EMA Trend Alignment (10/20/50) with MTF & SignalsBullish Crossovers 10>20>50 and Bearish Crossover 10<20<50
Médias Móveis
9/20 EMA Trend indicator Fill for daytrading fills a color in between the lines of the 9 and 20 EMA to show trend easily
EMA 50/200 Pullback + RSI (BTC/USDT 15m - 2 Bar Logic)I recognize that combining indicators requires clear justification on how the components interact Therefore the new scripts description will explicitly detail the strategys operational logic
Objective The strategy is a Trend Following Pullback System designed for high frequency time frames 15m
Synergy The EMA50 EMA200 defines the primary Trend Direction Trend Filter It then utilizes a 2 Bar Pullback Logic to find an entry point where the price has momentarily reversed against the trendline and the RSI 14 serves as a Momentum Filter RSI greater than 50 for Long RSI less than 50 for Short to minimize false signals
Smart Trend Signal with Bands [wjdtks255]Indicator Description for TradingView
Title: Adaptive Trend Kernel
Description:
The "Adaptive Trend Kernel " is a versatile trend-following and volatility indicator designed to help traders identify dynamic market trends, potential reversals, and price extremes within a channel. Built upon a customized linear regression model, this indicator provides clear visual cues to enhance your trading decisions.
Key Features:
Regression Line: A central dynamic line representing the core trend direction, calculated based on a user-defined "Regression Length."
Regression Bands: Standard deviation-based bands plotted around the Regression Line, which act like a dynamic channel. These bands expand and contract with market volatility, indicating potential overbought/oversold conditions relative to the trend.
Trend Reversal Signals: Distinct "Up" (green triangle up) and "Down" (red triangle down) signals are generated when the price (close) crosses over or under the Regression Line. These signals suggest potential shifts in the short-term trend direction.
Visual Customization: Highly flexible input options for adjusting line colors, band colors, line width, and panel opacity. Users can toggle the visibility of bands and trend labels to suit their chart preferences.
Panel Label: A subtle "Regression" label is dynamically positioned, offering clear context without cluttering the main chart.
How it Works: The indicator calculates a linear regression line as the adaptive center of the price movement. Standard deviation is then used to create upper and lower bands, encapsulating typical price fluctuations. Signals are fired when price breaks out of the regression line, suggesting a momentum shift in line with the established trend or a potential reversal.
Trading Methods & Strategies
Here are some trading strategies you can apply using the "Adaptive Trend Kernel " indicator:
Trend-Following with Confirmation:
Long Entry: Look for an "Up" signal (green triangle up) when the price is above the Regression Line, especially after a brief retracement towards the line. This confirms that the uptrend is likely resuming.
Short Entry: Look for a "Down" signal (red triangle down) when the price is below the Regression Line, especially after a brief rally towards the line. This confirms that the downtrend is likely resuming.
Exit Strategy: Consider exiting if an opposite signal appears, or if the price closes outside the opposite band, indicating potential overextension or reversal.
Reversal / Counter-Trend Play:
Long Entry (Aggressive): When the price approaches or briefly dips below the Lower Regression Band and then generates an "Up" signal (green triangle up). This could indicate a potential bounce from an oversold condition relative to the trend.
Short Entry (Aggressive): When the price approaches or briefly moves above the Upper Regression Band and then generates a "Down" signal (red triangle down). This could indicate a potential pullback from an overbought condition relative to the trend.
Confirmation: This strategy works best when combined with other reversal confirmation patterns (e.g., bullish/bearish engulfing candlesticks) or divergences in other momentum indicators (like RSI).
Volatility Breakout:
Entry (Long): After a period of low volatility where the Regression Bands are narrow, observe if the price decisively breaks above the Upper Regression Band and an "Up" signal appears. This suggests a strong bullish momentum breakout.
Entry (Short): After a period of low volatility where the Regression Bands are narrow, observe if the price decisively breaks below the Lower Regression Band and a "Down" signal appears. This suggests a strong bearish momentum breakdown.
Management: Volatility breakouts can be swift; use appropriate risk management and profit-taking strategies.
Important Considerations:
Risk Management: Always apply proper stop-loss and take-profit levels. No indicator is infallible.
Timeframe Sensitivity: Adjust the "Regression Length" and "Band Multiplier" according to the asset and timeframe you are trading. Shorter lengths might suit scalping, while longer lengths are better for swing trading.
Confirmation with Other Tools: For higher conviction trades, use this indicator in conjunction with other technical analysis tools such like volume, MACD, or RSI on an oscillator pane.
Backtesting: Always backtest any strategy on historical data to understand its performance characteristics before live trading.
Trinity ATR Strategy (Saty) - Backtest EditionThis is not supposed to be a standalone indicator, but releasing this to give a general overview of what it could do, each commodity and timeframe would need to be back tested. Use in conjunction with other indicators and price action. This is not financial advice and is not a guarantee of financial results.
Trinity Dynamic ATR Levels (Saty)This is an updated version of the SATY ATR levels ()
Trinity Dynamic ATR Levels
The core logic is 100 % identical: same higher-timeframe ATR calculation, same trigger at ~23.6 %, same Fibonacci and extension levels, same 8-21-34 EMA ribbon for the trend color in the table, and the table itself looks exactly like the original again (4 rows, clean layout, no extra target row). The visual and usability upgrades you now have that the original does not:
Lower Trigger line is now red instead of yellow, Upper Trigger line is now green instead of aqua/cyan to indicate to go long or short.
