Syndicate📘 Syndicate Indicator – Description
The Syndicate Indicator is a dynamic, precision-based visual tool for identifying trend direction, major reversals, and institutional golden pocket zones. Designed for clarity, minimalism, and sniper-level entries, it helps traders navigate market structure with confidence.
🔹 Trend Emoji Guide (Top-Right Corner Table):
• 📈✅ – Strong Uptrend Detected (Potential Long Bias)
• 📉✅ – Strong Downtrend Detected (Potential Short Bias)
• 🌀 – Market in Limbo (Neutral/No Trade Zone)
These trend cues are calculated using multi-layer confluence of EMAs, WaveTrend oscillator, and volume trend.
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🟨 Golden Pocket Lines
The script automatically plots high-confluence golden pocket zones from:
• Previous Day (Orange Dotted Lines)
• Previous Week (Fuchsia Dotted Lines)
• Previous Month (Teal Dotted Lines)
Golden pockets only appear when price is nearby (within a % range you can configure) to reduce chart clutter and highlight relevance.
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🔴 Reversal Signal Dots
Small dots (minimal size) show only the strongest reversal confluence:
• White dot = Bullish reversal opportunity
• Purple dot = Bearish reversal opportunity
These appear sparingly, using WaveTrend extremes + volume confirmation for high conviction signals.
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📜 Trading Rules (Beginner-Friendly)
✅ When to Consider a Long (NFA):
• Top-right emoji shows 📈✅
• Price is above both EMAs (50 & 200)
• WaveTrend confirms strong upward pressure
• Volume is above average
• Bonus: White dot or price bouncing from a golden pocket
✅ When to Consider a Short (NFA):
• Top-right emoji shows 📉✅
• Price is below both EMAs
• WaveTrend is trending down with pressure
• Volume is above average (bearish)
• Bonus: Purple dot or price rejecting a golden pocket
⚠️ When to Wait / Avoid Trading:
• Emoji shows 🌀 (limbo)
• Price is between the EMAs
• Low volume or choppy price action
• No dot signal or golden pocket interaction
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📌 Best Practices:
• Use on timeframes 5m–4H for best balance of precision and context
• Combine with Spiderline zones, SFPs, and divergence for stacked confluence
• Use alerts to stay notified when strong trend shifts occur
• Remember: No financial advice — always practice risk management and confirm entries manually
Forecasting
TSE USD Upper LimitThis script calculates and displays the daily upper price limit for a Tokyo Stock Exchange (TSE) stock based on the official JPX limit table. The limit is determined from the previous session’s closing price and displayed as a fixed horizontal line on the current chart. Ideal for tracking regulatory price caps and identifying squeeze scenarios.
TOLOMEO_EAthe strategy is based on intercepting a trend reversal first on RSI, then on EMA and then opening the position
IVO Trend IndicatorIVO Trend Indicator
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OBJECTIVE
As we all know, there are a multitude of indicators that aim to improve our trading operations, but many of them are confusing, and using several simultaneously can lead to trading errors. The indicator we have developed is based exclusively on the use of moving averages, so that together they are able to more accurately detect three important trading factors: TREND, STRENGTH, and MOMENTUM.
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HOW DOES IT CALCULATE THE 3 BASE VARIABLES?
The indicator uses four moving averages to identify these three variables.
1) TREND
Using two moving averages, we detect the chart's trend depending on how they cross and separate, so that the result will be (BULL, BEAR, NEUTRAL).
2) STRENGTH
Using two more moving averages, we detect the strength at that moment, that is, where the price is headed, regardless of its trend. The result will be (BULL, BEAR, NEUTRAL).
3) MOMENTUM
Using the intersection of two moving averages, we detect momentum, so that we know if the strength is still active in the same direction or is losing strength. The result will be (BULL, BEAR, NEUTRAL).
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CONTROL TABLE
The main advantage of the indicator is that it calculates the three variables (trend, strength, momentum) in the main timeframes and displays them in a control table so we can see the current price status at a glance.
It will also display a message for each timeframe as the sum of the three variables, so we know what's happening at any given moment without having to analyze anything.
Three types of messages for each timeframe (e.g., Weekly):
1) Weekly: BULLISH (losing strength) --> It's bullish, but it's losing strength because the momentum is bearish.
2) Weekly: BULLISH --> It's bullish.
3) Weekly: BULLISH (retracement) --> It's bullish in a retracement phase because its strength is bearish.
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GRAPH DISPLAY
1) The control table: (This is optional to display).
2) The 4 Moving Averages: (This is optional to display and the colors can be changed).
3) Bull or Bear signals based on strength: Bull or Bear messages will appear on the chart each time the strength changes value. (This is also optional to display and the colors can be changed).
4) Triangles at the bottom of the chart indicating price momentum: (This is also optional to display).
This is what the indicator provides to improve our daily trading.
For more information, please contact us in the following ways:
My TradingView profile: jmesado
Email: jmesado@gmail.com
Website: forexfibonacci.es
Thank you very much, and we will continue to update the indicator with improvements we already have in mind.
Greetings, TradingView community.
Triple RSI + MA這是一款強化型 RSI 技術指標，結合三組自定義 RSI 與其移動平均線（MA），提供多周期動能趨勢的視覺化參考，適合用於辨識轉折、背離、動能強弱切換等交易場景。
📈 功能亮點：
🔁 三組 RSI 自由調整：可針對短期、中期、長期分別設定不同 RSI 長度與資料來源
🔧 內建四種 MA 類型：支援 SMA、EMA、WMA、RMA，靈活調整每組 RSI 的平滑方式
🎯 多重動能對比：可觀察各週期 RSI 的同步與背離，輕鬆捕捉趨勢轉折
📊 視覺清晰：每組 RSI 與其 MA 使用不同顏色繪圖，輔以70/30超買超賣水平線，易於解讀
✅ 適用於多種市場：無論是股票、外匯、加密貨幣皆可適用
🧠 使用建議：
RSI 交叉其 MA 可作為轉勢訊號輔助
不同週期 RSI 出現背離時，代表可能的趨勢弱化或反轉
RSI 穿越 50 水平線可用作強弱分界
📌 Indicator Name (Suggested):
Triple RSI + MA – Multi-Timeframe Momentum Analyzer
📄 Description:
Triple RSI + MA is a powerful momentum analysis tool that combines three individually configurable RSI indicators with their corresponding moving averages. This multi-timeframe setup helps traders gain deeper insight into potential trend reversals, divergences, and momentum shifts.
🚀 Key Features:
🔁 Three Independent RSI Inputs: Customize the source and length for short-, medium-, and long-term RSI signals
🔧 Built-In MA Smoothing Options: Choose from SMA, EMA, WMA, or RMA to smooth each RSI line individually
🔍 Multi-Timeframe Momentum View: Compare RSI behavior across different timeframes to identify trend alignment or divergence
🎨 Clear Visual Representation: Each RSI and MA is color-coded, with overbought (70), oversold (30), and neutral (50) levels clearly marked
🧩 Versatile Across Markets: Suitable for use in forex, stocks, crypto, and other trading instruments
📘 How to Use:
RSI crossing above or below its MA can signal short-term momentum shifts
Divergences between different RSI levels may suggest a weakening or reversal of the current trend
The 50 level acts as a neutral zone – crossing above may indicate bullish momentum, and below suggests bearish pressure
Bayram Günleri 2020-2025// This script highlights the days of Ramadan Eid and Eid al-Adha (including the day before) on the chart.
// This indicator is designed to visually mark Ramadan Eid, Eid al-Adha, and their preceding days (Arefe) between 2020 and 2025.
