AAPL - Rising Trend Channel [MID-TERM]💡 Pattern: Falling Wedge 💡 RSI: 58 Neutral 💡 Risk: Medium ✅ Resistance: 196 ✅ Support: 174 PERFORMANCE 🔴 ST: NEGATIVE 🟢 MT: POSITIVE 🟢 LT: POSITIVE *ST: Short-term | MT: Mid-term | LT: Long-term Verify it first and believe later. WavePoint ❤️Longby wavepoint990
APPLE This rally isn't done yetApple (AAPL) is on an enormous +12.5% rally since the October 26 bottom on the 1W MA50 (red trend-line). Last week, the price even broke above the top (Lower Highs trend-line) of the Falling Wedge pattern and then the 1D MA100 (green trend-line). Despite the successive break-outs, this rally may not be technically over as the very same Falling Wedge break-out fractal in March 2022 extended as high as the 0.9 Fibonacci retracement level. As a result, we can see an extension to $195.00 before any short/ medium-term pull-back to the 1D MA50 (blue trend-line) again. ------------------------------------------------------------------------------- ** Please LIKE 👍, FOLLOW ✅, SHARE 🙌 and COMMENT ✍ if you enjoy this idea! Also share your ideas and charts in the comments section below! This is best way to keep it relevant, support us, keep the content here free and allow the idea to reach as many people as possible. ** ------------------------------------------------------------------------------- 💸💸💸💸💸💸 👇 👇 👇 👇 👇 👇Longby TradingShot5547
APPLE Continues at the bullish trendAPPLE The price was UP till 177.81 and reached about my previous target, as we said will start to rise, also from there will trying to continues at the bullish trend Remembering, may be do retest till 170.57, then continues at the bullish trend if the price fell and was not able rise should stable under 166.72, to be more bearish what about your thought about APPEL? tell usLongby ElenaMayiUpdated 9917
AAPL ~ Snapshot TA (Daily / Nov 2023)NASDAQ:AAPL chart mapping/analysis. Clear breakout of descending parallel channel (white). Bull target(s) Overhead gap fills Previous ATH (~197.70) Ascending trend-line resistance (green dotted) Upper range of ascending parallel channel (light blue) Bear target(s) Descending parallel channel (white) aka "return to scene of crime" 23.6% Fib Ascending trend-line (green dotted) + 38.2% Fib confluence support zone Descending trend-line (white dotted) by BlueHatInvestorUpdated 0
Investors' Holy Grail - The Business/Economic CycleThe business cycle describes how the economy expands and contracts over time. It is an upward and downward movement of the gross domestic product along with its long-term growth rate. The business cycle consists o f 6 phases/stages : 1. Expansion 2. Peak 3. Recession 4. Depression 5. Trough 6. Recovery 1) Expansion : Sectors Affected: Technology, Consumer discretion Expansion is the first stage of the business cycle. The economy moves slowly upward, and the cycle begins. The government strengthens the economy: Lowering taxes Boost in spending. - When the growth slows, the central bank reduces rates to encourage businesses to borrow. - As the economy expands, economic indicators are likely to show positive signals, such as employment, income, wages, profits, demand, and supply. - A rise in employment increases consumer confidence increasing activity in the housing markets, and growth turns positive. A high level of demand and insufficient supply lead to an increase in the price of production. Investors take a loan with high rates to fill the demand pressure. This process continues until the economy becomes favorable for expansion. 2) Peak : Sector Affected : Financial, energy, materials - The second stage of the business cycle is the peak which shows the maximum growth of the economy. Identifying the end point of an expansion is the most complex task because it can last for serval years. - This phase shows a reduction in unemployment rates. The market continues its positive outlook. During expansion, the central bank looks for signs of building price pressures, and increased rates can contribute to this peak. The central bank also tries to protect the economy against inflation in this stage. - Since employment rates, income, wages, profits, demand & supply are already high, there is no further increase. - The investor will produce more and more to fill the demand pressure. Thus, the investment and product will become expensive. At this time point, the investor will not get a return due to inflation. Prices are way higher for buyers to buy. From this situation, a recession takes place. The economy reverses from this stage. 3) Recession : Sector Affected : Utilities, healthcare, consumer staples - Two consecutive quarters of back-to-back declines in gross domestic product constitute a recession. - The recession is followed by a peak phase. In this phase economic indicators start melting down. The demand for the goods decreased due to expensive prices. Supply will keep increasing, and on the other hand, demand will begin to decline. That causes an "excess of supply" and will lead to falling in prices. 4) Depression : - In more prolonged downturns, the economy enters into a depression phase. The period of malaise is called depression. Depression doesn't happen often, but when they do, there seems to be no amount of policy stimulus that can lift consumers and businesses out of their slumps. When The economy is declining and falling below steady growth, this stage is called depression. - Consumers don't borrow or spend because they are pessimistic about the economic outlook. As the central bank cuts interest rates, loans become cheap, but businesses fail to take advantage of loans because they can't see a clear picture of when demand will start picking up. There will be less demand for loans. The business ends up sitting on inventories & pare back production, which they already produced. - Companies lay off more and more employees, and the unemployment rate soars and confidence flatters. 5) Trough : - When economic growth becomes negative, the outlook looks hopeless. Further decline in demand and supply of goods and services will lead to more fall in prices. - It shows the maximum negative situation as the economy reached its lowest point. All economic indicators will be worse. Ex. The highest rate of unemployment, and No demand for goods and services(lowest), etc. After the completion, good time starts with the recovery phase. 