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Artificial_intelligence

ETH Bullish From Here? Looking at our TA on ETH combined with our new AI/Machine learning indicators (releasing soon), we can see ETH is setting up for another bullish run. Our indicators have called the tops and bottoms pretty accurately, now it looks like we may have short-term upside. The big levels to watch out for are 1815 (support) and 1850 (resistance). If Ethereum cracks 1815 then that would invalidate our bullish thesis and set for a potential fall to 1780 then further of 1650. Although if we break 1850, then that sets clear skies to our next target of 1900, followed by 2000. As we're in this current chop, we always advise everyone to never force a trade and wait for a trade to come to you. This means waiting until multiple indications signal a buy (oversold at support, etc) or vice versa. Trading is all about discipline and those who don't have it will quickly be humbled. If you enjoyed our TA or have any questions about our upcoming indicator release, please comment below or send us a DM :)
Long
by CryptoScripts
Microsoft Challenges Fib 3.618 levelMicrosoft - NASDAQ:MSFT Expectations were beat across the board today but what does the long term monthly chart tell us? All is revealed in the chart. This is a key moment for NASDAQ:MSFT and a pull back or break through to established new highs wouldn't surprise. I'm happy to wait for the confirmations outlined in the chart. That MACD cross though looks appealing. Earnings Summary - Profits jumped 20% to 20.1 b - EPS: $2.69 / Exp $2.56 - Revenue: $56.19B / Exp $55.49B - Azure (cloud) revenue up 26% / Exp 27%
NASDAQ:MSFT
by PukaCharts
Differentiating your AI exposure from the Nasdaq-100The Nasdaq-100 has recorded its best H1 since the inception of the index in 1985, propelled by the year-to-date rally in the biggest tech stocks riding the artificial intelligence (AI) wave. For investors looking to benefit from the long-term growth offered by the AI megatrend, this period presents an opportunity to analyse how the AI-focused thematic strategies have fared in such a market and how they could perform going forward. In the first part of this two-part blog series, we discussed the case for a targeted AI strategy vs achieving exposure to AI through the Nasdaq-100. The key factors in favour of an AI strategy included a more comprehensive exposure to the breadth of AI activities, a potential inclusion of the mega caps of tomorrow, and diversification benefits. In this blog, we look at the AI space in Europe and discuss the signposts for investors in selecting a sound AI-focused thematic strategy and the importance of such a selection. The drivers of return dispersion in the AI peer group One of the simplest and most compelling arguments that not all AI strategies are created equal can be made by looking at the dispersion of returns within the AI peer group. The dispersion of returns across strategies aiming to harness the same theme is something that we continuously observe across a range of 42 themes tracked in our WisdomTree Thematic Universe1. This confirms that this phenomenon is not just specific to the AI theme. Based on the 15 AI strategies with available year-to-date history in Europe, we have observed that the year-to-date return experience across the AI strategies has been quite different - ranging from around 13% to up to 43%. The average return across the strategies was around 29.75%, or 9.4% lower than the return of the Nasdaq-100. Given that returns of a range of AI stocks have been boosted by the growing enthusiasm around ChatGPT and generative AI, we would view relative outperformance vs the average return in the AI peer group as one of the factors potentially suggesting a promising AI strategy. However, an important question to answer here is if a given AI strategy has been driven by the performance of the same key stocks driving the performance of the Nasdaq-100, or if it has been propelled by other return drivers. If the latter is true, such a strategy can present a return enhancement play for investors holding the Nasdaq-100 as the broad tech benchmark. While it is not always feasible to run performance attribution for each fund in the AI peer group, and assess how different its return drivers have been in contrast to the Nasdaq-100, we have observed that this dispersion boils down to strategy design, and how each fund is meant to capture the opportunities offered by the proliferation of AI. For example, in our WisdomTree Artificial Intelligence UCITS ETF (WTAI), enhancers (that is, the companies that are a prominent force in AI but with a smaller portion of products and revenues associated with the theme) receive only 10% weight during each semi-annual period. This means that tech giants that dominate the top 10 in the Nasdaq-100, jointly can receive only up to 10% weight. At the same time, more pure-play opportunities in the space (known as ‘engagers’) receive 50% weight at the rebalance, ensuring a certain degree of theme purity. The importance of a robust selection framework At WisdomTree, we have previously singled out five building blocks that comprise the selection framework for thematic strategies first proposed in our thematic white paper. In short, we invite investors to first focus on selecting strategies with a clear focus on the theme of interest, assess if the subject matter expertise is part of the strategy design and, if possible, evaluate the purity of the suggested exposure. All these signposts are more qualitative in nature, unlike the next step, which involves testing the shortlisted strategies for the level of differentiation they offer vs broad benchmarks, other themes, and each other. Let’s have a look at WTAI vs the best performing fund in the AI peer group year-to-date, that is, Fund A, and see if these two funds are differentiated vs the Nasdaq-100. One easy