// It colors the background in orange on those specific dates, making it easy to identify and analyze holiday periods.
// Works across all timeframes (1m, 1h, 1d, etc.).
// Dates are checked using year, month, and dayofmonth values manually.
// All times are based on Turkish local time (UTC+3).
// Ramazan Bayramı ve Kurban Bayramı günlerini gösterir
Dual Range Filter with VOL Stats (Enhanced)Advanced Event Trading Signal System for Binance
English:
This state-of-the-art analytical system is meticulously designed for Binance Event Contracts, leveraging sophisticated algorithmic technology to capture high-probability trading opportunities during market events. The system demonstrates exceptional performance specifically on 10-minute and 30-minute timeframes, where its proprietary signal generation achieves optimal accuracy. Through comprehensive win rate statistics and institutional-grade volume analysis, this advanced indicator provides traders with statistically validated entry points for event-driven market movements.
高级事件交易信号系统（币安事件合约专用）
中文：
这是一套专为币安事件合约精心设计的尖端分析系统，运用复杂的算法技术在市场事件中捕捉高概率交易机会。该系统在10分钟和30分钟时间周期上表现卓越，其专有信号生成技术达到最佳精度。通过全面的胜率统计和机构级成交量分析，这个高级指标为交易者提供经过统计验证的事件驱动型市场走势入场点。
Optimal Performance / 最佳性能:
Specialized for 10-minute and 30-minute timeframes / 专为10分钟和30分钟周期优化
Event-driven signal generation / 事件驱动型信号生成
Statistical validation through comprehensive win rate tracking / 通过全面胜率追踪进行统计验证
Professional event trading analytics / 专业事件交易分析
EMA50 Crossover Momentum Strategy v2I have observed such a phenomenon: when the stock price crosses EMA50 from a low point, its potential energy usually supports the stock price to continue to move to the same distance as before the crossing. For example, when the stock price is below EMA50, the lowest point is 5, and when it crosses the EMA50 of the previous trading day (because the EMA50 of the current trading day is changing, in order to simplify the calculation, take the EMA50 of the previous trading day), the price is 10, then the stock price is likely to continue to rise to 15.
True SeasonalityCONCEPTS
True Seasonality Indicator designed to forecast price based on historical data, best use on daily chart.
DETAILS & EXAMPLE OF HOW TO USE
On Gold chart, the blue graph indicate the few projected days in the future. On 8 April 2025, the indicator showing potential uptrend movement until mid of April, and after that sideways for sometimes.
FEATURES
Adjustable forecast bars & lookback
LIMITATIONS
The Indicator is best applied on daily chart.
Not intended as a stand-alone signal, but should be as part of long-term strategy analysis.
Should be combined with other lower-timeframe technical tools like supply and demand to find entry and confirmation.
Fair Value Trend Model [SiDec]ABSTRACT
This pine script introduces the Fair Value Trend Model, an on-chart indicator for TradingView that constructs a continuously updating "fair-value" estimate of an asset's price via a logarithmic regression on historical data. Specifically, this model has been applied to Bitcoin (BTC) to fully grasp its fair value in the cryptocurrency market. Symmetric channel bands, defined by fixed percentage offsets around this central fair-value curve, provide a visual band within which normal price fluctuations may occur. Additionally, a short-term projection extends both the fair-value trend and its channel bands forward by a user-specified number of bars.
INTRODUCTION
Technical analysts frequently seek to identify an underlying equilibrium or "fair value" about which prices oscillate. Traditional approaches-moving averages, linear regressions in price-time space, or midlines-capture linear trends but often misrepresent the exponential or power-law growth patterns observable in many financial markets. The Fair Value Trend Model addresses this by performing an ordinary least squares (OLS) regression in log-space, fitting ln(Price) against ln(Days since inception). In practice, the primary application has been to Bitcoin, aiming to fully capture Bitcoin's underlying value dynamics.
The result is a curved trend line in regular (price-time) coordinates, reflecting Bitcoin's long-term compounding characteristics. Surrounding this fair-value curve, symmetric bands at user-specified percentage deviations serve as dynamic support and resistance levels. A simple linear projection extends both the central fair-value and its bands into the immediate future, providing traders with a heuristic for short-term trend continuation.
This exposition details:
Data transformation: converting bar timestamps into days since first bar, then applying natural logarithms to both time and price.
Regression mechanics: incremental (or rolling-window) accumulation of sums to compute the log-space fit parameters.
Fair-value reconstruction: exponentiation of the regression output to yield a price-space estimate.
Channel-band definition: establishing ±X% offsets around the fair-value curve and rendering them visually.
Forecasting methodology: projecting both the fair-value trend and channel bands by extrapolating the most recent incremental change in price-space.
Interpretation: how traders can leverage this model for trend identification, mean-reversion setups, and breakout analysis, particularly in Bitcoin trading.
Analysing the macro cycle on Bitcoin's monthly timeframe illustrates how the fair-value curve aligns with multi-year structural turning points.
DATA TRANSFORMATION AND NOTATION
1. Timestamp Baseline (t0)
Let t0 = timestamp of the very first bar on the chart (in milliseconds). Each subsequent bar has a timestamp ti, where ti ≥ t0.
2. Days Since Inception (d(t))
Define the “days since first bar” as
d(t) = max(1, (t − t0) / 86400000.0)
Here, 86400000.0 represents the number of milliseconds in one day (1,000 ms × 60 seconds × 60 minutes × 24 hours). The lower bound of 1 ensures that we never compute ln(0).
3. Logarithmic Coordinates:
Given the bar’s closing price P(t), define:
xi = ln( d(ti) )
yi = ln( P(ti) )
Thus, each data point is transformed to (xi, yi) in log‐space.
REGRESSION FORMULATION
We assume a log‐linear relationship:
yi = a + b·xi + εi
where εi is the residual error at bar i. Ordinary least squares (OLS) fitting minimizes the sum of squared residuals over N data points. Define the following accumulated sums:
Sx = Σ for i = 1 to N
Sy = Σ for i = 1 to N
Sxy = Σ for i = 1 to N
Sx2 = Σ for i = 1 to N
N = number of data points
The OLS estimates for b (slope) and a (intercept) are:
b = ( N·Sxy − Sx·Sy ) / ( N·Sx2 − (Sx)^2 )
a = ( Sy − b·Sx ) / N
All‐Time Versus Rolling‐Window Mode:
All-Time Mode:
Each new bar increments N by 1.
Update Sx ← Sx + xN, Sy ← Sy + yN, Sxy ← Sxy + xN·yN, Sx2 ← Sx2 + xN^2.
Recompute a and b using the formulas above on the entire dataset.
Rolling-Window Mode:
Fix a window length W. Maintain two arrays holding the most recent W values of {xi} and {yi}.
On each new bar N:
Append (xN, yN) to the arrays; add xN, yN, xN·yN, xN^2 to the sums Sx, Sy, Sxy, Sx2.
If the arrays’ length exceeds W, remove the oldest point (xN−W, yN−W) and subtract its contributions from the sums.
Update N_roll = min(N, W).
Compute b and a using N_roll, Sx, Sy, Sxy, Sx2 as above.
This incremental approach requires only O(1) operations per bar instead of recomputing sums from scratch, making it computationally efficient for long time series.
