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Jobs vs. Inflation: Gold Steady Before PCE ShowdownHello, investors! Gold saw only a marginal 0.1% gain, closing at $3,739.42/oz on September 25. This struggle was due to better-than-expected US jobs data (jobless claims dropped sharply), which slightly pared back the market's expectation for a Fed rate cut in October (down to 85%). However, Gold maintains support from dovish Fed comments and potential political instability (like Trump's proposed 100% drug tariff). The entire market focus now shifts to today's (Sept 26) PCE Inflation Report. Expert Alert: If the PCE data is hotter than anticipated, Gold could face sharp, temporary downward pressure. Technical Analysis & Strategy Gold is currently consolidating within a triangle pattern and has yet to break the $375x resistance. While more selling pressure is possible before the PCE release, the long-term trend remains bullish. Outlook: Prioritize Buy if the price maintains above the Key Level $373x. If the news causes the price to break $373x, be ready to flip the strategy to Sell. Key Resistance: $3755, $3768, $3778 Key Support: $3738, $3727, $3712 Suggested Trading Strategy (Strict Risk Management): BUY SCALP Zone: $3739 - $3737 SL: $3733 TP: $3742 - $3747 - $3752 - $3757 - $3767 BUY ZONE Zone: $3704 - $3702 SL: $3694 TP: $3712 - $3722 - $3732 - $3742 - $3762 SELL ZONE Zone: $3776 - $3778 SL: $3786 TP: $3768 - $3758 - $3748 - $3728 - $3708 The market is at a critical juncture. What is your game plan for today? 👇 #Gold #XAUUSD #PCE #Fed #Inflation #TradingView #ATH
OANDA:XAUUSDLong
by Jeremy_NPC
CELLECOR GADGETS LTD – WEEKLY CHART ANALYSISFibonacci Levels and Price Structure Cellecor is currently trading near the 0.236 Fibonacci retracement level at ₹29.81 after a significant correction from its highs. Price has been consolidating above the previous support zone near ₹23.78, which also aligns with the “SL below 23” level marked on the chart. A bounce from the current area targets the immediate resistance cluster around the 0.382 (₹39.16) and 0.5 (₹46.71) Fibonacci levels, followed by 0.618 (₹54.27). Bullish Divergence on RSI A key highlight is the bullish RSI divergence visible on the weekly chart—while the price has made lower lows, the RSI has started forming higher lows. This divergence often hints at a potential reversal in trend or at least a pause in the ongoing downtrend, giving bulls a reason for cautious optimism. Trading Plan Entry Zone: Near current levels (₹29–31) if bullish reversal signals appear. Targets: ₹39 (0.382 Fib), ₹46.7 (0.5 Fib), ₹54.3 (0.618 Fib) based on Fibonacci retracement. Stop Loss: Below ₹23 as indicated on the chart for risk management. Confirmation: Look for volume pickup and continuation of positive RSI divergence. Disclaimer: This post is for educational purposes only, not financial advice. Please do your own due diligence before trading.
NSE:CELLECORLong
by cksharma23
EURUSD – Bearish Channel Continuation on H1EURUSD – Bearish Channel Continuation on H1 Market Overview EURUSD continues to move steadily within a descending channel, confirming a bearish market structure. Recent recovery attempts have been capped at supply zones, while liquidity remains concentrated at lower price levels. As long as the pair trades inside this channel, the preferred strategy is to look for selling opportunities. Technical Context The bearish channel remains intact, with strong seller defence in the 1.1720–1.1790 zone. Key resistance levels: 1.1753 and 1.1820. Only a clear break above 1.1820 would weaken the bearish scenario. Downside liquidity targets sit around 1.1630, with extended potential toward 1.1575 if selling pressure accelerates. Trading Scenarios 🔻 Priority – Sell Setups (with the channel trend) Sell Setup 1 Entry: 1.1720 – 1.1730 Stop Loss: 1.1750 Take Profit: 1.1695 – 1.1670 – 1.1652 – 1.1630 Sell Setup 2 Entry: 1.1780 – 1.1790 Stop Loss: 1.1810 Take Profit: 1.1755 – 1.1730 – 1.1700 – 1.1675 🔹 Alternative – Buy Setup (countertrend, lower probability) Buy Setup Entry: 1.1630 – 1.1620 Stop Loss: 1.1600 Take Profit: 1.1660 – 1.1680 – 1.1700 Note: This setup is only valid if price tests the demand zone around 1.1620–1.1630, which could trigger a short-term corrective bounce. Risk Management & Outlook Primary Bias: Stay bearish while price action remains within the channel. Invalidation: A confirmed H1/H4 close above 1.1820 invalidates the bearish view. Target: A decisive breakdown below 1.1630 could pave the way towards 1.1575. ✅ Conclusion: EURUSD remains in a clear downtrend. The main strategy is to sell rallies into resistance zones, targeting lower liquidity areas. Long positions can be considered only at strong demand levels, and should be treated as short-term corrective trades rather than a trend reversal.
Short
by ANFIBO_
AUDNZD Trading Idea – Momentum & Liquidity OutlookThe pair has been in a clear expansion phase, showing strength after multiple structure breaks. Momentum has favored the upside, while recent consolidation reflects market participants taking profits and rebalancing orders. A corrective wave appears to be unfolding, which is typical after strong impulsive moves. Such phases often allow liquidity collection before the next directional expansion. The broader sentiment suggests that buyers are still active, but short-term volatility may create temporary pullbacks. Educational Note: Markets move in cycles of impulse and correction. Recognizing these phases helps traders avoid chasing moves and instead prepare for continuation opportunities once the correction stabilizes.