analysis that investors can do to assess the degree of differentiation is to look at the overlap weight vs a broad benchmark and the percentage of common and unique holdings vs the same benchmark. In Figure 2, the analysis suggests that WTAI has relatively low overlap with the Nasdaq-100 and holds only 29% weight in the holdings common with the broad tech gauge. In contrast, Fund A has a relatively high overlap of around 40% and has invested around 62% weight in the stocks represented in the Nasdaq-100. We can extend our comparison further and resort to performance attribution, as both strategies are offered in an exchange-traded fund (ETF) wrapper and have to report their holdings on a daily basis. The top 10 holdings contributing to the year-to-date performance within WTAI and Fund A, exposes an interesting contrast between the two strategies. Within the top 10 contributors of Fund A, investors can find eight stocks in dark blue that have also been the top 10 year-to-date contributors in the Nasdaq-100. The average weight of the top 10 contributors in Fund A has been 45.6%, accounting for around 70% of the strategy’s return. Due to its market cap-driven weighting, the majority of holdings in Fund A that have posted year-to-date returns above 50%, and even above 100%, have received weights below 0.20% each. This has limited Fund A’s ability to benefit from the AI stocks not included in the Nasdaq-100. In turn, in WTAI, only Nvidia, also represented in the top 10 in the Nasdaq-100, has been within the top 10 year-to-date contributors. The average weight of the top 10 contributors has comprised only 23.5%, and the top 10 have jointly contributed only 56% to the strategy’s year-to-date return. Notably, the best-performing stock in WTAI was C3.ai and not Nvidia. Fund A had its own stock, Wistron, that has also beaten Nvidia with 204.7% year-to-date return, but the fund had only 0.08% average weight in it. Furthermore, in contrast to Fund A, 4 out of the 5 best-performing stocks in WTAI had average weights between 2.3% and 2.8%. This highlights that the strategy design behind WTAI has allowed the fund to not only benefit from strong returns posted by a range of AI stocks year-to-date, but also to differentiate its key return contributors from the broad tech benchmark. Sources 1 Please see page 8 of the WisdomTree European thematic monthly update for an overview of the WisdomTree Thematic Universe and page 4 for the dispersions of returns across the themes. 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
MVSTMicrovast Holdings, Inc Hi Folks, This stock belong the the EV + Battery sector MVST has a quite interesting chart pattern. • A big move in the past 1-3 months anywhere from 30%-100% the rally last for a few days to weeks. • Stock is going to catch up the ema 200 • Orderly consolidation with higher lows & tightening range: • RDM, VCP • Stocks surfs the rising EMA 10 or the EMA 20, and sometimes the EMA 50 • Volumes are significative compared to previous phase Let's keep it shortlisted
NASDAQ:MVSTLong
by NicolasPT1
2
Investing In Artificial Intelligence (AI) : Beginner’s GuideThe field of artificial intelligence (AI) has emerged as a highly attractive investment option, captivating the attention of investors worldwide. With its capacity to reshape industries and drive innovation, AI has gained prominence as a transformative technology. By simulating human intelligence and performing intricate tasks, AI is revolutionizing sectors ranging from transportation to finance and beyond. Given the rapid growth of the AI market, which is projected to reach revenues of up to $900 billion by 2026, having a comprehensive understanding of how to invest in this dynamic field has become crucial for investors. In this comprehensive guide tailored for beginners, we will delve into the fundamentals of AI, exploring its underlying concepts, methodologies, and applications across various industries. By gaining insight into the inner workings of AI, investors can grasp the potential impact it can have on different sectors, enabling them to identify promising investment opportunities. Moreover, we will examine diverse investment strategies that investors can consider when venturing into the AI market. These strategies will encompass a range of approaches, from investing in established AI companies and technology giants, to exploring opportunities in startups and early-stage ventures that are driving innovation in the AI space. Additionally, we will explore investment vehicles such as AI-focused exchange-traded funds (ETFs) and mutual funds, providing investors with a broader exposure to the AI market. Throughout this guide, we will address the key factors to consider when investing in AI, including the evaluation of AI technologies, understanding regulatory and ethical implications, and staying updated with the latest industry trends. By equipping investors with the necessary knowledge and insights, this guide aims to empower them to make informed investment decisions in the dynamic and evolving landscape of AI. As AI continues to redefine industries and shape the future, investing in this transformative technology presents an exciting opportunity for investors seeking long-term growth and exposure to cutting-edge innovation. Through this beginner's guide, we invite investors to embark on a journey into the world of AI investment, unlocking the potential for both financial returns and contributions to the advancement of society as a whole. Artificial Intelligence (AI) Explained Artificial Intelligence (AI) has emerged as a groundbreaking technology that aims to replicate human intelligence in computers and machines, surpassing human capabilities in terms of speed and accuracy. Leading companies like Microsoft (MSFT) and Google (GOOGL) utilize AI to develop systems capable of problem-solving, answering inquiries, and executing tasks that were