FAIR‐VALUE RECONSTRUCTION
Once coefficients (a, b) are obtained, the regressed log‐price at time t is:
ŷ(t) = a + b·ln( d(t) )
Mapping back to price space yields the “fair‐value”:
F(t) = exp( ŷ(t) )
= exp( a + b·ln( d(t) ) )
= exp(a) · ^b
In other words, F(t) is a power‐law function of “days since inception,” with exponent b and scale factor C = exp(a). Special cases:
If b = 1, F(t) = C · d(t), which is an exponential function in original time.
If b > 1, the fair‐value grows super‐linearly (accelerating compounding).
If 0 < b < 1, it grows sub‐linearly.
If b < 0, the fair‐value declines over time.
CHANNEL‐BAND DEFINITION
To visualise a “normal” range around the fair‐value curve F(t), we define two channel bands at fixed percentage offsets:
1. Upper Channel Band
U(t) = F(t) · (1 + α_upper)
where α_upper = (Channel Band Upper %) / 100.
2. Lower Channel Band
L(t) = F(t) · (1 − α_lower)
where α_lower = (Channel Band Lower %) / 100.
For example, default values of 50% imply α_upper = α_lower = 0.50, so:
U(t) = 1.50 · F(t)
L(t) = 0.50 · F(t)
When “Show FV Channel Bands” is enabled, both U(t) and L(t) are plotted in a neutral grey, and a semi‐transparent fill is drawn between them to emphasise the channel region.
SHORT‐TERM FORECAST PROJECTION
To extend both the fair‐value and its channel bands M bars into the future, the model uses a simple constant‐increment extrapolation in price space. The procedure is:
1. Compute Recent Increments
Let
F_prev = F( t_{N−1} )
F_curr = F( t_N )
Then define the per‐bar change in fair‐value:
ΔF = F_curr − F_prev
Similarly, for channel bands:
U_prev = U( t_{N−1} ), U_curr = U( t_N ), ΔU = U_curr − U_prev
L_prev = L( t_{N−1} ), L_curr = L( t_N ), ΔL = L_curr − L_prev
2. Forecasted Values After M Bars
Assuming the same per‐bar increments continue:
F_future = F_curr + M · ΔF
U_future = U_curr + M · ΔU
L_future = L_curr + M · ΔL
These forecasted values produce dashed lines on the chart:
A dashed segment from (bar_N, F_curr) to (bar_{N+M}, F_future).
Dashed segments from (bar_N, U_curr) to (bar_{N+M}, U_future), and from (bar_N, L_curr) to (bar_{N+M}, L_future).
Forecasted channel bands are rendered in a subdued grey to distinguish them from the current solid bands. Because this method does not re‐estimate regression coefficients for future t > t_N, it serves as a quick visual heuristic of trend continuation rather than a precise statistical forecast.
MATHEMATICAL SUMMARY
Summarising all key formulas:
1. Days Since Inception
d(t_i) = max( 1, ( t_i − t0 ) / 86400000.0 )
x_i = ln( d(t_i) )
y_i = ln( P(t_i) )
2. Regression Summations (for i = 1..N)
Sx = Σ
Sy = Σ
Sxy = Σ
Sx2 = Σ
N = number of data points (or N_roll if using rolling‐window)
3. OLS Estimator
b = ( N · Sxy − Sx · Sy ) / ( N · Sx2 − (Sx)^2 )
a = ( Sy − b · Sx ) / N
4. Fair‐Value Computation
ŷ(t) = a + b · ln( d(t) )
F(t) = exp( ŷ(t) ) = exp(a) · ^b
5. Channel Bands
U(t) = F(t) · (1 + α_upper)
L(t) = F(t) · (1 − α_lower)
with α_upper = (Channel Band Upper %) / 100, α_lower = (Channel Band Lower %) / 100.
6. Forecast Projection
ΔF = F_curr − F_prev
F_future = F_curr + M · ΔF
ΔU = U_curr − U_prev
U_future = U_curr + M · ΔU
ΔL = L_curr − L_prev
L_future = L_curr + M · ΔL
IMPLEMENTATION CONSIDERATIONS
1. Time Precision
Timestamps are recorded in milliseconds. Dividing by 86400000.0 yields days with fractional precision.
For the very first bar, d(t) = 1 ensures x = ln(1) = 0, avoiding an undefined logarithm.
2. Incremental Versus Sliding Summation
All‐Time Mode: Uses persistent scalar variables (Sx, Sy, Sxy, Sx2, N). On each new bar, add the latest x and y contributions to the sums.
Rolling‐Window Mode: Employs fixed‐length arrays for {x_i} and {y_i}. On each bar, append (x_N, y_N) and update sums; if array length exceeds W, remove the oldest element and subtract its contribution from the sums. This maintains exact sums over the most recent W data points without recomputing from scratch.
3. Numerical Robustness
If the denominator N·Sx2 − (Sx)^2 equals zero (e.g., all x_i identical, as when only one day has passed), then set b = 0 and a = Sy / N. This produces a constant fair‐value F(t) = exp(a).
Enforcing d(t) ≥ 1 avoids attempts to compute ln(0).
4. Plotting Strategy
The fair‐value line F(t) is plotted on each new bar. Its color depends on whether the current price P(t) is above or below F(t): a “bullish” color (e.g., green) when P(t) ≥ F(t), and a “bearish” color (e.g., red) when P(t) < F(t).
The channel bands U(t) and L(t) are plotted in a neutral grey when enabled; otherwise they are set to “not available” (no plot).
A semi‐transparent fill is drawn between U(t) and L(t). Because the fill function is executed at global scope, it is automatically suppressed if either U(t) or L(t) is not plotted (na).
5. Forecast Line Management
Each projection line (for F, U, and L) is created via a persistent line object. On successive bars, the code updates the endpoints of the same line rather than creating a new one each time, preserving chart clarity.
If forecasting is disabled, any existing projection lines are deleted to avoid cluttering the chart.
INTERPRETATION AND APPLICATIONS
1. Trend Identification
The fair‐value curve F(t) represents the best‐fit long‐term trend under the assumption that ln(Price) scales linearly with ln(Days since inception). By capturing power‐law or exponential patterns, it can more accurately reflect underlying compounding behavior than simple linear regressions.
When actual price P(t) lies above U(t), it may be considered “overextended” relative to its long‐term trend; when price falls below L(t), it may be deemed “oversold.” These conditions can signal potential mean‐reversion or breakout opportunities.
2. Mean‐Reversion and Breakout Signals
If price re‐enters the channel after touching or slightly breaching L(t), some traders interpret this as a mean‐reversion bounce and consider initiating a long position.
Conversely, a sustained move above U(t) can indicate strong upward momentum and a possible bullish breakout. Traders often seek confirmation (e.g., price remaining above U(t) for multiple bars, rising volume, or corroborating momentum indicators) before acting.
3. Rolling Versus All‐Time Usage
All‐Time Mode: Captures the entire dataset since inception, focusing on structural, long‐term trends. It is less sensitive to short‐term noise or volatility spikes.
Rolling‐Window Mode: Restricts the regression to the most recent W bars, making the fair‐value curve more responsive to changing market regimes, sudden volatility expansions, or fundamental shifts. Traders who wish to align the model with local behaviour often choose W so that it approximates a market cycle length (e.g., 100–200 bars on a daily chart).
4. Channel Percentage Selection
A wider band (e.g., ±50 %) accommodates larger price swings, reducing the frequency of breaches but potentially delaying actionable signals.
A narrower band (e.g., ±10 %) yields more frequent “overbought/oversold” alerts but may produce more false signals during normal volatility. It is advisable to calibrate the channel width to the asset’s historical volatility regime.
