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Fundamentalanalsysis

Will TRY Continue to Fly or Will it Hold the 30 and Say GoodbyePrice has been pushing higher and higher and climbed thousands and thousands of PIPs since 2021. But with the increased interest rates (42.5%), will this be enough to prevent price from higher? Potentially. There needs to be more confidence in the Lira, which could be happening. Pimco and Vanguard (US Investment Companies), are investing in Turkey, which could be a good sign. If companies are starting to invest in Turkey, this could help their currency issues. What could also help and maybe is helping currently, is the TRY is a good carry trade, especially if there is a halt to the rapid depreciation in the Lira. The CBRT will likely hold rates at his high lvls for a while as they work to break the upward trajectory. Additionally, if analyst, traders, and investors are correct, and the FED reduces rates, this will assist price on pushing lower. Furthermore, when economic data is released, if inflation starts taking a hit to the downside (currently above 61%), this could bring in that confidence that is needed also and start pushing the TRY lower. If all these factors do improve the Lira, I am thinking price might even be able to hit the 27 lvl. For now, I got a small position on this pair, collecting a decent amount of positive rollover. I will build up as price pushes higher. I am able to sustain if price pushes 10,000 pips against me. Price is currently over 7,000 pips against me, with a manageable floating loss, and I am still looking to build a larger position. Manage your risk and do your own due diligence before placing any trades.
Short
by DollarSaenz
2
LEARN THE MOST IMPORTANT FOREX FUNDAMENTALS 📰 Even though I am a pure technician and I rely only on technical analysis when I trade, we can not deny the fact that fundamentals are the main driver of the financial markets. In this post, we will discuss the most important fundamentals that affect forex market. You can check coming fundamental news on TradingView in the economic calendar. The calendar button on the right side will display the coming news. Click "only high importance" button and the system will display only the most important news. Here are the most important fundamental releases that you should pay close attention to: 📍Unemployment rate. Unemployment rate reflects the percentage of people without a job in a selected country or region. Rising unemployment rate usually signifies an unhealthy state of the economy and negatively affects the currency strength. 📍Housing prices. Housing prices reflect people's demand for housing. Rising rate reflects a healthy state of the economy, strengthening purchasing power of the individuals and their confidence in the future. Growing demand for housing is considered to be one of the most important drivers in the economy. 📍Inflation. Inflation reflects the purchasing power of a currency. It is usually measured by evaluation of the price of the selected basket of goods or services over some period. High inflation is usually the primary indicator of the weakness of the currency and the unhealthy state of the economy. 📍Monetary policy. Monetary policy is the actions of central banks related to money supply in the economy. There are two main levers: interests rates and bank reserve requirements. Higher interest rates suppress the economy, making the currency stronger. Lower interests rates increase the money supply, making the economy grow but devaluing the national currency. 📍Political discourse. Political discourse is the social, economical and geopolitical policies of the national government. Political ideology determines the set of priorities for the ruling party that directly impacts the state of the economy. 📍Payrolls and earnings. Payroll reports reflect the dynamic of the creation of new jobs by the economy, while average earnings show the increase or decrease of the earnings of the individuals. Growing earnings and payrolls positively affect the value of a national currency and signify the expansion of the economy. Pay closes attention to these fundamentals and monitor how the market reacts to that data. What fundamentals do you consider to be the most important? ❤️Please, support my work with like, thank you!❤️