Every single level group has its own color input so you can customize everything (previous close, fib levels, 61.8 %, 100 % ATR, extensions, 200 %, 300 %, etc.) without touching the code. Every plotted level now has a clear text label on the right side of the chart (“Prev Close”, “Lower Trig”, “Upper Trig”, “-61.8 %”, “+100 %”, “-200 %”, etc.) so you instantly know what you’re looking at.
A new input called “Target Distance (×ATR)” lets you decide how far your profit target is (default 1.0 = +100 % ATR, but you can set 1.618, 2.0, 2.618, etc. instantly).
As soon as price closes above the Upper Trigger or below the Lower Trigger, a big, obvious target box automatically appears on the right side of the screen showing the exact dollar target price for the active long or short (green box for longs, red box for shorts). When there is no active trigger, the box disappears and the table stays perfectly clean.
In short, you now have the exact same beloved Saty ATR indicator everyone uses, but with red/green triggers, full color control, level labels, and a beautiful dynamic target box that only shows up when you actually have a trade on — all while keeping the original clean 4-row table untouched. It’s the cleanest and most professional version you’ll find anywhere. Enjoy! 🚀
EMA Cross Strategy v5 (30 lots) (15 min candle only)- safe flip🚀 EMA Cross Strategy v5 (30 Lots) (15 min candle only)— Safe Flip Edition
Fully Automated | Fast | Reliable | Battle-tested
Welcome to a clean, powerful, and automation-friendly EMA crossover system.
This strategy is built for traders who want consistent trend-based entries without the risk of unwanted pyramiding or doubled positions.
🔥 How It Works
This strategy uses a fast EMA (10) crossing a slow EMA (20) to detect trend shifts:
Bullish Crossover → LONG (30 lots)
Bearish Crossover → SHORT (30 lots)
Every opposite signal safely flips the position by first closing the current trade, then opening a fresh position of exactly 30 lots.
No doubling.
No runaway position size.
No surprises.
Just clean, mechanical trend-following.
📈 Why This Strategy Stands Out
Unlike basic EMA crossbots, this version:
✔ Prevents unintended pyramiding
✔ Never over-allocates capital
✔ Works perfectly with webhook-based automation
✔ Produces stable, systematic entries
✔ Executes directional flips with precision
🔍 Backtest Highlights (1-Year)
(Backtests will vary by instrument/timeframe)
1,500+ trades executed
Profit factor above 1.27
Strong trend performance
Balanced long/short behavior
No margin calls
Consistent trade execution
This strategy thrives in trending markets and maintains strict discipline even in choppy conditions.
⚙️ Automation Ready
Designed for automated execution via webhook and API setups on supported platforms.
Just connect, run, and let the bot follow the rules without hesitation.
No emotions.
No overtrading.
No fear or greed.
Pure logic.
triple cruce CarpatosWe are using a moving average package: three exponential moving averages of 4, 18, and 40 periods, and a simple moving average of 200. This is similar to the classic triple death cross, except for a small change in the EMA from 14 to 18.
The idea is to use the triple cross of the fast moving averages to determine entry or exit points as appropriate, and a 200-period simple moving average to define the long-term trend.
Distância Preço vs EMAIndicador pra ser usado em tendencias consolidadas como referencias para retorno a média
Argentina Price per m² (USD) — (1999–2025)Overview
This indicator plots the historical USD price per square meter of apartments in CABA (Buenos Aires City), Argentina, combining annual data (1999–2011) from Maure Real Estate Market Reports with monthly data (2012–2025) from UCEMA and private market sources.
All values were manually digitized, cleaned, and consolidated to reconstruct the most complete long-term pricing series publicly available.
The script also includes SMA20, SMA50, and SMA100 over the custom dataset to support long-term trend analysis, cycle detection, and macro technical structure.
Data Sources
1999–2011 (Annual): Maure Real Estate Market Reports
2012–2020 (Monthly): UCEMA Real Estate Index
2020–2025 (Monthly): RE/MAX – UCEMA Market Monitor
How to Use This Indicator
This tool allows investors, developers, and analysts to:
Identify multiyear trend shifts
Compare cycles vs. Argentine macro environments
Map long-term support/resistance zones in real estate
Detect early signs of market recovery or contraction
Combine real estate fundamentals with technical analysis
The SMAs help visualize structural trends normally hidden in real estate data.
About This Work
This series was fully reconstructed and coded by engineer Francisco Michelich (@esFranMiche on X), combining market research, statistical consolidation, and technical analysis.
It is intended as an analytical tool, not an official financial index.
If you find this useful, feel free to follow and connect — feedback and collaboration are welcome.
Linkedin
X
ZH1/5-Min Opening Range Breakout Strategy with Market Biasx.com
"ZH1/5-Min Opening Range Breakout Strategy with Market Bias"
Golden Cross 50/200 EMATrend-following systems are characterized by having a low win rate, yet in the right circumstances (trending markets and higher timeframes) they can deliver returns that even surpass those of systems with a high win rate.
Below, I show you a simple bullish trend-following system with clear execution rules:
System Rules
-Long entries when the 50-period EMA crosses above the 200-period EMA.
-Stop Loss (SL) placed at the lowest low of the 15 candles prior to the entry candle.
-Take Profit (TP) triggered when the 50-period EMA crosses below the 200-period EMA.