5. Forecast Cautions
The short‐term projection assumes that the last single‐bar increment ΔF remains constant for M bars. In reality, trend acceleration or deceleration can occur, rendering the linear forecast inaccurate.
As such, the forecast serves as a visual guide rather than a statistically rigorous prediction. It is best used in conjunction with other momentum, volume, or volatility indicators to confirm trend continuation or reversal.
LIMITATIONS AND CONSIDERATIONS
1. Power‐Law Assumption
By fitting ln(P) against ln(d), the model posits that P(t) ≈ C · ^b. Real markets may deviate from a pure power‐law, especially around significant news events or structural regime changes. Temporary misalignment can occur.
2. Fixed Channel Width
Markets exhibit heteroskedasticity: volatility can expand or contract unpredictably. A static ±X % band does not adapt to changing volatility. During high‐volatility periods, a fixed ±50 % may prove too narrow and be breached frequently; in unusually calm periods, it may be excessively broad, masking meaningful variations.
3. Endpoint Sensitivity
Regression‐based indicators often display greater curvature near the most recent data, especially under rolling‐window mode. This can create sudden “jumps” in F(t) when new bars arrive, potentially confusing users who expect smoother behaviour.
4. Forecast Simplification
The projection does not re‐estimate regression slope b for future times. It only extends the most recent single‐bar change. Consequently, it should be regarded as an indicative extension rather than a precise forecast.
PRACTICAL IMPLEMENTATION ON TRADINGVIEW
1 Adding the Indicator
In TradingView’s “Indicators” dialog, search for Fair Value Trend Model or visit my profile, under "scripts" add it to your chart.
Add it to any chart (e.g., BTCUSD, AAPL, EURUSD) to see real‐time computation.
2. Configuring Inputs
Show Forecast Line: Toggle on or off the dashed projection of the fair‐value.
Forecast Bars: Choose M, the number of bars to extend into the future (default is often 30).
Forecast Line Colour: Select a high‐contrast colour (e.g., yellow).
Bullish FV Colour / Bearish FV Colour: Define the colour of the fair‐value line when price is above (e.g., green) or below it (e.g., red).
Show FV Channel Bands: Enable to display the grey channel bands around the fair‐value.
Channel Band Upper % / Channel Band Lower %: Set α_upper and α_lower as desired (defaults of 50 % create a ±50 % envelope).
Use Rolling Window?: Choose whether to restrict the regression to recent data.
Window Bars: If rolling mode is enabled, designate W, the number of bars to include.
3. Visual Output
The central curve F(t) appears on the price chart, coloured green when P(t) ≥ F(t) and red when P(t) < F(t).
If channel bands are enabled, the chart shows two grey lines U(t) and L(t) and a subtle shading between them.
If forecasting is active, dashed extensions of F(t), U(t), and L(t) appear, projecting forward by M bars in neutral hues.
CONCLUSION
The Fair Value Trend Model furnishes traders with a mathematically principled estimate of an asset’s equilibrium price curve by fitting a log‐linear regression to historical data. Its channel bands delineate a normal corridor of fluctuation based on fixed percentage offsets, while an optional short‐term projection offers a visual approximation of trend continuation.
By operating in log‐space, the model effectively captures exponential or power‐law growth patterns that linear methods overlook. Rolling‐window capability enables responsiveness to regime shifts, whereas all‐time mode highlights broader structural trends. Nonetheless, users should remain mindful of the model’s assumptions—particularly the power‐law form and fixed band percentages—and employ the forecast projection as a supplemental guide rather than a standalone predictor.
When combined with complementary indicators (e.g., volatility measures, momentum oscillators, volume analysis) and robust risk management, the Fair Value Trend Model can enhance market timing, mean‐reversion identification, and breakout detection across diverse trading environments.
REFERENCES
Draper, N. R., & Smith, H. (1998). Applied Regression Analysis (3rd ed.). Wiley.
Tsay, R. S. (2014). Introductory Time Series with R (2nd ed.). Springer.
Hull, J. C. (2017). Options, Futures, and Other Derivatives (10th ed.). Pearson.
These references provide background on regression, time-series analysis, and financial modeling.
DCA Investment Tracker Pro [tradeviZion]DCA Investment Tracker Pro: Educational DCA Analysis Tool
An educational indicator that helps analyze Dollar-Cost Averaging strategies by comparing actual performance with historical data calculations.
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💡 Why I Created This Indicator
As someone who practices Dollar-Cost Averaging, I was frustrated with constantly switching between spreadsheets, calculators, and charts just to understand how my investments were really performing. I wanted to see everything in one place - my actual performance, what I should expect based on historical data, and most importantly, visualize where my strategy could take me over the long term .
What really motivated me was watching friends and family underestimate the incredible power of consistent investing. When Napoleon Bonaparte first learned about compound interest, he reportedly exclaimed "I wonder it has not swallowed the world" - and he was right! Yet most people can't visualize how their $500 monthly contributions today could become substantial wealth decades later.
Traditional DCA tracking tools exist, but they share similar limitations:
Require manual data entry and complex spreadsheets
Use fixed assumptions that don't reflect real market behavior
Can't show future projections overlaid on actual price charts
Lose the visual context of what's happening in the market
Make compound growth feel abstract rather than tangible
I wanted to create something different - a tool that automatically analyzes real market history, detects volatility periods, and shows you both current performance AND educational projections based on historical patterns right on your TradingView charts. As Warren Buffett said: "Someone's sitting in the shade today because someone planted a tree a long time ago." This tool helps you visualize your financial tree growing over time.
This isn't just another calculator - it's a visualization tool that makes the magic of compound growth impossible to ignore.
