[DEM] Multiple Linear Regression Score Multiple Linear Regression Score is a composite momentum indicator that evaluates market conditions by analyzing a reference symbol (defaulting to NDX) across multiple technical dimensions and combining them into a single predictive score. The indicator processes ten different technical variables including RSI, MACD components (line, signal, and histogram), price relationships to various moving averages (10, 50, 100, 200), and short-term price changes (1-day and 5-day), converting most into binary signals (1 or 0) based on whether they're above or below zero. These binary and continuous inputs are then weighted using regression-derived coefficients and combined into a final percentage score that oscillates around zero, with the indicator also calculating a 20-period standard deviation of the score to measure volatility. This approach creates a data-driven sentiment gauge that quantifies the overall technical health of the reference market by mathematically weighting the importance of each technical factor based on historical relationships.
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[DEM] Multiple Linear Regression Oscillator Multiple Linear Regression Oscillator is a sophisticated momentum indicator that combines volume-weighted price action with multiple timeframe price changes to generate predictive signals through a linear regression model. The indicator calculates a volume-price ratio over 5 periods and incorporates price changes across four different lookback periods (2, 5, 10, and 20 bars), applying specific regression coefficients to each variable to produce a normalized oscillator that fluctuates around zero. The main output is plotted alongside a 10-period RMA smoothed version in yellow, with reference lines at +1, 0, and -1 to help identify overbought, neutral, and oversold conditions. This mathematical approach attempts to predict short-term price movements by weighting the historical relationship between volume, price momentum, and multi-timeframe price changes, essentially creating a data-driven oscillator that goes beyond traditional technical indicators by incorporating machine learning-derived coefficients.
[DEM] Moving Average Signal (With Backtesting) Moving Average Signal (With Backtesting) is designed to generate buy and sell signals using a highly configurable moving average system with over 20 different moving average types (including EMA, SMA, HMA, ALMA, McGinley, TRAMA, and others) combined with dynamic upper and lower bands based on standard deviation or ATR multipliers. It also includes a comprehensive backtesting framework to evaluate the historical performance of these signals. The indicator overlays directly on the price chart, plotting the moving average with upper and lower bands while coloring bars green when price is above the upper band, red when below the lower band, and purple when between the bands. The strategy generates buy signals when price crosses above the upper band after being below it for one bar but above it for the previous three bars (indicating a breakout after brief consolidation), and sell signals under opposite conditions with the lower band, creating a momentum-based system that filters for sustained moves beyond the moving average envelope while offering extensive customization options and integrated backtesting metrics.
[DEM] Four RMA Signal (With Backtesting) Four RMA Signal (With Backtesting) is designed to generate buy and sell signals based on a hierarchical alignment of four Rolling Moving Averages (RMA) with periods of 200, 300, 400, and 500, combined with price action confirmation through the fastest RMA line. It also includes a comprehensive backtesting framework to evaluate the historical performance of these signals. The indicator overlays directly on the price chart, plotting signals and displaying performance statistics in a table. The strategy generates buy signals when all four RMAs are aligned in ascending order (200>300>400>500, indicating strong bullish momentum across multiple timeframes) and the low crosses above the 200-period RMA, while sell signals are triggered when the RMAs are aligned in descending order (200<300<400<500, indicating strong bearish momentum) and the high crosses below the 200-period RMA, ensuring signals only occur during periods of confirmed long-term directional bias with immediate price confirmation through the fastest moving average.
[DEM] EMA Crossover Signal (With Backtesting) EMA Crossover Signal (With Backtesting) is designed to generate buy and sell signals based on the classic exponential moving average crossover strategy using two configurable EMA periods (default 9 and 21). It also includes a comprehensive backtesting framework to evaluate the historical performance of these signals. The indicator overlays directly on the price chart, plotting signals and displaying performance statistics in a table. The strategy generates buy signals when the shorter EMA crosses above the longer EMA (indicating upward momentum shift) and sell signals when the shorter EMA crosses below the longer EMA (indicating downward momentum shift), while the integrated backtesting system tracks signal accuracy, average returns, signal frequency per month, and total correct predictions for both buy and sell signals over a configurable holding period to help traders evaluate the effectiveness of the crossover parameters.