traditionally performed by humans. The advancement of AI systems has expanded their applications across diverse industries and sectors. One notable transformation is occurring in the transportation industry, where electric and autonomous vehicles are revolutionizing travel and poised to contribute trillions of dollars to the global economy. In the banking sector, AI is employed to enhance decision-making processes in high-speed trading, automate back-office functions such as risk management, and even introduce humanoid robots in branches to reduce costs. These examples only scratch the surface of the extensive range of AI applications. Analysts at International Data Corp. (IDC), a renowned market intelligence provider, project that the AI market will generate global revenues of up to $900 billion by 2026. This estimate reflects a significant compound annual growth rate of 18.6 percent from 2022 to 2026, underscoring the exponential growth potential of AI. What was once considered a luxury has now become an essential component of modern businesses. The global pandemic has accelerated the adoption of AI, making it pervasive across all aspects of business operations. From healthcare and manufacturing to finance and customer service, AI has demonstrated its value in enhancing efficiency, optimizing processes, and driving innovation. Investing in AI presents an opportunity to capitalize on its transformative potential. However, it is essential for investors to approach AI investments with a thorough understanding of the technology, its applications, and the companies leading the way. As AI continues to shape industries and redefine the future, investors who navigate this dynamic landscape stand to benefit from its long-term growth and the potential for significant returns. How To Invest In Artificial Intelligence As a retail investor, you may already have exposure to artificial intelligence (AI) through various prominent U.S. public companies that utilize AI or invest in this technology. However, if you're specifically interested in investing in AI, there are several approaches you can consider: Individual Stocks: Conduct thorough research and invest directly in companies that specialize in AI development, application, or integration. Look for companies with a strong focus on AI, a robust research and development program, and a history of innovation in the field. Exchange-Traded Funds (ETFs): Explore AI-focused ETFs that concentrate on companies involved in AI technologies. These funds offer diversification by investing in a portfolio of AI-related stocks, providing exposure to a broad range of companies in the AI sector. Index Funds: Invest in broad market index funds that include leading companies at the forefront of AI development. These funds track major market indices like the S&P 500, which often include prominent players in the AI industry. Additionally, Contract for Difference (CFD) trading is another option for investing in AI. CFDs allow you to speculate on the price movements of AI-related assets without actually owning the underlying assets. By taking long or short positions, you can potentially profit from both upward and downward price movements in the AI sector. However, it's important to note that CFD trading carries a higher level of risk and requires a good understanding of market dynamics. Top AI Stocks To Consider: Microsoft (MSFT) As of May 2023, Microsoft, the renowned developer of the Windows operating system, holds the position of the largest Artificial Intelligence (AI) company. In recent times, Microsoft has made significant strides in the field of AI, unveiling a range of new features and initiatives across its product line. One notable development is the integration of AI-powered enhancements into Edge, Microsoft's web browser. These enhancements leverage AI technology to provide users with improved browsing experiences, including enhanced performance, personalized recommendations, and advanced security features. Furthermore, Microsoft has incorporated AI capabilities into Bing, its search engine. The integration of AI allows Bing to deliver more accurate and relevant search results, enhancing the overall search experience for users. Highlighting its commitment to AI, Microsoft announced a substantial investment in OpenAI, the creator of ChatGPT, a widely used language model. This multiyear and multibillion-dollar partnership have resulted in the deployment of OpenAI models across Microsoft's product range, including the Azure OpenAI Service. Additionally, Microsoft's Azure cloud platform serves as the exclusive provider for OpenAI's cloud-based services. By investing in OpenAI and integrating AI capabilities into its products and services, Microsoft aims to harness the power of AI to deliver innovative solutions and enhance user experiences. This strategic focus on AI demonstrates Microsoft's recognition of the transformative potential of this technology and its dedication to remaining at the forefront of the AI industry. Tesla (TSLA) In the realm of electric vehicles (EVs), Tesla stands apart from technology giants like Microsoft and Alphabet by leveraging AI and robotics to drive innovation. The company has positioned itself as a leader in self-driving cars, an area heavily reliant on AI for tasks such as visual processing and strategic planning. Tesla is actively pursuing the development of self-driving technology and has been working on AI inference chips that are specifically designed to run its full self-driving software (FSD). These chips enable efficient and powerful processing capabilities, enabling Tesla vehicles to make real-time decisions and navigate autonomously. Beyond self-driving vehicles, Tesla has expanded its AI endeavors into the realm of humanoid robots. In October 2022, CEO Elon Musk unveiled "Optimus," a highly anticipated robot. Musk envisions a future where Tesla's robot business surpasses