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Part 8 Trading Master ClassOption Pricing Option prices depend on several factors, collectively described by the Black-Scholes model. The main components are: Underlying price: The current price of the stock or index. Strike price: Determines whether the option is ITM, ATM, or OTM. Time to expiration: Longer duration means higher premium, as there’s more time for the market to move favorably. Volatility: Higher volatility increases premium since price movements are more unpredictable. Interest rates and dividends: These have smaller effects but are still part of option pricing. The relationship between these factors is known as the “Greeks.”
MCX:SILVER1!Education
by SkyTradingZone
PHOENIXLTD 1 Week Time Frame ✅ Current Context The stock is trading around ~ ₹1,750 – ₹1,770 region. Technical indicators show mixed signals: daily SMAs are around ₹1,575-₹1,600, meaning price is above medium-term averages. Momentum indicators: some overbought signals present; trend strength moderate. 🔍 My Derived Key Levels (for next 1-2 weeks) Given current price and the above pivots, useful levels to watch: Near-term support: ~ ₹1,700 – ₹1,730 (psychological + price above SMA) First major support: ~ ₹1,470 – ₹1,500 zone (around S1) Immediate resistance: ~ ₹1,800 – ₹1,820 Stretch target / higher resistance: ~ ₹1,640 + zone (~R2) if a pull-back happens and this acts as resistance on any retracement
NSE:PHOENIXLTDLong
by Knowledgehub
Part 7 Trading Master ClassBasic Terminology To understand option trading, one must know a few key terms: Strike Price: The price at which the underlying asset can be bought (call) or sold (put). Premium: The price paid by the buyer to the seller for the option contract. Expiration Date: The date on which the option contract expires. In India, options typically expire every Thursday (for weekly options) or the last Thursday of the month (for monthly options). In-the-Money (ITM): A call option is ITM when the market price is above the strike price; a put option is ITM when the market price is below the strike price. Out-of-the-Money (OTM): A call is OTM when the market price is below the strike, and a put is OTM when the market price is above the strike. At-the-Money (ATM): When the market price and strike price are roughly equal.
NSE:RELIANCEEducation
by SkyTradingZone
XAUUSD – H4 PERSPECTIVE: WAIT FOR LIQUIDITY TEST BEFORE DEEP...💛 XAUUSD – H4 PERSPECTIVE: WAIT FOR LIQUIDITY TEST BEFORE DEEP DECLINE 🎯 🌤 1. Overview Hello everyone 💬 Gold just ended the week with a candle closing at the 4001 region, after a slight rise and then holding steady in the upward channel on the H4 frame. The current sideways movement is making it difficult for many traders to find short-term entry points. However, the 4090 area still has an unfilled liquidity gap (FVG), which coincides with the upper edge of the price channel. This could be the next short-term destination before the market adjusts for a deeper decline. From my perspective, gold might rise another leg to sweep the liquidity in the upper region, then adjust back to the 3785 area – an important Fibonacci Retracement zone, where a strong reaction from buyers is highly likely. 💹 2. Technical Analysis 📈 The price structure is still maintaining an upward trend within the H4 price channel, with each subsequent low being higher than the previous one. 🟣 The 4090–4102 area is a liquidity region yet to be swept, located at the channel's peak – a high probability of a downward reaction. 🔹 The potential Buy zone around 3785–3789 coincides with Fibonacci 0.618 and a strong historical support area. 💫 Main scenario: Price might test the upper liquidity region, then adjust down to the Buy Zone before forming a larger upward momentum. 🎯 3. Reference Trading Plan 💢 SELL scenario (short-term) Entry: 4098–4102 ｜ SL: 4112 TP: 4078 – 4025 – 3998 – 3920 – 3875 – 3785 💖 BUY scenario (long-term strategy) Entry: 3785–3789 ｜ SL: 3777 TP: 3810 – 3865 – 3925 – 3988 ⚠️ 4. Important Notes Prioritize short-term Sell if there is a strong reaction at the 4090–4100 region. Long-term Buy only if the price adjusts deeply to the 3785–3790 region. Limit emotional trading – this is a liquidity accumulation phase before major volatility. 🌷 5. Conclusion & Interaction with LanaM2 Gold is following the accumulation path before forming a major wave 💛 Be patient and observe reactions at the two critical regions 4090 and 3785, as these could be the pivot points for the coming week.