6) Recovery : Affected sectors: Industrials, materials, real estate - As a result of low prices, the economy begins to rebound from a negative growth rate, and demand and production are both starting to increase. - Companies stop shedding employees and start finding to meet the current level of demand. As a result, they are compelled to hire. As the months pass, the economy is once in expansion. - The business cycle is important because investors attempt to concentrate their investments on those that are expected to do well at a certain time of the cycle. - Government and the central bank also take action to establish a healthy economy. The government will increase expenditure and also take steps to increase production. After the recovery phases, the economy again enters the expansion phase. Safe heaven/Defensive Stocks - It maintains or anticipates its values over the crisis, then does well. We can even expect good returns in these asset classes. Ex. utilities, health care, consumer staples, etc. ("WE WILL DISCUSS MORE IN OUR UPCOMING ARTICLE DUE TO ARTICLE LENGTH.") It's a depression condition for me that I couldn't complete my discussion after spending many days in writing this article. However, I will upload the second part of this article that will help investors and traders in real life. This article took me a long time to write. I'm not expecting likes or followers, but I hope you will read it. @Money_Dictators Editors' picksEducationby Money_DictatorsUpdated 6969445
Algorithmic vs. Manual Trading - Which Strategy Reigns SupremeIntro: In the dynamic world of financial markets, trading strategies have evolved significantly over the years. With advancements in technology and the rise of artificial intelligence (AI), algorithmic trading, also known as algo trading, has gained immense popularity. Algo trading utilizes complex algorithms and automated systems to execute trades swiftly and efficiently, offering numerous advantages over traditional manual trading approaches. In this article, we will explore the advantages and disadvantages of algo trading compared to manual trading, providing a comprehensive overview of both approaches. We will delve into the speed, efficiency, emotion-free decision making, consistency, scalability, accuracy, backtesting capabilities, risk management, and diversification offered by algo trading. Additionally, we will discuss the flexibility, adaptability, intuition, experience, emotional intelligence, and creative thinking that manual trading brings to the table. Advantages of Algo trading: Speed and Efficiency: One of the primary advantages of algo trading is its remarkable speed and efficiency. With algorithms executing trades in milliseconds, algo trading eliminates the delays associated with manual trading. This speed advantage enables traders to capitalize on fleeting market opportunities and capture price discrepancies that would otherwise be missed. By swiftly responding to market changes, algo trading ensures that traders can enter and exit positions at optimal prices. Emotion-Free Decision Making: Humans are prone to emotional biases, which can cloud judgment and lead to irrational investment decisions. Algo trading removes these emotional biases by relying on pre-programmed rules and algorithms. The algorithms make decisions based on logical parameters, objective analysis, and historical data, eliminating the influence of fear, greed, or other human emotions. As a result, algo trading enables more disciplined and objective decision-making, ultimately leading to better trading outcomes. Consistency: Consistency is a crucial factor in trading success. Algo trading provides the advantage of maintaining a consistent trading approach over time. The algorithms follow a set of predefined rules consistently, ensuring that trades are executed in a standardized manner. This consistency helps traders avoid impulsive decisions or deviations from the original trading strategy, leading to a more disciplined approach to investing. Enhanced Scalability: Traditional manual trading has limitations when it comes to scalability. As trade volumes increase, it becomes challenging for traders to execute orders efficiently. Algo trading overcomes this hurdle by automating the entire process. Algorithms can handle a high volume of trades across multiple markets simultaneously, ensuring scalability without compromising on execution speed or accuracy. This scalability empowers traders to take advantage of diverse market opportunities without any operational constraints. Increased Accuracy: Algo trading leverages the power of technology to enhance trading accuracy. The algorithms can analyze vast amounts of market data, identify patterns, and execute trades based on precise parameters. By eliminating human error and subjectivity, algo trading increases the accuracy of trade execution. This improved accuracy can lead to better trade outcomes, maximizing profits and minimizing losses. Backtesting Capabilities and Optimization: Another significant advantage of algo trading is its ability to backtest trading strategies. Algorithms can analyze historical market data to simulate trading scenarios and evaluate the performance of different strategies. This backtesting process helps traders optimize their strategies by identifying patterns or variables that generate the best results. By fine-tuning strategies before implementing them in live markets, algo traders can increase their chances of success. Automated Risk Management: Automated Risk Management: Managing risk is a critical aspect of trading. Algo trading offers automated risk management capabilities that can be built into the algorithms. Traders can program specific risk parameters, such as stop-loss orders or position sizing rules, to ensure that losses are limited and positions are appropriately managed. By automating risk management, algo trading reduces the reliance on manual monitoring and helps protect against potential market downturns. Diversification: Diversification: Algo trading enables traders to diversify their portfolios effectively. With algorithms capable of simultaneously executing trades across multiple markets, asset classes, or strategies, traders can spread their investments and reduce overall risk. Diversification helps mitigate the impact of individual market fluctuations and can potentially enhance long-term returns. Removal of Emotional Biases: Finally, algo trading eliminates the influence of emotional biases that often hinder trading decisions. Fear, greed, and other emotions can cloud judgment and lead to poor investment choices. Byrelying on algorithms, algo trading removes these emotional biases from the decision-making process. This objective approach helps traders make more rational and data-driven decisions, leading to better overall trading performance. Disadvantage of Algo Trading System Vulnerabilities and Risks: One of the primary concerns with algo trading is system vulnerabilities and risks. Since algo trading relies heavily on technology and computer systems, any technical malfunction or system failure can have severe consequences. Power outages, network disruptions, or