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Artificial_intelligence

How can AI help to improve algorithmic trading strategies?AI is transforming the field of algorithmic trading, which involves using computer programs to execute trades based on predefined rules and strategies. AI can help to improve algorithmic trading performance and efficiency by providing advanced data analysis, predictive modeling, and optimization techniques. In this article, we will explore some of the ways that AI can enhance algorithmic trading and some of the challenges and opportunities that lie ahead. One of the main advantages of AI in algorithmic trading is its ability to process and interpret large and complex data sets in real-time. AI algorithms can leverage various sources of data, such as market prices, volumes, news, social media, sentiment, and historical trends, to identify patterns, correlations, and anomalies that may indicate trading opportunities. AI can also use natural language processing (NLP) and computer vision to extract relevant information from unstructured data, such as text, images, and videos. Another benefit of AI in algorithmic trading is its ability to learn from data and adapt to changing market conditions. AI algorithms can use machine learning (ML) and deep learning (DL) techniques to train on historical and live data and generate predictive models that can forecast future market movements and outcomes. AI can also use reinforcement learning (RL) techniques to learn from its own actions and feedback and optimize its trading strategies over time. A further aspect of AI in algorithmic trading is its ability to optimize trading performance and reduce costs. AI algorithms can use mathematical optimization methods to find the optimal combination of parameters, such as entry and exit points, order size, timing, and risk management, that can maximize profits and minimize losses. AI can also use high-frequency trading (HFT) techniques to execute trades at high speeds and volumes, taking advantage of small price fluctuations and arbitrage opportunities. AI can also help to reduce transaction costs, such as commissions, fees, slippage, and market impact, by using smart order routing and execution algorithms that can find the best available prices and liquidity across multiple venues. However, AI in algorithmic trading also faces some challenges and limitations that need to be addressed. One of the main challenges is the quality and reliability of data. AI algorithms depend on accurate and timely data to perform well, but data sources may be incomplete, inconsistent, noisy, or outdated. Data may also be subject to manipulation or hacking by malicious actors who may try to influence or deceive the algorithms. Therefore, AI algorithms need to have robust data validation, verification, and security mechanisms to ensure data integrity and trustworthiness. Another challenge is the complexity and interpretability of AI algorithms. AI algorithms may use sophisticated and nonlinear models that are difficult to understand and explain. This may pose a problem for traders who need to monitor and control their algorithms and regulators who need to oversee and audit their activities. Moreover, AI algorithms may exhibit unexpected or undesirable behaviors or outcomes that may harm the traders or the market stability. Therefore, AI algorithms need to have transparent and explainable methods that can provide clear and meaningful insights into their logic and decisions. However, there are also ethical and social implications of AI in algorithmic trading. AI algorithms may have an impact on the market efficiency, fairness, and inclusiveness. For example, AI algorithms may create or amplify market inefficiencies or distortions by exploiting information asymmetries or creating feedback loops or cascades. AI algorithms may also create or exacerbate market inequalities or exclusions by favoring certain groups or individuals over others or by creating barriers to entry or access for new or small players. Therefore, AI algorithms need to have ethical and social principles that can ensure their alignment with human values and interests. In conclusion, AI is a powerful tool that can help to improve algorithmic trading strategies and performance by providing advanced data analysis, predictive modeling, and optimization techniques. However, AI also poses some challenges and risks that need to be addressed by ensuring data quality and reliability, algorithm complexity and interpretability, and ethical and social implications. By doing so, AI can create a more efficient, effective, and equitable algorithmic trading environment for all stakeholders.