[DEM] EMA Cloud & Bars EMA Cloud & Bars is designed to provide visual trend analysis by combining two exponential moving averages of different lengths (default 50 and 150) with both a color-coded cloud fill and optional bar coloring to identify market conditions. The indicator plots the two EMAs as semi-transparent lines and fills the area between them with blue when the shorter EMA is above the longer EMA (indicating bullish conditions) or red when the shorter EMA is below the longer EMA (indicating bearish conditions). Additionally, it colors price bars green when price is above the shorter EMA and the shorter EMA is above the longer EMA (strong bullish alignment), red when price is below the shorter EMA and the longer EMA is above the shorter EMA (strong bearish alignment), and purple for all other conditions, providing traders with multiple visual cues for trend direction and strength while offering toggleable options for both the cloud display and bar coloring features.
[DEM] Double Hull Moving Average (DHMA) Double Hull Moving Average (DHMA) is designed to create an ultra-smooth and responsive trend-following indicator by applying the Hull Moving Average calculation twice to reduce lag while maintaining smoothness. The indicator first calculates a Hull Moving Average of the source price over the specified length (default 233), then applies another Hull Moving Average to the result, and finally uses the standard Hull formula (2 * HMA1 - HMA2) to create the Double Hull Moving Average. The resulting line changes color dynamically from green when trending upward to red when trending downward, with matching bar colors to provide clear visual confirmation of trend direction, offering traders a highly refined moving average that responds quickly to price changes while filtering out most market noise.
[DEM] Donchian Oscillator Donchian Oscillator is designed to measure the relative position of recent price action within the Donchian Channel by calculating how many bars have passed since the most recent highest high versus the most recent lowest low over a specified lookback period. The indicator computes the difference between bars since the last low and bars since the last high, then applies smoothing using an RMA to create an oscillator that fluctuates around a zero centerline displayed in a separate pane below the main chart. The oscillator uses gradient coloring from red (negative values indicating recent lows dominate) through purple (neutral) to green (positive values indicating recent highs dominate), helping traders identify momentum shifts and potential overbought/oversold conditions based on whether price is closer to making new highs or new lows within the specified range.
[DEM] Donchian Moving Average Donchian Moving Average is designed to create a smoothed trend-following indicator by combining Donchian Channel methodology with moving average smoothing to reduce noise and provide clearer directional signals. The indicator calculates the midpoint of the highest high and lowest low over a specified period (default 20 bars), then applies additional smoothing using an RMA (default 10 periods) to create a more stable trend line. The resulting moving average changes color from blue to red based on its relationship to its own short-term smoothed version (5-period RMA), with blue indicating upward momentum and red indicating downward momentum, while also coloring the price bars to match the trend direction for enhanced visual clarity of the overall market bias.
[DEM] Confirmation Signal (With Backtesting) Confirmation Signal (With Backtesting) is designed to generate buy and sell signals by combining Aroon oscillator analysis with Parabolic SAR positioning, smoothed EMA trend confirmation, and RSI filtering to create high-confidence trading opportunities. It also includes a comprehensive backtesting framework to evaluate the historical performance of these signals. The indicator overlays directly on the price chart, plotting signals and displaying performance statistics in a table while also coloring bars based on market conditions (green for bullish confirmation, red for bearish confirmation, purple for neutral). The strategy generates buy signals when the Aroon Up reaches 100% (new highs) combined with bullish trend confirmations, proper SAR positioning, RSI filters, and adequate time spacing between signals, while sell signals are triggered under opposite conditions, emphasizing signal quality over quantity through multiple confirmation layers and integrated backtesting metrics.
[DEM] Combo Moving Average Combo Moving Average is designed to create a composite trend-following indicator by averaging seven different types of moving averages into a single smoothed line. The indicator overlays directly on the price chart, combining ALMA (Arnaud Legoux Moving Average), EMA (Exponential), HMA (Hull), RMA (Rolling), SMA (Simple), VWMA (Volume Weighted), and WMA (Weighted) moving averages to provide a more robust and less noisy trend signal. The resulting composite moving average changes color dynamically - displaying green when the trend is upward (current value higher than previous) and red when the trend is downward, offering traders a clear visual representation of the overall market direction across multiple moving average methodologies.
