3 EMA Trend by TradeZeneThree EMAs in 1 Indicator
Overview
The 3 EMAs in 1 Indicator is a clean, lightweight trend-following tool that plots three customizable Exponential Moving Averages (EMAs) on a single chart, making it easy to identify the short-, medium-, and long-term market trend at a glance.
Designed for traders who prefer simplicity over clutter, this indicator provides visual trend confirmation through subtle background coloring while keeping the chart clean and easy to read.
Features
✅ Three fully customizable EMAs
EMA 1 (Default: 9)
EMA 2 (Default: 27)
EMA 3 (Default: 108)
✅ Individual show/hide options for each EMA
✅ Automatic trend background
Light Blue: Price is above EMA 2 (Bullish Bias)
Light Orange: Price is below EMA 2 (Bearish Bias)
✅ Lightweight and fast
Works smoothly on all timeframes and market instruments.
Suggested Usage
Many traders use the three EMA combination to:
Identify the overall market trend
Stay on the right side of momentum
Filter counter-trend trades
Improve trade selection alongside price action
Combine with support/resistance, VWAP, market structure, or volume analysis
This indicator is intentionally simple so it can fit into almost any trading strategy.
Default Settings
EMA 1: 9
EMA 2: 27
EMA 3: 108
These values can be customized to suit your trading style.
Disclaimer
This indicator is provided for educational and informational purposes only. It should not be considered financial or investment advice. Trading involves risk, and past performance does not guarantee future results. Always perform your own analysis and manage risk appropriately.
If you find this indicator useful, please consider giving it a 👍, adding it to your favorites, and share with your trader friends.
Happy Trading! Indicator
NeuPortal - Base Rate SignalsFive standard entry rules running simultaneously on the price chart: moving average crossover, RSI reversal, MACD cross, Bollinger re-entry and Stochastic cross. Each marks its own small triangle under or over the candle, tagged with the rule that fired it. When several agree on the same bar, a consensus label is drawn.
That part is ordinary. Thousands of scripts do it.
THE NUMBER EVERY SIGNAL SCRIPT LEAVES OUT
Each rule is scored live against the base rate on your chart. The table prints three things per rule:
hit - how often that rule was followed by a move in its own direction
base - how often ANY bar was followed by that same move over the same window
edge - the difference
That difference is the only thing an entry rule can honestly claim.
A rule that hits 54% sounds like an edge until you ask what a bar picked at random scores. In a market that drifted upward over the sample, "price is higher 20 bars later" might be true 53% of the time whatever you do. A rule at 54% against a 53% baseline has found almost nothing. Every signal indicator in existence reports the 54 and omits the 53.
The edge will often be small and sometimes negative. That is the expected result, not a fault in the script. On ETHUSDT 4h at the time of writing, a WMA 21/65 crossover long scores 44.7% against a base rate of 51.1% - an edge of minus 6.4 across 123 signals and 10,026 scored bars. Buying a random bar would have been better than buying that signal.
THE CONSENSUS ROW IS AN EXPERIMENT, NOT A FEATURE
"Three indicators confirm the entry" rests on an assumption nobody checks: that three indicators are three pieces of evidence.
They are not. Measured over 19,580 four-hour bars of full Binance history, the rank correlation between these families runs around 0.80. Stochastic against Williams %R reaches 0.92; RSI against CCI 0.90. For n readings correlated at r, the effective number of independent readings is about n / (1 + (n - 1) * r). Five rules at 0.80 come to roughly 1.4.
So set how many rules must agree, and watch what happens. If agreement were evidence, the edge would rise as the threshold rises. Usually only the signal count falls. Trading less often for the same expectation is not an improvement, and this is the first indicator I know of that lets you see that rather than assume it.
TIMING
Three modes. Confirmed waits for the bar to close and never changes afterwards. Anticipate fires one bar earlier by projecting each rule's spread across zero, so some of those crosses never happen. Live fires on the unfinished bar and repaints.
Switch between them and watch the edge column. Earlier is only better if the edge improves, and usually it does not. Note that in Live mode the historical percentages were not earned under those conditions - history contains no unfinished bars, so every past signal was scored as confirmed. Live mode flatters itself, and the table marks it.
HOW THE SCORING WORKS
A signal counts as correct if price closed higher (long) or lower (short) a fixed number of bars later. Every count uses only bars that had already completed when the label was drawn, so nothing repaints and no percentage knows anything the chart did not. Early in a chart the sample is tiny and the table says "too few" rather than printing a flattering number from six observations.
WHAT THIS IS NOT
Not a strategy and not advice. Hit rate says nothing about the size of wins against losses: a rule right 60% of the time can lose money steadily. This measures direction only, over one fixed horizon, with no costs, no slippage and no position sizing.
It is a tool for finding out whether a familiar rule does anything at all on your instrument. The usual answer is very little, and knowing that is worth more than another arrow.
Indicator
CrosswindCROSSWIND
Crosswind is a signal and trade management indicator built on EMA crossovers, but the crossover itself is only the starting point. Most crossover systems break down in two predictable places. They enter on the cross, which is very often the worst price in the whole move, and they exit at a fixed percentage target, which caps the rare large trends that are supposed to pay for all the small losers. Crosswind addresses both problems and then reports every result net of trading costs, so you can judge whether an edge actually survives the fee schedule.
THREE TIMEFRAME PRESETS
Selecting a trading style sets the EMA pair for you. 15 Min Scalping uses 9 and 21. 1 Hour Swing uses 13 and 48. Daily Trend uses 15 and 150. The preset also sets the width of the trailing stop, since noise that is meaningless on a daily chart will repeatedly eject you from a position on a 15 minute chart.
TREND FILTER
A 200 period SMA gates direction. Long signals are only considered while price trades above it and short signals only while price trades below it. The chart background shades faint green above and faint red below so the active regime is visible at a glance.
TWO SIGNAL MODES
Crossover mode fires when the fast EMA crosses the slow EMA in the direction of the trend filter.
Pullback mode waits. After the fast EMA crosses above the slow EMA, no signal is issued yet. The indicator waits for price to retrace into the slow EMA and then close back across it, within a window of bars that you control. You are buying the first dip after trend confirmation rather than the extension itself. Fewer signals, but a materially better average entry, and your initial stop sits closer to structure.
OPTIONAL MACD CONFIRMATION
A standard MACD can be required to agree with the signal direction. It reduces frequency and filters some counter momentum entries.
HOW A TRADE IS MANAGED
Risk is measured in R, where 1R is the initial stop distance of 2x ATR. Every number the indicator reports is expressed in these units, which makes results comparable across symbols and volatility regimes.
A trade passes through three stages.
Initial stop. Placed 2x ATR from entry. Nothing moves while the trade is proving itself.
Breakeven. Once the trade reaches 1R in your favour, the stop advances to entry plus the full round trip cost plus a small cushion. This is a real breakeven, not a nominal one, so a trade stopped at this stage does not quietly book a small loss.
Trail. Once the trade reaches 1.5R, a chandelier trail arms. It tracks the highest high reached since entry, offset by an ATR multiple, and it only ever ratchets in your favour. The stop line turns blue when the trail is live, so the current stage is always obvious on the chart.
There is no fixed profit target by default. A winning trade runs until the trail takes it out. If you want a cap for comparison purposes you can set a hard target expressed in R.
An alternative EMA trail is included, which follows the slow EMA with an ATR buffer, for traders who prefer a moving average exit.
COST ACCOUNTING
Fees and slippage are charged per side against the actual entry and exit prices, so cost scales properly with price rather than being a flat assumption. Funding is optional and charged per eight hours held, scaled by your chart timeframe. Defaults assume 0.06 percent taker fees and 0.02 percent slippage. Lower the fee if you post maker orders.
This matters more than most traders expect. Cost per trade is roughly twice the round trip percentage divided by the stop distance. On a daily chart with a wide stop this rounds to almost nothing. On a 15 minute chart with a tight ATR it can exceed a tenth of an R on every single trade, which is enough to turn a system with a respectable win rate into a losing one.
READING THE LABEL
The status label reports the live trade state and the closed trade record. Net R and average R per trade are the headline numbers. Gross R and cost drag are shown alongside them deliberately. If cost drag is consuming a large fraction of gross R, the honest conclusion is that the configuration trades too frequently for the size of its edge, and the fix is a stricter entry filter rather than a cleverer exit.
Best and worst trade, win rate, and the outcome of the most recent trade are also shown. Trend following configurations typically produce a win rate below fifty percent while remaining profitable, because the winners are much larger than the losers. Judge the system on average R, not on win rate.
ALERTS
Five alert conditions are available. Long signal, short signal, either signal, stop or trail hit, and trail armed.
