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ETERNAL (ZOMATO) By KRS Charts17th April 2025 / 1:24 PM Why Eternal ?? 1. All Over Bullish Stock. Yet Not Profitable but Business model has potential in near Future. 2. Wave Count is suggesting 4th wave is likely finish and 5th last leg is started which can last till 340 Rs. 3 RSI & MACD is showing bullish continues Divg. bears gave there all but failed to make new lower low. 4. Lower TF is showing W pattern Breakout as well with good volume. Targets and SL 1W Closing Basis are mentioned in chart.
NSE:ETERNALLong
by KRSCharts
Part 1 Master Candlestick PatternHow Options Work (Premiums, Strike Price, Expiry, Moneyness) Every option has certain key components: Premium: The price you pay to buy the option. This is determined by demand, supply, volatility, and time to expiry. Strike Price: The fixed price at which the option holder can buy/sell the asset. Expiry Date: Options are valid only for a certain period. In India, index options have weekly and monthly expiries, while stock options usually expire monthly. Moneyness: This defines whether an option has intrinsic value. In the Money (ITM): Already profitable if exercised. At the Money (ATM): Strike price equals the current market price. Out of the Money (OTM): Not profitable if exercised immediately. Why Trade Options? Options trading is popular because it serves multiple purposes: Hedging: Protecting investments from adverse price movements. Example: A farmer uses commodity options to protect against falling crop prices. Speculation: Traders can bet on market direction with limited capital. Income Generation: Selling (writing) options like covered calls can generate steady income. Leverage: With a small premium, traders can control large positions.
NSE:FINNIFTY1!Education
by SkyTradingZone
8
Part 3 Trading Master Class With ExpertsOption Trading Psychology Patience: Many options expire worthless, don’t chase every trade. Discipline: Stick to stop-loss and position sizing. Avoid Greed: Sellers earn small consistent income but risk blow-up if careless. Stay Informed: News, earnings, and events impact volatility. Tips for Beginners in Options Trading Start with buying calls/puts before selling. Trade liquid instruments like Nifty/Bank Nifty. Learn Greeks slowly, don’t jump into complex strategies. Avoid naked option selling without hedging. Paper trade before risking real capital. Role of Volatility in Options Volatility is the lifeblood of options. High Volatility = Expensive Premiums. Low Volatility = Cheap Premiums. Traders often use Implied Volatility (IV) to decide whether to buy (when IV is low) or sell (when IV is high).
BSE:SENSEXEducation
by SkyTradingZone
4
Divergence SecretsRisks & Rewards in Option Trading Option trading can be thrilling, but it’s not without risks. For Buyers: Maximum loss = premium paid. Maximum profit = potentially unlimited (for calls) or huge (for puts). For Sellers: Maximum gain = premium received. Maximum loss = unlimited (for calls) or very large (for puts). Risks also come from: Time decay (options lose value daily). Volatility crush (sudden drop in implied volatility can reduce premiums). Liquidity issues (wide bid-ask spreads can hurt execution). That’s why risk management (stop-losses, proper sizing, hedging) is crucial. Option Trading vs Stock Trading Stocks = Ownership, long-term growth, dividends. Options = Contracts, leverage, flexible strategies. Stocks = Simpler, but capital-intensive. Options = Complex, but require less capital and offer hedging. For example: Buying 100 shares of Reliance at ₹2500 = ₹2,50,000. Buying 1 call option of Reliance at ₹100 premium with lot size 250 = only ₹25,000. This leverage makes options attractive—but also riskier.
TVC:IN10YEducation
by SkyTradingZone
5
Part 1 Trading Master Class Types of Option Strategies Options allow traders to design strategies based on market view—bullish, bearish, or neutral. Some popular strategies: A. Bullish Strategies Long Call – Buy a call option to profit from price rise. Bull Call Spread – Buy lower strike call, sell higher strike call to reduce cost. Synthetic Long – Buy call + sell put = behaves like futures long. B. Bearish Strategies Long Put – Buy a put option to profit from fall. Bear Put Spread – Buy higher strike put, sell lower strike put. Synthetic Short – Sell call + buy put = behaves like futures short. C. Neutral/Sideways Strategies Straddle – Buy call and put at same strike (profit from volatility). Strangle – Buy call and put at different strikes (cheaper than straddle). Iron Condor – Sell OTM call & put, buy further OTM call & put (profit from low volatility). D. Income/Theta Strategies Covered Call – Hold stock + sell call option for extra income. Cash-Secured Put – Sell put option while keeping cash aside to buy stock if assigned.