Trend Strength Index Long Strategy📈 Trend Strength Index Long Strategy
This strategy combines the Trend Strength Index (TSI) with a Volume-Weighted Moving Average (VWMA) to identify high-probability long entries based on trend momentum and price confirmation.
📊 TSI Calculation : Measures correlation between price and time (bar index) over a user-defined period. Strong TSI values indicate trend momentum.
📏 VWMA Filter : Confirms bullish bias when price is above the VWMA.
🚀 Entry Condition : Long position is triggered when TSI crosses above -0.65 and price is above VWMA.
🔒 Exit Condition : Position is closed when TSI crosses above 0.65.
🎨 Visuals : Gradient fills highlight bullish and bearish zones. VWMA is plotted for trend context.
🧮 TSI Length: Adjustable (default 14)
📐 VWMA Length: Adjustable (default 55)
💸 Commission: 0.1% per trade
📊 Position Size: 75% of equity
⚙️ Slippage: 10 ticks
✅ Best used in trending markets with steady momentum.
⚠️ Avoid in choppy or range-bound conditions.
AA1 MACD 09.2025this is a learing project i want to share
the script is open for anyone
I combain some ema's mcad and more indicators to help find stocks in momentum
[Futures OI vs Price Change] (% Change)╔═══════════════════ RUBIXCUBE ══════════════════════╗
This indicator analyses the relationship between Open Interest percentage changes and price percentage changes in futures markets. Inspired by Checkonchain's market structure analysis, it displays this data as coloured column bars to identify different market conditions.
What This Indicator Shows
The indicator plots Open Interest percentage change as column bars, with colours representing four market regimes:
- Blue (Leveraged Rally): OI increases + Price increases (New leveraged long positions)
- Green (Spot Rally): OI decreases + Price increases (Organic buying or short covering)
- Orange (Leveraged Sell-Off): OI increases + Price decreases (New short positions or long liquidations)
- Red (Deleveraging Sell-Off): OI decreases + Price decreases (Position unwinding)
Bar transparency changes based on price movement magnitude. Larger price changes result in more solid bars, while smaller moves appear more transparent.
Data Sources
Aggregated Open Interest data from multiple exchanges:
- Binance USDT, USD & BUSD Perpetuals
- BitMEX USD & USDT Perpetuals
- Kraken USD Perpetuals
Settings
- OI % Change SMA: Smoothing period for Open Interest changes (Default: 7)
- Price % Change SMA: Smoothing period for price changes (Default: 7)
- Base Transparency: Baseline transparency level (0-100)
- Transparency Sensitivity: How much price change affects bar transparency
- Exchange Toggles: Enable/disable individual exchange data
Usage
This indicator helps identify market structure by showing whether price moves are accompanied by increasing or decreasing leveraged positions. Blue and orange bars indicate new leverage entering the market, while green and red bars suggest position reduction or organic spot activity.
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Kalman Adjusted Average True Range [BackQuant]Kalman Adjusted Average True Range
A volatility-aware trend baseline that fuses a Kalman price estimate with ATR “rails” to create a smooth, adaptive guide for entries, exits, and trailing risk.
Built on my original Kalman
This indicator is based on my original Kalman Price Filter:
That core smoother is used here to estimate the “true” price path, then blended with ATR to control step size and react proportionally to market noise.
What it plots
Kalman ATR Line the main baseline that turns up/down with the filtered trend.
Optional Moving Average of the Kalman ATR a secondary line for confluence (SMA/Hull/EMA/WMA/DEMA/RMA/LINREG/ALMA).
Candle Coloring (optional) paint bars by the baseline’s current direction.
Why combine Kalman + ATR?
Kalman reduces measurement noise and produces a stable path without the lag of heavy MAs.
ATR rails scale the baseline’s step to current volatility, so it’s calm in chop and more responsive in expansion.
The result is a single, intelligible line you can trade around: slope-up = constructive; slope-down = caution.
How it works (plain English)
Each bar, the Kalman filter updates an internal state (tunable via Process Noise , Measurement Noise , and Filter Order ) to estimate the underlying price.
