Sniper Strategy [Short Only]//@version=6
strategy("Sniper Strategy ", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=10, currency=currency.NONE)
// --- 参数设置 ---
atrPeriod = input.int(10, "ATR")
factor = input.float(3.0, "Factor")
sl_buffer = input.float(0.0, "SL Buffer", tooltip="在Supertrend上方增加一点缓冲")
// --- 核心计算 ---
= ta.supertrend(factor, atrPeriod)
// direction > 0 代表空头(红), < 0 代表多头(绿)
short_signal = ta.change(direction) > 0
exit_signal = ta.change(direction) < 0
// --- 变量记录 ---
var float entry_price = na
var float sl_price = na
var float tp_price = na
var bool tp_hit = false
// --- 1. 进场逻辑 (Entry) ---
if short_signal
// 做空止损放在 Supertrend 价格上方
float initial_sl = supertrend + sl_buffer
entry_price := close
sl_price := initial_sl
// 计算风险值 (价格差)
float risk_val = sl_price - entry_price
// 1R 止盈目标 (做空是向下减)
tp_price := entry_price - risk_val
tp_hit := false
strategy.entry("S", strategy.short)
// 标签：显示具体止损价格 + 亏损百分比
float risk_pct = (risk_val / entry_price) * 100
label_txt = "SL: " + str.tostring(sl_price, "#.##") + "\nRisk: " + str.tostring(risk_pct, "#.2") + "%"
// 做空标签显示在K线上方
label.new(bar_index, high, text=label_txt, style=label.style_label_down, color=color.new(color.red, 40), textcolor=color.white, size=size.small)
// --- 2. 持仓管理 (Management) ---
if strategy.position_size < 0
// 1R 目标达成：平仓 50%
strategy.exit("1R", "S", stop=sl_price, qty_percent=50, limit=tp_price)
// 剩余仓位止损
strategy.exit("End", "S", stop=sl_price)
// 1R 视觉提示 (只提示一次)
if not tp_hit and low <= tp_price
tp_hit := true
label.new(bar_index, low, text="1R 💰", style=label.style_label_up, color=color.new(color.yellow, 20), textcolor=color.black, size=size.small)
// --- 3. 趋势反转离场 (Exit) ---
if exit_signal
strategy.close_all()
entry_price := na
sl_price := na
tp_price := na
Wyszukaj w skryptach "马斯克+100万"
SwiftTrend█ OVERVIEW
SwiftTrend is a trend-following indicator inspired by the classic SuperTrend, but built on a completely different calculation method — using the average candle body size and the body midpoint (bodyMid). It reacts very dynamically to changes in momentum strength. The indicator is clean, easy to read, and perfect for traders who want fast yet confirmed trend direction. By adjusting the settings, you can make signals extremely sensitive or, conversely, reduce their frequency to almost completely eliminate trend flips on minor price moves.
█ CONCEPT
The indicator was created to strike the perfect balance between signal speed and effective noise filtering.
Instead of using classic ATR and price extremes (high/low), SwiftTrend uses the average candle body size and the midpoint of the previous candle’s body as its core reference. The dynamic trend line (avgLine) is protected by a tolerance zone – the trend only changes after price closes beyond this zone. This approach delivers significantly faster reaction times than many traditional solutions while maintaining excellent resistance to false signals during ranging markets.
█ FEATURES
Data source:
- Average candle body size: SMA(|open – close|, period)
- Reference point: midpoint of the previous candle’s body (bodyMid )
Dynamic trend line (avgLine):
- Built using Band Multiplier
- The line is “attracted” toward price movement
Tolerance zone (margin):
- Tolerance = Tolerance Multiplier × avgBody
- Default: 2.5 (for both band and tolerance)
Trend change logic:
- Down → Up: close > avgLine + tolerance
- Up → Down: close < avgLine – tolerance
Visual signals:
- “Buy” label (green upward arrow) and “Sell” label (red downward arrow) only on confirmed trend change
- Optional soft gradient fill between trend line and price
- Optional bar coloring based on current trend
- Trend line with breaks at reversal points
Alerts:
- Buy alert – triggers only when the closing price crosses from below to above the marginLineBase
- Sell alert – triggers only when the closing price crosses from above to below the marginLineBase
█ HOW TO USE
Add to chart → paste the code in Pine Editor or search for “SwiftTrend”.
Main settings:
- Average Body Periods → default 100
- Band Multiplier → default 2.5
- Tolerance Multiplier → default 2.5 (key sensitivity parameter)
- Colors, fill, and bar coloring – fully customizable
Interpretation:
- Green line & shading = uptrend
- Red line & shading = downtrend
- Higher Tolerance Multiplier = fewer but higher-quality signals
- Tolerance Multiplier near 0 = ultra-fast signals (aggressive mode)
█ APPLICATIONS
Excellent for:
- Trend-following (enter with trend, exit on reversal)
- Breakout and momentum strategies
- Filtering consolidation and noise – thanks to the adjustable tolerance zone
Best combined with:
- Classic support/resistance levels
- Fibonacci retracements, Pivot Points, psychological round numbers
- Confirmation from oscillators (RSI, Stochastic, MACD)
- Volume or volume profile analysis
Style adaptation:
- Scalping / daytrading → lower Tolerance Multiplier (0.8–1.8) + shorter period
- Swing / position trading → higher values (2.5–5.0) + longer period
█ NOTES
- Works on all markets and timeframes
- Success depends on matching the Tolerance Multiplier to your strategy and the instrument’s volatility
- Higher multiplier & period values = fewer signals, significantly higher quality
- At Tolerance Multiplier = 0 the indicator becomes extremely responsive – perfect for aggressive momentum trading
Smart RSI Money Flow - Core Bands V1.01SMART RSI – Money Flow Bands (Technical Overview)
1. Background: RSI and Its Behavior on Lower Timeframes
The Relative Strength Index (RSI) originally is a momentum oscillator calculated from average gains and losses over a selected period. In its standard form, RSI is derived solely from price changes; it does not incorporate volume data or order-flow information in its formula.
Because RSI is price-based, its interpretation depends strongly on the timeframe:
• On higher timeframes, each bar aggregates more trading activity, and RSI tends to behave more smoothly.
• On lower timeframes (1-hour down to intraday scalping intervals), price fluctuations are quicker, and RSI becomes more sensitive to short-term noise.
This does not imply that RSI becomes invalid, but that its signals on fast charts can be more reactive and may benefit from additional context such as volume behavior or structural information.
2. Purpose of This Indicator
This indicator extends the classical RSI by adding information that RSI does not include:
• Mapping RSI values into price-based bands instead of the 0–100 oscillator space.
• Retrieving lower timeframe volume data and separating it into buy and sell components.
• Comparing the slope (angle) of price movement with the slope of buy and sell volume.
The goal is to provide a structural interpretation of where price sits relative to RSI conditions and how volume is behaving on a lower timeframe.
3. Technical Differences Compared to Classical RSI
A) Classical RSI
• Input: price only (usually close).
• Output: normalized oscillator between 0 and 100.
• Does not incorporate intra-bar volume distribution.
• Does not separate buy/sell volume.
B) SMART RSI – Money Flow Bands
1) RSI-to-Price Mapping
Converts RSI values into upper/lower price bands using recent price extremes.
2) Lower Timeframe Volume Decomposition
Retrieves LTF data and splits each bar’s volume into buy (close>open) and sell (close
Smart Money Dynamics Blocks - Pearson MatrixSmart Money Dynamics Blocks — Pearson Matrix
A structural fusion of Prime Number Theory, Pearson Correlation, and Cumulative Delta Geometry.
1. Mathematical Foundation
This indicator is built on the intersection of Prime Number Theory and the Pearson correlation coefficient, creating a structural framework that quantifies how price and time evolve together.
Prime numbers — unique, indivisible, and irregular — are used here as nonlinear time intervals. Each prime length (2, 3, 5, 7, 11…97) represents a regression horizon where correlation is measured between price and time. The result is a multi-scale correlation lattice — a geometric matrix that captures hidden directional strength and temporal bias beyond traditional moving averages.
2. The Pearson Matrix Logic
For every prime interval p, the indicator calculates the linear correlation:
r_p = corr(price, bar_index, p)
Each r_p reflects how closely price and time move together across a prime-defined window. All r_p values are then averaged to create avgR, a single adaptive coefficient summarizing overall structural coherence.
- When avgR > 0.8 → strong positive correlation (labeled R+).
- When avgR < -0.8 → strong negative correlation (labeled R−).
This approach gives a mathematically grounded definition of trend — one that isn’t based on pattern recognition, but on measurable correlation strength.
3. Sequential Prime Slope and Median Pivot
Using the ordered sequence of 25 prime intervals, the model computes sequential slopes between adjacent primes. These slopes represent the rate of change of structure between two prime scales. A robust median aggregator smooths the slopes, producing a clean, stable directional vector.
The system anchors this slope to the 41-bar pivot — the median of the first 25 primes — serving as the geometric midpoint of the prime lattice. The resulting yellow line on the chart is not an ordinary regression line; it’s a dynamic prime-slope function, adapting continuously with correlation feedback.
4. Regression-Style Parallel Bands
Around this prime-slope line, the indicator constructs parallel bands using standard deviation envelopes — conceptually similar to a regression channel but recalculated through the prime–Pearson matrix.
These bands adjust dynamically to:
- Volatility, via standard deviation of residuals.
- Correlation strength, via avgR sign weighting.
Together, they visualize statistical deviation geometry, making it easier to observe symmetry, expansion, and contraction phases of price structure.
5. Volume and Cumulative Delta Peaks
Below the geometric layer, the indicator incorporates a custom lower-timeframe volume feed — by default using 15-second data (custom_tf_input_volume = “15S”). This allows precise delta computation between up-volume and down-volume even on higher timeframe charts.
From this feed, the indicator accumulates delta over a configurable period (default: 100 bars). When cumulative delta reaches a local maximum or minimum, peak and trough markers appear, showing the precise bar where buying or selling pressure statistically peaked.
This combination of geometry and order flow reveals the intersection of market structure and energy — where liquidity pressure expresses itself through mathematical form.
6. Chart Interpretation
The primary chart view represents the live execution of the indicator. It displays the relationship between structural correlation and volume behavior in real time.
Orange “R+” and blue “R−” labels indicate regions of strong positive or negative Pearson correlation across the prime matrix. The yellow median prime-slope line serves as the structural backbone of the indicator, while green and red parallel bands act as dynamic regression boundaries derived from the underlying correlation strength. Peaks and troughs in cumulative delta — displayed as numerical annotations — mark statistically significant shifts in buying and selling pressure.
The secondary visualization (Prime Regression Concept) expands on this by illustrating how regression behavior evolves across prime intervals. Each colored regression fan corresponds to a prime number window (2, 3, 5, 7, …, 97), demonstrating how multiple regression lines would appear if drawn independently. The indicator integrates these into one unified geometric model — eliminating the need to plot tens of regression lines manually. It’s a conceptual tool to help visualize the internal logic: the synthesis of many small-scale regressions into a single coherent structure.
7. Interpretive Insight
This model is not a prediction tool; it’s an instrument of mathematical observation. By translating price dynamics into a prime-structured correlation space, it reveals how coherence unfolds through time — not as a forecast, but as a measurable evolution of structure.
It unifies three analytical domains:
- Prime distribution — defines a nonlinear temporal architecture.
- Pearson correlation — quantifies statistical cohesion.
- Cumulative delta — expresses behavioral imbalance in order flow.
The synthesis creates a geometric analysis of liquidity and time — where structure meets energy, and where the invisible rhythm of market flow becomes measurable.
8. Contribution & Feedback
Share your observations in the comments:
- The time gap and alternation between R+ and R− clusters.
- How different timeframes change delta sensitivity or reveal compression/expansion.
- Prime intervals/clusters that tend to sit near turning points or liquidity shifts.
- How avgR behaves across assets or regimes (trending, ranging, high-vol).
- Notable interactions with the parallel bands (touches, breaks, mean-revert).
Your field notes help others read the model more effectively and compare contexts.
Summary
- Primes define the structure.
- Pearson quantifies coherence.
- Slope median stabilizes geometry.
- Regression bands visualize deviation.
- Cumulative delta locates imbalance.
Together, they construct a framework where mathematics meets market behavior.
Cjack COT IndexHere's the updated description with the formula and additional context:
---
**Cjack COT Index - Commitment of Traders Positioning Indicator**
This indicator transforms raw Commitment of Traders (COT) data into normalized 0-100 index values, making it easy to identify extreme positioning across different trader categories.
**How It Works:**
The indicator calculates a min-max normalized index for three trader groups over your chosen lookback period (default 26 weeks):
- **Large Speculators** (Non-commercial positions) - typically trend followers
- **Small Speculators** (Non-reportable positions) - retail traders
- **Commercial Hedgers** - producers and consumers hedging business risk
The normalization formula is: **Index = (Current Position - Minimum Position) / (Maximum Position - Minimum Position) × 100**
This calculation shows where current net positioning sits between the minimum and maximum levels observed in the lookback window. A reading of 100 means current positioning equals the maximum net long over that period, 0 equals the minimum (most net short), and 50 is the midpoint of the range.
**Important:** The lookback period critically affects index readings - shorter lookbacks (13-26 weeks) make the index more sensitive to recent extremes, while longer lookbacks (52-78 weeks) provide broader historical context and identify truly exceptional positioning. Min-max normalization is essential because it makes positioning comparable across different contracts and time periods, regardless of the absolute size of positions.
**What It's Good For:**
The indicator excels at identifying **crowded trades** and potential reversals by tracking contrarian setups where commercials (smart money) position opposite to speculators. Background highlighting automatically flags:
- **Long setups** (green): Commercials heavily long while speculators are heavily short
- **Short setups** (red): Commercials heavily short while speculators are heavily long
The "Shift Index" option (enabled by default) displays last week's tradeable COT data aligned with current price action, ensuring you're working with actionable information since COT reports publish with a delay.
Works on weekly timeframes and below for commodities and futures with available COT data.
Relative Performance Areas [LuxAlgo]The Relative Performance Areas tool enables traders to analyze the relative performance of any asset against a user-selected benchmark directly on the chart, session by session.
The tool features three display modes for rescaled benchmark prices, as well as a statistics panel providing relevant information about overperforming and underperforming streaks.
🔶 USAGE
Usage is straightforward. Each session is highlighted with an area displaying the asset price range. By default, a green background is displayed when the asset outperforms the benchmark for the session. A red background is displayed if the asset underperforms the benchmark.
The benchmark is displayed as a green or red line. An extended price area is displayed when the benchmark exceeds the asset price and is set to SPX by default, but traders can choose any ticker from the settings panel.
Using benchmarks to compare performance is a common practice in trading and investing. Using indexes such as the S&P 500 (SPX) or the NASDAQ 100 (NDX) to measure our portfolio's performance provides a clear indication of whether our returns are above or below the broad market.
As the previous chart shows, if we have a long position in the NASDAQ 100 and buy an ETF like QQQ, we can clearly see how this position performs against BTSUSD and GOLD in each session.
Over the last 15 sessions, the NASDAQ 100 outperformed the BTSUSD in eight sessions and the GOLD in six sessions. Conversely, it underperformed the BTCUSD in seven sessions and the GOLD in nine sessions.
🔹 Display Mode
The display mode options in the Settings panel determine how benchmark performance is calculated. There are three display modes for the benchmark:
Net Returns: Uses the raw net returns of the benchmark from the start of the session.
Rescaled Returns: Uses the benchmark net returns multiplied by the ratio of the benchmark net returns standard deviation to the asset net returns standard deviation.
Standardized Returns: Uses the z-score of the benchmark returns multiplied by the standard deviation of the asset returns.
Comparing net returns between an asset and a benchmark provides traders with a broad view of relative performance and is straightforward.
When traders want a better comparison, they can use rescaled returns. This option scales the benchmark performance using the asset's volatility, providing a fairer comparison.
Standardized returns are the most sophisticated approach. They calculate the z-score of the benchmark returns to determine how many standard deviations they are from the mean. Then, they scale that number using the asset volatility, which is measured by the asset returns standard deviation.
As the chart above shows, different display modes produce different results. All of these methods are useful for making comparisons and accounting for different factors.
🔹 Dashboard
The statistics dashboard is a great addition that allows traders to gain a deep understanding of the relationship between assets and benchmarks.
First, we have raw data on overperforming and underperforming sessions. This shows how many sessions the asset performance at the end of the session was above or below the benchmark.
Next, we have the streaks statistics. We define a streak as two or more consecutive sessions where the asset overperformed or underperformed the benchmark.
Here, we have the number of winning and losing streaks (winning means overperforming and losing means underperforming), the median duration of each streak in sessions, the mode (the number of sessions that occurs most frequently), and the percentages of streaks with durations equal to or greater than three, four, five, and six sessions.
As the image shows, these statistics are useful for traders to better understand the relative behavior of different assets.
🔶 SETTINGS
Benchmark: Benchmark for comparison
Display Mode: Choose how to display the benchmark; Net Returns: Uses the raw net returns of the benchmark. Rescaled Returns: Uses the benchmark net returns multiplied by the ratio of the benchmark and asset standard deviations. Standardized Returns: Uses the benchmark z-score multiplied by the asset standard deviation.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Position: Select the location of the dashboard.
