to AI’s future.
Oracle's technology plays a foundational role, much like GPUs have in AI development. As companies seek efficient cloud-database solutions for AI workloads, Oracle is well-positioned to fulfill this demand.
Considering their strong Q1 performance and the central role of their database software in this field, I now view Oracle as a strong buy. The company's AI-powered cloud solutions, strategic partnerships, and growing database market make their technology indispensable for the future of AI
Oracle’s fiscal Q1 for FY 2025 exceeded expectations, with non GAAP earnings per share (EPS) of $1.39, surpassing estimates by $0.06, and revenue hitting $13.3 billion, outperforming projections by $60 million. The cloud segment, which includes their AI database software, remains a significant growth driver, generating $5.6 billion in revenue.
Most of Oracle’s revenue came from the Americas, contributing $8.3 billion, a 6.9% year-over-year increase. The AI revolution, gaining momentum in the US, aligns with their strong revenue growth in this region.
During the Q1 earnings call, management emphasized their expanded partnerships with major tech companies like Google Cloud (Alphabet Inc) and AWS (Amazon), which are notable given that they are also competitors. Oracle highlighted its success in the AI training space, pointing to the construction of large data centers equipped with ultra-high-performance RDMA networks and 32,000-node NVIDIA GPU clusters.
In the EMEA region, crucial to Oracle’s growth due to rising demand for cloud infrastructure and AI solutions among European enterprises and governments (sovereign AI), the company reported $3.3 billion in revenue.
Oracle’s earnings per share aka EPS is projected to grow at a compound annual rate of 13.5% for FY 2025, increasing to 14.41% in FY 2026, and continuing to compound at a modest double-digit rate in the coming years.
While these projections show strong potential for Oracle to be a compounder, I believe they may be somewhat conservative. The company’s remaining performance obligations (RPO) jumped 53% year-over-year to $99 billion by the end of the first fiscal quarter, indicating that their pipeline of signed work is growing faster than revenue. Once Oracle scales its solutions and workforce to match this RPO growth, we could see both revenue and EPS accelerate further.
In fact, while Oracle’s forward revenue growth is projected at just 8.86% for the next 12 months, their backlog is growing by over 50%. This suggests a notable gap between revenue expectations and actual demand.
I believe the current revenue growth projections are too low, and once revised upward, they could become a key growth catalyst for the company.
As for Oracle’s valuation, its forward price-to-earnings (P/E) ratio stands at 24.74, which is just 6.76% above the sector median of 23.17. However, given Oracle’s growth potential, I think it warrants a P/E ratio closer to 30.12, which is roughly 30% above the sector median. This would imply an additional 21.75% upside for the stock, excluding dividends.
With a forward P/E ratio only slightly above the sector median, despite Oracle’s impressive growth, the company’s performance suggests the stock should be trading at a higher valuation.
Larry Ellison is the man that I always can trust his vision and always bullish on his spirit and his ambitious. Oracle expanding influence in AI, coupled with robust revenue growth, positions the stock for significant upside. AI is like a modern day Gold Rush, and Oracle, much like GPU makers, is providing the essential tools the "pickaxe" for AI companies so That’s a space I’m eager to invest in
the chart looks insane and if there will be pullback I consider it as a buy opportunity
Big CCD turnaround after new CEO moves HQ to London? September marked the start of experienced and proven Boris Bohrer-Bilowitzki as new CEO for Concordium. He immediately announced major plans and started by moving the HQ to London.
The company is gaining momentum in the current AI trend. Concordium positions itself at the heart of AI innovation and digital twin creation. Concordium's Web3ID emerges as a pivotal tool for AI companies, with accountability and transparency at its core. It is packed with ideas and partnerships with institutions and companies in the pipeline.
So.
Could the current double bottom mark the start of an (explosive) upward trend (like the IH&S)? The R&R makes me pay attention here!
Why Large Language Models Struggle with Financial Analysis.Large language models revolutionized areas where text generation, analysis, and interpretation were applied. They perform fabulously with volumes of textual data by drawing logical and interesting inferences from such data. But it is precisely when these models are tasked with the analysis of numerical, or any other, more-complex mathematical relationships that are inevitable in the world of financial analysis that obvious limitations start to appear.
Let's break it down in simpler terms.
Problem in Math and Numerical Data Now, imagine a very complicated mathematical formula, with hundreds of variables involved. All ChatGPT would actually do, if you asked it to solve this, is not really a calculation in the truest sense; it would be an educated guess based on the patterns it learned from training.