THE CONFIGURATION I USE
1 Hour Swing preset with signal mode set to Pullback, and the reversal option left off so that an opposite signal does not close and flip an open position. Trades finish on their own stop or trail, and the next signal is only taken once flat. This produces a lower trade count with cleaner entries and lets the trail do the work of deciding when a move is over.
LIMITATIONS WORTH KNOWING
Signals evaluate on bar close. Stop resolution uses the level carried in from the previous bar before the trail updates on the current bar, which avoids look ahead but means the trail lags by one bar. When a single bar's range covers both the stop and a hard target, the result is scored as a stop, because OHLC data cannot reveal which level was reached first. The statistics are a study of signal quality, not a full backtest, and they assume constant risk per trade with no position sizing or compounding.
This indicator is a tool for analysis and is not financial advice. Test any configuration on your own market and timeframe before risking capital. Indicator
Multi Talent Tool ProThis Multi Talent Tool Pro
Is a comprehensive, all-in-one PulseWire indicator designed to streamline your technical analysis by centralizing three critical trading components into one clean, professional interface.
Key Features
Multi-EMA Suite: Includes eight customizable Exponential Moving Averages (9, 15, 20, 25, 50, 100, 200, 400). You can toggle each one on/off, change colors, and adjust line thickness directly from the settings.
Higher Timeframe (HTF) Dashboard: Provides a "Heads-Up" view of market structure by drawing the last three candles of a higher timeframe directly onto your current chart. It features a smart-tinted background that changes color based on the HTF trend (Bullish vs. Bearish) and includes a live countdown timer until the next HTF candle closes.
Automated Pattern Recognition: Identifies high-probability reversal and indecision signals, specifically Bullish/Inverted Hammers, Dojis, and Engulfing Patterns. These are plotted as clean, professional labels directly on the chart for quick visual reference.
Server-Side Alerts: Every feature is alert-enabled. You can set custom triggers for EMA crossovers, pattern detection, and HTF candle closures, ensuring you never miss a trade setup even when you aren't looking at the screen.
Why It's a "Pro" Tool
Instead of cluttering your chart with multiple indicators, this tool uses garbage collection logic to ensure your screen remains clean. The HTF drawings and pattern labels are calculated to be unobtrusive, allowing you to maintain focus on your primary trading strategy while having all necessary context at your fingertips.
Quick Setup Guide
Right Margin: For the HTF candles to display clearly, right-click your price scale > Settings > Canvas > set your Right Margin to 25 or more.
Alerts: Access these by clicking the clock icon on the right sidebar. Select Multi Talent Tool Pro as the condition, and choose your preferred signal from the dropdown list.
This tool is optimized for traders who demand high-level situational awareness without the distraction of a "busy" chart. Indicator
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Signal Forge [LuxAlgo]The Signal Forge indicator is a modular technical analysis engine that allows users to blend 11 distinct technical filters into a unified signal and backtest the results in real-time. This tool aims to simplify strategy development by providing a visual framework for testing indicator confluence and risk management settings without writing code.
🔶 USAGE
The script provides a flexible logic system for generating signals based on the alignment of multiple technical components. Users can toggle specific indicators on or off and choose between "strict" mode (requiring ALL active indicators to agree) or "any" mode (where ANY active indicator can trigger a signal).
Signals are displayed on the chart as glowing orbs connected to the price action. Each signal includes a real-time historical win rate label at the moment of entry, allowing for a visual audit of the strategy's performance over time.
🔹 Indicator Selection
The tool includes 11 harmonized indicators:
SMA Crossover
RSI Filter (Levels)
MACD Crossover
Supertrend
Stochastic (Trend-based)
Bollinger Bands (Basis Filter)
EMA Crossover
Awesome Oscillator
Parabolic SAR
CCI Filter
ADX/DI Filter
🔹 Risk Management
Users can enable ATR-based Take Profit, Stop Loss, and Trailing Stop levels. When active, these levels are plotted on the chart. The Trailing Stop feature includes a specialized gradient fill that highlights the "breathing room" between the price and the exit level.
🔶 DETAILS
🔹 Dashboards
The script features two distinct dashboards to provide a comprehensive overview of the strategy:
Indicator Dashboard: Shows the real-time bullish/bearish status of all 11 indicators, their individual "standalone" win rates visualized with histograms, and their current toggle status.
Performance Dashboard: Provides a high-level summary of the combined strategy performance, including Net Profit %, Win Rate, Profit Factor, and Total Trades.
🔹 Logic Harmonization
To ensure different indicator types work together effectively, mean-reversion tools like the Stochastic and Bollinger Bands have been reconfigured to act as trend-confirmation filters. For example, the Stochastic signal is bullish when the %K is in the upper half of its range (> 50) rather than looking for oversold extremes, ensuring it aligns with trend-following components like Moving Averages.
🔶 SETTINGS
🔹 Signal Logic
Require All Enabled Indicators to Align: When enabled, every checked indicator must have the same directional bias to generate a signal.
🔹 Risk Management (ATR)
ATR Length: The period used for volatility-based exit calculations.
Take Profit/Stop Loss/Trailing Stop: Toggles and multipliers for managing trade exits.
🔹 Visuals
Orb Distance (ATR): Controls the vertical offset of signal orbs from the price candle.
Orb Base Size: Adjusts the thickness and glow intensity of the signal markers.
🔹 Dashboards
Dashboards: Enable or disable the table overlays.
Position/Size: Options to move and scale the Indicator and Performance tables to fit different screen layouts.
Indicator
Moving Average MTF**Moving Average MTF (Multi-Timeframe)**
This indicator plots three fully customizable moving averages, each calculated from an independent timeframe of your choice. Instead of being limited to the timeframe of your chart, each MA pulls data directly from its assigned timeframe — giving you a layered view of trend across multiple time horizons simultaneously.
By default the three MAs are set to 15 minutes, 1 hour, and 4 hours, all using a 50-period SMA. This makes the indicator best suited for use on a 5-minute chart, where all three timeframes sit above your chart and give you a clear short, medium, and macro trend stack in a single view.
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**Settings**
Each of the three MAs has its own independent group of controls:
- **Show MA** — Toggles the MA line on or off without removing it from the settings.
- **Show Label** — Toggles the end-of-line label that appears to the right of the last candle. The label displays the MA type, length, timeframe, and current value.
- **Length** — The number of candles used to calculate the MA, based on its assigned timeframe. Default is 50 for all three.
- **Timeframe** — The timeframe the MA is calculated from, regardless of what timeframe your chart is on. You can type any valid timeframe directly into this field.
- **Type** — The moving average algorithm. Choose from SMA, EMA, WMA, VWMA, RMA, or HMA.
- **Line Style** — Choose between Solid, Stepline, or Circles.
- **Line Thickness** — Controls the width of the line from 1 to 10.
- **Color** — Full color picker to set each MA to any color you prefer.
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**How to Use**
Keep your chart timeframe at or below the lowest MA timeframe you have set. With the defaults of 15min, 1h, and 4h, running the indicator on a 5-minute chart gives you the most meaningful read. When all three MAs are stacked and sloping in the same direction, trend is aligned across all three timeframes — the highest conviction environment for a trade. When they are tangled or conflicting, the market is in an indecisive state and it is generally best to wait for clarity.
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**Important Note**
If your chart timeframe is higher than any of the MA timeframes you have set, that MA will still display but the value will not be meaningful. The indicator will not produce errors — it is purely a logical consideration. Always ensure your chart timeframe sits below your lowest MA timeframe for accurate results. Indicator
Moving Average XLMoving Average XL is a customizable multi-moving-average overlay that allows traders to plot up to three separate moving averages on the chart at the same time. Each moving average can be independently enabled, adjusted, styled, and color-coded, making it useful for trend direction, dynamic support and resistance, crossover analysis, and multi-timeframe-style trend context.
Each MA group includes the same core settings. “Show MA” turns that moving average on or off. “Length” controls the number of candles used in the calculation, with shorter lengths reacting faster to price and longer lengths smoothing price action more heavily. “Type” lets the user choose between SMA, EMA, WMA, VWMA, RMA, and HMA depending on how responsive or smooth they want the line to be. “Line Style” changes the visual display between solid, stepline, or circles. “Line Thickness” controls the weight of the plotted line, and “Color” lets the user customize each average for easier chart reading.
This indicator is designed for traders who want a clean, flexible moving average tool without unnecessary clutter. Use shorter averages to track near-term momentum, medium averages to define intermediate trend direction, and longer averages to identify major trend bias or high-probability support and resistance areas. Indicator
JOAT Pressure Composite [JOAT]JOAT Pressure Composite
Introduction
JOAT Pressure Composite is an open-source accumulation-distribution and participation oscillator built to measure whether buying or selling pressure is strengthening, weakening, rotating, or diverging from price.