Risk Management
-Initial capital: $10,000
-Position size: 10% of capital per trade
-Commissions: 0.1% per trade
Important Note:
In the code, the stop loss is defined using the swing low (15 candles), but the position size is not adjusted based on the distance to the stop loss. In other words, 10% of the equity is risked on each trade, but the actual loss on the trade is not controlled by a maximum fixed percentage of the account — it depends entirely on the stop loss level. This means the loss on a single trade could be significantly higher or lower than 10% of the account equity, depending on volatility.
Implementing leverage or reducing position size based on volatility is something I haven’t been able to include in the code, but it would dramatically improve the system’s performance. It would fix a consistent percentage loss per trade, preventing losses from fluctuating wildly with changes in volatility.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to stop loss
And when volatility is high and would exceed the fixed percentage we want to expose per trade (if the SL is hit), we could reduce the position size accordingly.
Practical example:
Imagine we only want to risk 15% of the position value if the stop loss is triggered on Tesla (which has high volatility), but the distance to the SL represents a potential 23.57% drop. In this case, we subtract the desired risk (15%) from the actual volatility-based loss (23.57%):
23.57% − 15% = 8.57%
Now suppose we normally use $200 per trade.
To calculate 8.57% of $200:
200 × (8.57 / 100) = $17.14
Then subtract that amount from the original position size:
$200 − $17.14 = $182.86
In summary:
If we reduce the position size to $182.86 (instead of the usual $200), even if Tesla moves 23.57% against us and hits the stop loss, we would still only lose approximately 15% of the original $200 position — exactly the risk level we defined. This way, we strictly respect our risk management rules regardless of volatility swings.
I hope this clearly explains the importance of capping losses at a fixed percentage per trade. This keeps risk under control while maintaining a consistent percentage of capital invested per trade — preventing both statistical distortion of the system and the potential destruction of the account.
About the code:
Strategy declaration:
The strategy is named 'Golden Cross 50/200 EMA'.
overlay=true means it will be drawn directly on the price chart.
initial_capital=10000 sets the initial capital to $10,000.
default_qty_type=strategy.percent_of_equity and default_qty_value=10 means each trade uses 10% of available equity.
margin_long=0 indicates no margin is used for long positions (this is likely for simulation purposes only; in real trading, margin would be required).
commission_type=strategy.commission.percent and commission_value=0.1 sets a 0.1% commission per trade.
Indicators:
Calculates two EMAs: a 50-period EMA (ema50) and a 200-period EMA (ema200).
Crossover detection:
bullCross is triggered when the 50-period EMA crosses above the 200-period EMA (Golden Cross).
bearCross is triggered when the 50-period EMA crosses below the 200-period EMA (Death Cross).
Recent swing:
swingLow calculates the lowest low of the previous 15 periods.
Stop Loss:
entryStopLoss is a variable initialized as na (not available) and is updated to the current swingLow value whenever a bullCross occurs.
Entry and exit conditions:
Entry: When a bullCross occurs, the initial stop loss is set to the current swingLow and a long position is opened.
Exit on opposite signal: When a bearCross occurs, the long position is closed.
Exit on stop loss: If the price falls below entryStopLoss while a position is open, the position is closed.
Visualization:
Both EMAs are plotted (50-period in blue, 200-period in red).
Green triangles are plotted below the bar on a bullCross, and red triangles above the bar on a bearCross.
A horizontal orange line is drawn that shows the stop loss level whenever a position is open.
Alerts:
Alerts are created for:Long entry
Exit on bearish crossover (Death Cross)
Exit triggered by stop loss
Favorable Conditions:
Tesla (45-minute timeframe)
June 29, 2010 – November 17, 2025
Total net profit: $12,458.73 or +124.59%
Maximum drawdown: $1,210.40 or 8.29%
Total trades: 107
Winning trades: 27.10% (29/107)
Profit factor: 3.141
Tesla (1-hour timeframe)
June 29, 2010 – November 17, 2025
Total net profit: $7,681.83 or +76.82%
Maximum drawdown: $993.36 or 7.30%
Total trades: 75
Winning trades: 29.33% (22/75)
Profit factor: 3.157
Netflix (45-minute timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $11,380.73 or +113.81%
Maximum drawdown: $699.45 or 5.98%
Total trades: 134
Winning trades: 36.57% (49/134)
Profit factor: 2.885
Netflix (1-hour timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $11,689.05 or +116.89%
Maximum drawdown: $844.55 or 7.24%
Total trades: 107
Winning trades: 37.38% (40/107)
Profit factor: 2.915
Netflix (2-hour timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $12,807.71 or +128.10%
Maximum drawdown: $866.52 or 6.03%
Total trades: 56
Winning trades: 41.07% (23/56)
Profit factor: 3.891
Meta (45-minute timeframe)
May 18, 2012 – November 17, 2025
Total net profit: $2,370.02 or +23.70%
Maximum drawdown: $365.27 or 3.50%
Total trades: 83
Winning trades: 31.33% (26/83)
Profit factor: 2.419
Apple (45-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $8,232.55 or +80.59%
Maximum drawdown: $581.11 or 3.16%
Total trades: 140
Winning trades: 34.29% (48/140)
Profit factor: 3.009
Apple (1-hour timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $9,685.89 or +94.93%
Maximum drawdown: $374.69 or 2.26%
Total trades: 118
Winning trades: 35.59% (42/118)
Profit factor: 3.463
Apple (2-hour timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $8,001.28 or +77.99%
Maximum drawdown: $755.84 or 7.56%
Total trades: 67
Winning trades: 41.79% (28/67)
Profit factor: 3.825
NVDA (15-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $11,828.56 or +118.29%
Maximum drawdown: $1,275.43 or 8.06%
Total trades: 466
Winning trades: 28.11% (131/466)
Profit factor: 2.033
NVDA (30-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $12,203.21 or +122.03%
Maximum drawdown: $1,661.86 or 10.35%
Total trades: 245
Winning trades: 28.98% (71/245)
Profit factor: 2.291
NVDA (45-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $16,793.48 or +167.93%
Maximum drawdown: $1,458.81 or 8.40%
Total trades: 172
Winning trades: 33.14% (57/172)
Profit factor: 2.927
Advanced Intraday Darvas BoxThis indicator applies a modern Darvas Box strategy for intraday traders, using non-repainting pivot detection combined with strong filters to reduce chart noise:
Confirmed swing highs and lows: Boxes only form when genuine swing pivots appear, ensuring fully non-repainting signals.