OANDA:XAUUSDLong
by Lana_M2
GOLD SHOWS WEAKNESS – SELL THE RALLY TOWARD DEMAND!📅 WEEKLY PLAN – November 8, 2025 🚀 HOOK TITLE: 🔥 GOLD SHOWS WEAKNESS – SELL THE RALLY TOWARD DEMAND! 🔥 📊 Market Analysis: Gold continues to respect a bearish market structure, showing clear Break of Structure (BOS) and Change of Character (CHoCH) patterns on the 2H chart. After multiple rejections from the upper zones, price is likely forming a lower high before heading to retest the demand below. The market is currently consolidating between 4020–3980, suggesting a potential liquidity grab before the next impulsive drop. 🎯 Trade Plan: 🔹 Setup 1 – Sell Zone (4037–4039) Entry: 4037–4039 SL: 4043 TP1: 4018 TP2: 3976 TP3: 3931 🔹 Setup 2 – Sell Zone (4018–4020) Entry: 4018–4020 SL: 4024 TP1: 3976 TP2: 3931 TP3: 3929 🔹 Setup 3 – Buy Reaction Zone (optional scalp) Entry: 3931–3929 SL: 3923 TP1: 3974 TP2: 4018 (Only consider if strong bullish rejection or FVG fill appears) 📈 Outlook: Bias remains bearish unless price breaks and closes above 4043 (invalidating lower-high structure). Smart traders should sell into strength, waiting for confirmation wicks or bearish engulfing on lower timeframes (M15–M30) inside the marked zones. 📌 Weekly Bias: 🟥 SHORT / SELL MODE Targeting the imbalance fill toward 3930 area.
OANDA:XAUUSDShort
by Anneliese_Engel
Gold 4H – Key Liquidity Zones Ahead of US PMI & Fed Commentary🥇 XAUUSD – Weekly Smart Money Outlook | by Ryan_TitanTrader 📈 Market Context Gold continues to consolidate within a tight 4H range as traders prepare for a week influenced by U.S. PMI releases, Fed speeches, and shifting rate-cut expectations. Mixed economic signals — including softer labour data but resilient manufacturing prints — have kept gold trapped between supply overhead and stacked demand levels below. Institutional flows remain cautious, with markets waiting for clarity on the Fed’s stance. This uncertainty often fuels liquidity-driven sweeps, making this week especially favourable for SMC-style setups. Short-term volatility is expected as price interacts with major liquidity pools on both ends of the range. 🔎 Technical Analysis (4H / SMC View) • Price is moving within a well-defined range structure, with repeated liquidity grabs on both sides indicating accumulation by larger players. • The latest 4H ChoCH signals continued hesitation from buyers near the mid-range, hinting that the market may engineer another sweep before committing to a directional leg. • A significant Premium Supply Zone at 4154–4152 sits just above recent equal highs — an attractive area for liquidity hunts followed by potential short-term distribution. • Conversely, the Discount Demand Zone at 3907–3909 aligns with previous structural reaction levels and sits below a liquidity shelf, making it an ideal zone for re-accumulation. • Expect engineered stop-hunts around mid-range liquidity (4000–4016) before a stronger move develops. 🟢 Buy Zone: 3907–3909 SL: 3900 TP targets: 3978 → 4003 → 4016 → 4125 Rationale: • Discount zone within the current 4H range • Liquidity resting below the structure lows • Potential accumulation before the next bullish impulse 🔴 Sell Zone: 4154–4152 SL: 4161 TP targets: 4080 → 4016 → 3978 → 3920 Rationale: • Premium supply positioned above equal-high liquidity • Likely area for a sweep before corrective downside • Confluence with previous 4H structure rejection ⚠️ Risk Management Notes • Wait for M15 ChoCH or BOS confirmation inside each zone before entering. • Expect liquidity manipulation around 4000–4016, especially during US session opens. • Avoid entries 10–15 minutes before major Fed or PMI releases to limit spread expansion. • Scale partial profits at each structural target to lock in gains while letting runners play out. ✅ Summary Gold remains in a controlled 4H range with clear institutional footprints above and below the current price. Smart Money is likely to engineer a move into either the 4150 supply or the 3900 demand before choosing its next major direction. Both setups offer high-probability opportunities when combined with intraday confirmations. Stay patient, wait for liquidity sweeps, and respect structure. Premium sells remain valid at 4154–4152, while discounted buys are favoured at 3907–3909. 🔔 FOLLOW RYAN_TITANTRADER for daily SMC setups ⚡
OANDA:XAUUSDShort
by Ryan_TitanTrader
