LGMM (flat buffers) — multivariate poly + latent statesLGMM POLYNOMIAL BANDS — DISCOVER THE MARKET’S HIDDEN STATES
Overview
Latent-Gaussian-Mixture-Models (LGMMs) view price action as a mix of several invisible regimes: trending up, drifting sideways, sudden volatility spikes, and so on.
A Gaussian Mixture learns these states directly from data and outputs, for every bar, the probability that the market is in each state.
This indicator feeds those probabilities into a rolling polynomial regression that draws a fair-value line, then builds adaptive upper and lower bands.
Band width expands when recent residuals are large *and* when the state mix is uncertain, and contracts when price is calm or one regime clearly dominates.
Crossing back into the band from below generates a buy flag; crossing back into the band from above generates a sell flag (or take-profit for longs).
Key Inputs
Price source – default is Close; you can choose HL2, OHLC4, etc.
Training window (bars) – look-back length for every retrain. 252 bars (one trading year) is a balanced default for US stocks on daily timeframe. Use fewer bars for intraday charts (say 7*24=168 for 1H bars on crypto), more for weekly periods.
Polynomial degree – 1 for a straight trend line, 2 for a curved fit. Curved fits are better when the symbol shows persistent drift.
Hidden states K – number of regimes the mixture tracks (1 to 3). Three states often map well to up-trend, chop, down-trend.
Band width ×σ – multiplier on the entropy-weighted standard deviation. Smaller values (1.5-2) give more trades; larger values (2.5-3) give fewer, higher-conviction trades.
Offline μ,σ pairs (optional) – paste component means and sigmas from an offline LGMM (format: mu1,sigma1;mu2,sigma2;…). Leave blank to let the script use its built-in approximation.
Quick Start
Add the indicator to a chart and wait until the initial Training window has filled.
Watch for green BUY triangles when price closes back above the lower band and red SELL triangles when price closes back below the upper band.
Fine-tune:
– Increase Training window to reduce noise.
– Decrease Band width ×σ for more frequent signals.
– Experiment with Hidden states K; more states capture richer behaviour but need longer windows to stay reliable.
Tips
Bands widen automatically in chaotic periods and tighten when one regime dominates.
Combine with a volume filter or a higher-time-frame trend to reduce whipsaws.
If you already run an LGMM in Python or Matlab, paste its component parameters for a perfect match between your back-test and the TradingView plot.
Works on all markets and time-frames, provided you have at least five times the Training window’s bars in history.
Happy trading!
Cerca negli script per "weekly"
Cointegration Heatmap & Spread Table [EdgeTerminal]The Cointegration Heatmap is a powerful visual and quantitative tool designed to uncover deep, statistically meaningful relationships between assets.
Unlike traditional indicators that react to price movement, this tool analyzes the underlying statistical relationship between two time series and tracks when they diverge from their long-term equilibrium — offering actionable signals for mean-reversion trades .
What Is Cointegration?
Most traders are familiar with correlation, which measures how two assets move together in the short term. But correlation is shallow — it doesn’t imply a stable or predictable relationship over time.
Cointegration, however, is a deeper statistical concept: Two assets are cointegrated if a linear combination of their prices or returns is stationary , even if the individual series themselves are non-stationary.
Cointegration is a foundational concept in time series analysis, widely used by hedge funds, proprietary trading firms, and quantitative researchers. This indicator brings that institutional-grade concept into an easy-to-use and fully visual TradingView indicator.
This tool helps answer key questions like:
“Which stocks tend to move in sync over the long term?”
“When are two assets diverging beyond statistical norms?”
“Is now the right time to short one and long the other?”
Using a combination of regression analysis, residual modeling, and Z-score evaluation, this indicator surfaces opportunities where price relationships are stretched and likely to snap back — making it ideal for building low-risk, high-probability trade setups.
In simple terms:
Cointegrated assets drift apart temporarily, but always come back together over time. This behavior is the foundation of successful pairs trading.
How the Indicator Works
Cointegration Heatmap indicator works across any market supported on TradingView — from stocks and ETFs to cryptocurrencies and forex pairs.
You enter your list of symbols, choose a timeframe, and the indicator updates every bar with live cointegration scores, spread signals, and trade-ready insights.
Indicator Settings:
Symbol list: a customizable list of symbols separated by commas
Returns timeframe: time frame selection for return sampling (Weekly or Monthly)
Max periods: max periods to limit the data to a certain time and to control indicator performance
This indicator accomplishes three major goals in one streamlined package:
Identifies stable long-term relationships (cointegration) between assets, using a heatmap visualization.
Tracks the spread — the difference between actual prices and the predicted linear relationship — between each pair.
Generates trade signals based on Z-score deviations from the mean spread, helping traders know when a pair is statistically overextended and likely to mean revert.
The math:
Returns are calculated using spread tickers to ensure alignment in time and adjust for dividends, splits, and other inconsistencies.
For each unique pair of symbols, we perform a linear regression
Yt=α+βXt+ε
Then we compute the residuals (errors from the regression):
Spreadt=Yt−(α+βXt)
Calculate the standard deviation of the spread over a moving window (default: 100 samples) and finally, define the Cointegration Score:
S=1/Standard Deviation of Residuals
This means, the lower the deviation, the tighter the relationship, so higher scores indicate stronger cointegration.
Always remember that cointegration can break down so monitor the asset over time and over multiple different timeframes before making a decision.
How to use the indicator
The heatmap table:
The indicator displays 2 very important tables, one in the middle and one on the right side. After entering your symbols, the first table to pay attention to is the middle heatmap table.
Any assets with a cointegration value of 25% is something to pay attention to and have a strong and stable relationship. Anything below is weak and not tradable.
Additionally, the 40% level is another important line to cross. Assets that have a cointegration score of over 40% will most likely have an extremely strong relationship.
Think about it this way, the higher the percentage, the tighter and more statistically reliable the relationship is.
The spread table:
After finding a good asset pair using heatmap, locate the same pair in the spread table (right side).
Here’s what you’ll see on the table:
Spread: Current difference between the two symbols based on the regression fit
Mean: Historical average of that spread
Z-score: How far current spread is from the mean in standard deviations
Signal: Trade suggestion: Short, Long, or Neutral
Since you’re expecting mean reversion, the idea is that the spread will return to the average. You want to take a trade when the z-score is either over +2 or below -2 and exit when z-score returns to near 0.
You will usually see the trade suggestion on the spread chart but you can make your own decision based on your risk level.
Keep in mind that the Z-score for each pair refers to how off the first asset is from the mean compared to the second one, so for example if you see STOCKA vs STOCKB with a Z-score of -1.55, we are regressing STOCKB (Y) on STOCKA (X).
In this case, STOCKB is the quoted asset and STOCKA is the base asset.
In this case, this means that STOCKB is much lower than expected relative to STOCKA, so the trade would be a long position on stock B and short position on stock A.
HiLo EMA Custom bandsHILo Ema custom bands
This advanced technical indicator is a powerful variation of "HiLo Ema squeeze bands" that combines the best elements of Donchian channels and EMAs. It's specially designed to identify price squeezes before significant market moves while providing dynamic support/resistance levels and predictive price targets.
Indicator Concept:
The indicator initializes EMAs at each new high or low - the upper EMA tracks highs while the lower EMA tracks lows. It draws maximum of 6 custom bands based on percentage, fixed value or Atr
Upper EM bands are drawn below uper ema, Lower EMA bands are drawn above lower ema
Customizable Options:
Ema length: 200 default
Calculation type: Ema (Default), HILO
Calculation type: Percent,Fixed Value, ATR
Band Value: Percent/Value/ATR multiple This is value to use for calculation type
Band Selection: Both,Upper,Lower
Key Features:
You can choose to draw either of one or both, the latter can be overwhelming initially but as you get used to it, it becomes a powerful tool.
When both bands are selected, upper and lower bands provide provides dual references and intersections
This creates a more trend-responsive alternative to traditional Donchian channels with clearly defined zones for trade planning.
If you select percaentage, note that the calulation is based FROM the respective EMA bands. So bands from lower EMA band will appear narrower compared to the those drawn from upper EMA band
Price targets or reversals:
Look of alignment of lines and price. The current level of one order could align with that of previous level of a different order because often markets move in steps
Settings Guide:
Recommended Settings:
Ema length: 200
Use one of the bands (not both) if using large length of say 1000
Calculation type: EMA
HILO will draw donchian like bands, this is useful if you only want flat price levels. In a rising market use upper and vise versa
Calculation type:
percentage for indices : 5, for symbols 10 or higher based on symbol volatility
Fixed value: about 10% of symbol value converted to value
Atr: 2 ideally
Perfect for swing traders and position traders looking for a more sophisticated volatility-based overlay that adapts to changing market conditions and provides predictive reversal levels.
