Mastering Order Blocks: How to Trade Like Smart MoneyIntroduction
Order Blocks (OBs) are one of the most critical concepts in Smart Money trading. They represent areas where institutional traders have entered the market with significant volume, typically leading to strong price movements. Identifying and trading Order Blocks gives traders an edge by aligning with the footprints of Smart Money.
What is an Order Block?
An Order Block is the last bearish candle before a bullish move for bullish OBs, or the last bullish candle before a bearish move for bearish OBs. These candles represent areas where institutions accumulated or distributed large positions, leading to a market shift.
Types of Order Blocks
A Bullish Order Block appears at the end of a downtrend or during a retracement just before the price moves sharply upward. It is typically represented by the last bearish candle prior to an impulsive bullish move. Price will often return to this level to mitigate institutional orders before continuing upward.
A Bearish Order Block, in contrast, forms at the end of an uptrend or retracement where price begins a downward reversal. It is characterized by the last bullish candle before a strong bearish move. Price tends to revisit this level to mitigate before continuing lower.
How to Identify a Valid Order Block
The key to identifying a valid Order Block is first observing a strong impulsive move, also known as displacement, that follows the OB candle. The move must also result in a break of market structure or a significant shift in direction. Order Blocks that produce Fair Value Gaps (FVGs) or Market Structure Shifts (MSS) tend to be more reliable. Another important sign is when price returns to the OB for mitigation, offering a potential entry.
Entry Model Using Order Blocks
After locating a valid OB, the next step is to wait for price to return to this area. The ideal entry happens within the OB body or near its 50% level. For extra confirmation, look for a Market Structure Shift or Break of Structure on a lower timeframe. Entries are more powerful when combined with additional elements like Fair Value Gaps, liquidity grabs, or SMT Divergences. The stop-loss should be placed just beyond the OB’s high or low, depending on the direction of the trade.
Refinement Techniques
To increase precision, higher timeframe OBs can be refined by zooming into lower timeframes like the 1M or 5M chart. Within a broad OB zone, identify internal market structure, displacement candles, or embedded FVGs to determine a more precise entry point. One effective refinement is the Optimal Trade Entry (OTE), which is often found at the 50% level of the Order Block.
Order Blocks vs. Supply and Demand Zones
While they may seem similar, Order Blocks are more narrowly defined and specifically related to institutional order flow. Supply and Demand zones are broader and typically drawn around areas of price reaction, but OBs are derived from the final institutional candle before a large move and are often confirmed by structure shifts or displacement. This makes OBs more precise and actionable in the context of Smart Money concepts.
Target Setting from Order Blocks
Targets after entering from an OB should align with liquidity objectives. Common targets include internal liquidity like equal highs or lows, or consolidation zones just beyond the OB. External liquidity targets such as previous major swing highs or lows are also ideal, especially when they align with imbalances or Fair Value Gaps. It's important to adjust targets based on the current market structure and trading session.
Common Mistakes to Avoid
A frequent mistake is treating any candle before a move as an OB without verifying key signals like displacement or a Break of Structure. Entering without other confirmations, such as an MSS or liquidity sweep, can lead to poor trades. Another common error is placing the stop-loss too tightly within the OB, instead of just beyond it, increasing the chance of premature stop-outs. Traders should also avoid executing OB trades during low-liquidity sessions where price action can be unpredictable and wicky.
Final Thoughts
Order Blocks are foundational to Smart Money trading. They allow you to enter where institutions have placed large positions and offer clear invalidation and entry logic. With practice, you can identify high-quality OBs and combine them with other concepts like FVGs, MSS, and SMT for powerful, precise trades.
Practice on different timeframes and assets, and always look for clean displacement and structure confirmation. Mastering OBs is a big step toward becoming a consistently profitable trader.
Trust the Blocks. Trade with Intention.
Community ideas
Understanding Liquidity: Where Big Players Hunt Stops
Understanding Liquidity: Where Big Players Hunt Stops
Ever wondered why price suddenly spikes through your stop-loss and reverses moments later? That’s not a coincidence—it’s liquidity at play. This article will teach you how liquidity zones work, why stop hunts happen, and how to avoid getting trapped like the crowd.
🔵 What Is Liquidity in Trading?
Liquidity refers to how easily an asset can be bought or sold without drastically affecting its price. But in practical trading, liquidity is more than just volume—it’s where traders *place* their money.
Large players—institutions, market makers, or big accounts—need liquidity to fill orders.
They target areas where many retail stop-losses or pending orders are stacked.
These areas are often just above resistance or below support—classic stop-loss zones.
To move large positions without slippage, smart money uses stop hunts to trigger retail orders and create the liquidity they need.
🔵 Where Do Liquidity Zones Form?
Liquidity often builds up in predictable areas:
Above resistance: Where shorts place stop-losses.
Below support: Where longs place stop-losses.
Swing highs/lows: Obvious turning points everyone sees.
Round numbers: e.g., 1000, 10,000, 50,000.
Breakout zones: Where breakout traders place entries or stops.
These zones act like magnets. When price approaches them, it accelerates—seeking the liquidity pool behind the level.
🔵 What Is a Stop Hunt?
A stop hunt happens when price moves just far enough to trigger stop-losses before reversing. This isn’t market noise—it’s an intentional move by big players to:
Trigger a flood of stop orders (buy or sell).
Fill their own large positions using that liquidity.
Reverse price back to fair value or the prior trend.
Example: Price breaks above resistance → stops get hit → institutions sell into that liquidity → price drops sharply.