Long
by XAU_EMPIRE
Part 3 Learn Institutional Trading 1. Definition Options are financial derivatives that give the buyer the right, but not the obligation, to buy or sell an underlying asset at a specified price within a specified time. 2. Types of Options Call Option – Right to buy the underlying asset. Put Option – Right to sell the underlying asset. 3. Option Premium The price paid by the buyer to the seller (writer) for acquiring the option. 4. Strike Price The predetermined price at which the underlying asset can be bought or sold. 5. Expiry Date The date on which the option ceases to exist and becomes worthless if not exercised. 6. In-the-Money (ITM) Call: Market price > Strike price Put: Market price < Strike price 7. Out-of-the-Money (OTM) Call: Market price < Strike price Put: Market price > Strike price 8. At-the-Money (ATM) Market price ≈ Strike price; option has no intrinsic value, only time value. 9. Intrinsic Value Difference between the underlying asset’s current price and the strike price (if favorable). 10. Time Value The portion of the option premium that reflects the time remaining until expiry. 11. Option Writers Sellers of options who receive the premium and are obligated to fulfill the contract if exercised. 12. American vs European Options American: Can be exercised anytime before expiry. European: Can only be exercised on expiry date. 13. Hedging Options are used to protect against price movements in the underlying asset. 14. Speculation Traders use options to bet on price movements with limited capital and defined risk. 15. Leverage Options allow traders to control a large position with small capital, amplifying both gains and losses. 16. Volatility Impact Higher volatility generally increases option premiums, as the likelihood of profitable moves rises. 17. Greeks Metrics that measure option risk: Delta – Sensitivity to underlying price changes Gamma – Rate of change of Delta Theta – Time decay Vega – Sensitivity to volatility Rho – Sensitivity to interest rates 18. Strategies Common strategies include: Covered Call Protective Put Straddle & Strangle Butterfly & Iron Condor 19. Risk Buyers: Limited risk (premium paid) Sellers: Potentially unlimited risk if naked (unhedged) 20. Market Participants Retail traders Institutional investors Hedgers, speculators, and arbitrageurs
MCX:GOLD1!Education
by SkyTradingZone
3
BTC Crashes to 3-Week Low: A True Nerve Test for TradersHello fellow traders, Bitcoin has entered an extremely tense phase! BTC has slipped below 109,000 USD, marking its lowest point in three weeks. The main pressure comes from the looming expiry of a massive 22-billion-USD options contract at the end of the month, which is driving strong short-term selling. On the daily chart, prices keep getting rejected at the downtrend line and the Ichimoku cloud, confirming that bears still hold the upper hand. The current scenario points to further downside, with key support zones at 104,000 USD (TP1) and 98,900 USD (TP2). These are the critical “do-or-die” levels to watch closely — only if BTC manages to hold above them can we expect a recovery once the options-driven selling pressure eases. In short: Bitcoin is at a make-or-break moment. Traders, keep your stops tight and stay alert!
Short
by ShadowReaper_
3
#AGARWALEYE - IPO Base BreakOut Script: AGARWALEYE Key highlights: 💡⚡ 📈 Inverse Head & Shoulders BreakOut in Weekly Time Frame 📈 Volume Okish during Breakout 📈 IPO Base BreakOut 📈 Can go for a swing trade BUY ONLY ABOVE 495 DCB ⏱️ C.M.P 📑💰- 493 🟢 Target 🎯🏆 – 22% ⚠️ Stoploss ☠️🚫 – 11% ⚠️ Important: Market conditions are Bad, Position size 25% per Trade. Protect Capital Always ⚠️ Important: Always Exit the trade before any Event. ⚠️ Important: Always maintain your Risk:Reward Ratio as 1:2, with this RR, you only need a 33% win rate to Breakeven. ✅Like and follow to never miss a new idea!✅ Disclaimer: I am not SEBI Registered Advisor. My posts are purely for training and educational purposes. Eat🍜 Sleep😴 TradingView📈 Repeat 🔁 Happy learning with MMT. Cheers!🥂
NSE:AGARWALEYELong
by MMT_MakeMoneyTrading
1
Part 2 Ride The Big Moves 1. Challenges of Option Trading Complexity: Advanced strategies require understanding multiple variables. Time Sensitivity: Options lose value as expiry approaches. High Risk for Sellers: Uncovered options can result in unlimited losses. Psychological Pressure: Rapid price movements can lead to emotional decision-making. 2. Regulatory and Market Structure Option trading is heavily regulated to protect investors. In India, options are governed by the Securities and Exchange Board of India (SEBI) and traded on exchanges like NSE and BSE. Globally, major options markets include CBOE, NASDAQ, and Eurex. Exchanges ensure standardized contracts, margin requirements, and settlement mechanisms to reduce counterparty risk. Clearing corporations act as intermediaries, guaranteeing the fulfillment of option contracts. 3. Real-World Applications Hedging Portfolio Risk: Institutional investors use index options to protect large portfolios. Speculation: Traders profit from anticipated market moves using calls and puts. Income Strategies: Covered calls and cash-secured puts generate consistent income. Arbitrage Opportunities: Exploit price discrepancies between options and underlying assets. 4. Psychological Aspects Successful option trading requires emotional discipline: Avoid chasing losses or overtrading. Stick to a trading plan and risk limits. Understand the impact of leverage on both profits and losses. Learn from each trade to improve strategy over time. 5. Future of Option Trading The option market continues to evolve with technology, algorithmic trading, and artificial intelligence. Key trends include: Automated option trading using AI and machine learning. Expanded product offerings in commodities, currencies, and ETFs. Increased retail participation due to easy-to-use trading platforms. Advanced risk management tools for institutional investors. Option trading is a powerful tool for investors and traders seeking flexibility, leverage, and risk management. While it offers substantial profit potential, it requires a deep understanding of market mechanics, pricing factors, and strategic planning. Combining technical analysis, fundamental insights, and disciplined risk management is crucial for success. Whether hedging an existing portfolio or speculating on market movements, options provide unmatched versatility for modern traders. By mastering the fundamentals, exploring strategies, and practicing disciplined risk management, traders can harness the power of options to enhance returns while mitigating risks in dynamic financial markets.