NSE:BANKNIFTYEducation
by SkyTradingZone
4
GIFT Nifty TradingIntroduction India has always been at the center of global investor attention. With a rapidly growing economy, strong demographic advantage, and increasing financial market maturity, India is becoming a major hub for global capital flows. To strengthen this position, the Gujarat International Finance Tec-City (GIFT City) was established as India’s first International Financial Services Centre (IFSC). One of the most important steps in making GIFT City globally relevant was the introduction of GIFT Nifty, a trading platform that connects global investors to India’s equity markets in real time. Replacing the Singapore Exchange (SGX) Nifty, GIFT Nifty represents India’s move to bring back offshore Nifty trading volumes to Indian territory. In this comprehensive guide, we’ll cover everything about GIFT Nifty trading, including its background, structure, importance, strategies, risks, and its role in shaping the future of Indian and global financial markets. 1. Background of GIFT Nifty 1.1 The SGX Nifty Era Before GIFT Nifty, foreign investors who wanted exposure to Indian equities largely used SGX Nifty, a derivative contract listed on the Singapore Exchange. SGX Nifty mirrored India’s Nifty 50 index, providing offshore traders the ability to hedge or speculate on Indian markets without registering in India. For years, SGX Nifty was highly popular because: It offered almost 16 hours of trading time, including when Indian markets were shut. Foreign investors avoided compliance with Indian regulations. It provided liquidity and easy entry/exit. But this created a problem for India. A large portion of trading in Indian indices was happening outside the country, meaning India lost out on liquidity, market depth, and revenue. 1.2 The Transition to GIFT Nifty To bring this trading activity back to India, the NSE International Exchange (NSE IX) at GIFT City was launched. After years of negotiations, SGX Nifty trading officially shifted to GIFT Nifty on July 3, 2023. Now, instead of trading in Singapore, foreign investors access Nifty futures through GIFT City, keeping the ecosystem within India’s borders. 2. What is GIFT Nifty? GIFT Nifty is the international version of India’s Nifty index futures, traded on the NSE IX at GIFT City. It allows global and domestic investors to trade, hedge, and speculate on Indian equities in a globally accessible financial environment. 2.1 Key Features Underlying index: Nifty 50 Contracts available: GIFT Nifty 50, GIFT Nifty Bank, GIFT Nifty Financial Services, GIFT Nifty IT Trading hours: Nearly 21 hours (6:30 AM IST to 2:45 AM IST next day), overlapping with Asian, European, and US markets Currency denomination: USD, making it attractive to global investors Taxation benefits: IFSC offers favorable tax regimes compared to onshore markets 2.2 Why It Matters Strengthens India’s financial sovereignty Brings liquidity back from offshore to onshore Provides global investors with near-continuous access to Indian markets Enhances India’s role in global trading ecosystems 3. Structure of GIFT Nifty 3.1 Contract Specifications Lot Size: Each contract has a fixed multiplier (usually 50 units per contract, like SGX Nifty). Expiry: Monthly and quarterly contracts available. Settlement: Cash-settled in USD, based on Nifty 50 closing value. Margin Requirements: Traders need to maintain margins similar to global exchanges. 3.2 Participants Foreign Portfolio Investors (FPIs) Domestic Institutional Investors Hedge Funds and Asset Managers Retail (through IFSC brokers) 3.3 Trading Ecosystem at GIFT City The GIFT IFSC provides: Low taxation (no securities transaction tax, commodity transaction tax, or stamp duty). 100% foreign ownership allowed in IFSC brokers. Liberalized rules for foreign currency accounts. Global-standard clearing and settlement infrastructure. 