It is designed to expose internal sponsorship behind price movement rather than price movement alone.
The script combines weighted close-location flow, relative-volume sponsorship, volume sigma, effort, efficiency, momentum bias, VWAP bias, and confirmed higher-timeframe context into one composite pressure model.
The problem it solves is hidden participation.
Price can rise on weak effort.
Price can fall on poor sponsorship.
Price can continue moving while internal pressure deteriorates.
Pressure Composite tries to expose those changes earlier by measuring how much of the move is actually being sponsored by participation.
The oscillator pane carries the composite, signal line, envelope, flow ribbon, and extreme states.
At the same time, the indicator projects tailored information onto the main chart.
Price divergence is labeled clearly.
Expansion and absorption states are labeled directly on candles.
Anchored VWAP and trend context are overlaid on price so the oscillator and chart remain connected.
Core Concepts
1. Weighted Pressure Engine
The base flow uses close-location value and weighted volume.
closeLocationValue = (2.0 * close - low - high) / barRange
weightedVolume = volume * sponsorshipFactor
2. Pressure Z-Score
The raw pressure series is normalized with a Z-score.
3. Sigma and Effort Layers
Volume sigma and effort help distinguish aggressive participation from ordinary rotation.
4. Efficiency Bias
The script measures whether price is moving efficiently over the selected lookback.
5. VWAP Bias
Distance from anchored VWAP is normalized in ATR terms.
6. Confirmed Divergence Logic
Pivot-based divergence compares oscillator highs and lows to price highs and lows.
7. Expansion and Absorption Labels
The chart prints Bid Expansion, Offer Expansion, Bull Absorption, and Bear Absorption labels directly on price.
8. Confirmed Higher-Timeframe Context
The script pulls confirmed HTF composite states only.
Features
Composite pressure model: blends pressure, effort, sigma, efficiency, and VWAP bias
Flow ribbon: shows whether pressure is widening or fading
Envelope and extreme states: separates normal expansion from aggressive pressure
Confirmed divergence detection: compares oscillator pivots to price pivots
Clear divergence labeling: bullish and bearish pressure divergence is labeled directly on price
Expansion / absorption labels: market states are marked on actual candles
Anchored VWAP context: projected onto the chart for alignment
Fast / slow trend context: price-side guides remain visible while using the oscillator
Confirmed HTF states: non-repainting higher-timeframe pressure context
No dashboard: information is pushed into the chart and oscillator instead of a table
Input Parameters
Composite Engine:
Smoothing Type
Flow Smoothing
Normalization Length
Relative Volume Baseline
Relative Volume Boost
Volume Sigma Length
Effort Smoothing
Efficiency Length
Signal Length
Envelope Length
Envelope Multiplier
Extreme Multiplier
Pivot Length
Divergence Scan
ATR Length
Qualification / Display:
Use Trend Gate
Trend Fast EMA
Trend Slow EMA
Use VWAP Gate
Minimum Spread
Show Histogram
Show Signal Line
Show Envelope
Show Flow Ribbon
Show Divergence
Tint Price Bars
Shade Momentum States
Show Price Context
Show Price Event Labels
How to Use This Indicator
Step 1: Read the composite vs signal relationship to judge widening or fading pressure.
Step 2: Check whether the state is expansion or absorption.
Step 3: Watch labeled divergences closely, especially after extension.
Step 4: Use anchored VWAP and trend overlays to connect the oscillator back to price structure.
Step 5: Use confirmed HTF context as a quality filter rather than a prediction tool.
Indicator Limitations
Divergences can persist before price responds
Confirmed higher-timeframe context intentionally lags unfinished HTF candles
Low-volume environments can flatten the composite even while price drifts
Pressure quality does not guarantee immediate reversal or continuation
Originality Statement
This script is original in how it integrates weighted close-location flow, RVOL sponsorship, sigma, effort, efficiency, VWAP distance, confirmed HTF context, and direct price-chart state labeling into one coherent participation framework.
The components are combined because they all address one question:
how much real sponsorship exists behind current price movement.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not financial advice.
Pressure readings and divergences do not guarantee reversal or continuation.
Use the script as context and confirmation, not as a promise of outcome.
Best Use Cases
Measuring whether price movement is being sponsored by real participation
Spotting divergence between price and internal pressure
Reading expansion versus absorption conditions
Combining participation context with VWAP and trend structure
Interpretation Notes
The strongest bullish pressure states usually include positive pressure, supportive spread, constructive effort, and favorable price context above value.
The strongest bearish pressure states are the mirror image.
Divergences are most useful when they appear after extension or at major contextual levels.
Absorption labels should be treated as warnings that apparent directional continuation may be losing quality.
Publication Notes
This script is intended to be published with a clean chart where the oscillator, labeled divergence, and at least one price-context label are clearly visible.
Because there is no dashboard, the publication image should make the chart-side annotations easy to read.
Keep the chart clean so the viewer can immediately understand that the script links oscillator behavior back to price.
-Made with passion by jackofalltrades\
Indicator
Concordance Strategy [JOAT]JOAT Concordance Strategy
Introduction
JOAT Concordance Strategy is an open-source multi-factor PulseWire strategy designed to integrate the JOAT indicator stack into one execution framework.
It combines regime context, liquidity interaction, retracement logic, pressure confirmation, channel behavior, and participation filters to decide when enough independent evidence exists to justify a trade.
The problem it solves is single-factor dependency.
Trend-only systems often chase poor location.
Liquidity-only systems can trigger too early.
Oscillator-only systems can fade strong directional auctions.
Retracement-only systems can buy weak pullbacks without sponsorship.
This strategy attempts to solve that by requiring overlap.
It does not assume one tool family is sufficient on its own.
Instead, it asks whether multiple analytical dimensions agree.
That agreement is what the strategy calls concordance.
Core Concepts
1. Regime Gate
The strategy first evaluates local and higher-timeframe baseline structure, slope, volatility state, and directional control.
2. Hard and Soft Directional States
The system uses stronger and softer directional states instead of an all-or-nothing gate.
3. Liquidity and Structure Stack
Entries consider sweep behavior, break state, and displacement.
4. Retracement and Confluence Layer
Local and HTF retracement context help determine whether price is pulling back into a structurally meaningful area.
5. Pressure Confirmation
Pressure logic attempts to confirm that price action has sponsorship behind it rather than only visual momentum.
6. Sigma Channel State
Channel logic helps determine whether price is re-entering a directional path or fading from extension.
7. Participation Filter
Relative volume and delta-style participation help avoid weak sponsorship environments.
8. Risk and Exit Model
The strategy uses structure-aware ATR stops, partial exits, break-even logic, trailing behavior, and optional time exits.
Features
Integrated multi-factor entry model: regime, liquidity, retracement, pressure, channel, and participation
More active soft-entry path: allows more trades while keeping directional structure
Confirmed-bar logic: entries use confirmed state conditions
Equity-risk sizing: position size is derived from risk per trade
ATR and structure-aware stops: volatility and market structure both matter
Two-stage profit taking: TP1 and TP2 split the exit logic
Break-even and trailing logic: protects trades after expansion
Time-based exit: removes stale positions when needed
Dashboard: regime, confluence, pressure, ledger, and position state are displayed
Strategy Properties Used by Default
Initial capital: 100000
Commission type: percent
Commission value: 0.02
Pyramiding: 0
Position sizing: equity-risk based
Trade management: partial exits, break-even logic, ATR trail, optional time exit
How to Use This Strategy
Step 1: Treat it as a research framework rather than a promise of future performance.
Step 2: Evaluate it across multiple markets and timeframes because the more permissive logic should produce broader participation than the earlier strict version.
Step 3: Judge the quality of the trade distribution rather than focusing on one isolated metric.
Step 4: Respect the compromises between selectivity and trade frequency.
Step 5: Use realistic expectations and avoid reading a single backtest as proof of repeatable future outcomes.
Strategy Limitations
The strategy still depends on confirmed conditions and can therefore enter later than a discretionary trader
Trade frequency and quality vary significantly by symbol and timeframe
Default settings are general-purpose and may not be ideal for every market
Optimizing too aggressively can become curve fitting
Backtest results are hypothetical and do not guarantee future performance
Originality Statement
This strategy is original in how it requires agreement across regime, liquidity, retracement, pressure, channel, and participation modules before or during entry qualification.
The components are not merged simply to produce a busier system.
Each one addresses a different failure mode in execution.
Their overlap is the basis for participation.
Disclaimer
This strategy is provided for educational and informational purposes only.
It is not financial advice.
Backtest results are hypothetical and depend on assumptions, settings, and market selection.
They do not guarantee future returns.
Trading involves substantial risk of loss.