BSE:SENSEXEducation
by SkyTradingZone
2
Part 1 Ride The Big Moves 1. Introduction to Option Trading Option trading is one of the most versatile and dynamic segments of financial markets. Unlike traditional equity trading, where investors directly buy or sell shares, options give the right, but not the obligation, to buy or sell an underlying asset at a predetermined price on or before a specific date. This flexibility allows traders to hedge risks, speculate on market movements, and design strategies for income generation or protection against adverse price movements. Options are derivative instruments, meaning their value derives from an underlying asset, which can be stocks, indices, commodities, currencies, or ETFs. The global options market has grown exponentially over the last few decades due to its ability to provide leverage, risk management tools, and strategic investment opportunities for both retail and institutional traders. 2. Basic Concepts of Options To understand options trading, it’s essential to grasp some foundational concepts: 2.1 What is an Option? An option is a contract that grants the holder the right, but not the obligation, to buy or sell a specific asset at a predetermined price (called the strike price) within a defined period (expiry date). Call Option: Gives the holder the right to buy the underlying asset at the strike price. Put Option: Gives the holder the right to sell the underlying asset at the strike price. 2.2 Key Terminology Underlying Asset: The security on which the option is based. Strike Price / Exercise Price: The price at which the underlying asset can be bought or sold. Expiry Date: The date on which the option contract expires. Premium: The price paid by the buyer to the seller for the option. In-the-Money (ITM): Option has intrinsic value (e.g., a call option where strike price < current market price). Out-of-the-Money (OTM): Option has no intrinsic value (e.g., a call option where strike price > current market price). At-the-Money (ATM): Option strike price is approximately equal to the market price. 3. Types of Options Options can be broadly categorized based on style, market, and underlying asset. 3.1 Based on Style American Options: Can be exercised anytime before expiry. European Options: Can only be exercised on the expiry date. Bermuda Options: Can be exercised on specific dates prior to expiry. 3.2 Based on Market Exchange-Traded Options (ETOs): Standardized contracts traded on regulated exchanges. Over-The-Counter Options (OTC): Customized contracts traded directly between parties. 3.3 Based on Underlying Asset Equity Options: Based on individual stocks. Index Options: Based on market indices like Nifty, Sensex, S&P 500. Commodity Options: Based on commodities such as gold, oil, or agricultural products. Currency Options: Based on foreign exchange rates. ETF Options: Based on exchange-traded funds. 4. How Options Work Option trading involves two parties: the buyer and the seller (writer). Buyer (Holder): Pays the premium and holds the right to exercise the option. Seller (Writer): Receives the premium and has the obligation to fulfill the contract if the option is exercised. For example: Buying a call option gives the potential to profit if the underlying asset's price rises. Buying a put option profits if the underlying asset's price falls. Selling options can generate premium income but carries higher risk.
NSE:BANKNIFTYEducation
by SkyTradingZone
1
Wave 5 is about to start – today just time your Buy right!📊 Wave Perspective The market is still following the scenario of one more wave 5 increase. It is expected that on Friday morning, the price may move around 3765 to confirm the continuation trend. After confirmation, there will be 2 important zones to time your Buy for the big wave. ✅ Trading Plan Zone 1: High Entry – Main Priority Entry: 3749 – 3751 SL: 3746 TP: 3792 This is the first buying point, suitable for those who want to enter the wave early following the trend. Zone 2: Backup Entry – Last Support Entry: 3738 – 3736 Maximum SL: 3730 TP: 3792 This is a strong support zone, if the price breaks zone 1, this will be the "timing" zone to re-enter. Note: Since this is a backup entry, reduce Lot size, widen SL a bit, and tighten SL when the price matches to optimize risk. 📌 Capital Management Note Every order must comply with SL to avoid risks. Prioritize entering orders according to the big wave plan, avoid FOMO. EA setup: should be set to Only Buy according to the upward wave perspective. Analysis perspective is for reference only, combine with personal view before entering orders. 🎯 Expectation If the scenario is correct, the price may complete wave 5 at target 3792. Upon reaching TP, partial take profit can be done to secure profits.
OANDA:XAUUSDLong
by Linda_OneShotTrader
1
XAUUSD – FIBO MATRIX Trading Plan | Key Levels for TodayMarket Snapshot Gold is attracting steady buying interest as dovish Fed expectations keep the USD capped near 3-week highs. At the same time, geopolitical tensions and tariff concerns add to safe-haven demand. Focus now shifts to US PCE inflation data, which could trigger the next big move. 📍 Important Price Zones (M30) 🔴 SELL Reaction Zones 3767 – 377x → Major rejection area (Fibo 0.786). 3810 – 3817 → Strong SELL zone (Fibo 1.5 – 1.618). 🟢 BUY Support Zones 3725 → First support zone. 3690 – 3695 → Deep pullback support (Fibo confluence). 🎯 Trading Ideas 1️⃣ SELL Setup Entry: 3767 – 377x (if rejection signal shows). Targets: 3750 → 3725. SL: Above 3778. 2️⃣ BUY Setup Entry: 3725 with bullish confirmation. Targets: 3760 → 377x. SL: Below 3715. 3️⃣ Deep BUY Opportunity Entry: 3690 – 3695 zone. Targets: 3725 → 3760. SL: Below 3685. ⚡ Trading Insights Respect the Fibo reaction levels for clean entries. Risk range: 6–8 USD to avoid stop hunts. Book profits in steps: 1R → 2R → 3R for strong RR balance. 💬 Community Talk Do you see gold breaking above 3770 first, or dropping to 3725/3695 before bouncing back? Share your chart view 👇
OANDA:XAUUSDShort
by FranCis-MatrixFibo
XAUUSD – Range 3735–3755 now serves as trend confirmation zoneXAUUSD – Range 3735–3755 now serves as trend confirmation zone Technical Analysis Gold (XAUUSD) is moving within a narrow range of 3735–3755, and this price zone currently acts as a “pivot point” to confirm the next direction. Short-term resistance: 3755–3772, price has reacted strongly multiple times. If not decisively broken, selling pressure may continue. Key support: 3735, this is the decisive zone – breaking it will confirm a downward trend, targeting lower levels. Stronger resistance: 3790–3793, confluence of several previous peaks, where strong selling pressure may form. EMA200 H1 (3723) still supports the major uptrend, but the price has moved far and is now in the phase of retesting supply – demand zones. RSI (14) around 45–48, not yet in oversold territory but leaning towards the sellers. From a technical perspective, this is a market phase that requires confirmation: breaking above 3755 will reopen the upward momentum, while losing 3735 will reinforce short-term downward pressure. Trading Scenarios Sell Scenario (preferred if resistance holds): Sell 3769–3772, SL 3775, TP: 3755 – 3746 – 3737 Sell 3791–3793, SL 3798, TP: 3783 – 3772 – 3760 – 3745 Sell when price confirms below 3735, SL 3742, TP: 3726 – 3715 – 3702 – 3690 Buy Scenario (trend-following on breakout): Buy when price confirms above 3755, SL 3747, TP: 3766 – 3778 – 3790 Buy 3705–3702, SL 3697, TP: 3717 – 3726 – 3744 – 3763 – 3780 – 3790 Price Zones to Watch 3735–3755: trend confirmation range, most important in the short term. 3769–3772 and 3791–3793: strong resistance zones, potential Sell zone. 3702–3705: deep Buy zone, combined with strong support and EMA200. 3790: key resistance level, breaking it will reinforce the major uptrend. Outlook The gold market is in a decisive phase at the 3735–3755 range. Sellers have a short-term advantage, but if the price exceeds 3755, the uptrend may soon return. The best strategy is to trade based on price confirmation at key zones, combining profit-taking at each successive TP level to optimise gains. This is a reference scenario based on technical analysis, not an investment recommendation. Stay tuned for earlier analyses in upcoming sessions.