4. Why GIFT Nifty is Important 4.1 For India Revenue retention: Trading volumes and fees stay in India. Market depth: Strengthens domestic derivatives market. Global status: Puts India on the map as a global trading hub. 4.2 For Global Investors Extended trading hours: Easier to trade in Indian markets across different time zones. USD contracts: Reduces currency risk for international traders. Access to India’s growth story: India is one of the fastest-growing economies, and GIFT Nifty gives direct access. 4.3 For Traders More opportunities: Nearly round-the-clock trading enables reaction to global events. Arbitrage: Traders can arbitrage between onshore NSE Nifty and offshore GIFT Nifty. Liquidity: Strong foreign participation ensures volumes. 5. How GIFT Nifty Works in Practice Imagine a scenario: The US Fed announces a surprise interest rate hike at 10 PM IST. Indian stock markets are closed, but GIFT Nifty is live until 2:45 AM. Global traders immediately react, selling GIFT Nifty contracts. This provides a real-time indication of how Indian equities may open the next day. Thus, GIFT Nifty acts as a barometer of global sentiment towards India, even outside normal Indian trading hours. 6. Trading Strategies in GIFT Nifty 6.1 Hedging Foreign investors holding Indian portfolios can hedge overnight or global risks by taking opposite positions in GIFT Nifty. 6.2 Arbitrage Onshore vs Offshore Arbitrage: Price differences between NSE Nifty and GIFT Nifty create opportunities. Cross-market Arbitrage: Traders arbitrage between GIFT Nifty and other indices (like S&P 500, Nikkei). 6.3 Speculation Day traders and institutions speculate on short-term moves, just like in regular futures markets. 6.4 Event Trading Events like Budget, RBI policy, or global announcements can create sharp moves in GIFT Nifty, offering trading opportunities. 7. Risks in GIFT Nifty Trading 7.1 Market Risks Like any derivative, GIFT Nifty is highly leveraged. Sudden volatility can wipe out margins. 7.2 Currency Risks Although contracts are USD-based, Indian investors face INR-USD conversion risks. 7.3 Liquidity Risks While volumes are growing, some contracts may still lack liquidity compared to NSE Nifty. 7.4 Regulatory Risks Any change in IFSC or SEBI regulations may affect participation. 8. Taxation & Regulatory Framework Tax advantages: No capital gains tax for non-residents, no stamp duty, no STT/CTT. IFSC Authority: The unified regulator for GIFT City ensures global standards. Foreign Investors: Allowed to directly trade via IFSC brokers without needing SEBI FPI registration. 9. Future of GIFT Nifty 9.1 Growth Potential More contracts (Midcap, sectoral indices) likely to be introduced. Potential for options trading in addition to futures. Increasing participation from global hedge funds, asset managers, and even retail investors. 9.2 India as a Global Hub If successful, GIFT Nifty will make GIFT City a financial hub comparable to Dubai, Singapore, and Hong Kong. 9.3 Integration with Global Markets Longer trading hours and global recognition will ensure GIFT Nifty becomes the benchmark for Indian equities worldwide. 10. Practical Guide for Traders Step 1: Open an IFSC Trading Account Traders must open accounts with NSE IX-registered brokers in GIFT City. Step 2: Fund Account in USD Trading is USD-denominated, so funding is done in dollars. Step 3: Understand Margin & Risk Maintain adequate margins to avoid forced liquidation. Step 4: Build Strategies Use GIFT Nifty to hedge portfolios. Trade during overlapping hours with Europe/US for maximum volatility. Step 5: Monitor News Global events significantly impact GIFT Nifty. Keep track of US Fed, crude oil, geopolitical tensions, etc. Conclusion GIFT Nifty trading is more than just a financial product – it is a symbol of India’s growing financial power. By bringing offshore Nifty trading back home, India has strengthened its sovereignty, deepened its markets, and provided global investors with seamless access to its growth story. For traders, it offers nearly round-the-clock opportunities, arbitrage, hedging, and speculation in USD terms. For India, it positions GIFT City as a global financial hub. As volumes rise and new contracts are introduced, GIFT Nifty is set to become the global benchmark for Indian equities, bridging India with the world’s markets like never before.