Always validate assumptions independently and use responsible risk management.
Best Use Cases
Researching whether cross-confirmation improves selectivity over single-factor systems
Studying how regime, liquidity, retracement, and participation interact inside one strategy
Comparing trade frequency across markets and timeframes after the softer entry expansion
Testing realistic risk-management assumptions inside a multi-layer strategy
Interpretation Notes
This strategy should be evaluated as a process, not as a single summary metric.
Trade count matters.
Distribution of trades matters.
How the system behaves across different instruments matters.
The softer entry path was added to prevent the strategy from becoming too inactive, especially on higher timeframes.
That makes the strategy more usable for broad testing while still preserving directional structure.
Publication Notes
This strategy should be published with a clean chart and realistic default Properties.
If showing results, the description should stay grounded and avoid implying that one test run guarantees future outcomes.
The chart image should make the strategy entries and exits easy to understand.
-Made with passion by jackofalltrades
Evaluation Framework
1. Start by checking whether the strategy is active on the instrument and timeframe you care about.
2. Compare trade count before and after threshold changes.
3. Review whether trade quality remains acceptable as activity increases.
4. Study the interaction between regime, liquidity, pressure, and participation at entry.
5. Judge the strategy by distribution and robustness rather than one isolated metric.
Why This Matters
The strategy exists to test whether agreement across multiple independent analytical layers can improve execution quality.
That research question is more important than any one headline metric.
Open-Source Notes
This strategy is published open source so users can inspect how the modules overlap and how the risk model is applied.
Who This Is For
This strategy is for users who want to study how multiple context layers can be combined inside one execution model.
It is not intended for anyone looking for a one-click guarantee.
Summary
JOAT Concordance Strategy is best understood as a structured research tool.
It exists to test whether regime, liquidity, retracement, pressure, channel, and participation agreement can improve decision quality.
Additional Notes
This strategy should be judged with realistic commission and execution assumptions.
It should also be evaluated on enough trades to produce a meaningful sample.
The defaults are intended to stay grounded rather than theatrical.
Strategy
Regression Deviation Channel [JOAT]Regression Deviation Channel
Introduction
The Regression Deviation Channel is an institutional-style statistical trend and execution framework built around segmented regression, deviation envelopes, premium/discount zoning, breakout qualification, and risk mapping. Instead of acting like a plain moving-average channel, it models price through a best-fit regression path, measures dispersion with RMSE, then classifies where price is trading inside that structure: discount, equilibrium, or premium.
This version is designed to feel more like a desk-grade directional map than a simple overlay. It combines a frozen regression segment, internal band hierarchy, confidence scoring, Supertrend stack alignment, breakout detection, and ATR-based trade mapping into one visual structure. The goal is not just to show where price is, but whether the current move is balanced, compressed, expanding, or resolving.
Why This Indicator Exists
Most channels are too simple. They show boundaries but do not explain what price is doing inside those boundaries. This indicator was built to solve that by combining:
Segmented Regression: Tracks the current directional price path with a proper best-fit slope
Deviation Architecture: Uses RMSE to define statistically meaningful channel width
Premium / Discount Zoning: Splits the channel into expensive, fair value, and cheap territory
Breakout Qualification: Scores breakout quality using slope, participation, structure, and location
Trend Stack Context: Adds Supertrend alignment to distinguish strong directional pressure from noise
Trade Mapping: Builds clean ATR-based stop and multi-target projections after confirmed breaks
The result is a regression channel that does more than draw lines. It gives context, bias, execution framing, and visual hierarchy.
Core Components Explained
1. Segmented Regression Engine
= f_ols(winLen)
basisVal = intercept + slope * float(barsInSeg - 1)
upperVal = basisVal + rmse * multiplier
lowerVal = basisVal - rmse * multiplier
The core engine uses manual ordinary least squares regression to calculate the channel basis. Once the segment matures, the regression values are frozen and projected forward until price resolves beyond the envelope.
This “freeze and resolve” behavior keeps the channel visually stable instead of constantly shifting every bar.
2. RMSE Deviation Structure
Root mean squared error defines channel width, making the envelope responsive to how tightly price is hugging the trend.
Tight RMSE = cleaner trend structure
Wide RMSE = unstable or volatile structure
Internal bands split the envelope into inner, quarter, and outer zones
These nested bands create a true structure ladder instead of a single upper/lower shell.
3. Premium / Discount Channel Arrays
The channel is separated into three value areas:
Premium: Upper edge territory where price is extended and expensive relative to the current regression path
Equilibrium: The center band around fair value and neutral orderflow balance
Discount: Lower edge territory where price is cheap relative to the active path
This makes the indicator more useful for directional context:
Bull channels pressing premium signal strong continuation pressure
Bear channels pressing discount signal strong downside control
Repeated failure to hold premium/discount can signal exhaustion or rebalancing
4. Breakout Confidence Model
Breakouts are not treated equally. The indicator scores breakout quality using four ingredients:
Participation: Distance from the regression basis normalized by ATR
Slope Force: Strength of the normalized regression slope
Location: Whether price is already pressing the outer structure
Alignment: Whether price direction and Supertrend stack agree with the channel
breakoutConfidence = participation + slopeForce + location + alignment
This helps separate lazy drifts from high-quality channel resolution.
5. Supertrend Ribbon Stack
The Supertrend layer is not there as a generic add-on. It acts as a second-order directional filter.
Bull channel + bull Supertrend = higher-quality directional stack
Bear channel + bear Supertrend = stronger downside stack
When regression and Supertrend disagree, price is more likely in transition
The fill between regression basis and Supertrend visually shows whether pressure is aligned or conflicted.
6. ATR Risk Map
After a confirmed breakout, the indicator projects:
1 ATR-based stop level
3 reward targets using configurable risk-reward multiples
Auto-expiring lines so stale trade maps are removed
This gives the channel direct execution value instead of leaving the user to manually measure every move.
Visual Elements
Metallic Basis Line: Gold-toned centerline for the active regression basis
Outer Deviation Shell: Main channel boundaries with glow
Inner Structure Bands: Internal ladder for pressure staging
Premium / Discount Fills: Separate upper and lower value zones inside the channel
Equilibrium Fill: Neutral fair-value region
Supertrend Ribbon: Context layer showing secondary directional alignment
Iridescent Candles: Candle coloring that intensifies as control and confidence improve
Breakout Markers: Compact signals for confirmed resolves
Readiness Diamonds: Pre-break alignment markers when channel conditions are strong
The visual hierarchy is designed so you can read the channel at a glance without relying on heavy objects or clutter.
Dashboard
The dashboard is intentionally compact and fixed to the right side. It shows only the highest-signal metrics:
Bias
Regime
Flow
Channel Position
Confidence
Compression
Trend Stack
Trade Map
How to Use This Indicator
Step 1: Identify Channel Bias
Check whether the regression slope is bullish or bearish. That defines the primary directional path.
Step 2: Read Value Location
See whether price is trading in premium, equilibrium, or discount. This tells you whether price is extended or balanced inside the channel.
Step 3: Watch Trend Stack Alignment
When Supertrend and regression agree, directional pressure is cleaner. When they disagree, reduce conviction.
Step 4: Monitor Confidence
Use the breakout confidence score to judge whether price is merely drifting or building a meaningful resolution.
Step 5: Trade the Resolve, Not the Noise
Use breakout markers and ATR map levels when price exits the frozen envelope with qualified pressure.
Best Practices
Use higher timeframes for cleaner channel geometry
Treat equilibrium as fair value, not a signal by itself
Bull channels work best when premium holds and pullbacks respect the inner bands
Bear channels work best when discount holds and rallies fail at internal structure
High compression followed by rising confidence often precedes expansion
Use the risk map for framing, not blind automation
Indicator Limitations
Regression is still a model of recent price, not a guarantee of future direction
Sudden event-driven moves can invalidate the frozen segment quickly
Premium and discount are relative to the current channel, not absolute market value
High breakout confidence can still fail in thin or news-driven markets
Short segments increase responsiveness but also increase noise
Technical Implementation
Built in Pine Script v6 using:
Manual OLS regression
RMSE deviation envelopes
Segment freeze-and-resolve logic
Internal quarter and inner bands
Premium/discount channel zoning
Supertrend stack integration
Breakout confidence scoring
ATR-based stop and target map
Compact institutional dashboard
Originality Statement
This indicator is original in how it treats a regression channel as a full market-state framework instead of a static overlay. The value is not just in plotting upper and lower lines, but in combining:
Segment freezing
Internal value zoning
Directional stack confirmation
Breakout qualification
Execution mapping
Each layer contributes different information: regression defines path, RMSE defines structure, premium/discount defines value, Supertrend defines stack, and confidence defines quality.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Regression channels, premium/discount zones, and breakout scores are analytical tools, not guarantees of market outcome. All trading decisions remain the responsibility of the user.