Minimum box height: Small, "noise" boxes are filtered out using ATR multiples for meaningful zones.
Trend filter: Choose EMA, SMA, or VWAP to lock boxes and breakouts to market direction.
Volume confirmation: Boxes are only confirmed when volume is above a user-defined threshold, highlighting high-participation moves.
Breakout filter: Signals trigger only if the breakout candle closes substantially beyond the box, reducing false breakouts.
Limited box display: Recent boxes only, keeping your chart clean and readable.
Features & Inputs
Pivot sensitivity: Set the number of bars for swing calculation.
Box filtering: Specify the minimum ATR multiple for box size.
Trend selection: EMA, SMA, VWAP, or None.
Volume filter & threshold: Activate for greater breakout confidence.
Breakout/Breakdown strength: Set how far price must close beyond the box to signal power.
Maximum boxes: Control the number of active boxes to keep the chart clear.
How to Add and Use
Add to Chart:
Click the “Add to Favorite Scripts” star to mark this indicator.
Open your desired intraday chart (1m–30m works best).
Click “Indicators,” search for “Advanced Intraday Darvas Box,” and add to your chart.
Customize Inputs:
Use the settings gear ⚙️ to adjust pivot sensitivity, trend logic, box filtering, and volume confirmation.
Lower minimum box height or pivot length for more frequent signals. Raise them for sparser, higher conviction setups.
Reading Darvas Boxes:
Box Edges: Horizontal lines mark resistance (top) and support (bottom) of detected zones.
Shaded regions: Highlight the most relevant trading zones and where price could coil before breakout.
Breakout labels (↑/↓): These appear only when price makes a powerful, confirmed move beyond the box edge—aligned with trend.
Alerts: Turn on chart alerts using the “Strong Bullish Breakout” or “Strong Bearish Breakdown” alert conditions for automated signal monitoring.
Best Practices:
Use Darvas boxes to complement price action analysis. Combine with candlestick patterns, volume spikes, and other price structure.
Only trade strong breakout signals confirmed by volume and market direction.
Avoid excessive boxes—adjust "Max Boxes" and filters for your instrument and timeframe.
Important
This indicator is non-repainting and built for display clarity and clean signals.
No brokerage automation, no external linking, and pure price/volume logic—fully compliant with TradingView House Rules.
Always test settings and confirmations before using for live decision-making.
كلاستر
Detailed Description – Fibonacci Cluster Zones + OB + FVG (AR34)
This script is an advanced multi-layer confluence system developed under the AR34 Trading Framework, designed to identify high-accuracy reversal zones, liquidity imbalances, institutional footprints, and trend direction using a unified analytic engine.
It combines Fibonacci mathematics, Smart Money Concepts, market structure, and smart trend signals to produce precise, reliable trading zones.
⸻
🔶 1 — Fibonacci Retracement Zones + Custom Smart Levels
The script calculates the highest and lowest prices over a selected lookback period to generate key Fibonacci retracement levels:
• 0.236
• 0.382
• 0.500
• 0.618
• 0.786
• 1.000
You can also add up to three custom Fibonacci levels (0.66, 0.707, 0.88 or any value you want).
✔ Each level is drawn as a horizontal line
✔ Optional label display for every level
✔ Color and activation fully customizable
These levels help identify pullback zones and potential turning points.
⸻
🔶 2 — True Fibonacci Cluster Detection
The script automatically identifies Cluster Zones, which occur when:
1. A Fibonacci level
2. An Order Block
3. A Fair Value Gap
all overlap in the same price range.
When all three conditions align, the script prints a CLUSTER marker in yellow.
These zones represent:
• High-probability reversal areas
• Strong institutional footprints
• Highly reactive price levels
⸻
🔶 3 — Automatic Order Block (OB) Detection
The indicator detects Order Blocks based on structural candle behavior:
• Bearish candle → followed by bullish
• Price interacts with a Fibonacci level
• Area aligns with institutional order flow
When detected, the OB is marked for easy visualization.
⸻
🔶 4 — Fair Value Gap (FVG) Mapping
The script scans for liquidity imbalances using the classic FVG logic:
• low > high
When an FVG exists, it draws a green liquidity box.