OANDA:XAUUSDShort
by Steven-GoldTrading
SENSEX 1 Week View📉 Weekly Technical Overview (as of Sep 26, 2025) Current Level: Approximately 80,782.73 points Weekly Decline: ~2,000 points, reflecting a drop of about 2.35% Technical Indicators: Relative Strength Index (RSI): The RSI is currently in the oversold zone, indicating potential for a short-term rebound if buying interest returns Moving Averages: Technical analysis suggests a bearish trend, with moving averages signaling a "strong sell" outlook Pivot Points: Key support and resistance levels are being closely monitored to gauge potential reversal points 🔍 Key Support and Resistance Levels Support Levels: Approximately 80,000–80,300 points Resistance Levels: Around 81,500–82,000 points These levels are crucial for determining the market's short-term direction. A break below support may indicate further downside, while a move above resistance could signal a potential recovery. 📈 Outlook While the short-term technical indicators suggest a bearish trend, the oversold conditions and key support levels imply that the market may be due for a corrective bounce. However, the ongoing geopolitical tensions and trade-related uncertainties could continue to exert downward pressure on the index. Investors are advised to monitor the upcoming trading sessions closely, as a decisive move above or below the established support and resistance levels could provide clearer signals for the next phase of market movement.
BSE:SENSEXLong
by TechnicalExpress
2
KIRLOSBROS 1 Day View📊 1-Day Technical Summary Current Price: ₹2,030.50 Open: ₹1,998.00 High: ₹2,084.40 Low: ₹1,954.70 Close: ₹2,030.50 Volume: 177,664 shares VWAP: ₹2,029.19 Price Change: -0.67% 🔍 Technical Indicators RSI (14-day): 39.91 — Indicates a bearish trend, approaching oversold conditions MACD: -16.34 — Suggests a bearish momentum Moving Averages: All short-term and long-term moving averages (MA5 to MA200) are signaling a Strong Sell Stochastic RSI: In a bearish zone, reinforcing the downward momentum 📈 Support & Resistance Levels Immediate Support: ₹1,954.70 (Day's low) Immediate Resistance: ₹2,084.40 (Day's high) ⚠️ Conclusion The 1-day technical indicators for Kirloskar Brothers Ltd. suggest a bearish outlook, with the stock trading below key moving averages and exhibiting negative momentum. Traders should exercise caution and consider waiting for a confirmation of trend reversal before initiating long positions.
NSE:KIRLOSBROSLong
by TechnicalExpress
2
Introduction to Sector Rotation Strategies in Trading1. Understanding Sector Rotation Sector rotation is a trading strategy used by investors and traders to capitalize on the cyclical movements of different sectors of the economy. The concept stems from the observation that economic conditions, business cycles, and market sentiment affect various sectors differently at different stages of the cycle. By identifying which sectors are likely to outperform in a given phase, traders can allocate capital strategically to maximize returns. The financial markets are influenced by macroeconomic factors such as interest rates, inflation, consumer spending, corporate earnings, and geopolitical events. These factors create patterns of performance among different sectors—technology, healthcare, financials, energy, consumer discretionary, consumer staples, industrials, materials, utilities, and real estate. Sector rotation involves moving investments from one sector to another based on expected performance changes due to these macroeconomic shifts. 2. The Conceptual Basis of Sector Rotation 2.1 Economic Cycles and Sector Performance Economic cycles consist of expansion, peak, contraction, and trough phases. Each phase favors certain sectors over others: Expansion: During periods of economic growth, cyclical sectors such as technology, consumer discretionary, and industrials tend to outperform. Peak: At the peak of economic activity, investors may rotate toward sectors with stable earnings and dividends, like utilities and consumer staples. Contraction: Defensive sectors such as healthcare, utilities, and consumer staples often outperform as the economy slows. Trough: At the bottom of the cycle, early cyclicals like financials and industrials start to recover, signaling the beginning of the next rotation cycle. This cyclical nature forms the theoretical foundation for sector rotation strategies. 2.2 Market Sentiment and Behavioral Economics Market sentiment, influenced by investor psychology, can drive sector rotation independently of the fundamental economic cycle. For example, bullish investor sentiment often drives funds into growth sectors like technology, while bearish sentiment increases the appeal of defensive sectors. Understanding behavioral tendencies, including fear and greed, is essential for timing sector rotations. 2.3 Relative Strength and Momentum Indicators Technical analysts often use relative strength (RS) and momentum indicators to identify sectors with potential for outperformance. Relative strength compares the performance of one sector to another or to the broader market index. Momentum indicators, such as the Moving Average Convergence Divergence (MACD) or the Relative Strength Index (RSI), provide signals for trend reversals and optimal entry points. 3. Key Sectors and Their Roles in Rotation To implement a sector rotation strategy, traders must understand the characteristics of each sector: Technology: High growth, highly sensitive to economic expansion, driven by innovation and corporate earnings. Healthcare: Defensive, stable cash flows, less sensitive to economic cycles. Financials: Sensitive to interest rates, economic growth, and credit demand. Energy: Influenced by commodity prices and global economic demand. Consumer Discretionary: Cyclical, benefits from higher consumer spending. Consumer Staples: Defensive, maintains stable performance during downturns. Industrials: Cyclical, tied to economic growth, manufacturing, and infrastructure investment. Materials: Tied to commodity prices and industrial demand. Utilities: Defensive, steady dividends, low growth, preferred during economic uncertainty. Real Estate: Sensitive to interest rates and economic cycles. Understanding the sensitivity of each sector to macroeconomic variables is crucial for timing rotations effectively. 4. Tools and Techniques for Sector Rotation 4.1 Fundamental Analysis Traders use fundamental analysis to assess sector health, focusing on factors like GDP growth, interest rates, inflation, and corporate earnings. Key indicators include: Purchasing Managers’ Index (PMI) Inflation and CPI reports Central bank monetary policies Employment and consumer spending data These indicators help predict which sectors are likely to outperform in upcoming phases of the economic cycle. 4.2 Technical Analysis Technical tools assist in identifying the right timing for sector rotations: Sector ETFs: Exchange-traded funds provide exposure to specific sectors and allow for easy rotation. Moving Averages: Indicate trend direction and momentum for sector indices. Relative Strength Charts: Compare performance of sectors against the market benchmark. MACD and RSI: Detect overbought or oversold conditions, signaling potential rotation points. 4.3 Quantitative Models Quantitative models, including factor-based investing and algorithmic strategies, allow traders to systematically rotate sectors based on data-driven signals. Factors such as valuation ratios, growth metrics, momentum, and volatility can be incorporated into sector rotation models. 