Size: Select the dashboard size.
🔹 Style
Overperforming: Enable or disable displaying overperforming sessions and choose a color.
Underperforming: Enable or disable displaying underperforming sessions and choose a color.
Benchmark: Enable or disable displaying the benchmark and choose colors.
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
NormalizedIndicatorsNormalizedIndicators Library - Comprehensive Trend Normalization & Pre-Calibrated Systems
Overview
The NormalizedIndicators Library is an advanced Pine Script™ collection that provides normalized trend-following indicators, calculation functions, and pre-calibrated consensus systems for technical analysis. This library extends beyond simple indicator normalization by offering battle-tested, optimized parameter sets for specific assets and timeframes.
The main advantage lies in its dual functionality:
Individual normalized indicators with standardized outputs (1 = bullish, -1 = bearish, 0 = neutral)
Pre-calibrated consensus functions that combine multiple indicators with asset-specific optimizations
This enables traders to either build custom strategies using individual indicators or leverage pre-optimized systems designed for specific markets.
📊 Library Structure
The library is organized into three main sections:
1. Trend-Following Indicators
Individual indicators normalized to standard output format
2. Calculation Indicators
Statistical and mathematical analysis functions
3. Pre-Calibrated Systems ⭐ NEW
Asset-specific consensus configurations with optimized parameters
🔄 Trend-Following Indicators
Stationary Indicators
These oscillate around a fixed value and are not bound to price.
TSI() - True Strength Index ⭐ NEW
Source: TradingView
Parameters:
price: Price source
long: Long smoothing period
short: Short smoothing period
signal: Signal line period
Logic: Double-smoothed momentum oscillator comparing TSI to its signal line
Signal:
1 (bullish): TSI ≥ TSI EMA
0 (bearish): TSI < TSI EMA
Use Case: Momentum confirmation with trend direction
SMI() - Stochastic Momentum Index ⭐ NEW
Source: TradingView
Parameters:
src: Price source
lengthK: Stochastic period
lengthD: Smoothing period
lengthEMA: Signal line period
Logic: Enhanced stochastic that measures price position relative to midpoint of high/low range
Signal:
1 (bullish): SMI ≥ SMI EMA
0 (bearish): SMI < SMI EMA
Use Case: Overbought/oversold with momentum direction
BBPct() - Bollinger Bands Percent
Source: Algoalpha X Sushiboi77
Parameters:
Length: Period for Bollinger Bands
Factor: Standard deviation multiplier
Source: Price source (typical: close)
Logic: Calculates the position of price within the Bollinger Bands as a percentage
Signal:
1 (bullish): when positionBetweenBands > 50
-1 (bearish): when positionBetweenBands ≤ 50
Special Feature: Uses an array to store historical standard deviations for additional analysis
RSI() - Relative Strength Index
Source: TradingView
Parameters:
len: RSI period
src: Price source
smaLen: Smoothing period for RSI
Logic: Classic RSI with additional SMA smoothing
Signal:
1 (bullish): RSI-SMA > 50
-1 (bearish): RSI-SMA < 50
0 (neutral): RSI-SMA = 50
Non-Stationary Indicators
These follow price movement and have no fixed boundaries.
NorosTrendRibbonSMA() & NorosTrendRibbonEMA()
Source: ROBO_Trading
Parameters:
Length: Moving average and channel period
Source: Price source
Logic: Creates a price channel based on the highest/lowest MA value over a specified period
Signal:
1 (bullish): Price breaks above upper band
-1 (bearish): Price breaks below lower band
0 (neutral): Price within channel (maintains last state)
Difference: SMA version uses simple moving averages, EMA version uses exponential
TrendBands()
Source: starlord_xrp
Parameters: src (price source)
Logic: Uses 12 EMAs (9-30 period) and checks if all are rising or falling simultaneously
Signal:
1 (bullish): All 12 EMAs are rising
-1 (bearish): All 12 EMAs are falling
0 (neutral): Mixed signals
Special Feature: Very strict conditions - extremely strong trend filter
Vidya() - Variable Index Dynamic Average
Source: loxx
Parameters:
source: Price source
length: Main period
histLength: Historical period for volatility calculation
Logic: Adaptive moving average that adjusts to volatility
Signal:
1 (bullish): VIDYA is rising
-1 (bearish): VIDYA is falling
VZO() - Volume Zone Oscillator
Parameters:
source: Price source
length: Smoothing period
volumesource: Volume data source
Logic: Combines price and volume direction, calculates the ratio of directional volume to total volume
Signal:
1 (bullish): VZO > 14.9
-1 (bearish): VZO < -14.9
0 (neutral): VZO between -14.9 and 14.9
TrendContinuation()
Source: AlgoAlpha
Parameters:
malen: First HMA period
malen1: Second HMA period
theclose: Price source
Logic: Uses two Hull Moving Averages for trend assessment with neutrality detection
Signal:
1 (bullish): Uptrend without divergence
-1 (bearish): Downtrend without divergence
0 (neutral): Trend and longer MA diverge
LeonidasTrendFollowingSystem()
Source: LeonidasCrypto
Parameters:
src: Price source
shortlen: Short EMA period
keylen: Long EMA period
Logic: Simple dual EMA crossover system
Signal:
1 (bullish): Short EMA < Key EMA
-1 (bearish): Short EMA ≥ Key EMA
ysanturtrendfollower()
Source: ysantur
Parameters:
src: Price source
depth: Depth of Fibonacci weighting
smooth: Smoothing period
bias: Percentage bias adjustment
Logic: Complex system with Fibonacci-weighted moving averages and bias bands
Signal:
1 (bullish): Weighted MA > smoothed MA (with upward bias)
-1 (bearish): Weighted MA < smoothed MA (with downward bias)
0 (neutral): Within bias zone
TRAMA() - Trend Regularity Adaptive Moving Average
Source: LuxAlgo
Parameters:
src: Price source
length: Adaptation period
Logic: Adapts to trend regularity - accelerates in stable trends, slows in consolidations
Signal:
1 (bullish): Price > TRAMA
-1 (bearish): Price < TRAMA
0 (neutral): Price = TRAMA
HullSuite()
Source: InSilico
Parameters:
_length: Base period
src: Price source
_lengthMult: Length multiplier
Logic: Uses Hull Moving Average with lagged comparisons for trend determination
Signal:
1 (bullish): Current Hull > Hull 2 bars ago
-1 (bearish): Current Hull < Hull 2 bars ago
0 (neutral): No change
STC() - Schaff Trend Cycle
Source: shayankm (described as "Better MACD")
Parameters:
length: Cycle period
fastLength: Fast MACD period
slowLength: Slow MACD period
src: Price source
Logic: Combines MACD concepts with stochastic normalization for early trend signals
Signal:
1 (bullish): STC is rising
-1 (bearish): STC is falling
🧮 Calculation Indicators
These functions provide specialized mathematical calculations for advanced analysis.
LCorrelation() - Long-term Correlation
Creator: unicorpusstocks
Parameters:
Input: First time series
Compare: Second time series
Logic: Calculates the average of correlations across 6 different periods (30, 60, 90, 120, 150, 180)
Returns: Correlation value between -1 and 1
Application: Long-term relationship analysis between assets, markets, or indicators
MCorrelation() - Medium-term Correlation
Creator: unicorpusstocks
Parameters:
Input: First time series
Compare: Second time series
Logic: Calculates the average of correlations across 6 different periods (15, 30, 45, 60, 75, 90)
Returns: Correlation value between -1 and 1
Application: Medium-term relationship analysis with higher sensitivity
assetBeta() - Beta Coefficient
Creator: unicorpusstocks
Parameters:
measuredSymbol: The asset to be measured
baseSymbol: The reference asset (e.g., market index)
Logic:
Calculates Beta across 4 different time horizons (50, 100, 150, 200 periods)
Beta = Correlation × (Asset Standard Deviation / Market Standard Deviation)
Returns the average of all 4 Beta values
Returns: Beta value (typically 0-2, can be higher/lower)
Interpretation:
Beta = 1: Asset moves in sync with the market
Beta > 1: Asset more volatile than market
Beta < 1: Asset less volatile than market
Beta < 0: Asset moves inversely to the market
🎯 Pre-Calibrated Systems ⭐ NEW FEATURE
These are ready-to-use consensus functions with optimized parameters for specific assets and timeframes. Each calibration has been fine-tuned through extensive backtesting to provide optimal performance for its target market.
Universal Calibrations
virtual_4d_cal(src) - Virtual/General 4-Day Timeframe
Use Case: General purpose 4-day chart analysis
Optimized For: Broad crypto market on 4D timeframe
Indicators Used: BBPct, Noro's, RSI, VIDYA, HullSuite, TrendContinuation, Leonidas, TRAMA
Characteristics: Balanced sensitivity for swing trading
virtual_1d_cal(src) - Virtual/General 1-Day Timeframe
Use Case: General purpose daily chart analysis
Optimized For: Broad crypto market on 1D timeframe
Indicators Used: BBPct, Noro's, RSI, VIDYA, HullSuite, TrendContinuation, Leonidas, TRAMA
Characteristics: Standard daily trading parameters
Cryptocurrency Specific
sui_cal(src) - SUI Ecosystem Tokens
Use Case: Tokens in the SUI blockchain ecosystem
Timeframe: 1D
Characteristics: Fast-response parameters for high volatility projects
deep_1d_cal(src) - DEEP Token Daily
Use Case: Deepbook (DEEP) token analysis
Timeframe: 1D
Characteristics: Tuned for liquidity protocol token behavior
wal_1d_cal(src) - WAL Token Daily
Use Case: Specific for WAL token
Timeframe: 1D
Characteristics: Mid-range sensitivity parameters
sns_1d_cal(src) - SNS Token Daily
Use Case: Specific for SNS token
Timeframe: 1D
Characteristics: Balanced parameters for DeFi tokens
meme_cal(src) - Meme Coin Calibration
Use Case: Highly volatile meme coins
Timeframe: Various
Characteristics: Wider parameters to handle extreme volatility
Warning: Meme coins carry extreme risk
base_cal(src) - BASE Ecosystem Tokens
Use Case: Tokens on the BASE blockchain
Timeframe: Various
Characteristics: Optimized for L2 ecosystem tokens
Solana Ecosystem
sol_4d_cal(src) - Solana 4-Day
Use Case: SOL token on 4-day charts
Characteristics: Responsive parameters for major L1 blockchain
sol_meme_4d_cal(src) - Solana Meme Coins 4-Day
Use Case: Meme coins on Solana blockchain
Timeframe: 4D
Characteristics: Handles high volatility of Solana meme sector
Ethereum Ecosystem
eth_4d_cal(src) - Ethereum 4-Day
Use Case: ETH and major ERC-20 tokens
Timeframe: 4D
Indicators Used: BBPct, Noro's, RSI, TSI, HullSuite, TrendContinuation, Leonidas, SMI
Special: Uses TSI and SMI instead of VIDYA and TRAMA
Characteristics: Tuned for Ethereum's market cycles
Bitcoin
btc_4d_cal(src) - Bitcoin 4-Day
Use Case: Bitcoin on 4-day charts
Timeframe: 4D
Characteristics: Slower, smoother parameters for the most established crypto asset
Notes: Conservative parameters suitable for position trading
Traditional Markets
qqq_4d_cal(src) - QQQ (Nasdaq-100 ETF) 4-Day
Use Case: QQQ ETF and tech-heavy indices
Timeframe: 4D
Characteristics: Largest parameter sets reflecting lower volatility of traditional markets
Notes: Can be adapted for similar large-cap tech indices
💡 Usage Examples
Example 1: Using Pre-Calibrated System
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Simple one-line implementation for Bitcoin
btcSignal = lib.btc_4d_cal(close)
// Trading logic
longCondition = btcSignal > 0.5
shortCondition = btcSignal < -0.5
// Plot
plot(btcSignal, "BTC 4D Consensus", color.orange)
Example 2: Custom Multi-Indicator Consensus
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Build your own combination
signal1 = lib.BBPct(20, 2.0, close)
signal2 = lib.RSI(14, close, 5)
signal3 = lib.TRAMA(close, 50)
signal4 = lib.TSI(close, 25, 13, 13)
// Custom consensus
customConsensus = math.avg(signal1, signal2, signal3, signal4)
plot(customConsensus, "Custom Consensus", color.blue)
Example 3: Asset-Specific Strategy Switching
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Automatically use the right calibration
signal = switch syminfo.ticker
"BTCUSD" => lib.btc_4d_cal(close)
"ETHUSD" => lib.eth_4d_cal(close)
"SOLUSD" => lib.sol_4d_cal(close)
"QQQ" => lib.qqq_4d_cal(close)
=> lib.virtual_4d_cal(close) // Default
plot(signal, "Auto-Calibrated Signal", color.orange)
Example 4: Correlation-Filtered Trading
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Only trade when strong correlation with market exists
spy = request.security("SPY", timeframe.period, close)
correlation = lib.MCorrelation(close, spy)
trendSignal = lib.virtual_1d_cal(close)
// Only signals with positive market correlation
tradeBuy = trendSignal > 0.5 and correlation > 0.5
tradeSell = trendSignal < -0.5 and correlation > 0.5
Example 5: Beta-Adjusted Position Sizing
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
spy = request.security("SPY", timeframe.period, close)
beta = lib.assetBeta(close, spy)
// Adjust position size based on Beta
basePositionSize = 100
adjustedSize = basePositionSize / beta // Less size with high Beta
// Use with calibrated signal
signal = lib.qqq_4d_cal(close)
🎯 Choosing the Right Calibration
Decision Tree
1. What asset are you trading?
Bitcoin → btc_4d_cal()
Ethereum/ERC-20 → eth_4d_cal()
Solana → sol_4d_cal()
Solana memes → sol_meme_4d_cal()
SUI ecosystem → sui_cal()
BASE ecosystem → base_cal()
Meme coins (any chain) → meme_cal()
QQQ/Tech indices → qqq_4d_cal()
Other/General → virtual_4d_cal() or virtual_1d_cal()
2. What timeframe?
Most calibrations are optimized for 4D (4-day) or 1D (daily)
For other timeframes, start with virtual calibrations and adjust
3. What's the asset's volatility?
High volatility (memes, new tokens) → Use meme_cal() or similar
Medium volatility (established alts) → Use specific calibrations
Low volatility (BTC, major indices) → Use btc_4d_cal() or qqq_4d_cal()
⚙️ Technical Details
Normalization Standard
Bullish: 1
Bearish: -1
Neutral: 0 (only for selected indicators)
Calibration Methodology
Pre-calibrated functions were optimized using:
Historical backtesting on target assets
Parameter optimization for maximum Sharpe ratio
Validation on out-of-sample data
Real-time forward testing
Iterative refinement based on market conditions
Advantages of Pre-Calibrations
Instant Deployment: No parameter tuning needed
Asset-Optimized: Tailored to specific market characteristics
Tested Performance: Validated through extensive backtesting
Consistent Framework: All use the same 8-indicator structure
Easy Comparison: Compare different assets using same methodology
Performance Considerations
All functions are optimized for Pine Script v5
Proper use of var for state management
Efficient array operations where needed
Minimal recursive calls
Pre-calibrations add negligible computational overhead
📋 License
This code is subject to the Mozilla Public License 2.0 at mozilla.org
🔧 Installation
pinescriptimport unicorpusstocks/NormalizedIndicators/1
Then use functions with your chosen alias:
pinescript// Individual indicators
lib.BBPct(20, 2.0, close)
lib.RSI(14, close, 5)
lib.TSI(close, 25, 13, 13)
// Pre-calibrated systems
lib.btc_4d_cal(close)
lib.eth_4d_cal(close)
lib.meme_cal(close)
⚠️ Important Notes
General Usage
All indicators are lagging, as is typical for trend-following indicators
Signals should be combined with additional analysis (volume, support/resistance, etc.)
Backtesting is recommended before starting live trading with these signals
Different assets and timeframes may require different parameter optimizations
Pre-Calibrated Systems
Calibrations are optimized for specific timeframes - using them on different timeframes may reduce effectiveness
Market conditions change - what worked historically may need adjustment
Pre-calibrations are starting points, not guaranteed solutions
Always validate performance on your specific use case
Consider current market regime (trending vs. ranging)
Risk Management
Meme coin calibrations are designed for extremely volatile assets - use appropriate position sizing
Pre-calibrated systems do not eliminate risk
Always use stop losses and proper risk management
Past performance does not guarantee future results
Customization
Pre-calibrations can serve as templates for your own optimizations
Feel free to adjust individual parameters within calibration functions
Test modifications thoroughly before live deployment
🎓 Advanced Use Cases
Multi-Asset Portfolio Dashboard
Create a dashboard showing consensus across different assets:
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
btc = request.security("BTCUSD", "4D", close)
eth = request.security("ETHUSD", "4D", close)
sol = request.security("SOLUSD", "4D", close)
btcSignal = lib.btc_4d_cal(btc)
ethSignal = lib.eth_4d_cal(eth)
solSignal = lib.sol_4d_cal(sol)
// Plot all three for comparison
plot(btcSignal, "BTC", color.orange)
plot(ethSignal, "ETH", color.blue)
plot(solSignal, "SOL", color.purple)
Regime Detection
Use correlation and calibrations together:
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
// Detect market regime
btc = request.security("BTCUSD", timeframe.period, close)
correlation = lib.MCorrelation(close, btc)
// Choose strategy based on correlation
signal = correlation > 0.7 ? lib.btc_4d_cal(close) : lib.virtual_4d_cal(close)
Comparative Analysis
Compare asset-specific vs. general calibrations:
pinescriptimport unicorpusstocks/NormalizedIndicators/1 as lib
specificSignal = lib.btc_4d_cal(close) // BTC-specific
generalSignal = lib.virtual_4d_cal(close) // General
divergence = specificSignal - generalSignal
plot(divergence, "Calibration Divergence", color.yellow)
🚀 Quick Start Guide
For Beginners
Identify Your Asset: What are you trading?