This highlights:
• Gaps left by institutional moves
• High-value return zones
• Efficient price retracement levels
⸻
🔶 5 — Fibonacci Extension Projections
The script calculates extension targets using:
• 1.272
• 1.618
• 2.000
These are drawn as dashed teal lines and help forecast:
• Breakout continuation targets
• Wave extension objectives
• Take-profit areas
⸻
🔶 6 — Smart Trend Signal (EMA-200 Engine)
Trend direction is determined using the EMA 200:
• Price above EMA → uptrend
• Price below EMA → downtrend
A green or red signal icon appears only when the trend flips, reducing noise and improving clarity.
This helps detect:
• Trend shifts early
• Cleaner entries and exits
• Trend-based filtering
⸻
🔶 7 — Four-EMA Multi-Trend System
The indicator includes optional visualization of four moving averages:
• EMA 20 → Short-term
• EMA 50 → Medium-term
• EMA 100 → Long-term
• EMA 200 → Major trend
All are fully customizable (length + color + visibility).
⸻
🔶 8 — Dynamic Negative Fibonacci Levels (Green Only)
When enabled, the script calculates deep retracement zones using:
• –0.23
• –0.75
• –1.20
These negative Fibonacci levels are drawn in green and help identify:
• Deep liquidity capture points
• Hidden structural supports
• Potential reversal bottoms
⸻
🔶 9 — Complete User Control
Users maintain full control over:
✔ Enabling/disabling OB detection
✔ Enabling/disabling FVG detection
✔ Activating custom Fibonacci levels
✔ Showing or hiding labels
✔ Selecting timeframe for Fib calculations
✔ Adjusting moving average parameters
✔ Activating dynamic Fibonacci
The script is designed to be flexible, scalable, and suitable for any trading style.
⸻
🎯 Summary
This indicator is a powerful all-in-one analytical system that merges:
✔ Fibonacci Mathematics
✔ Smart Money Concepts (OB + FVG)
✔ Trend-based filtering
✔ Institutional cluster detection
✔ Dynamic extensions + retracements
✔ Multi-EMA trend mapping
شرح السكربت بالتفصيل – Fibonacci Cluster Zones + OB + FVG (AR34)
هذا السكربت هو نظام تحليل احترافي متكامل من تطوير AR34 Framework يجمع بين أقوى أدوات التداول الحديثة في مؤشر واحد، ويهدف إلى كشف مناطق الانعكاس القوية، والتجميع الذكي، والاتجاه العام، باستخدام مزيج علمي من فيبوناتشي + السيولة + الاتجاه.
يعمل هذا المؤشر بأسلوب Confluence Trading بحيث يدمج عدة مدارس مختلفة في طبقة واحدة لتحديد مناطق الانعكاس والارتداد والاختراق بدقة عالية.
⸻
🔶 1 — مناطق فيبوناتشي (Retracement) + الكلاستر الذكي
يقوم المؤشر بحساب أعلى وأدنى سعر خلال عدد محدد من الشموع (Retracement Length) ثم يرسم مستويات فيبوناتشي الكلاسيكية:
• 0.236
• 0.382
• 0.500
• 0.618
• 0.786
• 1.000
مع إمكانية إضافة 3 مستويات خاصة من اختيارك (0.66 – 0.707 – 0.88 وغيرها).
✔️ كل مستوى يتم رسمه بخط مستقل
✔️ يظهر بجانبه رقم المستوى إذا تم تفعيل خيار Show Fib Labels
✔️ يمكن تغيير لونه، قيمته، وتفعيله حسب رغبتك
⸻
🔶 2 — كاشف الكلاستر الحقيقي (Cluster Detection)
الكلاستر يُعتبر أقوى مناطق الارتداد في التحليل الفني.
السكربت يحدد الكلاستر عندما تتداخل 3 عناصر مع مستوى فيبوناتشي:
1. مستوى فيبوناتشي مهم
2. Order Block
3. Fair Value Gap
إذا اجتمعت الثلاثة في نفس المنطقة، يتم رسمها باللون الأصفر وتظهر كلمة CLUSTER.
هذا يعطيك:
• أقوى منطقة انعكاس
• أعلى دقة في تحديد نقاط الدخول
• مناطق ذات سيولة مرتفعة
⸻
🔶 3 — دمج Order Blocks تلقائياً
يكتشف المؤشر الـ OB الحقيقي باستخدام شروط حركة الشموع:
• bearish candle → bullish candle
• السعر لمس مستوى فيبوناتشي
• منطقة محتملة لتجميع المؤسسات
إذا تحققت الشروط يظهر OB باللون الأحمر.
⸻
🔶 4 — دمج Fair Value Gaps (FVG)
يكتشف الفجوات السعرية بين الشمعتين الأولى والثالثة:
• low > high
ويقوم برسم بوكس أخضر حول الفجوة (FVG Zone).
يساعدك على معرفة:
• مناطق اختلال السيولة
• أهداف السعر القادمة
• مناطق “العودة” المحتملة
⸻
🔶 5 — امتدادات فيبوناتشي (Fibonacci Extensions)
يقوم بحساب الامتدادات من مستويات:
• 1.272
• 1.618
• 2.0
ويظهرها بخطوط متقطعة (Teal Color).