the value of its cars, indicating a broader ambition to extend beyond the automotive industry. In addition to self-driving technology and robotics, Tesla is actively involved in various AI fields. This includes the development of Dojo chips and systems, which aim to enhance AI training and accelerate computational processes. Tesla also focuses on neural networks, autonomy algorithms, code foundations, and evaluation infrastructure to continuously improve and refine its AI capabilities. By applying AI and robotics to the EV industry, Tesla is at the forefront of technological advancements and aims to shape the future of transportation. Its commitment to developing cutting-edge AI solutions demonstrates the company's dedication to pushing the boundaries of innovation and redefining the possibilities within the automotive industry. IBM (IBM) In May 2023, IBM, a computing giant with a long-standing history in the technology industry, made a significant announcement regarding its platform called Watsonx. This platform is designed to empower developers by providing them with a comprehensive set of tools for creating AI models. Watsonx equips developers with machine learning tools, foundational models, hardware resources, and data storage capabilities, enabling them to build sophisticated AI applications. By offering a range of resources within a unified platform, IBM aims to streamline the AI development process and make it more accessible to developers. In collaboration with Hugging Face, a prominent provider of open-source AI libraries, IBM has integrated the benefits of Hugging Face's libraries and extensive collection of open models and datasets into the Watsonx.ai studio. This collaboration allows developers to leverage Hugging Face's resources and tap into a vast array of pre-trained models and datasets, accelerating the development of AI solutions. Beyond its AI offerings, IBM has been actively involved in AI integration research. The company's Global AI Adoption Index explores the impact of AI adoption on businesses and society as a whole. This research initiative aims to provide insights into the current state of AI adoption, identify trends, and understand the potential implications of AI on various industries and sectors. IBM's commitment to advancing AI technology, as demonstrated by its Watsonx platform and research initiatives, highlights the company's ongoing efforts to drive innovation and facilitate the integration of AI into diverse domains. By empowering developers and exploring the broader implications of AI adoption, IBM continues to play a significant role in shaping the future of artificial intelligence. Alphabet (GOOGL) Alphabet, the parent company of Google, has been actively investing in the AI sector, demonstrating its commitment to advancing artificial intelligence technologies. In April, Alphabet's venture capital subsidiary, CapitalG, played a leading role in a $100 million funding round for AlphaSense, an AI startup. This investment not only highlights Alphabet's financial support for AI innovation but also strengthens its presence in the AI industry. In addition to its investment activities, Google, as a part of Alphabet, has made substantial investments in other AI-related companies. For instance, Google has invested approximately $400 million in Anthropic, a competitor to ChatGPT, further expanding its involvement in the AI landscape. Furthermore, Google has acquired Alter, a startup specializing in AI avatars, which showcases its strategic focus on enhancing AI capabilities and exploring new applications for the technology. Within its own product ecosystem, Google has introduced various generative AI tools that leverage the power of artificial intelligence. One notable example is Bard, Google's own counterpart to ChatGPT, which provides real-time access to information from the web. This demonstrates Google's efforts to develop AI models capable of generating dynamic and contextually relevant content. Moreover, Google is incorporating AI functionality into its Workspace suite, starting with popular tools like Gmail and Google Docs. By integrating AI capabilities into these productivity tools, Google aims to enhance user experiences, improve efficiency, and enable new possibilities for collaboration and content generation. Alphabet's investments in AI startups, acquisitions, and the development of generative AI tools highlight the company's dedication to harnessing the potential of artificial intelligence. Through these initiatives, Alphabet continues to shape the AI landscape and drive innovation in the field. Amazon (AMZN) Amazon, a prominent player in the AI field, has established itself as a leader by offering a comprehensive suite of AI and machine learning (ML) services through its cloud computing platform, Amazon Web Services (AWS). AWS provides a wide range of tools and services that empower developers and businesses to integrate AI and ML functionalities into their applications and workflows efficiently. Notably, Amazon not only provides AI services to other businesses but also harnesses AI capabilities within its own operations. For instance, the company employs sophisticated AI algorithms in its online store to deliver personalized product recommendations to customers, creating a more tailored and engaging shopping experience. One of Amazon's most recognizable AI applications is Alexa, the virtual assistant powering Echo devices. Powered by natural language processing and ML algorithms, Alexa can comprehend and respond to user commands, enabling users to interact with their devices using voice commands. This integration of AI technology has revolutionized the way people interact with their smart devices and has become a prominent feature in many households. Amazon's commitment to AI is further evident through its ongoing investments in AI research and development. The company continually