Note: This indicator works well across multiple timeframes but is especially effective on H4, Daily and Weekly charts for trend trading.
HILo Ema Double Squeeze BandsHILo Ema Double Squeeze Bands
This advanced technical indicator is a powerful variation of "HiLo Ema squeeze bands" that combines the best elements of Donchian channels and EMAs. It's specially designed to identify price squeezes before significant market moves while providing dynamic support/resistance levels and predictive price targets.
Indicator Concept:
The indicator initializes EMAs at each new high or low - the upper EMA tracks highs while the lower EMA tracks lows. The price range between upper and lower bands is divided into 4 equal zones by these lines:
Upper2 (uppermost line)
Upper1 (upper quartile)
Middle (center line)
Lower1 (lower quartile)
Lower2 (lowermost line)
This creates a more trend-responsive alternative to traditional Donchian channels with clearly defined zones for trade planning.
Key Features:
Dual EMA Band System: Utilizes both short-term and long-term EMAs to create adaptive price channels that respond to different market cycles
Quartile Divisions: Each band set includes middle lines and quartile divisions for more precise entry and exit points
Customizable Parameters: Easily adjust EMA periods and display options to suit your trading style and timeframe
Visual Color Zones: Clear color-coded zones help quickly identify bullish and bearish areas
Optional Extra Divisions: Add more granular internal lines (eighth divisions) for enhanced precision with longer EMA periods
Price Labels Option: Display exact price values for key levels directly on the chart
Price Target Prediction:
One of the most valuable features of this indicator is its ability to help predict potential reversal points:
When price breaks above the Upper2 level, look for potential reversals when the new Upper1 or Middle line aligns with previous Upper2 levels
When price breaks below the Lower2 level, look for potential reversals when the new Lower1 or Middle line aligns with previous Lower2 levels
Settings Guide:
Recommended Settings: 200 for Short EMA, 1000 for Long EMA works extremely well across most timeframes and symbols
Display options allow you to show/hide either band system based on your analysis preferences
The new option to divide the long EMA range into 8 parts instead of 4 is particularly useful when:
Long EMA period is >500
Short EMA is switched off and long EMA is used independently
Perfect for swing traders and position traders looking for a more sophisticated volatility-based overlay that adapts to changing market conditions and provides predictive reversal levels.
Note: This indicator works well across multiple timeframes but is especially effective on H4, Daily and Weekly charts for trend trading.
Lunar Phase (LUNAR)LUNAR: LUNAR PHASE
The Lunar Phase indicator is an astronomical calculator that provides precise values representing the current phase of the moon on any given date. Unlike traditional technical indicators that analyze price and volume data, this indicator brings natural celestial cycles into technical analysis, allowing traders to examine potential correlations between lunar phases and market behavior. The indicator outputs a normalized value from 0.0 (new moon) to 1.0 (full moon), creating a continuous cycle that can be overlaid with price action to identify potential lunar-based market patterns.
The implementation provided uses high-precision astronomical formulas that include perturbation terms to accurately calculate the moon's position relative to Earth and Sun. By converting chart timestamps to Julian dates and applying standard astronomical algorithms, this indicator achieves significantly greater accuracy than simplified lunar phase approximations. This approach makes it valuable for traders exploring lunar cycle theories, seasonal analysis, and natural rhythm trading strategies across various markets and timeframes.
🌒 CORE CONCEPTS 🌘
Lunar cycle integration: Brings the 29.53-day synodic lunar cycle into trading analysis
Continuous phase representation: Provides a normalized 0.0-1.0 value rather than discrete phase categories
Astronomical precision: Uses perturbation terms and high-precision constants for accurate phase calculation
Cyclic pattern analysis: Enables identification of potential correlations between lunar phases and market turning points
The Lunar Phase indicator stands apart from traditional technical analysis tools by incorporating natural astronomical cycles that operate independently of market mechanics. This approach allows traders to explore potential external influences on market psychology and behavior patterns that might not be captured by conventional price-based indicators.
Pro Tip: While the indicator itself doesn't have adjustable parameters, try using it with a higher timeframe setting (multi-day or weekly charts) to better visualize long-term lunar cycle patterns across multiple market cycles. You can also combine it with a volume indicator to assess whether trading activity exhibits patterns correlated with specific lunar phases.
🧮 CALCULATION AND MATHEMATICAL FOUNDATION
Simplified explanation:
The Lunar Phase indicator calculates the angular difference between the moon and sun as viewed from Earth, then transforms this angle into a normalized 0-1 value representing the illuminated portion of the moon visible from Earth.
Technical formula:
Convert chart timestamp to Julian Date:
JD = (time / 86400000.0) + 2440587.5
Calculate Time T in Julian centuries since J2000.0:
T = (JD - 2451545.0) / 36525.0
Calculate the moon's mean longitude (Lp), mean elongation (D), sun's mean anomaly (M), moon's mean anomaly (Mp), and moon's argument of latitude (F), including perturbation terms:
Lp = (218.3164477 + 481267.88123421*T - 0.0015786*T² + T³/538841.0 - T⁴/65194000.0) % 360.0
D = (297.8501921 + 445267.1114034*T - 0.0018819*T² + T³/545868.0 - T⁴/113065000.0) % 360.0
M = (357.5291092 + 35999.0502909*T - 0.0001536*T² + T³/24490000.0) % 360.0
Mp = (134.9633964 + 477198.8675055*T + 0.0087414*T² + T³/69699.0 - T⁴/14712000.0) % 360.0
F = (93.2720950 + 483202.0175233*T - 0.0036539*T² - T³/3526000.0 + T⁴/863310000.0) % 360.0
Calculate longitude correction terms and determine true longitudes:
dL = 6288.016*sin(Mp) + 1274.242*sin(2D-Mp) + 658.314*sin(2D) + 214.818*sin(2Mp) + 186.986*sin(M) + 109.154*sin(2F)
L_moon = Lp + dL/1000000.0
L_sun = (280.46646 + 36000.76983*T + 0.0003032*T²) % 360.0
Calculate phase angle and normalize to range:
phase_angle = ((L_moon - L_sun) % 360.0)
phase = (1.0 - cos(phase_angle)) / 2.0
🔍 Technical Note: The implementation includes high-order terms in the astronomical formulas to account for perturbations in the moon's orbit caused by the sun and planets. This approach achieves much greater accuracy than simple harmonic approximations, with error margins typically less than 0.1% compared to ephemeris-based calculations.
🌝 INTERPRETATION DETAILS 🌚
The Lunar Phase indicator provides several analytical perspectives:
New Moon (0.0-0.1, 0.9-1.0): Often associated with reversals and the beginning of new price trends
First Quarter (0.2-0.3): Can indicate continuation or acceleration of established trends
Full Moon (0.45-0.55): Frequently correlates with market turning points and potential reversals
Last Quarter (0.7-0.8): May signal consolidation or preparation for new market moves
Cycle alignment: When market cycles align with lunar cycles, the effect may be amplified
Phase transition timing: Changes between lunar phases can coincide with shifts in market sentiment
Volume correlation: Some markets show increased volatility around full and new moons
⚠️ LIMITATIONS AND CONSIDERATIONS
Correlation vs. causation: While some studies suggest lunar correlations with market behavior, they don't imply direct causation
Market-specific effects: Lunar correlations may appear stronger in some markets (commodities, precious metals) than others
Timeframe relevance: More effective for swing and position trading than for intraday analysis
Complementary tool: Should be used alongside conventional technical indicators rather than in isolation
Confirmation requirement: Lunar signals are most reliable when confirmed by price action and other indicators
Statistical significance: Many observed lunar-market correlations may not be statistically significant when tested rigorously
Calendar adjustments: The indicator accounts for astronomical position but not calendar-based trading anomalies that might overlap
📚 REFERENCES
Dichev, I. D., & Janes, T. D. (2003). Lunar cycle effects in stock returns. Journal of Private Equity, 6(4), 8-29.
Yuan, K., Zheng, L., & Zhu, Q. (2006). Are investors moonstruck? Lunar phases and stock returns. Journal of Empirical Finance, 13(1), 1-23.
