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
Indicator
Parallax Covenant Strategy [JOAT]Parallax Covenant Strategy
Introduction
Parallax Covenant Strategy is an open-source, non-repainting PulseWire strategy that integrates multiple analytical engines into one realistic execution framework. It combines regime detection, pressure confirmation, mapped bias, structure context, wave release logic, and ATR-based risk management to produce entries and exits only when several independent conditions agree.
The problem this strategy solves is weak single-factor trading. A crossover alone is rarely enough. A structure break alone is often early. A momentum spike alone can be noisy. Parallax Covenant requires alignment between regime, internal pressure, mapped bias, structural context, and release behavior before taking a trade. This creates a more selective, context-aware model than a one-indicator strategy.
Core Concepts
1. Composite Regime Engine
The strategy builds a directional regime from a structural baseline, tolerance corridors, and expansion/compression state. This acts as the primary directional context.
2. Pressure Confirmation
An internal pressure model blends weighted candle force and channel position to avoid taking trades simply because price is above or below a baseline.
3. Mapping and Higher-Timeframe Bias
The strategy uses a mapped momentum framework and an optional confirmed higher-timeframe bias filter so lower-timeframe entries can align with broader conditions.
4. Structure and Release Filters
Demand and supply context, swing structure, and release-from-compression logic help prevent entries from firing in the middle of low-quality noise.
5. Realistic Risk Management
The strategy uses ATR-based stops, reward-to-risk targets, optional trailing logic after a minimum multiple of risk, and regime-failure exits. This makes the model more realistic than fixed-tick toy strategies.
Features
Multi-engine entry stack: Regime, pressure, mapping, structure, and release alignment
Confirmed-bar logic: Entry conditions are evaluated on confirmed bars
Optional higher-timeframe bias filter: Uses confirmed higher-timeframe values
Demand and supply context: Trade logic includes structural location awareness
ATR stop and target model: Risk adjusts to symbol volatility
Trailing stop activation: Trail can engage after a defined reward threshold
Regime-failure exit: Closes trades when core directional conditions break down
Maximum time-in-trade control: Avoids stale positions
Institutional dashboard: Top-right strategy state summary
Alertconditions: Regime shifts, releases, and setup confirmations
How to Use This Strategy
Step 1: Study the Dashboard
The dashboard shows whether the system currently sees bullish, bearish, or balanced conditions and how the internal engines align.
Step 2: Understand the Entry Stack
Trades only trigger when multiple conditions confirm together. If you see a setup fail to trigger, that is often intentional filtering rather than a bug.
Step 3: Respect the Risk Model
Stops and targets are volatility-based. Results will vary materially across symbols and timeframes because the strategy adapts to local ATR conditions.
Step 4: Evaluate by Regime, Not by Individual Trade
This strategy is meant to be judged over a broad sample. It is a context-and-confirmation model, not a scalping script trying to predict every turn.
Strategy Limitations
The strategy is intentionally selective and may skip many charts or periods
Higher-timeframe confirmation uses confirmed data and can therefore feel slower than live-developing bias models
ATR-based exits adapt to volatility, which means trade statistics can shift significantly across markets
No strategy can remove all adverse conditions, especially during sudden event-driven repricing
Originality Statement
Parallax Covenant Strategy is original in the way it integrates multiple distinct analytical engines into one non-repainting framework. It is not a basic moving average crossover, not a single-oscillator strategy, and not a toy example of ATR stops. Its value comes from requiring alignment between market regime, internal pressure, mapped bias, structure, and release conditions before entering risk.
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any instrument. Historical backtest results do not guarantee future performance. Always use realistic expectations, proper risk management, and independent judgment.
- Made with passion by jackofalltrades
Strategy
Indicator
Moving Average Ribbon (6-Band)Moving Average Ribbon with 6 configurable bands. Built for traders who use multiple MAs to read trend structure, Stage Analysis (Weinstein), and the Minervini Trend Template.