5. Benefits of Sector Rotation Strategies Enhanced Returns: Capturing sector outperformance can generate alpha beyond broad market gains. Risk Management: Rotating into defensive sectors during downturns reduces portfolio volatility. Diversification: Moving across sectors balances exposure and mitigates sector-specific risks. Flexibility: Can be applied in both long-only and long-short portfolios. Data-Driven Decision Making: Combines fundamental, technical, and macroeconomic analysis for strategic investment. 6. Challenges in Sector Rotation While sector rotation can be profitable, it comes with challenges: Timing Risks: Entering or exiting a sector too early can reduce returns or create losses. Transaction Costs: Frequent rotation may increase brokerage fees and slippage. Complex Analysis: Requires constant monitoring of economic indicators, earnings reports, and technical trends. Market Volatility: Unexpected events can disrupt rotation patterns. Behavioral Biases: Traders may react emotionally, missing optimal rotation opportunities. Successful sector rotation demands discipline, research, and a systematic approach. 7. Practical Implementation of Sector Rotation 7.1 Using Sector ETFs Exchange-traded funds (ETFs) tracking sector indices provide an easy method for implementing rotation strategies. For example: Technology ETF: QQQ or XLK Healthcare ETF: XLV Financial ETF: XLF Investors can allocate capital dynamically based on economic signals and technical indicators. 7.2 Rotating Across Industry Sub-Sectors Advanced traders rotate within sectors to capture micro-trends. For example, within the technology sector, semiconductors may outperform software during one cycle, while cloud computing leads in another. 7.3 Integrating with Broader Portfolio Strategy Sector rotation can complement broader portfolio strategies like: Value investing Growth investing Momentum trading Dividend investing Integrating sector rotation helps enhance returns and manage risks across market cycles. 8. Case Studies and Historical Examples 8.1 The 2008 Financial Crisis During the 2008 financial crisis, defensive sectors like consumer staples, healthcare, and utilities outperformed, while cyclical sectors like financials and industrials suffered. Traders who rotated into defensive sectors preserved capital and captured relative outperformance. 8.2 Post-COVID-19 Recovery (2020–2021) Technology and consumer discretionary sectors led the recovery due to shifts in consumer behavior and digital adoption. Investors who rotated into these growth sectors early benefited from significant gains. 8.3 Commodity Price Cycles Energy and materials sectors often experience rotations based on commodity cycles. Traders tracking oil, gas, and metals prices can anticipate sector performance to adjust portfolio allocations accordingly. 9. Sector Rotation and Global Markets Sector rotation is not limited to domestic markets. International investors can apply rotation strategies to: Emerging markets Developed markets Regional ETFs Global macroeconomic factors, such as interest rate differentials, trade policies, and geopolitical tensions, create opportunities for cross-border sector rotation. 10. The Future of Sector Rotation With the rise of technology, artificial intelligence, and data analytics, sector rotation strategies are becoming more sophisticated. AI-driven models can: Analyze vast economic datasets Predict sector performance with machine learning Automate rotation decisions Reduce human bias Furthermore, thematic investing and ESG (Environmental, Social, Governance) trends are influencing sector performance, providing new dimensions for rotation strategies. 11. Conclusion Sector rotation is a dynamic and nuanced trading strategy that leverages economic cycles, market sentiment, and technical analysis to maximize portfolio performance. By understanding sector behavior, monitoring macroeconomic indicators, and applying disciplined entry and exit strategies, traders can enhance returns while managing risks. Though complex, sector rotation remains a powerful tool for both institutional and individual investors seeking to navigate the ever-changing landscape of financial markets.
NSE:NIFTYEducation
by TechnicalExpress
1
Public vs Private Banks in Trading1. Introduction Banking institutions play a crucial role in the financial ecosystem, acting as intermediaries between savers and borrowers, facilitating economic growth, and influencing market stability. Within India, banks are broadly classified into public sector banks and private sector banks, both of which participate in trading activities but with different operational strategies, risk appetites, and market impacts. Trading by banks refers to activities such as: Equity trading: Buying and selling shares of companies. Debt trading: Involving government bonds, corporate bonds, and other fixed-income instruments. Derivatives trading: Futures, options, swaps for hedging or speculative purposes. Forex trading: Buying and selling foreign currencies. Commodity trading: Participation in commodity markets, often indirectly. The distinction between public and private banks in these trading activities affects liquidity, market volatility, investor confidence, and overall financial stability. 2. Overview of Public and Private Banks 2.1 Public Sector Banks (PSBs) Public sector banks are banks in which the government holds a majority stake (usually over 50%), giving it significant control over operations and policies. Examples in India include: State Bank of India (SBI) Punjab National Bank (PNB) Bank of Baroda (BoB) Characteristics: Government ownership provides implicit trust and perceived safety. Mandated to serve social and economic objectives, sometimes at the cost of profitability. Larger branch networks, especially in semi-urban and rural areas. Regulatory oversight tends to be stricter, focusing on stability rather than aggressive profits. 2.2 Private Sector Banks Private banks are owned by private entities or shareholders with the primary objective of profit maximization. Examples include: HDFC Bank ICICI Bank Axis Bank Characteristics: More technologically advanced and customer-centric. Flexible, agile, and willing to explore new trading strategies. High focus on efficiency, profitability, and risk-adjusted returns. Typically have fewer rural branches but dominate urban and digital banking. 3. Role of Banks in Trading Banks are central players in the financial markets. Their trading activities can be categorized as: 3.1 Proprietary Trading Banks trade with their own capital to earn profits. Private banks often engage more aggressively due to higher risk appetite. 3.2 Client Trading Banks execute trades on behalf of clients, such as corporates, mutual funds, or high-net-worth individuals. Both public and private banks participate, but private banks may offer more advanced advisory and trading platforms. 3.3 Hedging and Risk Management Banks use derivatives and other instruments to hedge risks associated with: Currency fluctuations Interest rate changes Commodity price movements Public banks often hedge conservatively due to regulatory oversight, whereas private banks may engage in complex derivative strategies. 4. Trading in Different Market Segments 4.1 Equity Markets Public Banks: Typically invest in blue-chip companies and government initiatives; tend to hold stable equity portfolios. Private Banks: Active in IPOs, mutual funds, and portfolio management; may leverage proprietary trading desks for short-term gains. 