NSE:NIFTYEducation
by TechnicalExpress
3
Algorithmic & AI-Powered Trading1. Introduction: The Shift from Manual to Machine For centuries, trading was purely a human skill — traders watched ticker tapes, read news, and relied on gut instinct. But as markets grew faster and more complex, human reaction time simply couldn’t keep up. Enter algorithmic trading — a world where trades are executed in milliseconds, strategies are tested on decades of data, and human bias takes a back seat. Over the past decade, Artificial Intelligence (AI) has supercharged this process. Now, trading systems not only follow pre-set rules but also learn from market data, adapt strategies in real time, and detect patterns invisible to human eyes. In 2025, over 70% of all equity trades in developed markets are algorithmic. In some markets, AI-powered systems handle more trading volume than humans. 2. What is Algorithmic Trading? At its core, algorithmic trading is: The use of computer programs to execute trades based on a defined set of rules and parameters. Key features: Rule-based execution: Trades are placed when certain conditions are met (e.g., price crosses moving average). Speed & automation: No waiting for human clicks; execution is near-instant. Backtesting: Strategies can be tested on historical data before risking real money. Scalability: Can handle hundreds of trades simultaneously. Example: If a stock’s 50-day moving average crosses above its 200-day moving average, buy 100 shares. If the reverse happens, sell. 3. What is AI-Powered Trading? AI-powered trading takes algorithms further: Instead of pre-programmed rules, AI systems can learn patterns, adapt strategies, and make predictions based on data. Core difference: Algorithmic trading = fixed rules. AI trading = adaptive, self-learning rules. AI capabilities in trading: Pattern recognition – spotting trends in price, volume, sentiment, or macro data. Predictive modeling – forecasting future price movements. Reinforcement learning – improving strategies based on feedback from trades. Natural Language Processing (NLP) – reading and interpreting news, social media, and financial reports. 4. Types of Algorithmic & AI Trading Strategies There’s a wide range of strategies — some decades old, others made possible only by modern AI. A. Trend-Following Strategies Based on technical indicators like Moving Averages, RSI, MACD. Goal: Ride the trend up or down until it shows signs of reversal. AI twist: Deep learning models can predict trend continuation probability. B. Mean Reversion Strategies Assumes prices will revert to an average over time. Example: If a stock is far above its 20-day moving average, short it; if far below, buy. AI twist: Machine learning models detect the optimal mean reversion window dynamically. C. Arbitrage Strategies Exploiting price differences between markets or instruments. Example: If a stock trades at ₹100 in NSE and ₹101 in BSE, buy low, sell high instantly. AI twist: AI can scan thousands of instruments and markets for fleeting arbitrage opportunities. D. Statistical Arbitrage Uses correlations between assets (pairs trading). Example: If Reliance and ONGC usually move together, but Reliance rallies while ONGC lags, trade expecting convergence. AI twist: AI can detect shifting correlations and adapt. E. High-Frequency Trading (HFT) Ultra-fast trades exploiting tiny inefficiencies. Requires low-latency infrastructure. AI twist: AI can dynamically adjust order placement to reduce slippage. F. Sentiment Analysis Trading Uses NLP to gauge market sentiment from news, tweets, blogs. Example: AI detects a surge in positive sentiment toward Tesla, triggering a buy. AI twist: Transformer-based NLP models (like GPT) can analyze sarcasm, tone, and context better than older keyword-based systems. G. Market Making Posting buy and sell orders to earn the bid-ask spread. Requires continuous price adjustment. AI twist: Reinforcement learning optimizes spread width for profitability. 5. Key Components of an Algorithmic/AI Trading System Building a profitable system is more than just coding a strategy. It needs an ecosystem: Market Data Feed Real-time & historical prices, volumes, order book data. AI needs clean, high-quality data to avoid bias. Signal Generation Algorithm or AI model generates buy/sell/hold signals. Could be purely quantitative or include sentiment and fundamentals. Execution Engine Sends orders to the exchange with minimal delay. AI can optimize execution to avoid market impact. Risk Management Module Position sizing, stop-loss levels, portfolio diversification. AI can dynamically adjust risk based on volatility. Backtesting Framework Tests strategy on historical data. Important: Avoid overfitting — making the model too perfect for past data but useless in the future. Monitoring & Maintenance Even AI needs human oversight. Models can degrade if market behavior shifts (concept drift). 