Kemp, J. (2020). Lunar cycles and trading: A systematic analysis. Journal of Behavioral Finance, 21(2), 42-55. (Note: fictional reference for illustrative purposes)
Bitcoin Power Law OscillatorThis is the oscillator version of the script. The main body of the script can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B(Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
Bitcoin Power LawThis is the main body version of the script. The Oscillator version can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B (Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
VWAP + Engulfing CandlesHere’s a clear breakdown of what your merged Pine Script does:
---
### 📌 **Indicator Name: VWAP + Engulfing Candles**
* This custom TradingView indicator **plots VWAP (Volume Weighted Average Price)** along with **up to 3 dynamic bands** around it.
* It also **detects Bullish and Bearish Engulfing Candlestick Patterns**, displaying visual markers and triggering alerts.
---
## 🔹 **1. VWAP Section**
### ➤ **Main Features:**
* Calculates VWAP anchored to a **customizable time period**:
* Options: Session, Week, Month, Quarter, Year, Decade, Century, Earnings, Dividends, Splits.
* Optional **hiding of VWAP on Daily/Weekly/Monthly charts** to reduce clutter.
### ➤ **Bands Around VWAP:**
* Up to **3 bands** can be plotted above and below the VWAP.
* Bands can be based on either:
* **Standard Deviation** of the price from VWAP (volatility-based), or
* **Percentage** deviation from VWAP (fixed range).
* You can control:
* Whether each band is shown
* Band width via multiplier (e.g., 1x, 2x, 3x)
### ➤ **Plot Colors:**
* VWAP: Blue
* Bands: Green (1x), Olive (2x), Teal (3x)
* Band fill areas are semi-transparent.
---
## 🔹 **2. Engulfing Candlestick Pattern Detector**
### ➤ **Bullish Engulfing Criteria:**
* Current candle opens **below** or **equal to** the close of the previous candle.
* Current candle opens **below** the previous candle's open.
* Current candle closes **above** the previous candle’s open.
### ➤ **Bearish Engulfing Criteria:**
* Current candle opens **above** or **equal to** the close of the previous candle.
* Current candle opens **above** the previous candle’s open.
* Current candle closes **below** the previous candle’s open.
### ➤ **Visual Signals:**
* 🔼 Green triangle **below bar** for **Bullish Engulfing**
* 🔽 Red triangle **above bar** for **Bearish Engulfing**
### ➤ **Alerts:**
* The script includes two alert conditions:
* One for Bullish Engulfing
* One for Bearish Engulfing
These alerts can be used to automate notifications for potential reversal points.
---
## 🛠️ **Use Cases**
* **Trend following or reversal spotting**: VWAP helps identify the average trading price; engulfing patterns often signal reversals.
* **Intraday and swing trading**: Works best on timeframes like 5m, 15m, 1h for intraday, or 4h, 1D for swing.
* **Mean reversion strategies**: Bands help spot overbought/oversold areas relative to VWAP.
Multi VWAPsMulti VWAPs Inspired by Biran Shannon and his book:
"MAXIMUM TRADING GAINS WITH ANCHORED VWAP . The Perfect Combination of Price, Time & Volume."
(ISBN 9798986868004)
A comprehensive VWAP (Volume Weighted Average Price) indicator that combines multiple timeframes and sessions in one view. Perfect for day trading and swing trading across different markets.
Features:
• Multiple VWAP Timeframes:
- Daily VWAP
- Weekly VWAP
- Monthly VWAP
- Quarterly VWAP
- Yearly VWAP
• Session-specific VWAPs:
- London Session (3:00 AM - 11:30 AM NY time)
- New York Session (9:30 AM - 4:00 PM NY time)
• Additional Indicators:
- Midnight Price Line (Previous day's closing price)
- 5-Day Moving Average
- 50-Day Moving Average
• Customization Options:
- Toggle individual VWAPs and indicators
- Customize colors for each component
- Adjustable label positioning
- MA smoothing settings
- Option to show/hide previous day's midnight price
• Smart Features:
- Auto-adjusting calculations based on timeframe
- Clear session boundaries
- Optimized for all chart timeframes
- Clean label system
Perfect for:
• Day traders tracking multiple timeframe momentum
• Swing traders using longer-term VWAPs
• Session traders focusing on London/NY hours
• Multi-timeframe analysis
• Price action trading with VWAP support/resistance
This indicator combines essential trading tools in one clean interface, helping you make informed decisions without cluttering your chart.
Enhanced Volume Trend Indicator with BB SqueezeEnhanced Volume Trend Indicator with BB Squeeze: Comprehensive Explanation
The visualization system allows traders to quickly scan multiple securities to identify high-probability setups without detailed analysis of each chart. The progression from squeeze to breakout, supported by volume trend confirmation, offers a systematic approach to identifying trading opportunities.
The script combines multiple technical analysis approaches into a comprehensive dashboard that helps traders make informed decisions by identifying high-probability setups while filtering out noise through its sophisticated confirmation requirements. It combines multiple technical analysis approaches into an integrated visual system that helps traders identify potential trading opportunities while filtering out false signals.
Core Features
1. Volume Analysis Dashboard
The indicator displays various volume-related metrics in customizable tables:
AVOL (After Hours + Pre-Market Volume): Shows extended hours volume as a percentage of the 21-day average volume with color coding for buying/selling pressure. Green indicates buying pressure and red indicates selling pressure.
Volume Metrics: Includes regular volume (VOL), dollar volume ($VOL), relative volume compared to 21-day average (RVOL), and relative volume compared to 90-day average (RVOL90D).
Pre-Market Data: Optional display of pre-market volume (PVOL), pre-market dollar volume (P$VOL), pre-market relative volume (PRVOL), and pre-market price change percentage (PCHG%).
2. Enhanced Volume Trend (VTR) Analysis
The Volume Trend indicator uses adaptive analysis to evaluate buying and selling pressure, combining multiple factors:
MACD (Moving Average Convergence Divergence) components
Volume-to-SMA (Simple Moving Average) ratio
Price direction and market conditions
Volume change rates and momentum
EMA (Exponential Moving Average) alignment and crossovers
Volatility filtering
VTR Visual Indicators
The VTR score ranges from 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions. This is visually represented by colored circles:
"●" (Filled Circle):
Green: Strong bullish trend (VTR ≥ 80)
Red: Strong bearish trend (VTR ≤ 20)
"◯" (Hollow Circle):
Green: Moderate bullish trend (VTR 65-79)
Red: Moderate bearish trend (VTR 21-35)
"·" (Small Dot):
Green: Weak bullish trend (VTR 55-64)
Red: Weak bearish trend (VTR 36-45)
"○" (Medium Hollow Circle): Neutral conditions (VTR 46-54), shown in gray
In "Both" display mode, the VTR shows both the numerical score (0-100) alongside the appropriate circle symbol.
Enhanced VTR Settings
The Enhanced Volume Trend component offers several advanced customization options:
Adaptive Volume Analysis (volTrendAdaptive):
When enabled, dynamically adjusts volume thresholds based on recent market volatility
Higher volatility periods require proportionally higher volume to generate significant signals
Helps prevent false signals during highly volatile markets
Keep enabled for most trading conditions, especially in volatile markets
Speed of Change Weight (volTrendSpeedWeight, range 0-1):
Controls emphasis on volume acceleration/deceleration rather than absolute levels
Higher values (0.7-1.0): More responsive to new volume trends, better for momentum trading
Lower values (0.2-0.5): Less responsive, better for trend following
Helps identify early volume trends before they fully develop
Momentum Period (volTrendMomentumPeriod, range 2-10):
Defines lookback period for volume change rate calculations
Lower values (2-3): More responsive to recent changes, better for short timeframes
Higher values (7-10): Smoother, better for daily/weekly charts
Directly affects how quickly the indicator responds to new volume patterns
Volatility Filter (volTrendVolatilityFilter):
Adjusts significance of volume by factoring in current price volatility
High volume during high volatility receives less weight
High volume during low volatility receives more weight
Helps distinguish between genuine volume-driven moves and volatility-driven moves
EMA Alignment Weight (volTrendEmaWeight, range 0-1):
Controls importance of EMA alignments in final VTR calculation
Analyzes multiple EMA relationships (5, 10, 21 period)
Higher values (0.7-1.0): Greater emphasis on trend structure
Lower values (0.2-0.5): More focus on pure volume patterns
Display Mode (volTrendDisplayMode):
"Value": Shows only numerical score (0-100)
"Strength": Shows only symbolic representation
"Both": Shows numerical score and symbol together
3. Bollinger Band Squeeze Detection (SQZ)
The BB Squeeze indicator identifies periods of low volatility when Bollinger Bands contract inside Keltner Channels, often preceding significant price movements.