software glitches can disrupt trading operations and potentially lead to financial losses. It is crucial for traders to have robust risk management measures in place to mitigate these risks effectively. Technical Challenges and Complexity: Technical Challenges and Complexity: Algo trading involves complex technological infrastructure and sophisticated algorithms. Implementing and maintaining such systems require a high level of technical expertise and resources. Traders must have a thorough understanding of programming languages and algorithms to develop and modify trading strategies. Additionally, monitoring and maintaining the infrastructure can be challenging and time-consuming, requiring continuous updates and adjustments to keep up with evolving market conditions. Over-Optimization: Another disadvantage of algo trading is the risk of over-optimization. Traders may be tempted to fine-tune their algorithms excessively based on historical data to achieve exceptional past performance. However, over-optimization can lead to a phenomenon called "curve fitting," where the algorithms become too specific to historical data and fail to perform well in real-time market conditions. It is essential to strike a balance between optimizing strategies and ensuring adaptability to changing market dynamic Over Reliance on Historical Data: Algo trading heavily relies on historical data to generate trading signals and make decisions. While historical data can provide valuable insights, it may not always accurately reflect future market conditions. Market dynamics, trends, and relationships can change over time, rendering historical data less relevant. Traders must be cautious about not relying solely on past performance and continuously monitor and adapt their strategies to current market conditions. Lack of Adaptability: Another drawback of algo trading is its potential lack of adaptability to unexpected market events or sudden changes in market conditions. Algo trading strategies are typically based on predefined rules and algorithms, which may not account for unforeseen events or extreme market volatility. Traders must be vigilant and ready to intervene or modify their strategies manually when market conditions deviate significantly from the programmed rules. Advantages of Manual Trading Flexibility and Adaptability: Manual trading offers the advantage of flexibility and adaptability. Traders can quickly adjust their strategies and react to changing market conditions in real-time. Unlike algorithms, human traders can adapt their decision-making process based on new information, unexpected events, or emerging market trends. This flexibility allows for agile decision-making and the ability to capitalize on evolving market opportunities. Intuition and Experience: Human traders possess intuition and experience, which can be valuable assets in the trading process. Through years of experience, traders develop a deep understanding of the market dynamics, patterns, and interrelationships between assets. Intuition allows them to make informed judgments based on their accumulated knowledge and instincts. This human element adds a qualitative aspect to trading decisions that algorithms may lack. Complex Decision-making: Manual trading involves complex decision-making that goes beyond predefined rules. Traders analyze various factors, such as fundamental and technical indicators, economic news, and geopolitical events, to make well-informed decisions. This ability to consider multiple variables and weigh their impact on the market enables traders to make nuanced decisions that algorithms may overlook. Emotional Intelligence and Market Sentiment: Humans possess emotional intelligence, which can be advantageous in trading. Emotions can provide valuable insights into market sentiment and investor psychology. Human traders can gauge market sentiment by interpreting price movements, news sentiment, and market chatter. Understanding and incorporating market sentiment into decision-making can help traders identify potential market shifts and take advantage of sentiment-driven opportunities. Contextual Understanding: Manual trading allows traders to have a deep contextual understanding of the markets they operate in. They can analyze broader economic factors, political developments, and industry-specific dynamics to assess the market environment accurately. This contextual understanding provides traders with a comprehensive view of the factors that can influence market movements, allowing for more informed decision-making. Creative and Opportunistic Thinking: Human traders bring creative and opportunistic thinking to the trading process. They can spot unique opportunities that algorithms may not consider. By employing analytical skills, critical thinking, and out-of-the-box approaches, traders can identify unconventional trading strategies or undervalued assets that algorithms may overlook. This creative thinking allows traders to capitalize on market inefficiencies and generate returns. Complex Market Conditions: Manual trading thrives in complex market conditions that algorithms may struggle to navigate. In situations where market dynamics are rapidly changing, volatile, or influenced by unpredictable events, human traders can adapt quickly and make decisions based on their judgment and expertise. The ability to think on their feet and adjust strategies accordingly enables traders to navigate challenging market conditions effectively. Disadvantage of Manual Trading Emotional Bias: Algo trading lacks human emotions, which can sometimes be a disadvantage. Human traders can analyze market conditions based on intuition and experience, while algorithms solely rely on historical data and predefined rules. Emotional biases, such as fear or greed, may play a role in decision-making, but algorithms cannot factor in these nuanced human aspects. Time and Effort: Implementing and maintaining algo trading systems require time and effort. Developing effective algorithms and strategies demands significant technical expertise and resources. Traders need to continuously monitor and update their algorithms to ensure they remain relevant in changing market conditions. This ongoing commitment can be time-consuming and may require additional personnel or technical support. Execution Speed: While algo trading is known for its speed, there can be challenges with execution. In fast-moving markets, delays in order execution can lead to missed opportunities or less favorable trade outcomes. Algo trading systems need to be equipped with high-performance infrastructure and reliable connectivity to execute trades swiftly and efficiently. Information Overload: In today's digital age, vast amounts of data are available to