-Made with passion by officialjackofalltrades
Indicator
Confluence Engine Strategy [JOAT]Confluence Engine Strategy
Overview
Confluence Engine Strategy is a fully automated Pine Script v6 strategy that combines four independent signal layers into a single numeric confluence score (0–100) before executing any trade. Entries require genuine agreement between linear regression momentum, dual EMA trend regime, ATR volatility state, and higher-timeframe bias. All exits are ATR-proportional with configurable take-profit and stop-loss multiples, plus a bar-based timeout and a trend-flip emergency exit. Commission (0.05% per side) and slippage (2 ticks) are configured for realistic backtesting.
Why Require Confluence?
Single-condition strategies (e.g., "go long when RSI crosses 50") produce entries in every conceivable market environment — ranging, trending, low-volatility, high-volatility — most of which are statistically unfavourable for that signal type. Requiring multiple independent conditions to agree simultaneously filters the entry universe down to the high-probability subset where each individual indicator is operating in its most favourable context. The Confluence Engine makes this filtering explicit and auditable through a numeric score.
Signal Layer 1 — Linear Regression Crossover
The primary entry trigger mirrors the Regression Flux Candles logic: a 21-bar linear regression of close (LR close) crossing above/below an 8-bar SMA of itself. The LR approach de-noises price before computing the crossover, significantly reducing the whipsaw rate compared to raw close-based SMA crossovers.
Signal Layer 2 — Dual EMA Trend Regime
Two exponential moving averages (fast: 21-period, slow: 55-period) define the trend regime. Long entries are only considered when the fast EMA is above the slow EMA; short entries only when fast is below slow. This prevents the LR crossover from triggering counter-trend entries in established trends — one of the most common sources of false signals in momentum strategies.
Signal Layer 3 — ATR Volatility State
The current 14-bar ATR is compared to a 50-bar ATR. Entries are only accepted when the current ATR is above a configurable fraction of the slow ATR (default 0.7). This volatility gate blocks trades during compression phases — low-volatility periods where breakouts frequently fail. The strategy only participates when directional energy is present.
Signal Layer 4 — Higher-Timeframe Bias
A higher-timeframe linear regression direction is fetched via request.security() with lookahead_off. The HTF LR close vs. HTF LR open comparison gives a single bullish/bearish vote from the higher timeframe. Long entries receive a confluence bonus when the HTF agrees; short entries receive a bonus when the HTF is bearish. This aligns trade direction with the prevailing macro bias.
Confluence Score and Threshold
Each of the four layers contributes points to the confluence score:
- LR crossover in direction: +30
- Dual EMA alignment: +25
- ATR volatility expansion: +20
- HTF bias alignment: +25
Maximum score: 100. The minimum required score to execute an entry (default 60) filters out entries where fewer than three layers agree. This threshold is adjustable — lower it for more signals, raise it for higher selectivity.
Entry Logic
Long: LR crossover up AND the accumulated confluence score >= minimum AND the signal is on a confirmed bar AND warmup has elapsed AND no position is currently open AND no cooldown bars remain.
Short: LR crossover down AND confluence >= minimum AND same guards.
A configurable cooldown period (default 5 bars) prevents re-entering the same direction immediately after an exit, avoiding overtrading in choppy conditions.
Exit Logic — Four Exit Conditions
1. ATR Take-Profit: Long exits when close >= entry + ATR × TP multiplier (default 2.0). Short exits below entry - ATR × TP.
2. ATR Stop-Loss: Long exits when close <= entry - ATR × SL multiplier (default 1.2). Short exits above entry + ATR × SL.
3. Bar Timeout: If neither TP nor SL is hit within a configurable number of bars (default 20), the trade exits at market — preventing capital from being locked in stalled trades.
4. Trend Flip Exit: If the dual EMA regime flips against the trade direction (fast EMA crosses slow EMA), the trade exits immediately — recognising that the structural basis for the entry has been invalidated.
Strategy Properties
- Initial capital: $10,000
- Order size: 10% of equity per trade (sustainable risk allocation)
- Commission: 0.05% per side (representative of major exchange fees)
- Slippage: 2 ticks (accounts for spread and execution delay)
- Currency: USD
- Pyramiding: disabled (one position at a time)
These settings are designed to produce realistic backtesting results. Risk per trade is capped well below the 5–10% equity guideline. Commission and slippage are included to prevent overstating performance.
Inputs Reference
Signal Layers
- LR Length (21) — linear regression period
- Signal SMA Length (8) — crossover trigger SMA
- Fast EMA (21) / Slow EMA (55) — trend regime definition
- ATR Length (14) / ATR Slow Length (50) / ATR Threshold (0.70)
- HTF Timeframe — higher-timeframe bias source (default "D")
Confluence & Filters
- Min Confluence Score (60) — minimum sum of layer scores required for entry
- Cooldown Bars (5) — bars to wait after exit before re-entering
- Max Bars in Trade (20) — timeout exit
Risk Management
- TP ATR Multiple (2.0) — take-profit distance in ATR units
- SL ATR Multiple (1.2) — stop-loss distance in ATR units
How to Read the Results
Apply the strategy to a liquid instrument on a 1H or 4H chart with sufficient history to generate 100+ trades. Evaluate:
- Net profit relative to max drawdown (seek ratio > 2:1)
- Win rate in context of average win vs. average loss
- Profit factor (total gross profit / total gross loss, seek > 1.3)
- Number of trades (sufficient sample size for statistical inference)
Adjust the confluence minimum score to trade off signal frequency against quality: 50 produces more trades, 75 produces fewer but higher-quality entries.
Non-Repainting Design
All entries fire on strategy.entry() within barstate.isconfirmed blocks. HTF bias uses lookahead_off. No future bar data is accessed. Historical signals do not shift position.
Limitations
- The strategy is designed as a general-purpose framework. It is not optimised for any specific instrument or session. Optimal parameters vary significantly across markets and timeframes.
- ATR-based exits are approximate. In gap markets (equities overnight, weekend gaps on crypto), the stop-loss may be exceeded significantly before the exit executes.
- Backtesting results are computed on historical data only and do not account for execution quality, broker-specific fees, or market impact. Past backtesting performance does not guarantee future live results.
- The bar timeout exit may prematurely close positions that would have eventually reached TP. This is a deliberate conservative design choice to limit capital lock-up, not a flaw.
Disclaimer
This strategy is provided for educational and informational purposes only. Backtesting results presented in the strategy tester represent historical simulation and do not guarantee any future trading outcome. Past performance is not indicative of future results. Never risk capital you cannot afford to lose. Always use proper risk management and conduct independent analysis before making any trading decisions.
Made with passion by officialjackofalltrades
Strategy
RSI Trend Dashboard + SMMA Channel OverlayAt its core, this script is an RSI trend framework designed to organize momentum into a compact dashboard that is easy to read at a glance, while also extending that same logic back onto the main chart through an optional SMMA-style channel overlay. Instead of treating RSI as just a single line crossing fixed levels, this script breaks it into a layered structure: current RSI state, higher-timeframe comparison, fast and slow RSI average relationships, and a summarized fast-vs-slow regime table view. The goal is not simply to show whether RSI is high or low but to create a cleaner way to read momentum alignment, trend agreement, and chart-side context from one unified engine.
The foundation of the script is the 5-row RSI trend strip. That strip is built to answer a practical set of questions quickly:
Is RSI in a bullish, bearish, or neutral zone?
Is chart RSI above or below its higher-timeframe RSI reference?
Is RSI above or below its fast average?
Is RSI above or below its slow average?
And is the fast average currently above or below the slow average?
That matters because momentum is often easier to interpret as a stack of relationships instead of as one isolated value. A single RSI print can be helpful, but RSI in relation to HTF RSI, fast structure, and slow structure often gives a better read on whether momentum is strengthening, weakening, or starting to rotate.
The added features here are not meant to feel bolted on. They are different ways of reading the same momentum structure. In this script, that includes:
➖ a 5-row trend strip
➖ a stabilized higher-timeframe RSI comparison
➖ fast and slow RSI average relation rows
➖ a fast-vs-slow summary row
➖ a compact dashboard table with current values, bar-to-bar deltas, and slope arrows
➖ an optional RSI-colored price candle overlay
➖ an optional Trend SMMA Channel Overlay on the main chart
➖ an optional smoothed OHLC4 price-average line used to color the channel
➖ optional bullish and bearish triangle markers derived from the overlay engine
The dashboard table is there to keep the same engine readable in a more precise format. The pane gives the fast visual impression. The table gives the actual current readings: rounded values, simple deltas, and short slope arrows so the trader can see not only where RSI and its companion series are, but whether they are currently improving, fading, or flattening. I like that combination because it keeps the script visual first, but still lets you confirm the details without needing to inspect each series manually.