Most MA ribbon indicators on PulseWire max out at 4 bands. That works for basic trend reads, but if you're running a system that uses short-term EMAs for execution timing AND longer SMAs for structural trend confirmation, you run out of slots. This indicator gives you 6.
DEFAULT CONFIGURATION
- MA #1: 5 EMA — short-term momentum
- MA #2: 10 EMA — execution / pullback entries
- MA #3: 20 SMA — short-term trend
- MA #4: 50 SMA — intermediate trend
- MA #5: 150 SMA — Trend Template structural MA
- MA #6: 200 SMA — long-term trend / institutional reference
Defaults are calibrated for daily-chart swing trading with the Minervini Trend Template in mind (price above 50/150/200 in proper order). Every band is fully configurable.
EACH BAND HAS
- Enable / disable toggle
- MA type: SMA, EMA, SMMA (RMA), WMA, VWMA
- Source selection (close, open, hl2, etc.)
- Length input
- Color picker
USE CASES
- Stage 2 trend confirmation (Weinstein / Minervini)
- Pullback entries to short-term EMAs in established uptrends
- Visualizing MA stack alignment for trend-following systems
- Quickly toggling bands on/off to test configurations
Built on the structure of PulseWire's standard MA Ribbon, extended to 6 bands. Indicator
Momentum Covenant Bias [JOAT]Momentum Covenant Bias
Introduction
Momentum Covenant Bias is an open-source momentum pane designed to classify whether the market is in a constructive, defensive, balanced, or compressed state. It blends WaveTrend timing, RSI displacement, normalized trend distance, compression logic, layered state bands, pane boxes, and an optional force-overlay TP/SL scaffold when fresh confirmed momentum shifts occur.
This indicator is meant to solve timing. Trend and auction context can describe where the market is, but they do not always tell you whether momentum is actually participating in the current move. Momentum Covenant Bias translates several independent momentum dimensions into one composite state engine and presents them in a clean, institutional-style pane.
Core Concepts
1. WaveTrend Timing
WaveTrend serves as the primary turning-point rhythm engine. The script uses the relationship between the main line and signal line to measure timing pressure.
2. RSI Displacement
RSI is evaluated not only relative to 50, but also relative to its own smoothed mean. This helps distinguish raw strength from persistent displacement.
3. Normalized Trend Distance
Price distance from the slower trend baseline is normalized by ATR so the output remains portable across markets with different price scales.
4. Compression State
Compression logic compares recent range behavior to a slower baseline. This helps identify lower-energy conditions before expansion.
5. State Boxes and Overlay Scaffold
The pane includes positive, negative, and compression zones, and can project a force-overlay TP/SL scaffold on the chart when a fresh momentum shift is confirmed.
Features
Composite momentum score: Combines WaveTrend, RSI, trend distance, and compression context
Signal line: Smoothed line for momentum transitions
Layered state bands: Positive, negative, and extension zones rendered as gradients
Compression boxes: Visual isolation of low-energy conditions
Top-right dashboard: Displays composite score, signal, wave state, RSI, compression, trend distance, and scaffold status
Force-overlay TP/SL scaffold: Optional informational rails on fresh positive or negative momentum shifts
Confirmed-bar state promotion: Uses confirmed bars for event states instead of unstable intrabar triggers
How to Use This Indicator
Step 1: Read the composite state first. Balanced states should be interpreted differently from impulse states.
Step 2: Compare the composite score to the signal line. Fresh separation often matters more than absolute level alone.
Step 3: Watch compression zones. These can help explain why a market is not yet extending despite directional context elsewhere.
Step 4: If using the optional scaffold, treat it as a planning aid that reflects momentum state, not as a standalone trade system.
Indicator Limitations
Momentum state can reverse quickly in whipsaw markets
Compression logic can remain active for extended periods in slow markets
WaveTrend and RSI are still derivatives of price and can lag during violent reversals
The overlay scaffold is informational and does not execute orders
Originality Statement
Momentum Covenant Bias is original in the way it combines multi-source momentum confirmation, pane state boxes, gradient regime presentation, and force-overlay planning rails in one open-source script. The indicator is intended as a timing layer that complements structure and auction context instead of replacing them.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Momentum conditions are derived from historical price behavior and may fail or reverse without warning. Use proper risk management and independent validation.