FOREXCOM:XAUUSDEducation
by VasilyTrader
1
Navigating the Chip Maze: Should You Invest in Synopsys?Navigating the Chip Maze: Should You Invest in Synopsys? Synopsys, a titan in the Electronic Design Automation (EDA) landscape, offers intriguing prospects for investors curious about the semiconductor industry. But before diving in, let's unpack the company, analyze its potential, and explore options – with a strong disclaimer: trading is inherently risky and not suitable for everyone. Synopsys: Powering the Chip Revolution Founded in 1986, Synopsys has carved a niche by providing essential tools and services for chip design and verification. Imagine them as the architects and inspectors of the tiny brains powering our devices. Their clients? Tech giants like Apple, Intel, and Samsung, relying on Synopsys for efficient, secure chip development. Products and Services: EDA Tools: The bread and butter – software enabling chip design, simulation, and verification. Silicon IP: Pre-designed building blocks, saving chipmakers time and money. Software Security and Quality: Tools to identify and fix vulnerabilities in software, crucial in an increasingly interconnected world. Financials and Performance: Revenue: $5.3 billion (FY 2023) Net Income: $1.2 billion (FY 2023) Ratings: Leader in Gartner's Magic Quadrant for EDA, "100 Best Companies to Work For" by Fortune So, Buy, Sell, or Hold? This is where things get tricky. Analysing publicly available information can't guarantee future performance. Several factors could influence Synopsys' stock price: Overall Semiconductor Market: A booming market benefits Synopsys, but downturns can impact sales. Technological Advancements: Staying ahead of the curve in EDA is crucial, and continuous innovation is key. Competition: Other EDA players like Cadence Design Systems pose constant competition. Options Trading: A Calculated Gamble? Remember, options involve significant risks. Buying call options bets on a stock price increase, while put options profit from a decrease. With expirations ranging from 1-12 months, you choose your timeframe and risk tolerance. However, options decay in value over time, and misjudgment can lead to substantial losses. The Verdict: Do Your Research, Proceed with Caution Synopsys is a prominent player in a growing industry, but the decision to invest ultimately rests on your individual financial goals and risk appetite. Conduct thorough research, understand the risks involved, and never invest more than you can afford to lose. Consider seeking professional financial advice before making any investment decisions. Risk Warning Trading stocks and options is a risky activity and can result in losses. You should only trade if you understand the risks involved and are comfortable with the potential for losses. Risk Warning: Trading is Not for Everyone It's essential to emphasize that trading stocks and options carries inherent risks. Market volatility, unpredictable events, and human error can lead to significant losses. Therefore, it's crucial to undertake thorough research, understand the underlying risks, and only invest funds that can be comfortably afforded to lose. ------------------------------------ Rating: STRONG BUY Risk Disclaimer! The article information and the data is for general information use only, not advice! --------------------------------------------------------------------- Risk Warning Trading stocks and options is a risky activity and can result in losses. You should only trade if you understand the risks involved and are comfortable with the potential for losses. Risk Disclaimer! General Risk Warning: Trading on the Financial Markets, Stock Exchange and all its asset derivatives is highly speculative and may not be suitable for all investors. Only invest with money you can afford to lose and ensure that you fully understand the risks involved. It is important that you understand how Trading and Investing on the stock exchange works and that you consider whether you can afford the high risk of loss!