An ATR band (Period × Factor) defines the allowed per-bar adjustment. The baseline cannot “jump” beyond those rails in one step.
A direction flip is detected when the baseline’s slope changes sign (upturn/downturn), and alerts are provided for both.
Typical uses
Trend confirmation Trade in the baseline’s direction; avoid fading a firmly rising/falling line.
Pullback timing Look for entries when price mean-reverts toward a rising baseline (or exits on tags of a falling one).
Trailing risk Use the baseline as a dynamic guide; many traders set stops a small buffer beyond it (e.g., a fraction of ATR).
Confluence Enable the MA overlay of the Kalman ATR; alignment (baseline above its MA and rising) supports continuation.
Inputs & what they do
Calculation
Kalman Price Source which price the filter tracks (Close by default).
Process Noise how quickly the filter can adapt. Higher = more responsive (but choppier).
Measurement Noise how much you distrust raw price. Higher = smoother (but slower to turn).
Filter Order (N) depth of the internal state array. Higher = slightly steadier behavior.
Kalman ATR
Period ATR lookback. Shorter = snappier; longer = steadier.
Factor scales the allowed step per bar. Larger factors permit faster drift; smaller factors clamp movement.
Confluence (optional)
MA Type & Period compute an MA on the Kalman ATR line , not on price.
Sigma (ALMA) if ALMA is selected, this input controls the curve’s shape. (Ignored for other MA types.)
Visuals
Plot Kalman ATR toggle the main line.
Paint Candles color bars by up/down slope.
Colors choose long/short hues.
Signals & alerts
Trend Up baseline turns upward (slope crosses above 0).
Alert: “Kalman ATR Trend Up”
Trend Down baseline turns downward (slope crosses below 0).
Alert: “Kalman ATR Trend Down”
These are state flips , not “price crossovers,” so you avoid many one-bar head-fakes.
How to start (fast presets)
Swing (daily/4H) ATR Period 7–14, Factor 0.5–0.8, Process Noise 0.02–0.05, Measurement Noise 2–4, N = 3–5.
Intraday (5–15m) ATR Period 5–7, Factor 0.6–1.0, Process Noise 0.05–0.10, Measurement Noise 2–3, N = 3–5.
Slow assets / FX raise Measurement Noise or ATR Period for calmer lines; drop Factor if the baseline feels too jumpy.
Reading the line
Rising & curving upward momentum building; consider long bias until a clear downturn.
Flat & choppy regime uncertainty; many traders stand aside or tighten risk.
Falling & accelerating distribution lower; short bias until a clean upturn.
Practical playbook
Continuation entries After a Trend Up alert, wait for a minor pullback toward the baseline; enter on evidence the line keeps rising.
Exit/reduce If long and the baseline flattens then turns down, trim or exit; reverse logic for shorts.
Filters Add a higher-timeframe check (e.g., only take longs when the daily Kalman ATR is rising).
Stops Place stops just beyond the baseline (e.g., baseline − x% ATR for longs) to avoid “tag & reverse” noise.
Notes
This is a guide to state and momentum, not a guarantee. Combine with your process (structure, volume, time-of-day) for decisions.
Settings are asset/timeframe dependent; start with the presets and nudge Process/Measurement Noise until the baseline “feels right” for your market.
Summary
Kalman ATR takes the noise-reduction of a Kalman price estimate and couples it with volatility-scaled movement to produce a clean, adaptive baseline. If you liked the original Kalman Price Filter (), this is its trend-trading cousin purpose-built for cleaner state flips, intuitive trailing, and confluence with your existing
RSI Trend Navigator [QuantAlgo]🟢 Overview
The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions.