seeks to advance AI technologies, exploring new applications and improving existing capabilities. By embracing AI in various aspects of its business, Amazon aims to enhance customer experiences, drive innovation, and remain at the forefront of AI integration in the industry. Oracle (ORCL) Oracle (ORCL), a renowned provider of cloud computing solutions, has emerged as a leading player in the AI landscape by offering the Oracle Cloud Infrastructure. This robust cloud platform serves as the foundation for various workloads, including AI applications, empowering businesses to leverage the benefits of AI technology. Recognizing the growing significance of AI, Oracle has taken steps to enhance its AI capabilities for enterprise customers. Notably, the company has expanded its collaboration with Nvidia, a prominent chipmaker specializing in AI hardware. This strategic partnership allows Oracle to harness the power of Nvidia's advanced AI-focused GPUs (Graphics Processing Units) and other hardware technologies. By integrating Nvidia's hardware into its infrastructure, Oracle aims to deliver enhanced AI performance to its enterprise customers. This collaboration equips businesses with the ability to process vast datasets and execute complex AI algorithms more efficiently, leading to improved insights and outcomes. By leveraging Nvidia's powerful AI hardware, Oracle demonstrates its commitment to providing cutting-edge AI solutions that address the evolving needs of businesses in the era of digital transformation. Through its collaboration with Nvidia and its focus on advancing AI capabilities, Oracle solidifies its position as a leading provider of AI-enabled cloud infrastructure and reinforces its commitment to empowering businesses with the tools and technologies needed to harness the potential of AI in their operations. How To Select The AI Stocks To Invest In : When selecting AI stocks to invest in, it's important to conduct thorough research and consider various factors. Here are some key considerations to help guide your decision-making process: 1) Company's fundamentals: Review the financial health and performance of the company. Analyze its financial statements, including the balance sheet, income statement, and cash flow statement. Look at key indicators such as the price-to-earnings (P/E) ratio, return on equity (ROE), and debt-to-equity (D/E) ratio to assess its profitability and financial stability. 2) Technical analysis: If you're a short-term trader, utilize technical analysis to study price patterns and trends. Use technical indicators and candlestick charts to identify entry and exit points based on historical price movements. 3) Analyst ratings: Consider the latest analyst ratings and commentary on specific stocks. Analyst opinions can provide valuable insights, but keep in mind that they are subjective and should be considered alongside other factors. 4) Latest company news: Stay updated on a company's news and developments. Look for announcements related to AI investments, acquisitions, R&D initiatives, and new product offerings. This information can indicate a company's growth potential and competitive positioning. 5) Competitive landscape: Assess the company's position within the AI industry and its competitive advantage. Consider its technology, market share, and ability to innovate. Evaluate how it compares to other players in the market. 6) Management team: Evaluate the leadership and management team of the company. Look for experienced executives who have a track record of success and a clear vision for the company's future. 7) Industry trends: Stay informed about the latest trends and advancements in the AI industry. Understand how AI is being adopted across different sectors and the potential impact it may have on the company you're considering. 8) Regulatory environment: Consider the regulatory landscape surrounding AI. Assess how regulations and policies may affect the company's operations and growth prospects. 9) Diversification: Manage risk by diversifying your investments across different AI stocks and sectors. This helps mitigate the impact of individual stock performance and provides exposure to a range of opportunities. Conclusion: Investing in AI presents unique opportunities for investors as this cutting-edge technology continues to transform industries and drive innovation. The potential for AI to revolutionize various sectors, enhance efficiency, and create new business models is immense. Whether through individual stock investments, AI-focused ETFs, index funds, or even CFD trading, investors can participate in the AI market and potentially benefit from its growth. However, investing in AI requires careful consideration and research. It is important to understand the fundamentals of AI, including its applications and potential impact on industries. Analyzing company financials, such as balance sheets and income statements, can provide insights into the financial health and long-term potential of AI-focused companies. Staying updated on industry trends, news, and developments is crucial. Monitoring AI-related investments, partnerships, research, and product advancements can help identify companies that are at the forefront of AI innovation. Diversification is also key in AI investing. Spreading investments across different AI stocks, sectors, and geographies can help mitigate risk and capture opportunities in various segments of the AI market. Lastly, it is important to remain informed and adaptable as AI technology continues to evolve. Regularly assessing and adjusting investment strategies based on market conditions and emerging trends is essential to capitalize on the transformative potential of AI. By understanding the fundamentals, conducting thorough research, and staying informed, investors can position themselves to potentially benefit from the growth and impact of AI in the years to come.