NASDAQ:SNPSLong
by TheTrade_Academ
JBL (Long) - an outperforming value-playFundamentals The market is obviously overbought (still expecting a pullback), which could potentially give space to the stock to consolidate and form a cup-and-handle formation Fundamentally, the company is sound - it has seen a decrease in demand, reflected in the decrease of revenue. However, efficiency gains meant that profit has gone up regardless, hence the price rise. The earning are currently pricing another fall in revenue (yet, the price is still rising), hence a potential beat could serve as a nice boost to the share price. Why am I interested in a firm with declining revenue? Because it has a lot of things going - the firm is expanding into various sectors (including healthcare, semiconductor equipment, and AI-driven data centers), which gives it a diversified customer base + it has signed a massive $2.2bn agreement with BYD , giving it an entry into the EV market Cheap - P/E ratio of 23, despite the rise in price (based on Willliam O'Neill - the biggest winners of his careers had a starting P/E between 20-40) Only problem is a pretty high level of debt Technicals The usual - accumulated base , currently on the verge of breaking the upper resistance Another way to look at it is a broken bullish pennant The most likely scenario I see is a consolidation along with the market and then breaking either close to the earnings or on earnings The bottom indicator shows a recent outperformance compared to S&P500 Stochastics has been in the upper range for a while - again, showing that it will probably pull back for a little while Trade There are plenty way to go about it - I will likely choose to wait until the stock price consolidates around the resistance and wait for a breakout If the breakout happens now, I would once again advise to enter the trade, but with the caveat of giving the trade more space for a potential pullback back to the support Of course, if the stock starts receding from here, the trade is off; same goes for a failed break out Main caveat is the earnings - if the stock disappoints, then once again, the trade wouldn't be advisable Follow me for more analysis & Feel free to ask any questions you have, I am happy to help If you like my content, Please leave a like, comment or a donation , it motivates me to keep producing ideas, thank you :)
NYSE:JBLLong
by jurajholik
EURUAD I Detailed analysis ahead of AUD Cash Rate ReportWelcome back! Let me know your thoughts in the comments! ** EURAUD Analysis - Listen to video! We recommend that you keep this pair on your watchlist and enter when the entry criteria of your strategy is met. Please support this idea with a LIKE and COMMENT if you find it useful and Click "Follow" on our profile if you'd like these trade ideas delivered straight to your email in the future. Thanks for your continued support!
by BKTradingAcademy
2
DXY to continue declineDXY started a recovery from 100.257 from the heavy decline due to the pause in the interest rate hikes back in December 13th, 2023. The index started to recover from 28th December and to 102.723 due to the positive news from the last Friday NFP fundamentals. Price was quickly knocked down by the negative news on the ISMs late Friday. DXY January candle has done a retracement unto the 61.8%-78.6% (EMA 20) of the December bearish candle. As a result of the retracement on the December candle, the DXY is expected to retest the weekly EMA 200 on the key level 100.500 and as at the ending of last Friday, price was resisted by the weekly resistance. On the Daily, the DXY index is expected to retest the EMA 200 at 101.706 and subsequently retest the key level 101.500 again. The important fundamentals this week are mainly the Thursday's Core CPI m/m and the Friday's PP1 m/m where the economists are projecting a negative news for the CPI. We need to keep an eagle eye on the news this week to make informed decisions.
CAPITALCOM:DXY
by AbeikuGlobal_FX
2
USDJPY Bullish Ahead of US GDP AnnouncementHi Traders! USDJPY is in an ascending channel, and there is a bullish outlook on the market. Here are the details: After the pullback from the weekly high, the market seems to have found support near the channel support line. We are now looking for a break and close above the 20 EMA for a confirmation signal to target an exit near the weekly high. Preferred Direction: Buy Entry Level: 143.250 Stop Level: 142.271 Target Level: 145.209 Technical Indicators: 20 EMA Please make sure to click on the like/boost button 🚀 as your support greatly helps. Trade safely and responsibly. BluetonaFX
Long
by BluetonaFX
2
RECOGNIZING ENGULFING CANDLESTICK Hello traders! - I want to present the engulfing candlestick pattern and will try to explain why it is important to recognize this pattern formation. - The engulfing candlestick is a crucial tool in technical analysis for traders in financial markets. It serves as a powerful indicator of potential trend reversals or continuation, providing valuable insights into market sentiment and potential future price movements. - Recognizing and interpreting these patterns can enhance the ability to spot potential trend reversals, confirm existing trends, and make informed trading decisions. However, like any technical analysis tool, it is important to use engulfing patterns in conjunction with other indicators and risk management techniques for a comprehensive approach to trading. Follow, like, and comment to see the daily/weekly content: www.tradingview.com
BITSTAMP:ETHUSD
by GoodTradeST
USDJPY I Bullish USD unemployment claims long from supportWelcome back! Let me know your thoughts in the comments! ** USDJPY Analysis - Listen to video! We recommend that you keep this pair on your watchlist and enter when the entry criteria of your strategy is met. Please support this idea with a LIKE and COMMENT if you find it useful and Click "Follow" on our profile if you'd like these trade ideas delivered straight to your email in the future. Thanks for your continued support!