BITSTAMP:BTCUSDEducation
by JS_TechTrading
AI and Algorithmic Trading #1AI and Algorithmic Trading #1 - Introduction to AI and Algorithmic Trading In recent years, algorithmic trading has become increasingly popular in the world of finance. Algorithmic trading refers to the use of computer programs to automate the trading process, including the analysis of market data, the identification of trading opportunities, and the execution of trades. As algorithmic trading has become more prevalent, artificial intelligence (AI) has emerged as a key tool for traders looking to gain a competitive advantage in the market. In this article, we'll provide an overview of AI and its role in algorithmic trading. What is Algorithmic Trading? Before we dive into AI, let's first define algorithmic trading. Algorithmic trading, also known as automated trading or algo trading, is a method of executing trades using computer programs. These programs can analyze market data, identify trading opportunities, and execute trades at a speed and efficiency that is impossible for human traders. Algorithmic trading can be used for a variety of trading strategies, including high-frequency trading, statistical arbitrage, and trend following. What is AI? Artificial intelligence refers to the ability of machines to perform tasks that would typically require human intelligence. AI can be divided into several categories, including machine learning, natural language processing, and pattern recognition. Machine learning is a type of AI that involves training algorithms to learn from data, enabling them to make predictions or decisions without being explicitly programmed. Natural language processing involves teaching machines to understand and interpret human language, while pattern recognition involves identifying patterns in data. Benefits of AI in Algorithmic Trading One of the key benefits of using AI in algorithmic trading is the ability to make faster and more accurate trading decisions. AI algorithms can analyze vast amounts of market data in real-time, identifying trading opportunities and executing trades with a speed and efficiency that is impossible for human traders. Additionally, AI algorithms can learn from their mistakes and adjust their strategies accordingly, leading to more consistent and profitable trading outcomes. Challenges of AI in Algorithmic Trading While the benefits of AI in algorithmic trading are significant, there are also potential challenges associated with this technology. One of the main challenges is the need for high-quality data. AI algorithms rely on large datasets to learn from, and if the data is incomplete or inaccurate, the algorithms may produce flawed results. Additionally, AI algorithms may be subject to biases, both in the data they are trained on and in their decision-making processes. Finally, there are ethical considerations around the use of AI in trading, particularly around the potential for AI to exacerbate market volatility or contribute to systemic risk. The Future of AI in Algorithmic Trading Despite these challenges, it is clear that AI will continue to play an important role in algorithmic trading in the years to come. As the technology continues to develop, we can expect to see even more sophisticated AI algorithms being used to analyze market data, identify trading opportunities, and execute trades. Additionally, we may see new applications of AI in areas such as risk management and portfolio optimization. Conclusion In conclusion, AI is an increasingly important tool for traders looking to gain a competitive advantage in the world of algorithmic trading. By using AI algorithms to analyze market data and make trading decisions, traders can operate with a speed and efficiency that is impossible for human traders. However, there are also potential challenges associated with using AI in trading, including the need for high-quality data and ethical considerations. As the technology continues to develop, we can expect to see even more sophisticated applications of AI in the world of algorithmic trading.
BITSTAMP:BTCUSDEducation
by JS_TechTrading
Trade talk with A.IQ1. Your Advise to the experienced traders. As an AI language model, I cannot provide personalized advice to specific individuals. However, here are some general tips that experienced traders may find useful: 1.1 Stick to your trading plan: Experienced traders know the importance of having a solid trading plan and sticking to it. Your trading plan should include your risk management strategy, entry and exit points, and profit targets. Avoid deviating from your plan based on emotions or market noise. 1.2 Continue learning: The markets are constantly evolving, so it's important for experienced traders to continue learning and adapting to changes. Stay updated with market news and events, learn new trading strategies, and be open to new ideas and perspectives. 1.3 Practice good risk management: Experienced traders understand the importance of managing risk. Make sure you understand risk management principles and use tools like stop-loss orders and position sizing to limit your risk. 1.4 Stay disciplined: Trading can be a stressful and emotional experience, but experienced traders know the importance of staying disciplined and keeping their emotions in check. Stick to your trading plan, avoid impulsive decisions, and don't let fear or greed drive your trading decisions. 1.5 Review and analyze your trades: Successful traders are always looking for ways to improve their performance. Take the time to review and analyze your trades, identify areas for improvement, and make adjustments to your trading plan as necessary. Q2. How to trade Head and shoulder patterns? 2.1 The head and shoulders pattern is a technical analysis pattern that is commonly used by traders to identify potential trend reversals. Here are the basic steps for trading a head and shoulders pattern: 2.2 Identify the pattern: The head and shoulders pattern consists of three peaks, with the middle peak (the "head") being higher than the other two (the "shoulders"). The neckline is a line that connects the lows between the shoulders. 