The higher-timeframe layer is an important part of the script. Rather than leaving RSI fully isolated to the local chart, this indicator compares the chart RSI against the next logical higher timeframe so traders can quickly judge whether local momentum is aligned with broader context or starting to separate from it. The script uses SimpleCryptoLife’s HighTimeframeSampling library to stabilize that HTF reference series, which helps keep the higher-timeframe comparison cleaner and more reliable in live use.
The chart-side Trend SMMA Channel Overlay serves a different purpose. While the pane organizes RSI structure, the overlay projects a smoother trend context directly onto price using Wilder-style smoothed high and low boundaries, along with an optional smoothed OHLC4 price-average line. That creates a second way to read the same market: the pane shows internal momentum relationships, while the chart overlay helps show whether smoothed price-average behavior is pressing above the channel, below it, or back inside it. In other words, the pane gives the momentum-state view and the chart gives the price-structure view.
This script also uses auto timeframe length resolvers for the main chart-side overlay tools, which I think makes it more practical across different chart speeds. Instead of forcing users to constantly retune multiple lengths when moving from lower timeframes to higher ones, the script can automatically resolve separate preset lengths for the Trend SMMA channel, the OHLC4 price-average line, and the bullish/bearish triangle engine. Manual controls are still available, but the default design is meant to stay more adaptive and chart-friendly out of the box.
A practical way to think about it:
➡️ If RSI is strong, above HTF RSI, and above both fast and slow averages, momentum is generally aligned in the bullish direction.
➡️ If RSI is weak, below HTF RSI, and below both fast and slow averages, momentum is generally aligned in the bearish direction.
➡️ If the rows begin to disagree with each other, that often signals transition, cooling, or a market that is no longer moving with the same clean momentum structure.
➡️ If the Trend SMMA overlay is also pushing outside its channel in the same direction, that can help reinforce what the pane is already suggesting.
➡️ If the pane and chart overlay begin to disagree, that can be a useful sign that trend strength may be losing alignment.
This is not meant to predict reversals by itself, and I would not treat it as a stand-alone signal machine. The way I use it is more practical:
➖ to judge whether RSI momentum is aligned or mixed
➖ to compare local RSI behavior against higher-timeframe context
➖ to see whether fast and slow momentum structure are still confirming each other
➖ to keep pane-space momentum and chart-space trend context visually connected
That overall framing is very similar to the way my previous Chandelier and Heikin Ashi publishings were written: one central engine, then multiple companion layers that help interpret the same underlying structure rather than replacing it with unrelated tools.
Bar Replay is especially useful here. Watching the strip build one bar at a time makes it much easier to see when RSI shifts from neutral into directional territory, when chart RSI moves above or below its HTF reference, when the fast/slow relationship changes, and how the chart-side SMMA overlay responds as price-average behavior moves through the channel. Scripts like this are often easier to understand dynamically than from a single static screenshot.
Like most momentum tools, this works best with confluence. I would not use it in isolation. Structure, volume, support and resistance, price action, market regime, and higher-timeframe context all still matter. The value of this script is not that it replaces those tools. The value is that it gives RSI a more organized dashboard-style expression while also extending that same read onto the main chart through a cleaner trend overlay.
Credit where it’s due: this script uses SimpleCryptoLife’s HighTimeframeSampling library for the stabilized HTF reference, and portions of the Trend SMMA channel, OHLC4 price-average interaction, and bullish/bearish triangle logic were adapted from concepts used in SimpleCryptoLife’s open-source Price Action Trend work. I always want that lineage to be clear, especially when chart-side concepts have been reworked into a different script and broader dashboard framework.
Indicator
Indicator
MTF Confluence Gauge [JOAT]MTF Confluence Gauge
Introduction
One of the most persistent challenges in technical analysis is the problem of timeframe conflict. A setup that looks perfectly constructed on a 15-minute chart can be swimming against a powerful current on the 4-hour chart, while simultaneously aligned with the daily trend. Traders who operate on a single timeframe are making decisions without full awareness of the forces acting on the instrument across the full spectrum of market participants — from short-term speculators to institutional position traders whose horizons span weeks or months.
The MTF Confluence Gauge addresses this challenge by simultaneously reading the HEMA (Hull-EMA Hybrid) trend state of up to 5 configurable assets across 5 configurable timeframes — producing 25 individual trend readings. Each reading is a directional vote: +1 for bullish HEMA alignment, -1 for bearish alignment, 0 for neutral. These 25 votes are summed into a raw score ranging from -25 to +25, normalized to a -100 to +100 scale, and further refined by local market modifiers including a delta proxy, volume RSI, volatility squeeze state, and local HEMA trend. The result is a composite gauge that represents the aggregate directional consensus across assets and timeframes simultaneously.
This multi-asset capability makes the indicator unique even among multi-timeframe tools. Most MTF indicators read a single instrument across multiple timeframes. The MCG reads multiple instruments across multiple timeframes — enabling users to understand whether a bullish signal on their primary instrument is supported by correlated assets (e.g., sector ETFs, index futures, correlated crypto pairs) or is an isolated move that runs counter to the broader market ecosystem. A long signal supported by bullish readings across correlated assets and multiple timeframes is fundamentally different in quality from one that is isolated to a single timeframe of a single instrument.
Core Concepts
1. HEMA Trend Function for MTF Reads
The HEMA trend function is the foundational building block of every cell in the 5×5 matrix. For each asset-timeframe combination, request.security() retrieves the HEMA values on that timeframe, and the relative alignment of the fast, slow, and macro HEMA layers determines the trend vote. The lookahead parameter is explicitly set to barmerge.lookahead_off to ensure no future data contamination — the trend reading reflects only information that was available at the close of the most recent completed bar of the target timeframe.
f_hema(src, len) =>
ta.ema(2 * ta.ema(src, len / 2) - ta.ema(src, len), math.round(math.sqrt(len)))
f_mtfTrend(sym, tf) =>
h1 = request.security(sym, tf, f_hema(close, hFast), lookahead=barmerge.lookahead_off)
h2 = request.security(sym, tf, f_hema(close, hSlow), lookahead=barmerge.lookahead_off)
h3 = request.security(sym, tf, f_hema(close, hMacro), lookahead=barmerge.lookahead_off)
h1 > h2 and h2 > h3 ? 1 : h1 < h2 and h2 < h3 ? -1 : 0
This function is called 25 times — once per cell in the matrix. The result for each call is stored in a 5×5 array of integers and subsequently used for both the raw score calculation and the table cell coloring.
2. Raw Score and Normalization
The 25 individual trend votes are summed to produce a raw score. This sum is then smoothed with a 3-bar EMA to reduce single-bar noise. Normalization to the range is achieved by dividing the smoothed raw score by 25 (the maximum possible absolute value) and multiplying by 100.
rawScore = 0
for r = 0 to 4
for c = 0 to 4
rawScore += trendMatrix.get(r * 5 + c)
smoothedRaw = ta.ema(rawScore, 3)
normalizedScore = smoothedRaw / 25 * 100
The normalized score forms the base for the histogram and is displayed in the dashboard as the "MTF Bias" value. By normalizing against the theoretical maximum, the scale is consistent regardless of how many assets are configured as neutral (0 votes) — the maximum expressible bull consensus is always +100 and the maximum bear consensus is always -100.
3. Local Score Modifiers
The raw MTF score represents the multi-asset, multi-timeframe consensus, but it does not account for the specific conditions of the primary chart instrument at the current moment. Four local modifier calculations adjust the score based on immediate market context. The local HEMA trend applies a ±10 point bonus. The delta proxy (bar-range-based buying/selling pressure) applies a ±5 point bonus. Volume RSI above threshold applies a ±5 point bonus in the direction of the local trend. The volatility squeeze state applies a ±5 bonus when the market is not squeezing (i.e., volatility is freely expressing direction). All individual bonuses are summed and the combined total is clamped to the range.
localBonus = localTrend * 10
deltaBonus = deltaPos ? 5 : -5
volBonus = highVol ? (localTrend > 0 ? 5 : -5) : 0
sqzBonus = squeezing ? 0 : localTrend * 5
totalScore = math.max(-100, math.min(100, normalizedScore + localBonus + deltaBonus + volBonus + sqzBonus))
displayScore = ta.ema(totalScore, 5)
The final display score is a 5-bar EMA of the adjusted total, providing visual smoothness in the histogram while retaining the responsiveness of the underlying calculations. Local modifiers mean the gauge can show strong bull bias from MTF readings while still being dampened by bearish local conditions — a useful warning mechanism.