هذه المستويات مهمة لتوقع:
• أهداف اختراق
• مناطق TP
• امتداد موجات السعر
⸻
🔶 6 — إشارة الاتجاه الذكية (Smart Trend Engine – EMA200)
يعتمد على EMA 200 لتحديد الاتجاه العام:
• إذا السعر فوق EMA200 → اتجاه صاعد
• إذا السعر تحت EMA200 → اتجاه هابط
ويظهر المؤشر:
🟢 سهم أخضر عند تحول الاتجاه لصعود
🔴 سهم أحمر عند تحول الاتجاه لهبوط
ميزة التحول فقط عند تغيير الاتجاه (No Noise).
⸻
🔶 7 — أربع موفنقات احترافية (EMA 20 – 50 – 100 – 200)
المؤشر يعرض الموفنقات الأربعة الأساسية:
• EMA 20 → اتجاه قصير
• EMA 50 → متوسط
• EMA 100 → طويل
• EMA 200 → الاتجاه الرئيسي
مع إمكانية:
• تغيير اللون
• تغيير الطول
• إخفائها وإظهارها
⸻
🔶 8 — فيبوناتشي الديناميكي (Dynamic Green Fib)
ميزة قوية جداً تظهر فقط عند تفعيلها.
تحسب أعلى وأدنى سعر في Lookback Period ثم ترسم مستويات سلبية:
• –0.23
• –0.75
• –1.20
هذه المستويات تظهر كخطوط خضراء تحت السعر وتستخدم لـ:
• تحديد مناطق الانعكاس المخفية
• رصد الدعم الديناميكي
• اكتشاف القيعان المحتملة
⸻
🔶 9 — المرونة الكاملة للمستخدم
المؤشر يسمح لك التحكم بكل شيء:
✔️ تفعيل/إلغاء الـ OB
✔️ تفعيل/إلغاء الـ FVG
✔️ تفعيل/إلغاء مستويات فيبوناتشي
✔️ إضافة مستويات مخصصة
✔️ اختيار الفريم المستخدم
✔️ تغيير الألوان
✔️ التحكم في الاتجاه والموفنقات
⸻
🎯 الخلاصة
هذا السكربت يعمل كنظام تحليلي متكامل يجمع:
✔️ فيبوناتشي
✔️ السيولة المؤسسية (OB + FVG)
✔️ الاتجاه الذكي
✔️ الكلاستر الاحترافي
✔️ الموفنقات
✔️ فيبوناتشي الديناميكي
DCA Bot v7 - Cryptosa Nostra 1.0Technical Overview: Adaptive RSI DCA Bot
This is a sophisticated DCA (Dollar Cost Averaging) indicator designed for accumulating assets and managing portfolio distribution. It does not trade on simple RSI crosses. Instead, it combines multi-zone RSI analysis with ATR-based volatility triggers to execute staggered, dynamically-sized trades.
Its core feature is a "learning" engine that adapts its own settings over time. This "brain" can be trained on historical data and then applied to your real-time portfolio holdings via a "Live Override" feature.
Core Logic: How It Works
A trade is only executed when two conditions are met simultaneously:
The RSI Condition: The RSI must be inside one of the four pre-defined zones.
The Price Condition: The price must cross a "trigger line" (the green or red line) that is dynamically calculated based on volatility.
1. The Four RSI Zones
This script uses four distinct zones to determine the intent to trade:
Deep Buy Zone (Default: RSI <= 35 & Downtrend): This is the primary "value" buy signal. It only activates if the RSI is deeply oversold and the price is below the 200-period Trend MA.
Reload Buy Zone (Default: RSI 40-50 & Uptrend): This is a "buy the dip" signal. It looks for minor pullbacks during an established uptrend (price above the 200-period Trend MA).
Profit-Taking Zone (Default: RSI 70-80): Triggers a standard, small sell when the market is overbought.
Euphoria Zone (Default: RSI >= 80): Triggers a larger, more aggressive sell during extreme "blow-off" tops.
2. Dynamic Trade Sizing
The amount to buy or sell is not fixed. It scales dynamically based on how high or low the RSI is:
Buy Sizing: Spends a higher percentage of available cash when RSI is at its lowest (e.g., 35) and a smaller percentage when it's at the top of the reload zone (e.g., 50).
Sell Sizing: Sells a smaller percentage of holdings when RSI just enters the overbought zone (e.g., 70) and a much larger percentage when it's in the euphoria zone (e.g., 80+).
3. The "Adaptive Brain" (ATR Multipliers)
This is the script's learning mechanism. The green/red trigger lines are calculated as: Last Trade Price +/- (ATR * Multiplier).
This "Multiplier" is the brain. It adapts based on trade performance.
After a successful trade (as defined by profit_target_multiplier), the bot gets more confident and reduces the multiplier. This places the next trigger line closer to the price, making it more aggressive.
After a losing trade (as defined by loss_limit_multiplier), the bot gets more cautious and increases the multiplier. This places the next trigger line further away, making it more patient.
How to Use This Indicator
This script is designed to be "trained" on historical data to provide relevant signals for today.
To Train the Brain: In the settings, go to "1. Backtest Settings". Set the "Start Date (For Learning)" to a date in the past (e.g., 6 months or 1 year ago). The script will run a simulation from that date, allowing its Adaptive Multipliers (the "brain") to adjust to the market's volatility.
To See Live Signals: In "2. Live Portfolio Override", check the box "Override Backtest Balance?" and enter your real current coin and USD holdings.