Option Buying vs Option Selling in the Indian Market1. Understanding Options in Brief An option is a financial derivative contract that gives the buyer the right, but not the obligation, to buy or sell an underlying asset (such as Nifty, Bank Nifty, or stocks) at a predetermined price (strike price) before or on a specific date (expiry date). Call Option (CE): Gives the buyer the right to buy the asset. Put Option (PE): Gives the buyer the right to sell the asset. The seller (also known as the writer) of an option, on the other hand, has the obligation to fulfill the contract if the buyer decides to exercise it. 2. Option Buying – The Right Without Obligation Definition: When a trader buys an option, they pay a premium to acquire the right to buy (Call) or sell (Put) the underlying asset. This is a leveraged position where the maximum loss is limited to the premium paid. Example: Suppose Nifty is trading at 22,000 and a trader buys a 22,000 CE at ₹150. If Nifty rises to 22,400 by expiry, the option may be worth ₹400, giving a profit of ₹250 (₹400 - ₹150). If Nifty falls or remains below 22,000, the option expires worthless, and the buyer loses ₹150 (premium). Advantages of Option Buying: Limited Risk: The maximum loss is limited to the premium paid. Unlimited Profit Potential: Profits can be substantial if the underlying asset moves sharply in the expected direction. Leverage: Traders can control large positions with a small amount of capital. Hedging Tool: Option buyers can hedge existing stock or portfolio positions against adverse movements. Simplicity: Easier to understand for beginners as risks are predefined. Disadvantages of Option Buying: Time Decay (Theta): The value of options erodes as expiry approaches if the price does not move favorably. Low Probability of Success: Most options expire worthless; hence, consistent profitability is difficult. Implied Volatility (IV) Risk: A drop in volatility can reduce option prices even if the direction is correct. Requires Precise Timing: The move in the underlying must be quick and significant to overcome time decay. 3. Option Selling – The Power of Probability Definition: Option sellers (writers) receive a premium by selling (writing) options. They are obligated to fulfill the contract if the buyer exercises it. Sellers profit when the market remains stable or moves against the option buyer’s position. Example: If a trader sells a Nifty 22,000 CE at ₹150 and Nifty remains below 22,000 till expiry, the seller keeps the entire ₹150 premium as profit. However, if Nifty rises to 22,400, the seller incurs a loss of ₹250 (₹400 - ₹150). Advantages of Option Selling: High Probability of Profit: Since most options expire worthless, sellers statistically have better odds. Benefit from Time Decay: Sellers gain as the option premium reduces with each passing day. Volatility Advantage: When volatility drops, option prices fall, benefiting sellers. Range-Bound Profitability: Sellers can profit even in sideways markets, unlike buyers who need strong price movement. Disadvantages of Option Selling: Unlimited Risk: Losses can be theoretically unlimited, especially for uncovered (naked) positions. Margin Requirement: Sellers must maintain significant margin with brokers, reducing leverage. Emotional Stress: Constant monitoring is needed as rapid moves in the market can cause heavy losses. Complex Strategies Required: Often, sellers use spreads or hedges to control risk, which requires advanced knowledge. 4. Market Behavior and Strategy Selection Option Buyers Thrive When: The market makes sharp and fast movements in a particular direction. Implied volatility is low before the trade and increases later. There is a news event or earnings announcement expected to cause large swings. The trend is strong and directional (e.g., breakout setups). Example Strategies for Buyers: Long Call or Long Put Straddle or Strangle (when expecting volatility) Call Debit Spread or Put Debit Spread Option Sellers Succeed When: The market remains range-bound or moves slowly. Implied volatility is high at the time of entry and drops later. Time decay favors them as expiry nears. The trader expects no major event or breakout. Example Strategies for Sellers: Short Straddle / Short Strangle Iron Condor Credit Spreads (Bull Put Spread, Bear Call Spread) Covered Call Writing 5. Role of Implied Volatility (IV) and Time Decay In the Indian market, IV and Theta play crucial roles in deciding profitability. For Buyers: They need an increase in IV (expectation of higher movement). Rising IV inflates option premiums, helping buyers. For Sellers: They gain when IV drops (post-event or consolidation), as option prices fall. Time Decay (Theta) always works against buyers and in favor of sellers. For example, in the last week before expiry, options lose value rapidly if the underlying does not move significantly. 6. Regulatory and Practical Considerations in India Margins: SEBI’s framework requires SPAN + Exposure margin, making naked selling capital-intensive. Liquidity: Nifty, Bank Nifty, and FinNifty have high liquidity, making both buying and selling viable. Taxation: Option profits are treated as business income for both buyers and sellers. Brokerage and Slippage: Active option sellers often face higher transaction costs due to large volumes. Retail Participation: Most retail traders prefer buying options due to low capital requirements, while professional traders prefer selling for steady income. 