4. The 5×5 Color-Coded Table
The visual centerpiece of this indicator is the 5×5 table rendered in the oscillator pane. Each of the 25 cells represents one asset-timeframe combination. Bullish cells are filled with teal and display an upward arrow (▲). Bearish cells are filled with red and display a downward arrow (▼). Neutral cells are filled with violet and display a dash (—). Row 6 of the table shows the column-sum score for each timeframe column, giving an immediate vertical read of how strongly any given timeframe is leaning across all configured assets. This allows traders to identify whether bias is uniform across timeframes or concentrated in specific horizons.
5. Histogram, Squeeze Background, and Reference Lines
The composite score is rendered as a histogram with gradient fill — teal shades above zero transitioning toward deep teal at maximum bull readings, red shades below zero deepening toward maximum bear. Reference lines at ±25 define the "bias threshold" — readings beyond this level indicate a meaningful multi-timeframe lean. Reference lines at ±60 define the "strong conviction threshold" — readings here suggest near-uniform agreement across the majority of configured cells. When the local volatility squeeze is active (detected via ATR compression), the oscillator pane background tints violet, visually indicating that the current score may be elevated or depressed relative to its normal expression due to compressed price action.
Features
25-Cell MTF Matrix: 5 configurable assets × 5 configurable timeframes, each independently returning a HEMA trend vote.
lookahead_off Security Calls: All request.security() calls use barmerge.lookahead_off to prevent future bar data contamination.
Smoothed Normalization: Raw score EMA-smoothed then normalized to for consistent cross-session comparability.
Four Local Modifiers: Local HEMA trend, delta proxy, volume RSI, and squeeze state each contribute bonus points to produce a context-aware composite score.
5×5 Color-Coded Table: Teal/red/violet cells with directional arrows and column score totals for immediate visual matrix reading.
Gradient Histogram: color.from_gradient fill above and below zero with reference lines at ±25 (bias) and ±60 (strong conviction).
Squeeze Background Tint: Violet overlay on oscillator pane background when local volatility compression is detected.
Nine-Row Dashboard: MTF bias label (six levels from STRONG BULL to STRONG BEAR), composite score, raw MTF score, squeeze state, Pearson R, delta bias, volume RSI, and local trend.
Six Alert Conditions: Cross above +25, cross below -25, cross above +60, cross below -60, cross above 0, cross below 0.
Input Parameters
Asset Configuration:
Asset 1-5 Symbols: Ticker symbols for each of the five configurable assets (defaults: current symbol, SPY, QQQ, GLD, TLT or equivalents)
Timeframe Configuration:
TF1-TF5: Five timeframe strings for the matrix columns (defaults: "15", "60", "240", "D", "W")
HEMA Settings:
Fast Length: HEMA fast period for all MTF reads (default: 20)
Slow Length: HEMA slow period for all MTF reads (default: 50)
Macro Length: HEMA macro period for all MTF reads (default: 100)
Local Modifier Settings:
Delta Window: Smoothing period for delta proxy calculation (default: 10)
Volume RSI Threshold: Level above which volume is considered high (default: 65)
ATR Squeeze Length: Period for local volatility compression detection (default: 20)
Display Settings:
Show Table: Toggle the 5×5 trend matrix table (default: true)
Show Histogram: Toggle the composite score histogram (default: true)
Show Dashboard: Toggle the nine-row information table (default: true)
Show Squeeze Background: Toggle the violet compression tint (default: true)
How to Use This Indicator
Step 1: Configure Assets for Your Trading Context
The indicator's value scales directly with the relevance of the configured assets to your primary instrument. For equity traders, configuring sector ETFs correlated with the primary stock (e.g., XLK for technology stocks, XLF for financials) alongside index instruments (SPY, QQQ, DIA) creates a meaningful consensus gauge. For crypto traders, configuring BTC, ETH, and leading altcoins provides an ecosystem-wide directional read. For forex traders, related currency pairs and safe-haven instruments (gold, bonds) capture macro correlation. Spend time selecting assets whose price behavior is structurally linked to your primary trading instrument.
Step 2: Use the Table for Timeframe Structure Analysis
Before looking at the composite score, read the table column by column. If the shorter timeframe columns (15m, 1H) are predominantly teal (bullish) but the longer timeframe columns (Daily, Weekly) are predominantly red (bearish), the market is in short-term counter-trend bounce territory — a higher-risk environment for long trades. Conversely, when both short and long timeframe columns are aligned in the same direction, the consensus is clean and structural. The column score row at the bottom of the table quantifies this alignment numerically.
Step 3: Interpret the Composite Score Levels
The ±25 threshold is the first meaningful level. A score above +25 indicates that more than half of the 25 cells are bullish (adjusted for local modifiers), suggesting a genuine bias rather than random noise. Between +25 and +60, the market has a directional lean but lacks uniform agreement. Above +60, the consensus is strong — the majority of assets across the majority of timeframes are in bullish alignment. The inverse applies below -25 and -60. Cross-zero signals (score moving from negative to positive) indicate a shift in aggregate consensus, which is often a leading indicator of trend changes on the primary instrument.
Step 4: Monitor Local Modifier Impact
The dashboard displays both the raw MTF score and the composite adjusted score. The difference between these two values reflects the cumulative impact of local modifiers. A large positive difference means local conditions (delta, volume, squeeze, HEMA) are amplifying the MTF signal. A large negative difference means local conditions are dampening it — the MTF matrix shows bulls, but the primary instrument itself is not confirming. In these cases, patience is warranted before entering.
Indicator Limitations
The indicator makes 25 request.security() calls plus additional local calculations. On crowded chart setups with many other indicators, this computational load may affect chart loading time. PulseWire enforces limits on request.security() calls per script; users should be aware of this limit if adding other indicators with security calls.
All 25 MTF trend readings update on the chart's native timeframe bars. Readings from higher timeframes update only when a new bar completes on that timeframe — the HEMA reading for a weekly timeframe, for instance, updates only at the weekly close. Between weekly closes, the weekly cell reading remains at the prior week's value.
HEMA calculations at very short periods on very high timeframes (e.g., period 20 on a Monthly timeframe) may have insufficient bars to produce statistically stable readings. Users should ensure the target instrument has sufficient history on all configured timeframes.
Asset correlation is dynamic — assets that are correlated in one market regime may decouple in another. A gauge configured for normal market correlation may produce misleading readings during crisis events when traditional correlations break down.
The local modifier adjustments (±10, ±5, ±5, ±5) are fixed contribution weights. They do not adapt to changing market conditions and may disproportionately influence the composite score during specific regimes.
The composite score is a simplified linear aggregation of heterogeneous signals. It treats a weekly HEMA reading as equivalent to a 15-minute HEMA reading in terms of contribution weight, which may not reflect the practical importance of longer timeframe trends.
Originality Statement
The MTF Confluence Gauge is an original multi-dimensional trend aggregation tool that differs meaningfully from existing multi-timeframe indicators.
The 5×5 asset-timeframe matrix — simultaneously reading five user-configurable assets (not just one instrument across five timeframes) across five user-configurable timeframes — is an original architectural choice that enables cross-asset consensus analysis not available in standard MTF indicators.
The HEMA-based trend vote function (requiring all three HEMA layers to be in sequence for a definitive +1 or -1 vote, otherwise returning 0) is a more stringent trend classification than simple moving average crossovers typically used in MTF dashboards.
The four-component local modifier system — HEMA bonus, delta proxy bonus, volume RSI bonus, and squeeze state bonus — applied as additive adjustments to the normalized MTF score before display is an original composite scoring architecture.
The six-level bias label system in the dashboard (STRONG BULL, BULL, SLIGHT BULL, SLIGHT BEAR, BEAR, STRONG BEAR) derived from the composite score threshold ranges provides a human-readable categorical summary not commonly implemented in MTF oscillators.
The visual integration of the 5×5 table within the oscillator pane (rather than as a separate overlay) alongside the gradient histogram, squeeze background tint, and reference lines at ±25 and ±60 represents a unified pane design not seen in comparable indicators.
Disclaimer
The MTF Confluence Gauge is provided for educational and informational purposes only. It is a technical analysis tool and does not constitute financial advice. Multi-timeframe and multi-asset confluence does not guarantee trade success. Correlation between assets changes over time and cannot be relied upon to remain stable. All trading involves risk of loss. Users are solely responsible for their own trading decisions. Please consider your individual risk tolerance and consult a licensed financial professional before engaging in any trading activity.
