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Nvidia Adds $330 Billion in a Single DayNvidia's stock valuation skyrocketed, adding $330 billion in a single day, surpassing its prior record gain of $277 billion. This increase was fueled by Microsoft announcing a 60% increase in AI spending for 2024, totaling $69 billion. Consequently, Nvidia's stock price surged nearly 13%, elevating its market cap to $2.88 trillion and making it the third-most valuable company globally, behind Apple and Microsoft. Despite this record-setting performance, Nvidia faced a tumultuous July, with its stock price decreasing by 16% throughout the month, closing down 5% despite a partial recovery. This decline reflected broader market volatility, as seen in the Nasdaq’s 1.5% drop. On Tuesday, Nvidia's shares dipped 7%, testing the crucial $100 support level. However, the positive response to Microsoft's investment suggests Nvidia might maintain its momentum above this critical threshold. Last month, the stock hit multiple highs, peaking at $140 on June 20, indicating strong market confidence. For Nvidia to surpass this record high, its stock would need an additional 20% gain. If you enjoyed this post, make sure to like, and follow for more quality content! If you have any questions or comments, comment below. We reply to every comment! See below for more information on our trading techniques. As always, keep it simple, keep it Sublime.
NASDAQ:NVDALong
by Sublime_Trading
How to Use Artificial Intelligence for Stock TradingHow to Use Artificial Intelligence for Stock Trading As you may know, AI can mimic human intelligence and make decisions based on data analysis. Artificial intelligence can be used in stock trading to analyse historical market and stock data, generate investment ideas, form portfolios, and automatically buy and sell stocks. AI is able to quickly process huge amounts of data and make informed trading decisions. AI-based trading strategies can be used to identify patterns and trends in real time. This FXOpen article explores the process of using artificial intelligence in stock trading and highlights the pros and cons of AI automated trading. How Does Trading with AI Work? Using AI for trading stocks is a relatively new practice. AI analyses markets with accuracy and efficiency and makes forecasts that help traders mitigate risks and provide higher potential returns. Here’s an overview of how AI stock trading works. The first stage needed for an AI model to function properly is robust data collection and preprocessing. This stage is akin to gathering raw materials to create a final product. During the second stage, specialists load historical data and algorithms into the model, which serve as the basis for identifying trends and price fluctuations that took place in the past. This way, the model obtains the information it will then analyse and learns how to analyse it. During the third stage, the model uses real-time data from various sources, such as financial news and economic indicators, to make forecasts. As new data becomes available, the models can be adjusted and refined. The best AI stock trading software can only be created using cleaned, structured, and prepared data. The final stage includes making trading decisions, such as when to buy or sell stocks, based on the processed data. AI systems can execute trades automatically. AI can also manage investment portfolios by adjusting the allocation of assets depending on market conditions. What to Look Out for When Using AI in Trading When creating an AI system for trading, choosing the most appropriate algorithm is of paramount importance. There’s a wide range of algorithms; for example, support vector machines (SVMs) are well suited for classification tasks and recurrent neural networks (RNNs) for sequence prediction. The choice of algorithms depends on trading goals and the type of data a trader will be working with. It’s a good idea to look at performance metrics such as accuracy, precision, recall, and F1 score to determine which algorithm is the best fit for your trading strategy. If you decide to implement AI in stock market trading, you’ll need to pay attention to a few things that will allow you to minimise risks. Risk Management and Control Although AI offers many benefits in trading, it creates a new set of risks, in particular, the risk of automated decision-making. It’s important to have human oversight to ensure that the AI is making informed decisions. Human expertise helps identify potential risks and adjust the AI model as needed. Traders can take precautions, such as setting stop-loss and take-profit levels, to make sure that AI algorithms do not cause excessive losses. Data Quality Poor-quality data can lead to inaccurate predictions and incorrect trades. It’s important that the data uploaded to the system is accurate, relevant, and up-to-date and that the AI stock market trading software provider is trustworthy and reliable. Ideally, an AI system will continuously analyse incoming data and adapt to changing market conditions. For example, if an unexpected economic event occurs, the AI model must be capable of adjusting its strategies in real time. Regulatory Compliance The adoption of AI in trading also brings forth regulatory challenges. When using AI, it is critical to comply with financial regulations to avoid legal issues. This includes ensuring that the AI model is transparent and explainable