That could be used to predict, for example, after reading through several thousand symbols, that the most probable digit after the equals sign is 4, based on statistical probability, but not because there's a good deal of serious mathematical reason for it. This, in short, is a consequence of the fact indicated above, namely that LLMs are created to predict patterns in a language rather than solve equations or carry out logical reasoning through problems. To put it better, consider the difference between an English major and a math major: the English major can read and understand text very well, but if you hand him a complicated derivative problem, he's likely to make an educated guess and check it with a numerical solver, rather than actually solve it step by step.
That is precisely how ChatGPT and similar models tackle a math problem. They just haven't had the underlying training in how to reason through numbers in the way a mathematics major would do.
Financial Analysis and Applying It
Okay, so why does this matter for financial analysis? Suppose you were engaging in some financial analytics on the performance of a stock based on two major data sets: 1) a corpus of tweets about the company and 2) movements of the stock. ChatGPT would be great at doing some sentiment analysis on tweets.
This is able to scan through thousands of tweets and provide a sentiment score, telling if the public opinion about the company is positive, negative, or neutral. Since text understanding is one of the major functionalities of LLMs, it is possible to effectively conduct the latter task.
It gets a bit more challenging when you want it to take a decision based on numerical data. For example, you might ask, "Given the above sentiment scores across tweets and additional data on stock prices, should I buy or sell the stock at this point in time?" It's for this that ChatGPT lets you down. Interpreting raw numbers in the form of something like price data or sentiment score correlations just isn't what LLMs were originally built for.
In this case, ChatGPT will not be able to judge the estimation of relationship between the sentiment scores and prices. If it guesses, the answer could just be entirely random. Such unreliable prediction would be not only of no help but actually dangerous, given that in financial markets, real monetary decisions might be based on the data decisions.
Why Causation and Correlation are Problematic for LLMs More than a math problem, a lot of financial analysis is really trying to figure out which way the correlation runs—between one set of data and another. Say, for example, market sentiment vs. stock prices. But then again, if A and B move together, that does not automatically mean that A causes B to do so because correlation is not causation. Determination of causality requires orders of logical reasoning that LLMs are absolutely incapable of.
One recent paper asked whether LLMs can separate causation from correlation. The researchers developed a data set of 400,000 samples and injected known causal relationships to it. They also tested 17 other pre-trained language models, including ChatGPT, on whether it can be told to determine what is cause and what is effect. The results were shocking: the LLMs performed close to random in their ability to infer causation, meaning they often couldn't distinguish mere correlation from true cause-and-effect relationships. Translated back into our example with the stock market, one might see much more clearly why that would be a problem. If sentiment towards a stock is bullish and the price of a stock does go up, LLM simply wouldn't understand what the two things have to do with each other—let alone if it knew a stock was going to continue to go up. The model may as well say "sell the stock" as give a better answer than flipping a coin would provide.
Will Fine-Tuning Be the Answer
Fine-tuning might be a one-time way out. It will let the model be better at handling such datasets through retraining on the given data. The fine-tuned model for sentiment analysis of textual stock prices should, in fact, be made to pick up the trend between those latter two features.
However, there's a catch.
While this is also supported by the same research, this capability is refined to support only similar operating data on which the models train. The immediate effect of the model on completely new data, which involves sentiment sources or new market conditions, will always put its performance down.
In other words, even fine-tuned models are not generalizable; thus, they can work with data which they have already seen, but they cannot adapt to new or evolving datasets.
Plug-ins and External Tools: One Potential Answer Integration of such systems with domain-specific tooling is one way to overcome this weakness. This is quite akin to the way that ChatGPT now integrates Wolfram Alpha for maths problems. Since ChatGPT is incapable of solving a math problem, it sends the problem further to Wolfram Alpha—a system set up and put in place exclusively for complex calculations—and then relays the answer back to them.
The exact same approach could be replicated in the case of financial analysis: Once the LLM realizes it's working with numerical data or that it has had to infer causality, then work on the general problem can be outsourced to those prepared models or algorithms that have been developed for those particular tasks. Once these analyses are done, the LLM will be able to synthesize and lastly provide an enhanced recommendation or insight. Such a hybrid approach of combining LLMs with specialized analytical tools holds the key to better performance in financial decision-making contexts. What does that mean for a financial analyst and a trader? Thus, if you plan to use ChatGPT or other LLMs in your financial flow of analysis, such limitations shall not be left unattended. Powerful the models may be for sentiment analysis, news analysis, or any type of textual data analysis, numerical analysis should not be relayed on by such models, nor correlational or causality inference-at least not without additional tools or techniques. If you want to do quantitative analysis using LLMs or trading strategies, be prepared to carry out a lot of fine-tuning and many integrations of third-party tools that will surely be able to process numerical data and more sophisticated logical reasoning. That said, one of the most exciting challenges for the future is perhaps that as research continues to sharpen their capability with numbers, causality, and correlation, the ability to use LLMs robustly within financial analysis may improve.