🔵 Signs You’re in a Liquidity Grab
Look for these clues:
Fast spike beyond key levels followed by rejection.
Wick-heavy candles near highs/lows.
Price touches a level, then sharply reverses.
High volume on failed breakouts or fakeouts.
These are signs of a liquidity event—not a real breakout.
🔵 How to Trade Around Liquidity Zones
You can use liquidity traps to your advantage instead of becoming their victim.
Avoid obvious stops: Don’t place stops directly below support or above resistance. Instead, use ATR-based or structure-based stops.
Wait for confirmation: Don’t chase breakouts. Let price break, reject, then re-enter inside the range.
Watch for wick rejections: If price quickly returns after a level is breached, it's often a trap.
Use higher timeframe confluence: Liquidity grabs are more powerful when they align with HTF reversals or zones.
🔵 Real Example: Liquidity Sweep Before Reversal
In this chart, we see a textbook liquidity grab:
Price breaks below support.
Longs get stopped out.
Candle prints a long wick.
Market reverses into an uptrend.
This is where smart traders enter— after the trap is set, not during.
🔵 Final Thoughts
Liquidity is the invisible hand of the market. Stop hunts aren’t personal—they’re structural. Big players simply go where the orders are. As retail traders, the best thing we can do is:
Understand where traps are set.
Avoid being part of the crowd.
Trade the reaction, not the initial breakout.
By thinking like the smart money, you can stop getting hunted—and start hunting for better trades.
How to Trade Gold with AI-Powered Algos in 2025📊 How to Trade Gold with AI-Powered Algos in 2025
A practical action plan for serious gold traders
🔍 1. Know Why Gold Requires Custom Algo Tactics
Gold is volatile, news-sensitive, and driven by macro events like Fed policy, geopolitics, and inflation. Generic stock or crypto bots fail here — gold needs precise, event-aware automation.
🧠 2. Use AI-Powered Bots Trained for Gold Volatility
Deploy bots that adapt to real-time data like CPI releases, bond yields, and geopolitical headlines. Use machine learning models that detect gold breakouts, consolidations, and safe-haven flows.
Top AI algos for gold traders: Multiple systems based on MT4/MT5
Fully-automated, AI-based gold bot with breakout detection, precision entries, and built-in risk control.
⚙️ 3. Build or Choose the Right Algo Strategy for Gold
Trend-Following: Use 21/50 EMA crosses on H1 and H4
Mean Reversion: Bollinger Band fades in range-bound sessions
Breakout Algos: Trigger trades on CPI or FOMC event volatility
Volume-Based AI: Analyze volume spikes vs. historical patterns
🧪 4. Backtest Gold-Specific Models
Always test your bot using historical gold data, especially during NFP weeks, Fed meetings, and geopolitical escalations. Use data from 2018 to 2024 for high-volatility periods.
Tools: TradingView for Pine Script testing, MetaTrader 5 for EA deployment
🛡️ 5. Control Risk with Gold-Specific Parameters
Max drawdown: Keep under 15 percent
Stop-loss: Always use hard stops (not just trailing)
Position sizing: 0.5 to 1 percent of capital per trade
Use volatility filters: Avoid entries during thin liquidity hours
🔄 6. Automate Monitoring and Adaptation
Run multiple bots for breakout, momentum, and reversal setups
Use dashboards to track gold-specific metrics like VIX, USDX, DXY, and 10Y Treasury yields Integrate AI that adjusts parameters after major data releases
🚀 7. Prepare for 2025 Market Structure
Gold is increasingly driven by
Central bank digital currency rollouts
USD de-dollarization risks
Global stagflation or recession themes
DeFi and tokenized gold products
Your algo must factor in these macro narratives using real-time data feeds
📌 Gold Algo Trading Success Plan 2025
Use AI bots built for gold volatility
Trade high-probability breakouts post-news
Backtest with gold-specific macro filters
Maintain strict risk limits with max 15 percent drawdown
Monitor global news and macro data with bot triggers
Continuously optimize and adapt
Gold is not just a commodity — it’s a signal of global risk. Automate smartly, manage risk tightly, and use AI to stay one move ahead.
Before You Trade, Feel the Market’s Pulse, Sentiment Reveal allIn the world of trading, most people chase complex tools, custom algorithms, or so-called magical indicators. But what often gets overlooked is market sentiment—the invisible force behind most price movements.
Hello✌
Spend 3 minutes ⏰ reading this educational material. The main points are summarized in 3 clear lines at the end 📋 This will help you level up your understanding of the market 📊 and Bitcoin💰.
🎯 Analytical Insight on Bitcoin: A Personal Perspective:
Bitcoin is approaching a significant support level. I’m expecting at least a 6% price increase, with the primary target at $99,500.📈
Now, let's dive into the educational section , which builds upon last week's lesson (linked in the tags of this analysis). Many of you have been eagerly waiting for this, as I have received multiple messages about it on Telegram.
🧠 What Is Market Sentiment?
Market sentiment is how traders feel—fearful, greedy, or uncertain. When most are bullish, the market may be topping. When panic spreads, bottoms can form.
🔍 Why Sentiment Matters More Than Just Charts
Technical analysis tells us what has happened. Sentiment analysis hints at what might come next.
Price isn't always truth—emotion often drives breakouts or breakdowns.
🛠️ Tools for Sentiment Analysis on TradingView
📊 Long/Short Ratio
Check if the crowd is overly long or short. Too many longs? It may signal greed—be careful.
📄 COT Reports
For gold, oil, or indices, look at institutional positions. Big players often move opposite to retail.