traders. Algo trading systems can quickly process large volumes of information, but there is a risk of information overload. Filtering through excessive data and identifying relevant signals can be challenging. Traders must carefully design algorithms to focus on essential information and avoid being overwhelmed by irrelevant or noisy data. The Power of AI in Enhancing Algorithmic Trading: Data Analysis and Pattern Recognition: AI algorithms excel at processing vast amounts of data and recognizing patterns that may be difficult for human traders to identify. By analyzing historical market data, news, social media sentiment, and other relevant information, AI-powered algorithms can uncover hidden correlations and trends. This enables traders to develop more robust trading strategies based on data-driven insights. Predictive Analytics and Forecasting: AI algorithms can leverage machine learning techniques to generate predictive models and forecasts. By training on historical market data, these algorithms can identify patterns and relationships that can help predict future price movements. This predictive capability empowers traders to anticipate market trends, identify potential opportunities, and adjust their strategies accordingly. Real-time Market Monitoring: AI-based systems can continuously monitor real-time market data, news feeds, and social media platforms. This enables traders to stay updated on market developments, breaking news, and sentiment shifts. By incorporating real-time data into their algorithms, traders can make faster and more accurate trading decisions, especially in volatile and rapidly changing market conditions. Adaptive and Self-Learning Systems: AI algorithms have the ability to adapt and self-learn from market data and trading outcomes. Through reinforcement learning techniques, these algorithms can continuously optimize trading strategies based on real-time performance feedback. This adaptability allows the algorithms to evolve and improve over time, enhancing their ability to generate consistent returns and adapt to changing market dynamics. Enhanced Decision Support: AI algorithms can provide decision support tools for traders, presenting them with data-driven insights, risk analysis, and recommended actions. By combining the power of AI with human expertise, traders can make more informed and well-rounded decisions. These decision support tools can assist in portfolio allocation, trade execution, and risk management, enhancing overall trading performance. How Algorithmic Trading Handles News and Events? In the fast-paced world of financial markets, news and events play a pivotal role in driving price movements and creating trading opportunities. Algorithmic trading has emerged as a powerful tool to capitalize on these dynamics. Automated News Monitoring: Algorithmic trading systems are equipped with the capability to automatically monitor news sources, including financial news websites, press releases, and social media platforms. By utilizing natural language processing (NLP) and sentiment analysis techniques, algorithms can filter through vast amounts of news data, identifying relevant information that may impact the market. Real-time Data Processing: Algorithms excel in processing real-time data and swiftly analyzing its potential impact on the market. By integrating news feeds and other event-based data into their models, algorithms can quickly evaluate the relevance and potential market significance of specific news or events. This enables traders to react promptly to emerging opportunities or risks. Event-driven Trading Strategies: Algorithmic trading systems can be programmed to execute event-driven trading strategies. These strategies are designed to capitalize on the market movements triggered by specific events, such as economic releases, corporate earnings announcements, or geopolitical developments. Algorithms can automatically scan for relevant events and execute trades based on predefined criteria, such as price thresholds or sentiment analysis outcomes. Sentiment Analysis: Sentiment analysis is a crucial component of news and event-based trading. Algorithms can analyze news articles, social media sentiment, and other textual data to assess market sentiment surrounding a specific event or news item. By gauging positive or negative sentiment, algorithms can make informed trading decisions and adjust strategies accordingly. Backtesting and Optimization: Algorithmic trading allows for backtesting and optimization of news and event-driven trading strategies. Historical data can be used to test the performance of trading models under various news scenarios. By analyzing the past market reactions to similar events, algorithms can be fine-tuned to improve their accuracy and profitability. Algorithmic News Trading: Algorithmic news trading involves the automatic execution of trades based on predefined news triggers. For example, algorithms can be programmed to automatically buy or sell certain assets when specific news is released or when certain conditions are met. This automated approach eliminates the need for manual monitoring and ensures swift execution in response to news events. Risk Management: Algorithmic trading systems incorporate risk management measures to mitigate the potential downside of news and event-driven trading. Stop-loss orders, position sizing algorithms, and risk management rules can be integrated to protect against adverse market movements or unexpected news outcomes. This helps to minimize losses and ensure controlled risk exposure. Flash Crash 2010: A Historic Market Event On May 6, 2010, the financial markets experienced an unprecedented event known as the "Flash Crash." Within a matter of minutes, stock prices plummeted dramatically, only to recover shortly thereafter. This sudden and extreme market turbulence sent shockwaves through the financial world and highlighted the vulnerabilities of an increasingly interconnected and technology-driven trading landscape. The Flash Crash Unfolds: On that fateful day, between 2:32 p.m. and 2:45 p.m. EDT, the U.S. stock market experienced an abrupt and severe decline in prices. Within minutes, the Dow Jones Industrial Average (DJIA) plunged nearly 1,000 points, erasing approximately $1 trillion in market value. Blue-chip stocks, such as Procter & Gamble and Accenture, saw their prices briefly crash to a mere fraction of their pre-crash values. This sudden and dramatic collapse was followed by a swift rebound, with prices largely recovering by the end of the trading session. The Contributing Factors: Several factors converged to create the perfect storm for the Flash Crash. One key element was the increasing prevalence of high-frequency trading (HFT), where computer