-Made with passion by jackofalltrades
Indicator
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
Sniper Trader V6.5 Pro SMC, FVGs & Volume Sweep EngineSniper Trader Pro is an all-in-one Smart Money Concepts (SMC) indicator designed to filter out market noise and identify high-probability institutional setups. Built for precision, this algorithm detects liquidity sweeps, Fair Value Gaps (FVGs), and volume-backed rejections, giving you a clear visual map of where the "Smart Money" is trapping retail traders.
Optimized for volatile assets like indices (NASDAQ/NQ, S&P500) on the 5-minute timeframe, this tool acts as a complete trading system.
Core Features
Dynamic Liquidity Boxes (FVGs): Automatically plots Demand (Aqua) and Supply (Red) zones based on momentum. The algorithm features a smart "garbage collector" that instantly deletes boxes once they are fully mitigated by price, keeping your chart perfectly clean.
Institutional Trend Filters: Integrates key dynamic support/resistance levels, including the 14 EMA, 80 HMA, 200 EMA, and the daily VWAP, allowing you to gauge the macro and micro trends at a glance.
Volume-Backed Sweep Signals: The indicator doesn't just look for wicks; it analyzes the relationship between wick size, body size, and relative volume. It plots clear "LONG" and "SHORT" triangles only when a rejection wick touches a key dynamic level (EMA/VWAP) and is backed by above-average volume.
Ultimate Sensitivity Engine: Fully customizable settings. You can adjust the required wick size, maximum opposite wick size, and volume multiplier to adapt the trigger sensitivity to the current market volatility.
How to Trade with Gems Sniper Trader Pro
This indicator is built to trade pullbacks into liquidity zones in the direction of the macro trend.
For a LONG Setup:
Ensure the price is trading above the 200 EMA (Macro Trend).
Wait for the price to pull back and enter an Aqua Demand Box.
Look for a green LONG triangle signal. This confirms a liquidity sweep bouncing off the 14 EMA, 80 HMA, or VWAP with institutional volume.
Place your Stop Loss safely below the sweep wick.
For a SHORT Setup:
Ensure the price is trading below the 200 EMA.
Wait for a fake breakout into a Red Supply Box.
Look for a red SHORT triangle rejecting the zone with volume.
Place your Stop Loss above the rejection wick.
Pro Tip :
Avoid taking signals that float in the middle of nowhere. The highest probability trades occur when the sweep signal perfectly aligns (confluence) with a Liquidity Box and a dynamic level like the VWAP. 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
Charter Execution Model [JOAT]Charter Execution Model
Introduction
Charter Execution Model is an open-source Pine Script v6 strategy that integrates the broader JOAT framework into a single non-repainting execution model. It does not rely on one trigger alone. Instead, it uses a hierarchy of filters: regime eligibility first, liquidity bias second, structure confirmation third, and imbalance or displacement triggers fourth. Only when those layers align does the strategy consider taking a trade.
The goal of this strategy is not to present a magical black box. It is to model a disciplined decision stack. Many strategies fail because they treat every trigger the same way regardless of context. Charter Execution Model is built around the idea that context should do most of the work. If the market is not in a mature directional regime, if the liquidity ledger is not skewed appropriately, or if local structure does not agree, then a trigger by itself is not enough.
The script uses realistic execution controls directly in the declaration: fixed initial capital, percent-of-equity sizing, non-zero commission, non-zero slippage, no pyramiding, confirmed-bar evaluation, and orders processed on close. Those defaults are intended to make the backtest more responsible and easier to interpret than an overly aggressive model with idealized execution assumptions.
This strategy is best understood as a research framework. It can help traders study how context filters, imbalance triggers, continuation pressure, and ATR-based exits behave when combined inside one model. It is not a guarantee of future profitability, and it should be evaluated thoughtfully across symbols, regimes, and timeframes.