📈 Volume & Open Interest
If price moves up but volume lags, the move might be weak. Rising open interest shows strong participation.
🔧 Community Sentiment Scripts
Search “Sentiment” under indicators to explore user-built tools for emotional insight.
📅 Real-World Example:
📌 BTC Sentiment Snapshot – Jan 2025
Bitcoin rallied from $93.4K to $102K in early January 2025.
But while price surged, volume stayed weak and long positions piled up, signaling FOMO rather than strength.
Within days, BTC dropped back to $92.5K, liquidating over-leveraged longs.
Lesson: When sentiment overheats without strong volume, a correction often follows.
🎯 How to Use These Insights
When Long/Short ratios become extreme, look for divergences or reversal signals.
Combine sentiment data with technical signals (e.g., RSI divergence near resistance) for stronger confirmation.
If price rises on low volume, consider the possibility of a fake move or bull trap.
🧩 Final Thoughts
Market sentiment is the unspoken language of traders. Learn to hear it—and you’ll act before the rest.
TradingView gives you the tools. Now it’s your job to feel the crowd.
However , this analysis should be seen as a personal viewpoint, not as financial advice ⚠️. The crypto market carries high risks 📉, so always conduct your own research before making investment decisions. That being said, please take note of the disclaimer section at the bottom of each post for further details 📜✅.
🧨 Our team's main opinion is: 🧨
Bitcoin is approaching a key support level, with an expectation of at least a 6% price increase, targeting \$99,500.
Market sentiment , which reflects traders' emotions like fear or greed, plays a crucial role in price movements, sometimes more than technical analysis alone. Tools for sentiment analysis on TradingView include the Long/Short Ratio, COT Reports, Volume & Open Interest, and Community Sentiment Scripts. A real-world example showed Bitcoin's price surge without volume support, followed by a correction. To trade effectively, combine sentiment data with technical signals like RSI divergence. Understanding market sentiment can help traders anticipate market movements before they happen.
Give me some energy !!
✨We invest countless hours researching opportunities and crafting valuable ideas. Your support means the world to us! If you have any questions, feel free to drop them in the comment box.
Cheers, Mad Whale. 🐋
Ratio Charts in TradingView and IAAbove you can see the Bitcoin to Ethereum ratio chart. Ratio analysis between two or more symbols is a critical method for comparing the strength and weakness of assets relative to each other. TradingView offers basic capabilities for this task, but with the help of artificial intelligence (AI) and custom scripts, much more advanced and creative analyses can be conducted.
Here are some practical ideas:
1. Creating Conditional Ratio Scripts
2. Comparing Relative Averages and Issuing Smart Signals
3. Calculating Composite Ratios of Multiple Assets
4. Smart Alerts Based on Price Pattern Breakouts
For more information, search Google for "How to Use Ratio Charts in TradingView: A Hidden Gem for Traders."
This is how to read the chart using Weis Wave with Speed IndexReading the chart:
1. We have bottom down and we pull back with high up volume waves, approaching the Fib area. Notice how SI is increasing on the up waves as we are reaching Fib from 13.3 to 15.7 to 18.4 and last not able to break previous resistance at 20.4. This means sellers are absorbing all buy orders of people entering long thinking that the trend will continue.
2. Notice the up volume wave with SI 20.4 and respective pip move right above it which is small compared to the amount of volume used - This is absorption.
3. The highest PVR bar at the beginning of the down wave - more sellers
4. Entry Short on the Plutus Short signal
Notice all the Short signals following confirming the continuation of the down move!
Simple as that, if you are able to read the chart and not just following signals from an indicator.
Enjoy!
MACD: More Than Just a Crossover ToolHello, traders! 🔥
The MACD (Moving Average Convergence Divergence) indicator is one of the most trusted tools in technical analysis — but often one of the most oversimplified. While many traders focus on signal line crossovers, the real power of MACD lies in its ability to visualize market momentum, subtle shifts in trend strength, and early signs of potential reversals.
Let’s unpack how MACD behaves using the weekly BTC/USDT chart ✍🏻.
🔧 Understanding the Mechanics
At its core, MACD is the difference between two exponential moving averages — typically the 12-period EMA and the 26-period EMA. The result is the MACD line (blue). The orange line represents a 9-period Exponential Moving Average (EMA) of the MACD line, commonly referred to as the signal line. The histogram reflects the distance between them, helping to visualize when momentum is building or fading.
📊 MACD in Action — Weekly BTC Chart Breakdown
Looking at the BTC/USDT weekly chart, several notable MACD behaviors stand out:
1. The Bullish Acceleration in Early 2023
In early 2023, MACD crossed above the signal line, accompanied by a sharp rise in the histogram. This indicated strong positive momentum, as the price began recovering from the 2022 lows. The histogram’s expansion confirmed increasing divergence between the short- and long-term EMAs — a classic sign of trend acceleration.
2. Peak Momentum in Late 2023
Around late 2023, the MACD line peaked while the histogram also reached maximum height. This wasn’t just a confirmation of strength — it also hinted that momentum may have reached a climax. Despite price continuing to rise slightly, the MACD curve started to flatten — an early warning of potential exhaustion in trend strength.
3. Bearish Convergence into Q1 2025
In early 2025, the MACD line turned downward and eventually crossed below the signal line, while the histogram flipped to red. This reflected a cooldown in bullish momentum rather than an immediate reversal. What’s notable is how price didn’t collapse sharply, but moved into a pullback phase — illustrating how MACD can show momentum softening before price visibly reacts.