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🎯 What This Indicator Does
This educational indicator provides DCA analysis tools. Users can input investment scenarios to study:
Theoretical Performance: Educational calculations based on historical return data
Comparative Analysis: Study differences between actual and theoretical scenarios
Historical Projections: Theoretical projections for educational analysis (not predictions)
Performance Metrics: CAGR, ROI, and other analytical metrics for study
Historical Analysis: Calculates historical return data for reference purposes
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🚀 Key Features
Volatility-Adjusted Historical Return Calculation
Analyzes 3-20 years of actual price data for any symbol
Automatically detects high-volatility stocks (meme stocks, growth stocks)
Uses median returns for volatile stocks, standard CAGR for stable stocks
Provides conservative estimates when extreme outlier years are detected
Smart fallback to manual percentages when data insufficient
Customizable Performance Dashboard
Educational DCA performance analysis with compound growth calculations
Customizable table sizing (Tiny to Huge text options)
9 positioning options (Top/Middle/Bottom + Left/Center/Right)
Theme-adaptive colors (automatically adjusts to dark/light mode)
Multiple display layout options
Future Projection System
Visual future growth projections
Timeframe-aware calculations (Daily/Weekly/Monthly charts)
1-30 year projection options
Shows projected portfolio value and total investment amounts
Investment Insights
Performance vs benchmark comparison
ROI from initial investment tracking
Monthly average return analysis
Investment milestone alerts (25%, 50%, 100% gains)
Contribution tracking and next milestone indicators
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📊 Step-by-Step Setup Guide
1. Investment Settings 💰
Initial Investment: Enter your starting lump sum (e.g., $60,000)
Monthly Contribution: Set your regular DCA amount (e.g., $500/month)
Return Calculation: Choose "Auto (Stock History)" for real data or "Manual" for fixed %
Historical Period: Select 3-20 years for auto calculations (default: 10 years)
Start Year: When you began investing (e.g., 2020)
Current Portfolio Value: Your actual portfolio worth today (e.g., $150,000)
2. Display Settings 📊
Table Sizes: Choose from Tiny, Small, Normal, Large, or Huge
Table Positions: 9 options - Top/Middle/Bottom + Left/Center/Right
Visibility Toggles: Show/hide Main Table and Stats Table independently
3. Future Projection 🔮
Enable Projections: Toggle on to see future growth visualization
Projection Years: Set 1-30 years ahead for analysis
Live Example - NASDAQ:META Analysis:
Settings shown: $60K initial + $500/month + Auto calculation + 10-year history + 2020 start + $150K current value
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🔬 Pine Script Code Examples
Core DCA Calculations:
// Calculate total invested over time
months_elapsed = (year - start_year) * 12 + month - 1
total_invested = initial_investment + (monthly_contribution * months_elapsed)
// Compound growth formula for initial investment
theoretical_initial_growth = initial_investment * math.pow(1 + annual_return, years_elapsed)
// Future Value of Annuity for monthly contributions
monthly_rate = annual_return / 12
fv_contributions = monthly_contribution * ((math.pow(1 + monthly_rate, months_elapsed) - 1) / monthly_rate)
// Total expected value
theoretical_total = theoretical_initial_growth + fv_contributions
Volatility Detection Logic:
// Detect extreme years for volatility adjustment
extreme_years = 0
for i = 1 to historical_years
yearly_return = ((price_current / price_i_years_ago) - 1) * 100
if yearly_return > 100 or yearly_return < -50
extreme_years += 1
// Use median approach for high volatility stocks
high_volatility = (extreme_years / historical_years) > 0.2
calculated_return = high_volatility ? median_of_returns : standard_cagr
Performance Metrics:
// Calculate key performance indicators
absolute_gain = actual_value - total_invested
total_return_pct = (absolute_gain / total_invested) * 100
roi_initial = ((actual_value - initial_investment) / initial_investment) * 100
cagr = (math.pow(actual_value / initial_investment, 1 / years_elapsed) - 1) * 100
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📊 Real-World Examples
See the indicator in action across different investment types:
Stable Index Investments:
AMEX:SPY (SPDR S&P 500) - Shows steady compound growth with standard CAGR calculations
Classic DCA success story: $60K initial + $500/month starting 2020. The indicator shows SPY's historical 10%+ returns, demonstrating how consistent broad market investing builds wealth over time. Notice the smooth theoretical growth line vs actual performance tracking.
MIL:VUAA (Vanguard S&P 500 UCITS) - Shows both data limitation and solution approaches
Data limitation example: VUAA shows "Manual (Auto Failed)" and "No Data" when default 10-year historical setting exceeds available data. The indicator gracefully falls back to manual percentage input while maintaining all DCA calculations and projections.
MIL:VUAA (Vanguard S&P 500 UCITS) - European ETF with successful 5-year auto calculation
Solution demonstration: By adjusting historical period to 5 years (matching available data), VUAA auto calculation works perfectly. Shows how users can optimize settings for newer assets. European market exposure with EUR denomination, demonstrating DCA effectiveness across different markets and currencies.
NYSE:BRK.B (Berkshire Hathaway) - Quality value investment with Warren Buffett's proven track record
Value investing approach: Berkshire Hathaway's legendary performance through DCA lens. The indicator demonstrates how quality companies compound wealth over decades. Lower volatility than tech stocks = standard CAGR calculations used.
High-Volatility Growth Stocks:
NASDAQ:NVDA (NVIDIA Corporation) - Demonstrates volatility-adjusted calculations for extreme price swings
High-volatility example: NVIDIA's explosive AI boom creates extreme years that trigger volatility detection. The indicator automatically switches to "Median (High Vol): 50%" calculations for conservative projections, protecting against unrealistic future estimates based on outlier performance periods.
NASDAQ:TSLA (Tesla) - Shows how 10-year analysis can stabilize volatile tech stocks
Stable long-term growth: Despite Tesla's reputation for volatility, the 10-year historical analysis (34.8% CAGR) shows consistent enough performance that volatility detection doesn't trigger. Demonstrates how longer timeframes can smooth out extreme periods for more reliable projections.
NASDAQ:META (Meta Platforms) - Shows stable tech stock analysis using standard CAGR calculations
Tech stock with stable growth: Despite being a tech stock and experiencing the 2022 crash, META's 10-year history shows consistent enough performance (23.98% CAGR) that volatility detection doesn't trigger. The indicator uses standard CAGR calculations, demonstrating how not all tech stocks require conservative median adjustments.
Notice how the indicator automatically detects high-volatility periods and switches to median-based calculations for more conservative projections, while stable investments use standard CAGR methods.
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📈 Performance Metrics Explained
Current Portfolio Value: Your actual investment worth today
Expected Value: What you should have based on historical returns (Auto) or your target return (Manual)
Total Invested: Your actual money invested (initial + all monthly contributions)
Total Gains/Loss: Absolute dollar difference between current value and total invested
Total Return %: Percentage gain/loss on your total invested amount
ROI from Initial Investment: How your starting lump sum has performed
CAGR: Compound Annual Growth Rate of your initial investment (Note: This shows initial investment performance, not full DCA strategy)
vs Benchmark: How you're performing compared to the expected returns
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⚠️ Important Notes & Limitations
Data Requirements: Auto mode requires sufficient historical data (minimum 3 years recommended)
CAGR Limitation: CAGR calculation is based on initial investment growth only, not the complete DCA strategy
Projection Accuracy: Future projections are theoretical and based on historical returns - actual results may vary
Timeframe Support: Works ONLY on Daily (1D), Weekly (1W), and Monthly (1M) charts - no other timeframes supported
Update Frequency: Update "Current Portfolio Value" regularly for accurate tracking
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📚 Educational Use & Disclaimer
This analysis tool can be applied to various stock and ETF charts for educational study of DCA mathematical concepts and historical performance patterns.
Study Examples: Can be used with symbols like AMEX:SPY , NASDAQ:QQQ , AMEX:VTI , NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:GOOGL , NASDAQ:AMZN , NASDAQ:TSLA , NASDAQ:NVDA for learning purposes.
EDUCATIONAL DISCLAIMER: This indicator is a study tool for analyzing Dollar-Cost Averaging strategies. It does not provide investment advice, trading signals, or guarantees. All calculations are theoretical examples for educational purposes only. Past performance does not predict future results. Users should conduct their own research and consult qualified financial professionals before making any investment decisions.
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© 2025 TradeVizion. All rights reserved.
Kappa Weighted IndexI have created an indicator with options to select if you invested in separate stocks to get one price index I hope you will find helpful.
Any questions on that please give me a shout
Previous Two Days HL + Asia H/L + 4H Vertical Lines📊 Indicator Overview
This custom TradingView indicator visually marks key market structure levels and session data on your chart using lines, labels, boxes, and vertical guides. It is designed for traders who analyze intraday and multi-session behavior — especially around the New York and Asia sessions — with a focus on 4-hour price ranges.
🔍 What the Indicator Tracks
1. Previous Two Days' Ranges (6PM–5PM NY Time)
PDH/PDL (Day 1 & Day 2): Draws horizontal lines marking the previous two trading days’ highs and lows.
Midlines: Calculates and displays the midpoint between each day’s high and low.
Color-Coded: Uses strong colors for Day 1 and more transparent versions for Day 2, to help differentiate them.
2. Asia Session High/Low (6 PM – 2 AM NY Time)
Automatically tracks the high and low during the Asia session.
Extends these levels until the following day’s NY close (4 PM).
Shows a midline of the Asia session (optional dotted line).