2.3 Wait for confirmation: Once you have identified the pattern, wait for a confirmed breakout below the neckline. This confirms that the pattern is valid and increases the probability of a trend reversal. 2.4 Set a stop-loss: Place a stop-loss order above the right shoulder of the pattern to limit your risk if the market moves against you. 2.5 Set a profit target: Calculate the distance between the head and the neckline, and use this to set a profit target for your trade. 2.6 Monitor the trade: Monitor the trade closely and adjust your stop-loss and profit target as necessary. Q3. Do people get rich day trading? While it is true that some traders have become wealthy from trading, it is important to understand that trading is not a guaranteed path to riches. Trading involves risk, and losses are a natural part of the process. In fact, the majority of traders lose money, and only a small percentage are consistently profitable over the long term. Furthermore, becoming a successful trader requires a significant amount of time, effort, and dedication. It's not something that can be achieved overnight, and there are no shortcuts or easy solutions. In addition, it's important to have realistic expectations about trading. While it is possible to make money from trading, it is not a get-rich-quick scheme. Successful traders typically have a long-term perspective, and they focus on building consistent profits over time. In summary, while trading can potentially lead to wealth, it is not a guaranteed path to riches. Trading involves risk, requires a significant amount of time and effort, and success is not guaranteed. As with any other profession, success in trading requires hard work, dedication, and a commitment to ongoing learning and improvement. Q.4 Can you help someone to become a profitable trader? As an AI language model, I can provide educational information and guidance to help someone become a profitable trader. However, becoming a profitable trader requires more than just information and guidance - it requires a combination of knowledge, experience, discipline, and a commitment to ongoing learning and improvement. Some of the ways in which I can help someone become a profitable trader include: 4.1 Providing educational resources on trading fundamentals, technical analysis, risk management, and other key trading concepts. 4.2Assisting with the development of a personalized trading plan based on an individual's unique goals, risk tolerance, and trading style. 4.3 Offering insights into market conditions and potential trading opportunities across a range of asset classes. 4.4 Providing support and guidance on managing emotions and maintaining discipline in the face of market volatility and uncertainty. 4.5 Offering feedback and analysis on trading strategies and performance, with a focus on identifying areas for improvement and optimization. 4.6 It's important to note that becoming a profitable trader is a long-term process that requires patience, discipline, and a willingness to learn from both successes and failures. With the right guidance and approach, however, it is possible to achieve consistent profitability and success in the markets. Q5. Do prayers help in trading? As an AI language model, I do not have a religious belief, but I can provide a general response to your question. Prayer is a personal spiritual practice that may bring comfort and guidance to an individual. However, it is not a guaranteed method for achieving success in trading or any other activity. Trading success depends on a combination of factors, including knowledge, experience, discipline, and a sound trading strategy. It's important to approach trading with a rational and analytical mindset, rather than relying on external factors such as prayer or luck. While prayer may provide emotional support and help manage stress, it is not a substitute for a well-developed trading plan and disciplined approach to the markets. In summary, while prayer may have personal and emotional benefits, it is not a reliable or effective means for achieving success in trading. A disciplined and rational approach to trading, based on sound principles and a well-developed trading plan, is key to long-term success. Q6. How to trade triangle pattern? The triangle pattern is a common chart pattern that occurs when the price of an asset consolidates between two converging trendlines. Trading the triangle pattern involves identifying the breakout direction and taking a position in that direction. Here are some general steps to trade the triangle pattern: 6.1 Identify the triangle pattern: Look for a period of consolidation where the price moves between two converging trendlines, forming a triangle shape on the chart. 6.2 Determine the direction of the breakout: As the price nears the apex of the triangle, it will typically break out in one direction or the other. Look for a breakout that is accompanied by high volume and follow-through price action. 6.3 Enter a position: Once you have determined the direction of the breakout, enter a position in that direction. This can be done through buying or selling, depending on whether the breakout is to the upside or downside. 6.4 Set stop-loss and take-profit levels: It's important to manage your risk by setting stop-loss levels to limit potential losses and take-profit levels to lock in profits. These levels should be based on your risk tolerance and trading strategy. 6.5 Monitor the trade: Keep an eye on the price action after the breakout to ensure that it continues to move in your favor. If the price fails to continue in the breakout direction, it may be wise to exit the trade with a small loss. 6.6 Consider other factors: It's important to consider other factors, such as market conditions and economic events, that may affect the price of the asset. This can help you make more informed trading decisions. In summary, trading the triangle pattern involves identifying the breakout direction and taking a position in that direction while managing risk through stop-loss and take-profit levels. However, it's important to consider other factors that may affect the price of the asset and to monitor the trade closely to ensure that it continues to move in your favor.