4.2 Debt Markets Public Banks: Major participants in government bonds, treasury bills, and large-scale debt issuance. Private Banks: Active in corporate bonds, debentures, and structured debt instruments. 4.3 Forex Markets Public Banks: Facilitate trade-related foreign exchange, hedging imports/exports; conservative trading. Private Banks: Aggressive forex trading, currency swaps, and derivatives to maximize profits. 4.4 Commodity Markets Public Banks: Minimal direct participation; may finance commodity traders. Private Banks: May engage in commodity-linked derivatives for proprietary or client trading. 4.5 Derivatives Markets Public Banks: Hedging-driven; lower exposure to high-risk derivatives. Private Banks: Speculation and hedging; higher use of futures, options, and structured products. 5. Comparative Performance Analysis 5.1 Profitability Private banks typically have higher net interest margins and return on equity. Public banks focus on financial inclusion and stability; profits are secondary. 5.2 Risk Management Public banks prioritize capital preservation; may carry higher non-performing assets (NPAs). Private banks employ advanced risk modeling; NPAs are lower, but exposure to market risks is higher. 5.3 Market Impact Public banks stabilize markets during crises due to government backing. Private banks drive market innovation through new trading products and digital platforms. 6. Regulation and Compliance Both public and private banks in India are regulated by the Reserve Bank of India (RBI). Public Banks: Must follow government mandates on priority sector lending, capital adequacy, and lending limits. Private Banks: While regulated, they enjoy more freedom in investment strategies, provided they adhere to Basel III norms and RBI guidelines. 7. Technological and Digital Edge Public Banks Historically slower in adopting technology. Initiatives like Core Banking Solutions (CBS) have modernized operations. Digital trading platforms are limited. Private Banks Early adopters of digital trading platforms, mobile banking, and AI-based trading analytics. Focus on client-driven solutions like portfolio optimization, robo-advisory, and high-frequency trading. 8. Case Studies 8.1 State Bank of India (SBI) Large-scale government bond trading. Stable equity portfolio; focus on corporate and retail clients. Conservative derivatives trading. 8.2 HDFC Bank Active in equity derivatives and forex trading. Aggressive risk-adjusted proprietary trading strategies. Strong digital platforms for client trading. 9. Challenges and Opportunities Public Banks Challenges: High NPAs, bureaucratic hurdles, and slower adoption of technology. Limited risk-taking capacity restricts trading profits. Opportunities: Government support can stabilize during crises. Potential for technology partnerships to modernize trading platforms. Private Banks Challenges: Vulnerable to market volatility and regulatory scrutiny. Aggressive trading strategies can backfire during crises. Opportunities: High profit potential through innovative trading and fintech integration. Can attract high-net-worth clients and institutional investors. 10. Impact on Financial Markets Public Banks: Act as stabilizers; provide liquidity during market stress. Private Banks: Drive market efficiency and innovation; increase competition. Combined Effect: Both types ensure a balanced ecosystem where stability and growth coexist. 11. Future Trends in Banking and Trading Integration of AI and Machine Learning: Private banks leading in algorithmic trading and predictive analytics. Public banks adopting AI for risk management and operational efficiency. Blockchain and Digital Assets: Both sectors exploring blockchain for secure and transparent trading. Cryptocurrency exposure remains limited but monitored. Sustainable and ESG Investments: Increasing focus on green bonds, socially responsible funds, and ESG-compliant derivatives. Global Market Expansion: Private banks expanding cross-border trading. Public banks supporting government-backed international trade financing. 12. Conclusion Public and private banks serve complementary roles in the trading ecosystem: Public Banks: Conservative, stable, government-backed, stabilizing force in markets. Private Banks: Agile, profit-oriented, technologically advanced, driving market innovation. A robust financial system requires both sectors to function effectively. Public banks ensure economic stability, especially in times of crisis, while private banks provide innovation, efficiency, and competitive trading solutions. For investors, understanding these differences is critical when assessing bank stock investments, trading opportunities, or market trends.
CAPITALCOM:GOLDEducation
by TechnicalExpress
1
How AI is Transforming Financial Markets1. Introduction Financial markets have traditionally relied on human expertise, intuition, and historical data analysis to make decisions. While these methods have served well, they are often limited by human cognitive biases, data processing constraints, and the speed at which information is absorbed and acted upon. Artificial Intelligence, encompassing machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics, is enabling financial institutions to overcome these limitations. AI can process vast amounts of structured and unstructured data, identify patterns, make predictions, and execute actions in real-time. This has paved the way for smarter trading strategies, enhanced risk mitigation, and improved customer experiences. The integration of AI in finance is not just a technological upgrade; it represents a paradigm shift in the structure and functioning of financial markets globally. 2. AI in Trading and Investment 2.1 Algorithmic Trading Algorithmic trading refers to the use of computer algorithms to automate trading strategies. AI enhances algorithmic trading by making it adaptive, predictive, and capable of handling complex patterns that traditional models may overlook. Machine Learning Algorithms: AI-powered algorithms can analyze historical data and detect subtle market patterns to make predictions about asset price movements. Unlike traditional models that rely on fixed rules, machine learning algorithms continuously learn and adapt based on new data. High-Frequency Trading (HFT): AI facilitates HFT by enabling trades to be executed in milliseconds based on micro-market changes. AI models analyze price fluctuations, order book dynamics, and market sentiment to execute trades at optimal moments. Predictive Analytics: AI predicts market trends, volatility, and asset price movements with high accuracy. Techniques like reinforcement learning allow models to simulate and optimize trading strategies in virtual market environments before applying them in real markets. 2.2 Robo-Advisors Robo-advisors are AI-driven platforms that provide automated investment advice and portfolio management services. They use algorithms to assess an investor’s risk profile, financial goals, and market conditions, creating personalized investment strategies. Accessibility: Robo-advisors democratize investing by making professional-grade financial advice accessible to retail investors at low costs. Portfolio Optimization: AI dynamically adjusts portfolios based on market conditions, maximizing returns while minimizing risk. Behavioral Analysis: By analyzing investor behavior, AI can provide personalized guidance to reduce emotional trading, which is a common source of losses. 