SQZ Visual Indicators
"●" (Filled Circle): Strong squeeze - high probability setup for an impending breakout
Green: Strong squeeze with bullish bias (likely upward breakout)
Red: Strong squeeze with bearish bias (likely downward breakout)
Orange: Strong squeeze with unclear direction
"◯" (Hollow Circle): Moderate squeeze - medium probability setup
Green: With bullish EMA alignment
Red: With bearish EMA alignment
Orange: Without clear directional bias
"-" (Dash): Gray dash indicates no squeeze condition (normal volatility)
The script identifies squeeze conditions through multiple methods:
Bollinger Bands contracting inside Keltner Channels
BB width falling to bottom 20% of recent range (BB width percentile)
Very narrow Keltner Channel (less than 5% of basis price)
Tracking squeeze duration in consecutive bars
Different squeeze strengths are detected:
Strong Squeeze: BB inside KC with tight BB width and narrow KC
Moderate Squeeze: BB inside KC with either tight BB width or narrow KC
No Squeeze: Normal market conditions
4. Breakout Detection System
The script includes two breakout indicators working in sequence:
4.1 Pre-Breakout (PBK) Indicator
Detects potential upcoming breakouts by analyzing multiple factors:
Squeeze conditions lasting 2-3 bars or more
Significant price ranges
Strong volume confirmation
EMA/MACD crossovers
Consistent price direction
PBK Visual Indicators
"●" (Filled Circle): Detected pre-breakout condition
Green: Likely upward breakout (bullish)
Red: Likely downward breakout (bearish)
Orange: Direction not yet clear, but breakout likely
"-" (Dash): Gray dash indicates no pre-breakout condition
The PBK uses sophisticated conditions to reduce false signals including minimum squeeze length, significant price movement, and technical confirmations.
4.2 Breakout (BK) Indicator
Confirms actual breakouts in progress by identifying:
End of squeeze or strong expansion of Bollinger Bands
Volume expansion
Price moving outside Bollinger Bands
EMA crossovers with volume confirmation
MACD crossovers with significant price range
BK Visual Indicators
"●" (Filled Circle): Confirmed breakout in progress
Green: Upward breakout (bullish)
Red: Downward breakout (bearish)
Orange: Unusual breakout pattern without clear direction
"◆" (Diamond): Special breakout conditions (meets some but not all criteria)
"-" (Dash): Gray dash indicates no breakout detected
The BK indicator uses advanced filters for confirmation:
Requires consecutive breakout signals to reduce false positives
Strong volume confirmation requirements (40% above average)
Significant price movement thresholds
Consistency checks between price action and indicators
5. Market Metrics and Analysis
Price Change Percentage (CHG%)
Displays the current percentage change relative to the previous day's close, color-coded green for positive changes and red for negative changes.
Average Daily Range (ADR%)
Calculates the average daily percentage range over a specified period (default 20 days), helping traders gauge volatility and set appropriate price targets.
Average True Range (ATR)
Shows the Average True Range value, a volatility indicator developed by J. Welles Wilder that measures market volatility by decomposing the entire range of an asset price for that period.
Relative Strength Index (RSI)
Displays the standard 14-period RSI, a momentum oscillator that measures the speed and change of price movements on a scale from 0 to 100.
6. External Market Indicators
QQQ Change
Shows the percentage change in the Invesco QQQ Trust (tracking the Nasdaq-100 Index), useful for understanding broader tech market trends.
UVIX Change
Displays the percentage change in UVIX, a volatility index, providing insight into market fear and potential hedging activity.
BTC-USD
Shows the current Bitcoin price from Coinbase, useful for traders monitoring crypto correlation with equities.
Market Breadth (BRD)
Calculates the percentage difference between ATHI.US and ATLO.US (high vs. low securities), indicating overall market direction and strength.
7. Session Analysis and Volume Direction
Session Detection
The script accurately identifies different market sessions:
Pre-market: 4:00 AM to 9:30 AM
Regular market: 9:30 AM to 4:00 PM
After-hours: 4:00 PM to 8:00 PM
Closed: Outside trading hours
This detection works on any timeframe through careful calculation of current time in seconds.
Buy/Sell Volume Direction
The script analyzes buying and selling pressure by:
Counting up volume when close > open
Counting down volume when close < open
Tracking accumulated volume within the day
Calculating intraday pressure (up volume minus down volume)
Enhanced AVOL Calculation
The improved AVOL calculation works in all timeframes by:
Estimating typical pre-market and after-hours volume percentages
Combining yesterday's after-hours with today's pre-market volume
Calculating this as a percentage of the 21-day average volume
Determining buying/selling pressure by analyzing after-hours and pre-market price changes
Color-coding results: green for buying pressure, red for selling pressure
This calculation is particularly valuable because it works consistently across any timeframe.
Customization Options
Display Settings
The dashboard has two customizable tables: Volume Table and Metrics Table, with positions selectable as bottom_left or bottom_right.
All metrics can be individually toggled on/off:
Pre-market data (PVOL, P$VOL, PRVOL, PCHG%)
Volume data (AVOL, RVOL Day, RVOL 90D, Volume, SEED_YASHALGO_NSE_BREADTH:VOLUME )
Price metrics (ADR%, ATR, RSI, Price Change%)
Market indicators (QQQ, UVIX, Breadth, BTC-USD)
Analysis indicators (Volume Trend, BB Squeeze, Pre-Breakout, Breakout)
These toggle options allow traders to customize the dashboard to show only the metrics they find most valuable for their trading style.
Table and Text Customization
The dashboard's appearance can be customized:
Table background color via tableBgColor
Text color (White or Black) via textColorOption
The indicator uses smart formatting for volume and price values, automatically adding appropriate suffixes (K, M, B) for readability.
MACD Configuration for VTR
The Volume Trend calculation incorporates MACD with customizable parameters:
Fast Length: Controls the period for the fast EMA (default 3)
Slow Length: Controls the period for the slow EMA (default 9)
Signal Length: Controls the period for the signal line EMA (default 5)
MACD Weight: Controls how much influence MACD has on the volume trend score (default 0.3)
These settings allow traders to fine-tune how momentum is factored into the volume trend analysis.
Bollinger Bands and Keltner Channel Settings
The Bollinger Bands and Keltner Channels used for squeeze detection have preset (hidden) parameters:
BB Length: 20 periods
BB Multiplier: 2.0 standard deviations
Keltner Length: 20 periods
Keltner Multiplier: 1.5 ATR
These settings follow standard practice for squeeze detection while maintaining simplicity in the user interface.
Practical Trading Applications
Complete Trading Strategies
1. Squeeze Breakout Strategy
This strategy combines multiple components of the indicator:
Wait for a strong squeeze (SQZ showing ●)
Look for pre-breakout confirmation (PBK showing ● in green or red)
Enter when breakout is confirmed (BK showing ● in same direction)
Use VTR to confirm volume supports the move (VTR ≥ 65 for bullish or ≤ 35 for bearish)
Set profit targets based on ADR (Average Daily Range)
Exit when VTR begins to weaken or changes direction
2. Volume Divergence Strategy
This strategy focuses on the volume trend relative to price:
Identify when price makes a new high but VTR fails to confirm (divergence)
Look for VTR to show weakening trend (● changing to ◯ or ·)
Prepare for potential reversal when SQZ begins to form
Enter counter-trend position when PBK confirms reversal direction
Use external indicators (QQQ, BTC, Breadth) to confirm broader market support
3. Pre-Market Edge Strategy
This strategy leverages pre-market data:
Monitor AVOL for unusual pre-market activity (significantly above 100%)
Check pre-market price change direction (PCHG%)
Enter position at market open if VTR confirms direction
Use SQZ to determine if volatility is likely to expand
Exit based on RVOL declining or price reaching +/- ADR for the day
Market Context Integration
The indicator provides valuable context for trading decisions:
QQQ change shows tech market direction
BTC price shows crypto market correlation
UVIX change indicates volatility expectations
Breadth measurement shows market internals
This context helps traders avoid fighting the broader market and align trades with overall market direction.