Education
by Aadil1000x
INTUSDT technical Analysis From technical analysis wise, a clear breakout from a falling wedge on W & 3D frames, it is retesting, I think it will make 10x from here. According to INTchain twitter account: “The INT Chain Foundation officially announced that it will conduct in-depth research and expansion on AIGC and ChatGPT related technologies, with an ever-changing pace, profoundly, quickly, and thoroughly changing the existing IoT chain model.” That’s BULLISH but you need to keep in mind the following. 1- It’s a small cap project with huge potential but with a low liquidity “ manage your risks” 2- Take profit along the way and enjoy. Good luck
ILong
by BadrAAA
Intraday ES 22nd March - Gamma + Options + Darkpool analysisGEX: Positive Price above Gamma Flip Point - decreased Volatility Structure of Gamma: Mostly negative, spread across multiple strikes Expected Range: 3991 - 4077 Most probable end-of-day outcome: Price close above most negative gamma spikes (3990, 3940, 3840). Therefore Key Support is at 3940. Gamma Spikes chart from my AI Data Analysis software Yesterday's session was skyrocketing and honestly despite observing incoming Supply to the market near Resistance, price reacted weak to this area and after couple of hours continued to increase. As the result, we fulfilled most probable end-of-day outcome, but plan wasn't met accordingly to my expectations. Well, this is market magic 🙂 For today's session, we have similar expected end-of-day outcome where Support at 3940 is below bottom level of expected trading range at 3991. In general, on 3990 we see gamma spike, so this level works as significant support too. After climbing up, any supports are much lower than level of current price so seems the market can start shifting into Bullish sentiment. It's too early to confirm that, but something is happening. Let's keep observing. From Resistance perspective, we have spike at 4040. Plan for today's trades I marked on second chart attached to analysis. Good luck!
CME_MINI:ES1!
by skyline-trader
3
The End of an Era: Is Google's Reign Over?I believe that right now is an incredible time to short googles stock, The challenges facing it over the next few years could topple its position as an industry leader. Current price: 105.35 Target 1: 90.55 (-14%) Target 2: 74.50 (-29%) The regulatory scrutiny that Google is facing is a significant threat to the company's future. If the company is found guilty of antitrust violations, it could face substantial fines and restrictions on its business practices, which could lead to a loss of market share and revenue. Moreover, the negative publicity generated by these investigations could harm Google's brand image and reputation. In addition to regulatory scrutiny, Google is also facing increased competition from Microsoft's backed venture OpenAI. OpenAI is a major player in the artificial intelligence (AI) space, and is rapidly expanding its capabilities in natural language processing, computer vision, and other areas. As Google relies heavily on AI for many of its products and services, such as search and Google Assistant, increased competition in this area could pose a significant threat to the company's market position. These challenges have already had an impact on Google's stock price, which has fallen from its all-time high of $150.70 in November 2021 to its current level of $105.30. This decline is likely due in part to concerns about regulatory scrutiny and competition from OpenAI. Looking ahead, it is difficult to predict with certainty what the future holds for Google. However, it is clear that the company will need to address the regulatory concerns and navigate the increasingly competitive landscape if it hopes to maintain its market position and continue to grow. If it can successfully address these challenges and continue to innovate and adapt, Google could emerge from this period of uncertainty even stronger than before. However, if it fails to do so, its stock price could continue to decline, and its market position could be threatened.