📌 What This Can Tells Us
The MACD indicator on this weekly BTC chart shows how momentum often shifts before the trend itself breaks. Each crossover, divergence, or histogram change is not a guarantee, but a cue to pay closer attention.
Key takeaways:
Strong Histogram Expansion = Confidence in the Current Move.
Peaks in MACD Without Price Making New Highs = Potential Divergence.
Shrinking Histogram + Converging Lines = Momentum Stalling.
🧠 Final Thought
MACD isn’t just about “buy when it crosses” or “sell on red bars.” It’s a narrative tool, showing how the story of the price develops beneath the surface. On higher timeframes, such as the weekly chart, it can potentially highlight macro momentum shifts long before they become apparent in price action alone.
Don't Miss this: Mastering Wave 3 Targets in Elliott Wave TheoryHello friends,
Welcome to RK_Chaarts,
Today we'll analyze WOCKHARDT LTD's chart using the Elliott Wave theory for educational purposes.
In this educational series, we'll explore how to assume the target of wave three. Today's topic is specifically focused on understanding the measurements and projections for wave three.
We can see that wave one on the monthly chart is complete, and wave two has also ended. Currently, we're likely in wave three.
Generally, wave three's target is 161.8% of wave one. If wave one is 100 points, wave three's target would be around 162 points. If extended, it can reach 261 points, 361 points, or even 423% in rare cases.
However, a key rule is that wave three will never be the shortest. If it's not extended, we expect it to be at least equal to wave one. Typically, wave three reaches 161.8% in general cases.
We've shared this analysis in a video format for educational purposes only. Please note that this is not a tip or advisory. Watch the video carefully to understand how the Elliott Wave theory helps us analyze the chart and set targets.
Thanks for joining and watching the video! If you like this series, please like and comment below. Your feedback will encourage us to create more content.
I am not Sebi registered analyst.
My studies are for educational purpose only.
Please Consult your financial advisor before trading or investing.
I am not responsible for any kinds of your profits and your losses.
Most investors treat trading as a hobby because they have a full-time job doing something else.
However, If you treat trading like a business, it will pay you like a business.
If you treat like a hobby, hobbies don't pay, they cost you...!
Hope this post is helpful to community
Thanks
RK💕
Disclaimer and Risk Warning.
The analysis and discussion provided on in.tradingview.com is intended for educational purposes only and should not be relied upon for trading decisions. RK_Chaarts is not an investment adviser and the information provided here should not be taken as professional investment advice. Before buying or selling any investments, securities, or precious metals, it is recommended that you conduct your own due diligence. RK_Chaarts does not share in your profits and will not take responsibility for any losses you may incur. So Please Consult your financial advisor before trading or investing.
PineScript v6: Conditional Expressions from Libraries
I thought it appropriate to make some quick notes on calling conditional expressions from PineScript v6 libraries, seeing as I have recently updated all of my libraries to v6 and most of my function exports output booleans or values that are ultimately derived from other functions that output booleans.
When calling functions in v6 that output booleans or values derived from other functions that output booleans, it is best practice to first declare the function return globally before you use said output as input for anything else.
For example, instead of calling my swing low and uptrend functions (which both return booleans) as part of a broader conditional expression:
//@version=6
indicator('Example Conditional Expression 1')
import theEccentricTrader/PubLibSwing/3 as sw
import theEccentricTrader/PubLibTrend/2 as tr
uptrend = sw.sl() and tr.ut()
plotshape(uptrend)
I would first declare the function returns as global variables and then call the broader conditional expression using said variables:
//@version=6
indicator('Example Conditional Expression 2')
import theEccentricTrader/PubLibSwing/3 as sw
import theEccentricTrader/PubLibTrend/2 as tr
sl = sw.sl()
ut = tr.ut()
uptrend = sl and ut
plotshape(uptrend)
This demonstrates different behaviour from v5, where you could combine functions that output booleans in conditional expressions without error or warning.
The same also applies to functions that output values derived from other functions that output booleans. In the example below, my swing low price and bar index functions output float and integer values, respectively, but these values are derived from the swing low function, which is a function that returns a boolean. So these return values should also be first declared globally for later use, just like the swing low and uptrend functions:
//@version=6
indicator('Example Conditional Expression 3', overlay = true)
import theEccentricTrader/PubLibSwing/3 as sw
import theEccentricTrader/PubLibTrend/2 as tr
sl = sw.sl()
ut = tr.ut()
slp_0 = sw.slp(0)
slpbi_0 = sw.slpbi(0)
slp_1 = sw.slp(1)
slpbi_1 = sw.slpbi(1)
if sl and ut
line.new(slpbi_1, slp_1, slpbi_0, slp_0, color = color.green)
Using Moving Averages Like a ChaseHow Institutions May Be Using Moving Averages to Align Technicals with Fundamentals
Are moving averages just for retail traders and chart watchers? Not if you're JPMorgan Chase.
While many associate moving averages (MAs) with simple trading strategies, institutional giants like JPMorgan Chase likely use them very differently. Instead of relying on MAs to chase trends, they may use them as confluence tools—where technical signals meet macroeconomic insight, risk models, and long-term strategy.
Here’s how JPMorgan might be using moving averages across their medium- to long-term investments—and what you can learn from it.
📊 1. Moving Averages as Investment Benchmarks
At the institutional level, MAs aren’t just "buy/sell" triggers. JPMorgan likely treats the 50-day and 200-day moving averages as dynamic references that help answer broader questions:
Is this trend aligned with the macro picture?
Is this a real shift, or just short-term volatility?
How do fund flows behave around these levels?