and that it does not engage in illegal activities such as insider trading. AI trading strategies should comply with all relevant laws. Case Studies and Examples One real-life example of successful AI adoption in trading is the case of the hedge fund Renaissance Technologies, which uses proprietary trading algorithms based on artificial intelligence. The New York-based hedge fund has a reputation as one of the most successful investment companies in the world using AI. Bridgewater Associates, also one of the world’s largest hedge funds, uses AI to analyse market data and make trading decisions. The fund has been successful in using AI to identify patterns and trends in market data. The third example is the use of AI in high-frequency trading. High-frequency trading involves using algorithms to execute trades at high speed. AI makes it possible to execute trades with speed and accuracy that exceeds human capabilities. Benefits and Challenges of AI Trading The new technology has both advantages and pitfalls. Here’s a table summarising the benefits and challenges of using AI algorithmic trading. Benefits - Increased efficiency - Improved accuracy - Effective risk management - Real-time analysis - Diversified trading strategies - Enhanced liquidity management and execution of large orders - Improved decision-making Challenges - Low-quality data - Overfitting - Limited human oversight - Compliance with financial regulations - Cost - Potential for increased complexity - Potential for reduced transparency Using AI can result in increased efficiency, improved accuracy, effective risk management, and much more. Of course, there are other ways to analyse the market. For example, on the TickTrader trading platform, you can trade using advanced tools for analysing and assessing risks. Data quality issues, model overfitting, and limited human oversight are the potential risks that can hinder the effectiveness of trading. To mitigate these challenges, consider validating data, testing the model, and adapting to evolving market conditions. Final Thoughts AI allows traders to analyse vast amounts of data, identify patterns, and make informed decisions quickly. However, it’s important to manage and control the risks associated with the use of AI in trading. Carefully consider the challenges and limitations and endeavour to take steps to mitigate them. You can open an FXOpen account to start trading, and as you gain experience, consider implementing advanced technologies, including AI. This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
NASDAQ:TSLAEducation
by FXOpen
6
Microsoft Earnings Raise Fears Over AI Spending. Bubble Go Pop?Playing catch-up is big among the highflyers of technology as the Magnificent Seven club races to slurp up AI demand. But is AI spending going to lead to AI bonanza? It’s not that straightforward. Microsoft (ticker: MSFT ) reported its earnings update for the spring quarter Tuesday after the closing bell. But it failed to appease investors who seem to be waking up to a reality where the billions of dollars jammed into artificial intelligence might not that easily convert into coveted profits. The AI-optimistic large-cap behemoth has spent piles of cash on advancing its artificial-intelligence capabilities without much to show for it. Markets punished the stock in after-hours trading with shares diving as deep as 8% — a drop that later recovered but still lingered under the flatline. “Throw Some AI in There, They’ll Love It” You know how much CEOs love to throw AI in their earnings calls? Microsoft boss Satya Nadella praised the company’s AI efforts in the call with shareholders but even the overuse of AI couldn’t bring the feelgood factor. Microsoft’s AI-powered cloud business, Azure, grew 29% in the three months to June, falling short of expectations and undershooting the 31% growth in the previous quarter. The company rushed to patch it up and assuage spooked investors, saying the slowdown was due in part to demand for AI running ahead of capacity. Microsoft: Throws $55.7 billion in capital expenditures. AI: * giggles, burps * "Thanks for the cash." For the past three months — the company’s fiscal fourth quarter — Microsoft saw its capital expenditures balloon by almost 80% year-over-year to $19 billion. Moreover, for fiscal 2024, total capital expenditures, or how much the company spent on new stuff, hit $55.7 billion — a figure that is likely to get surpassed next year as Microsoft projects increased spending on AI. Microsoft’s quarterly results are the latest example, after Google’s (ticker: GOOGL ) flop of an earnings report and Tesla’s (ticker: TSLA ) profit-squeezing quarter , of Big Tech’s lofty aspirations when it comes to AI. And the pushback reaction from investors shows that expectations are so high, it’s near-impossible to beat them. Big Tech is racing to build out the infrastructure layer that will allow AI to scale so it can start churning out a profit. But the going has recently gotten tough. The Magnificent Seven club of tech mainstays washed out more than $1.5 trillion from its collective market value in the past three weeks. The question that lingers on investors’ minds right now is how long can markets stay patient before they see revenue growth from AI materialize? Let Us Know Your Thoughts! With all the hype around AI, do you see a bubble in the works? Or justified no-froth, no-nonsense valuations? Share your thoughts below!