Long
by BKTradingAcademy
3
AI-Driven Market Analysis: Revolutionizing Financial InsightsIntroduction Market analysis has long been the cornerstone of financial decision-making, offering insights into market trends, asset valuation, and investment opportunities. Traditionally, this analysis has relied on a combination of statistical methods, fundamental analysis, and expert judgment to interpret market dynamics and forecast future movements. However, the finance industry is currently undergoing a seismic shift with the introduction and integration of Artificial Intelligence (AI). AI, with its unparalleled ability to process and analyze vast quantities of data at unprecedented speeds, is revolutionizing market analysis. Unlike traditional methods, which often struggle with the sheer volume and complexity of modern financial data, AI algorithms can quickly sift through global market data, news, and financial reports, identifying patterns and correlations that might escape human analysts. This capability is not just about handling data efficiently; it's about uncovering deeper market insights and offering more nuanced, informed perspectives on market movements. The growing role of AI in financial market analysis is multifaceted. It encompasses predictive analytics, which forecasts market trends and asset price movements; risk assessment, which evaluates potential risks and market volatility; and sentiment analysis, which gauges market sentiment by analyzing news, social media, and financial reports. These AI-driven approaches are transforming how investors, traders, and financial institutions make decisions, offering a more data-driven, precise, and comprehensive view of the markets. As we delve deeper into the world of AI-driven market analysis, it's crucial to understand both its potential and its limitations. While AI provides powerful tools for market analysis, it also introduces new challenges and considerations, particularly around data quality, algorithmic bias, and ethical implications. In this article, we'll explore how AI is changing the landscape of market analysis, examining its applications, benefits, and future prospects in the ever-evolving world of finance. The Evolution of Market Analysis A Brief History of Market Analysis in Finance Market analysis in finance has a storied history, evolving through various stages as it adapted to changing markets and technological advancements. Initially, market analysis was predominantly fundamental, focusing on the intrinsic value of assets based on economic indicators, financial statements, and industry trends. Technical analysis, which emerged later, shifted the focus to statistical trends in market prices and volumes, seeking to predict future movements based on historical patterns. Over the decades, these approaches were refined, incorporating increasingly sophisticated statistical models. However, they remained limited by the human capacity to process information. Analysts were constrained by the volume of data they could analyze and the speed at which they could process it. This often led to a reactive approach to market changes, rather than a predictive one. Transition from Traditional Methods to AI Integration The advent of computer technology brought the first major shift in market analysis. Computers enabled quicker processing of data and complex mathematical modeling, allowing for more sophisticated analyses that could keep pace with the growing volume and velocity of financial market data. The introduction of quantitative analysis in the latter part of the 20th century marked a significant step in this evolution, as it used complex mathematical and statistical techniques to identify market opportunities. The real transformation, however, began with the integration of AI and machine learning into market analysis. AI's ability to learn from data, identify patterns, and make predictions, has taken market analysis to an entirely new level. AI algorithms can analyze vast datasets — including historical price data, financial news, social media sentiment, and economic indicators — much faster and more accurately than any human analyst could. This integration of AI into market analysis has led to the development of predictive models that can forecast market trends and anomalies with a higher degree of accuracy. AI-driven tools are now capable of real-time analysis, providing instantaneous insights that help traders and investors make more informed decisions. Furthermore, AI's ability to continually learn and adapt to new data sets it apart from static traditional models, allowing for a more dynamic and responsive approach to market analysis. The transition from traditional methods to AI integration represents a paradigm shift in market analysis. This evolution is not just about adopting new tools but signifies a fundamental change in how financial markets are understood and navigated. As we continue to advance in the realm of AI, the potential for even more sophisticated and insightful market analysis grows, promising to reshape the landscape of finance in ways we are only beginning to comprehend. Fundamentals of AI in Market Analysis The integration of Artificial Intelligence (AI) and