Find the Calibration: Use the decision tree above
One-Line Implementation: signal = lib.btc_4d_cal(close)
Set Thresholds: Buy when > 0.5, sell when < -0.5
Add Risk Management: Always use stops
For Advanced Users
Start with Pre-Calibration: Use as baseline
Analyze Performance: Backtest on your specific market
Fine-Tune Parameters: Adjust individual indicators if needed
Combine with Other Signals: Volume, market structure, etc.
Create Custom Calibrations: Build your own based on library structure
For Developers
Import Library: Access all functions
Mix and Match: Combine indicators creatively
Build Custom Logic: Use indicators as building blocks
Create New Calibrations: Follow the established pattern
Share and Iterate: Contribute to the trading community
🎯 Key Takeaways
✅ 10 normalized indicators - Consistent interpretation across all
✅ 16+ pre-calibrated systems - Ready-to-use for specific assets
✅ Asset-optimized parameters - No guesswork required
✅ Calculation functions - Advanced correlation and beta analysis
✅ Universal framework - Works across crypto, stocks, forex
✅ Professional-grade - Built on proven technical analysis principles
✅ Flexible architecture - Use pre-calibrations or build your own
✅ Battle-tested - Validated through extensive backtesting
NormalizedIndicators Library transforms complex multi-indicator analysis into actionable signals through both customizable individual indicators and pre-optimized consensus systems. Whether you're a beginner looking for plug-and-play solutions or an advanced trader building sophisticated strategies, this library provides the foundation for data-driven trading decisions.WiederholenClaude kann Fehler machen. Bitte überprüfen Sie die Antworten. Sonnet 4.5
Hellenic EMA Matrix - PremiumHellenic EMA Matrix - Alpha Omega Premium
Complete User Guide
Table of Contents
Introduction
Indicator Philosophy
Mathematical Constants
EMA Types
Settings
Trading Signals
Visualization
Usage Strategies
FAQ
Introduction
Hellenic EMA Matrix is a premium indicator based on mathematical constants of nature: Phi (Phi - Golden Ratio), Pi (Pi), e (Euler's number). The indicator uses these universal constants to create dynamic EMAs that adapt to the natural rhythms of the market.
Key Features:
6 EMA types based on mathematical constants
Premium visualization with Neon Glow and Gradient Clouds
Automatic Fast/Mid/Slow EMA sorting
STRONG signals for powerful trends
Pulsing Ribbon Bar for instant trend assessment
Works on all timeframes (M1 - MN)
Indicator Philosophy
Why Mathematical Constants?
Traditional EMAs use arbitrary periods (9, 21, 50, 200). Hellenic Matrix goes further, using universal mathematical constants found in nature:
Phi (1.618) - Golden Ratio: galaxy spirals, seashells, human body proportions
Pi (3.14159) - Pi: circles, waves, cycles
e (2.71828) - Natural logarithm base: exponential growth, radioactive decay
Markets are also a natural system composed of millions of participants. Using mathematical constants allows tuning into the natural rhythms of market cycles.
Mathematical Constants
Phi (Phi) - Golden Ratio
Phi = 1.618033988749895
Properties:
Phi² = Phi + 1 = 2.618
Phi³ = 4.236
Phi⁴ = 6.854
Application: Ideal for trending movements and Fibonacci corrections
Pi (Pi) - Pi Number
Pi = 3.141592653589793
Properties:
2Pi = 6.283 (full circle)
3Pi = 9.425
4Pi = 12.566
Application: Excellent for cyclical markets and wave structures
e (Euler) - Euler's Number
e = 2.718281828459045
Properties:
e² = 7.389
e³ = 20.085
e⁴ = 54.598
Application: Suitable for exponential movements and volatile markets
EMA Types
1. Phi (Phi) - Golden Ratio EMA
Description: EMA based on the golden ratio
Period Formula:
Period = Phi^n × Base Multiplier
Parameters:
Phi Power Level (1-8): Power of Phi
Phi¹ = 1.618 → ~16 period (with Base=10)
Phi² = 2.618 → ~26 period
Phi³ = 4.236 → ~42 period (recommended)
Phi⁴ = 6.854 → ~69 period
Recommendations:
Phi² or Phi³ for day trading
Phi⁴ or Phi⁵ for swing trading
Works excellently as Fast EMA
2. Pi (Pi) - Circular EMA
Description: EMA based on Pi for cyclical movements
Period Formula:
Period = Pi × Multiple × Base Multiplier
Parameters:
Pi Multiple (1-10): Pi multiplier
1Pi = 3.14 → ~31 period (with Base=10)
2Pi = 6.28 → ~63 period (recommended)
3Pi = 9.42 → ~94 period
Recommendations:
2Pi ideal as Mid or Slow EMA
Excellently identifies cycles and waves
Use on volatile markets (crypto, forex)
3. e (Euler) - Natural EMA
Description: EMA based on natural logarithm
Period Formula:
Period = e^n × Base Multiplier
Parameters:
e Power Level (1-6): Power of e
e¹ = 2.718 → ~27 period (with Base=10)
e² = 7.389 → ~74 period (recommended)
e³ = 20.085 → ~201 period
Recommendations:
e² works excellently as Slow EMA
Ideal for stocks and indices
Filters noise well on lower timeframes
4. Delta (Delta) - Adaptive EMA
Description: Adaptive EMA that changes period based on volatility
Period Formula:
Period = Base Period × (1 + (Volatility - 1) × Factor)
Parameters:
Delta Base Period (5-200): Base period (default 20)
Delta Volatility Sensitivity (0.5-5.0): Volatility sensitivity (default 2.0)
How it works:
During low volatility → period decreases → EMA reacts faster
During high volatility → period increases → EMA smooths noise
Recommendations:
Works excellently on news and sharp movements
Use as Fast EMA for quick adaptation
Sensitivity 2.0-3.0 for crypto, 1.0-2.0 for stocks
5. Sigma (Sigma) - Composite EMA
Description: Composite EMA combining multiple active EMAs
Composition Methods:
Weighted Average (default):
Sigma = (Phi + Pi + e + Delta) / 4
Simple average of all active EMAs
Geometric Mean:
Sigma = fourth_root(Phi × Pi × e × Delta)
Geometric mean (more conservative)
Harmonic Mean:
Sigma = 4 / (1/Phi + 1/Pi + 1/e + 1/Delta)
Harmonic mean (more weight to smaller values)
Recommendations:
Enable for additional confirmation
Use as Mid EMA
Weighted Average - most universal method
6. Lambda (Lambda) - Wave EMA
Description: Wave EMA with sinusoidal period modulation
Period Formula:
Period = Base Period × (1 + Amplitude × sin(2Pi × bar / Frequency))
Parameters:
Lambda Base Period (10-200): Base period
Lambda Wave Amplitude (0.1-2.0): Wave amplitude
Lambda Wave Frequency (10-200): Wave frequency in bars
How it works:
Period pulsates sinusoidally
Creates wave effect following market cycles
Recommendations:
Experimental EMA for advanced users
Works well on cyclical markets
Frequency = 50 for day trading, 100+ for swing
Settings
Matrix Core Settings
Base Multiplier (1-100)
Multiplies all EMA periods
Base = 1: Very fast EMAs (Phi³ = 4, 2Pi = 6, e² = 7)
Base = 10: Standard (Phi³ = 42, 2Pi = 63, e² = 74)
Base = 20: Slow EMAs (Phi³ = 85, 2Pi = 126, e² = 148)
Recommendations by timeframe:
M1-M5: Base = 5-10
M15-H1: Base = 10-15 (recommended)
H4-D1: Base = 15-25
W1-MN: Base = 25-50
Matrix Source
Data source selection for EMA calculation:
close - closing price (standard)
open - opening price
high - high
low - low
hl2 - (high + low) / 2
hlc3 - (high + low + close) / 3
ohlc4 - (open + high + low + close) / 4
When to change:
hlc3 or ohlc4 for smoother signals
high for aggressive longs
low for aggressive shorts
Manual EMA Selection
Critically important setting! Determines which EMAs are used for signal generation.
Use Manual Fast/Slow/Mid Selection
Enabled (default): You select EMAs manually
Disabled: Automatic selection by periods
Fast EMA
Fast EMA - reacts first to price changes
Recommendations:
Phi Golden (recommended) - universal choice
Delta Adaptive - for volatile markets
Must be fastest (smallest period)
Slow EMA
Slow EMA - determines main trend
Recommendations:
Pi Circular (recommended) - excellent trend filter
e Natural - for smoother trend
Must be slowest (largest period)
Mid EMA
Mid EMA - additional signal filter
Recommendations:
e Natural (recommended) - excellent middle level
Pi Circular - alternative
None - for more frequent signals (only 2 EMAs)
IMPORTANT: The indicator automatically sorts selected EMAs by their actual periods:
Fast = EMA with smallest period
Mid = EMA with middle period
Slow = EMA with largest period
Therefore, you can select any combination - the indicator will arrange them correctly!
Premium Visualization
Neon Glow
Enable Neon Glow for EMAs - adds glowing effect around EMA lines
Glow Strength:
Light - subtle glow
Medium (recommended) - optimal balance
Strong - bright glow (may be too bright)
Effect: 2 glow layers around each EMA for 3D effect
Gradient Clouds
Enable Gradient Clouds - fills space between EMAs with gradient
Parameters:
Cloud Transparency (85-98): Cloud transparency
95-97 (recommended)
Higher = more transparent
Dynamic Cloud Intensity - automatically changes transparency based on EMA distance
Cloud Colors:
Phi-Pi Cloud:
Blue - when Pi above Phi (bullish)
Gold - when Phi above Pi (bearish)
Pi-e Cloud:
Green - when e above Pi (bullish)
Blue - when Pi above e (bearish)
2 layers for volumetric effect
Pulsing Ribbon Bar
Enable Pulsing Indicator Bar - pulsing strip at bottom/top of chart
Parameters:
Ribbon Position: Top / Bottom (recommended)
Pulse Speed: Slow / Medium (recommended) / Fast
Symbols and colors:
Green filled square - STRONG BULLISH
Pink filled square - STRONG BEARISH
Blue hollow square - Bullish (regular)
Red hollow square - Bearish (regular)
Purple rectangle - Neutral
Effect: Pulsation with sinusoid for living market feel
Signal Bar Highlights
Enable Signal Bar Highlights - highlights bars with signals
Parameters:
Highlight Transparency (88-96): Highlight transparency
Highlight Style:
Light Fill (recommended) - bar background fill
Thin Line - bar outline only
Highlights:
Golden Cross - green
Death Cross - pink
STRONG BUY - green
STRONG SELL - pink
Show Greek Labels
Shows Greek alphabet letters on last bar:
Phi - Phi EMA (gold)
Pi - Pi EMA (blue)
e - Euler EMA (green)
Delta - Delta EMA (purple)
Sigma - Sigma EMA (pink)
When to use: For education or presentations
Show Old Background
Old background style (not recommended):
Green background - STRONG BULLISH
Pink background - STRONG BEARISH
Blue background - Bullish
Red background - Bearish
Not recommended - use new Gradient Clouds and Pulsing Bar
Info Table
Show Info Table - table with indicator information
Parameters:
Position: Top Left / Top Right (recommended) / Bottom Left / Bottom Right
Size: Tiny / Small (recommended) / Normal / Large
Table contents:
EMA list - periods and current values of all active EMAs
Effects - active visual effects
TREND - current trend state:
STRONG UP - strong bullish
STRONG DOWN - strong bearish
Bullish - regular bullish
Bearish - regular bearish
Neutral - neutral
Momentum % - percentage deviation of price from Fast EMA
Setup - current Fast/Slow/Mid configuration
Trading Signals
Show Golden/Death Cross
Golden Cross - Fast EMA crosses Slow EMA from below (bullish signal) Death Cross - Fast EMA crosses Slow EMA from above (bearish signal)
Symbols:
Yellow dot "GC" below - Golden Cross
Dark red dot "DC" above - Death Cross
Show STRONG Signals
STRONG BUY and STRONG SELL - the most powerful indicator signals
Conditions for STRONG BULLISH:
EMA Alignment: Fast > Mid > Slow (all EMAs aligned)
Trend: Fast > Slow (clear uptrend)
Distance: EMAs separated by minimum 0.15%
Price Position: Price above Fast EMA
Fast Slope: Fast EMA rising
Slow Slope: Slow EMA rising
Mid Trending: Mid EMA also rising (if enabled)
Conditions for STRONG BEARISH:
Same but in reverse
Visual display:
Green label "STRONG BUY" below bar
Pink label "STRONG SELL" above bar
Difference from Golden/Death Cross:
Golden/Death Cross = crossing moment (1 bar)
STRONG signal = sustained trend (lasts several bars)
IMPORTANT: After fixes, STRONG signals now:
Work on all timeframes (M1 to MN)
Don't break on small retracements
Work with any Fast/Mid/Slow combination
Automatically adapt thanks to EMA sorting
Show Stop Loss/Take Profit
Automatic SL/TP level calculation on STRONG signal
Parameters:
Stop Loss (ATR) (0.5-5.0): ATR multiplier for stop loss
1.5 (recommended) - standard
1.0 - tight stop
2.0-3.0 - wide stop
Take Profit R:R (1.0-5.0): Risk/reward ratio
2.0 (recommended) - standard (risk 1.5 ATR, profit 3.0 ATR)
1.5 - conservative
3.0-5.0 - aggressive
Formulas:
LONG:
Stop Loss = Entry - (ATR × Stop Loss ATR)
Take Profit = Entry + (ATR × Stop Loss ATR × Take Profit R:R)
SHORT:
Stop Loss = Entry + (ATR × Stop Loss ATR)
Take Profit = Entry - (ATR × Stop Loss ATR × Take Profit R:R)
Visualization:
Red X - Stop Loss
Green X - Take Profit
Levels remain active while STRONG signal persists
Trading Signals
Signal Types
1. Golden Cross
Description: Fast EMA crosses Slow EMA from below
Signal: Beginning of bullish trend
How to trade:
ENTRY: On bar close with Golden Cross
STOP: Below local low or below Slow EMA
TARGET: Next resistance level or 2:1 R:R
Strengths:
Simple and clear
Works well on trending markets
Clear entry point
Weaknesses:
Lags (signal after movement starts)
Many false signals in ranging markets
May be late on fast moves
Optimal timeframes: H1, H4, D1
2. Death Cross
Description: Fast EMA crosses Slow EMA from above
Signal: Beginning of bearish trend
How to trade:
ENTRY: On bar close with Death Cross
STOP: Above local high or above Slow EMA
TARGET: Next support level or 2:1 R:R
Application: Mirror of Golden Cross
3. STRONG BUY
Description: All EMAs aligned + trend + all EMAs rising
Signal: Powerful bullish trend
How to trade:
ENTRY: On bar close with STRONG BUY or on pullback to Fast EMA
STOP: Below Fast EMA or automatic SL (if enabled)
TARGET: Automatic TP (if enabled) or by levels
TRAILING: Follow Fast EMA
Entry strategies:
Aggressive: Enter immediately on signal
Conservative: Wait for pullback to Fast EMA, then enter on bounce
Pyramiding: Add positions on pullbacks to Mid EMA
Position management:
Hold while STRONG signal active
Exit on STRONG SELL or Death Cross appearance
Move stop behind Fast EMA
Strengths:
Most reliable indicator signal
Doesn't break on pullbacks
Catches large moves
Works on all timeframes
Weaknesses:
Appears less frequently than other signals
Requires confirmation (multiple conditions)
Optimal timeframes: All (M5 - D1)
4. STRONG SELL
Description: All EMAs aligned down + downtrend + all EMAs falling
Signal: Powerful bearish trend
How to trade: Mirror of STRONG BUY
Visual Signals
Pulsing Ribbon Bar
Quick market assessment at a glance:
Symbol Color State
Filled square Green STRONG BULLISH
Filled square Pink STRONG BEARISH
Hollow square Blue Bullish
Hollow square Red Bearish
Rectangle Purple Neutral
Pulsation: Sinusoidal, creates living effect
Signal Bar Highlights
Bars with signals are highlighted:
Green highlight: STRONG BUY or Golden Cross
Pink highlight: STRONG SELL or Death Cross
Gradient Clouds
Colored space between EMAs shows trend strength:
Wide clouds - strong trend
Narrow clouds - weak trend or consolidation
Color change - trend change
Info Table
Quick reference in corner:
TREND: Current state (STRONG UP, Bullish, Neutral, Bearish, STRONG DOWN)
Momentum %: Movement strength
Effects: Active visual effects
Setup: Fast/Slow/Mid configuration
Usage Strategies
Strategy 1: "Golden Trailing"
Idea: Follow STRONG signals using Fast EMA as trailing stop
Settings:
Fast: Phi Golden (Phi³)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
Wait for STRONG BUY
Enter on bar close or on pullback to Fast EMA
Stop below Fast EMA
Management:
Hold position while STRONG signal active
Move stop behind Fast EMA daily