7. Real-World Insights Around 70–80% of retail traders in India buy options, but most lose money due to time decay and poor timing. Professional traders and institutions prefer option writing using hedged strategies to generate consistent returns. Successful traders often combine both — buying for directional plays and selling for income generation. 8. Which Is Better – Buying or Selling? There’s no one-size-fits-all answer. It depends on market conditions, trading capital, and risk appetite. If you have small capital, prefer buying options with strict stop-loss and a clear directional view. If you have large capital and can manage risk with spreads or hedges, selling options can provide consistent returns. Combining both (for example, selling options in high volatility and buying in low volatility) can create balance. Conclusion The debate between option buying and option selling in the Indian market revolves around risk vs. probability. Option buyers enjoy limited risk and unlimited profit potential but low success rates. Option sellers face higher risk but benefit from time decay and probability in their favor. In essence: Buy options when expecting a big, fast move. Sell options when expecting a range-bound or stable market. A disciplined approach, risk management, and understanding of volatility are the keys to succeeding in either strategy. In the dynamic Indian derivatives market, mastering both sides of the trade — when to buy and when to sell — transforms an ordinary trader into a consistently profitable one.
MCX:NATURALGAS1!Education
by TechnicalExpress
AI and Machine Learning in Stock Market Forecasting1. Introduction to AI and Machine Learning in Finance Artificial Intelligence refers to the simulation of human intelligence in machines that can learn, reason, and make decisions. Machine Learning, a subset of AI, involves algorithms that improve automatically through experience. In finance, AI and ML are used to analyze market data, forecast trends, and automate trading strategies. Unlike traditional statistical models that rely on fixed mathematical relationships, ML models adapt dynamically to changing market conditions. This adaptability makes them particularly useful in forecasting stock prices, where patterns are non-linear, complex, and influenced by multiple interacting variables. 2. Traditional Methods vs. AI-Based Forecasting Traditional stock market forecasting techniques — such as fundamental analysis, technical analysis, and econometric models — depend heavily on historical data and human interpretation. These models often assume linear relationships and static patterns, which may not hold true in volatile markets. In contrast, AI and ML models can process: Large volumes of structured and unstructured data Non-linear dependencies Real-time information updates For example, a traditional regression model may struggle to account for sudden market shocks, whereas an ML algorithm can learn from data anomalies and adapt to new market behaviors through continuous learning. 3. Machine Learning Techniques in Stock Market Forecasting AI-driven forecasting utilizes various ML algorithms, each suited for different kinds of financial predictions: a. Supervised Learning Supervised learning algorithms are trained using labeled historical data — for example, past stock prices and associated indicators — to predict future values. Common models include: Linear and Logistic Regression Support Vector Machines (SVM) Random Forests Gradient Boosting Machines (XGBoost, LightGBM) These algorithms can forecast future price movements, classify stocks as “buy,” “hold,” or “sell,” and identify potential risks. b. Unsupervised Learning In unsupervised learning, algorithms detect hidden patterns in data without labeled outcomes. Techniques like K-Means Clustering and Principal Component Analysis (PCA) are used to: Identify stock groupings with similar behavior Detect anomalies or unusual trading activities Segment markets based on volatility or performance trends c. Deep Learning Deep Learning models, particularly Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks, are highly effective in time-series forecasting. These models capture temporal dependencies — such as how past price movements influence future prices — and are capable of handling sequential data efficiently. For instance, an LSTM model can analyze years of price history, trading volume, and sentiment data to forecast the next day’s closing price. d. Reinforcement Learning Reinforcement Learning (RL) is a powerful AI approach where algorithms learn optimal trading strategies through trial and error. The