2.3 Sentiment Analysis AI leverages natural language processing to analyze news articles, social media, earnings calls, and financial reports to gauge market sentiment. Market Prediction: Positive or negative sentiment extracted from textual data can provide early signals for stock price movements. Event Detection: AI detects geopolitical events, regulatory changes, or corporate announcements that could impact markets. Investor Insight: By analyzing sentiment patterns, AI helps investors anticipate market reactions, enhancing decision-making efficiency. 3. Risk Management and Compliance 3.1 Credit Risk Assessment AI has transformed how banks and financial institutions assess creditworthiness. Traditional credit scoring models relied on limited historical data and rigid criteria, but AI can evaluate a broader set of variables. Alternative Data: AI analyzes non-traditional data such as social behavior, transaction patterns, and digital footprints to assess credit risk. Predictive Modeling: Machine learning models predict the probability of default more accurately than conventional statistical models. Dynamic Risk Assessment: AI continuously monitors borrowers’ behavior and financial health, updating risk profiles in real-time. 3.2 Market Risk and Portfolio Management AI enhances market risk management by modeling complex market dynamics and stress scenarios. Scenario Analysis: AI simulates various market conditions, helping fund managers understand potential portfolio risks. Volatility Prediction: Machine learning models forecast market volatility using historical data, enabling proactive risk mitigation strategies. Optimization: AI optimizes portfolio allocations by balancing expected returns against potential risks in real-time. 3.3 Regulatory Compliance and Fraud Detection Financial markets are heavily regulated, and compliance is critical. AI automates compliance processes and fraud detection. Anti-Money Laundering (AML): AI detects suspicious transaction patterns indicative of money laundering or financial crimes. RegTech Solutions: AI ensures adherence to regulatory requirements by automating reporting, monitoring, and auditing processes. Fraud Detection: AI identifies anomalies in transaction data, preventing fraudulent activities with greater speed and accuracy than human oversight. 4. Enhancing Market Efficiency AI improves market efficiency by reducing information asymmetry and enhancing decision-making for market participants. 4.1 Price Discovery AI algorithms facilitate faster and more accurate price discovery by analyzing multiple data sources simultaneously, including market orders, economic indicators, and news. 4.2 Liquidity Management AI optimizes liquidity by forecasting cash flow needs, monitoring order book dynamics, and predicting market depth. 4.3 Reducing Transaction Costs Automated trading and AI-driven market analysis reduce operational and transaction costs, enabling more efficient markets. 5. AI in Customer Experience and Personalization 5.1 Personalized Financial Services AI personalizes customer experiences by analyzing behavior patterns, transaction histories, and preferences. Tailored Products: Banks and fintech firms offer customized investment products, loans, and insurance policies. Chatbots and Virtual Assistants: AI-driven chatbots handle routine queries, transactions, and financial advice, improving customer satisfaction. Financial Wellness Tools: AI analyzes spending and saving patterns to provide actionable advice, helping users achieve financial goals. 5.2 Behavioral Insights By understanding investor behavior, AI helps reduce irrational decisions, encourages disciplined investing, and supports financial literacy. 6. AI-Driven Innovation in Financial Products AI is not only enhancing existing financial services but also driving the creation of new products. Algorithmic Derivatives: AI designs derivatives and structured products tailored to specific investor needs. Dynamic Insurance Pricing: AI models assess risk dynamically, enabling real-time premium adjustments. Smart Contracts and Blockchain: AI combined with blockchain technology automates contract execution, reducing counterparty risks and improving transparency. 7. Challenges and Risks of AI in Financial Markets While AI offers numerous advantages, its adoption also comes with challenges: 7.1 Model Risk AI models are only as good as the data and assumptions underlying them. Poorly designed models can lead to significant financial losses. 7.2 Ethical and Regulatory Concerns AI’s decision-making process is often opaque (“black-box problem”), raising concerns about accountability, fairness, and compliance. 7.3 Cybersecurity Threats AI systems are vulnerable to cyber-attacks, data breaches, and adversarial attacks that can manipulate outcomes. 7.4 Market Stability The widespread use of AI in high-frequency trading and algorithmic strategies may amplify market volatility and systemic risks. 8. Case Studies of AI Transforming Financial Markets 8.1 JPMorgan Chase: COiN Platform JPMorgan’s Contract Intelligence (COiN) platform uses AI to analyze legal documents and extract key data points, reducing manual review time from thousands of hours to seconds. 8.2 BlackRock: Aladdin Platform BlackRock’s Aladdin platform integrates AI for risk management, portfolio optimization, and predictive analytics, providing a comprehensive view of market exposures and investment opportunities. 8.3 Goldman Sachs: Marcus and Trading Algorithms Goldman Sachs uses AI-driven trading algorithms for securities and commodities, while Marcus leverages AI to enhance customer lending and risk assessment processes. 8.4 Retail Trading Platforms Platforms like Robinhood and Wealthfront utilize AI to offer personalized recommendations, portfolio rebalancing, and real-time insights to millions of retail investors. 9. Future Trends 9.1 Explainable AI (XAI) Future financial markets will increasingly demand AI systems that are transparent and explainable, ensuring accountability and regulatory compliance. 9.2 Integration with Quantum Computing Quantum computing combined with AI could revolutionize financial modeling, enabling previously impossible optimizations and simulations. 9.3 Cross-Asset AI Trading AI will integrate insights across equities, commodities, currencies, and derivatives, enhancing cross-asset trading strategies. 9.4 Democratization of AI Tools As AI tools become more accessible, retail investors and smaller institutions will be able to leverage advanced analytics, leveling the playing field. 9.5 Sustainable and Ethical Finance AI will help investors incorporate ESG (Environmental, Social, Governance) factors into investment decisions, promoting sustainable financial markets. 10. Conclusion AI is fundamentally reshaping financial markets, making them faster, smarter, and more efficient. From algorithmic trading and risk management to customer personalization and product innovation, AI’s applications are extensive and transformative. However, this transformation comes with challenges, including ethical concerns, regulatory compliance, cybersecurity risks, and market stability issues. As AI continues to evolve, financial markets will likely witness further innovation, democratization, and efficiency. Institutions that effectively harness AI while managing its risks will be best positioned to thrive in the increasingly complex and dynamic global financial ecosystem. In essence, AI is not just changing how financial markets operate—it is redefining the very nature of finance, turning data into intelligence, and intelligence into strategic advantage. The future of financial markets will be defined by those who can master the synergy between human insight and artificial intelligence.