NASDAQ:MSFT
by TradingView
23
Amazon at $2 Trillion: What’s Driving the Stock to Record Highs?Tripled profits, a bet on AI, and a strategy to take on rising rivals from the East have propelled the ecommerce and cloud computing giant to the lofty price tag. Innovation on Amazon’s Mind Amazon (ticker: AMZN ) hit $2 trillion in market value just before the year clocked out for the first half. In the final week of June, the Jeff Bezos-founded online retailer soared past the formidable milestone, becoming the fifth company to ever breathe the rarefied air beyond $2 trillion. What’s been driving Amazon stock to line up right after Alphabet (ticker: GOOGL ), Nvidia (ticker: NVDA ), Apple (ticker: AAPL ) and Microsoft (ticker: MSFT )? It’s a mix of fortunate and timely events, and all can be summed up with one word: innovation. Amazon raked in sky-high profits of $15 billion for the most recent quarter. The figure was up three times from the same quarter last year. More importantly, the company, now under the stewardship of Andy Jassy as chief exec, is pivoting more resources to meet the growing demand for artificial intelligence. Shifting Focus to Artificial Intelligence Amazon Web Services (AWS) is the firm’s cloud computing business and also the world’s biggest one. It’s largely the cash cow at Amazon with profit margins as wide as 38%. Now, it’s getting a boost from businesses looking to inject AI into their products and services. The fast-growing AI-focused unit is growing at a “$100 billion annual revenue run rate,” according to Jassy. For the quarter ended March 31, AWS sales rose 17% to $25 billion, beating forecasts for $24.5 billion and also coming ahead of the previous quarter’s 13% growth pace. It seems that the AI hype is sweeping across the Amazon halls and conference rooms. Generative AI got praised by Amazon’s chief financial officer Brian Olsavsky as “a multibillion-dollar revenue run rate business for us.” Looking for a meaningful edge doesn’t stop with artificial intelligence. Pitted Against Temu and Shein Rising ecommerce competition from the East is forcing the $2 trillion giant to embrace a new line of business — ultra-low-cost goods shipped directly from China. A new discount section is in the works for Amazon.com after smaller rivals Temu and Shein have threatened to slurp up a significant market share. The new section, according to reports, will be added to the homepage of the retailer’s app. It will be targeting American customers willing to wait nine to 11 days for goods shipped from China warehouses, as opposed to the regular one or two-day delivery time for goods delivered from within the US. Also, each item will get a price tag of no more than 20 bucks. Temu, owned by PDD Holdings, and China-founded Shein have flooded the internet with cheap stuff and massive discounts thanks to splurging billions of dollars in advertising campaigns. Amazon, a mainstay in the FAANG stocks list , is among the few companies to be of gargantuan size yet nimble enough to stay relevant in the changing landscape of its industry. Will the pivot to cheap goods succeed in stamping out the aggressive competition from China? Or will the corporate giant be outperformed by the brilliant maneuvering of low-caliber foreign retailers? Share your thoughts in the comments!
NASDAQ:AMZN
by TradingView
5
DELL moves higher in continuation LONGDELL on the weekly chart shows its bullish trend which accelerated this past March as shown on the Prive Volume Trend. The relative volume indicator shows some spiking blue volume bars of buying volume = 3 of the 13 weeks in the past quarter. I see this as a long swing trade or even an investment to hold at an easy to get into price compared with SMCI. DELL may be a bit overbought and overextended but I am convinced it is for good reasons and that a trade here will pay profit over time. The dip of 5% in the past trading day provides a good entry.
NYSE:DELLLong
by AwesomeAvani
Bittensor the Bitcoin Of Artificial IntelligenceElliot Wave Pattern: The chart shows an Elliot Wave pattern in which waves 1, 2, 3, 4, and 5 are identified. Currently, the price is in the corrective area of ​​wave C. This implies that the correction may be nearing its end and a potential reversal towards the next impulsive wave may occur. The next rally will be the very impulsive based because we are in major wave 3. Fibonacci Retracement: The price is currently around the 0.618 (approx. $308.16) and 0.5 (approx. $393.81) Fibonacci retracement levels. This level is often considered a strong support level in technical analysis. If the price manages to stay above this level, a significant upward movement is likely. Bullish Divergence on RSI: The RSI (Relative Strength Index) indicator shows a bullish divergence, which means that even though prices are falling, purchasing power is starting to increase. This is often a signal that the price will reverse upwards. Price targets: Potential price targets based on Fibonacci extensions are approximately $1,003.05 (1.618) and $1,409.51 (2.618). This indicates the potential for a large increase from the current price if a reversal occurs. EMA (Exponential Moving Average): The price is currently below the 21-day EMA, which serves as dynamic resistance. A break above this EMA will provide additional confirmation that an uptrend is underway. Taking into account the factors above, TAO/Bittensor has the potential to experience a significant increase if the price manages to stay above the critical support level and there is confirmation of the bullish divergence on the RSI.
Long
by CryptoWizard_
1
PLTR: Potential Giant H&SIt's not quite there, but it's certainly on track... don't take this as a prediction of the future because well that's impossible. Lot's will need to line up for this to occur but so far so good. Retailers selling off, institutions are buying, and the company is growing 20% YoY. If growth improves near the 14-15 dollar levels, we could see a very bullish reversal. If we get down to the 15's, I think it would be a blessing. Best of luck y'all. This isn't trading advise. Make your own decisions. This is just some fun technical analysis.