system receives rewards for profitable trades and penalties for losses, gradually learning to maximize returns. RL is increasingly used in algorithmic trading systems that make autonomous buy/sell decisions based on real-time market data. 4. Data Sources for AI-Based Forecasting AI and ML models rely on diverse data sources to generate accurate predictions: Historical Market Data: Price, volume, volatility, and returns over time. Fundamental Data: Earnings, balance sheets, and macroeconomic indicators. Alternative Data: News sentiment, social media trends, Google searches, and even satellite imagery. Technical Indicators: Moving averages, RSI, MACD, and Bollinger Bands. By integrating structured (numerical) and unstructured (text, images) data, AI models can capture market sentiment and detect emerging trends that traditional models may overlook. 5. Applications of AI and ML in Stock Forecasting a. Price Prediction Machine learning models are used to forecast short-term and long-term price movements. Algorithms such as LSTMs and Random Forests analyze time-series data to predict next-day or next-week stock prices. b. Sentiment Analysis Natural Language Processing (NLP), a branch of AI, interprets financial news, analyst reports, and social media content to gauge market sentiment. For example, a surge in negative news sentiment about a company may signal an upcoming drop in its stock price. c. Portfolio Optimization AI systems analyze correlations among different assets and optimize portfolios to maximize returns while minimizing risk. Tools like Markowitz’s modern portfolio theory can be enhanced by machine learning models that adapt dynamically to market volatility. d. High-Frequency Trading (HFT) In high-frequency trading, AI algorithms execute thousands of trades per second based on micro-movements in prices. ML models process real-time market data streams and make ultra-fast trading decisions with minimal human intervention. e. Risk Management and Anomaly Detection AI systems monitor trading patterns to identify abnormal behavior, potential fraud, or risk exposure. These models help financial institutions comply with regulations and safeguard investor assets. 6. Benefits of AI and ML in Forecasting Accuracy and Efficiency: AI models can analyze vast datasets quickly and produce precise forecasts. Adaptability: They adjust to evolving market dynamics without manual recalibration. Automation: Reduces human error and enables algorithmic trading. Sentiment Integration: Incorporates behavioral and psychological aspects of markets. Continuous Learning: Models improve over time as they process more data. AI thus empowers traders, analysts, and institutions to make data-driven decisions and respond rapidly to market changes. 7. Challenges and Limitations Despite their promise, AI and ML in stock forecasting face certain limitations: Data Quality Issues: Inaccurate or biased data can mislead models. Overfitting: ML models may perform well on training data but fail in real-world scenarios. Black-Box Nature: Many AI models lack transparency in how they generate predictions, posing trust issues. Market Unpredictability: Events like political crises, pandemics, or natural disasters can disrupt models trained on historical data. Ethical and Regulatory Concerns: Use of AI-driven trading can lead to market manipulation or flash crashes if not monitored. Hence, human oversight remains essential even in AI-based systems. 8. Future of AI and ML in Financial Forecasting The future of AI in finance lies in hybrid models — combining human expertise with machine intelligence. Emerging technologies such as Quantum Computing, Explainable AI (XAI), and Federated Learning will further enhance forecasting capabilities. Moreover, integration of blockchain data, real-time global sentiment, and predictive analytics will make AI-driven models more robust and transparent. In the coming years, AI systems are expected to play a central role not just in forecasting but also in risk management, compliance automation, and personalized investment advice through robo-advisors. 9. Conclusion AI and Machine Learning have transformed the way investors, institutions, and analysts approach the stock market. From pattern recognition and sentiment analysis to autonomous trading and portfolio optimization, these technologies offer powerful tools for understanding and predicting market behavior. While challenges such as data quality, overfitting, and transparency remain, continuous advancements in AI research promise more reliable and interpretable forecasting systems. Ultimately, the combination of human insight and AI-driven analytics represents the future of intelligent investing — where data, algorithms, and human judgment work hand in hand to navigate the ever-changing financial markets.