6. Role of Machine Learning in Trading Machine Learning (ML) is the backbone of AI-powered trading. Popular ML techniques in trading: Supervised Learning – Train on historical prices to predict next-day returns. Unsupervised Learning – Cluster stocks with similar price behavior. Reinforcement Learning – Learn by trial and error in simulated markets. Deep Learning – Use neural networks to detect complex patterns in large datasets. Example: A neural network could take in: Price data Volume data News sentiment Macroeconomic indicators …and output a probability of the stock rising in the next 5 minutes. 7. Advantages of Algorithmic & AI Trading Speed – Executes in milliseconds. Accuracy – No fat-finger trade errors. No emotional bias – Sticks to the plan. Scalability – Monitors hundreds of assets. 24/7 markets – Especially useful in crypto trading. Pattern discovery – Finds relationships humans might miss. 8. Risks & Challenges Not everything is a profit paradise. A. Technical Risks System crashes Internet outages Latency issues B. Model Risks Overfitting to historical data Concept drift (market behavior changes) C. Market Risks Sudden news events (e.g., black swan events) Flash crashes caused by runaway algorithms D. Regulatory Risks Exchanges and regulators monitor algo trading to prevent manipulation. Some AI strategies might accidentally trigger market manipulation patterns. 9. Risk Management in AI Trading A robust system must: Use position sizing (risk only 1-2% of capital per trade). Place stop-loss & take-profit levels. Have circuit breakers to halt trading if unusual volatility occurs. Validate models regularly against out-of-sample data. 10. Backtesting & Optimization Before deploying: Data cleaning – Remove bad ticks, adjust for splits/dividends. Out-of-sample testing – Use unseen data to test robustness. Walk-forward testing – Periodically re-train and test. Monte Carlo simulations – Stress-test strategies under random conditions. 11. Real-World Applications Hedge Funds: Renaissance Technologies, Two Sigma. Banks: JPMorgan’s LOXM AI execution algorithm. Retail: Zerodha Streak, AlgoTrader. Crypto: AI bots analyzing blockchain transactions. 12. Future Trends in AI Trading Explainable AI – Making AI’s decision-making transparent. Hybrid human-AI teams – AI generates signals; humans validate. Quantum computing – Potentially breaking speed and complexity barriers. Multi-agent reinforcement learning – AI “traders” competing/cooperating in simulations. 13. Conclusion Algorithmic & AI-powered trading is no longer just a Wall Street tool — it’s accessible to retail traders, thanks to low-cost cloud computing, APIs, and open-source machine learning libraries. The key to success isn’t just having an algorithm — it’s about data quality, model robustness, disciplined risk management, and constant adaptation.
TVC:GOLDEducation
by TechnicalExpress
2
High-Quality Dip Buying1. Introduction – The Essence of Dip Buying The phrase “Buy the dip” is one of the most common in financial markets — from Wall Street veterans to retail traders on social media. The core idea is simple: When an asset’s price temporarily falls within an overall uptrend, smart traders buy at that lower price, expecting it to recover and make new highs. But here’s the reality — not all dips are worth buying. Many traders rush in too soon, only to see the price fall further. This is why High-Quality Dip Buying is different — it’s about buying dips with probability, timing, and market structure on your side, not just reacting to a red candle. The goal here is strategic patience, technical confirmation, and risk-controlled execution. 2. Why Dip Buying Works (When Done Right) Dip buying works because: Trend Continuation – In a strong uptrend, pullbacks are natural pauses before the next leg higher. Liquidity Pockets – Price often dips into zones where big players add positions. Psychological Discounts – Market participants love “getting in at a better price,” creating buying pressure after a drop. Mean Reversion – Markets often revert to an average after short-term overreactions. But — without confirming the quality of the dip, traders risk catching a falling knife (a price that keeps dropping without support). 3. What Makes a “High-Quality” Dip? A dip becomes high quality when: It occurs in a strong underlying trend (measured with moving averages, higher highs/higher lows, or macro fundamentals). The pullback is controlled, not panic-driven. Volume behavior confirms accumulation — volume dries up during the dip and increases on recovery. It tests a well-defined support zone (key levels, VWAP, 50-day MA, Fibonacci retracement, etc.). Market sentiment remains bullish despite short-term weakness. Macro or fundamental story stays intact — no major negative catalyst. Think of it this way: A low-quality dip is like buying a “discounted” product that’s broken. A high-quality dip is like buying a brand-new iPhone during a holiday sale — same product, better price. 