machine learning into market analysis marks a significant advancement in the way financial data is interpreted and utilized. Understanding the fundamentals of these technologies is essential to appreciate their impact on market analysis. Explanation of AI and Machine Learning AI refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. In the context of market analysis, AI enables the automation of complex tasks, including data processing, pattern recognition, and predictive analytics. Machine learning, a subset of AI, involves the development of algorithms that can learn and improve from experience without being explicitly programmed. In market analysis, machine learning algorithms analyze historical data to identify patterns and predict future market behavior. The more data these algorithms are exposed to, the more accurate their predictions become. Types of AI Models Used in Market Analysis 1. Neural Networks: Inspired by the human brain's structure, neural networks consist of layers of interconnected nodes that process data in a manner similar to human neurons. In market analysis, neural networks are used for their ability to detect complex patterns and relationships within large datasets. They are particularly effective in predicting price movements and identifying trading opportunities based on historical market data. 2. Regression Models: These models are fundamental in statistical analysis and are used to understand relationships between variables. In finance, regression models help in forecasting asset prices and understanding the impact of various factors (like interest rates, GDP growth, etc.) on market trends. 3. Time Series Analysis Models: Time series models are crucial in financial market analysis, as they are specifically designed to analyze and forecast data points collected over time. These models help in understanding and predicting trends, cyclicality, and seasonal variations in market data. 4. Natural Language Processing (NLP): NLP is used to analyze textual data, such as financial news, earnings reports, and social media posts, to gauge market sentiment. By processing and interpreting the nuances of human language, NLP models can provide insights into how public sentiment is likely to impact market movements. 5. Decision Trees and Random Forests: These models are used for classification and regression tasks. In market analysis, they can help in categorizing stocks into different classes based on their characteristics or in predicting the likelihood of certain market events. 6. Reinforcement Learning: This type of machine learning involves algorithms learning optimal actions through trial and error. In trading, reinforcement learning can be used to develop strategies that adapt to changing market conditions to maximize returns. Each of these AI models brings a unique set of capabilities to market analysis. Their ability to handle large volumes of data, recognize complex patterns, and make informed predictions is transforming the field of financial analysis, allowing for more nuanced and sophisticated market insights. As AI technology continues to evolve, its applications in market analysis are poised to become even more integral to financial decision-making. Key Applications of AI in Market Analysis The incorporation of Artificial Intelligence (AI) in market analysis has opened up new frontiers in understanding and predicting market behavior. AI's ability to process vast datasets and uncover intricate patterns provides invaluable insights for investors, traders, and financial analysts. Here are some key applications of AI in market analysis: 1. Predictive Analytics for Market Trends One of the most significant contributions of AI in market analysis is predictive analytics. AI algorithms, particularly those based on machine learning, are adept at analyzing historical data to forecast future market trends. These algorithms can identify subtle patterns and correlations that might be invisible to the human eye, enabling predictions about price movements, market volatility, and potential trading opportunities. As these models are exposed to more data over time, their accuracy in forecasting trends continues to improve. 2. Real-time Data Processing and Interpretation The financial markets generate vast amounts of data every second. AI excels in processing this data in real-time, providing instantaneous insights that are critical in a fast-paced trading environment. This capability allows for the monitoring of live market conditions, immediate identification of market shifts, and quick response to unforeseen events. Real-time analysis ensures that trading strategies can be adjusted promptly to capitalize on market opportunities or mitigate risks. 3. Automated Technical Analysis Technical analysis involves the study of historical market data, primarily price and volume, to forecast future market behavior. AI-driven automated technical analysis takes this to a new level by using algorithms to scan and interpret market data at scale. These algorithms can automatically identify technical indicators, chart patterns, and other key metrics used in technical analysis. This automation not only speeds up the analysis process but also eliminates human bias and error, leading to more objective and reliable insights. 