-Made with passion by officialjackofalltrades
Indicator
AG Pro Moving Average Ribbon Stress Meter [AGPro Series]AG Pro Moving Average Ribbon Stress Meter
Overview / What It Does
This indicator is designed to read the internal condition of a moving-average ribbon rather than treating the ribbon as a simple trend overlay. Instead of asking only whether the ribbon is bullish or bearish, it asks a different question: is the ribbon structurally calm, starting to load, becoming strained, or losing internal order.
The script builds a six-line moving-average ribbon, measures how those averages interact with each other, and converts that interaction into a stress framework. The result is a visual map that helps show whether the ribbon is organized, stretched, unstable, or resetting after stress.
In practical terms, the script is built to help users evaluate ribbon quality, internal synchronization, and the degree of structural pressure inside the moving-average stack. It is not intended to forecast future prices, call tops or bottoms, or replace broader market analysis. Its purpose is to organize what the ribbon is doing now and how stable or unstable that structure appears to be.
The chart output combines multiple layers: the ribbon itself, a central stress spine, edge bands, optional stress aura, event labels, and a compact status panel. Together, these elements aim to make the ribbon easier to interpret without requiring the user to manually inspect every moving average line on every bar.
Unique Edge
Many ribbon-style tools focus on directional bias, crossovers, or broad expansion and contraction. This script focuses on internal ribbon stress.
Its main distinction is that it does not treat all ribbon trends as equal. A ribbon can be rising while still carrying internal disagreement. A ribbon can also look compressed or visually clean while underlying alignment, slope behavior, width dynamics, or price stretch are beginning to deteriorate. This script is built to surface those conditions.
The goal is not to reduce the market to a single signal. The goal is to provide a structured visual read on whether the moving-average stack is operating in a calm state, a loaded state, a strained state, or a more unstable condition. That makes it more useful as a workflow tool than as a simple trend-colour overlay.
Another point of differentiation is presentation. The script uses a ribbon-focused visual design so that the user can read internal condition directly from the chart. Focus modes, theme presets, stress spine layering, and a compact panel are included to keep the display informative without turning the chart into a dense dashboard.
Methodology
The script evaluates ribbon condition through five stress components.
1) Order Stress
This measures whether the moving averages are stacked cleanly or whether their order is becoming mixed. Lower stress suggests cleaner structural order. Higher stress suggests more internal disorder.
2) Slope Dispersion Stress
This evaluates how consistently the moving averages are sloping together. When the ribbon lines are moving with similar directional agreement, synchronization is stronger. When their slopes diverge, internal stress rises.
3) Width Instability Stress
This tracks whether the ribbon width is behaving in a stable or unstable way. A ribbon can widen in an orderly way or in a more erratic way. This component attempts to distinguish between those conditions.
4) Curvature Stress
This evaluates bending in the ribbon core. Strong changes in ribbon curvature may indicate increasing internal pressure or transition.
5) Price Stretch Stress
This measures how far price is moving from the ribbon core relative to ribbon width and ATR-based normalization. This is not a directional claim. It is a structure-based distance measure.
These components are weighted and blended into a smoothed Stress Score. That score then feeds the state engine.
Primary states include Calm, Loaded, Strained, Critical, Fractured, and Recovery. The panel and visual styling use those states to summarize the ribbon condition at the current bar.
Signals & Alerts
This script is built around state transitions and structural events rather than buy/sell promises.
Depending on settings, users may see event labels and alerts such as:
Stress Build
Shows that stress has crossed into an early loading phase.
Strained
Shows that the ribbon has moved into a more stressed internal state.
Critical Load
Highlights a higher-pressure condition where instability has become more meaningful.
Ribbon Fracture
Marks a stronger structural failure condition when stress and ribbon order deterioration align.
Stress Reset
Shows that a previously elevated stress condition has cooled enough to register recovery.
Order Restored
Highlights improvement in ribbon order after disorder had been present.
These events are not trade instructions. They are context markers intended to help users track shifts in ribbon condition. Alerts should be interpreted together with market structure, timeframe context, volatility, and personal risk management.
Key Inputs
Source and MA Type
The ribbon can be built from different moving-average types and data sources.
Ribbon Lengths
Users can define the six ribbon lengths to fit their preferred structure and timeframe.
Stress Engine Inputs
ATR length, slope lookback, width lookback, curvature lookback, smoothing, and component references allow users to calibrate how sensitive the stress model should be.
Weights
The script includes separate weights for order stress, slope dispersion, width instability, curvature stress, and price stretch stress.
Thresholds
Loaded, Strained, Critical, and Fracture thresholds can be adjusted for tighter or looser state transitions.
Theme Presets and Focus Mode
Theme presets and focus modes allow the ribbon to be displayed in different visual styles while preserving the same logic.
Events and Panel
Users can control label density, label spacing, marker visibility, and panel position.
Limitations & Transparency
This script is an interpretation framework built around moving-average relationships. It does not know future price movement, and it does not claim certainty. Like any model built on smoothed market data, it will react more slowly in some environments and may produce fewer useful transitions in others.
Different assets and timeframes can produce different ribbon personalities. A threshold or weight set that feels balanced on one market may feel too sensitive or too quiet on another. Users should expect to adapt settings if they move between instruments with very different volatility or trend behavior.
The stress model is also deliberately selective. It does not try to label every fluctuation or classify every candle. Its purpose is to organize ribbon condition, not to describe every possible market state.
This indicator should also not be confused with a complete trading plan. It does not define entries, exits, position sizing, or account risk. It is best used as a structural context tool inside a broader workflow.
Risk Disclosure
This script is for chart analysis and educational use. It is not financial advice, investment advice, or a promise of outcome.
No indicator can guarantee performance, remove risk, or eliminate false readings. Market conditions change, correlations shift, and trend behavior can weaken or reverse without warning. Any decision taken from this script should be made within a broader framework that includes price structure, liquidity, volatility, timeframe alignment, and risk control.
Users are responsible for testing settings, understanding the limitations of moving-average tools, and deciding whether the information produced by the script fits their own process.
Indicator
Cross PBThis Pine Script v6 indicator identifies potential trend changes using crossovers of two moving averages (fast and slow), enhanced by a candlestick body confirmation mechanism. It provides two distinct signal types for refined entry/exit points.
Key Features:
Dual Signal System Based on Candle Close:
Alert 1 (Buy/Sell): Triggers after a bullish crossover (fast MA crosses above slow MA) AND a bearish candle (close < open) closes below the fast MA. The inverse applies for a sell signal (bearish crossover + bullish candle + close above fast MA).
Alert 2 (Buy/Sell): Similar to Alert 1, but the candle close condition is checked relative to the slow MA, providing a broader price zone validation.
Moving Average Flexibility: Allows independent selection of length, price source (close, hl2, hlc3, etc.), and type (SMA, EMA, WMA, HMA, ALMA, TMA, TSMA, KAMA, AMA, etc.) for all three moving averages.
Alert Control: Independently enable or disable alerts for buy/sell signals of type 1 and type 2.
Visualization: Plots all three moving averages on the chart for visual tracking of their interactions.
Usage:
The indicator aims to capture the start of trends. The logic of using a bearish candle to confirm a bullish signal (and vice-versa) might represent a dynamic of rejection or consolidation immediately after the crossover before a new trend effectively begins. This can help filter out standard false moving average crossover signals. Indicator
Indicator
Indicator
Welles Wilders MAs - MTFWelles Wilder Moving Averages - Multi-Timeframe (MTF)
This indicator displays Welles Wilder's Smoothed Moving Averages calculated from a higher timeframe of your choice, allowing you to view longer-term trend data on lower timeframe charts (such as tick charts, second charts, or any intraday timeframe).
KEY FEATURES:
• Multi-Timeframe Capability: Plot moving averages from any timeframe (default: 5 minutes) on your current chart
• Four Trend Layers: Short (34), Medium (72), Medium Extension (89), and Long (144) period moving averages
• Welles Wilder Smoothing: Uses the original Welles Wilder moving average formula for smoother, less reactive trend lines
• Flexible Coloring Options: Choose between price-based coloring or MA crossover-based coloring
• Visual Trend Zones: Shaded areas between moving averages help identify trend strength and direction
• Customizable: Adjust all periods, colors, and the source timeframe to fit your trading style
IDEAL FOR:
• Tick chart traders who want to see higher timeframe trends
• Day traders needing multi-timeframe analysis on a single chart
• Traders using range bars, Renko, or other non-time-based charts
• Anyone wanting to filter trades based on higher timeframe moving average trends
HOW TO USE:
1. Add the indicator to your chart
2. Set your preferred timeframe in the settings (default is 5 minutes)
3. Adjust MA periods and colors to your preference
4. Use the MA crossovers and price position relative to the MAs to identify trend direction and potential entry/exit points
The Welles Wilder MA is a type of exponential moving average that provides smooth trend-following capabilities with less whipsaw than traditional moving averages. Indicator
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