Rather than acting on the average itself, JPMorgan probably uses it to validate investment theses and smooth out the noise.
⚙️ 2. Confluence: Where Technicals and Fundamentals Align
In large portfolios, confluence is king. It’s not just about one indicator—but about multiple factors aligning to strengthen conviction.
MAs might be used alongside:
Macro trends (GDP growth, inflation, interest rates)
Sector momentum (e.g. financials vs. tech rotation)
Earnings growth and valuation models
Liquidity flows and volatility data
When a stock reclaims its 200-day MA and fundamentals improve, that’s a green light. When everything lines up, JPMorgan can move with more confidence.
📈 3. A Probabilistic (Not Predictive) Approach
Institutions don’t deal in absolutes—they deal in probabilities. JPMorgan’s quant teams likely test how often certain MA setups lead to favorable outcomes under different market regimes.
So instead of reacting to a crossover, they may ask:
"How often does this setup succeed, given current economic conditions?"
If the odds are strong, they’ll scale in. If not, they’ll wait or hedge. It’s a measured, data-driven approach to timing.
🛡️ 4. Risk Management and Strategic Timing
Moving averages are also incredibly useful for managing portfolio risk. They offer:
Clarity in volatile markets
Timing cues for rebalancing
Visual structure for entries/exits
MAs help JPMorgan place guardrails around long-term positions—keeping strategy in check while avoiding overreactions to noise.
🔍 Final Thought: JPMorgan Isn’t Chasing Trends—They’re Refining Them
The lesson for investors? Don’t treat moving averages as magic lines. Used well, they become tools of confirmation and control, not prediction.
For JPMorgan Chase, MAs are likely just one piece of a much larger puzzle—blending technicals with fundamentals, data science, and market context to execute with precision.
💡 Pro Tip: You can apply the same idea to your own strategy—use moving averages to validate your thesis, not to drive it. Confluence is the key.
Trading Performance Review🎯 April 4 – May 3 | Trading Performance Review
Over the past 30 days, I executed 146 trades with a data-driven strategy focused on risk-adjusted returns and quantitative consistency.
🔍 Performance Metrics:
Total Trades: 146
Win Rate: 70.55%
Winning Trades: 103
Losing Trades: 43
Profitable Days: 22 / 30
No-Trade Days: 2
Winning vs Losing Trade Ratio:
✅ Winning Trades: 70.5%
❌ Losing Trades: 29.5%
Daily Outcome Distribution:
🟢 Profitable Days: 73.3%
🔴 Loss Days: 20%
⚪ No Trade: 6.7%
📈 This outcome reflects a strategy rooted in structured risk management, discipline, and probability-based execution — not impulsive decisions. Each trade was placed with purpose, not emotion.
With every data point, my trading edge sharpens. The goal remains the same: consistent performance through controlled risk and strategic action.
Progress is not measured by the number of trades, but by the quality of each decision.
EURUSD SHORT FORECAST & TRADE EXECUTION Q2 W19 D5 Y25EURUSD SHORT FORECAST & TRADE EXECUTION Q2 W19 D5 Y25
Professional Risk Managers👋
Welcome back to another FRGNT chart update📈
Diving into some Forex setups using predominantly higher time frame order blocks alongside confirmation breaks of structure.
Let’s see what price action is telling us today!
💡Here are some trade confluences 📝
✅Weekly order block rejection
✅Daily order block rejection
✅Intraday 15' order blocks
✅Tokyo ranges to be filled
✅1' multiple breaks of structure short
✅1' bearish engulfing candle
✅Entry upon the rebalance of the 1' engulfing candle
✅Short position from a probable point of interest
🔑 Remember, to participate in trading comes always with a degree of risk, therefore as professional risk managers it remains vital that we stick to our risk management plan as well as our trading strategies.
📈The rest, we leave to the balance of probabilities.
💡Fail to plan. Plan to fail.
🏆It has always been that simple.
❤️Good luck with your trading journey, I shall see you at the very top.
🎯Trade consistent, FRGNT X
From Tulips to Tech: The Evolution of Financial Bubbles 🎯 Introduction:
financial/economic bubbles are a recurring theme in economic history, this is often when a particular financial asset goes to unrealistic price levels often making money for early investors but usually these high price levels do not match their fundamental value this is then followed by a large public participation who also want a piece of the pie eventually with the price collapsing or sharply declining blowing or living investors in a large financial loss..
From 17th-century tulip gardens to 21st-century crypto manias, one thing has remained constant: Humans never learn.
Every generation thinks this time is different — but the pattern of bubbles keeps repeating.
Here's the crash course in 400 years of financial euphoria, panic, and pain.
🧠 Section 1: 1637 — Tulip Mania 🌷
The original bubble.
In the Netherlands, rare tulip bulbs were worth more than houses.
Prices exploded... then collapsed 90% in a matter of weeks.
Lesson: Speculation + FOMO is not new. Humans were flipping flowers before they flipped crypto.
Mini Nerd Tip:
"When people stop caring about value and only care about price rising, watch out."
🧠 Section 2: 1720 — South Sea Bubble 📜
Britain’s South Sea Company promised massive profits trading with South America (but barely did any business).
Politicians and aristocrats pumped the stock price.
Collapsed spectacularly → ruined many fortunes (including Isaac Newton himself:
"I can calculate the motion of heavenly bodies, but not the madness of men.")
Mini Nerd Tip:
"If a bubble needs government help to stay alive, it's already dying."
🧠 Section 3: 1929 — Wall Street Crash 🏛️
Roaring 20s: endless optimism, cheap margin loans, "stocks only go up!"