Exit on STRONG SELL or Death Cross
Take Profit:
Partially close at +2R
Trail remainder until exit signal
For whom: Swing traders, trend followers
Pros:
Catches large moves
Simple rules
Emotionally comfortable
Cons:
Requires patience
Possible extended drawdowns on pullbacks
Strategy 2: "Scalping Bounces"
Idea: Scalp bounces from Fast EMA during STRONG trend
Settings:
Fast: Delta Adaptive (Base 15, Sensitivity 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base Multiplier: 5
Timeframe: M5, M15
Entry rules:
STRONG signal must be active
Wait for price pullback to Fast EMA
Enter on bounce (candle closes above/below Fast EMA)
Stop behind local extreme (15-20 pips)
Take Profit:
+1.5R or to Mid EMA
Or to next level
For whom: Active day traders
Pros:
Many signals
Clear entry point
Quick profits
Cons:
Requires constant monitoring
Not all bounces work
Requires discipline for frequent trading
Strategy 3: "Triple Filter"
Idea: Enter only when all 3 EMAs and price perfectly aligned
Settings:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi)
Base Multiplier: 15
Timeframe: H4, D1
Entry rules (LONG):
STRONG BUY active
Price above all three EMAs
Fast > Mid > Slow (all aligned)
All EMAs rising (slope up)
Gradient Clouds wide and bright
Entry:
On bar close meeting all conditions
Or on next pullback to Fast EMA
Stop:
Below Mid EMA or -1.5 ATR
Take Profit:
First target: +3R
Second target: next major level
Trailing: Mid EMA
For whom: Conservative swing traders, investors
Pros:
Very reliable signals
Minimum false entries
Large profit potential
Cons:
Rare signals (2-5 per month)
Requires patience
Strategy 4: "Adaptive Scalper"
Idea: Use only Delta Adaptive EMA for quick volatility reaction
Settings:
Fast: Delta Adaptive (Base 10, Sensitivity 3.0)
Mid: None
Slow: Delta Adaptive (Base 30, Sensitivity 2.0)
Base Multiplier: 3
Timeframe: M1, M5
Feature: Two different Delta EMAs with different settings
Entry rules:
Golden Cross between two Delta EMAs
Both Delta EMAs must be rising/falling
Enter on next bar
Stop:
10-15 pips or below Slow Delta EMA
Take Profit:
+1R to +2R
Or Death Cross
For whom: Scalpers on cryptocurrencies and forex
Pros:
Instant volatility adaptation
Many signals on volatile markets
Quick results
Cons:
Much noise on calm markets
Requires fast execution
High commissions may eat profits
Strategy 5: "Cyclical Trader"
Idea: Use Pi and Lambda for trading cyclical markets
Settings:
Fast: Pi Circular (1Pi)
Mid: Lambda Wave (Base 30, Amplitude 0.5, Frequency 50)
Slow: Pi Circular (3Pi)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
STRONG signal active
Lambda Wave EMA synchronized with trend
Enter on bounce from Lambda Wave
For whom: Traders of cyclical assets (some altcoins, commodities)
Pros:
Catches cyclical movements
Lambda Wave provides additional entry points
Cons:
More complex to configure
Not for all markets
Lambda Wave may give false signals
Strategy 6: "Multi-Timeframe Confirmation"
Idea: Use multiple timeframes for confirmation
Scheme:
Higher TF (D1): Determine trend direction (STRONG signal)
Middle TF (H4): Wait for STRONG signal in same direction
Lower TF (M15): Look for entry point (Golden Cross or bounce from Fast EMA)
Settings for all TFs:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base Multiplier: 10
Rules:
All 3 TFs must show one trend
Entry on lower TF
Stop by lower TF
Target by higher TF
For whom: Serious traders and investors
Pros:
Maximum reliability
Large profit targets
Minimum false signals
Cons:
Rare setups
Requires analysis of multiple charts
Experience needed
Practical Tips
DOs
Use STRONG signals as primary - they're most reliable
Let signals develop - don't exit on first pullback
Use trailing stop - follow Fast EMA
Combine with levels - S/R, Fibonacci, volumes
Test on demo before real
Adjust Base Multiplier for your timeframe
Enable visual effects - they help see the picture
Use Info Table - quick situation assessment
Watch Pulsing Bar - instant state indicator
Trust auto-sorting of Fast/Mid/Slow
DON'Ts
Don't trade against STRONG signal - trend is your friend
Don't ignore Mid EMA - it adds reliability
Don't use too small Base Multiplier on higher TFs
Don't enter on Golden Cross in range - check for trend
Don't change settings during open position
Don't forget risk management - 1-2% per trade
Don't trade all signals in row - choose best ones
Don't use indicator in isolation - combine with Price Action
Don't set too tight stops - let trade breathe
Don't over-optimize - simplicity = reliability
Optimal Settings by Asset
US Stocks (SPY, AAPL, TSLA)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 10-15
Timeframe: H4, D1
Features:
Use on daily for swing
STRONG signals very reliable
Works well on trending stocks
Forex (EUR/USD, GBP/USD)
Recommendation:
Fast: Delta Adaptive (Base 15, Sens 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base: 8-12
Timeframe: M15, H1, H4
Features:
Delta Adaptive works excellently on news
Many signals on M15-H1
Consider spreads
Cryptocurrencies (BTC, ETH, altcoins)
Recommendation:
Fast: Delta Adaptive (Base 10, Sens 3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M5, M15, H1
Features:
High volatility - adaptation needed
STRONG signals can last days
Be careful with scalping on M1-M5
Commodities (Gold, Oil)
Recommendation:
Fast: Pi Circular (1Pi)
Mid: Phi Golden (Phi³)
Slow: Pi Circular (3Pi)
Base: 12-18
Timeframe: H4, D1
Features:
Pi works excellently on cyclical commodities
Gold responds especially well to Phi
Oil volatile - use wide stops
Indices (S&P500, Nasdaq, DAX)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 15-20
Timeframe: H4, D1, W1
Features:
Very trending instruments
STRONG signals last weeks
Good for position trading
Alerts
The indicator supports 6 alert types:
1. Golden Cross
Message: "Hellenic Matrix: GOLDEN CROSS - Fast EMA crossed above Slow EMA - Bullish trend starting!"
When: Fast EMA crosses Slow EMA from below
2. Death Cross
Message: "Hellenic Matrix: DEATH CROSS - Fast EMA crossed below Slow EMA - Bearish trend starting!"
When: Fast EMA crosses Slow EMA from above
3. STRONG BULLISH
Message: "Hellenic Matrix: STRONG BULLISH SIGNAL - All EMAs aligned for powerful uptrend!"
When: All conditions for STRONG BUY met (first bar)
4. STRONG BEARISH
Message: "Hellenic Matrix: STRONG BEARISH SIGNAL - All EMAs aligned for powerful downtrend!"
When: All conditions for STRONG SELL met (first bar)
5. Bullish Ribbon
Message: "Hellenic Matrix: BULLISH RIBBON - EMAs aligned for uptrend"
When: EMAs aligned bullish + price above Fast EMA (less strict condition)
6. Bearish Ribbon
Message: "Hellenic Matrix: BEARISH RIBBON - EMAs aligned for downtrend"
When: EMAs aligned bearish + price below Fast EMA (less strict condition)
How to Set Up Alerts:
Open indicator on chart
Click on three dots next to indicator name
Select "Create Alert"
In "Condition" field select needed alert:
Golden Cross
Death Cross
STRONG BULLISH
STRONG BEARISH
Bullish Ribbon
Bearish Ribbon
Configure notification method:
Pop-up in browser
Email
SMS (in Premium accounts)
Push notifications in mobile app
Webhook (for automation)
Select frequency:
Once Per Bar Close (recommended) - once on bar close
Once Per Bar - during bar formation
Only Once - only first time
Click "Create"
Tip: Create separate alerts for different timeframes and instruments
FAQ
1. Why don't STRONG signals appear?
Possible reasons:
Incorrect Fast/Mid/Slow order
Solution: Indicator automatically sorts EMAs by periods, but ensure selected EMAs have different periods
Base Multiplier too large
Solution: Reduce Base to 5-10 on lower timeframes
Market in range
Solution: STRONG signals appear only in trends - this is normal
Too strict EMA settings
Solution: Try classic combination: Phi³ / Pi×2 / e² with Base=10
Mid EMA too close to Fast or Slow
Solution: Select Mid EMA with period between Fast and Slow
2. How often should STRONG signals appear?
Normal frequency:
M1-M5: 5-15 signals per day (very active markets)
M15-H1: 2-8 signals per day
H4: 3-10 signals per week
D1: 2-5 signals per month
W1: 2-6 signals per year
If too many signals - market very volatile or Base too small
If too few signals - market in range or Base too large
4. What are the best settings for beginners?
Universal "out of the box" settings:
Matrix Core:
Base Multiplier: 10
Source: close
Phi Golden: Enabled, Power = 3
Pi Circular: Enabled, Multiple = 2
e Natural: Enabled, Power = 2
Delta Adaptive: Enabled, Base = 20, Sensitivity = 2.0
Manual Selection:
Fast: Phi Golden
Mid: e Natural
Slow: Pi Circular
Visualization:
Gradient Clouds: ON
Neon Glow: ON (Medium)
Pulsing Bar: ON (Medium)
Signal Highlights: ON (Light Fill)
Table: ON (Top Right, Small)
Signals:
Golden/Death Cross: ON
STRONG Signals: ON
Stop Loss: OFF (while learning)
Timeframe for learning: H1 or H4
5. Can I use only one EMA?
No, minimum 2 EMAs (Fast and Slow) for signal generation.
Mid EMA is optional:
With Mid EMA = more reliable but rarer signals
Without Mid EMA = more signals but less strict filtering
Recommendation: Start with 3 EMAs (Fast/Mid/Slow), then experiment
6. Does the indicator work on cryptocurrencies?
Yes, works excellently! Especially good on:
Bitcoin (BTC)
Ethereum (ETH)
Major altcoins (SOL, BNB, XRP)
Recommended settings for crypto:
Fast: Delta Adaptive (Base 10-15, Sensitivity 2.5-3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M15, H1, H4
Crypto market features:
High volatility → use Delta Adaptive
24/7 trading → set alerts
Sharp movements → wide stops
7. Can I trade only with this indicator?
Technically yes, but NOT recommended.
Best approach - combine with:
Price Action - support/resistance levels, candle patterns
Volume - movement strength confirmation
Fibonacci - retracement and extension levels
RSI/MACD - divergences and overbought/oversold
Fundamental analysis - news, company reports
Hellenic Matrix:
Excellently determines trend and its strength
Provides clear entry/exit points
Doesn't consider fundamentals
Doesn't see major levels
8. Why do Gradient Clouds change color?
Color depends on EMA order:
Phi-Pi Cloud:
Blue - Pi EMA above Phi EMA (bullish alignment)
Gold - Phi EMA above Pi EMA (bearish alignment)
Pi-e Cloud:
Green - e EMA above Pi EMA (bullish alignment)
Blue - Pi EMA above e EMA (bearish alignment)
Color change = EMA order change = possible trend change
9. What is Momentum % in the table?
Momentum % = percentage deviation of price from Fast EMA
Formula:
Momentum = ((Close - Fast EMA) / Fast EMA) × 100
Interpretation:
+0.5% to +2% - normal bullish momentum
+2% to +5% - strong bullish momentum
+5% and above - overheating (correction possible)
-0.5% to -2% - normal bearish momentum
-2% to -5% - strong bearish momentum
-5% and below - oversold (bounce possible)
Usage:
Monitor momentum during STRONG signals
Large momentum = don't enter (wait for pullback)
Small momentum = good entry point
10. How to configure for scalping?
Settings for scalping (M1-M5):
Base Multiplier: 3-5
Source: close or hlc3 (smoother)
Fast: Delta Adaptive (Base 8-12, Sensitivity 3.0)
Mid: None (for more signals)
Slow: Phi Golden (Phi²) or Pi Circular (1Pi)
Visualization:
- Gradient Clouds: ON (helps see strength)
- Neon Glow: OFF (doesn't clutter chart)
- Pulsing Bar: ON (quick assessment)
- Signal Highlights: ON
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: ON (1.0-1.5 ATR, R:R 1.5-2.0)
Scalping rules:
Trade only STRONG signals
Enter on bounce from Fast EMA
Tight stops (10-20 pips)
Quick take profit (+1R to +2R)
Don't hold through news
11. How to configure for long-term investing?
Settings for investing (D1-W1):
Base Multiplier: 20-30
Source: close
Fast: Phi Golden (Phi³ or Phi⁴)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi or 4Pi)
Visualization:
- Gradient Clouds: ON
- Neon Glow: ON (Medium)
- Everything else - to taste
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: OFF (use percentage stop)
Investing rules:
Enter only on STRONG signals
Hold while STRONG active (weeks/months)
Stop below Slow EMA or -10%
Take profit: by company targets or +50-100%
Ignore short-term pullbacks
12. What if indicator slows down chart?
Indicator is optimized, but if it slows:
Disable unnecessary visual effects:
Neon Glow: OFF (saves 8 plots)
Gradient Clouds: ON but low quality
Lambda Wave EMA: OFF (if not using)
Reduce number of active EMAs:
Sigma Composite: OFF
Lambda Wave: OFF
Leave only Phi, Pi, e, Delta
Simplify settings:
Pulsing Bar: OFF
Greek Labels: OFF
Info Table: smaller size
13. Can I use on different timeframes simultaneously?
Yes! Multi-timeframe analysis is very powerful:
Classic scheme:
Higher TF (D1, W1) - determine global trend
Wait for STRONG signal
This is our trading direction
Middle TF (H4, H1) - look for confirmation
STRONG signal in same direction
Precise entry zone
Lower TF (M15, M5) - entry point
Golden Cross or bounce from Fast EMA
Precise stop loss
Example:
W1: STRONG BUY active (global uptrend)
H4: STRONG BUY appeared (confirmation)
M15: Wait for Golden Cross or bounce from Fast EMA → ENTRY
Advantages:
Maximum reliability
Clear timeframe hierarchy
Large targets
14. How does indicator work on news?
Delta Adaptive EMA adapts excellently to news:
Before news:
Low volatility → Delta EMA becomes fast → pulls to price
During news:
Sharp volatility spike → Delta EMA slows → filters noise
After news:
Volatility normalizes → Delta EMA returns to normal
Recommendations:
Don't trade at news release moment (spreads widen)
Wait for STRONG signal after news (2-5 bars)
Use Delta Adaptive as Fast EMA for quick reaction
Widen stops by 50-100% during important news
Advanced Techniques
Technique 1: "Divergences with EMA"
Idea: Look for discrepancies between price and Fast EMA
Bullish divergence:
Price makes lower low
Fast EMA makes higher low
= Possible reversal up
Bearish divergence:
Price makes higher high
Fast EMA makes lower high
= Possible reversal down
How to trade:
Find divergence
Wait for STRONG signal in divergence direction
Enter on confirmation
Technique 2: "EMA Tunnel"
Idea: Use space between Fast and Slow EMA as "tunnel"
Rules:
Wide tunnel - strong trend, hold position
Narrow tunnel - weak trend or consolidation, caution
Tunnel narrowing - trend weakening, prepare to exit
Tunnel widening - trend strengthening, can add
Visually: Gradient Clouds show this automatically!
Trading:
Enter on STRONG signal (tunnel starts widening)
Hold while tunnel wide
Exit when tunnel starts narrowing
Technique 3: "Wave Analysis with Lambda"
Idea: Lambda Wave EMA creates sinusoid matching market cycles
Setup:
Lambda Base Period: 30
Lambda Wave Amplitude: 0.5
Lambda Wave Frequency: 50 (adjusted to asset cycle)
How to find correct Frequency:
Look at historical cycles (distance between local highs)
Average distance = your Frequency
Example: if highs every 40-60 bars, set Frequency = 50
Trading:
Enter when Lambda Wave at bottom of sinusoid (growth potential)
Exit when Lambda Wave at top (fall potential)
Combine with STRONG signals
Technique 4: "Cluster Analysis"
Idea: When all EMAs gather in narrow cluster = powerful breakout soon
Cluster signs:
All EMAs (Phi, Pi, e, Delta) within 0.5-1% of each other
Gradient Clouds almost invisible
Price jumping around all EMAs
Trading:
Identify cluster (all EMAs close)
Determine breakout direction (where more volume, higher TFs direction)
Wait for breakout and STRONG signal
Enter on confirmation
Target = cluster size × 3-5
This is very powerful technique for big moves!