🟢 How It Works
The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information:
rsiValue = ta.rsi(source, rsiPeriod)
smoothedRSI = ta.ema(rsiValue, rsiSmoothing)
normalizedRSI = (smoothedRSI - 50) / 50
It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint:
adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1)
This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions:
var float adaptiveTrend = source
adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source)
The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling:
rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity
rsiTrendValue = adaptiveTrend + rsiAdjustment
ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning:
atr = ta.atr(atrPeriod)
deviation = atr * atrMultiplier
upperBound = rsiTrendValue + deviation
lowerBound = rsiTrendValue - deviation
The trend line positioning uses these band constraints to determine its final value:
if upperBound < trendLine
trendLine := upperBound
if lowerBound > trendLine
trendLine := lowerBound
Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states:
trendUp = trendLine > trendLine
trendDown = trendLine < trendLine
if trendUp
isBullish := true
isBearish := false
else if trendDown
isBullish := false
isBearish := true
The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning.
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions
Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions
Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit
Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
6 MAs, BMSB, Pi Cycle TopThis indicator has 6 Moving averages that are highly customizable and visible on multiple time frames, it also includes the Bull Market Support Band (BMSB) and the Pi Cycle Top indicator which has been very good at predicting Cycle Tops for Bitcoin (BTC). You can customize all the moving averages, as well as using simple or exponential, you can also easily customize colors and line weights.
Created by: Dan Heilman
Triple-EMA Cloud (3× configurable EMAs + timeframe + fill)About This Script
Name: Triple-EMA Cloud (3× configurable EMAs + timeframe + fill)
What it does:
The script plots three Exponential Moving Averages (EMAs) on your chart.
You can set each EMA’s length (how many bars or days it averages over), source (for example, closing price, opening price, or the midpoint of high + low), and timeframe (you can have one EMA use daily data, another hourly data, etc.).
The indicator draws a “cloud” or channel by shading the area between the outermost two EMAs of the three. This lets you see a band or zone that the price is moving in, defined by those EMAs.
You also get full control over how each of the three EMA‐lines looks: color, thickness, transparency, and plot style (solid line, steps, circles, etc.).
How to Use It (for Beginners)
Here’s how a trader who’s new to charts can use this tool, especially when looking for pullbacks or undercut price action.
Key Concepts
Trend: Imagine the market price is generally going up or down. EMAs are a way to smooth out price movements so you can see the trend more clearly.
Pullback: When a price has been going up (an uptrend), sometimes it dips down a little before going up again. That dip is the pullback. It’s a chance to enter or add to a position at a “better price.”
Undercut: This is when price drops below an important level (for example an EMA) and then comes back up. It looks like it broke below, but then it recovers. That may show reverse pressure or strength building.
How the Script Helps With Pullbacks & Undercuts
Marking Trend Zones with the Cloud
The cloud between the outer EMA lines gives you a zone of expected support/resistance. If the price is above the cloud, that zone can act like a “floor” in uptrends; if it is below, the cloud might act like a “ceiling” in downtrends.
Watching Price vs the EMAs
If the price pulls back toward the cloud (or toward one of the EMAs) and then bounces back up, that’s a signal that the uptrend might continue.
If the price undercuts (goes a bit below) one of the EMAs or the cloud and then returns above it, that can also be a signal. It suggests that even though there was a temporary drop, buyers stepped in.
Using the Three EMAs for Confirmation
Because the script uses three EMAs, you can see how tightly or loosely they are spaced.
If all three EMAs are broadly aligned (for example, in an uptrend: shorter length above longer length, each pulling from reliable price source), that gives more confidence in trend strength.
If the middle EMA (or different source/timeframe) is holding up as support while others are above, it strengthens signal.
Entry & Exit Points
Entry: For example, after a pullback toward the cloud or “mid‐EMA”, wait for price to show a bounce up. That could be a better entry than buying at the top.
Stop Loss / Risk: You might place a stop loss just below the cloud or the lowest of your selected EMAs so that if price breaks through, the idea is invalidated.
Profit Target: Could be a recent high, resistance level, or a fixed reward-risk multiple (for example aiming to make twice what you risked).
Practical Steps for New Traders
Set up the EMAs
Choose simple lengths like 10, 21, 50.
For example, EMA #1 = length 10, source Close, timeframe “current chart”; EMA #2 = length 21, source (H+L)/2; EMA #3 = length 50, maybe timeframe daily.
Observe the Price Action
When price moves up, then dips, see if it comes back near the shaded cloud or one of the EMAs.
See if the dip touches the EMAs lightly (not a big drop) and then price starts climbing again.