Highlights the Asia session background in gray.
Labels Asia High and Low on the chart for easy reference.
3. Last Closed 4-Hour Candle Range
At the start of every new 4H candle, it:
Draws a box from the last closed 4H candle.
Box spans horizontally across a set number of bars (adjustable).
Top and bottom lines indicate the high and low of that 4H candle.
Midline, 25% (Q1) and 75% (Q3) levels are also drawn inside the box using dotted lines.
Helps traders identify premium/discount zones within the previous 4H range.
4. Vertical 4H Time Markers
Draws vertical dashed lines to mark the start and end of the last 4H candle range.
Based on the standard 4H bar timing in NY (e.g. 5:00, 9:00, 13:00, 17:00).
⚙️ Inputs & Options
Line thickness, color customization for all levels.
Option to place labels on the right or left side of the chart.
Toggle for enabling/disabling the 4H box.
Adjustable box extension length (how far to extend the range visually).
✅ Ideal Use Cases
Identifying reaction zones from prior highs/lows.
Spotting reversals during Asia or NY session opens.
Trading intraday setups based on 4H structure.
Anchoring scalping or swing entries off major session levels.
Enhanced Seasonality Trade BacktestEnhanced Seasonality Trade Backtest
Overview
A comprehensive Pine Script indicator that backtests seasonal trading strategies by analyzing historical price performance during specific date ranges. The tool provides detailed statistics, visual markers, and election cycle filtering to identify profitable seasonal patterns.
Key Features
📊 Backtesting Engine
Tests up to 50 years of historical data
Configurable entry/exit dates (day/month)
Automatic holiday/weekend date adjustment
Separate analysis for long and short positions
🗳️ Election Cycle Filter
All Years: Test every year in the lookback period
Election Years: US presidential election years only (2024, 2020, 2016...)
Pre-Election Years: Years before elections (2023, 2019, 2015...)
Post-Election Years: Years after elections (2021, 2017, 2013...)
📈 Comprehensive Statistics
Win rate percentage
Total and average returns
Best/worst performing years
Detailed trade-by-trade breakdown
Years tested vs. years filtered
🎯 Visual Indicators
Entry/exit lines for all historical trades
Future trade date projections
Background highlighting during trade periods
Color-coded performance labels
⚙️ Customization Options
Toggle between long/short analysis
Show/hide price and date details
Adjustable table position
Future trade date visualization
Use Cases
Seasonal Trading: Identify recurring profitable periods (e.g., "Sell in May")
Election Cycle Analysis: Test how political cycles affect market performance
Strategy Validation: Backtest specific date-range strategies
Risk Assessment: Analyze worst-case scenarios and drawdowns
Perfect For
Swing traders looking for seasonal edges
Portfolio managers timing market entries/exits
Researchers studying market cyclicality
Anyone wanting to quantify seasonal market behavior
ONLY WORKS IN 1D TIME FRAME
Session Status Table📌 Session Status Table
Session Status Table is an indicator that displays the real-time status of the four major trading sessions:
* 🇯🇵 Asia (Tokyo)
* 🇬🇧 London
* 🇺🇸 New York AM
* 🇺🇸 New York PM
It shows which sessions are currently open, how much time remains until they open or close, and optionally sends alerts in advance.
🧩 Features:
* Real-time session table — shows the status of each session on the chart.
* Color-coded statuses:
* 🟢 Green – Session is open
* 🔴 Red – Session is closed
* ⚪ Gray – Weekend
* Countdown timers until session open or close.
* User alerts — receive a notification a custom number of minutes before a session starts.
⚙️ Customization:
* Table position — fully configurable.
* Session colors — customizable for open, closed, and weekend states.
* Session labels — customizable with icons.
* Notifications:
* Enabled through TradingView's Alerts panel.
* User-defined lead time before session opens.
🕒 Time Zones:
All times are calculated in UTC to ensure consistency across different markets and regions, avoiding discrepancies from time zones and daylight saving time.
🚨 How to enable alerts:
1. Open the "Alerts" panel in TradingView.
2. Click "Create Alert".
3. In the condition dropdown, choose "Session Status Table".
4. Set to any alert() trigger.
5. Save — you'll be notified a set number of minutes before each session begins.
ℹ️ Technical Notes:
* Built with Pine Script version 6.
* Logically divided into clear sections: inputs, session calculations, table rendering, and alerts.
* Optimized for performance and reliability on all timeframes.
Ideal for traders who use session activity in their strategies — especially in Forex, crypto, and futures markets.
Holy Grail Setup with Confidence OpacityVersion 1
Triggers Raschke's Holy Grail set up. More translucent=less confidence, more opaque=more confidence.
Uses Raschke's default parameters
20 EMA + ADX > 30 + pullback and reversal
ADX stands for Average Directional Index, a technical indicator developed by Welles Wilder to quantify trend strength — not direction, just strength.
It's a core component of Linda Raschke’s Holy Grail strategy, where the goal is to only trade pullbacks during strong trends.
ADX ranges from 0 to 100:
Below 20: Weak or no trend (range-bound market)
25–30 and above: Strong trend
50+: Very strong trend (often near trend exhaustion)
In the Holy Grail setup, Raschke recommends only taking trades when ADX > 30, to ensure that:
The market is trending
Pullbacks are more likely to resolve in the direction of the trend
NY Open 15-Min Candle Detector + EMAs & VWAP (BG Time)
➡️ NY Open 15-Min Candle Detector with EMAs & VWAP (BG Time)
🟢 This indicator is a powerful tool for traders looking to pinpoint and visualize the critical first 15-minute trading range of the New York session, precisely aligned with Bulgarian time (Europe/Sofia). It's perfect for those who trade around the NYSE open (09:30 AM New York time) but prefer to see these key levels mapped to their local time. In addition to the opening range, it integrates three Exponential Moving Averages (EMAs) and the Volume Weighted Average Price (VWAP) for a comprehensive trading perspective.
🔥 Key Features:
Precise NY Open 15-Minute Range (Bulgarian Time):
Automatically identifies and highlights the initial 15-minute candle that opens at 16:30 BG time, which directly corresponds to the 09:30 AM New York Stock Exchange (NYSE) opening bell.
The background of this specific 15-minute period is clearly colored for immediate visual recognition.
Draws durable horizontal lines marking the High, Low, and Mid-Point of this crucial opening range, extending them across the chart for the remainder of the trading day.
Handles Daylight Saving Time (DST) changes automatically for the "Europe/Sofia" timezone.
🟢 Three Customizable Exponential Moving Averages (EMAs):
Includes three distinct EMAs (default lengths: 20, 50, 200).
Each EMA offers independent control over its length, data source (e.g., Close, Open, HLC3), color, and line width.
Individual visibility toggles allow you to display only the EMAs relevant to your strategy.
Default colors: EMA 20 (White), EMA 50 (Green), EMA 200 (Red) – all with a line width of 2 for optimal visibility.
📈 Volume Weighted Average Price (VWAP):
Displays the session-based VWAP, offering a crucial average price weighted by trading volume.
Customizable color (default: Yellow) and line width (default: 2).
Can be toggled on/off.
Real-Time Breakout Alerts:
Generates clear alerts when the price breaks above the 15-minute range's high or below its low, providing timely notifications for potential trading setups.
⚙️ How to Use:
Apply to Chart: Simply add the indicator to any chart in TradingView.
Verify Time: The "Market Start Hour (BG Time)" and "Market Start Minute (BG Time)" inputs are pre-set to 16:30, aligning with the 09:30 AM NY Open. You can adjust these if your specific market open differs.