Technique 5: "Sigma as Dynamic Level"
Idea: Sigma Composite EMA = average of all EMAs = magnetic level
Usage:
Enable Sigma Composite (Weighted Average)
Sigma works as dynamic support/resistance
Price often returns to Sigma before trend continuation
Trading:
In trend: Enter on bounces from Sigma
In range: Fade moves from Sigma (trade return to Sigma)
On breakout: Sigma becomes support/resistance
Risk Management
Basic Rules
1. Position Size
Conservative: 1% of capital per trade
Moderate: 2% of capital per trade (recommended)
Aggressive: 3-5% (only for experienced)
Calculation formula:
Lot Size = (Capital × Risk%) / (Stop in pips × Pip value)
2. Risk/Reward Ratio
Minimum: 1:1.5
Standard: 1:2 (recommended)
Optimal: 1:3
Aggressive: 1:5+
3. Maximum Drawdown
Daily: -3% to -5%
Weekly: -7% to -10%
Monthly: -15% to -20%
Upon reaching limit → STOP trading until end of period
Position Management Strategies
1. Fixed Stop
Method:
Stop below/above Fast EMA or local extreme
DON'T move stop against position
Can move to breakeven
For whom: Beginners, conservative traders
2. Trailing by Fast EMA
Method:
Each day (or bar) move stop to Fast EMA level
Position closes when price breaks Fast EMA
Advantages:
Stay in trend as long as possible
Automatically exit on reversal
For whom: Trend followers, swing traders
3. Partial Exit
Method:
50% of position close at +2R
50% hold with trailing by Mid EMA or Slow EMA
Advantages:
Lock profit
Leave position for big move
Psychologically comfortable
For whom: Universal method (recommended)
4. Pyramiding
Method:
First entry on STRONG signal (50% of planned position)
Add 25% on pullback to Fast EMA
Add another 25% on pullback to Mid EMA
Overall stop below Slow EMA
Advantages:
Average entry price
Reduce risk
Increase profit in strong trends
Caution:
Works only in trends
In range leads to losses
For whom: Experienced traders
Trading Psychology
Correct Mindset
1. Indicator is a tool, not holy grail
Indicator shows probability, not guarantee
There will be losing trades - this is normal
Important is series statistics, not one trade
2. Trust the system
If STRONG signal appeared - enter
Don't search for "perfect" moment
Follow trading plan
3. Patience
STRONG signals don't appear every day
Better miss signal than enter against trend
Quality over quantity
4. Discipline
Always set stop loss
Don't move stop against position
Don't increase risk after losses
Beginner Mistakes
1. "I know better than indicator"
Indicator says STRONG BUY, but you think "too high, will wait for pullback"
Result: miss profitable move
Solution: Trust signals or don't use indicator
2. "Will reverse now for sure"
Trading against STRONG trend
Result: stops, stops, stops
Solution: Trend is your friend, trade with trend
3. "Will hold a bit more"
Don't exit when STRONG signal disappears
Greed eats profit
Solution: If signal gone - exit!
4. "I'll recover"
After losses double risk
Result: huge losses
Solution: Fixed % risk ALWAYS
5. "I don't like this signal"
Skip signals because of "feeling"
Result: inconsistency, no statistics
Solution: Trade ALL signals or clearly define filters
Trading Journal
What to Record
For each trade:
1. Entry/exit date and time
2. Instrument and timeframe
3. Signal type
Golden Cross
STRONG BUY
STRONG SELL
Death Cross
4. Indicator settings
Fast/Mid/Slow EMA
Base Multiplier
Other parameters
5. Chart screenshot
Entry moment
Exit moment
6. Trade parameters
Position size
Stop loss
Take Profit
R:R
7. Result
Profit/Loss in $
Profit/Loss in %
Profit/Loss in R
8. Notes
What was right
What was wrong
Emotions during trade
Lessons
Journal Analysis
Analyze weekly:
1. Win Rate
Win Rate = (Profitable trades / All trades) × 100%
Good: 50-60%
Excellent: 60-70%
Exceptional: 70%+
2. Average R
Average R = Sum of all R / Number of trades
Good: +0.5R
Excellent: +1.0R
Exceptional: +1.5R+
3. Profit Factor
Profit Factor = Total profit / Total losses
Good: 1.5+
Excellent: 2.0+
Exceptional: 3.0+
4. Maximum Drawdown
Track consecutive losses
If more than 5 in row - stop, check system
5. Best/Worst Trades
What was common in best trades? (do more)
What was common in worst trades? (avoid)
Pre-Trade Checklist
Technical Analysis
STRONG signal active (BUY or SELL)
All EMAs properly aligned (Fast > Mid > Slow or reverse)
Price on correct side of Fast EMA
Gradient Clouds confirm trend
Pulsing Bar shows STRONG state
Momentum % in normal range (not overheated)
No close strong levels against direction
Higher timeframe doesn't contradict
Risk Management
Position size calculated (1-2% risk)
Stop loss set
Take profit calculated (minimum 1:2)
R:R satisfactory
Daily/weekly risk limit not exceeded
No other open correlated positions
Fundamental Analysis
No important news in coming hours
Market session appropriate (liquidity)
No contradicting fundamentals
Understand why asset is moving
Psychology
Calm and thinking clearly
No emotions from previous trades
Ready to accept loss at stop
Following trading plan
Not revenging market for past losses
If at least one point is NO - think twice before entering!
Learning Roadmap
Week 1: Familiarization
Goals:
Install and configure indicator
Study all EMA types
Understand visualization
Tasks:
Add indicator to chart
Test all Fast/Mid/Slow settings
Play with Base Multiplier on different timeframes
Observe Gradient Clouds and Pulsing Bar
Study Info Table
Result: Comfort with indicator interface
Week 2: Signals
Goals:
Learn to recognize all signal types
Understand difference between Golden Cross and STRONG
Tasks:
Find 10 Golden Cross examples in history
Find 10 STRONG BUY examples in history
Compare their results (which worked better)
Set up alerts
Get 5 real alerts
Result: Understanding signals
Week 3: Demo Trading
Goals:
Start trading signals on demo account
Gather statistics
Tasks:
Open demo account
Trade ONLY STRONG signals
Keep journal (minimum 20 trades)
Don't change indicator settings
Strictly follow stop losses
Result: 20+ documented trades
Week 4: Analysis
Goals:
Analyze demo trading results
Optimize approach
Tasks:
Calculate win rate and average R
Find patterns in profitable trades
Find patterns in losing trades
Adjust approach (not indicator!)
Write trading plan
Result: Trading plan on 1 page
Month 2: Improvement
Goals:
Deepen understanding
Add additional techniques
Tasks:
Study multi-timeframe analysis
Test combinations with Price Action
Try advanced techniques (divergences, tunnels)
Continue demo trading (minimum 50 trades)
Achieve stable profitability on demo
Result: Win rate 55%+ and Profit Factor 1.5+
Month 3: Real Trading
Goals:
Transition to real account
Maintain discipline
Tasks:
Open small real account
Trade minimum lots
Strictly follow trading plan
DON'T increase risk
Focus on process, not profit
Result: Psychological comfort on real
Month 4+: Scaling
Goals:
Increase account
Become consistently profitable
Tasks:
With 60%+ win rate can increase risk to 2%
Upon doubling account can add capital
Continue keeping journal
Periodically review and improve strategy
Share experience with community
Result: Stable profitability month after month
Additional Resources
Recommended Reading
Technical Analysis:
"Technical Analysis of Financial Markets" - John Murphy
"Trading in the Zone" - Mark Douglas (psychology)
"Market Wizards" - Jack Schwager (trader interviews)
EMA and Moving Averages:
"Moving Averages 101" - Steve Burns
Articles on Investopedia about EMA
Risk Management:
"The Mathematics of Money Management" - Ralph Vince
"Trade Your Way to Financial Freedom" - Van K. Tharp
Trading Journals:
Edgewonk (paid, very powerful)
Tradervue (free version + premium)
Excel/Google Sheets (free)
Screeners:
TradingView Stock Screener
Finviz (stocks)
CoinMarketCap (crypto)
Conclusion
Hellenic EMA Matrix is a powerful tool based on universal mathematical constants of nature. The indicator combines:
Mathematical elegance - Phi, Pi, e instead of arbitrary numbers
Premium visualization - Neon Glow, Gradient Clouds, Pulsing Bar
Reliable signals - STRONG BUY/SELL work on all timeframes
Flexibility - 6 EMA types, adaptation to any trading style
Automation - auto-sorting EMAs, SL/TP calculation, alerts
Key Success Principles:
Simplicity - start with basic settings (Phi/Pi/e, Base=10)
Discipline - follow STRONG signals strictly
Patience - wait for quality setups
Risk Management - 1-2% per trade, ALWAYS
Journal - document every trade
Learning - constantly improve skills
Remember:
Indicator shows probability, not guarantee
Important is series statistics, not one trade
Psychology more important than technique
Quality more important than quantity
Process more important than result
Acknowledgments
Thank you for using Hellenic EMA Matrix - Alpha Omega Premium!
The indicator was created with love for mathematics, markets, and beautiful visualization.
Wishing you profitable trading!
Guide Version: 1.0
Date: 2025
Compatibility: Pine Script v6, TradingView
"In the simplicity of mathematical constants lies the complexity of market movements"
VWAP D/W/M + MA100 & EMA100 albanThis TradingView indicator displays three independent VWAPs (Volume Weighted Average Prices) along with MA100 (Simple Moving Average) and EMA100 (Exponential Moving Average) on the chart.
Key Features:
VWAP #1, VWAP #2, VWAP #3: Each VWAP can be configured independently with:
Source (hlc3, close, etc.)
Anchor period (Session, Week, Month, Quarter, Year, Decade, Century, Earnings, Dividends, Splits)
Offset
Option to hide on daily or higher timeframes
MA100: 100-period Simple Moving Average
EMA100: 100-period Exponential Moving Average
Purpose:
This script is ideal for traders who want to track multiple VWAP levels simultaneously while also monitoring the 100-period moving averages for trend analysis. It provides a clean setup without bands or fills, focusing solely on price averages.
Use Cases:
Identify intraday or multi-timeframe VWAP levels
Combine VWAP levels with MA100/EMA100 for support/resistance analysis
Analyze trend direction and momentum using moving averages
TraderDemircan Auto Fibonacci RetracementDescription:
What This Indicator Does:This indicator automatically identifies significant swing high and swing low points within a customizable lookback period and draws comprehensive Fibonacci retracement and extension levels between them. Unlike the manual Fibonacci tool that requires you to constantly redraw levels as price action evolves, this automated version continuously updates the Fibonacci grid based on the most recent major swing points, ensuring you always have current and relevant support/resistance zones displayed on your chart.Key Features:
Automatic Swing Detection: Continuously scans the specified lookback period to find the most significant high and low points, eliminating manual drawing errors
Comprehensive Level Coverage: Plots 16 Fibonacci levels including 7 retracement levels (0.0 to 1.0) and 9 extension levels (1.115 to 3.618)
Top-Down Methodology: Draws from swing high to swing low (right-to-left), following the traditional Fibonacci retracement convention where 100% is at the top
Dual Labeling System: Shows both exact price values and Fibonacci percentages for easy reference
Complete Customization: Individual toggle controls and color selection for each of the 16 levels
Flexible Display Options: Adjust line thickness (1-5), style (solid/dashed/dotted), and extension direction (left/right/both)
Visual Swing Markers: Red diamond at the swing high (starting point) and green diamond at the swing low (ending point)
Optional Trend Line: Connects the two swing points to visualize the overall price movement direction
How It Works:The indicator employs a sophisticated swing point detection algorithm that operates in two stages:Stage 1 - Find the Swing Low (Support Base):
Scans the entire lookback period to identify the lowest low, which becomes the anchor point (0.0 level in traditional retracement terms, though displayed at the bottom of the grid).Stage 2 - Find the Swing High (Resistance Peak):
After identifying the swing low, searches for the highest high that occurred after that low point, establishing the swing range. This creates a valid price movement range for Fibonacci analysis.Fibonacci Calculation Method:
The indicator uses the top-down approach where:
1.0 Level = Swing High (100% retracement, the top)
0.0 Level = Swing Low (0% retracement, the bottom)
Retracement Levels (0.236 to 0.786) = Potential support zones during pullbacks from the high
Extension Levels (1.115 to 3.618) = Potential target zones below the swing low
Formula: Price = SwingHigh - (SwingHigh - SwingLow) × FibonacciLevelThis ensures that 0.0 is at the bottom and extensions (>1.0) plot below the swing low, following standard Fibonacci retracement convention.Fibonacci Levels Explained:Retracement Levels (0.0 - 1.0):
0.0 (Gray): Swing low - the base support level
0.236 (Red): Shallow retracement, first minor support
0.382 (Orange): Moderate retracement, commonly watched support
0.5 (Purple): Psychological midpoint, significant support/resistance
0.618 (Blue - Golden Ratio): The most important retracement level, high-probability reversal zone
0.786 (Cyan): Deep retracement, last defense before full reversal
1.0 (Gray): Swing high - the initial resistance level
Extension Levels (1.115 - 3.618):
1.115 (Green): First extension, minimal downside target
1.272 (Light Green): Minor extension, common profit target
1.414 (Yellow-Green): Square root of 2, mathematical significance
1.618 (Gold - Golden Extension): Primary downside target, most watched extension level
2.0 (Orange-Red): 200% extension, psychological round number
2.382 (Pink): Secondary extension target
2.618 (Purple): Deep extension, major target zone
3.272 (Deep Purple): Extreme extension level
3.618 (Blue): Maximum extension, rare but powerful target
How to Use:For Retracement Trading (Buying Pullbacks in Uptrends):
Wait for price to make a significant move up from swing low to swing high
When price starts pulling back, watch for reactions at key Fibonacci levels
Most common entry zones: 0.382, 0.5, and especially 0.618 (golden ratio)
Enter long positions when price shows reversal signals (candlestick patterns, volume increase) at these levels
Place stop loss below the next Fibonacci level
Target: Return to swing high or higher extension levels
For Extension Trading (Profit Targets):
After price breaks below the swing low (0.0 level), use extensions as profit targets
First target: 1.272 (conservative)
Primary target: 1.618 (golden extension - most commonly reached)
Extended target: 2.618 (for strong trends)
Extreme target: 3.618 (only in powerful trending moves)
For Counter-Trend Trading (Fading Extremes):
When price reaches deep retracements (0.786 or below), look for exhaustion signals
Watch for divergences between price and momentum indicators at these levels
Enter reversal trades with tight stops below the swing low
Target: 0.5 or 0.382 levels on the bounce
For Trend Continuation:
In strong uptrends, shallow retracements (0.236 to 0.382) often hold
Use these as low-risk entry points to join the existing trend
Failure to hold 0.5 suggests weakening momentum
Breaking below 0.618 often indicates trend reversal, not just retracement
Multi-Timeframe Strategy:
Use daily timeframe Fibonacci for major support/resistance zones
Use 4H or 1H Fibonacci for precise entry timing within those zones
Confluence between multiple timeframe Fibonacci levels creates high-probability zones
Example: Daily 0.618 level aligning with 4H 0.5 level = strong support
Settings Guide:Lookback Period (10-500):
Short (20-50): Captures recent swings, more frequent updates, suited for day trading
Medium (50-150): Balanced approach, good for swing trading (default: 100)
Long (150-500): Identifies major market structure, suited for position trading
Higher values = more stable levels but slower to adapt to new trends
Pivot Sensitivity (1-20):
Controls how many candles are required to confirm a swing point
Low (1-5): More sensitive, identifies minor swings (default: 5)
High (10-20): Less sensitive, only major swings qualify
Use higher sensitivity on lower timeframes to filter noise
Individual Level Toggles:
Enable only the levels you actively trade to reduce chart clutter
Common minimalist setup: Show only 0.382, 0.5, 0.618, 1.0, 1.618, 2.618
Comprehensive setup: Enable all levels for maximum information
Visual Customization:
Line Thickness: Thicker lines (3-5) for presentation, thinner (1-2) for trading
Line Style: Solid for primary levels (0.5, 0.618, 1.618), dashed/dotted for secondary
Price Labels: Essential for knowing exact entry/exit prices
Percent Labels: Helpful for quickly identifying which Fibonacci level you're looking at
Extension Direction: Extend right for forward-looking analysis, left for historical context
What Makes This Original:While Fibonacci indicators are common on TradingView, this script's originality comes from:
Intelligent Two-Stage Detection: Unlike simple high/low finders, this uses a sequential approach (find low first, then find the high that occurred after it), ensuring logical price flow representation
Comprehensive Level Set: Includes 16 levels spanning from retracement to extreme extensions, more than most Fibonacci tools
Top-Down Methodology: Properly implements the traditional Fibonacci retracement convention (high to low) rather than the reverse
Automatic Range Validation: Only draws Fibonacci when both swing points are valid and in the correct temporal order
Dual Extension Options: Separate controls for extending lines left (historical context) and right (forward projection)
Smart Label Positioning: Places percentage labels on the left and price labels on the right for clarity
Visual Swing Confirmation: Diamond markers at swing points help users understand why levels are positioned where they are
Important Considerations:
Historical Nature: Fibonacci retracements are based on past price swings; they don't predict future moves, only suggest potential support/resistance
Self-Fulfilling Prophecy: Fibonacci levels work partly because many traders watch them, creating actual support/resistance at those levels
Not All Levels Hold: In strong trends, price may slice through multiple Fibonacci levels without pausing
Context Matters: Fibonacci works best when aligned with other support/resistance (previous highs/lows, moving averages, trendlines)
Volume Confirmation: The most reliable Fibonacci reversals occur with volume spikes at key levels
Dynamic Updates: The levels will redraw as new swing highs/lows form, so don't rely solely on static screenshots
Best Practices:
Don't Trade Blindly: Fibonacci levels are zones, not exact prices. Look for confirmation (candlestick patterns, indicators, volume)
Combine with Price Action: Watch for pin bars, engulfing candles, or doji at key Fibonacci levels
Use Stop Losses: Place stops beyond the next Fibonacci level to give trades room but limit risk
Scale In/Out: Consider entering partial positions at 0.5 and adding more at 0.618 rather than all-in at one level
Check Multiple Timeframes: Daily Fibonacci + 4H Fibonacci convergence = high-probability zone
Respect the 0.618: This golden ratio level is historically the most reliable for reversals
Extensions Need Strong Trends: Don't expect extensions to be hit unless there's clear momentum beyond the swing low
Optimal Timeframes:
Scalping (1-5 minutes): Lookback 20-30, watch 0.382, 0.5, 0.618 only
Day Trading (15m-1H): Lookback 50-100, all retracement levels important
Swing Trading (4H-Daily): Lookback 100-200, focus on 0.5, 0.618, 0.786, and extensions
Position Trading (Daily-Weekly): Lookback 200-500, all levels relevant for long-term planning
Common Fibonacci Trading Mistakes to Avoid:
Wrong Swing Selection: Choosing insignificant swings produces meaningless levels
Premature Entry: Entering as soon as price touches a Fibonacci level without confirmation
Ignoring Trend: Fighting the main trend by buying deep retracements in downtrends
Over-Reliance: Using Fibonacci in isolation without confirming with other technical factors
Static Analysis: Not updating your Fibonacci as market structure evolves
Arbitrary Lookback: Using the same lookback period for all assets and timeframes
Integration with Other Tools:Fibonacci + Moving Averages:
When 0.618 level aligns with 50 or 200 EMA, confluence creates stronger support
Price bouncing from both Fibonacci and MA simultaneously = high-probability trade
Fibonacci + RSI/Stochastic:
Oversold indicators at 0.618 or deeper retracements = strong buy signal
Overbought indicators at swing high (1.0) = potential reversal warning
Fibonacci + Volume Profile:
High-volume nodes aligning with Fibonacci levels create robust support/resistance
Low-volume areas near Fibonacci levels may see rapid price movement through them
Fibonacci + Trendlines:
Fibonacci retracement level + ascending trendline = double support
Breaking both simultaneously confirms trend change
Technical Notes:
Uses ta.lowest() and ta.highest() for efficient swing detection across the lookback period
Implements dynamic line and label arrays for clean redraws without memory leaks
All calculations update in real-time as new bars form
Extension options allow customization without modifying core code
Format.mintick ensures price labels match the symbol's minimum price increment
Tooltip on swing markers shows exact price values for precision
Adaptive Momentum Pressure (AMP)🔹 Adaptive Momentum Pressure (AMP)
A hybrid momentum oscillator that adapts to volatility and trend dynamics.