Core Concepts
1. Regime Eligibility Layer
The first gate determines whether the market is mature enough to even consider longs or shorts. It uses a directional midpoint and structural midpoint built from EMA and HMA references, then normalizes their spread by ATR and combines that with heat positioning inside the recent price range.
bool bullRegime = directionalMid > structuralMid
float regimeStrength = clamp(spreadNorm * 0.60 + math.abs(heatNorm - 50.0) * 0.80, 0, 100)
bool matureBullRegime = bullRegime and regimeStrength >= regimeFloor and regimePersistence >= 12
That means the strategy does not allow triggers to fire in weak or undeveloped directional states. Context comes first.
2. Liquidity Bias Layer
Next, the strategy builds a rolling bin-based liquidity distribution and compares buy-side volume versus sell-side volume. A long context requires positive liquidity bias and price above the reference EMA. A short context requires negative liquidity bias and price below the reference EMA.
This adds an inventory-style filter so the strategy is not trading purely off price shape.
3. Structure Filter
Local structure is confirmed using pivot-derived reference points and a rolling swing lookback. Longs require price to hold above recent swing support and above the slow EMA. Shorts require the inverse.
This helps reduce cases where a regime and liquidity reading are still positive or negative, but local price structure has already started to degrade.
4. Trigger Stack
Once context aligns, the strategy allows three possible triggers: a confirmed imbalance gap, a displacement shift, or an optional continuation retest into the directional midpoint. This means the model can participate through both fresh displacement and controlled continuation.
Importantly, the trigger layer does not override the context layer. It only becomes active when the earlier filters already agree.
5. ATR-Based Exit Framework
Risk management is handled through ATR-sensitive invalidation and two fixed-R profit targets. When the regime is especially strong, an optional trailing rule tightens the stop using recent local price action.
This creates a trade structure with a defined stop, two staged exits, and optional adaptation in stronger conditions without relying on unrealistic all-in-all-out assumptions.
Features
Four-layer decision hierarchy: Regime, liquidity, structure, and trigger conditions must align before entry
Confirmed-bar logic: Entries are evaluated only on confirmed bars to avoid repaint-style execution logic
Non-zero execution costs: Includes realistic commission and slippage in the strategy declaration
No pyramiding: Prevents stacking multiple positions in the same direction
Partial profit framework: Uses two independent `strategy.exit()` orders to scale out at separate R multiples
Optional continuation triggers: Allows pullback-style participation inside already qualified context
Optional strong-regime trailing stop: Tightens exits when regime strength is elevated
Dashboard summary: Displays regime, liquidity bias, pressure, trigger state, position state, stop settings, and current risk fields
Clean visual overlay: Shows directional and structural mids with contextual fill directly on the chart
Open-source research design: Lets users inspect and adapt the full context-to-execution hierarchy
Default Strategy Properties
Initial capital: `100000` is used as the default starting capital in the script declaration
Position sizing: Orders use `strategy.percent_of_equity` with a default quantity of `10`, meaning the strategy allocates 10% of equity per position by default
Commission: Commission is modeled as `0.02%` per trade
Slippage: Slippage is modeled as `2` ticks
Pyramiding: Pyramiding is set to `0`, so the model does not stack entries in the same direction
Order timing: `process_orders_on_close = true` and `calc_on_every_tick = false`, so the model evaluates and processes with confirmed-bar logic
Input Parameters
Regime:
Fast Length: Controls the fast directional reference
Slow Length: Controls the slow structural reference
ATR Length: Sets the ATR normalization length
Heat Window: Defines the range window for heat normalization
Regime Strength Floor: Sets the minimum maturity threshold for context eligibility
Liquidity Filter:
Liquidity Lookback: Sets the rolling history used for the liquidity model
Liquidity Bins: Controls the liquidity distribution granularity
Liquidity Bias Floor: Sets the minimum skew required before liquidity counts as directional
Structure Filter:
Pivot Length: Sets pivot confirmation sensitivity
Swing Lookback: Defines the rolling structural context window
Trigger Stack:
Gap Sigma Filter: Sets the minimum imbalance displacement required for gap-style triggers
Shift Momentum Length: Controls the raw momentum lookback
Shift RSI Length: Controls the pressure RSI smoothing
Displacement Floor: Sets the threshold for shift-style triggers
Allow Continuation Triggers: Enables or disables pullback continuation entries
Continuation Pressure Floor: Sets the minimum pressure level for continuation logic
Risk Management:
Stop ATR Multiplier: Scales the ATR contribution to stop placement
Target 1 R: Sets the first partial profit target
Target 2 R: Sets the second partial profit target
Trail In Strong Regime: Enables optional trailing behavior when regime strength is elevated
How to Use This Strategy
Step 1: Evaluate Context Before Results
Begin by understanding what the strategy is trying to do rather than focusing immediately on performance output. It only wants to trade when a mature regime, directional liquidity bias, and confirming structure are all aligned. If that idea does not match your own process, the results will be hard to interpret.