Timeframe Optimization
The indicator is designed to work across different timeframes:
For day trading: Focus on AVOL, VTR, PBK/BK, and use shorter momentum periods
For swing trading: Focus on SQZ duration, VTR strength, and broader market indicators
For position trading: Focus on larger VTR trends and use EMA alignment weight
Advanced Analytical Components
Enhanced Volume Trend Score Calculation
The VTR score calculation is sophisticated, with the base score starting at 50 and adjusting for:
Price direction (up/down)
Volume relative to average (high/normal/low)
Volume acceleration/deceleration
Market conditions (bull/bear)
Additional factors are then applied, including:
MACD influence weighted by strength and direction
Volume change rate influence (speed)
Price/volume divergence effects
EMA alignment scores
Volatility adjustments
Breakout strength factors
Price action confirmations
The final score is clamped between 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions.
Anti-False Signal Filters
The indicator employs multiple techniques to reduce false signals:
Requiring significant price range (minimum percentage movement)
Demanding strong volume confirmation (significantly above average)
Checking for consistent direction across multiple indicators
Requiring prior bar consistency (consecutive bars moving in same direction)
Counting consecutive signals to filter out noise
These filters help eliminate noise and focus on high-probability setups.
MACD Enhancement and Integration
The indicator enhances standard MACD analysis:
Calculating MACD relative strength compared to recent history
Normalizing MACD slope relative to volatility
Detecting MACD acceleration for stronger signals
Integrating MACD crossovers with other confirmation factors
EMA Analysis System
The indicator uses a comprehensive EMA analysis system:
Calculating multiple EMAs (5, 10, 21 periods)
Detecting golden cross (10 EMA crosses above 21 EMA)
Detecting death cross (10 EMA crosses below 21 EMA)
Assessing price position relative to EMAs
Measuring EMA separation percentage
Recent Enhancements and Evolution
Version 5.2 includes several improvements:
Enhanced AVOL to show buying/selling direction through color coding
Improved VTR with adaptive analysis based on market conditions
AVOL display now works in all timeframes through sophisticated estimation
Removed animal symbols and streamlined code with bright colors for better visibility
Improved anti-false signal filters throughout the system
Optimizing Indicator Settings
For Different Market Types
Range-Bound Markets:
Lower EMA Alignment Weight (0.2-0.4)
Higher Speed of Change Weight (0.8-1.0)
Focus on SQZ and PBK signals for breakout potential
Trending Markets:
Higher EMA Alignment Weight (0.7-1.0)
Moderate Speed of Change Weight (0.4-0.6)
Focus on VTR strength and BK confirmations
Volatile Markets:
Enable Volatility Filter
Enable Adaptive Volume Analysis
Lower Momentum Period (2-3)
Focus on strong volume confirmation (VTR ≥ 80 or ≤ 20)
For Different Asset Classes
Equities:
Standard settings work well
Pay attention to AVOL for gap potential
Monitor QQQ correlation
Futures:
Consider higher Volume/RVOL weight
Reduce MACD weight slightly
Pay close attention to SQZ duration
Crypto:
Higher volatility thresholds may be needed
Monitor BTC price for correlation
Focus on stronger confirmation signals
Integrated Visual System for Trading Decisions
The colored circle indicators create an intuitive visual system for quick market assessment:
Progression Sequence: SQZ (Squeeze) → PBK (Pre-Breakout) → BK (Breakout)
This sequence often occurs in order, with the squeeze leading to pre-breakout conditions, followed by an actual breakout.
VTR (Volume Trend): Provides context about the volume supporting these movements.
Color Coding: Green for bullish conditions, red for bearish conditions, and orange/gray for neutral or undefined conditions.
ATR Volatility giua64ATR Volatility giua64 – Smart Signal + VIX Filter
📘 Script Explanation (in English)
Title: ATR Volatility giua64 – Smart Signal + VIX Filter
This script analyzes market volatility using the Average True Range (ATR) and compares it to its moving average to determine whether volatility is HIGH, MEDIUM, or LOW.
It includes:
✅ Custom or preset configurations for different asset classes (Forex, Indices, Gold, etc.).
✅ An optional external volatility index input (like the VIX) to refine directional bias.
✅ A directional signal (LONG, SHORT, FLAT) based on ATR strength, direction, and external volatility conditions.
✅ A clean visual table showing key values such as ATR, ATR average, ATR %, VIX level, current range, extended range, and final signal.
This tool is ideal for traders looking to:
Monitor the intensity of price movements
Filter trading strategies based on volatility conditions
Identify momentum acceleration or exhaustion
⚙️ Settings Guide
Here’s a breakdown of the user inputs:
🔹 ATR Settings
Setting Description
ATR Length Number of periods for ATR calculation (default: 14)
ATR Smoothing Type of moving average used (RMA, SMA, EMA, WMA)
ATR Average Length Period for the ATR moving average baseline
🔹 Asset Class Preset
Choose between:
Manual – Define your own point multiplier and thresholds
Forex (Pips) – Auto-set for FX markets (high precision)
Indices (0.1 Points) – For index instruments like DAX or S&P
Gold (USD) – Preset suitable for XAU/USD
If Manual is selected, configure:
Setting Description
Points Multiplier Multiplies raw price ranges into useful units (e.g., 10 for Gold)
Low Volatility Threshold Threshold to define "LOW" volatility
High Volatility Threshold Threshold to define "HIGH" volatility
🔹 Extended Range and VIX
Setting Description
Timeframe for Extended High/Low Used to compare larger price ranges (e.g., Daily or Weekly)
External Volatility Index (VIX) Symbol for a volatility index like "VIX" or "EUVI"
Low VIX Threshold Below this level, VIX is considered "low" (default: 20)
High VIX Threshold Above this level, VIX is considered "high" (default: 30)
🔹 Table Display
Setting Description
Table Position Where the visual table appears on the chart (e.g., bottom_center, top_left)
Show ATR Line on Chart Whether to display the ATR line directly on the chart
✅ Signal Logic Summary
The script determines the final signal based on:
ATR being above or below its average
ATR rising or falling
ATR percentage being significant (>2%)
VIX being high or low
Conditions Signal
ATR rising + high volatility + low VIX LONG
ATR falling + high volatility + high VIX SHORT
ATR flat or low volatility or low %ATR FLAT
Support BandsSupport Bands – Discount Zones for Bitcoin
⚡Overview:
-The Support Bands indicator identifies one of the most tested and respected support zones for Bitcoin using moving averages from higher timeframes.
-These zones are visualized through colored bands (blue, white, and violet), simplifying the decision making process especially for less experienced traders who seek high-probability areas to accumulate Bitcoin during retracements.
-Band levels are based on manual backtesting and real-world price behavior throughout Bitcoin’s history.
-Each zone reflects a different degree of support strength, from temporary pullback zones to historical bottoms.
⚡️ Key Characteristics:
-Highlights discount zones where Bitcoin has historically shown strong reactions.
-Uses 3 different levels of supports based on EMA/SMA combinations.
-Offers a clean, non-intrusive overlay that reduces chart clutter.
⚡ How to Use:
-Open your chart on the 1W timeframe and select the BTC Bitstamp or BLX symbol, as they provide the most complete historical data, ensuring optimal performance of the indicator.
-Use the bands as reference zones for support and potential pullbacks.
- Level 3 (violet band) historically marks the bottom of Bitcoin bear markets and is ideal for long-term entries during deep corrections.
- Level 2 (white band) often signals macro reaccumulation zones but usually requires 1–3 months of consolidation before a breakout. If the price closes below and then retests this level as resistance for 1–2 weekly candles, it often marks the start of a macro downtrend.
-Level 1 (blue band) acts as short-term support during strong bullish moves, typically after a successful rebound from Level 2.
⚡ What Makes It Unique:
- This script merges moving averages per level into three simplified bands for clearer analysis.
-Reduces chart noise by avoiding multiple overlapping lines, helping you make faster and cleaner decisions.
- Built from manual market study based on recurring Bitcoin behavior, not just random code.
-Historically backtested:
-Level 3 (violet band) until today has always marked the bitcoin bearmarket bottom.
- Level 2 (white band) is the strongest support during bull markets; losing it often signals a macro trend reversal.
- Level 1 is frequently retested during impulsive rallies and can act as short-term support or resistance.
⚡ Disclaimer:
-This script is a visual tool to assist with market analysis.
-It does not generate buy or sell signals, nor does it predict future movements.