OANDA:XAUUSDEducation
by TechnicalExpress
The Psychology Behind Winning TradesThe Psychology Behind Winning Trades 🧠💹✨ Introduction – Hook: 📊 “Why do some traders consistently win 💰 while others struggle 💔?” It’s rarely the strategy—it’s the mindset behind the trade! 🧠🌟 Your emotions, thoughts, and biases control your decisions, even with perfect technical skills. 🎯 1️⃣ What is Trading Psychology? Trading psychology is the study of how emotions and mental habits affect trading decisions. 🌈🧘‍♂️ It’s about understanding: How fear 😨, greed 😍, or impatience ⏳ impacts your trades Why you sometimes ignore your rules 📝 How discipline 💪 can make the difference between profit 🏆 and loss 💸 💡 Tip: Even the best strategies fail if your mind isn’t in control. 🧠✨ 2️⃣ Common Psychological Traps & How They Appear in Trades Trap Emoji Effect Example in Trading Fear 😨 Exiting too early Closing a winning trade because you’re scared of losing profits 💔 Greed 😍 Holding losing trades Waiting for a loss to “come back” and losing more money 💸 FOMO 🏃‍♂️💨 Jumping impulsively Entering trades last minute because everyone else is trading 🚀 Revenge Trading 😤🔥 Emotional loss-chasing Trying to recover losses by taking bigger, risky trades 💣 💡 Insight: Recognizing these emotions is the first step to controlling them. 🌟 3️⃣ How to Master Your Trading Mind 1️⃣ Pre-Trade Preparation 🧘‍♀️✅ Check your emotional state before trading 🕊️ Confirm your trade plan is clear 📋✨ 2️⃣ During the Trade ✋🎯 Stick to your rules, don’t let emotions take over 💪🔥 Avoid impulsive exits or entries ⏱️❌ 3️⃣ Post-Trade Reflection 📖🖊️ Keep a Trading Journal: note emotions, mistakes & wins ✨📓 Review trades to improve your mindset over time 📈🌟 4️⃣ Pro Tips for Winning Psychology 🔥 Mindset Checklist: Am I trading calmly? 😌💭 Am I following my plan? 📋✅ Am I chasing losses or profits emotionally? ⚖️💡 💡 Daily Mindset Practice: Meditation 🧘‍♂️, journaling ✍️, or reviewing trades 📊 can help you stay disciplined under pressure 💎🌟 5️⃣ Why It Matters Trading without psychology = strategy leaks money 💸💨 Emotional control = consistency, higher win rates, confidence 🏆💪 Professionals don’t just trade charts—they trade themselves 🧠✨ 6️⃣ Engagement Section 👇 Question for your audience: “What’s the biggest psychological trap YOU’ve faced in trading? Share your story below! 💬💭💖”
TVC:GOLDEducation
by XAU_EMPIRE
Cholamandalam Financial Holdings Ltd (CFHL) Triangle Breakout 1DCholamandalam Financial Holdings Ltd (CFHL) – Triangle Breakout & 1-Year Resistance Breakout 🚀 📊 Technical View: CFHL has given a triangle breakout along with a 1-year resistance breakout, indicating strong bullish momentum. If Trend continues, The price action also shows a successful retest of the breakout zone, shows trend continuation. Resistance Turned Support: ₹1650 – previously a resistance, now acting as strong support. Current Action: Price broke above the ₹1650 range, retested the level today , and is now moving upward again. Next Resistance Targets Levels: ₹1824 / ₹2004 Support Levels: ₹1536 / ₹1410 🏦 Company Overview: Cholamandalam Financial Holdings Limited (CFHL), incorporated in 1949, is a part of the Murugappa Group, one of India’s most diversified business conglomerates. CFHL is a Non-Deposit Taking Systemically Important Core Investment Company (CIC) registered with the Reserve Bank of India (RBI). The company holds substantial investments in group companies and provides a diverse range of financial products and risk management services to individual and corporate clients through its subsidiaries and group companies. 📈 For educational purpose only. Not a buy/sell recommendation.