4. Sentiment Analysis from News and Social Media Market sentiment, the overall attitude of investors towards a particular market or security, can significantly influence market movements. AI, particularly through Natural Language Processing (NLP), plays a crucial role in analyzing sentiment. It processes vast amounts of unstructured data from news articles, financial reports, social media posts, and other textual sources to gauge public sentiment towards the market or specific investments. By analyzing this data, AI can provide insights into how collective sentiment is likely to impact market trends and investment decisions. These applications highlight the transformative role of AI in market analysis. By leveraging AI for predictive analytics, real-time data processing, automated technical analysis, and sentiment analysis, market participants can gain a more comprehensive, accurate, and nuanced understanding of market dynamics. This advanced level of analysis is not only enhancing traditional market analysis methods but is also shaping new strategies and approaches in the financial sector. Case Studies: Success Stories of AI-Driven Market Analysis The integration of Artificial Intelligence (AI) in market analysis has not only been a topic of academic interest but has also seen practical applications with significant impacts on market decisions. Several real-world case studies illustrate how AI-driven analysis has transformed trading strategies and financial insights. Here are a couple of notable examples: Case Study 1: AI in Predicting Stock Market Trends One of the most prominent examples is the use of AI by a leading investment firm to predict stock market trends. The firm developed a machine learning model that analyzed decades of market data, including stock prices, trading volumes, and economic indicators. This model was designed to identify patterns that precede significant market movements. In one instance, the AI system predicted a substantial market correction based on unusual trading patterns it detected, which were subtle enough to be overlooked by traditional analysis methods. The firm acted on this insight, adjusting its portfolio to mitigate risk. When the market did correct as predicted, the firm was able to avoid significant losses, outperforming the market and its competitors. Case Study 2: Enhancing Hedge Fund Strategies with AI Another case involves a hedge fund that integrated AI into its trading strategies. The fund employed deep learning algorithms to analyze not just market data but also alternative data sources such as satellite images, social media sentiment, and supply chain information. This comprehensive analysis allowed the fund to identify unique investment opportunities and trends before they became apparent to the market at large. For example, by analyzing satellite images of retail parking lots, the AI could predict quarterly sales trends for certain companies before their earnings reports were released. Combining these insights with traditional financial analysis, the fund made informed decisions that led to substantial returns, demonstrating the power of AI in enhancing traditional investment strategies. Impact of AI on Specific Market Decisions These case studies illustrate the profound impact AI can have on market decisions. AI-driven market analysis allows for more accurate predictions, better risk management, and the identification of unique investment opportunities. It enables market participants to make more informed, data-driven decisions, often leading to better financial outcomes. Moreover, the use of AI in these examples highlights a shift towards a more proactive approach in market analysis. Rather than reacting to market events, AI allows analysts and investors to anticipate changes and act preemptively. This shift is not just about leveraging new technologies but represents a broader change in the philosophy of market analysis and investment strategy. In summary, these real-world applications of AI in market analysis showcase its potential to transform financial strategies and decision-making processes. As AI technology continues to evolve and become more sophisticated, its role in market analysis is set to become even more integral and impactful. Future of AI in Market Analysis The landscape of market analysis is rapidly evolving, with Artificial Intelligence (AI) at the forefront of this transformation. The future of AI in market analysis is not just about incremental improvements but also about paradigm shifts in how financial data is processed, interpreted, and utilized for decision-making. Here are some emerging trends and potential shifts that could redefine the role of AI in market analysis: Emerging Trends and Technologies 1. Advanced Predictive Analytics: The future will likely see more sophisticated predictive models using AI. These models will not only forecast market trends but also provide probabilistic scenarios, offering a range of possible outcomes with associated probabilities. 