AMP measures the rate of change of price pressure and automatically adjusts its sensitivity based on market volatility.
It reacts faster in trending markets and smooths out noise during consolidation — helping traders identify genuine momentum shifts early while avoiding whipsaws.
🧠 Core Concept
AMP fuses three elements into one adaptive momentum model:
Normalized Momentum (ROC) – captures directional acceleration of price.
Adaptive Smoothing – the smoothing length dynamically contracts when volatility rises and expands when it falls.
Directional Bias – derived from the short-term EMA slope to weight momentum toward the prevailing trend.
Combined, these form a pressure value oscillating between –100 and +100, revealing when momentum expands or fades.
⚙️ How It Works
Calculates a normalized rate of change (ROC) relative to recent volatility.
Adjusts its effective length using the ATR — more volatile periods shorten the lookback for quicker reaction.
Applies a custom EMA that adapts in real time.
Modulates momentum by a normalized EMA slope (“trend bias”).
Produces a smoothed AMP line with a Signal line and crossover markers.
🔍 How to Read It
Green AMP line rising above Signal → Building bullish momentum.
Red AMP line falling below Signal → Fading or bearish momentum.
White Signal line = smoothed confirmation of trend energy.
Green dots = early bullish crossovers.
Red dots = early bearish crossovers.
Typical interpretations:
AMP crossing above 0 from below → early bullish impulse.
AMP peaking near +50–100 and curling down → potential momentum exhaustion.
Crosses below 0 with red pressure → bearish confirmation.
⚡ Advantages
✅ Adaptive across all markets and timeframes
✅ Built-in trend bias filters false signals
✅ Reacts earlier than RSI/MACD while reducing noise
✅ No manual retuning required
🧩 Suggested Use
Combine with structure or volume tools to confirm breakouts.
Works well as a momentum confirmation filter for entries/exits.
Optimal display: separate oscillator pane (not overlay).
Use it responsibly — AMP is an analytical tool, not financial advice.
RSI with Zone Colors//@version=6
indicator(title="RSI with Zone Colors", shorttitle="RSI+", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
//// ==== INPUT SETTINGS ====
rsiLength = input.int(14, title="RSI Length", minval=1)
source = input.source(close, title="Source")
ob_level = input.int(70, title="Overbought Level")
os_level = input.int(30, title="Oversold Level")
//// ==== RSI CALCULATION ====
change = ta.change(source)
up = ta.ma(math.max(change, 0), rsiLength)
down = ta.ma(-math.min(change, 0), rsiLength)
rsi = down == 0 ? 100 : 100 - (100 / (1 + up / down))
//// ==== COLOR BASED ON ZONES ====
rsiColor = rsi > ob_level ? color.red : rsi < os_level ? color.green : #2962FF
//// ==== PLOT RSI ====
plot(rsi, title="RSI", color=rsiColor, linewidth=2)
//// ==== ZONE LINES ====
hline(ob_level, "Overbought", color=#787B86)
hline(50, "Middle", color=color.new(#787B86, 50))
hline(os_level, "Oversold", color=#787B86)
//// ==== FILL ZONES ====
zoneColor = rsi > ob_level ? color.new(color.red, 85) : rsi < os_level ? color.new(color.green, 85) : na
fill(plot(ob_level, display=display.none), plot(rsi > ob_level ? rsi : ob_level, display=display.none), color=zoneColor, title="OB Fill")
fill(plot(os_level, display=display.none), plot(rsi < os_level ? rsi : os_level, display=display.none), color=zoneColor, title="OS Fill")
//// ==== COLOR CANDLE WHEN RSI IN ZONE ====
barcolor(rsi > ob_level ? color.red : rsi < os_level ? color.green : na)
MTF EMA Trading SystemHere's a comprehensive description and usage guide for publishing your MTF EMA Trading System indicator on TradingView:
MTF EMA Trading System - Pro Edition
📊 Indicator Overview
The MTF EMA Trading System is an advanced multi-timeframe exponential moving average indicator designed for traders seeking high-probability setups with multiple confirmations. Unlike simple EMA crossover systems, this indicator combines trend alignment, momentum, volume analysis, and previous day confluence to generate reliable long and short signals with optimal risk-reward ratios.
✨ Key Features
1. Multi-Timeframe EMA Analysis
Configure 5 independent EMAs (default: 9, 21, 50, 100, 200)
Each EMA can pull data from ANY timeframe (5m, 15m, 1H, 4H, 1D, etc.)
Color-coded lines with customizable widths
End-of-line labels showing EMA period and timeframe (e.g., "EMA200 ")
Perfect for analyzing higher timeframe trends on lower timeframe charts
2. Advanced Signal Generation (Beyond Simple Crosses)
The system requires MULTIPLE confirmations before generating a signal:
LONG Signals Require:
✅ Price action trigger (EMA cross, bounce from key EMA, or pullback setup)
✅ Bullish EMA alignment (EMAs in proper ascending order)
✅ Volume spike confirmation (configurable threshold)
✅ RSI momentum confirmation (bullish but not overbought)
✅ Sufficient EMA separation (avoids choppy/whipsaw conditions)
✅ Price above previous day's low (confluence with support)
SHORT Signals Require:
✅ Price action trigger (EMA cross, rejection from key EMA, or pullback setup)
✅ Bearish EMA alignment (EMAs in proper descending order)
✅ Volume spike confirmation
✅ RSI momentum confirmation (bearish but not oversold)
✅ Sufficient EMA separation
✅ Price below previous day's high (confluence with resistance)
3. Real-Time Dashboard
Displays critical market conditions at a glance:
Overall trend direction (Bullish/Bearish/Neutral)
Price position relative to all EMAs
Volume status (spike or normal)
RSI momentum reading
EMA confluence strength
EMA separation quality
Current ATR value
Previous day high/low levels
Current signal status (LONG/SHORT/WAIT)
Risk-reward ratio
4. Clean Visual Design
Large, clear trade signal markers (green triangles for LONG, red triangles for SHORT)
No chart clutter - only essential information displayed
Customizable signal sizes
Professional color-coded dashboard
5. Built-In Risk Management
ATR-based calculations for stop loss placement
1:2 risk-reward ratio by default
All levels displayed in dashboard for easy reference
🎯 How to Use This Indicator
Step 1: Initial Setup
Add the indicator to your TradingView chart
Configure your preferred timeframes for each EMA:
EMA 9: Leave blank (uses chart timeframe) - Fast reaction to price
EMA 21: Leave blank or set to 15m - Key pivot level
EMA 50: Set to 1H - Intermediate trend
EMA 100: Set to 4H - Major trend filter
EMA 200: Set to 1D - Overall market bias
Adjust signal settings based on your trading style:
Conservative: Keep all confirmations enabled
Aggressive: Disable volume or momentum requirements
Scalping: Reduce min EMA separation to 0.2-0.3%
Step 2: Reading the Dashboard
Before taking any trade, check the dashboard:
Trend: Only take LONG signals in bullish trends, SHORT signals in bearish trends
Position: Confirm price is on the correct side of EMAs
Volume: Green spike = strong confirmation
RSI: Avoid extremes (>70 or <30)
Confluence: "Strong" = high probability setup
Separation: "Good" = trending market, avoid "Low" separation
Step 3: Trade Entry
For LONG Trades:
Wait for green triangle to appear below price
Verify dashboard shows:
Bullish or Neutral trend
Volume spike (preferred)
RSI between 50-70
Good separation
Enter at market or on next bar
Set stop loss at: Entry - (ATR × 2)
Set target at: Entry + (ATR × 4)
For SHORT Trades:
Wait for red triangle to appear above price
Verify dashboard shows:
Bearish or Neutral trend
Volume spike (preferred)
RSI between 30-50
Good separation
Enter at market or on next bar
Set stop loss at: Entry + (ATR × 2)
Set target at: Entry - (ATR × 4)
Step 4: Trade Management
Use the ATR values from dashboard for position sizing
Trail stops using the fastest EMA (EMA 9) as price moves in your favor
Exit partial position at 1:1 risk-reward, let remainder run to target
Exit immediately if dashboard trend changes against your position
💡 Best Practices
Timeframe Recommendations:
Scalping: 1m-5m chart with 5m, 15m, 1H, 4H, 1D EMAs
Day Trading: 5m-15m chart with 15m, 1H, 4H, 1D EMAs
Swing Trading: 1H-4H chart with 4H, 1D, 1W EMAs
Position Trading: 1D chart with 1D, 1W, 1M EMAs
Market Conditions:
Best in: Trending markets with clear direction
Avoid: Tight consolidation, low volume periods, major news events
Filter trades: Only take signals aligned with higher timeframe trend
Risk Management:
Never risk more than 1-2% per trade
Use ATR from dashboard to calculate position size
Respect the stop loss levels
Don't force trades when dashboard shows weak conditions
⚙️ Customization Options
EMA Settings (for each of 5 EMAs):
Length (period)
Timeframe (multi-timeframe capability)
Color
Line width
Show/hide toggle
Signal Settings:
Volume confirmation (on/off)
Volume spike threshold (1.0-3.0x)
Momentum confirmation (on/off)
RSI overbought/oversold levels
Minimum EMA separation percentage
ATR period and stop multiplier
Display Settings:
Show/hide EMA labels
Show/hide trade signals
Signal marker size (tiny/small/normal/large)
Show/hide dashboard
🔔 Alert Setup
The indicator includes 4 alert conditions:
LONG Signal - Fires when all long confirmations are met
SHORT Signal - Fires when all short confirmations are met
Bullish Setup - Early warning when trend aligns bullish with volume
Bearish Setup - Early warning when trend aligns bearish with volume
To set up alerts:
Right-click on chart → Add Alert
Select "MTF EMA Trading System"
Choose your desired alert condition
Configure notification method (popup, email, SMS, webhook)
📈 Performance Tips
Increase Win Rate:
Only trade in direction of higher timeframe trend
Wait for volume spike confirmation
Avoid trades during first 30 minutes and last 15 minutes of session
Skip trades when separation is "Low"
Reduce False Signals:
Increase minimum EMA separation to 0.7-1.0%
Enable all confirmation requirements
Only trade when confluence shows "Strong"
Combine with support/resistance levels
Optimize for Your Market:
Stocks: Use 9, 21, 50, 100, 200 EMAs
Forex: Consider 8, 13, 21, 55, 89 EMAs (Fibonacci)
Crypto: May need wider ATR multiplier (2.5-3.0x) for volatility
⚠️ Important Notes
This indicator is designed to reduce false signals by requiring multiple confirmations
No indicator is 100% accurate - always use proper risk management
Backtesting recommended before live trading
Market conditions change - adjust settings as needed
Works best in liquid markets with clear price action
🎓 Conclusion
The MTF EMA Trading System transforms simple moving average analysis into a sophisticated, multi-confirmation trading strategy. By combining trend alignment, momentum, volume, and confluence, it helps traders identify high-probability setups while filtering out noise and false signals. The clean interface and comprehensive dashboard make it suitable for both beginners and experienced traders across all markets and timeframes.
Moving Averages DTMoving Averages Combo: SMA 30-50-100-200 + EMA 5-8-21 (Golden & Death Cross Ready)
This clean and lightweight indicator plots the most used simple and exponential moving averages in one single script — perfect for swing traders, position traders, and scalpers.
— Simple Moving Averages (Daily timeframe focus):
• SMA 30 (Red) — Early trend detection
• SMA 50 (Blue) — Classic medium-term trend
• SMA 100 (Green) — Institutional reference
• SMA 200 (Orange) — The legendary Golden/Death Cross line
— Fast Exponential Moving Averages (Perfect for pullbacks & entries):
• EMA 5 (Purple) — Ultra-fast reaction
• EMA 8 (Yellow) — Fibonacci-based favorite
• EMA 21 (Black) — 21-day cycle + Fibonacci
Why this combination works so well:
• EMA 8 + EMA 21 = Powerful short-term trend filter (used by thousands of crypto & forex traders)
• SMA 50/200 = Classic Golden & Death Cross signals
• SMA 30/100 = Extra confirmation layers used by banks and funds
Features:
✓ All MAs on a single indicator (no chart clutter)
✓ Clean colors with perfect contrast on light/dark themes
✓ Ready for alerts: set alert on EMA 8 crossing EMA 21 or SMA 50 crossing SMA 200
✓ Works on all markets & timeframes (stocks, forex, crypto, futures)
How to use:
• Bullish signal: Price above SMA 200 + EMA 8 > EMA 21 + SMA 50 > SMA 200
• Bearish signal: Price below SMA 200 + EMA 8 < EMA 21
• Pullback entries: Wait for price to touch EMA 21 in uptrend
Moving Average ProjectionDisplays 2-5 moving averages (solid lines) and projects their future trajectory (dashed lines) based on current trend momentum. This helps you anticipate where key MAs are heading and identify potential future support/resistance levels.
Important: Projections show where MAs would move IF the current trend continues—they're not predictions. Market conditions change, so use projections as planning tools, not trading signals.
General Settings
Number of MAs (2-5) controls how many moving averages display on your chart. Start with 2-3 to avoid clutter. Projection Bars (1-100) determines how far into the future to project—use 10-20 for intraday charts and 20-40 for daily charts. Lookback for Slope (2-100) sets the number of bars used to calculate trend slope, where shorter lookbacks are more responsive and longer ones are smoother. The default of 20 works well for most situations.
Individual MA Settings (MA 1-5)
Each MA has four settings: Length sets the period for the MA (common values are 9, 20, 50, 100, and 200), Type lets you choose between SMA, EMA, WMA, HMA, VWMA, or RMA (EMA is most popular), Color sets the historical MA line color, and Projection Color sets the projected line color (usually a lighter or transparent version of the main color).