PLong
by HassiOnTheMoon
Economic Overview | The "Yellowstone Bubble"On Thursday, May 16th, I was sipping coffee and watching The Today Show , when a guest appeared on the program to talk about how much money YOU are supposedly making in your 401(k). Oddly enough the commentator - who was identified as the "chief business correspondent for CNN" - then reminded viewers that "you really should only look at your 401(k) once or twice a year".... What?....WHAT? My first thought: we don't need to be lectured on how often we should be checking on our retirement funds. But this got me thinking, WHY do these "professional money managers" insist that working people not pay attention to their money?? I am speculating here, but I assume it is because retirement fund managers (large investment institutions) are also in the business of making money and therefore TAKING PROFIT. Is there any evidence for this?... Well, yes: Now factor in all of the nonsense that is constantly pumped by television commentators, meme stock pumpers, crypto fantasies, immature CEOs, and more recently - celebrities and professional athletes. Have you ever stopped to think about the fact that there is a television commercial for $QQQ... Things have become so obscene that money managers are paying for airtime to deceptively lure regular people into buying their securities, so they can take profits, after already receiving bailouts. You've seen it, there are several versions of the same commercial and the narrative goes something like "I'm investing in QQQ for the future". The Unemployment Rate has bottomed - there is no more growth to be had and even if we were to see unemployment trend below 3%, we can go back to the early 1950s and 1960s to see that financial markets really DON'T return much more below 3% unemployment; again this is because there is no more growth below 3% and therefore marginally less return. Credit card delinquency is rising rapidly, thanks to inflation from Covid helicopter money. And Household Debt-to-GDP has also bottomed. This one is particularly concerning because as we just explained, there is no more growth to be achieved from here (UNRATE). So, ask yourself: what happens if GDP falls ? Answer: household debt as a proportion of GDP rises by at leas that amount (it's a ratio - it has no choice). Expanding on this question, ask yourself: what happens if household debt continues to rise, amid maxed out unemployment? Answer: the already record profit-margins of investment banks increase to highly unstable levels, thereby further incentivizing profit-taking. Anyway, I am calling this market the Yellowstone Bubble . Everyone is a rich tough-guy cattle rancher, everyone is a crypto professional, everyone thinks "Tesla is the future" (LOL), everyone is an AI expert, everyone is a pro because they scroll forums and listen to some podcast. In a world that runs on "users" and "clicks" and web traffic, you must remain vigilant! Take care!
FRED:UNRATEShort
by ChiefMacro
OpenAI’s search engine: Implications beyond GOOG stockOpenAI has denied rumors claiming it's set to reveal an AI-powered search engine for its flagship chatbot, ChatGPT, on Monday. Although there is speculation that OpenAI is being a bit of a wise guy, and the product it will demo is not a search engine, but what they might dub as the next generation of search engines. It will be interesting to see if this product, whenever it is first demonstrated, is anything Google will have to worry about. According to Bloomberg, OpenAI’s search tool will be partly powered by Microsoft’s Bing search engine. Make of that what you will. Either way, this could likely ratchet up competition with Google and the market might have already begun to price in this risk to GOOG stock. But what other stocks could face a negative or positive risk from this development? Maybe we can ask ChatGPT: “Online advertising companies: Companies that heavily rely on Google's advertising platform for revenue could face challenges if advertisers shift their budgets to the new search engine. This includes companies like The Trade Desk (TTD), Magnite Inc. (MGNI), and Criteo S.A. (CRTO). E-commerce platforms: Google's search engine is a major source of traffic for many e-commerce platforms. If a rival search engine gains popularity, it could impact the flow of traffic and potentially affect revenue for companies like Amazon (AMZN), eBay Inc. (EBAY), and Shopify Inc. (SHOP). Payment processing companies: Google's search engine facilitates e-commerce transactions, which benefits payment processing companies like PayPal Holdings Inc. (PYPL) and Square Inc. (SQ). If a rival search engine affects e-commerce traffic patterns, it could indirectly impact payment processing companies. Digital marketing agencies: Companies that specialize in search engine optimization (SEO) and search engine marketing (SEM) services may see a shift in demand if advertisers allocate resources away from Google towards the new search engine. Examples include companies like WPP plc (WPP) and Omnicom Group Inc. (OMC). Data analytics companies: Google's search engine generates vast amounts of data, which is valuable for analytics purposes. If a new search engine captures market share, it could impact data analytics companies that rely on Google's data for insights. Companies like Nielsen Holdings plc (NLSN) and The Dun & Bradstreet Corporation (DNB) could be affected. Online review platforms: Google's search engine plays a significant role in driving traffic to online review platforms like Yelp Inc. (YELP) and TripAdvisor Inc. (TRIP). A new search engine could potentially change the dynamics of online reviews and impact these platforms' user base and revenue streams.”