2. Explainable AI (XAI): As AI models become more complex, there will be a greater need for transparency and interpretability. XAI aims to make AI decision-making processes understandable to humans, which is crucial for trust and compliance in financial markets. 3. Integration of Alternative Data: AI's ability to process and analyze non-traditional data sources, such as satellite imagery, IoT sensor data, and social media content, will become more prevalent. This will provide deeper, more diverse insights into market dynamics. 4. Real-time Risk Management: AI will enable more dynamic risk assessment models that update in real-time, considering the latest market data and trends. This will allow for more agile and responsive risk management strategies. 5. Automated Compliance and Regulation Monitoring: AI systems will increasingly monitor and ensure compliance with changing regulatory requirements, reducing the risk of human error and the burden of manual oversight. 6. Quantum Computing in Market Analysis: The potential integration of quantum computing could exponentially increase the speed and capacity of market data analysis, allowing for even more complex and comprehensive market models. Potential Shifts in Market Analysis Strategies 1. From Reactive to Proactive Analysis: AI enables a shift from reacting to market events to proactively predicting and preparing for them. This will lead to more forward-thinking investment strategies. 2. Personalization of Investment Strategies: AI can tailor investment advice and strategies to individual investors' profiles, risk appetites, and goals, leading to more personalized financial planning and portfolio management. 3. Democratization of Market Analysis: Advanced AI tools could become more accessible to a broader range of investors and firms, leveling the playing field between large institutions and smaller players. 4. Increased Emphasis on Data Strategy: As AI becomes more central to market analysis, there will be an increased focus on data strategy - how to source, manage, and leverage data effectively. 5. Redefining Skill Sets in Finance: The rising importance of AI will change the skill sets valued in finance professionals. There will be a greater emphasis on data science skills alongside traditional financial analysis expertise. In conclusion, the future of AI in market analysis is not just promising but revolutionary. It is poised to redefine traditional practices, introduce new capabilities, and create opportunities for innovation in the financial sector. As these technologies advance, they will continue to shape the strategies and decisions of market participants, marking a new era in financial market analysis.
AMEX:SPYEducation
by JS_TechTrading
Unlocking Gold's Next Move Factors at Play in the Marketgold price is gaining momentum in anticipation of a further increase, with the Bull Flag pattern still in effect, giving hope to buyers. The 14-day Relative Strength Index (RSI) is approaching overbought levels, indicating the potential for more upward movement. The immediate resistance for the gold price is at $1,997, which corresponds to the five-month highs. Breaking above $2,000 on a weekly closing basis is crucial for further gains. The next significant resistance level is around $2,020, which represents the mid-May highs. On the other hand, if the price is rejected near the multi-month high of $1,997, it could lead to a sharp correction towards the previous day's low at $1,972. If it continues to decline, the next support level to watch is at $1,963, followed by the psychological level of $1,950. Gold is currently trading above $1,980 as it takes a pause after recent volatile trading. Factors influencing the market include the possibility of Japanese FX intervention, strong US Gross Domestic Product (GDP) data, ongoing Middle East concerns, and positive earnings from Amazon.com Inc. The focus is shifting to US inflation data. The positive market sentiment is partially suppressing the US Dollar and US Treasury bond yields, allowing gold to maintain its positive momentum. Investor optimism is fueled by strong post-market earnings reports from US tech companies, including Amazon.com Inc. Despite geopolitical tensions in the Middle East, including military strikes by the US and preparations for a ground invasion in Gaza, gold remains influenced by broader market sentiment, geopolitical developments, end-of-week flows, and bond market movements. The US Congress has a new Speaker of the House, Mike Johnson, and concerns about a government shutdown persist. While the US Personal Consumption Expenditures - Price Index is on the horizon, it may receive limited attention as the recent US Q3 GDP report already included quarterly PCE inflation figures. The report showed a 4.9% annualized growth rate in the third quarter, surpassing the 4.2% estimate, largely driven by factors such as consumer spending, inventories, exports, residential investment, and government spending. This economic performance aligns with the Federal Reserve's outlook for higher interest rates in the future, even though it didn't significantly impact the US Dollar or Treasury bond yields. Gold initially corrected lower in response to the data but later found support to close slightly higher on Thursday.
CAPITALCOM:GOLDLong
by sabellaFX