algorithms execute trades at lightning-fast speeds. This automated trading, combined with the interconnectedness of markets, exacerbated the speed and intensity of the crash. Additionally, the widespread use of stop-loss orders, which are triggered when a stock reaches a specified price, amplified the selling pressure as prices rapidly declined. A lack of adequate market safeguards and regulatory mechanisms further exacerbated the situation. Role of Algorithmic Trading: Algorithmic trading played a significant role in the Flash Crash. As the markets rapidly declined, certain algorithmic trading strategies failed to function as intended, exacerbating the sell-off. These algorithms, designed to capture small price discrepancies, ended up engaging in a "feedback loop" of selling, pushing prices even lower. The speed and automation of algorithmic trading made it difficult for human intervention to effectively mitigate the situation in real-time. Market Reforms and Lessons Learned: The Flash Crash of 2010 prompted significant regulatory and technological reforms aimed at preventing similar events in the future. Measures included the implementation of circuit breakers, which temporarily halt trading during extreme price movements, and revisions to market-wide circuit breaker rules. Market surveillance and coordination between exchanges and regulators were also enhanced to better monitor and respond to unusual trading activity. Additionally, the incident highlighted the need for greater transparency and scrutiny of algorithmic trading practices. Implications for Market Stability: The Flash Crash served as a wake-up call to market participants and regulators, underscoring the potential risks associated with high-frequency and algorithmic trading. It highlighted the importance of ensuring that market infrastructure and regulations keep pace with technological advancements. The incident also emphasized the need for market participants to understand the intricacies of the trading systems they employ, and for regulators to continually evaluate and adapt regulatory frameworks to address emerging risks. The Flash Crash of 2010 stands as a pivotal moment in financial market history, exposing vulnerabilities in the increasingly complex and interconnected world of electronic trading. The event triggered significant reforms and led to a greater focus on market stability, transparency, and risk management. While strides have been made to enhance market safeguards and regulatory oversight, ongoing vigilance and continuous adaptation to technological advancements are necessary to maintain the integrity and stability of modern financial markets. How Algorithmic Trading Thrives in Changing Markets? Algorithmic trading (ALGO) can tackle changing market conditions through various techniques and strategies that allow algorithms to adapt and respond effectively. Here are some ways ALGO can address changing market conditions: Real-Time Data Analysis: Algo systems continuously monitor market data, including price movements, volume, news feeds, and economic indicators, in real-time. By analyzing this data promptly, algorithms can identify changing market conditions and adjust trading strategies accordingly. This enables Algo to capture opportunities and react to market shifts more rapidly than human traders. Dynamic Order Routing: Algo systems can dynamically route orders to different exchanges or liquidity pools based on prevailing market conditions. By assessing factors such as liquidity, order book depth, and execution costs, algorithms can adapt their order routing strategies to optimize trade execution. This flexibility ensures that algo takes advantage of the most favorable market conditions available at any given moment. Adaptive Trading Strategies: Algo can utilize adaptive trading strategies that are designed to adjust their parameters or rules based on changing market conditions. These strategies often incorporate machine learning algorithms to continuously learn from historical data and adapt to evolving market dynamics. By dynamically modifying their rules and parameters, algo systems can optimize trading decisions and capture opportunities across different market environments. Volatility Management: Changing market conditions often come with increased volatility. Algo systems can incorporate volatility management techniques to adjust risk exposure accordingly. For example, algorithms may dynamically adjust position sizes, set tighter stop-loss levels, or modify risk management parameters based on current market volatility. These measures help to control risk and protect capital during periods of heightened uncertainty. Pattern Recognition and Statistical Analysis: Algo systems can employ advanced pattern recognition and statistical analysis techniques to identify recurring market patterns or anomalies. By recognizing these patterns, algorithms can make informed trading decisions and adjust strategies accordingly. This ability to identify and adapt to patterns helps algocapitalize on recurring market conditions while also remaining adaptable to changes in market behavior. Backtesting and Simulation: Algo systems can be extensively backtested and simulated using historical market data. By subjecting algorithms to various market scenarios and historical data sets, traders can evaluate their performance and robustness under different market conditions. This process allows for fine-tuning and optimization of algo strategies to better handle changing market dynamics. In summary, algo tackles changing market conditions through real-time data analysis, dynamic order routing, adaptive trading strategies, volatility management, pattern recognition, statistical analysis, and rigorous backtesting. By leveraging these capabilities, algo can effectively adapt to evolving market conditions and capitalize on opportunities while managing risks more efficiently than traditional trading approaches The Rise of Algo Traders: Is Technical Analysis Losing Ground? Although algorithmic trading (algo trading) can automate and optimize certain elements of technical analysis, it is improbable that it will fully substitute it. Technical analysis is a financial discipline that encompasses the examination of historical price and volume data, chart patterns, indicators, and other market variables to inform trading strategies. There are several reasons why algo traders cannot entirely supplant technical analysis: Interpretation of Market Psychology: Technical analysis incorporates the understanding of market psychology, which is based on the belief that historical price patterns repeat themselves due to human behavior. It involves analyzing investor sentiment, trends, support and resistance levels, and other