NASDAQ:GOOG
by BlackBull_Markets
AAPL in Risk of Bear MarketApple is having a tough period with weakening China demand, lack of growth and innovation, AI lag, regulatory challenges that threaten its lucrative walled garden business model and other headwinds. These challenges weigh on the stock, which shed more than 10% in the first quarter. Along with Tesla, they were the only stocks to fall, among the Magnificent Seven. The situation deteriorated further in April, as AAPL hit the lowest levels in a year and is now in risk of a bear market . Moves below $160 would mean losses of 20% and more from the December record high, which is generally viewed as the threshold for a bear market. On the other hand Apple is still one of the most valuable companies in the world and investors are unlikely to give up on it and there are reasons for optimism. iPhone sales have shown resilience and the smartphone market is poised for a rebound. Its CEO appears determined to not let China fall, but also looks to India, which has significant untapped potential. Apple also launched the Vision Pro AR headset this year, looking for an early entry to a nascent market, while AI progress could be showcased soon. AAPL is having a good week and although we could see further rebound, the upside contains multiple roadblocks. Closes above the EMA200 would be required for the downside momentum to halt. The stocks trajectory will be influenced by the upcoming earnings report, which is due on May 2. Top and bottom lines, China & India performance, guidance and AI progress, will be some of the focal points. Stratos Markets Limited (www.fxcm.com): CFDs are complex instruments and come with a high risk of losing money rapidly due to leverage. 68% of retail investor accounts lose money when trading CFDs with this provider . You should consider whether you understand how CFDs work and whether you can afford to take the high risk of losing your money. Stratos Europe Ltd (trading as “FXCM” or “FXCM EU”), previously FXCM EU Ltd (www.fxcm.com): CFDs are complex instruments and come with a high risk of losing money rapidly due to leverage. 73% of retail investor accounts lose money when trading CFDs with this provider . You should consider whether you understand how CFDs work and whether you can afford to take the high risk of losing your money. Stratos Trading Pty. Limited (www.fxcm.com): Trading FX/CFDs carries significant risks. FXCM AU (AFSL 309763). Please read the Financial Services Guide, Product Disclosure Statement, Target Market Determination and Terms of Business at www.fxcm.com Stratos Global LLC (www.fxcm.com): Losses can exceed deposits. Any opinions, news, research, analyses, prices, other information, or links to third-party sites contained on this video are provided on an "as-is" basis, as general market commentary and do not constitute investment advice. The market commentary has not been prepared in accordance with legal requirements designed to promote the independence of investment research, and it is therefore not subject to any prohibition on dealing ahead of dissemination. Although this commentary is not produced by an independent source, FXCM takes all sufficient steps to eliminate or prevent any conflicts of interests arising out of the production and dissemination of this communication. The employees of FXCM commit to acting in the clients' best interests and represent their views without misleading, deceiving, or otherwise impairing the clients' ability to make informed investment decisions. For more information about the FXCM's internal organizational and administrative arrangements for the prevention of conflicts, please refer to the Firms' Managing Conflicts Policy. Please ensure that you read and understand our Full Disclaimer and Liability provision concerning the foregoing Information, which can be accessed via FXCM`s website: Stratos Markets Limited clients please see: www.fxcm.com Stratos Europe Ltd clients please see: www.fxcm.com Stratos Trading Pty. Limited clients please see: www.fxcm.com Stratos Global LLC clients please see: www.fxcm.com Past Performance is not an indicator of future results.
NASDAQ:AAPLShort
by FXCM
Why did HPE Breakout?As shown on the one-hour chart, in the last trading session, HPE broke out of its usual trading the range being the blue high-volume area on the profile. This is with increased volatility as shown by the indicator and the large top wicks on the rising green candles. Why did this occur? Were traders simply buying anything in the IT sector vaguely related to AI after the NVDA breakout? Does HPE have a role in artificial intelligence? Was this a sympathy play? The Luxalgo Supply / Demand indicator shows supply immediately overhead. The wicks on the last several candles show a defined level. This might be called a " tweezer top " Overall, I see this as an excellent short setup to be played with either short selling or a put option as the retracement seems inevitable.
NYSE:HPEShort
by AwesomeAvani
NUNET #NTX AI Crypto SEXY chart , sexy category DYOR from my 2 mins of research ; I doubt a real usage of graphic card buying and renting going on through this platform A SCAM if u will but that really doesn't matter for the price going forward if you only plan to ride a up wave... and not marry the bag. Maybe one of these platforms will actually be used to provide decentralised compute RNDR, GPU right ?? are those real? who knows like I said doesn't matter the chart looks good So that's why I am sharing it.
by BallaJi
7
SoundHound AI $SOUN - Artificial Intelligence is on the rise!SoundHound AI - Everybody is talking about Artificial Intelligence (AI). The social media buzz is all about AI. The world is asking questions like: What are the possibilities? How far will AI go in its reach into day-to-day society? Meanwhile, AI stocks like NASDAQ:SOUN are becoming more and more popular. If SoundHound's stock price makes it to the $9.00 key zone, it will be 100% away from the all-time high. Can the media buzz propel SoundHound AI to new heights?
NASDAQ:SOUNLong
by PortfolioBuildersClub
1
PLTR pre-earnings play LONGPLTR has earnings on February 5 while on the 120 minute chart, the price action is that of a rising wedge with price compressing between a rising support trendline and a falling resistance trendline the extension of the neckline of the head and shoulders pattern of November. PLTR fell today and is near and above support. In a long trade, I see the target as 18 ( at the resistance trendline) with a narrow stop loss just under the support trendline. This makes for a possible 6% profit with a very good reward-to-risk ratio. A call option for the 2/16 expiration striking $17 is also under immediate consideration.