Look for undercuts
If price briefly goes below a line (or below cloud) and then closes back above, that’s undercut + recovery. That bounce back is often meaningful.
Manage risk
Only put in money you can afford to lose.
Use small position size until you get comfortable.
Use stop-loss (as mentioned) in case the price doesn’t bounce as expected.
Practice
Put this indicator on charts (stocks you follow) in past time periods. See how price behaved with pullbacks / undercuts relative to the EMAs & cloud. This helps you learn to see signals.
What It Doesn’t Do (and What to Be Careful Of)
It doesn’t predict the future — it simply shows zones and trends. Price can still break down through the cloud.
In a “choppy” market (i.e. when price is going up and down without a clear trend), signals from EMAs / clouds are less reliable. You’ll get more “false bounces.”
Under / overshoots & big news events can break through clean levels, so always watch for confirmation (volume, price behavior) before putting big money in.
ma btc Multiple MA Convergence Alertbtc and eth ma15 20 50 200if converge
alert("EMA15, MA20, MA50, MA200 are converging/overlap crossing!", alert.freq_once_per_bar_close)
Champs LevelsEasy Bullish & Bearish sentiments to show short term trends.
How it works:
Orange line → 8 EMA
Purple line → Premarket High
Red line → Premarket Low
Background flashes green when above both, red when below both
🚀 marker = bullish breakout, ⚠ marker = bearish breakdown
Alerts for both sides
Guppy MMA [Alpha Extract]A sophisticated trend-following and momentum assessment system that constructs dynamic trader and investor sentiment channels using multiple moving average groups with advanced scoring mechanisms and smoothed CCI-style visualizations for optimal market trend analysis. Utilizing enhanced dual-group methodology with threshold-based trend detection, this indicator delivers institutional-grade GMMA analysis that adapts to varying market conditions while providing high-probability entry and exit signals through crossover and extreme value detection with comprehensive visual mapping and alert integration.
🔶 Advanced Channel Construction
Implements dual-group architecture using short-term and long-term moving averages as foundation points, applying customizable MA types to reduce noise and score-based averaging for sentiment-responsive trend channels. The system creates trader channels from shorter periods and investor channels from longer periods with configurable periods for optimal market reaction zones.
// Core Channel Calculation Framework
maType = input.string("EMA", title="Moving Average Type", options= )
// Short-Term Group Construction
stMA1 = ma(close, st1, maType)
stMA2 = ma(close, st2, maType)
// Long-Term Group Construction
ltMA1 = ma(close, lt1, maType)
ltMA2 = ma(close, lt2, maType)
// Smoothing Application
smoothedavg = ma(overallAvg, 10, maType)
🔶 Volatility-Adaptive Zone Framework
Features dynamic score-based averaging that expands sentiment signals during strong trend periods and contracts during consolidation phases, preventing false signals while maintaining sensitivity to genuine momentum shifts. The dual-group averaging system optimizes zone boundaries for realistic market behavior patterns.
// Dynamic Sentiment Adjustment
shortTermAvg = (stScore1 + stScore2 + ... + stScore11) / 11
longTermAvg = (ltScore1 + ltScore2 + ... + ltScore11) / 11
// Dual-Group Zone Optimization
overallAvg = (shortTermAvg + longTermAvg) / 2
allMAAvg = (shortTermAvg * 11 + longTermAvg * 11) / 22
🔶 Step-Like Boundary Evolution
Creates threshold-based trend boundaries that update on smoothed average changes, providing visual history of evolving bullish and bearish levels with performance-optimized threshold management limited to key zones for clean chart presentation and efficient processing.
🔶 Comprehensive Signal Detection
Generates buy and sell signals through sophisticated crossover analysis, monitoring smoothed average interaction with zero-line and thresholds for high-probability entry and exit identification. The system distinguishes between trend continuation and reversal patterns with precision timing.
🔶 Enhanced Visual Architecture
Provides translucent zone fills with gradient intensity scaling, threshold-based historical boundaries, and dynamic background highlighting that activates upon trend changes. The visual system uses institutional color coding with green bullish zones and red bearish zones for intuitive market structure interpretation.