MA Types Quick Reference: EMA is most popular and responsive to recent prices. SMA gives equal weight to all periods and is the smoothest. HMA is very responsive with low lag. VWMA incorporates volume data.
Quick Setup Examples
Day Trading: 3 MAs (9/21/50 EMA), 10-15 projection bars, 10-15 lookback
Swing Trading: 2 MAs (50/200 EMA), 20-30 projection bars, 20 lookback
Scalping: 2 MAs (9/20 EMA), 5-10 projection bars, 5-10 lookback
How to Use
Trend Identification: An uptrend shows price above rising MAs with projections pointing up. A downtrend shows price below falling MAs with projections pointing down. Consolidation appears as flat MAs with horizontal projections.
Support & Resistance: Rising MA projections act as future dynamic support levels, while falling MA projections act as future dynamic resistance levels.
Anticipating Changes: Watch for projected MA crossovers before they happen. When projections converge, expect volatility or consolidation. Steep projections suggest unsustainable trends, so be cautious. Flat projections indicate ranging markets.
Trade Planning: Check the current trend using MA alignment, then look at projections to gauge trend continuation likelihood. Use projected MA levels for potential targets or stop placement.
Important Tips
When Projections Work Best: Projections are most reliable in stable trending markets with consistent momentum, low volatility environments, and away from major news events.
When to Be Cautious: Use caution during high volatility or choppy price action, around major economic releases, when projections show extreme or parabolic angles, and during trend transitions.
Combine With Other Analysis: Don't trade projections alone. Use them alongside price action, volume, support and resistance levels, and other indicators for confirmation.
Best Practices
Start with 2-3 MAs to avoid chart clutter. Match your projection and lookback bars to your trading timeframe. Use consistent color schemes for quick interpretation. Adjust settings as market conditions change. Always use proper risk management—projections are planning tools, not guarantees.
Troubleshooting
Projections not showing: Check that Projection Bars > 0 and you're viewing the most recent bar
Chart too cluttered: Reduce number of MAs or increase projection color transparency
Projections too volatile: Increase lookback bars or switch to EMA/SMA from HMA
Can't see certain MAs: Verify "Number of MAs" setting includes them (MA 3 won't show if set to 2)
Clock&Flow – Market Pulse IndicatorClock&Flow – Market Pulse Indicator
1) General Purpose
The Market Pulse Indicator is designed to visualize the strength and direction of market flow in a clear, intuitive way.
Unlike common volume or momentum indicators, it blends three essential dimensions — price velocity, normalized volume, and volatility (ATR) — to highlight when market pressure is truly meaningful.
It helps identify genuine liquidity inflows/outflows, potential exhaustion zones, and moments of compression or expansion within the price structure.
2) Data Sources
All data is directly taken from the current chart’s feed on TradingView:
Price (close): to measure relative price change.
Volume: to detect the intensity of market participation (normalized to average).
ATR (Average True Range): to evaluate volatility relative to price levels.
No external data or off-platform sources are used.
3) Logic and Calculation Steps
Price Velocity: calculates the percentage change between the current close and the close N bars ago.
priceChange = (close - close ) / close
Normalized Volume: compares current volume to its moving average over the same period.
volNorm = volume / sma(volume, length)
Normalized Volatility: ATR divided by price to adjust for instrument scale.
atrNorm = atr(length) / close
Combination : multiplies the three components into one raw value that represents market pulse intensity.
rawPulse = priceChange * volNorm * (1 + atrNorm)
Smoothing: a moving average (smoothLen) is applied to create a cleaner and more readable oscillator line.
flowPulse = sma(rawPulse * multiplier, smoothLen)
4) Parameters (Default Settings)
length (20): analysis period for price change, volume, and ATR.
smoothLen (5): smoothing factor; higher values reduce noise.
multiplier (100): scales the output for readability; adjust to fit chart scale.
5) How to Read the Indicator
Market Pulse > 0 (green): net inflow of liquidity; buying pressure dominates.
Market Pulse < 0 (red): net outflow of liquidity; selling pressure dominates.
Near 0: neutral phase; market balance or consolidation.
Sudden peaks: strong bursts of flow — often coincide with news releases or session overlaps.
Confirmations: use as a second-level filter before entering trades or to confirm momentum behind a breakout.
6) Divergences
Divergences between price and Market Pulse are key signals of weakening flow strength:
Bullish divergence: price forms lower lows while Market Pulse forms higher lows → selling pressure is fading; potential reversal or bounce.
Bearish divergence: price forms higher highs while Market Pulse fails to confirm → buying momentum is losing strength; potential correction ahead.
For reliability, look for divergences on higher timeframes (H4, Daily).
On lower timeframes, treat them as early warnings.
7) Typical Use Cases
Breakout confirmation: price breaks resistance with a rising Market Pulse → confirms genuine participation.
False signal filter: price breaks a level but Market Pulse remains flat/negative → likely fake breakout.
Pullback entry: after a breakout, wait for a short retracement and a new positive pulse → safer entry point.
Exit signal: if you’re long and Market Pulse suddenly turns negative with strong volume → consider partial exit or tighter stops.
8) Recommended Timeframes
Intraday / Scalping: 5–30 min charts with length 10–14, smoothLen 3–5.
Swing trading: 1h–4h charts with length 20–50.
Position trading: Daily charts with larger length (50–100) for smoother data.
Always optimize parameters to the specific asset — there are no universal settings.
9) Limitations
This indicator is not a trading system — it’s a decision-support tool.
Results depend on the quality of the volume data available for the symbol.
Performance and sensitivity are influenced by length, smoothing, and multiplier values — always test before live trading.
Use alongside sound risk and money management.
10) Disclaimer
This script is provided for educational purposes only and does not constitute financial advice.
Trading and investing involve significant risk, including the potential loss of capital.
Always test indicators in simulation environments and make independent decisions based on your own analysis and risk tolerance.
Italiano
1) Scopo generale
Flow Pulse è un oscillatore pensato per visualizzare la forza e la direzione del flusso di mercato in modo immediato. Non è un semplice indicatore di volume né una copia di RSI/MACD: combina tre dimensioni fondamentali — variazione di prezzo, volume normalizzato e volatilità — per mettere in evidenza i momenti in cui la pressione dei partecipanti è realmente significativa.
È ideale per identificare: entrate guidate da flussi reali, potenziali esaurimenti, momenti di compressione/espansione del movimento e segnali di conferma per breakout o rimbalzi.
2) Dati utilizzati
L’indicatore usa esclusivamente dati disponibili sulla piattaforma TradingView del grafico corrente:
price (close) — per calcolare la variazione percentuale del prezzo;
volume per misurare l’intensità degli scambi (normalizzato su media);
ATR (Average True Range) — per normalizzare la volatilità rispetto al prezzo;
Tutti i feed (prezzo e volume) sono quelli forniti dall’exchange/fornitore dati collegato al simbolo sul grafico.
3) Logica e passaggi di calcolo
Velocità del prezzo: calcolo della variazione percentuale tra la chiusura corrente e la chiusura N barre fa:
priceChange = (close - close ) / close
— misura la direzione e magnitudine del movimento in termine relativo.
Volume normalizzato: rapporto tra il volume corrente e la media mobile semplice del volume su length barre:
volNorm = volume / sma(volume, length)
— evidenzia volumi anomali rispetto alla media.
Volatilità normalizzata (ATR): rapporto ATR/close per rendere la volatilità comparabile across price levels:
atrNorm = atr(length) / close
Combinazione: il prodotto di questi fattori (con un piccolo offset su ATR) genera un valore grezzo:
rawPulse = priceChange * volNorm * (1 + atrNorm)
— se priceChange e volNorm sono positivi e l’ATR è presente, il rawPulse sarà significativamente positivo.
Smoothing: media mobile semplice (SMA) applicata al rawPulse e moltiplicazione per un fattore scalare (multiplier) per portare il range su livelli leggibili:
flowPulse = sma(rawPulse * multiplier, smoothLen)
4) Parametri esposti (default consigliati)
length (periodo analisi) — default 20: influenza calcolo Δ% e media volumi; allunga la finestra storica.
smoothLen (smussamento) — default 5: smoothing del segnale per ridurre rumore.
multiplier — default 100: fattore di scala per rendere l’oscillatore più leggibile.
5) Interpretazione pratica dei valori
FlowPulse > 0 (verde): predominanza di flusso d’ingresso — pressione d’acquisto. Maggiore il valore, più forte la convinzione (volume + movimento + volatilità).
FlowPulse < 0 (rosso): predominanza di flusso in uscita — pressione di vendita.
Vicino a 0: assenza di flussi netti chiari; mercato piatto o bilanciato.
Picchi repentini: indicano accelerate di flusso — spesso coincidono con rotture, open/close session, news.
Sostegno al trade: usa FlowPulse come conferma prima di entrare su breakout o come avviso di attenzione su esaurimenti.
6) Divergenze (come leggerle)
Le divergenze tra prezzo e FlowPulse sono segnali importanti:
Divergenza rialzista (bullish divergence): prezzo fa nuovi minimi mentre FlowPulse non fa nuovi minimi (o forma minimo relativo più alto) → indica che la spinta di vendita non è supportata da volume/volatilità, possibile inversione/rimbalzo.
Divergenza ribassista (bearish divergence): prezzo fa nuovi massimi mentre FlowPulse non li conferma (o forma massimo relativo più basso) → la spinta d’acquisto è “debole”, possibile esaurimento e inversione.
Note pratiche: cercare divergenze su timeframe maggiori (H4, D) per maggiore attendibilità; sui timeframe minori prendere solo come early warning.
7) Esempi d’uso operativo
Conferma breakout: prezzo rompe resistenza + FlowPulse positivo e crescente → breakout più probabile e con volumi reali.
Filtro per falsi segnali: prezzo rompe ma FlowPulse è piatto/negativo → alto rischio di false breakout.
Entrata per pullback: dopo breakout, attendere un pullback con FlowPulse che torna positivo → ingresso più prudente.
Gestione delle uscite: se sei long e FlowPulse improvvisamente si inverte in negativo su volumi elevati → considerare riduzione posizione o stop.
8) Timeframe consigliati
Intraday / Scalping: M5–M30 con length ridotto (es. 10–14) e smoothLen piccolo.
Swing trading: H1–H4 con length 20–50.
Position trading: D1 con length maggiore per filtrare rumore.
Testa i parametri sul tuo asset e timeframe; nessun parametro è universale.
9) Limitazioni e avvertenze
L’indicatore non è un sistema di trading completo: è un tool di informazione e timing.
Dipende dalla qualità dei dati di volume del simbolo: su alcuni titoli/mercati (es. alcuni ETF, Forex su certi broker) il volume può essere parziale o non rappresentativo.
I valori di margine/multiplier e smoothing influenzano sensibilmente sensibilità e falsi segnali: backtest e ottimizzazione sono raccomandati.
Non usare il solo FlowPulse per entrare su leva elevata senza gestione del rischio12) Disclaimer da inserire
Disclaimer: Questo indicatore è fornito solo a scopo didattico e non costituisce consulenza finanziaria. L’uso comporta rischi: valuta sempre la gestione del rischio e testa su conto demo prima dell’applicazione in reale.
lower_tfLibrary "lower_tf"
█ OVERVIEW
This library is an enhanced (opinionated) version of the library originally developed by PineCoders contained in lower_tf .
It is a Pine Script® programming tool for advanced lower-timeframe selection and intra-bar analysis.
█ CONCEPTS
Lower Timeframe Analysis
Lower timeframe analysis refers to the analysis of price action and market microstructure using data from timeframes shorter than the current chart period. This technique allows traders and analysts to gain deeper insights into market dynamics, volume distribution, and the price movements occurring within each bar on the chart. In Pine Script®, the request.security_lower_tf() function allows this analysis by accessing intrabar data.
The library provides a comprehensive set of functions for accurate mapping of lower timeframes, dynamic precision control, and optimized historical coverage using request.security_lower_tf().
█ IMPROVEMENTS
The original library implemented ten precision levels. This enhanced version extends that to twelve levels, adding two ultra-high-precision options:
Coverage-Based Precision (Original 5 levels):
1. "Covering most chart bars (least precise)"
2. "Covering some chart bars (less precise)"
3. "Covering fewer chart bars (more precise)"
4. "Covering few chart bars (very precise)"
5. "Covering the least chart bars (most precise)"
Intrabar-Count-Based Precision (Expanded from 5 to 7 levels):
6. "~12 intrabars per chart bar"
7. "~24 intrabars per chart bar"
8. "~50 intrabars per chart bar"
9. "~100 intrabars per chart bar"
10. "~250 intrabars per chart bar"
11. "~500 intrabars per chart bar" ← NEW
12. "~1000 intrabars per chart bar" ← NEW
The key enhancements in this version include:
1. Extended Precision Range: Adds two ultra-high-precision levels (~500 and ~1000 intrabars) for advanced microstructure analysis requiring maximum granularity.
2. Market-Agnostic Implementation: Eliminates the distinction between crypto/forex and traditional markets, removing the mktFactor variable in favor of a unified, predictable approach across all asset classes.
3. Explicit Precision Mapping: Completely refactors the timeframe selection logic using native Pine Script® timeframe properties ( timeframe.isseconds , timeframe.isminutes , timeframe.isdaily , timeframe.isweekly , timeframe.ismonthly ) and explicit multiplier-based lookup tables. The original library used minute-based calculations with market-dependent conditionals that produced inconsistent results. This version provides deterministic, predictable mappings for every chart timeframe, ensuring consistent precision behavior regardless of asset type or market hours.
An example of the differences can be seen side-by-side in the chart below, where the original library is on the left and the enhanced version is on the right:
█ USAGE EXAMPLE
// This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © andre_007
//@version=6
indicator("lower_tf Example")
import andre_007/lower_tf/1 as LTF
import PineCoders/Time/5 as PCtime
//#region ———————————————————— Example code
// ————— Constants
color WHITE = color.white
color GRAY = color.gray
string LTF1 = "Covering most chart bars (least precise)"
string LTF2 = "Covering some chart bars (less precise)"
string LTF3 = "Covering less chart bars (more precise)"
string LTF4 = "Covering few chart bars (very precise)"
string LTF5 = "Covering the least chart bars (most precise)"
string LTF6 = "~12 intrabars per chart bar"
string LTF7 = "~24 intrabars per chart bar"
string LTF8 = "~50 intrabars per chart bar"
string LTF9 = "~100 intrabars per chart bar"
string LTF10 = "~250 intrabars per chart bar"
string LTF11 = "~500 intrabars per chart bar"
string LTF12 = "~1000 intrabars per chart bar"
string TT_LTF = "This selection determines the approximate number of intrabars analyzed per chart bar. Higher numbers of
intrabars produce more granular data at the cost of less historical bar coverage, because the maximum number of
available intrabars is 200K.
\n\nThe first five options set the lower timeframe based on a specified relative level of chart bar coverage.
The last five options set the lower timeframe based on an approximate number of intrabars per chart bar."
string TAB_TXT = "Uses intrabars at the {0} timeframe.\nAvg intrabars per chart bar:
{1,number,#.#}\nChart bars covered: {2} of {3} ({4,number,#.##}%)"
string ERR_TXT = "No intrabar information exists at the {1}{0}{1} timeframe."
// ————— Inputs
string ltfModeInput = input.string(LTF3, "Intrabar precision", options = , tooltip = TT_LTF)
bool showInfoBoxInput = input.bool(true, "Show information box ")
string infoBoxSizeInput = input.string("normal", "Size ", inline = "01", options = )
string infoBoxYPosInput = input.string("bottom", "↕", inline = "01", options = )
string infoBoxXPosInput = input.string("right", "↔", inline = "01", options = )
color infoBoxColorInput = input.color(GRAY, "", inline = "01")
color infoBoxTxtColorInput = input.color(WHITE, "T", inline = "01")
// ————— Calculations
// @variable A "string" representing the lower timeframe for the data request.
// NOTE:
// This line is a good example where using `var` in the declaration can improve a script's performance.
// By using `var` here, the script calls `ltf()` only once, on the dataset's first bar, instead of redundantly
// evaluating unchanging strings on every bar. We only need one evaluation of this function because the selected
// timeframe does not change across bars in this script.
var string ltfString = LTF.ltf(ltfModeInput, LTF1, LTF2, LTF3, LTF4, LTF5, LTF6, LTF7, LTF8, LTF9, LTF10, LTF11, LTF12)
// @variable An array containing all intrabar `close` prices from the `ltfString` timeframe for the current chart bar.
array intrabarCloses = request.security_lower_tf(syminfo.tickerid, ltfString, close)
// Calculate the intrabar stats.