CAPITALCOM:GOOGShort
by Helios_Capital_Investment
2
FET/USDT Soon to break from triangle?This is how i would trade FET/USDT. The chart shows that the price movement occurs within a bullish triangle. Enter a long position when/if the price out of the triangle to the upside. -------------------- Targets: 1: 0.47 2: 0.5 3: 0.52 4: 0.55 5: 0.57 6: 0.59 Trade safely! -------------------- About Fetch.ai: "Fetch.ai is an AI-backed blockchain environment that helps users create a decentralized digital economy within a single ledger. Users can create agents that act on the behalf of individuals, organizations, devices, and services. All these agents are connected and can make transactions and communicate with one another." Source: kriptomat.io
Long
by Droz_TA
5
RU AI? Elliott WaveIf you find this info inspiring/helpful, please consider a boost and follow! Any questions or comments, please leave a comment! Also, check out the links in my signature to get to know me better! This would be the BEST case scenario. Lots of ways to count but again this is the count with the quickest turn around. Because of the lack of conviction, it has to prove the turn to me. $3.00 is the ideal area for this idea. Then it need to put an impulse up with a correction facing down as illustrated. Cheers!
NYSE:BBAILong
by CryptoKnee
Disinflation – Fact or Fiction?CME: S&P Technology Select Sector ( CME_MINI:XAK1! ) The U.S. consumer price index (CPI) rose 0.5% in January and +6.4% year over year, reported the Bureau of Labor Statistics (BLS) on Tuesday. Excluding food and energy, Core CPI increased 0.4% monthly and 5.6% yearly. Economists surveyed by Dow Jones expected the headline CPI to grow 0.4% monthly and 6.2% yearly. Expectations for core CPI changes were 0.3% and 5.5%, respectively. On Tuesday, US stocks fell at open in response to the hotter-than-expected CPI report. But major indexes recovered somewhat at the close of the day. The Dow Jones Industrial Average slipped 156 points, or -0.46%, after initially losing over 300 points. The S&P 500 was flat at 4,136 (-0.03%), and the Nasdaq 100 gained 68 points to 11,960. US Treasury yields ticked higher. 2-year yield went up 94 ticks to 4.628%, while 10-year yield lifted 36 points to 3.755%. Bond investors widely expected the Federal Reserve to raise rates by 25 basis points to the 4.75%-5.00% range in March. Mega Trend in US Inflation While we usually focus on the percentage changes in inflation, CPI data are constructed as indexes, each using 1982-84 price data as a baseline at 100. January CPI reading of 299.170 is 0.8% above December of 296.797. It is up 6.4% from 281.148 in January 2022 (Data in this section is from Table 1 in the January CPI release). Interpretation: Today, the average price of goods and services in the U.S. is about 3 times as high as the price level from nearly four decades ago. This translates into a compound annual growth rate (CAGR) of 2.93% for the past 38 years. Insights: Long-run inflation rate is almost one percentage point higher than the Fed policy target. With less restrictive monetary policy on one hand, but more expansive fiscal policy on the other, the 2% goal appears to be far fetching. Barring a major recession, I expect the US inflation to stay above its 3% historical average in the foreseeable future. In the past four decades, cost of many consumer goods tripled in price, including Food (+219%), Energy (+183) and Core CPI (+202%). But there are noticeable outliners: • Tobacco and smoking products, +1289% • Motor vehicle insurance, +559% • Medical care services, +502% • New vehicle, +77% • Apparel, +28% January CPI Readings Before diving into the data, we should know that when BLS releases CPI data in February, it readjusts the weighting to account for the latest changes in the cost of living. For 2023, CPI weights are updated annually based on a single calendar year of consumer expenditure data. This reflects a change from prior practice of updating weights biennially. The changes of weighting by product and service category in the January report: CPI Category Old Weight New Weight Change Housing 46.40% 44.40% +2.0% Entertainment 5.70% 5.40% +0.3% Food 14.50% 14.40% +0.1% Clothing 2.50% 2.50% 0.0% Other 2.60% 2.70% -0.1% Medical 7.70% 8.10% -0.4% Education 5.20% 5.80% -0.6% Transport 15.30% 16.70% -1.4% Rising shelter costs accounted for nearly half the monthly price increase. The component accounts for more than one-third of the index and rose 0.7% on the month and was up 7.9% from a year ago. Energy also was a significant contributor, up 2% month over month (M/M) and 8.7% annually, while food costs rose 0.5% M/M and 10.1% annually. Food: Up 0.5% M/M in January from 0.1% in