Result: The "Live Status" table (top-right) will now display signals from the trained brain but will calculate the "Potential Buy %" and "Potential Sell %" based on your real portfolio. The "Buy Multi" and "Sell Multi" fields show you the brain's current learned values.
SMC Lite + PVSRA + MA Combo HELL 1great trading tool what you see is what you get supply and resistance pvsra candles
ATR Trend + RSI Pullback Strategy [Profit-Focused]This strategy is designed to catch high-probability pullbacks during strong trends using a combination of ATR-based volatility filters, RSI exhaustion levels, and a trend-following entry model.
Strategy Logic
Rather than relying on lagging crossovers, this model waits for RSI to dip into oversold zones (below 40) while price remains above a long-term EMA (default: 200). This setup captures pullbacks in strong uptrends, allowing traders to enter early in a move while controlling risk dynamically.
To avoid entries during low-volatility conditions or sideways price action, it applies a minimum ATR filter. The ATR also defines both the stop-loss and take-profit levels, allowing the model to adapt to changing market conditions.
Exit logic includes:
A take-profit at 3× the ATR distance
A stop-loss at 1.5× the ATR distance
An optional early exit if RSI crosses above 70, signaling overbought conditions
Technical Details
Trend Filter: 200 EMA – must be rising and price must be above it
Entry Signal: RSI dips below 40 during an uptrend
Volatility Filter: ATR must be above a user-defined minimum threshold
Stop-Loss: 1.5× ATR below entry price
Take-Profit: 3.0× ATR above entry price
Exit on Overbought: RSI > 70 (optional early exit)
Backtest Settings
Initial Capital: $10,000
Position Sizing: 5% of equity per trade
Slippage: 1 tick
Commission: 0.075% per trade
Trade Direction: Long only
Timeframes Tested: 15m, 1H, and 30m on trending assets like BTCUSD, NAS100, ETHUSD
This model is tuned for positive P&L across trending environments and volatile markets.
Educational Use Only
This strategy is for educational purposes only and should not be considered financial advice. Past performance does not guarantee future results. Always validate performance on multiple markets and timeframes before using it in live trading.
Bitcoin AHR999 Indicator
AHR999 Indicator
The AHR999 Indicator is created by a Weibo user named ahr999. It assists Bitcoin investors in making investment decisions based on a timing strategy. This indicator implies the short-term returns of Bitcoin accumulation and the deviation of Bitcoin price from its expected valuation.
When the AHR999 index is < 0.45 , it indicates a buying opportunity at a low price.
When the AHR999 index is between 0.45 and 1.2 , it is suitable for regular investment.
When the AHR999 index is > 1.2 , it suggests that the coin price is relatively high and not suitable for trading.
In the long term, Bitcoin price exhibits a positive correlation with block height. By utilizing the advantage of regular investment, users can control their short-term investment costs, keeping them mostly below the Bitcoin price.
Average Price BUY-SELL_Bulent-V2Tracking prices that you have defined and trigger the crossing of them
Smoothed VWAP Bands + EMAsSmoothed VWAP bands
With my script, you take the raw standard deviation and apply an EMA (exponential moving
Advantages:
1. Less noise:
* The bands don’t jump around with every tiny price spike.
* Makes it easier to judge real price extremes.
2. Better zone visualization:
* Inner and outer bands are smoother and more visually “stable.”
* Easier to see meaningful trends, support/resistance, and breakout zones.
3. Fewer fakeouts:
* Traders can filter out small false signals because smoothed bands only move when volatility actually changes.
4. Dynamic to volatility:
* EMA smoothing keeps the bands adaptive:
* In quiet periods, bands tighten.
* In volatile periods, bands expand.
* But it avoids extreme jitter caused by every micro-move.
Safe Zone Rules
1. Long entries (green zone):
* Price above VWAP (trend bullish).
* Price inside inner band ±1σ (not touching outer extremes).
* Optional: candle close confirmation (price fully above inner band).
2. Short entries (red zone):
* Price below VWAP (trend bearish).
* Price inside inner band ±1σ.
* Optional: candle close confirmation.
3. Outer bands (±2σ):
* Considered overextended zones → avoid entries to reduce fakeouts.
4. Visual cues:
* Safe zones shaded lightly green/red inside inner band.
* Outer bands remain unshaded (for context).
Here’s a cheat sheet for trading the Smoothed VWAP Bands + EMAs that shows safe entry zones and trend alignment clearly.
Smoothed VWAP Bands + EMAs Cheat Sheet
Price Action Relative to Bands & EMAs
+2σ (Outer Upper Band)
----------------
Extreme volatility zone
Avoid entries here
+1σ (Inner Upper Band)
----------------
Safe zone limit for longs
Consider profit taking here
VWAP Line (Green = Bullish, Red = Bearish)
==================
Core trend indicator
Only trade in VWAP trend direction
-1σ (Inner Lower Band)
----------------
Safe zone limit for shorts
Good for entries in trend direction
-2σ (Outer Lower Band)
----------------
Extreme volatility zone
Avoid entries here
1️⃣ Trend Direction with VWAP & EMAs
* VWAP → shows the overall session trend.
* Price above VWAP → bullish
* Price below VWAP → bearish
* EMA 5 (blue) → short-term momentum
* EMA 20 (orange) → medium-term trend
Rule: Only take trades in the direction of the trend:
* Long trades → price > VWAP and EMA 5 > EMA 20
* Short trades → price < VWAP and EMA 5 < EMA 20
This prevents chasing trades against the trend and reduces fakeouts.