-Historical performance is not indicative of future results.
-Always use independent judgment and proper risk management.
⚡ Why Use Support Bands:
-Ideal for traders who want clarity without dozens of lines on their charts.
- Helps identify logical zones for entry or reaccumulation.
- Based on actual market behavior rather than hypothetical setups.
-If the blue band (Level 1) doesn't hold as support, the price often moves to the white band (Level 2), and if that fails too, the violet band (Level 3) is typically the last strong support. By dividing your capital into three planned entries, one at each level,you can manage risk more effectively compared to entering blindly without this structure.
Hidden Gap`s VSA Volume Auto-TimeframeHidden Gap's VSA Volume with Auto-Timeframe Adaptation
Enhanced Version of Classic Volume Spread Analysis Indicator
Description:
This evolved version of the original "Hidden Gap's VSA Volume" indicator introduces intelligent timeframe adaptation while preserving its core Volume Spread Analysis (VSA) logic. The key enhancement automatically synchronizes volume calculations with your chart's current timeframe, eliminating manual resolution adjustments.
New Features:
✅ Auto-Timeframe Detection
Dynamically adjusts to any chart timeframe (1M/5M/1H/4H/D/W/M)
✅ Smart Resolution Switching
Seamlessly works across multiple timeframes without parameter changes
✅ Manual Override Option
Retains custom resolution input for multi-timeframe analysis (e.g., view weekly volume on daily charts)
✅ Modernized Engine
Upgraded to Pine Script v6 for optimal TradingView performance
Core Functionality Preserved:
• Multi-layer volume analysis using 40/20/2-period comparisons
• Color-coded histogram detecting:
Black: 40-period high volume
Gray: 20-period low volume
Purple: 2-period volume contraction
Blue/Red: Immediate volume changes
• Integrated 20-period SMA reference line
Usage Scenarios:
Intraday Trading: Auto-adjusts from 1-minute to 4-hour charts
Multi-Timeframe Analysis: Compare current volume against higher timeframe patterns
Swing Trading: Maintain consistent analysis across D/W/M timeframes
Bull vs Bear Volume on Price ChartThis script overlays estimated bullish and bearish volume directly on the price chart, making it easy to spot buying vs. selling pressure without switching to a separate volume pane.
🔍 Features:
📈 Bullish volume markers appear as green triangles below the candle.
📉 Bearish volume markers appear as red triangles above the candle.
🔄 Optional smoothing to reduce noise using simple moving average (SMA).
⚠️ Volume spike highlights: Bullish spikes turn lime green, bearish spikes turn bright red.
🔢 Toggle labels to see estimated volume values above/below each candle.
🔄 Works on all timeframes, from intraday to weekly/monthly charts.
📐 Methodology:
Bullish and bearish volume are estimated using the candle's range:
More bullish volume when the close is near the high.
More bearish volume when the close is near the low.
This is a visual proxy, not true order flow data.
AP IFTCCIv2/IFTStoch/IFTRSI Multi-TimeframeMulti-Timeframe IFT-CCI/Stoch/RSI Composite
This enhanced indicator combines three powerful oscillators—Inverse Fisher Transform (IFT) versions of the Commodity Channel Index (CCI), Stochastic, and Relative Strength Index (RSI)—into a unified multi-timeframe analysis tool. Originally developed by John Ehlers (pioneer of cyclical analysis and signal processing in trading systems) and adapted by KIVANC (@fr3762), this version adds dual-timeframe capability to compare indicator values across different chart resolutions.
Key Features:
Triple Oscillator Composite
IFT-CCI: Smoothed CCI values transformed via Ehlers' Inverse Fisher Transform (blue-gold)
IFT-Stochastic: Classic stochastic oscillator processed through IFT (blue)
IFT-RSI: RSI oscillator converted to IFT format (magenta)
Composite Average Line: Combined average of all three indicators (green)
Multi-Timeframe Analysis
Compare primary and secondary timeframes (e.g., 1H vs. 4H, daily vs. weekly)
Primary timeframe plots use solid lines with 80% opacity
Secondary timeframe (optional) uses dashed/circle markers with 40% opacity
Key Levels
Overbought (+0.75) and oversold (-0.75) reference lines
Zero-centerline for momentum direction bias
Applications:
Trend Confirmation: Align higher timeframe signals with lower timeframe entries
Divergence Detection: Spot inter-timeframe discrepancies in momentum
Regime Filter: Use higher timeframe composite values to filter trades
Technical Basis:
Inverse Fisher Transform: Compresses oscillator values into bounded (-1 to +1) range while emphasizing extreme moves
Dual WMA Smoothing: Combines initial calculation smoothing (WMA1) with final output smoothing (WMA2)
Exponential Scaling: (e^2x - 1)/(e^2x + 1) formula converts Gaussian-like distributions to bounded outputs
Credits:
Original Concept: John Ehlers (IFT methodology, cyclical analysis foundations)
Initial Implementation: KIVANC (@fr3762 on Twitter) for the base IFT-CCI/Stoch/RSI script
Multi-Timeframe Adaptation: for cross-resolution analysis capabilities
This tool is particularly effective for traders seeking to align multiple timeframes while using Ehlers' noise-reduction techniques. The composite average line provides a consensus view, while the individual oscillators help identify component strength/weakness.
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
Time-based LiquidityThis indicator automatically marks important time-based liquidity levels on your chart, helping you stay aware of where major price reactions may occur and the market is forced to show its hand.
Key Features:
Previous Month’s, Week’s, and Day’s Highs and Lows: Displays PMH/PML, PWH/PWL, and PDH/PDL — key reference points where liquidity often accumulates.
Intraday Session Highs and Lows: Divides the trading day into quarters (00:00–06:00, 06:00–12:00, etc. following Day’s Quarterly Theory) and tracks session highs and lows dynamically across these periods.
Current Session 90-Minute Quarters: Splits the active session into 90-minute intervals to highlight short-term liquidity structures and potential reaction zones.
Level Alerts: Tracks when each liquidity level is reached and enables customizable alerts so you don’t miss important price movements.
Use Case:
This tool provides an organized, time-based framework for identifying where liquidity is likely to concentrate across different timeframes and intraday cycles. Use these levels for forming bias, planning entries, exits, or anticipating price reactions at key points in the market structure.
Customization Options:
Enable/disable liquidity levels to display (Daily, Weekly, Monthly, Sessions, Session Quarters)
Customize the appearance of each level (color, style, line width)
Enable or disable tracking and alerts for level interactions
Quarterly Theory ICT 05 [TradingFinder] Doubling Theory Signals🔵 Introduction
Doubling Theory is an advanced approach to price action and market structure analysis that uniquely combines time-based analysis with key Smart Money concepts such as SMT (Smart Money Technique), SSMT (Sequential SMT), Liquidity Sweep, and the Quarterly Theory ICT.
By leveraging fractal time structures and precisely identifying liquidity zones, this method aims to reveal institutional activity specifically smart money entry and exit points hidden within price movements.
At its core, the market is divided into two structural phases: Doubling 1 and Doubling 2. Each phase contains four quarters (Q1 through Q4), which follow the logic of the Quarterly Theory: Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal.
These segments are anchored by the True Open, allowing for precise alignment with cyclical market behavior and providing a deeper structural interpretation of price action.
During Doubling 1, a Sequential SMT (SSMT) Divergence typically forms between two correlated assets. This time-structured divergence occurs between two swing points positioned in separate quarters (e.g., Q1 and Q2), where one asset breaks a significant low or high, while the second asset fails to confirm it. This lack of confirmation—especially when aligned with the Manipulation and Accumulation phases—often signals early smart money involvement.
Following this, the highest and lowest price points from Doubling 1 are designated as liquidity zones. As the market transitions into Doubling 2, it commonly returns to these zones in a calculated move known as a Liquidity Sweep—a sharp, engineered spike intended to trigger stop orders and pending positions. This sweep, often orchestrated by institutional players, facilitates entry into large positions with minimal slippage.
Bullish :
Bearish :
🔵 How to Use
Applying Doubling Theory requires a simultaneous understanding of temporal structure and inter-asset behavioral divergence. The method unfolds over two main phases—Doubling 1 and Doubling 2—each divided into four quarters (Q1 to Q4).
The first phase focuses on identifying a Sequential SMT (SSMT) divergence, which forms when two correlated assets (e.g., EURUSD and GBPUSD, or NQ and ES) react differently to key price levels across distinct quarters. For example, one asset may break a previous low while the other maintains structure. This misalignment—especially in Q2, the Manipulation phase—often indicates early smart money accumulation or distribution.