December. Annualized inflation is 10.1%. Energy: Up 2.0% M/M in January from -3.1% in December. Annualized gain is 8.7%, of which, gasoline (+1.9%), diesel (+27.7%), electricity (+11.9%), and natural gas (+26.7%). Shelter: Up 0.7% M/M in January from 0.8% in December. Up 7.9% Y/Y. Transportation: Up 0.9% M/M in January from 0.6% in December. Up 14.6% Y/Y. While the headline CPI ticks down from 6.5% to 6.4% on an annualized basis, January price increase of 0.5% is significantly higher than the December reading of +0.1%. Overall inflation level is undoubtedly on the way down, but price increases from food, shelter and transportation are very sticky and don’t normally go down once moving up. Is disinflation a fact or fiction? I think we are somewhere in between, in the Twilight Zone. The US Stock Market Narratives In the past three years, the stock market narratives have changed several times: • After the initial pandemic hit in March 2020, US stocks staged a very impressive bull run. Growth drivers were US companies innovating with new products and services and catering for “work-from-home” employees and “play-at-home” consumers. • 2022 started with a major geopolitical crisis, pushing stocks sharply down. Fed rate hikes from March 2022 dragged major stock indexes into bear market territory. • Since inflation peaked in July and the Core CPI reading confirmed it in October 2022, US stock market began to rebound, centering on the notion of “Fed Pivot”. More recently, investors are caught by conflicting economic data. • Unemployment at 50-year low vs. Big Techs pushing rounds of massive lay-offs; • Lower inflation rate vs. “Eggflation” and “Shrinkflation” that consumers experience; • Whether the Fed is hawkish or dovish depends on the next dataset. While investors try to make sense of all these, stock market moves sideways. The 30-day returns for Dow and the S&P are -0.83% and +3.20%, respectively. Are we at the beginning of a new bull market? Or is it a bear relief, a temporary rebound from a bear market? To make an assessment, you need to know how many more rate hikes could be (pick a number between 1 and 4), and what the terminal rate would be (5.0%, 5.25%, 5.5%, 5.75%, or 6.0%)? I have no idea. When uncertainty becomes the dominant narrative, it’s time to explore opportunities that promise more certainties. AI - New Engine for Economic Growth One visible exception is Nasdaq 100, which gained 8.9% in the past month. S&P Technology Select Sector Index (XAK) had an even higher return at 9.5%. Most Big Tech companies were vastly overstaffed during the pandemic years. With stock prices cutting by two thirds or more, they are forced to live within their cash flow. Cutting off unprofitable divisions and laying off redundant staff help them survive in leaner years. This is certainly very painful for the tech workers and their families. To investors, Big Tech may have transformed itself from lofty Growth Stock to reasonably priced Value Stock. For Nasdaq 100, its trailing 12-month price/earnings ratio was 34 one year ago. It is 23.63 as of February 10th, according to Birinyi Associates. Technological breakthroughs have always powered the US economy to growth for the long run. Personal computers in the 1980s, Internet for the 1990s, smart phones and mobile internet in the 2000s, and electric vehicles in the 2010s, just to name a few. In my opinion, Artificial Intelligence will be our economic growth engine in 2023. While AI is nothing new, the viral success of ChatGPT has sensationally changed the game. Its popularity among mainstream consumers helps form strong support for all publicly traded companies in the AI sector, not just for OpenAI and its parent Microsoft. While writing this report, I asked ChatGPT one question: “Please show me the top-10 publicly traded stocks in the AI field.” Below is his/her/its answer: 1. Alphabet Inc. (GOOGL) - Google's parent company, which has been investing heavily in AI technology and applications. 2. NVIDIA Corporation (NVDA) - A leading company in graphics processing units (GPUs), which are commonly used in AI training and inferencing. 3. International Business Machines Corporation (IBM) - A company that has been developing AI technologies for several years and has a range of products and services, including the Watson AI platform. 4. Microsoft Corporation (MSFT) - Microsoft has invested heavily in AI technologies, and its Azure platform provides a range of AI tools and services. 5. Amazon.com, Inc. (AMZN) - Amazon's AI capabilities are used in a variety of products and services, including the Alexa voice assistant and its recommendation algorithms. 