NASDAQ:TSLAEducation
by FOREXN1
10
Crypto's Impending Boom: Market Shifts and Global DynamicsCryptocurrencies in the Face of Rising Bond Yields and a Strengthening Dollar Cryptocurrencies have been on a short-term downward trend, attributed to deteriorating liquidity within crypto and outside crypto due to rising bond yields and the strengthening dollar, as they are sensitive to rates and liquidity fluctuations. Their recent downturn can also be explained by the fact that they had performed much better than their interest rate & liquidity models had suggested and by US tech stocks sucking flows and liquidity. Capital Flows: The Rising Crypto Tide in Hong Kong Significant rallies in the crypto sector could be on the horizon, especially when the double bottoms in Bitcoin and Ethereum are swept. Some important reasons are the impending acceptance of crypto exchanges by Hong Kong and the return of cash to Voyager's creditors. As Chinese citizens grapple with capital outflows, liquidity flows from China could be redirected to the crypto sector through Hong Kong. At the same time, with mounting US-China tensions, cryptocurrencies could provide an alternative, potentially the only proxy investment to AI (US big tech). In the Face of Uncommon Volatility: A Premonition of Crypto Spikes As we navigate the debt ceiling crisis, we might experience volatility spikes, even though volatility remains subdued. Next week we might start seeing some significant moves, as USD 3.6 billion worth of options expired this Friday, constituting roughly 26% of Deribit's open interest. Implied volatility is at its lowest, with DVOL trading at 44 for BTC and ETH and shorter-dated even lower. This is relatively uncommon, and whenever we've seen such low volatility, a significant spike in vol has followed soon after. A Confluence of Events: Setting the Stage for Crypto Price Surge The latest spike in January coincided with a price rally, which may reoccur, given the significant expiration of mainly call options, with a Put/Call ratio of 0.38. With events such as Voyager distributing >1B in cash to creditors, Hong Kong authorizing crypto trade for its citizens, US tech investors capitalizing/diversifying on >3T gains and redirecting some into crypto, and potential issues with the US banking system or USD stablecoins due to a possible US default, the stage is set for a potentially explosive growth in crypto prices. The last part is something many ignore, but FUD, or real issues around banks or stablecoins, could recreate the conditions for another SVB - USDC type rally, as investors view Bitcoin and Ethereum as the safe havens of crypto and of the financial system broadly. Bullish on Synergy: The Powerful Integration of AI and Crypto The convergence of AI and crypto can create new business models, enhance decision-making processes, improve trust and transparency, and unlock organizational and operational efficiencies. Some areas where AI and crypto can synergize: AI-Powered Smart Contracts, New forms of financial tools, AI-to-AI financial transactions, Enhanced Security and Privacy both for AI and Cryptocurrencies and so on. AI will integrate and interact with open and trustless systems like crypto, but it's unlikely to interact with closed systems like banks. The confluence between the two technologies is apparent, making me bullish long-term. Trade ideas As mentioned in my recent ETHBTC idea, Ethereum looks stronger than Bitcoin. However, Bitcoin looks cleaner than Ethereum. Bitcoin has two critical untested areas lower: 25000-25700 - with 25200 and the double bottom at 25800 being the basic levels, and 22600-23600 - which is an area that the market didn't test appropriately as it went higher, especially 22600, which was the critical breakout level. BTCUSD has two triple tops higher, one around 27600 and the other around 29900. It's unclear whether the double bottom will be swept first or one or both of the triple tops will be swept first, but to me, it's clear that the market will probably rally much higher once the bottom is swept. Given everything I mentioned above, it's better to bet on the upside and not short the market here. Therefore long around 25700 and cut below 24900, long around 23600 and cut below 22500, with targets at 27600 and 29900. Despite all the bankruptcies and negativity around US regulations, it's better to go long than short, as everything else seems quite positive. Although there are some potential negative catalysts for crypto, and 2023-2024 could be like 2019-2020 for crypto, I think that dips are for buying and that it's more likely than not that we are in a bull market rather than a bear market.