🔶 Intelligent Zone Management
Implements automatic trend relevance filtering, displaying signals only when smoothed average proximity warrants analysis attention. The system maintains optimal performance through smart averaging management and historical level tracking with configurable MA periods for various market conditions.
🔶 Multi-Dimensional Analysis Framework
Combines trend continuation analysis through threshold crossovers with momentum detection via extreme markers, providing comprehensive market structure assessment suitable for both trending and ranging market conditions with score-normalized accuracy.
🔶 Advanced Alert Integration
Features comprehensive notification system covering buy signals, sell signals, strong bull conditions, and strong bear conditions with customizable alert conditions. The system enables precise position management through real-time notifications of critical sentiment interaction events and zone boundary violations.
🔶 Performance Optimization
Utilizes efficient MA smoothing algorithms with configurable types for noise reduction while maintaining responsiveness to genuine market structure changes. The system includes automatic visual level cleanup and performance-optimized visual rendering for smooth operation across all timeframes.
This indicator delivers sophisticated GMMA-based market analysis through score-adaptive averaging calculations and intelligent group construction methodology. By combining dynamic trader and investor sentiment detection with advanced signal generation and comprehensive visual mapping, it provides institutional-grade trend analysis suitable for cryptocurrency, forex, and equity markets. The system's ability to adapt to varying market conditions while maintaining signal accuracy makes it essential for traders seeking systematic approaches to trend trading, momentum reversals, and sentiment continuation analysis with clearly defined risk parameters and comprehensive alert integration.
ProfitAlgo.io TrendSync SimulationThe TrendSync Simulation is a gradient-based trend-following framework that helps traders quickly identify bullish vs bearish market structure while filtering out short-term noise.
Instead of relying on a single moving average or indicator, TrendSync builds a layered “trend cloud” in 3 different MODES, KUMO, PFA, HMA anchored against a reference band. These layers create a visual gradient that shifts with market direction.
When combined with its color-adaptive candles, you can turn off your candle setting colors within the chart settings of TradingView for the TrendSync color mapping which transforms raw price action into an easy-to-read flow map of institutional momentum.
📊 How It Works
Each layer creates a smooth gradient that shifts with trend direction:
Bullish trends form a rising, green-shaded cloud.
Bearish trends form a descending, red-shaded cloud.
Transitions appear as fading or compressing gradients, signaling potential reversals or consolidations.
Candles are also dynamically colored based on normalized momentum, allowing traders to see directional strength at a glance.
🔑 Key Features
✅ Gradient Cloud – A layered trend structure that visually shifts from bearish → bullish.
✅ Multiple Modes – Choose between KUMO, PFA, or HMA logic for responsiveness vs. smoothness.
✅ Dynamic Trend Candles – Bars adapt color based on momentum strength.
✅ Customizable Visualization – Adjust transparency, colors, and gradient strength to fit your chart style.
✅ Clarity of Direction – Highlights dominant flow while reducing noise from minor fluctuations.
⚙️ Settings Explained
Trend Method (KUMO / PFA / HMA): Controls the type of moving average used for the cloud.
Gradient Colors: Define the shading of bullish vs. bearish zones.
Transparency Controls: Adjust how strong or subtle the gradient cloud appears.
Lookback Length : Longer = smoother trend; shorter = more reactive.
💡 Use Cases
Identify trend bias quickly without switching between multiple indicators.
Confirm entries with liquidity or breakout strategies by aligning with the cloud.
Detect weakening or strengthening momentum via gradient compression.
Avoid trading against dominant higher time-frame flow with trend-colored candles .
⚡ Why It Matters
Markets often look chaotic on raw candlestick charts. TrendSync cuts through that noise by layering moving averages into a visual gradient, revealing institutional momentum in real time. Whether scalping, day trading, or swing trading, TrendSync provides a synchronized view of trend direction that adapts to different trading styles.
⚡ Paired with the Back End Order Matrix, TrendSync provides the clarity of direction after liquidity zones are exposed, creating a complete institutional-style framework inside TradingView.
EXAMPLE 1A
EXAMPLE 1B
EXAMPLE 1C
EXAMPLE 2A