1929: Stock market crashed, triggering the Great Depression.
People were buying stocks with 10% down and gambling recklessly.
Mini Nerd Tip:
"When leverage is everywhere, the smallest panic causes waterfalls."
🧠 Section 4: 2000 — Dotcom Bubble 💻
Everyone thought the internet would change everything (it did — but slower and differently).
Companies with no profits were valued in billions.
"Eyeballs" were treated as real revenue.
NASDAQ lost 78% from top to bottom.
Mini Nerd Tip:
"Innovation creates real value... but hype inflates fake value faster."
🧠 Section 5: 2008 — Housing Bubble 🏡
Banks handed out mortgages to anyone.
Financial engineering (CDOs, synthetic MBS) created the illusion of safety.
US housing prices collapsed → global financial crisis.
"Too Big to Fail" became the famous phrase.
Mini Nerd Tip:
"If everyone is getting rich easily, someone is lying or blind."
🧠 Section 6: 2017/2021 — Crypto & Meme Stocks 🚀
Gamestop, Dogecoin, NFTs, Shiba Inu — the wildest "everyone’s a genius" market since the 1920s.
Social media + free apps = amplified bubble speed.
Massive rises, insane collapses.
Mini Nerd Tip:
"Technology changes, human emotion doesn’t."
🧠 Final Section: Why Bubbles Will Never End
Greed, fear, and FOMO are timeless.
Every era dresses up bubbles in new clothes (flowers, sea companies, internet, crypto).
Smart traders understand this pattern — and use it to survive and thrive.
"**Bubbles don't pop because of bad assets. They pop because confidence disappears
put together by : Pako Phutietsile as @currencynerd
courtesy of : @TradingView
NAS100 and the analysis that has reached a conclusion and has noToday I was reviewing my previous analyses when I came across this chart on NAS100 and after months of waiting, it had come to fruition.
It's a bit late to publish now, but I will gradually increase the number of symbols and arrange the time so that the results are available to everyone on time!!
Good luck!
MJ.REZAEI
Breadbasket Basics: Trading Wheat Futures🟡 1. Introduction
Wheat may be a breakfast-table staple, but for traders, it’s a globally sensitive asset — a commodity that reacts to geopolitics, climate patterns, and shifting demand from dozens of countries.
Despite its critical role in food security and its status as one of the most traded agricultural commodities, wheat is often overlooked by traders who focus on corn or soybeans. Yet wheat offers a unique combination of liquidity, volatility, and macro sensitivity that makes it highly attractive for both hedgers and speculators.
If you’re new to trading wheat, this guide gives you a solid foundation: how the wheat market works, who the key players are, and what makes wheat such a dynamic futures product.
🌍 2. Types of Wheat and Where It Grows
One of the first things traders need to understand is that wheat is not a single, uniform product. It’s a diverse group of grain types, each with its own characteristics, end uses, and pricing dynamics.
The major classes of wheat include:
Hard Red Winter (HRW): High-protein wheat grown in the central U.S. — used in bread and baking.
Soft Red Winter (SRW): Lower protein, used for pastries and crackers.
Hard Red Spring (HRS): Grown in the Northern Plains; prized for high gluten content.
Durum Wheat: Used for pasta, grown mainly in North Dakota and Canada.
White Wheat: Grown in the Pacific Northwest; used for noodles and cereals.
Each class responds differently to weather, demand, and regional risks — giving traders multiple ways to diversify or hedge.
Major global producers include:
United States
Russia
Canada
Ukraine
European Union
Australia
India
These regions experience different planting and harvesting calendars — and their weather cycles are often out of sync. This creates trading opportunities year-round.
🛠️ 3. CME Group Wheat Contracts
Wheat futures are traded on the Chicago Board of Trade (CBOT), part of the CME Group.
Here are the two key contracts:
o Standard Wheat
Ticker: ZW
Size = 5,000 bushels
Tick = 0.0025 = $12.50
Margin = ~$1,750
o Micro Wheat
Ticker: MZW
Size = 500 bushels
Tick = 0.0050 = $2.50
Margin = ~$175
Keep in mind that margins are subject to change — always confirm with your broker. Micro contracts are ideal for scaling in/out of trades or learning market structure without large capital risk.
📅 4. Wheat’s Seasonality and Supply Chain
Unlike corn or soybeans, wheat is planted and harvested across multiple seasons depending on the variety and geography.
In the U.S., winter wheat (HRW and SRW) is planted in the fall (September–November) and harvested in early summer (May–July). Spring wheat (HRS) is planted in spring (April–May) and harvested late summer.
Globally, things get even more staggered:
Australia’s wheat is harvested in November–December
Ukraine and Russia harvest in June–August
Argentina’s crop comes off the fields in December–January
This scattered global schedule means news headlines about one country’s weather or war (think Ukraine in 2022) can quickly shift sentiment across the entire futures curve.
📈 5. Who Trades Wheat and Why
Wheat is traded by a wide range of participants — each with their own objectives and strategies. Understanding their behavior can give you an edge in anticipating market moves.
Commercial hedgers:
Farmers lock in prices to protect against adverse weather or market crashes.
Grain elevators and exporters use futures to manage inventory risk.
Flour mills hedge their input costs to protect profit margins.
Speculators:
Hedge funds and CTAs trade wheat based on global macro trends, weather anomalies, or technical setups.
Retail traders increasingly use micro contracts to gain exposure to agricultural markets with lower capital risk.
Spread traders bet on pricing differences between wheat classes or harvest years.