Customize Visuals: Tailor the colors, line widths, and background visibility of the opening range to match your chart theme.
➡️ Configure Indicators: Easily enable/disable, set lengths, sources, and colors for the EMAs and VWAP according to your technical analysis preferences.
Set Alerts: Activate the breakout alerts to receive notifications directly from TradingView when significant price action occurs outside the initial NY Open range.
This indicator is an indispensable tool for day traders and swing traders focusing on the New York session's opening momentum, combining precise time-based analysis with essential moving averages and volume-weighted pricing for a comprehensive trading edge.
linktr.ee
Advance Smc Ict V4 The Advance SMC ICT Indicator is designed to assist traders in mapping market structure and identifying key price zones based on Smart Money Concepts (SMC) such as dz idm , dz ext , hist idm , hist dz ext & tracks major and minor order flow, and marks potential areas of interest, such as the Golden Zone. The indicator aims to simplify complex chart analysis, providing a structured approach to observing market movements across different timeframes.
✦Understanding the Concept of Order Blocks
DZ IDM
Dz idm is the zone just below inducement . it is also know as decisional order block .
This decisional order block plays a crucial role in identifying potential trade entries and is especially effective at highlighting key reversal zones.
This order block contains inducement liquidity above it, which enhances its significance compared to other order blocks.
Chart Illustration
This diagram illustrates the IDM Order Block (OB-IDM), which is the first order block that appears just below the current IDM level.
SETTING
1. Customizable IDM OB BG Color – Demand
Define the fill color for demand-side IDM OBs to highlight buy zones clearly.
2. Customizable IDM OB BG Color – Supply
Define the fill color for supply-side IDM OBs to mark sell zones distinctly.
3. Customizable IDM OB Text Color – Demand
Choose the label color for “Demand” text so it remains legible over the demand zone.
4. *Customizable IDM OB Text Color – Supply
Choose the label color for “Supply” text so it stands out over the supply zone.
DZ EXT
Extreme Order Block (OB-EXT):
The OB-EXT refers to the extreme order block identified between a Major Low and a Major High. Positioned at the edge of a swing range, this zone often reflects the initial point of strong price movement and can serve as a key area where institutional activity may have occurred.
Usage:
The OB-EXT is used to highlight potential high-probability reversal zones. Its location at structural extremes makes it useful for identifying trade entries during deep pullbacks or at the beginning of trend shifts. Traders often monitor this level for reaction when price revisits it, as it can signal renewed interest and possible directional continuation.
Chart Illustration
Setting
1. Customizable EXT OB BG Color – Demand
Define the fill color for demand-side EXT Order Blocks to highlight key buy zones.
2. Customizable EXT OB BG Color – Supply
Define the fill color for supply-side EXT Order Blocks to mark critical sell zones.
3. Customizable EXT OB Text Color – Demand
Choose the “Demand” label color so it remains legible over the demand-zone background.
4. Customizable EXT OB Text Color – Supply
Choose the “Supply” label color so it stands out clearly against the supply-zone fill.
✦HIST IDM OB AND HIST EXT OB
This indicator automatically identifies and highlights key swing zones to enhance market structure analysis.This features help traders to focus on current swing ,
It dynamically marks the current active swing zones as:
DZ IDM: The most recent Inverse Demand Momentum zone, based on current price structure.
DZ EXT: The latest extreme zone between a major swing low and high.
It also tracks unmitigated historical zones as:
Hist DZ IDM: Previous IDM zones that have not yet been mitigated.
Hist DZ EXT: Past extreme zones that remain untested.
Chart Illustration
✦Minor Order flow
This tool is designed to help traders visualize both Smart Money Concepts (SMC) and Minor Order Flow in a structured and effective way. In a bullish market, a Minor Order Flow zone is defined as the last unmitigated selling move before price continues upward after a short pullback. In a bearish market, it marks the last unmitigated buying move before price resumes its downward trend.
The indicator tracks these zones in real-time,
TradingView
OANDA:XAUUSD Chart Image by AlgoHub100
dynamically labeling unmitigated zones in pink for visibility. Once price revisits and mitigates a zone, its color changes to a bluish tone, clearly showing which areas are active versus completed. This visual shift allows traders to focus on relevant swing levels, filtering out old or already-reacted zones.
Chart Illustration
Minor Order Flow Settings
-Control how Minor Order Flow levels appear on your chart:
-Toggle ON/OFF to enable or disable Minor Order Flow for a cleaner chart when needed.
-Max Count limits the number of Minor Order Flow levels shown (default: 10).
-Separate Bullish and Bearish Colors for easy identification of market direction.
-Custom Colors let you choose distinct visual styles for bullish and bearish flows.
✦Major Order flow
Major Order Flow
The Major Order Flow highlights the last unmitigated selling move in a bullish market and the last unmitigated buying move in a bearish market. These levels represent key institutional order blocks where price is likely to react.
Unmitigated Zones are displayed in blue on the chart, indicating potential areas of interest where price may return.
Once the zone is mitigated (touched by price), the color changes to greyish blue, signaling the zone has been tested.
Chart Illustration
MAJOR ORDER FLOW VS MINOR ORDER FLOW
Major Order Flow identifies the last unmitigated selling move in a bullish market (or buying move in a bearish market). These zones are shown in blue and change to greyish blue once mitigated. Minor Order Flow tracks the last unmitigated move within a larger structure, helping refine entries.
TradingView
OANDA:XAUUSD Chart Image by AlgoHub100
Breaker Block Indicator Overview
This indicator automatically identifies and confirms two special order block levels (breaker blocks) to highlight key supply and demand zones. It pre-marks these zones and then confirms them when price breaks through with a single candle. By focusing solely on these validated zones, the indicator helps traders concentrate on only the most significant supply and demand zones.
OB IDM Breaker Block
An OB IDM Breaker Block is an order block located just below an Inducement (IDM) level, which is a liquidity trap designed to lure traders. The indicator flags this block in advance. When price breaks the block with a single candle, it becomes a confirmed breaker block. This break indicates the inducement has failed and highlights a strong supply or demand zone.
OB EXT Breaker Block
An OB EXT Breaker Block is the extreme order block that lies between a Break of Structure (BOS) and a Change of Character (CHoCH). A BOS occurs when price clears a prior swing high or low, and a CHoCH is an early sign of reversal. The OB EXT is the first (outermost) order block in that swing, and it is marked by the indicator ahead of time. When price breaks this block with a single candle, it becomes a confirmed breaker block, signaling a major shift and highlighting a key supply or demand zone.
Breaker Block identifies a former order block that was invalidated by a break of structure and later retested. These levels often act as support or resistance zones, reflecting a potential shift in market sentiment. Traders may use Breaker Blocks to spot areas where price could react, helping with trade entries or exits.
Chart Illustration
TradingView
OANDA:XAUUSD Chart Image by AlgoHub100
✦Golden zone
The Golden Zone is the critical retracement band between the 61.8% and 78.6% Fibonacci levels of a significant market swing. This indicator automatically recognizes when price breaks a prior swing (Break of Structure, or BOS) and then shifts momentum (Change of Character, or CHoCH). As soon as these two events occur, it anchors a Fibonacci retracement between the BOS high/low and the CHoCH point, shading the area between the 0.618 and 0.786 levels (default: yellow fill).
Although TradingView’s built-in Fibonacci tool is free, it requires you to click two swing points every time—leaving you to guess whether those swings truly represent a valid BOS or CHoCH. In contrast, this indicator’s built-in logic ensures that the 61.8%–78.6% band is always drawn on the most relevant portion of price action without any extra effort. Whenever price completes a new BOS → CHoCH sequence, the Golden Zone instantly redraws, so you never have delayed or outdated retracements.