6. Baidu, Inc. (BIDU) - A Chinese company that has been investing heavily in AI technologies, including natural language processing and autonomous driving. 7. Alibaba Group Holding Limited (BABA) - A Chinese company that has also invested heavily in AI technologies and has been developing AI applications for e-commerce, logistics, and finance. 8. Intel Corporation (INTC) - A company that has been developing hardware specifically for AI, including custom processors and FPGA chips. 9. Twilio Inc. (TWLO) - A company that provides cloud-based communication services and has been investing in AI technologies to improve its services. 10. Advanced Micro Devices, Inc. (AMD) - A company that develops CPUs and GPUs for AI applications and has been investing heavily in machine learning and other AI technologies. This is very impressive. ChatGPT not only gives me a list of the companies, but also highlights each company’s involvement in the AI field. Since ChatGPT doesn’t have data beyond 2021, we come back to our trusty TradingView to pull out 1-year return charts. What a brutal year! Only Microsoft manages to gain 5.3%. The rest in the list had negative returns from -10% to 40%. Twilio is the loss leader, yielding -66.8% in the last 12 months. This drives home the two major risks in new technology investing: Firstly, at an early stage, you have no idea which technology will win out at the end. Is it direct current (DC) or alternative current (AC)? Airship or Aircraft? VHS or Betamax? Cable TV or satellite TV? And TDMA or GSM for cellular signal? Secondly, you do not know which company will become a leader in a winner-take-all market. If you go back in time and invest in the new automobile industry in 1908, you have a 99% chance of losing money, unless you luckily picked Ford, General Motors, or Chrysler out of the 253 publicly traded automakers. Likewise, if you invested in mobile phone companies in early 2000, you likely picked Motorola, Blackberry, Ericsson, or Nokia. However, when an outsider Apple launch a breakthrough product, iPhone 1 in 2007, it knocked out all leading cellphone markers and became the ultimate winner. Right now, I predict that most electric vehicle makers will go out of business in five years, except for Tesla, and maybe BYD. The Case for S&P Technology Select Sector Index Consistently picking winners in emerging technologies is extremely difficult. Even the smartest stock picker could not beat the market. Take Cathy Wood’s Ark Innovation ETF (ARKK) as an example, its cumulative returns comparing to the Nasdaq 100 were: • 1-year: -42.8% vs. -12.4%; • 5-year: -2.1% vs. +85.1%; • Since Inception (8-year): +100.3% vs. +203.5%. Diversification is a very powerful concept in investing, notably in times of uncertainty. Concentrating on stock picking, many active managers tend to cloud objective assessment with their own conviction and lose sight of potential market leaders amid emerging mega trends. Passive investment via index futures focusing on the high-tech sector allows us to express our conviction and capture emerging trends. XAK is one of the 11 sector indexes in the S&P 500. Its top holdings are Apple (AAPL), Microsoft (MSFT), Nvidia (NVDA), Visa (V), Mastercard (MA), Broadcom (AVGO), Cisco (CSCO), and Adobe (ADBE). My research shows that S&P Technology Select Sector (XAK) outperformed many Big Tech stocks and ETFs in both short-term and long-term. According to Fact Sheet published by S&P, as of January 31st, the annualized historical returns are -15.22% (1Y), 13.82% (3Y), 16.22% (5Y) and 18.48% (10Y). Total returns since inception are 6,425.9%. You may invest in one of the technology sector ETFs, such as SPDR XLK, iShare IYW, and Vanguard VGT. But CME E-Mini S&P Technology Select Sector Index Futures (XAK) has distinguished features over ETFs. Firstly, XAK has five quarterly contracts to choose from: March, June, September, December and March 2024. This allows us to evaluate strategies focusing on expected future value of the index, up to 1 year ahead. Secondly, you could place either Long or Short position, allowing both bullish and bearish strategies to implement. Thirdly, initial margin of placing 1 contract is approximately 35% of the notional value. This built-in leverage could enhance the returns if market moves in the right direction. Finally, by holding a long position on the quarterly futures contract and rolling it each quarter, investors could replicate the strategy of holding the stocks or the ETFs. 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 trade set-ups and express my market views. If you have futures in your trading portfolio, check out on CME Group data plans in TradingView that suit your trading needs www.tradingview.com
CME_MINI:XAK1!Long
by JimHuangChicago
3