NSE:CHOLAFINLong
by Madhumitha_Prabhu
Tamilnad Mercantile Bank (TMB) – Update | 3.5% Move from Our Lvl🟢 Tamilnad Mercantile Bank (TMB) – Update | 3.5% Move from Our Level 🚀 Latest Update : Our analysis shared around ₹499 has played out well — TMB made an intraday high of ₹517, gaining nearly 3.5% from the mentioned level. 🏦 Company Overview: Tamilnad Mercantile Bank Limited is one of the oldest and leading old private sector banks in India. The bank offers a wide range of banking products and services to retail, MSME, agricultural, and corporate customers. Retail Products: Home loans, personal loans, auto loans, educational loans, business loans, and security-backed loans. MSME Portfolio: Loans for manufacturing, traders, and service sector enterprises. Agricultural Loans: Offered to individual farmers, farmer groups, agri-businesses, and agri-corporates. 📊 Technical View: High Reached: ₹517 (▲3.5%) Resistance: ₹510 – price tested and faced mild rejection here. Supports: ₹466 / ₹440 💡 View: The stock showed strong momentum from the support zone and approached its major 1-year resistance area near ₹510–₹515. A sustained close above ₹515 can confirm a breakout and open the next upside targets of ₹535 / ₹600. 📈 For educational purpose only. Not a buy/sell recommendation.
NSE:TMBLong
by Madhumitha_Prabhu
This is a GBP/JPY (4H) setup This is a GBP/JPY (4H) setup — a bearish structure with two target points clearly marked below the current price. 🧭 Chart Breakdown: The price has broken below the ascending trendline and the Ichimoku Cloud, showing bearish momentum. The first target point is at a nearby support level, and the second is a deeper extension move. 🎯 Targets: First target: around 174.60 – 174.70 zone Second target: around 172.90 – 173.00 zone 🔍 Summary: Trend: Bearish below 176.50 Targets: TP1 → 174.60 TP2 → 172.90 Invalidation: Break back above 176.80 (re-entry into the cloud/trendline)
Short
by HussaiN_JaNi
1
SUI– Breakout Setup Forming, Bulls Eyeing a Move Toward $20SUI/USDT – Breakout Setup Forming, Bulls Eyeing a Move Toward $20 SUI is building a strong re-accumulation base after months of correction. The $1.6–$2 demand zone continues to attract heavy buying interest, the same zone that triggered the last major rally. Technical Highlights: ✅ Multiple liquidity grabs with strong rebounds ✅ $1.6–$2 zone acting as key accumulation area ✅ Descending trendline compression nearing breakout ✅ Structure remains bullish above $1.6 A confirmed breakout above the descending trendline could launch SUI into a high-momentum phase, targeting higher resistances. Upside Levels: $4.8 / $10 / $20 – Macro channel target Accumulation View: Smart money is active below $2, positioning early before expansion. As long as $1.6 holds, the structure favors a bullish continuation. High compression. Low noise. When this trendline breaks, volatility will speak loud. NFA & DYOR
Long
by CryptoPatel
ETH/USDT (4H) chartETH/USDT (4H) chart: The price is currently trading near a support zone (around $3,250–3,300). The chart shows a potential bullish setup with two marked target points above. The Ichimoku Cloud suggests resistance around mid-levels before a full reversal. Here’s the breakdown 👇 🔹 Key Levels: Support zone: $3,250 – $3,300 First target (inside the cloud): around $3,700 – $3,750 Second target (top / resistance zone): around $4,150 – $4,200 🔹 Summary: If ETH holds the current support and breaks above the cloud: Target 1: ≈ $3,700 Target 2: ≈ $4,200 Invalidation: below $3,200 (support breakdown)