COINBASE:BTCUSDLong
by BitcoinMacro
S&P 500: Expensive but Not OverpricedCME: E-Mini S&P 500 ( CME_MINI:ES1! ), S&P Technology Sector ( CME_MINI:XAK1! ) These days, the S&P 500 is not behaving like a well-diversified stock market index. The “Magnificent Seven”, which includes Nvidia NASDAQ:NVDA , Apple NASDAQ:AAPL , Tesla NASDAQ:TSLA , Microsoft NASDAQ:MSFT , Google NASDAQ:GOOGL , Meta NASDAQ:META and Amazon NASDAQ:AMZN , is up roughly 60% year-to-date. These 7 tech stocks now represents ~30% of the entire S&P 500 index. Meanwhile, the remaining 493 companies in the S&P 500 are up only 3% YTD. Altogether, the S&P 500 is up 15.8% YTD as of June 15th. The tech-heavy Nasdaq 100, which includes all the Magnificent Seven, is up 39.5% YTD. The Dow Jones Industrial Average, with only one of the seven, NASDAQ:AAPL , in its components, had a very disappointing return of 4.0% YTD. What sparks the recent market rally is OpenAI’s ChatGPT. Its November 20th launch ignited a global sensation in Artificial Intelligence. By now, the entire US stock market is being held up by the red-hot AI momentum. S&P 500 Performance by Sector Of the 11 S&P select sectors, I found that only Technology has a decent 12-month performance. Three other sectors have low single-digit return, and the rest are in the red. (Data source: S&P Global, 12-month returns as of May 31st, 2023). • Consumer Discretionary: -0.83% • Consumer Staples: 0.22% • Energy: -8.23% • Financials: -8.55% • Real Estate: -15.47% • Health Care: -1.71% • Industrials: -4.15% • Materials: -10.69% • Technology: 18.16% • Utilities: --9.96% • Communication Services: 4.47% • S&P 500: 1.15% Once again, data confirms that the recent stock market rally is exclusively reserved for the tech stocks. Investing in the S&P 500 is like holding an outstanding tech-sector fund on one hand, and a sucker fund of poorly-performing stocks on the other. Statistical Analysis of the S&P 500 Diving deeper into the S&P, I found that its 3-year mean is 4027.2 as of June 15th. The standard deviation during this period is 395.6. We know from probability distribution that the time series of price data falls inside plus or minus one standard deviation approximately 33% of the time. This corresponds to the index range of 3632 and 4423. Data trend shows that whenever the index broke away from this boundary, it had the tendency of getting pulled back in. This fits the rule of mean reversion, as seen below: • The S&P broke through 4400 in August 2021 and reached its record height at 4800 in January 2022. Over the next four months, it plunged 1,000 points, or -22.8%. • The S&P fell below 3600 in September 2022. It rebounded after it crossed the -1 STD line and regained 24% as of last Friday. S&P 500 closed at 4,453.75 on June 15th, which placed it 30 points above the +1 STD line. It is approaching “expensive” level from the historical perspective. But will it trend down from here? I seriously doubt it. The AI momentum could carry the stock market index much higher. We are at an early stage to even access how AI could revolutionize our world. Waves of technological breakthroughs and new applications would continue to fire up investor sentiment. Recent resolution of the Debt Ceiling Crisis and the Fed pausing rate hikes in June are also strong tailwinds which have helped lift stock market valuation. If the index reaches the +2 STD line, at 4818.43, we could argue that it marks a turning point. We shall understand that this is not a broad-based stock market rally. The consequence of high inflation and high interest rates would weigh on company profitability for many months to come. At lofty valuation, the Magnificent Seven could no longer carry the weight of 493 mediocre companies. The S&P could come crushing down under its own weight. Hedging the Risk of a Tech Sector Fallout In my opinion, while the S&P 500 is expensive, it is not yet overpriced. We could still ride the AI wave by holding stocks or a long position in the stock index futures. I am not particularly concerned whether you call this a new bull market or a bear market rally. However, the entire stock market is overly concentrated in the tech sector. A handful of chip manufacturers, namely Nvidia and TSMC, holds systemic risk. If their production is threatened by geopolitical conflicts, the entire stock market could crash. Nvidia sees its share price doubled this year, and has a ridiculous price earnings ratio of 222. Its massive $1 trillion market valuation has been built upon the huge promise of AI. Any negative news on Nvidia would have a disproportionally large impact on the S&P. To hedge the risk of AI bubble going busted, I am exploring a spread trade with long S&P index futures NYSE:ES and short Technology Select Sector futures $XAK. Since the Magnificent Seven accounts for 30% of S&P 500 market value, I am considering a 10:3 spread ratio. By measure of contract notional value, for every $100,000 