PLong
by AwesomeAvani
14
♨ Nvidia stocks are heading Up to recover, after September meltNvidia stocks moved higher in early Monday trading after analysts at Goldman Sachs NYSE:GS added the chipmaker, along with three other stocks, to its flagship list of stock recommendations. Goldman Sachs analysts added Nvidia to the bank's "Americas Conviction List", a step up from the 'buy' rating it assigned to the stock in late August, while holding its price target in place at $605 per share. "Look for Nvidia to maintain its statues as the accelerated computing industry standard for the foreseeable futures given its competitive moat and the urgency with which customers are developing and deploying increasingly complex AI models," Goldman argued. The bank also added cybersecurity group Okta NASDAQ:OKTA , industrial supply group Cintas NASDAQ:CTAS and biotech Quanterix NASDAQ:QTRX to the "conviction buy" list while removing Salesforce NYSE:CRM and Johnson Controls NYSE:JCI . Nvidia, the world's biggest AI chipmaker, forecast current quarter revenues of around $16 billion in August when it published stronger-than-expected second quarter earnings and later unveiled an make it easier for clients to run AI applications on Google Cloud NASDAQ:GOOGL using Nvidia-made chips with deeper integration between hardware and software offerings. "We’re at an inflection point where accelerated computing and generative AI have come together to speed innovation at an unprecedented pace," said CEO Jensen Huang of the Google agreement. "Our expanded collaboration with Google Cloud will help developers accelerate their work with infrastructure, software and services that supercharge energy efficiency and reduce costs." Nvidia shares were marked 3% higher in early Monday trading to change hands at $ 448 /share. The stock is up more than 200% for this year, and reached an all-time high of $487.84 on Aug 29, 2023. Technical picture says, Nvidia NASDAQ:NVDA stocks are still on its positive path, and trading above 6- and 12-months simple moving averages. Moreover the key breakout of technical indicator known as "a Triangle" is happening right here as stocks are recovering form the bearish hug.
NASDAQ:NVDALong
by Pandorra
2
SNOWFLAKE breaking long time resistanceThere is a multi year resistance around $205 for NYSE:SNOW Signs I'm looking for: Top of channel to become support, a bounce off there and a move into $220 should confirm that. I want to see the SuperTrend indicator stay green, upwards of the level of where the red downtrend line exists. SuperTrends on higher time frame charts work the best. It's often pretty solid when used on individual stocks rather than an index. Take a look at the supertrend (strategy) and mess around with different time frames. You'll see the cumulative return is very high, often much higher than just buying and holding the equity. Let me know what you think : )
NYSE:SNOWLong
by DontSlamTheDoor
6
AI in trading - 6 hottest topics (part 2/2)Alternative Data ADs provide a better picture of a company's situation, raw materials, currencies. It also allows us to assess the "current state" (nowcasting) of significant indicators. Those data make trading signals better, more precise, less risky and more profitable. It is a revolution accompanying the AI revolution and even preceding it. In my opinion, it is more important today than AI, which is only in its early stages (despite many impressive achievements). In my opinion, through AD, funds can earn more and build their competitive advantage over others. ADs are not part of Artificial Intelligence. An example of AD is credit card sales data. This data can be used to predict the financial performance of companies. If we have historical data, then in the simplest case, to make forecasts, all we need is a spreadsheet! And when we are interested in more advanced indicators of future profitability, such as consumer spending patterns, brand loyalty, switching between products/brands, trending moods, competitors performance, models created using Machine Learning can come into play. With the increasing number of data sources and the complication of forecasting models, traditional ones will be replaced in a considerable part or even entirely by AI/ML-based models. For a broader discussion of Alternative Data, see the separate article in this issue. Visualization It is easier for humans to look than to think. "Analysis" by sight developed long before abstract thinking. There is something severe behind this remark. It is much easier for us to understand a situation when it is shown using images rather than just a verbal description. Therefore, as much as possible, use visual aids - graphics, pictures, diagrams, or charts to illustrate data, situations and processes. Indeed, it is good practice to consider what goal we want to achieve, define the target group and identify which parts of the message will benefit from such enhanced presentation. The same applies to respecting the simplicity of the message, playing with colours and ensuring maximum readability. Another good practice is to provide a benchmark, or reference point, to which we compare some quantity. Our mind performs better by observing the differences between some benchmarks and the current indication. An excellent practice is to make it easy for the audience to understand the situation quickly. Thus, when preparing visual aids, try to help them understand the situation as quickly as possible – for example: whether we are in the realm of "normal" or have already gone beyond it. All key, critical processes should have some sort of graphic representation. It should allow for a quick assessment of the situation, especially in unusual or crises. So let’s say I give you a colour scheme, where green means everything is going well, orange – attention required, and red – we have a critical situation. Sound familiar? It should. As AI matures, the amount of information and complexity of systems (and portfolios) will only increase. Therefore, using standardized metrics within a company to illustrate key processes is something worth developing as a valuable skill. Let me say it another way to emphasize the particular importance of this topic - the ability to graphically present important processes for a company is a competence worth developing. It is worth discussing what indicators to use, what types of graphs, what colours, and what schemes to facilitate and enhance understanding, ability, and speed of decision making. Visual communication is one of the essential elements of building and consolidating a company's structural intelligence. Automatization Automatization is the critical process underlying the use of artificial intelligence. It involves gradually learning and automating more functions of human intelligence. The ultimate stage of AI development in trading is full machine autonomy with a level of perception, "thinking", decision-making far exceeding human capabilities