2️⃣ Entry Zones Using Smoothed VWAP Bands
* Inner band (±1σ) → “safe entry zone”
* Outer band (±2σ) → volatility extremes → avoid entries here
Rule: Enter longs inside the inner band above VWAP and shorts inside the inner band below VWAP.
Best used on intraday timeframes.
15, 5, 2, 1 min charts.
Normalised Volume Oscillator [BackQuant]Normalised Volume Oscillator
A refined evolution of the Klinger Volume Oscillator, rebuilt for clarity, precision, and adaptability. This tool normalizes volume-driven momentum into a bounded scale so you can easily identify shifts in accumulation and distribution across any asset or timeframe, while keeping readings comparable between markets.
What this indicator does
The Normalised Volume Oscillator quantifies the balance between buying and selling pressure using the Klinger Volume Oscillator (KVO) as its base, then rescales it dynamically into a normalized range between -0.5 and +0.5. This normalization allows traders to interpret relative strength and exhaustion in volume flow, rather than dealing with raw unbounded values that differ across symbols.
It is a momentum-volume hybrid that reveals the strength of trend participation: when buyers dominate, normalized readings rise toward +0.5; when sellers dominate, they fall toward -0.5. The midline (0) acts as an equilibrium between accumulation and distribution.
Core components
Klinger Volume Oscillator: The foundation of this indicator, combining volume with price trend direction to measure long-term money flow relative to short-term movement.
Normalization process: The raw KVO is scaled over a user-defined Normalisation Period , computing `(KVO - lowest) / (highest - lowest) - 0.5`. This centers all readings around zero, allowing overbought/oversold detection independent of asset volatility or volume magnitude.
Signal moving average: The normalized KVO is smoothed with a user-selectable moving average type—SMA, EMA, DEMA, TEMA, HMA, ALMA, and others. This becomes the signal line for confirmation of trend direction or mean-reversion setups.
How it works conceptually
1. The KVO detects when volume supports price movement (bullish) or diverges from it (bearish).
2. The script normalizes the raw KVO so that relative magnitude is consistent—what is “strong buying pressure” looks the same on BTCUSD as it does on AAPL.
3. Overbought and oversold regions are derived statistically, rather than from arbitrary values, based on percentile zones around ±0.4 and ±0.5.
4. The oscillator is optionally combined with a moving average to help identify crossovers, momentum shifts, and divergence confirmation.
How to interpret it
Above 0: Indicates dominant buying pressure and likely continuation of upward momentum.
Below 0: Suggests dominant selling pressure and potential continuation of downward movement.
Crosses of 0: Often mark transitions between accumulation and distribution phases.
+0.4 to +0.5 zone: Overbought region where buying intensity is stretched; watch for deceleration or divergence.
[-0.4 to -0.5 zone: Oversold region indicating panic or exhaustion in selling.
Signal-line crossover: A traditional momentum confirmation method; when the normalized KVO crosses above its moving average, buyers regain control, and vice versa.
Why normalization matters
Typical volume oscillators are asset-specific—what is considered “high” volume for one symbol is not the same for another. By dynamically normalizing KVO values within a rolling lookback, this version transforms raw amplitude into a standardized scale. This means you can:
Compare multiple assets objectively.
Set consistent alert thresholds for overbought/oversold regions.
Avoid misleading interpretations from absolute oscillator values.
Customization and UI
Moving Average Type & Period: Select your preferred smoothing method (SMA, EMA, TEMA, etc.) and adjust its period to tune sensitivity.
Normalisation Period: Defines how many bars the KVO range is measured over; shorter periods adapt faster, longer ones smooth more.
Visual Toggles:
* Show Oscillator : enables or hides the core histogram.
* Show Moving Average : adds a smoothed overlay for signal confirmation.
* Paint Candles : optional color overlay for chart candles based on oscillator direction.
* Show Static Levels : displays ±0.4 and ±0.5 zones for overbought/oversold boundaries.
How to use it
Trend confirmation: Use midline (0) crossovers as confirmation of emerging trend shifts—cross above 0 suggests a new bullish phase, cross below 0 a bearish one.
Reversal spotting: Look for normalized readings reaching ±0.5 and flattening, or diverging against price extremes.
Divergence analysis: When price makes a new high but the normalized oscillator fails to, it signals waning buying conviction (and vice versa for lows).
Multi-timeframe integration: Works best alongside higher timeframe trend filters or moving averages; normalization makes this consistent.
Alerts
Prebuilt alert conditions allow quick automation:
Midline crossovers (0): transition between accumulation and distribution.
Overbought (+0.4) and Oversold (-0.4) triggers for potential exhaustion.
Signal moving-average crosses for confirmation entries.
Tips for use
Combine with price structure—don’t fade every overbought/oversold reading; confirm with break of structure or candle patterns.
Use longer normalization periods for position trading, shorter for intraday analysis.
In choppy markets, treat 0-line oscillations as noise filters, not trade triggers.
Summary
The Normalised Volume Oscillator modernizes the classic Klinger Volume Oscillator by normalizing its readings into a standardized range. This makes it more adaptive across assets and timeframes, improves interpretability, and provides intuitive, data-driven overbought/oversold levels. Whether used standalone or as a confirmation layer, it offers a clearer view of volume dynamics—revealing when markets are truly being accumulated, distributed, or stretched beyond their sustainable extremes.