in ES long positions, short XAK by $30,000. • ESU3 is quoted 4,459 on June 15th. Its notional value is five times the index, or $222,950. Each contract requires a margin of $11,200; • XAKU3 is quoted 1761.40 on the same day. Its notional value is 100 times the index, or $176,140. Each contract requires a margin of $9,500. • The spread trade would consist of 4 long ES futures and 1 short XAK futures. If an investor already had investment in S&P component stocks, he could hold on to them. However, the investor could consider shorting XAK futures to hedge the downside risk. For every $600K in stock investment, hedge it with 1 short XAK position. The logic of this trade is that if the tech sector gets into trouble, the short XAK trade would protect the value of long stock positions. Happy trading. Disclaimers *Trade ideas cited above are for illustration only, as an integral part of a case study to demonstrate the fundamental concepts in risk management under the market scenarios being discussed. They shall not be construed as investment recommendations or advice. Nor are they used to promote any specific products, or services. CME Real-time Market Data help identify trading set-ups and express my market views. 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
CME_MINI:ES1!Long
by JimHuangChicago
AMD -> Wait For This SupportHello Traders, welcome to this free and educational multi-timeframe technical analysis. On the weekly timeframe you can see that AMD stock is currently retesting and already starting to reject a quite nice previous weekly resistance area at the $130 level. You can also see that the overall uptrend is still valid, after the recent 50% pump AMD is definitely ready for a correction though so I am now just waiting for a correction back to the next support zone at the $105 level before I then do expect more continuation towards the upside. On the daily timeframe you can see that market structure is still bullish, I am also not really interested in actually shorting AMD, instead I am waiting for a retest of the $105 area and some bullish confirmation and then I do expect another rally towards the upside from there. Thank you for watching and I will see you tomorrow! You can also check out my previous analysis of this asset:
NASDAQ:AMDLong
by basictradingtv
39
Nvidia -> The Final ConsolidationHello Traders, welcome to this free and educational multi-timeframe technical analysis . On the weekly timeframe you can see that over the past 150 days Nvidia stock is actually up about 200% and is therefore definitely ready for a short term correction. You can also see that we do have the next previous resistance zone which is now turned support exactly at the $325 area so I am now just waiting for Nvidia to actually retest this zone and then I do expect more continuation towards the upside. On the daily timeframe you can see that Nvidia stock is currently stuck in between support and resistance - nothing too interesting for now, I am just waiting for a break below the previous support area at $375 and then I do expect Nvidia to fill the gap and retrace back to the $325 level. Thank you for watching and I will see you tomorrow! You can also check out my previous analysis of this asset:
NASDAQ:NVDAShort
by basictradingtv
45
AI - worth a watchThis is a stock I've recently bought, based on the technical readings alone. Fundamentally it may not be worth a long term hold, but I do believe it's a good trade opportunity. As you can see we had a falling wedge and breakout on the weekly with weekly bullish divergence on the RSI. We are currently over the 18 on the week , so bias is up. However, we also just reached the weekly BB, so some resistance here is to be expected. If they can hold 12 dollars, this may get a bounce to at least 20 and if it really takes off, 34 and possibly 50. There's no volume but it does seem to be finishing a base here. I can't guarantee if this is an area to buy, but I do recommend this stock as a watch in 2023.
NYSE:AILong
by the_sunship
14
PATH - Rising Volume Lifts PricesOn the 4H chart PATH was on a trend down in April. The strength momentum ( green band) was in a narrow range. In May as can be seen on the indicators, both volume and more especially volatility have increased significantly. The chart pattern is now that of an upward facing megaphone reflecting the volatility. The strength momentum band is much wider. Price is above the POC line of the volume profile reflecting a bullish dominance. Fundamentally, PATH is a player is the exploding AI subsector. Cathie Wood is quietly accumulating shares for her ETFs as are many other large portfolio investors. In summary, PATH appears to be an excellent long setup. Sitting in the shadows of NVDA, MU, TSM and others whose focus is hardware, PATH provides software and services it. Its path to hypergrowth and so price appreciation appears to be abundantly clear.
NYSE:PATHLong
by AwesomeAvani