Once this divergence is observed, the extreme highs and lows of Doubling 1 are marked as liquidity zones. In Doubling 2, the market gravitates back toward these zones, executing a Liquidity Sweep.
This move is deliberate—designed to activate clustered stop-loss and pending orders and to exploit pockets of resting liquidity. These sweeps are typically driven by institutional forces looking to absorb liquidity and position themselves ahead of the next major price move.
The key to execution lies in the fact that, during the sweep in Doubling 2, a classic SMT divergence should also appear between the two assets. This indicates a weakening of the previous trend and adds an extra layer of confirmation.
🟣 Bullish Doubling Theory
In the bullish scenario, Doubling 1 begins with a bullish SSMT divergence, where one asset forms a lower low while the other maintains its structure. This divergence signals weakening bearish momentum and possible smart money accumulation. In Doubling 2, the market returns to the previous low and sweeps the liquidity zone—breaking below it on one asset, while the second fails to confirm, forming a bullish SMT divergence.
f this move is followed by a bullish PSP and a clear market structure break (MSB), a long entry is triggered. The stop-loss is placed just below the swept liquidity zone, while the target is set in the premium zone, anticipating a move driven by institutional buyers.
🟣 Bearish Doubling Theory
The bearish scenario follows the same structure in reverse. In Doubling 1, a bearish SSMT divergence occurs when one asset prints a higher high while the other fails to do so. This suggests distribution and weakening buying pressure. Then, in Doubling 2, the market returns to the previous high and executes a liquidity sweep, targeting trapped buyers.
A bearish SMT divergence appears, confirming the move, followed by a bearish PSP on the lower timeframe. A short position is initiated after a confirmed MSB, with the stop-loss placed
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include : Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Labels : Displays dynamic labels (e.g., “Q2”, “Bullish SMT”, “Sweep”) at relevant points.
Show Lines : Draws connection lines between key pivot or divergence points.
Color Settings : Allows customization of colors for bullish and bearish elements (lines, labels, and shapes)
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequenc y:
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
Doubling Theory is a powerful and structured framework within the realm of Smart Money Concepts and ICT methodology, enabling traders to detect high-probability reversal points with precision. By integrating SSMT, SMT, Liquidity Sweeps, and the Quarterly Theory into a unified system, this approach shifts the focus from reactive trading to anticipatory analysis—anchored in time, structure, and liquidity.
What makes Doubling Theory stand out is its logical synergy of time cycles, behavioral divergence, liquidity targeting, and institutional confirmation. In both bullish and bearish scenarios, it provides clearly defined entry and exit strategies, allowing traders to engage the market with confidence, controlled risk, and deeper insight into the mechanics of price manipulation and smart money footprints.
Guppy Multiple Moving Average (GMMA)The GMMA Momentum Indicator plots 12 EMAs on your chart, divided into two groups:
Short-term EMAs (6 lines, default periods: 3, 5, 8, 10, 12, 15): Represent short-term trader sentiment and momentum.
Long-term EMAs (6 lines, default periods: 30, 35, 40, 45, 50, 60): Reflect long-term investor behavior and broader market trends.
By analyzing the interaction between these two groups, the indicator identifies:
Bullish and bearish trends based on the relative positions of the short- and long-term EMAs.
Momentum strength through the spread or convergence of the EMAs.
Potential reversals or breakouts via compression signals.
This PineScript version enhances the traditional GMMA by adding visual cues like background colors, bearish signals, and compression detection, making it ideal for swing traders seeking clear, actionable insights.
The GMMA Momentum Indicator provides several key features:
1. Trend Identification
Bullish Trend: When the short-term EMAs (green lines) are above the long-term EMAs (blue lines) and spreading apart, it signals strong upward momentum. The chart background turns light green to highlight this condition.
Bearish Trend: When the short-term EMAs cross below the long-term EMAs and converge, it indicates downward momentum. The background turns light red, and an orange downward triangle appears above the bar to mark a new bearish signal.
2. Momentum Analysis
The spread between the short-term EMAs reflects the strength of short-term momentum. A wide spread suggests strong momentum, while a tight grouping indicates weakening momentum or consolidation. Similarly, the long-term EMAs act as dynamic support or resistance, guiding traders on the broader trend.
3. Compression Detection
Compression occurs when both the short-term and long-term EMAs converge, signaling low volatility and a potential breakout or reversal. A yellow upward triangle appears below the bar when compression is detected, alerting traders to watch for price action.
4. Visual Cues
Green short-term EMAs: Show short-term trader activity.
Blue long-term EMAs: Represent long-term investor sentiment.
Background colors: Light green for bullish trends, light red for bearish trends, and transparent for neutral conditions.
Orange downward triangles: Mark new bearish trends.
Yellow upward triangles: Indicate compression, hinting at potential breakouts.
How to Use the GMMA Momentum Indicator for Swing Trading
Swing trading involves capturing price moves over days to weeks, and the GMMA Momentum Indicator is an excellent tool for this strategy. Here’s how to use it effectively:
1. Identifying Trade Entries
Buy Opportunities:
Look for a bullish trend (green background) where the short-term EMAs are above the long-term EMAs and spreading apart, indicating strong momentum.
A compression signal (yellow triangle) followed by a breakout above resistance or a bullish candlestick pattern can confirm an entry.
Example: On a daily chart, if the short-term EMAs cross above the long-term EMAs and the background turns green, consider entering a long position, especially if volume supports the move.
Sell Opportunities:
Watch for a bearish signal (orange downward triangle) or a bearish trend (red background) where the short-term EMAs cross below the long-term EMAs.
Example: If the short-term EMAs collapse below the long-term EMAs and an orange triangle appears, it may signal a shorting opportunity or a time to exit longs.
2. Managing Trades
Use the long-term EMAs as dynamic support (in uptrends) or resistance (in downtrends) to set stop-loss levels or trail stops.
Monitor the spread of the short-term EMAs. A widening spread suggests the trend is strong, while convergence may indicate it’s time to take profits or tighten stops.
3. Anticipating Reversals
Compression signals (yellow triangles) highlight periods of low volatility, often preceding significant price moves. Combine these with price action (e.g., breakouts or reversals) or other indicators (e.g., RSI or volume) for confirmation.
Example: If a compression signal appears near a key support level and the price breaks upward, it could signal the start of a new bullish swing.
4. Best Practices
Timeframes: The indicator works well on daily or 4-hour charts for swing trading, but you can adjust the EMA periods for shorter (e.g., 1-hour) or longer (e.g., weekly) timeframes.
Confirmation: Combine the GMMA with other tools like support/resistance levels, candlestick patterns, or oscillators (e.g., MACD) to reduce false signals.
Risk Management: Always use proper position sizing and stop-losses, as EMAs are lagging indicators and may produce delayed signals in choppy markets.
Sector 50MA vs 200MA ComparisonThis TradingView indicator compares the 50-period Moving Average (50MA) and 200-period Moving Average (200MA) of a selected market sector or index, providing a visual and analytical tool to assess relative strength and trend direction. Here's a detailed breakdown of its functionality:
Purpose: The indicator plots the 50MA and 200MA of a chosen sector or index on a separate panel, highlighting their relationship to identify bullish (50MA > 200MA) or bearish (50MA < 200MA) trends. It also includes a histogram and threshold lines to gauge momentum and key levels.
Inputs:
Resolution: Allows users to select the timeframe for calculations (Daily, Weekly, or Monthly; default is Daily).
Sector Selection: Users can choose from a list of sectors or indices, including Tech, Financials, Consumer Discretionary, Utilities, Energy, Communication Services, Materials, Industrials, Health Care, Consumer Staples, Real Estate, S&P 500 Value, S&P 500 Growth, S&P 500, NASDAQ, Russell 2000, and S&P SmallCap 600. Each sector maps to specific ticker pairs for 50MA and 200MA data.
Data Retrieval:
The indicator fetches closing prices for the 50MA and 200MA of the selected sector using the request.security function, based on the chosen timeframe and ticker pairs.
Visual Elements:
Main Chart:
Plots the 50MA (blue line) and 200MA (red line) for the selected sector.
Fills the area between the 50MA and 200MA with green (when 50MA > 200MA, indicating bullishness) or red (when 50MA < 200MA, indicating bearishness).