factors that can influence market movements. Algo traders may use technical indicators to identify these patterns, but they may not fully capture the nuances of market sentiment and psychological factors. Subjectivity in Analysis: Technical analysis often involves subjective interpretation by traders, as different individuals may analyze the same chart or indicator differently. Algo traders rely on predefined rules and algorithms that may not encompass all the subjective elements of technical analysis. Human traders can incorporate their experience, intuition, and judgment to make nuanced decisions that may not be easily captured by algorithms. Market Adaptability: Technical analysis requires the ability to adapt to changing market conditions and adjust strategies accordingly. While algorithms can be programmed to adjust certain parameters based on market data, they may not possess the same adaptability as human traders who can dynamically interpret and respond to evolving market conditions in real-time. Unpredictable Events: Technical analysis is often challenged by unexpected events, such as geopolitical developments, economic announcements, or corporate news, which can cause significant market disruptions. Human traders may have the ability to interpret and react to these events based on their knowledge and understanding, while algo traders may struggle to respond effectively to unforeseen circumstances. Fundamental Analysis: Technical analysis primarily focuses on price and volume data, while fundamental analysis considers broader factors such as company financials, macroeconomic indicators, industry trends, and news events. Algo traders may not have the capacity to analyze fundamental factors and incorporate them into their decision-making process, which can limit their ability to fully replace technical analysis. In conclusion, while algo trading can automate certain elements of technical analysis, it is unlikely to replace it entirely. Technical analysis incorporates subjective interpretation, market psychology, adaptability, and fundamental factors that may be challenging for algorithms to fully replicate. Human traders with expertise in technical analysis and the ability to interpret market dynamics will continue to play a significant role in making informed trading decisions. The Ultimate Winner - Algo Trading or Manual Trading? Determining whether algo trading or manual trading is best depends on various factors, including individual preferences, trading goals, and skill sets. Both approaches have their advantages and limitations, and what works best for one person may not be the same for another. Let's compare the two: Speed and Efficiency: Algo trading excels in speed and efficiency, as computer algorithms can analyze data and execute trades within milliseconds. Manual trading involves human decision-making, which may be subject to cognitive biases and emotional factors, potentially leading to slower execution or missed opportunities. Emotion and Discipline: Algo trading eliminates emotional biases from trading decisions, as algorithms follow predefined rules without being influenced by fear or greed. Manual trading requires discipline and emotional control to make objective decisions, which can be challenging for some traders. Adaptability: Algo trading can quickly adapt to changing market conditions and execute trades based on pre-programmed rules. Manual traders can adapt their strategies as well, but it may require more time and effort to monitor and adjust to rapidly evolving market dynamics. Complexity and Technical Knowledge: Algo trading requires programming skills or the use of algorithmic platforms, which can be challenging for traders without a technical background. Manual trading, on the other hand, relies on an understanding of fundamental and technical analysis, which requires continuous learning and analysis of market trends. Strategy Development: Algo trading allows for systematic and precise strategy development based on historical data analysis and backtesting. Manual traders can develop their strategies as well, but it may involve more subjective interpretations of charts, patterns, and indicators. Risk Management: Both algo trading and manual trading require effective risk management. Algo trading can incorporate predetermined risk management parameters into algorithms, whereas manual traders need to actively monitor and manage risk based on their judgment. Ultimately, the best approach depends on individual circumstances. Some traders may prefer algo trading for its speed, efficiency, and objective decision-making, while others may enjoy the flexibility and adaptability of manual trading. It is worth noting that many traders use a combination of both approaches, utilizing algo trading for certain strategies and manual trading for others. In conclusion, algorithmic trading offers benefits such as speed, efficiency, and risk management, while manual trading provides adaptability and human intuition. AI enhances algorithmic trading by processing data, recognizing patterns, and providing decision support. Algos excel in automated news monitoring and event-driven strategies. However, the Flash Crash of 2010 exposed vulnerabilities in the interconnected trading landscape, with algorithmic trading exacerbating the market decline. It serves as a reminder to implement appropriate safeguards and risk management measures. Overall, a balanced approach that combines the strengths of both algorithmic and manual trading can lead to more effective and resilient trading strategies. Editors' picksEducationby Money_DictatorsUpdated 1111378
Apple Roadmap Oct 2023Apple is the largest and most important stock in the market. It does appear with limited short term downsideby NeonUpdated 112
Apple closed above ascending trend line of a triangelApple closed above the ascending trend line of the triangle and below the lower line of the channel , weekly and monthly MACD's and MA's showing negativeness, day is neutral. Monday opening will guide us , pl. go through all the graphics in comment section by omvats1Updated 1119
AAPLStock analysis AAPL to day 11/11/23 . your opinion matters to me . and good luck to everyone Longby MSA199338