🔍 For retail traders especially, micro contracts like XW open the door to professional markets without oversized exposure.
🧠 6. What Makes Wheat Unique in Futures Markets
Wheat is often considered the most geopolitically sensitive of the major grains. Here’s why:
Price can spike fast — even on rumor alone (e.g., export bans or missile strikes near ports).
Production risks are global — the market reacts not just to the U.S. crop, but to conditions in Russia, Ukraine, and Australia.
Storage and quality matter — protein levels and moisture content affect milling demand.
Unlike corn, wheat doesn’t have a single dominant industrial use (like ethanol). This means food demand is king, and food security often drives policy decisions that affect futures pricing.
📌 7. Summary / Takeaway
Wheat may not get as much media attention as corn or soybeans, but it’s a deeply important — and deeply tradable — market. Its global footprint, class differences, and sensitivity to weather and politics make it a must-know for serious agricultural futures traders.
Whether you're just starting out or looking to diversify your trading playbook, understanding wheat is an essential step. Learn its rhythms, follow its news, and respect the fact that every crop cycle brings a new story to the market.
🧭 This article is part of an ongoing educational series exploring futures trading in agricultural commodities.
📅 Watch for the next release: “Soybeans: The Global Protein Powerhouse.”
When charting futures, the data provided could be delayed. Traders working with the ticker symbols discussed in this idea may prefer to use CME Group real-time data plan on TradingView: www.tradingview.com - This consideration is particularly important for shorter-term traders, whereas it may be less critical for those focused on longer-term trading strategies.
General Disclaimer:
The trade ideas presented herein are solely for illustrative purposes forming a part of a case study intended to demonstrate key principles in risk management within the context of the specific market scenarios discussed. These ideas are not to be interpreted as investment recommendations or financial advice. They do not endorse or promote any specific trading strategies, financial products, or services. The information provided is based on data believed to be reliable; however, its accuracy or completeness cannot be guaranteed. Trading in financial markets involves risks, including the potential loss of principal. Each individual should conduct their own research and consult with professional financial advisors before making any investment decisions. The author or publisher of this content bears no responsibility for any actions taken based on the information provided or for any resultant financial or other losses.
Why Being Delusional Might Be Your Greatest Asset in TradingIf you think you’re going to make a full-time living trading financial markets you’re completely delusional!... and that's a good thing.
It was 1997, and two friends—let’s call them Reed and Marc—thought it would be fun to have a movie night and rent Apollo 13 from their local Blockbuster store.
For those of you who might need some context, Blockbuster was a video rental store where you’d go to rent a movie you’d like to watch.
This was shortly after discovering fire and the wheel, and it was revolutionary. At its peak, Blockbuster was worth approximately $5 billion and had over 80,000 employees across 9000 stores worldwide.
Their business model was very simple, and although they generated revenue in various ways, their core revenue was generated through a combination of rental fees, video sales and late fees.
You see, it just so happened that our two friends who thought it would be fun to rent Apollo 13, chill at home, and eat popcorn would essentially have to pay the $40 late fee, and they were admittedly, not too happy about that.
As they sat in frustration, one of them came up with the idea to start a website and rent movies to people without charging a late fee.
Instead people would just pay a monthly subscription of around $19.95 per month and they could rent up to three movies of their choosing and keep it for as long as they wanted, no rental fee, no video sales, no late fees, just a monthly subscription of $19.95.
If people wanted to rent a new set of DVD’s then all they’d need to do is return the DVD’s they’d initially rented and the new set was mailed to them within a day or two.
Now it is important to mention that all this occurred toward the end of the third industrial revolution and the internet was not nearly as advanced as it is today. People would use a dial-up connection which only produced 56 kbps or slower.
Streaming was near impossible unless you enjoyed watching a movie in three-minute increments before it loaded the next three minutes. Downloading a movie could take an entire day or even longer.
It’s fair to say that our two friends Reed and Marc were throwing stones at giants, but they had very good aim.
I’m sure you heard the story where a boy aimed at a giant's head and threw him with a stone. Turns out the boy won that fight, and ultimately claimed victory for his people, but I digress.
You see Reed had a background in computer science and software development, and at the time he co-founded a software company called Pure Software. Marc had a background in marketing and product development.
It’s safe to say that they made a very good team, but they were still going up against giants, they were challenging a system that was working with a system that was not even established yet. Essentially, they either had to be very confident or extremely delusional. Turns out they were both.
They decided to brainstorm a few names for their little startup, everything from Kibble to TakeOne, and even DirectPix and none of it seemed to stick. Eventually, they decided to combine the words “internet” and “film” to make “Netflix”.
Today Netflix is the most popular streaming platform, with its annual revenue peaking at 33.7 Billion back in 2023.
I share this story with you because it really takes more than just experience, skill, and luck to take on giants, I would argue you need to have a healthy amount of delusion as well.
So, if you think you're going to make a full-time living trading financial markets, you're completely delusional—and that might be the best thing going for you.
Because the truth is, every breakthrough, every disruption, every world-changing idea begins with someone who dares to believe in something that doesn’t quite make sense to the rest of the world—yet.
Reed and Marc didn’t just challenge a system; they challenged what was possible at the time. They bet on a future that didn’t exist—on a slower internet, a skeptical audience, and an unproven model. What looked like delusion was a vision in disguise.
In trading, as in business and life, it’s not the most logical or the most experienced who wins—it’s often those who are bold enough to stay in the game when everyone else calls it crazy. You’ll need skill, yes.
Strategy, of course. But you’ll also need the unreasonable belief that you can beat the odds, learn the rules, and then rewrite them entirely. So go ahead—be delusional.