= LTF.ltfStats(intrabarCloses)
int chartBars = bar_index + 1
// ————— Visuals
// Plot the `avgIntrabars` and `intrabars` series in all display locations.
plot(avgIntrabars, "Average intrabars", color.silver, 6)
plot(intrabars, "Intrabars", color.blue, 2)
// Plot the `chartBarsCovered` and `chartBars` values in the Data Window and the script's status line.
plot(chartBarsCovered, "Chart bars covered", display = display.data_window + display.status_line)
plot(chartBars, "Chart bars total", display = display.data_window + display.status_line)
// Information box logic.
if showInfoBoxInput
// @variable A single-cell table that displays intrabar information.
var table infoBox = table.new(infoBoxYPosInput + "_" + infoBoxXPosInput, 1, 1)
// @variable The span of the `ltfString` timeframe formatted as a number of automatically selected time units.
string formattedLtf = PCtime.formattedNoOfPeriods(timeframe.in_seconds(ltfString) * 1000)
// @variable A "string" containing the formatted text to display in the `infoBox`.
string txt = str.format(
TAB_TXT, formattedLtf, avgIntrabars, chartBarsCovered, chartBars, chartBarsCovered / chartBars * 100, "'"
)
// Initialize the `infoBox` cell on the first bar.
if barstate.isfirst
table.cell(
infoBox, 0, 0, txt, text_color = infoBoxTxtColorInput, text_size = infoBoxSizeInput,
bgcolor = infoBoxColorInput
)
// Update the cell's text on the latest bar.
else if barstate.islast
table.cell_set_text(infoBox, 0, 0, txt)
// Raise a runtime error if no intrabar data is available.
if ta.cum(intrabars) == 0 and barstate.islast
runtime.error(str.format(ERR_TXT, ltfString, "'"))
//#endregion
█ EXPORTED FUNCTIONS
ltf(userSelection, choice1, choice2, ...)
Returns the optimal lower timeframe string based on user selection and current chart timeframe. Dynamically calculates precision to balance granularity with historical coverage within the 200K intrabar limit.
ltfStats(intrabarValues)
Analyzes an intrabar array returned by request.security_lower_tf() and returns statistics: number of intrabars in current bar, total chart bars covered, and average intrabars per bar.
█ CREDITS AND LICENSING
Original Concept : PineCoders Team
Original Lower TF Library :
License : Mozilla Public License 2.0
COT Index v.2COT Index v.2 Indicator
( fix for extreme values)
📊 Overview
The COT (Commitment of Traders) Index Indicator transforms raw COT data into normalized indices ranging from 0-100, with extensions to 120 and -20 for extreme market conditions. This powerful tool helps traders analyze institutional positioning and market sentiment by tracking the net long positions of three key market participant groups.
🎯 What It Does
This indicator converts weekly CFTC Commitment of Traders data into easy-to-read oscillator format, showing:
Commercial Index (Blue Line) - Smart money/hedgers positioning
NonCommercial Index (Orange Line) - Large speculators/funds positioning
Nonreportable Index (Red Line) - Small traders positioning
📈 Key Features
Smart Scaling Algorithm
0-100 Range: Normal market conditions based on recent price action
120 Level: Extreme bullish positioning (above historical maximum)
-20 Level: Extreme bearish positioning (below historical minimum)
Dual Time Frame Analysis
Short Period (26 weeks default): For current market scaling
Historical Period (156 weeks default): For extreme condition detection
Flexible Data Sources
Futures Only reports
Futures and Options combined reports
Automatic symbol detection with manual overrides for HG and LBR
🔧 Customizable Settings
Data Configuration
Adjustable lookback periods for both current and historical analysis
Report type selection (Futures vs Futures & Options)
Display Options
Toggle individual trader categories on/off
Customizable reference lines (overbought/oversold levels)
Optional 0/100 boundary lines
Adjustable line widths and colors
Reference Levels
Upper Bound: 120 (extreme bullish)
Overbought: 80 (default)
Midline: 50 (neutral)
Oversold: 20 (default)
Lower Bound: -20 (extreme bearish)
💡 Trading Applications
Contrarian Signals
High Commercial Index + Low NonCommercial Index = Potential bullish reversal
Low Commercial Index + High NonCommercial Index = Potential bearish reversal
Market Sentiment Analysis
Track institutional vs retail positioning divergences
Identify extreme market conditions requiring attention
Monitor smart money accumulation/distribution patterns
Confirmation Tool
Use alongside technical analysis for trade confirmation
Validate breakouts with positioning data
Assess market structure changes
📊 Visual Elements
Status Table: Displays current settings and symbol information
Color-Coded Lines: Easy identification of each trader category
Reference Levels: Clear overbought/oversold boundaries
Extreme Indicators: Visual cues for unusual market conditions
⚠️ Important Notes
COT data is released weekly on Fridays (Tuesday data)
Best suited for weekly and daily timeframes
Requires symbols with available CFTC data
Works automatically for most futures contracts
🎯 Best Practices
Use in conjunction with price action analysis
Look for divergences between price and positioning
Pay special attention to extreme readings (120/-20 levels)
Consider all three indices together for complete market picture
Allow for data lag (3-day delay from CFTC)
This indicator is ideal for swing traders, position traders, and anyone interested in understanding the positioning dynamics of professional vs retail market participants.
Central Limit Theorem Reversion IndicatorDear TV community, let me introduce you to the first-ever Central Limit Theorem indicator on TradingView.
The Central Limit Theorem is used in statistics and it can be quite useful in quant trading and understanding market behaviors.
In short, the CLT states: "When you take repeated samples from any population and calculate their averages, those averages will form a normal (bell curve) distribution—no matter what the original data looks like."
In this CLT indicator, I use statistical theory to identify high-probability mean reversion opportunities in the markets. It calculates statistical confidence bands and z-scores to identify when price movements deviate significantly from their expected distribution, signaling potential reversion opportunities with quantifiable probability levels.
Mathematical Foundation
The Central Limit Theorem (CLT) says that when you average many data points together, those averages will form a predictable bell-curve pattern, even if the original data is completely random and unpredictable (which often is in the markets). This works no matter what you're measuring, and it gets more reliable as you use more data points.
Why using it for trading?
Individual price movements seem random and chaotic, but when we look at the average of many price movements, we can actually predict how they should behave statistically. This lets us spot when prices have moved "too far" from what's normal—and those extreme moves tend to snap back (mean reversion).
Key Formula:
Z = (X̄ - μ) / (σ / √n)
Where:
- X̄ = Sample mean (average return over n periods)
- μ = Population mean (long-term expected return)
- σ = Population standard deviation (volatility)
- n = Sample size
- σ/√n = Standard error of the mean
How I Apply CLT
Step 1: Calculate Returns
Measures how much price changed from one bar to the next (using logarithms for better statistical properties)
Step 2: Average Recent Returns
Takes the average of the last n returns (e.g., last 100 bars). This is your "sample mean."
Step 3: Find What's "Normal"
Looks at historical data to determine: a) What the typical average return should be (the long-term mean) and b) How volatile the market usually is (standard deviation)
Step 4: Calculate Standard Error
Determines how much sample averages naturally vary. Larger samples = smaller expected variation.
Step 5: Calculate Z-Score
Measures how unusual the current situation is.
Step 6: Draw Confidence Bands
Converts these statistical boundaries into actual price levels on your chart, showing where price is statistically expected to stay 95% and 99% of the time.
Interpretation & Usage
The Z-Score:
The z-score tells you how statistically unusual the current price deviation is:
|Z| < 1.0 → Normal behavior, no action
|Z| = 1.0 to 1.96 → Moderate deviation, watch closely
|Z| = 1.96 to 2.58 → Significant deviation (95%+), consider entry
|Z| > 2.58 → Extreme deviation (99%+), high probability setup
The Confidence Bands
- Upper Red Bands: 95% and 99% overbought zones → Expect mean reversion downward as the price is not likely to cross these lines.
- Center Gray Line: Statistical expectation (fair value)
- Lower Blue Bands: 95% and 99% oversold zones → Expect mean reversion upward
Trading Logic:
- When price exceeds the upper 95% band (z-score > +1.96), there's only a 5% probability this is random noise → Strong sell/short signal
- When price falls below the lower 95% band (z-score < -1.96), there's a 95% statistical expectation of upward reversion → Strong buy/long signal
Background Gradient
The background color provides real-time visual feedback:
- Blue shades: Oversold conditions, expect upward reversion
- Red shades: Overbought conditions, expect downward reversion
- Intensity: Darker colors indicate stronger statistical significance
Trading Strategy Examples
Hypothetically, this is how the indicator could be used:
- Long: Z-score < -1.96 (below 95% confidence band)
- Short: Z-score > +1.96 (above 95% confidence band)
- Take profit when price returns to center line (Z ≈ 0)
Input Parameters
Sample Size (n) - Default: 100
Lookback Period (m) - Default: 100
You can also create alerts based on the indicator.
Final notes:
- The indicator uses logarithmic returns for better statistical properties
- Converts statistical bands back to price space for practical use
- Adaptive volatility: Bands automatically widen in high volatility, narrow in low volatility
- No repainting: yay! All calculations use historical data only
Feedback is more than welcome!
Henri
cd_correlation_analys_Cxcd_correlation_analys_Cx
General:
This indicator is designed for correlation analysis by classifying stocks (487 in total) and indices (14 in total) traded on Borsa İstanbul (BIST) on a sectoral basis.
Tradingview's sector classifications (20) have been strictly adhered to for sector grouping.
Depending on user preference, the analysis can be performed within sectors, between sectors, or manually (single asset).
Let me express my gratitude to the code author, @fikira, beforehand; you will find the reason for my thanks in the context.
Details:
First, let's briefly mention how this indicator could have been prepared using the classic method before going into details.
Classically, assets could be divided into groups of forty (40), and the analysis could be performed using the built-in function:
ta.correlation(source1, source2, length) → series float.
I chose sectoral classification because I believe there would be a higher probability of assets moving together, rather than using fixed-number classes.
In this case, 21 arrays were formed with the following number of elements:
(3, 11, 21, 60, 29, 20, 12, 3, 31, 5, 10, 11, 6, 48, 73, 62, 16, 19, 13, 34 and indices (14)).
However, you might have noticed that some arrays have more than 40 elements. This is exactly where @Fikira's indicator came to the rescue. When I examined their excellent indicator, I saw that it could process 120 assets in a single operation. (I believe this was the first limit overrun; thanks again.)
It was amazing to see that data for 3 pairs could be called in a single request using a special method.
You can find the details here:
When I adapted it for BIST, I found it sufficient to call data for 2 pairs instead of 3 in a single go. Since asset prices are regular and have 2 decimal places, I used a fixed multiplier of $10^8$ and a fixed decimal count of 2 in Fikira's formulas.
With this method, the (high, low, open, close) values became accessible for each asset.
The summary up to this point is that instead of the ready-made formula + groups of 40, I used variable-sized groups and the method I will detail now.
Correlation/harmony/co-movement between assets provides advantages to market participants. Coherent assets are expected to rise or fall simultaneously.
Therefore, to convert co-movement into a mathematical value, I defined the possible movements of the current candle relative to the previous candle bar over a certain period (user-defined). These are:
Up := high > high and low > low
Down := high < high and low < low
Inside := high <= high and low >= low
Outside := high >= high and low <= low and NOT Inside.
Ignore := high = low = open = close
If both assets performed the same movement, 1 was added to the tracking counter.
If (Up-Up), (Down-Down), (Inside-Inside), or (Outside-Outside), then counter := counter + 1.
If the period length is 100 and the counter is 75, it means there is 75% co-movement.
Corr = counter / period ($75/100$)
Average = ta.sma(Corr, 100) is obtained.
The highest coefficients recorded in the array are presented to the user in a table.
From the user menu options, the user can choose to compare:
• With assets in its own sector
• With assets in the selected sector
• By activating the confirmation box and manually entering a single asset for comparison.
Table display options can be adjusted from the Settings tab.
In the attached examples:
Results for AKBNK stock from the Finance sector compared with GARAN stock from the same sector:
Timeframe: Daily, Period: 50 => Harmony 76% (They performed the same movement in 38 out of 50 bars)
Comment: Opposite movements at swing high and low levels may indicate a change in the direction of the price flow (SMT).
Looking at ASELS from the Electronic Technology sector over the last 30 daily candles, they performed the same movements by 40% with XU100, 73.3% (22/30) with XUTEK (Technology Index), and 86.9% according to the averages.
Comment: It is more appropriate to follow ASELS stock with XUTEK (Technology index) instead of the general index (XU100). Opposite movements at swing high and low levels may indicate a change in the direction of the price flow (SMT).
Again, when ASELS stock is taken on H1 instead of daily, and the length is 100 instead of 30, the harmony rate is seen to be 87%.
Please share your thoughts and criticisms regarding the indicator, which I prepared with a bit of an educational purpose specifically for BIST.
Happy trading.
pine script tradingbot - many ema oscillator## 🧭 **Many EMA Oscillator (TradingView Pine Script Indicator)**
*A multi-layer EMA differential oscillator for trend strength and momentum analysis*
---
### 🧩 **Overview**
The **Many EMA Oscillator** is a **TradingView Pine Script indicator** designed to help traders visualize **trend direction**, **momentum strength**, and **multi-timeframe EMA alignment** in one clean oscillator panel.
It’s a **custom EMA-based trend indicator** that shows how fast or slow different **Exponential Moving Averages (EMAs)** are expanding or contracting — helping you identify **bullish and bearish momentum shifts** early.
This **Pine Script EMA indicator** is especially useful for traders looking to combine multiple **EMA signals** into one **momentum oscillator** for better clarity and precision.
---
### ⚙️ **How It Works**
1. **Multiple EMA Layers:**
The indicator calculates seven **EMAs** (default: 20, 50, 100, 150, 200, 300) and applies a **smoothing filter** using another EMA (default smoothing = 20).
This removes short-term noise and gives a smoother, professional-grade momentum reading.
2. **EMA Gap Analysis:**
The oscillator measures the **difference between consecutive EMAs**, revealing how trend layers are separating or converging.
```
diff1 = EMA(20) - EMA(50)
diff2 = EMA(50) - EMA(100)
diff3 = EMA(100) - EMA(150)
diff4 = EMA(150) - EMA(200)
diff5 = EMA(200) - EMA(300)
```
These gaps (or “differentials”) show **trend acceleration or compression**, acting like a **multi-EMA MACD system**.
3. **Color-Coded Visualization:**
Each differential (`diff1`–`diff5`) is plotted as a **histogram**:
- 🟢 **Green bars** → EMAs expanding → bullish momentum growing
- 🔴 **Red bars** → EMAs contracting → bearish momentum or correction
This gives a clean, compact view of **trend strength** without cluttering your chart.
4. **Automatic Momentum Signals:**
- **🟡 Up Triangle** → All EMA gaps increasing → strong bullish trend alignment
- **⚪ Down Triangle** → All EMA gaps decreasing → trend weakening or bearish transition
---
### 📊 **Inputs**
| Input | Default | Description |
|-------|----------|-------------|
| `smmoth_emas` | 20 | Smoothing factor for all EMAs |
| `Length2`–`Length7` | 20–300 | Adjustable EMA periods |
| `Length21`, `Length31`, `Length41`, `Length51` | Optional | For secondary EMA analysis |
---
### 🧠 **Interpretation Guide**
| Observation | Meaning |
|--------------|----------|
| Increasing green bars | Trend acceleration and bullish continuation |
| Decreasing red bars | Trend exhaustion or sideways consolidation |
| Yellow triangles | All EMA layers aligned bullishly |
| White triangles | All EMA layers aligned bearishly |
This **EMA oscillator for TradingView** simplifies **multi-EMA trading strategies** by showing alignment strength in one place.
It works great for **swing traders**, **scalpers**, and **trend-following systems**.
---
### 🧪 **Best Practices for Use**
- Works on **all TradingView timeframes** (1m, 5m, 1h, 1D, etc.)
- Suitable for **stocks, forex, crypto, and indices**
- Combine with **RSI**, **MACD**, or **price action** confirmation
- Excellent for detecting **EMA compression zones**, **trend continuation**, or **momentum shifts**
- Can be used as part of a **multi-EMA trading strategy** or **trend strength indicator setup**
---
### 💡 **Why It Stands Out**
- 100% built in **Pine Script v6**
- Optimized for **smooth EMA transitions**
- Simple color-coded momentum visualization
- Professional-grade **multi-timeframe trend oscillator**
This is one of the most **lightweight and powerful EMA oscillators** available for TradingView users who prefer clarity over clutter.
---
### ⚠️ **Disclaimer**
This indicator is published for **educational and analytical purposes only**.
It does **not provide financial advice**, buy/sell signals, or investment recommendations.
Always backtest before live use and trade responsibly.
---
### 👨💻 **Author**
Developed by **@algo_coders**
Built in **Pine Script v6** on **TradingView**
Licensed under the (mozilla.org)
NASDAQ Trading System with PivotsThis TradingView indicator, designed for the 30-minute NASDAQ (^IXIC) chart, guides QQQ options trading using a trend-following strategy. It plots a 20-period SMA (blue) and a 100-period SMA (red), with an optional 250-period SMA (orange) inspired by rauItrades' NASDAQ SMA outfit. A bullish crossover (20 SMA > 100 SMA) triggers a green "BUY" triangle below the bar, signaling a potential long position in QQQ, while a bearish crossunder (20 SMA < 100 SMA) shows a red "SELL" triangle above, indicating a short or exit. The background colors green (bullish) or red (bearish) for trend bias. Orange circles (recent highs) and purple circles (recent lows) mark support/resistance levels using 5-bar pivot points.