All aspects of the Golden Zone are fully customizable. You can replace the default 0.618/0.786 boundaries with any retracement values—such as 0.65/0.85 or 0.50/0.75—by entering your preferred ratios in the settings. Once set, those custom levels apply to every future swing, eliminating manual redraws. Likewise, the fill color, opacity, and boundary-line colors can be changed to match your chart’s theme. Select your color choices once, and each new Golden Zone appears consistently across multiple charts and timeframes.
By combining automatic structure alignment with one-click strategy adaptation (custom Fibonacci levels) and flexible styling (color, opacity, line thickness), this indicator saves you countless clicks and removes human error from swing selection. It provides a reliable, always-on highlight of where institutional orders commonly accumulate or distribute, making it easier to spot high-probability pullback entries or reversal areas.
Chart Illustration
This image shows our indicator automatically detecting major SMC swings and shading the Fibonacci 0.618–0.786 “Golden Zone” between each Break of Structure (BOS) and its subsequent Change of Character (CHoCH). By instantly plotting this band, you trade at a discounted price within the swing without manually identifying or drawing Fib lines. All retracement levels (e.g., 0.65/0.85, 0.50/0.75) and zone colors (fill, opacity, and boundary lines) are fully customizable—set your preferred ratios and styling once, and the indicator applies them on every new swing. This automation removes guesswork, saves clicks, and ensures you always see the most relevant pullback area in real time.
Minor Pullback
A minor pullback appears as a shallow retracement within an ongoing trend, without breaking the larger market structure. It represents a brief pause before price resumes its primary direction.
Traders can view minor pullbacks as opportunities to enter at slightly improved prices while the trend remains intact.
Observing how price recovers from a minor pullback helps confirm whether momentum continues in the same direction.
These pullbacks allow users to assess existing positions, consider small adjustments, and check nearby support or resistance levels.
Settings: Enabling “Show Internal Structure” highlights all minor pullbacks on the chart.
Example:
Major Pullback
A major pullback occurs when price retraces more deeply, often testing significant swing points or support/resistance zones. It can temporarily approach or break a key structure level before resuming the trend.
Traders might view a major pullback as a deeper buying opportunity in an uptrend or a validation of support.
Major pullbacks sometimes act as liquidity pools where stop-hunters target orders before a reversal.
The indicator flags major pullbacks distinctly, helping users recognize when caution is advised and when to adjust risk management.
Settings: Enabling “Mark High/Low” automatically labels major swing highs and lows.
Example:
SMC Market Structure
Smart Money Concepts focus on how institutions move price. This indicator highlights core structure components:
Break of Structure (BOS)
Indicates trend continuation when price breaks a previous swing high in an uptrend or swing low in a downtrend.
The indicator marks BOS events so users can verify that the prevailing direction remains intact.
Change of Character (CHOCH)
Signals a possible trend shift when price fails to make a new high in an uptrend and instead breaks the previous low, or vice versa.
CHOCH events are labeled to warn that momentum may be shifting.
Inducement (Trap Zones)
Marks areas where price briefly fakes a breakout to capture liquidity (stop-hunts) before reversing.
Identifying inducement moves helps avoid entries during false breakouts and encourages waiting for clearer confirmation.
The indicator labels induced swings, assisting in recognizing when a breakout may be a trap rather than a sustained move.
Example:
Order Blocks & Point of Interest (POI)
Order blocks represent price areas where institutional buying or selling created a significant move. This indicator distinguishes several types:
Point of Interest (POI)
A collective name for zones where price reactions often occur: Order Block, Breaker Block, and Mitigation Block.
Demand Zone (Bullish Order Block)
A price region where buy orders have overwhelmed sell orders, often forming a base before an upward move.
Traders may consider these zones when seeking long entries.
Supply Zone (Bearish Order Block)
Where sell orders exceed buy orders, frequently causing a downward reversal.
Traders might watch these zones for short entries or to set profit targets.
Breaker Block & Mitigation Block
Breaker Block appears after price breaks through a prior order block and then returns to test it from the opposite side, acting as flipped support or resistance.
Mitigation Block represents areas where institutions address unfilled orders created by previous moves, helping identify unbalanced liquidity.
Single Candle Order Block (SCOB)
A specific order block defined by one candlestick that initiates a notable price imbalance.
SCOBs often signal precise institutional interest and are flagged to show potential reversal or continuation levels.
Settings:
Enabling “Show POI” displays all Order Blocks, Breaker Blocks, and Mitigation Blocks.
Enabling “Institutional Order Block” toggles Demand/Supply Zones.
CONCLUSION
The Advance SMC ICT Indicator stands out by translating Smart Money Concepts into clear, actionable visuals—mapping inducement zones alongside four specialized order block types, including IDM and Extreme Order Blocks, to highlight where institutional activity is most likely concentrated. By combining precise structure analysis (BOS, CHOCH, inducements) with liquidity and fair value gap identification, it gives traders a nuanced view of where supply and demand pressures intersect. In practice, this means users can more easily spot where stop-runs may occur, recognize high-probability entry areas, and avoid common traps created by large-scale order flows.
While the Advance SMC ICT Indicator provides valuable insights into how professional participants interact with price, it is not a standalone trading system. Traders should always confirm its signals with their own analysis, apply sound risk management techniques, and consider broader market context before executing any trade.
Institutional MFI + VWAP Engine PROMoney flow index, shows green when momentum is bullish and red when bearish
Institutional Momentum PROBullish and bearish momentum, showing potential exhaustion on the long side and short side
VWAP Institutional Playbook PROInstitution trading playbook, buy and sell signals only when 3 confluences line up(FVG, Order blocks, Liquidity Sweeps)
DB - Range Filter heikenashi Strategy
DB - Range Filter Heikenashi Strategy
Smart Filtering Meets Heiken-Ashi Precision for Adaptive Trend Breakouts
This is not your average range filter strategy. Built from the ground up with adaptive signal logic and hybrid candle interpretation, this script merges range-based volatility filtering with Heiken-Ashi smoothing to isolate meaningful breakouts—while filtering out noise with surgical precision.
🔍 Key Innovations:
• Dynamic Range Filtering Engine: Combines smoothed average range with directional bias to create high-confidence entries.
• Candle Type Toggle: Choose between standard candles or Heiken-Ashi to shape your signals to your trading style.
• Dual-Layer Trend Confirmation: Upward and downward movement counters ensure trend commitment before triggering entries.
• Time-Filtered Backtesting: Easily isolate strategy performance within precise historical windows.
• Optional Smart Stops: Add stop loss & take profit rules without changing the core logic—perfect for risk-managed deployment.
📈 Visual & Practical Features:
• Multi-color bar analysis to identify strength, weakness, and transition zones.
• Upper and lower dynamic bands for visualizing profit targets and range boundaries.
• Buy/Sell signal labels with direction-aware logic to avoid choppy conditions.
• Ideal for high-volatility assets (e.g., BTC) on short timeframes, but fully tunable for any market.
Built for traders who value clarity over chaos, this strategy aims to reduce false signals and offer a cleaner execution framework for trend followers and breakout scalpers alike.
> Make volatility your ally, not your enemy.
S&P500 Long nach X roten Tagen)The strategy buys the S&P future after 4 consecutive red days and an elevated VIX index, and exits either time-based, with a trailing stop, or after a predefined holding period.