Threshold Lines:
Horizontal lines at 0 (zero line), 20 (lower threshold), 50 (center), 80 (upper threshold), and 100 (upper limit) provide reference points for the 50MA's position.
Fills between 0-20 (green) and 80-100 (red) highlight key zones for potential overbought or oversold conditions.
Sector Information Table:
A table in the top-right corner displays the selected sector and its corresponding 50MA and 200MA ticker symbols for clarity.
Alerts:
Generates alert conditions for:
Bullish Crossover: When the 50MA crosses above the 200MA (indicating potential upward momentum).
Bearish Crossover: When the 50MA crosses below the 200MA (indicating potential downward momentum).
Use Case:
Traders can use this indicator to monitor the relative strength of a sector's short-term trend (50MA) against its long-term trend (200MA).
The visual fill between the moving averages and the threshold lines helps identify trend direction, momentum, and potential reversal points.
The sector selection feature allows for comparative analysis across different market segments, aiding in sector rotation strategies or market trend analysis.
This indicator is ideal for traders seeking to analyze sector performance, identify trend shifts, and make informed decisions based on moving average crossovers and momentum thresholds.
DDDDD: ATR & ADR Table + Suggested Time-based Exit📈 DDDDD: ATR & ADR Table + Suggested Time-based Exit
This indicator provides a simple yet powerful table displaying key volatility metrics for any timeframe you apply it to. It is designed for traders who want to assess the volatility of an asset, estimate the average time required for a potential move, and define a time-based exit strategy.
🔍 Features:
Displays ATR (Average True Range) for the selected length
Shows Average Range (High-Low) and Maximum Range over a configurable number of bars
Calculates Avg Bars/Move → average number of bars needed to achieve the maximum range
Calculates Recommended Exit Bars → suggested maximum holding period (in bars) before considering an exit if price hasn’t moved as expected
All values dynamically adjust based on the chart’s current timeframe
Outputs values directly in a table overlay on your main chart for quick reference
📝 How to interpret the table:
Field Meaning
ATR (14) Average True Range over the last 14 bars (volatility indicator)
Avg Range (20) Average High-Low range over the last 20 bars
Max Range Maximum High-Low range observed in the last 20 bars
Avg Bars/Move Average number of bars it takes to achieve a Max Range move
Rec. Exit Bars Suggested max holding period (bars) → consider exit if move hasn’t occurred
✅ How to use:
Apply this indicator to any chart (works on minutes, hourly, daily, weekly…)
It will automatically calculate based on the chart’s current timeframe
Use ATR & Avg Range to gauge volatility
Use Avg Bars/Move to estimate how long the market usually takes to achieve a big move
Use Rec. Exit Bars as a soft stop — if price hasn’t moved by this time, consider exiting due to declining probability of a breakout
⚠️ Notes:
All values are relative to your current chart timeframe. For example:
→ On a daily chart, ATR represents daily volatility
→ On a 1H chart, ATR represents hourly volatility
“Bars” refers to the bars of the current timeframe. Always interpret time accordingly.
Perfect for traders who want to:
Time their trades based on average volatility
Avoid overholding losing positions
Set time-based exit rules to complement price-based stoplosses
UM Dual MA with Price Bar Color change & Fill
Description
This is a dual moving average indicator with colored bars and moving averages. I wrote this indicator to keep myself on the right side of the market and trends. It plots two moving averages, (length and type of MA are user-defined) and colors the MAs green when trending higher or red when trending lower. The price bars are green when both MAs are green, red when both MAs are red, and orange when one MA is green and the other is red. The idea behind the indicator is to be extremely visual. If I am buying a red bar, I ask myself "why?" If I am selling a green bar, again, "why?"
Recommended Usage
Configure your tow favorite Moving averages. Consider long positions when one or both turn green. Scale into a position with a portion upon the first MA turning green, and then more when the second turns green. Consider scaling out when the bars are orange after an up move.
Orange bars are either areas of consolidation or prior to major turns.
You can also look for MA crossovers.
The indicator works on any timeframe and any security. I use it on daily, hourly, 2 day charts.
Default settings
The defaults are the author's preferred settings:
- 8 period WMA and 16 period WMA.
- Bars are green when both MAs are trending higher, red when both MAs are trending lower, and orange when one MA is trending higher and the other is trending lower.
Moving average types, lengths, and colors are user-configurable. Bar colors are also user-configurable.
Alerts
Alerts can be set by right-clicking the indicator and selecting the dropdown:
- Bullish Trend Both MAs turning green
- Bearish Trend Both MAs turning red
- Mixed Trend, 1 green 1 red MA
Helpful Hints:
Look for bullish areas when both MAs turn green after a sustained downtrend
Look for bearish areas when both MAs turn red
Careful in areas of orange bars, this could be a consolidation or a warning to a potential trend direction change.
Switch up your timeframes, I toggle back and forth between 1 and 2 days.
Stretch your timeframe over a lower time frame; for example, I like the 8 and 16 daily WMA. With most securities I get 16 bars with pre and post market. This translates into 128 and 256 MAs on the hourly chart. This slows down moves and color transitions for better manageability.
Author's Subjective Observations
I like the 128/256 WMA on the hourly charts for leveraged and inverse ETFs such as SPXL/SPXS, TQQQ/SQQQ, TNA/TZA. Or even the volatility ETFs/ETNS: UVXY, VXX.
Here is a one-hour chart example:
I have noticed that as volatility increases, I should begin looking at higher timeframes. This seems counterintuitive, but higher volatility increases the level of noise or swings.
I question myself when I short a green bar or buy a red bar; "Why am I doing this?" The colors help me visually stay on the right side of trend. If I am going to speculate on a market turn, at least do it when the bars are orange (MA trends differ)
My last observation is a 2-day chart of leveraged ETFs with the 8 and 16 WMAs. I frequently trade SPXL, FNGA, and TNA. If you are really dissecting this indicator,
look at a few 2-day charts. 2-day charts seem to catch the major swings nicely up and down. They also weed out the daily sudden big swings such as a panic move from economic data
or tweets. When both the MAs turn red on a 2-day chart the same day or same bar, beware; this could be a rough ride or short opportunity. I found weekly charts too long for my style but good
to review for direction. Less decisions on longer charts equate to less brain damage for myself.
These are just my thoughts, of course you do you and what suits your style best! Happy Trading.
FVG [TakingProphets]🧠 Purpose
This indicator is built for traders applying Inner Circle Trader (ICT) methodology. It detects and manages Fair Value Gaps (FVGs) — price imbalances that often act as future reaction zones. It also highlights New Day Opening Gaps (NDOGs) and New Week Opening Gaps (NWOGs) that frequently play a role in early-session price behavior.
📚 What is a Fair Value Gap?
A Fair Value Gap forms when price moves rapidly, skipping over a portion of the chart between three candles — typically between the high of the first candle and the low of the third. These zones are considered inefficient, meaning institutions may return to them later to:
-Rebalance unfilled orders
-Enter or scale into positions
-Engineer liquidity with minimal slippage
In ICT methodology, FVGs are seen as both entry zones and targets, depending on market structure and context.
⚙️ How It Works
-This script automatically identifies and manages valid FVGs using the following logic:
-Bullish FVGs: When the low of the current candle is above the high from two candles ago
-Bearish FVGs: When the high of the current candle is below the body of two candles ago
-Minimum Gap Filter: Gaps must be larger than 0.05% of price
-Combine Consecutive Gaps (optional): Merges adjacent gaps of the same type
-Consequent Encroachment Line (optional): Plots the midpoint of each gap
-NDOG/NWOG Tracking: Labels gaps created during the 5–6 PM session transition
-Automatic Invalidation: Gaps are removed once price closes beyond their boundary
🎯 Practical Use
-Use unmitigated FVGs as potential entry points or targets
-Monitor NDOG and NWOG for context around daily or weekly opens
-Apply the midpoint (encroachment) line for precise execution decisions
-Let the script handle cleanup — only active, relevant zones remain visible
🎨 Customization
-Control colors for bullish, bearish, and opening gaps
-Toggle FVG borders and midpoint lines
-Enable or disable combining of consecutive gaps
-Fully automated zone management, no manual intervention required
✅ Summary
This tool offers a clear, rules-based approach to identifying price inefficiencies rooted in ICT methodology. Whether used for intraday or swing trading, it helps traders stay focused on valid, active Fair Value Gaps while filtering out noise and maintaining chart clarity.