Long
by HussaiN_JaNi
3
ASTRAL golden crossAstral golden cross, FVG, BUY for target with stoploss as shown in chart. Astral Limited financial and key features: Market Cap: ₹41,790 crore Price to Earnings (P/E) Ratio: 82.0 Book Value: ₹141 Dividend Yield: 0.24% Return on Capital Employed (ROCE): 19.7% Return on Equity (ROE): 14.9% Debt Level: Almost debt free with borrowings of about ₹30 crore as of 2024 Revenue: ₹6,017 crore (TTM) Operating Profit: ₹963 crore with operating margin around 16% Net Profit: ₹505 crore Earnings Per Share (EPS): ₹18.96 Dividend Payout: Approximately 19.4% Total Assets: Around ₹5,198 crore with net block growth indicating capacity expansion Business Focus: Leading manufacturer of CPVC pipes, PVC pipes, plumbing products, adhesives, and sealants in India. Growth: Strong sales growth over past years driven by product diversification and geographic expansion; 10-year sales CAGR ~15%, profit CAGR ~21% Listed on NSE and BSE and part of indices like Nifty Midcap 150. Astal stands out for its financial discipline, low debt, steady profitability, and strong market presence in the Indian plumbing solutions and building materials sector.
NSE:ASTRALLong
by rajeshpgpg
EUR/JPY (1H) chartEUR/JPY (1H) chart, here’s what can be interpreted based on my annotations and price action: Support level (green zone): around 178.00 – 178.20 Current price: 177.88 Breakdown below cloud: already happened previously, price retested resistance (support turned resistance) and dropped again. My also drawn two target points below — one short-term and one deeper move. --- 🎯 Target Analysis From my markings and price structure: First target (short-term): around 176.40 – 176.50 → This aligns with my first green arrow and matches a previous minor swing low. Second target (main target): around 175.20 – 175.30 → This is the lower arrow, which aligns with the bottom of my previous structure (major support zone). --- 📊 Trade Idea Summary If my looking at a short setup (since price rejected the resistance zone): Sell Entry: below 177.70 (confirmation of rejection) Target 1: 176.40 Target 2: 175.20 Stop-loss: above 178.20 – 178.30 (just above resistance zone) --- ⚖ Risk/Reward (approximate) If entering at 177.70: SL: 178.30 (≈ 60 pips risk) TP1: 176.40 (≈ 130 pips reward) TP2: 175.20 (≈ 250 pips reward) ➡ R:R = 1:2 to 1:4 --- ✅ Conclusion: My first target is 176.40, and my main target is 175.20. This setup looks valid if price stays below the 178.00 resistance and cloud confirms bearish momentum.
Short
by HussaiN_JaNi
3
AUD/JPY 4H chartAUD/JPY 4H chart: The price was in an upward channel, then broke down sharply below both the Ichimoku cloud and the support trendline. There’s a clearly marked resistance zone around 100.2–100.6, which the price rejected strongly. The chart shows a target line drawn downward from the breakout area. Based on the image, the target point appears to be around the 97.80–98.00 zone. 🔍 Summary: Resistance: 100.2–100.6 Current price: ≈ 99.21 Bearish breakdown target: 97.8–98.0 Bias: Bearish continuation while below 99.6
Short
by HussaiN_JaNi
3