Just make sure you’ve got the grit, the patience, and the aim to back it up.
What “giant” are you bold enough to challenge next?
How to Enter Trades the RIGHT Way!In this video, we're tackling an important question from our community member who's been crushing it in paper trading but faces the common challenge of entering trades blindly based on alerts, fearing they'll miss out otherwise.
We'll discuss:
Why blindly following signals can hurt your long-term success
The power of context in market structure: Why waiting for price to hit key support/resistance levels drastically improves your entries
A practical approach to manage FOMO: How scaling into trades can balance quick reaction times with better entries and tighter stops
Real examples of good vs. rushed entries, highlighting the impact on your risk-to-reward
This daily pattern can change your view on price!Dear Community,
How many patterns do you know?
<5?
<20?
>20?
How many of them actually work with GREAT accuracy?
Patterns are something that we often use in trying to predict the markets….BUT I dear to say pattern alone won’t work?
THE PATTERN NEED A FRAMEWORK!
let’s discuss this “pattern” highlighted on your screen.
Why is the candle after that “doji “ higher?
Often you try to “call tops” in the market place.
And after seeing this “doji”…. WE SELL RIGHT?
if the maker is going up why do we try and call a top?
Why do we try and not “follow the trend?”
On your daily chart examine this.
IF THE MARKET IF BULLISH AND I SEE A DOJI!
Study the candle that formed just after. YOU WILL BE AMAZED BY THE FINDINGS 😃.
No I will not share the stats. If an “homework” for your own development. Let’s discuss this further in the comments below.
Trading Without Goals Is Just Gambling With StructureA lot of traders talk about discipline. But few realize that discipline has to be anchored to something. It doesn’t work in a vacuum. Without a clear reason to stay focused, most people eventually fall back into overtrading, revenge trading, or breaking their own rules.
That “something” is your personal set of financial goals.
If you’re trading without a list of well-defined, written goals—short term and long term—you’re not building a system. You’re improvising. And over time, the market will punish improvisation.
Goals Create the Structure That Risk Management Lives In
It’s common to hear that risk management is the key to long-term success in Forex. That’s true. But risk management doesn’t exist in isolation. You can’t determine how much to risk per trade if you don’t know what you’re aiming for in the big picture.
When your trading plan is connected to real financial targets—like building a retirement fund, generating side income, or compounding over years, you stop treating each trade like a lottery ticket.
Your lot size changes. Your trade frequency changes. Your psychology changes.
Clarity Reduces Emotion
One of the biggest causes of emotional trading is uncertainty. When you’re not clear on where you're going or why you’re even in a trade, the smallest loss can shake your confidence. A win might tempt you to increase your size. A string of losses might tempt you to change systems or walk away completely.
But when you’re trading with a purpose, decisions become less reactive. You have a framework to evaluate whether something aligns with your objectives.
And that makes it easier to say no to setups that don’t fit, or to walk away from the screen when nothing’s there.
Write Your Goals Down—In Detail
If your goals aren’t written, they don’t exist.
And “make money” is not a goal. It’s a wish.
Good goals are specific, time-based, and measurable. For example:
Grow a $1,000 account to $1,500 over 6 months by risking 1% per trade
Extract 4% per month on average while maintaining a max drawdown of 10%
Build a track record of 100 trades with full journal documentation and risk control
Once written, these goals form the backbone of your trading plan. They influence your risk-per-trade, your system choice, and how often you trade.
They also give you a benchmark. You’ll know if you’re making progress or just going in circles.
Final Thought: Know What You’re Playing For
Too many traders operate without direction. They chase results, compare themselves to others, and burn out. It doesn’t have to be this way.
Start with the end in mind. Know why you’re trading. Set real goals. And let those goals drive your decisions, your risk management, and your daily focus.
Discipline becomes easier when you have something worth being disciplined for.
I have been for 2.5 years on Demo, and will not move from there until I achieve the targets that I have set. Achieving those targets on Demo does mean I will achieve them on live trading. On the other hand, not achieving them on a Demo account mean that the only thing I will be able to achieve on a live account is blow the account away.
Learn KEY PRINCIPLES of Technical Analysis in Gold Forex Trading
In the today's article, we will discuss the absolute basics of trading - 3 key principles of technical analysis in Forex & Gold Trading.
1️⃣History Repeats
History tends to repeat itself in the Forex market.
Certain trends are cyclical and may reemerge in a predictable manner, certain key levels are respected again and again over time.
Take a look at the example:
Silver perfectly respected a historical horizontal resistance in 2011 that was respected in 1980 already. Moreover, the price action before and after the tests of the underlined zone were absolutely identical.
2️⃣Priced In
All relevant information about a currency pair: economical and political events, rumors, and facts; is already reflected in a price.
When the FED increased the rate 26th of July by 25 bp, EURUSD bounced instead of falling. Before the rate hike, the market was going down on EXPECTATIONS of a rate hike. The release of the news was already price in.
3️⃣Pattern DO Work
Some specific price models can be applied for predicting the future price movements.
Technicians strongly believe that certain formations - being applied and interpreted properly, can give the edge on the market.
Depending on the trading style, different categories of patterns exist: harmonic patterns, price action patterns, wave patterns, candlestick patterns...
Above, I have listed various price action patterns that are applied by many traders and investors as the main tool for analyzing the financial markets.
If you believe in these 3 principles, you are an inborn technician!
Study technical analysis and learn to apply these principles to make money in trading.
b]❤️Please, support my work with like, thank you!❤️
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