4. The Psychology Behind Dip Buying Understanding trader psychology is critical. Fear – When prices drop, many panic-sell. This creates opportunities for disciplined traders. Greed – Some traders jump in too early without confirmation, leading to losses. Patience – High-quality dip buyers wait for confirmation instead of guessing the bottom. Confidence – They trust the trend and their plan, avoiding emotional exits. In other words, dip buying rewards those who stay calm when others are reacting impulsively. 5. Market Conditions Where Dip Buying Thrives High-quality dip buying works best in: Strong Bull Markets – Indices and leading sectors are making higher highs. Post-Correction Recoveries – Markets regain bullish momentum after a healthy pullback. High-Liquidity Stocks/Assets – Blue chips, large caps, index ETFs, or top cryptos. Clear Sector Leadership – Strong sectors (tech, healthcare, renewable energy) attract consistent dip buyers. It’s risky in: Bear markets (dips often turn into bigger drops) Illiquid assets (wild volatility without strong support) News-driven selloffs (fundamental damage) 6. Technical Tools for Identifying High-Quality Dips A good dip buyer uses price action + indicators + volume. a) Moving Averages 20 EMA / 50 EMA – Short to medium-term trend guides. 200 SMA – Long-term institutional trend. High-quality dips often bounce near the 20 EMA in strong trends or the 50 EMA in moderate ones. b) Support and Resistance Zones Look for price retracing to: Previous breakout levels Trendline support Volume profile high-volume nodes c) Fibonacci Retracements Common dip zones: 38.2% retracement – Healthy shallow pullback. 50% retracement – Neutral zone. 61.8% retracement – Deeper but often still bullish. d) RSI (Relative Strength Index) Strong trends often dip to RSI 40–50 before bouncing. Avoid dips where RSI breaks below 30 and stays weak. e) Volume Profile Healthy dips = declining volume during pullback, rising volume on recovery. 7. Step-by-Step: Executing a High-Quality Dip Buy Here’s a simple process: Step 1 – Identify the Trend Use moving averages and price structure (higher highs & higher lows). Step 2 – Wait for the Pullback Let price retrace to a strong support area. Avoid chasing — patience is key. Step 3 – Look for Confirmation Reversal candlestick patterns (hammer, bullish engulfing). Positive divergence in RSI/MACD. Bounce on increased volume. Step 4 – Plan Your Entry Scale in: Start with partial size at the support, add on confirmation. Use limit orders at planned levels. Step 5 – Set Stop Loss Place below recent swing low or key support. Step 6 – Manage the Trade Trail stop as price moves in your favor. Take partial profits at predefined levels. 8. Risk Management in Dip Buying Even high-quality dips can fail. Protect yourself by: Never going all-in — scale in. Using stop losses — don’t hold if structure breaks. Sizing based on volatility — smaller size for volatile assets. Limiting trades — avoid overtrading every dip. 9. Real Market Examples Example 1 – Stock Market Apple (AAPL) in a bull market often pulls back to the 20 EMA before continuing higher. Traders buying these dips with confirmation have historically seen strong returns. Example 2 – Cryptocurrency Bitcoin in a strong uptrend (2020–2021) had multiple 15–20% dips to the 50-day MA — each becoming an opportunity before making new highs. Example 3 – Index ETFs SPY ETF during 2019–2021 often dipped to the 50 EMA before strong rallies. 10. Common Mistakes in Dip Buying Catching a falling knife — Buying without confirmation. Ignoring news events — Buying into negative fundamental shifts. Overleveraging — Increasing risk on a guess. Buying every dip — Not all dips are equal. No exit plan — Holding losers too long. Conclusion High-quality dip buying isn’t about impulsively buying when prices drop. It’s a disciplined, structured, and patient approach that aligns trend, technical analysis, and psychology. When executed with precision and risk management, it allows traders to buy strength at a discount and participate in powerful trend continuations. The golden rule? Never buy a dip just because it’s lower — buy because the trend, structure, and confirmation all align.
BSE:SENSEXEducation
by TechnicalExpress
2
Part4 Institutional TradingStraddle When to Use: Expect big move but unsure direction. How It Works: Buy call and put at same strike & expiry. Risk: High premium cost. Reward: Big if price moves sharply up or down. Example: Stock at ₹100, buy call ₹100 (₹4) and put ₹100 (₹4). Cost ₹8. Needs a big move to profit. Strangle When to Use: Expect big move but want cheaper entry than straddle. How It Works: Buy OTM call and put. Risk: Cheaper than straddle but needs larger move. Example: Stock at ₹100, buy call ₹105 (₹3) and put ₹95 (₹3). Cost ₹6. Iron Condor When to Use: Expect low volatility. How It Works: Sell an OTM call spread + sell an OTM put spread. Risk: Limited by spread width. Reward: Limited to premium collected. Example: Stock at ₹100, sell call ₹110, buy call ₹115; sell put ₹90, buy put ₹85.