NSE:RELIANCEEducation
by TechnicalExpress
1
Types of Trading in India: An In-Depth Analysis1. Equity Trading (Stock Trading) Overview: Buying and selling shares of companies listed on stock exchanges like NSE and BSE. Key Features: Can be short-term (intraday) or long-term (investment). Investors earn through capital appreciation and dividends. Benefits: High liquidity, transparency, regulated market. Risks: Market volatility can lead to significant losses. Example: Buying shares of Reliance Industries and selling after a price rise. 2. Intraday Trading Overview: Buying and selling stocks within the same trading day. Key Features: Traders do not hold positions overnight. Relies heavily on technical analysis. Benefits: Quick profits, no overnight risk. Risks: High leverage increases risk; requires constant monitoring. Example: Buying Infosys in the morning and selling by afternoon for short-term gains. 3. Futures and Options (Derivatives Trading) Overview: Contracts whose value is derived from underlying assets like stocks, indices, or commodities. Key Features: Futures obligate buying/selling at a fixed date. Options provide the right, not obligation, to buy/sell. Benefits: Hedging, leverage, speculation. Risks: High risk due to leverage; can lead to large losses. Example: Buying Nifty Call Option to profit from a market rise. 4. Commodity Trading Overview: Buying and selling commodities such as gold, silver, oil, and agricultural products on MCX or NCDEX. Key Features: Includes spot, futures, and options contracts. Influenced by global demand, supply, and geopolitical factors. Benefits: Portfolio diversification, inflation hedge. Risks: Price volatility, geopolitical risks, storage costs (for physical commodities). Example: Trading crude oil futures anticipating a price surge. 5. Currency Trading (Forex Trading) Overview: Trading in foreign currency pairs like USD/INR, EUR/INR. Key Features: Can be spot or derivative contracts. Driven by global economic events and RBI policies. Benefits: High liquidity, global opportunities. Risks: Exchange rate volatility, leverage risks. Example: Buying USD against INR expecting INR to weaken. 6. Mutual Fund Trading Overview: Investing in professionally managed funds that pool money from multiple investors. Key Features: Equity, debt, hybrid funds available. Can be SIP (Systematic Investment Plan) or lump sum. Benefits: Professional management, diversification, lower risk. Risks: Returns are market-linked; management fees apply. Example: Investing in HDFC Equity Fund via monthly SIP. 7. Bond and Debt Securities Trading Overview: Trading government and corporate bonds, debentures, and fixed-income instruments. Key Features: Predictable income through interest payments. Less volatile than equity markets. Benefits: Capital preservation, steady returns. Risks: Interest rate fluctuations, credit risk of issuers. Example: Buying 10-year government bonds for stable returns. 8. Cryptocurrency Trading Overview: Buying and selling digital currencies like Bitcoin, Ethereum, and Indian crypto tokens. Key Features: Highly volatile and largely unregulated in India. Includes spot trading and futures trading. Benefits: Potential for high returns, global market access. Risks: Extreme volatility, regulatory uncertainty, cyber risks. Example: Trading Bitcoin on WazirX anticipating a price spike. 9. IPO and Primary Market Trading Overview: Investing in companies during their Initial Public Offering before they are listed. Key Features: Subscription-based allotment via brokers or banks. Potential for listing gains. Benefits: Opportunity to buy at a lower price before listing. Risks: Listing may underperform; market sentiment affects gains. Example: Applying for LIC IPO shares expecting listing gains. 10. Algorithmic and High-Frequency Trading (HFT) Overview: Automated trading using computer algorithms to execute orders at high speed. Key Features: Relies on pre-set rules, AI, and quantitative models. Popular among institutional traders and hedge funds. Benefits: Speed, accuracy, can exploit small price differences. Risks: Requires technical expertise, market flash crashes possible. Example: Using algorithmic trading to scalp Nifty futures in milliseconds. Conclusion India offers a wide spectrum of trading opportunities for investors and traders—from traditional stock markets to cutting-edge algorithmic and crypto trading. Choosing the right type depends on risk tolerance, capital, time horizon, and knowledge of the market. While equities, derivatives, and commodities dominate in terms of popularity, newer avenues like cryptocurrencies and algorithmic trading are gaining traction rapidly.
BITSTAMP:BTCUSDEducation
by TechnicalExpress
1
LiamTrading – Gold may fake a move before dropping Gold is trading around the 375x region and might exhibit a "fake breakout" upwards before adjusting downwards. The price structure on the H4 chart shows: Strong resistance is located at the 3770–3773 region, coinciding with the 0.786 – 1.0 Fibonacci extension area. This is a confluence zone prone to a downward reaction. The main trendline remains upward, but the RSI is gradually weakening, indicating that the buying force is not as strong. Short-term support is at 3710–3713, also the 0.5 – 0.618 fibo zone, suitable for buy scalping orders. A larger support area is at 3688–3691, where it converges with the trendline bottom and important Fibonacci, considered a sustainable "buy zone." Trading Plan Reference Sell: 3770 – 3773, SL 3778, TP 3756 – 3743 – 3725 – 3710 Buy scalping: 3710 – 3713, SL 3705, TP 3725 – 3736 – 3748 – 3760 Buy zone: 3688 – 3691, SL 3684, TP 3699 – 3710 – 3725 – 3736 – 3745 – 3760 In summary, gold may create a false upward move to the resistance zone 3770–3773 before reversing to adjust. Traders should patiently wait for confirmation signals at key price zones to enter optimal orders and manage risks tightly. This is my personal view on XAUUSD. If you find it useful, follow for the fastest updates on upcoming scenarios, continuously updated at comulity
OANDA:XAUUSDShort
by LiamTradingFX
LiamTrading XAUUSD Scenario Today Fibo & Volume Profile AnalysisLiamTrading XAUUSD Scenario Today:Fibo & Volume Profile Analysis Gold, after testing the 375x zone, has shown clear signs of weakening. On the H1 chart, the price structure is forming an adjustment phase aligning with key Fibonacci and Volume Profile levels. This is the time when the market starts to “filter” liquidity, creating opportunities for both short sell orders and buy orders at strong support zones. Technical Analysis Fibonacci indicates the 0.786 – 1.0 zone around 3756–3758 coincides with strong resistance and FVG, with a high potential for a reversal. Volume Profile points out the POC area around 3735–3740, if breached, it will pave the way for deeper downward pressure. The confluence support zone of 0.618 fibo + large volume around 3688–3691 is suitable for scalping buy. Further, the area 3648–3651 is reinforced by VAL and the bottom of the volume profile, making it a strong long-term “Buy zone.” Trading Plan Reference Sell zone: 3756 – 3758, SL 3763, TP 3750 – 3748 – 3736 – 3710 – 3690 – 3655 Buy scalping: 3688 – 3691, SL 3685, TP 3701 – 3715 – 3728 Long-term Buy zone: 3648 – 3651, SL 3640, TP 3670 – 3688 – 3700 – 3718 – 3733 – 3755 In summary, gold is moving in accordance with the technical structure confirmed by Fibonacci and Volume Profile. Today's scenario prioritises observing reactions around the sell zone 3756–3758 to find short opportunities, and waiting to buy at value zones 369x and 365x for the recovery wave. This is my personal view on XAUUSD. If you want the fastest updates on the next gold scenarios, follow me and join the community to stay informed.
OANDA:XAUUSDShort
by LiamTradingFX