APPLE: Long entry with target area 196Good morning trader, today I share this view on Apple which leads me to increase my medium-term positions and open a short-term position. In this analysis I predict that in the next few days the price may reach the area of 196 where the previous highs are located. In favor of this entry there are several reasons given in part by signals and indications provided by my personal indicators, including LuBot which shows a Long signal on a candle that comes out above the positive TrendCloud that supports prices in recent weeks. The current candle is yellow so the short structure has returned positive (SBS signal) and this also happens in the TF daily as seen below. We also have an area of support given by previous highs which has kept prices above around 173 points for most of the time and now we see a positive break of the descending trendline that united the highs of the last few weeks. To integrate and support a Long entry, secondary indicators come into play including the Predictum which shows positivity for the month of November, LuTrender is positive on both Weekly and Daily and finally EVE seems to be ready for an increase in volatility and therefore could see a quick market breakout in the next few days that could bring prices into the target area of 196. I could expect one last retracement to the support area before the extension. Longby LuTrader_LB9
"Apple Inc. (AAPL) Potential Upside "Apple Inc. (AAPL) Potential Upside: A Fundamental Analysis" I believe Apple (AAPL) presents a promising opportunity with potential benefits and risks. **Trade Idea:** - **Entry:** Current market price - **Stop Loss:** $172.08 - **Target:** $190/$200 **Fundamental Benefits:** 1. Strong financials and consistent revenue growth. 2. Robust product portfolio with a loyal customer base. 3. Potential for positive developments in upcoming product releases or partnerships. **Fundamental Risks:** 1. Market volatility and macroeconomic factors may impact stock performance. 2. Dependency on a few key products, making the company vulnerable to market shifts. 3. Regulatory challenges in the tech industry could pose threats. **Disclaimer:** Always conduct thorough research and consider your risk tolerance before making any investment decisions. This idea is for educational purposes only and not financial advice.Longby meetj170
NASDAQ SHORT MARKET ANALYSISMarket is at down momentum at 1DTF but break trend line zone to mitigate bearish order block (BeOB) at price188.14 SL 190.44 TP 167.09 wait for target to activate.Shortby mayalaclu98222
WHAT IF? APPLE Is at the beginnign of a nice Elliot Wave Cycle?Beating earnings is a big deal right now for tech sectors. Apple did, with almost a point to spare. And with the reliance on phones and connectivity, might Apple be the one that will rise higher above the rest? I'm asking questions to justify my projections, but I think if we throw some impulse waves out there and see how we caught a 60% rise during the last impulse wave - maybe $250 per share in July 2024 isn't too crazy. Longby cnote560
$AAPL timber*This is not financial advice, so trade at your own risks* *My team digs deep and finds stocks that are expected to perform well based off multiple confluences* *Experienced traders understand the uphill battle in timing the market, so instead my team focuses mainly on risk management !! This chart analysis is for reference purposes only !! If you want to see more, please like and follow us @SimplyShowMeTheMoneyShortby SimplyShowMeTheMoney5
$AAPL Bullish ActionHowdy Traders! Recently, NASDAQ:AAPL has been creating this consolidation. *Personally, pattern types are invalid in trading. Trades should not be conducted and executed only when a 'flag' or a 'wedge' emerges. Instead, use consolidation. It is a definite thing that a stock has consolidated. Back to the charts. With this consolidation, it can be noted that NASDAQ:AAPL has broken through the top and has created this bullish position. It may come back to retest the previous resistance as a support, but it also may not. The price target is $186 for the short-term, and $195 for the near future. Buena Fortuna (Good Luck)!Longby fjack1928229
APPLE longinterval:240 min time identified: 18:58 pm (UTC+2) DESCRIPTION: We are entering the holiday season, and Apple stocks have the tendency to recover around this time, so we want to hop on this one. we are going long, we broke through the first bearish trendline; we want to break the next, the recent low was also taken out which is a good signal for a bullish move, a double bottom is also developing which is another confluence for a bullish move, we bag our 1000 pips, bail out before anything weird happens. Longby sootywhaleUpdated 221
Beautifull Apple buyFirst we see a nice breakpout to the upside. Now in a abcde correction wiche looks almost finished. Trade save amigo's.Longby G1D3onnUpdated 4
Apple - Sick Fundamentals Mean a New All Time HighI have recent calls on the SPX SPX ES - Welcome To The Fourth Quarter Rodeo The Nasdaq Nasdaq Futes - You Wanted a Dip For That 'Santa Rally,' Aye? SPY SPY - Did We Bottom, Or Is Manipulation Coming? And Tesla Tesla - Remember, The Ponzi Always Continues Which generally have a bullish-into-year-end thesis accompanying them, but caution that an October bottom for the second year in a row and a mega three day rally to start November may be something of a trap. When it comes to Apple, we have reservations that we topped under $200, for really obvious reasons, especially considering that on the monthly, the last three months of bearish price action haven't been that bearish. Yet, because the weekly shows us that there are two bars under $150 and $140 from last year that never printed a low, that those areas are probably protected until Apple starts to seriously deflate and enter an end-of-life cycle bear market. If Apple is going to enter an end of life cycle bear market, the MMs will 100% take out the $200 range and sell everything there first. So, fundamentally, why would Apple be at the end of its life? The answer is simple: the company, all these years, wed itself to the Chinese Communist Party, which is the scourge of humanity, The Beast, and the benefactor to Babylon (Shanghai). There's lots of really horrific data involving Apple numbers and the Chinese market right now, and the CCP under Xi Jinping is also rushing to replace other phone companies with domestic product, like the notorious Huawei. The elephant in the room when it comes to cellular and computer purchases in China is that they're down because there are less people in China as a result of the enormous damage the novel pneumonia pandemic that originated in Wuhan City has caused. SARS 1 in 2003 was covered up by the Party. The CCP made it seem like only a few thousand people died, when in reality, some accounts have stated that several million people died. Today, the Party still claims that less than 122,000 people died from COVID-19, despite China being the epicentre of the disease. You don't need an expert, or even a calculator, to figure out what's really going on and why the Chinese economy is in trouble. What's at stake for Xi and his faction is the 24-year-long organ harvesting genocide and persecution against Falun Dafa's 100 million