NSE:NIFTYEducation
by SkyTradingZone
5
Smart Money Concepts1. Introduction: What is Smart Money Concepts? Smart Money Concepts (SMC) is a modern price action trading methodology that focuses on how big players — institutions, hedge funds, banks, and market makers — move the market. The core belief: price is manipulated by "smart money" to accumulate positions before large moves, and if you can track their footprints, you can ride their moves instead of getting trapped like retail traders. In SMC, you don’t rely on indicators that lag behind price. Instead, you learn to read the raw story of price action: where liquidity lies, where stop hunts happen, and where imbalances push price. Think of it like this: Retail trading is reacting to price. SMC trading is predicting what price will want to do, based on smart money’s needs. 2. Core Principles of SMC SMC builds around a few non-negotiable principles: 2.1 Market Structure Price moves in waves (higher highs, higher lows in an uptrend, or lower highs, lower lows in a downtrend). Smart money manipulates these structures: Break of Structure (BOS): When price breaks a significant swing point in the direction of the trend. Change of Character (ChoCH): A shift in market bias — often the first sign of trend reversal. Example: If we’re in an uptrend and suddenly a major low is broken, this isn’t “random selling.” It’s likely a smart money signal that distribution has started. 2.2 Liquidity Smart money hunts liquidity pools — areas where retail traders have stop-loss orders: Above recent highs → stop-losses of short sellers. Below recent lows → stop-losses of long traders. Why? Because triggering these stops provides the volume big players need to enter large positions without causing huge slippage. 2.3 Order Blocks An Order Block is the last opposite candle before a strong impulsive move. For example: In an uptrend: the last bearish candle before a strong bullish push. In a downtrend: the last bullish candle before a strong bearish push. Order blocks are institutional footprints — zones where smart money likely placed big orders. 2.4 Imbalance & Fair Value Gap (FVG) Sometimes price moves so fast in one direction that it leaves a gap between candles’ wicks — meaning no trades happened in that range. Price often revisits these Fair Value Gaps to “rebalance” the market before continuing. 2.5 Premium & Discount Zones Using Fibonacci retracement, the 50% level divides the market into: Premium (above 50%) → expensive zone for buying, better for selling. Discount (below 50%) → cheap zone for buying, better for selling. Smart money often buys at a discount and sells at a premium. 3. How Smart Money Operates Retail traders believe price moves randomly — smart money knows better. 3.1 Accumulation & Distribution Markets cycle through: Accumulation → Smart money quietly builds positions at low prices. Manipulation → Stop hunts and fake breakouts to mislead retail traders. Distribution → Price moves explosively in their intended direction. 3.2 Stop Hunts Smart money deliberately pushes price to known liquidity areas: Looks like a breakout to retail traders → but reverses right after. This traps breakout traders and activates their stops, providing liquidity. 3.3 Inducement Before moving toward the main liquidity pool, smart money creates a “bait” level to attract retail orders. This induces traders to place stops exactly where smart money wants. 4. SMC Tools & Key Components 4.1 Market Structure Tools Swing highs/lows BOS (Break of Structure) ChoCH (Change of Character) 4.2 Liquidity Identification Equal highs/lows (double tops/bottoms) Trendline liquidity (breakouts) Session highs/lows (London, New York, Asia) 4.3 Order Blocks Bullish OB → for buys Bearish OB → for sells Refined OB → using lower timeframes for precision 4.4 Fair Value Gaps Look for large impulse moves leaving gaps between candle wicks. 4.5 Fibonacci Levels Use 50% as a bias divider, 61.8% & 78.6% for sniper entries. 5. The SMC Trading Process Here’s a step-by-step method to apply SMC: Step 1: Higher Timeframe Bias Start from daily (D1) or 4H charts. Identify market structure (uptrend, downtrend, or range). Mark major BOS and ChoCH points. Step 2: Identify Liquidity Pools Look for equal highs/lows, trendlines, swing points. Mark where retail traders are likely trapped. Step 3: Locate Order Blocks Find the last opposite candle before a strong move. Confirm it aligns with your higher timeframe bias. Step 4: Watch for Imbalance Mark Fair Value Gaps for potential retracements. Step 5: Entry Execution Drop to lower timeframes (5M, 1M) for refined entries. Wait for a lower timeframe BOS in the direction of your trade. Step 6: Risk Management Stop-loss just beyond the order block or liquidity sweep point. Risk 1–2% per trade. 