in every aspect. What does this mean for traders and funds now and in the future? Now Today, automatization is one of the main topics because it takes the burden of routine activities and responsibilities off the shoulders of traders. One of the main problems that traders complain about is excessive workload and information overload. The primary candidates for automation are routine activities that require no intellectual input. And over time, more and more activities will be automated - and more about that in a moment. Suppose we have a great trader. Only some of his activities add value, and he should focus on them. You can consider using supporting programs or someone else to help with the remaining tasks. What should not be automated are non-routine decisions, decisions in exceptional or critical situations and those requiring synthetic expertise beyond the reach of AI tools. Instead, you can automate the execution of decisions in critical situations with confidence. In an extreme situation, the trader only presses the appropriate key. A program then tries to escape from the market as quickly as possible. It tries to use liquidity, reduce costs and minimize the negative impact of the large order it exits. In nine out of ten situations, it will do this better than the trader and, in the case of substantial orders, in ten out of ten. Automatization will expand to include more and more activities, including non-routine ones, over time. In the future To understand what automatization in a fund will look like in the future, we must first learn the decision-making process of a discrete trader or automated system. The decision-making process consists of all the elements that lead from the initial analysis (what to trade and where to trade it) through the choice of location, entry, position management, exit, to post-trade analysis. There can, of course, be many more of these steps if we take a more detailed approach (and the largest funds do). Automatization here is about taking a single element of the decision-making process and trying to refine it first (to find the best practices) and then automate it. It would also be beneficial to provide a feedback channel so that we and, in time, the AI system can improve this element based on the incoming and analyzed data. In short, we want the system to learn on its own. In short, we automate best practices at each step and provide feedback so that the system learns and improves. On the other hand, entry automation may involve breaking positions into smaller ones, examining order structures above and below, creating and executing entry strategies to minimize cost and adversarial price moves. Hiding positions and maximizing positions for the best signals may also be part of the automation. Summary We have discussed six of the "hottest" topics currently occurring in the Artificial Intelligence field. Two are sure to be the most important: XAI and Alternative data. The first - because it opens up a powerful new trend of adjusting the latest tools to a trader's level of understanding. We already know that a gradient descent on a differentiable manifold tells him nothing. The second - because it is alternative data that gives traders and funds their main competitive advantage today. In conclusion, it is worth repeating one important thought: the AI revolution is just beginning. It will completely change our world and ways of investing. This process is incredibly fascinating. The New City Trader was born out of a desire to share this fascination. If you liked this post, give it a boost 🚀 and drop a comment so we know to publish more for you. Cheers! Follow: www.tradingview.com
Education
by drSwierk
AI in trading - 6 hottest topics (part 1/2)In this article, you'll learn about six of the most critical and "hottest" elements that make up or are associated with AI today. In addition, you'll learn the basics of the tools that will shape the future of trading. First in the biggest and wealthiest funds and then in smaller ones as well. I invite you to take a journey into this near and far future of trading. NLP Natural Language Processing is the common name for many tools to analyze written and spoken text: company documents, press articles, news, analysis, web pages, social media posts, company’s product reviews. Advanced NLP software recognizes context up to about a thousand words. That's a lot, and soon, there will be more. NLP allows you to analyze many features of text, such as: - whether the text about a particular company is positive or negative, - whether it is clear and transparent or obscure and convoluted, - whether the authors express themselves positively or negatively about the future. When we analyze texts of reports and press statements, it turns out that all of the above elements can be a good indicator of future financial performance. Social media texts Already now, the analysis of posts in social media and online shops allows determining the sentiment - the opinion about the company and its products, which usually precedes the financial results. Sometimes it is also possible to find and analyze the sentiment of different investor groups about the company and its future which also affects the share price. "The stripper that will change our World" The next gigantic step in the evolution of NLP come from extracting written knowledge from millions of books, academic articles and other texts and help create coherent theories of how the economy, or supply chains, works. This development will give theoretical and practical insights into the factors that affect the financial performance of companies, industries and all relevant economic processes. Already today, we see the first signs of the creation of such tools. Spoken text NLP also covers spoken word analysis: statements from TV news, films, other video material, or telephone conversations are automatically transcribed and subject to the same analysis as written content. Thanks to this, we now have access to knowledge about the level of Forex volume. The systems analyze the volume at major banks and brokers and traders' volume over the phone. Until last year, data on this was not available in real-time. I will find out if anything has changed yet and write about it in future issues. I know that there were plans to provide this volume in real-time as well. Machine Learning Machine learning is dozens of tools for machine problem-solving. But today is different than you might think. We are in the first phase of the evolution of these tools. To understand this and to understand their potential, I will give a practical example: how does solving a problem using machine learning tools look like... In simple terms: 1. the process consists of problem formulation and preparation of a mathematical model (specialist), 2. further collection and preparation of data (specialist), 3. selection of one of the ML solutions (specialist), 4. feeding the software with data (specialist), 5. data processing (software), 6. finally, we have the interpretation of the obtained result (specialist) - someone has to explain the result in non-mathematical terms. Only one element of this sequence is automated - the fifth. All the rest requires the use of specialists' knowledge and experience. Today, the real driving engine of AI is... the specialists. And it will remain so for a long time to come. "Real AI" is still very, very scarce. Over time, each step will be done automatically. Only then will we see the true power of machine learning and AI. We are at the beginning of this journey, the first stage of evolution (and I believe there will be five). I didn't want to start this thematic series by describing ML tools. I preferred to show their current place in general. In the future, I will describe some Machine Learning solutions and how they are used to create trading systems. I will also give examples of such systems so that you can form your own opinion about them. What is worth knowing is that despite the impressive achievements of AI-related technology, this is just the beginning of this revolution. It will change everything we know. We are only at the beginning of the AI revolution. It will change everything we know. XAI or Explainable AI It is currently probably the hottest topic in AI. Some ML tools are so complex that we don't know how the machine got the result, how it made the decision or the recommendation. We call them "black box" for short - it's dark inside, and we don't know what's happening there. Nevertheless, the math behind it is excellent, and the results are often astounding. So, we have a result, but we don't know how it was achieved. We don't know because the process leading to the development is very complex and has many steps. And if we don't understand "how it works", then several problems arise. I will describe them for the case where we have a black-box that gives input and output signals: - beyond simply allocating a small % of capital to the position, risk management becomes problematic; - we have little or no control over the position (except for the exit); - we don't get the most out of a tool we don't trust. And this is a problem when we have spent several million in its creation; - we don't know if a given series of losses is temporary because the market has changed, or maybe the system has stopped working for a given market. So it will only lose from now on. And since the results are good, we will try to explain how it works in one way or another. The problem of finding an explanation and education for exploiting the potential of AI will also run through the following issues. For a fund that employs traders, this problem is as practical as it gets. A trader in his seventies would like to know how much money can be made on a "black box." For example, let's take a trader who is 75 years old, active and, on top of that, a co-owner of a fund. And he would like to find out how "this new thing" works because it may be worth increasing the capital that this "new toy" has to use. But how, without knowing what's going on inside, define the trading framework? What risks to assume, a reasonable capital commitment, when difficulties arise, and what to do when they do? Moreover, after all, we have to adapt to the boss's scope of knowledge and experience. Thus, for example, we cannot start the lecture with the geometry of differentiable manifolds and Kullback - Leibler divergence for probability distributions (such mathematics can be used there) if he has no idea about it. It is a fascinating problem. Important enough that we are preparing for publication a broader article on this topic: how to explain and help traders understand new tools, in particular black-boxes. How to estimate risk, build confidence, define a framework in which they will feel safe with the new device. Someone who has an easygoing boss already thinks they can relax and not bother explaining the operating principle of their wonderful black box. But, unfortunately, this is not the case because other people on the horizon would like to know how it works. There are several groups of such people. Those who want or need to know what's going on inside The first would be the law regulators and the courts. The Financial Supervisory Commission may want to know if, by any chance, the recent large positions, as claimed by us placed by a "black box", are not an instance of insider trading. If you have a similar idea of defending yourself in court (from being accused of insider trading), then know that it makes no sense. We may not know what is inside, but the signal must appear again after simulating the conditions created by the signal. Then we have the risk management department, which would also like to know how it works or at least what it resembles. All they have left is to allocate a small amount of capital to the signal. A black box position is like a plane without windows. We take off on command, fly with no way to tell where we are and land on command. The only assurance of safety is the statistic that, for example, a position is profitable six times out of ten. This value means that we have four hard landings per every ten take-offs. It is a moderately comfortable situation, although in some cases, it will suffice. Has the system already stopped working? Now, we have something even less pleasant: if we do not know the rules of decision making, we cannot be sure that a given series of losses is not the end of the system because the market has changed and the previous rules no longer work. Exaggerated? Maybe, but only a little. The use of various AI tools will only grow, including black-boxes, and this has to be dealt with one way or another. The major funds already have some prescriptions for what to do. In future articles, I will describe them. The topic is even more important because, for the vast majority of non-mathematicians, i.e. traders, portfolio managers, C-level managers, practically every AI/ML tool is a black box. For some reason, explanations such as dealing with a multidimensional, differentiable manifold immersed in a vector space do not help. Explainable AI fits into a broader trend - most people and traders have no idea what new tools do. There is a great need to explain to users how AI/ML tools work, what they provide, their limits of use and when they stop working. Education is vital because a fund's competitive advantage will soon be created at the interface between the team and the tools, AI systems. Competitive advantage in the future will depend on the so-called structural intelligence of the company. The largest funds are already working in this direction, although they can not name it so cleverly. We will also devote quite a few articles to this in the future, which is one of this magazine's goals. If you liked this post, give it a boost 🚀 and drop a comment so we know to publish more for you. Cheers!
Education
by drSwierk