practitioners. Although Xi has not participated in the persecution, and has, to the contrary, been killing via his Anti-corruption Campaign the Jiang Zemin faction who started and maintained the persecution all these years, the problem is that Xi is the head of the Party. When you kill a dragon, you decapitate it. But first, you start with its tail. And it's telling that former Premier Li Keqiang died a few weeks ago, merely in his 60s, at the hands of "an heart attack." So the fundamentals on Apple are bad because of China. So, with great faith in the principle of reversed logic, we actually look for longs with the chance to sell over $200. But the charts, as they stand, are not giving us a long signal. Everything, including Apple, bounced so hard in the first three days of November, and for Apple this came on the back of an earnings report, that we have to view the situation with major reservations, expecting that the candle painting of the low for the monthly bar has not yet been completed. Last October, Apple pretended to bottom, pretended to double bottom in November, and then gave it all back and set the low of the year at the end of 2022, and all of this happened while the indexes had properly bottomed in October. There was none of that "Magnificent 7" talk back then. So, how to trade this? I think it's wiser to go long on a breakout over $183 in a size that allows you to take partials at $198, $205, and $215 than it is to have bought in the last three days. And if we do dump, where we're looking for reversal patterns is at or below the April of 2022 low at $159.80~. But if we're about to moon for manipulation, we're actually likely to see a sweep just below the current November low of $167.90. So long as you can buy there without getting expired worthless on some short dated options, you'll have the best chance to ride the manipulation wave. But be careful. When it's time for the CCP to fall, all the bigger dominoes go with it, because they're all really lesser dominoes. Gap down overnight because of the time difference between Beijing and Manhattan means margin calls that scale in brutality, because Wall Street won't be in the mood to go risk on anything ever again. Nor will it have the money or the breath to.Longby LordWrymouthUpdated 8
🚧APPLE 🍎 Retest posable)hello traders what do you think about this analysis nxet traget?? Microsoft-Backed OpenAI Plans a Store for AI. It's Taking a Page from Apple's Playbook. — Barrons.com Nov 7, 202318:26 GMT+5 By Adam Clark Artificial intelligence is about to have its App Store moment. OpenAI is launching a store for customized versions of its ChatGPT AI bot made by third-parties, following the trail blazed by Apple with smartphone applications. OpenAI said the customized versions of ChatGPT will be called 'GPTs' and could be used for specialized purposes such as math tutoring or creating marketing materials. It's a big test for OpenAI, which is 49% owned by Microsoft MSFT , as to whether offering customized AI models will help bring widespread adoption, almost a year after the initial launch of ChatGPT triggered a frenzy of excitement around the technology. At the developer conference on Monday where the store was announced, OpenAI said that ChatGPT had more than 100 million weekly active users. It also unveiled a new AI model, GPT-4 Turbo, which it is offering at a lower price than its predecessor.Shortby World-forex-traders5
Short opportunity, AAPLA nice area of supply which I personally think is gonna do its job.Shortby hopemhar5
Bull Flag BreakoutI hadn't zoomed out to see this until this morning. Very distinct bull flag breakout on the Daily. will need more info to see what happens next by PapaBearBryant1
APPL (Apple Inc) Two Tiered Wyckoff Distribution SchematicHi Everyone! The chart above is an INTERACTIVE chart. Meaning, you can zoom in, zoom out, drag it around, etc... as you wish. I'll post the chart again below in a format intended for proper viewing as intended. There will be "multiple" black swan events resulting in the events of Phase C, D and E depicted in this chart taking place. Anticipate new COVID lockdowns world wide beginning the end of Q-3 or some time in Q-4 of 2023. Mainly for the purpose of attempting to steal another U.S. presidential election. There will also be multiple events world wide during 2024; resulting in a Sign of Weakness in Phase D. There will be a period of sideways price action before falling down once again with a SIgn of Weakness event in Phase E. It's also likely we see multiple Sign of Weakness events in Phase E before we find bottom in 2025. I do not know "when" these black swan events will take place. All I know is major social, political, geopolitical, financial and economic events will take place to execute this Distribution Schematic all the way to our Sign of Weakness events in Phase E. The globalist in the WEF, UN, NATO, US, IMF, BIS, etc... know their FIAT monetary scam is coming to its end. They are desperately attempting to avoid more people waking up to their plans to control all of us. What better way to control us than to diminish our food supply, bankrupt all of us with a collapse supposedly caused by events THEY CREATED. What's the "main" purpose of creating these events and why so desperate to carry them out as soon as possible? Well, the FIAT Central Banking System is approaching its end due to inflation. So, they need multiple distractions (events) to take place in order to have SOMETHING to blame the collapse of their system. They don't want people blaming "them" for this collapse. Many of you are already awake. Some of you still must walk through the darkness before you finally see the light. We (as human beings) are still DIVIDED by propaganda these globalist propagate. But that's okay... Soon, we (Republican, Democrat, Independent) will be united. AT least most of us. Why? Well, when everyone's ability to put food on the table, pay rent/mortgage, put gas in the car, etc... is affected to the point of putting many into despair, we will finally unite to rid this world of those who seek to control all of us in an effort to gratify themselves. There are dark dark times ahead. Unfortunately, we must go through these dark times to avoid a major civil war between us all. To avoid needless bloodshed. It had to be done this way to wake many up who have been sleeping and unite us all for a common best good for all humanity. I look forward to that day most all of us are finally united for the best good of all. Until then, prepare and plan well for what's to come. And most importantly, Stay Awesome! Davidby WyckoffModeUpdated 8869
AAPL shows a strong supportAAPL shows a strong support and travelling inside a channel pattern. Targeting for 177Longby the23chartsUpdated 0