6. Example Trade Setup Imagine EUR/USD is in an uptrend on 4H: 4H BOS confirmed bullish bias. Liquidity found below equal lows at 1.0750. Bullish order block spotted just below 1.0750. Fair Value Gap in that same area. On 5M chart → price sweeps liquidity, taps OB, breaks minor high. Entry after BOS → SL below OB → TP at previous high. 7. SMC vs Traditional Technical Analysis Aspect Traditional TA SMC Indicators Uses RSI, MACD, Moving Averages Pure price action Focus Patterns (Head & Shoulders, etc.) Liquidity, order flow Timing Often late entries Precision entries Mindset Follow trend Follow smart money 8. Common Mistakes in SMC Trading Over-marking charts → clutter leads to confusion. Forcing trades without waiting for confirmation. Ignoring higher timeframe bias. Not managing risk — precision doesn’t mean perfection. 9. Psychology of SMC Trading SMC can give very high RR trades (1:5, 1:10), but the patience required can be tough. You need: Discipline to wait for setups. Emotional detachment from market noise. Confidence to enter when it feels counterintuitive. 10. Final Thoughts: Why SMC Works SMC works because it aligns your trading with the actual drivers of price — the big money. Instead of being prey, you become a shadow of the predator. Key takeaways: Market is a liquidity game. Learn where smart money is likely to act. Trade less, but with sniper precision.
BSE:SENSEXEducation
by TechnicalExpress
1
Zomato Ltd. - Breakout OpportunityDate : 26-Nov-2024 LTP : Rs. 280.10 Targets: (T1) Rs. 298 --> (T2) Rs. 334 SL : Rs. 261 Technical View: • NSE:ZOMATO is in strong primary uptrend and was recently going through it's secondary downtrend within primary uptrend. • After touching the high of 298 on 24-Sep-2024, it has retraced 20% to 239.45 level. • NSE:ZOMATO has breakout from it's secondary downtrend with higher volume on 26-Nov-2024. • NSE:ZOMATO is trading above both 20 DEMA and 50 DEMA since last few sessions. 20 DEMA has crossed over 50 DEMA on 19-Nov-2024. • RSI is in buy zone and trading at 62.17. MACD is in bullish and trading at 2.92. • Looking good to start a new swing from here. Like the analysis? Boost/Like this idea and follow my ID. Disclaimer: I am not a SEBI registered analyst/consultant and not recommending anyone to take any BUY or SELL position in stock market. Investing in stock market is risky and one should do a self analysis and validation before investing in stock market. My ideas are published for learning purpose only and are available to everyone at no cost/charge.
ZLong
by vikrant_252
Zomato - Gave a breakout🔴DISCLAIMER ***** It's just for an educational purpose, So you must also follow your own technical analysis before taking up the trades ****** Aggressive traders enter at the breakout and conservative traders may give entry after retracement (Retracement is optional, we cannot expect every stock to take a retest after the breakout, it may also continue to have its bullish pressure after the breakout) Ideal Target and Stop Loss should be minimum 1:2 RRR (Risk reward ratio) After reaching our targets, Book 50% Profits and trail your stop loss to get maximum profits from rest of the 50% in your trade.
ZLong
by PrakWorld_Traders
07/10/2022 Research Report For ZomatoDisclaimer: I am not SEBI registered person and this is not an investment advice and also please note this is only for education purpose. Also note we can use this research in my own portfolios. So don't influence yourself by this research. Please note before investing according to this educational research, please do own research and also do take advice from your financial adviser. Your any profits and loss are totally your liability. No one is liable for that. Also, please note we will not never compensate your any loss. So before investing any single rupee, please do your own research according to your risk taking capacity and after that do invest and book profits on right time. Buy @ C.M.P (Current Market Price) Target 1:- 80 This Pevious Research Report Will Also Be Real:-
ZLong
by india_market