Step 2: Study Trigger Type Distribution
Not all entries come from the same source. Some come from imbalance gaps, some from displacement shifts, and some from continuation pressure. Understanding which trigger type dominates on a given market can be more useful than simply checking net profit.
Step 3: Understand The Exit Framework
The model uses a staged exit approach. Half the position is managed toward the first target and half toward the second. A stop is always active, and strong-regime trailing can tighten the exit path further. Review this logic carefully before drawing conclusions from the backtest.
Step 4: Keep Expectations Realistic
The strategy includes commission, slippage, confirmed-bar logic, and no pyramiding, but that still does not make the backtest “real.” Results depend on the instrument, the timeframe, the data sample, and how well the context assumptions fit the market studied.
Step 5: Use It As A Research Framework
Charter Execution Model is best used as a framework for studying context-first execution logic. Adapt the filters, test the thresholds, and evaluate how the hierarchy behaves across different environments rather than assuming the defaults are universally optimal.
Strategy Limitations
The strategy relies on historical context filters that may adapt poorly to sudden regime shifts or atypical event-driven conditions
Liquidity bias is based on bar-level directional volume attribution rather than true exchange order-flow data
Processing orders on close simplifies execution and can differ materially from real fills on fast markets
Backtest results are sensitive to parameter choices, timeframe selection, instrument behavior, and dataset length
Originality Statement
Charter Execution Model is original in the way it organizes multiple analytical layers into a disciplined execution hierarchy. It is not published as a simple indicator mashup strategy:
It requires mature regime, directional liquidity bias, and local structure to align before any trigger is allowed to matter
It supports multiple trigger archetypes inside the same context framework rather than treating one trigger as universally sufficient
It combines staged exits, ATR-sensitive invalidation, and optional strong-regime trailing inside a consistent risk model
It exposes its internal context state on-chart so users can study why the strategy is active or inactive at any point
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Backtest results depend on assumptions, data quality, slippage, commission, bar resolution, and market conditions. Past performance does not guarantee future results. Always use independent judgment and proper risk management before using any strategy logic in live markets.
-Made with passion by jackofalltrades
Strategy
Concordance Regime Synthesis [JOAT]Concordance Regime Synthesis
Introduction
Concordance Regime Synthesis is an open-source strategy framework that combines regime state, pressure, participation, structure, and higher-timeframe bias into one non-repainting confluence model. The strategy is designed to avoid single-factor entries by requiring multiple independent conditions to align before risk is deployed.
Core Concepts
1. Multi-factor confluence scoring
Long and short setups are scored independently using regime direction, normalized price pressure, participation-axis deviation, delta behavior, recent structure, and optional higher-timeframe bias.
2. Regime-aware execution
Entries only occur when directional confluence exceeds a threshold and the score spread clearly favors one side.
3. ATR-based risk handling
Stops, targets, and optional trailing logic are all derived from ATR so the strategy adapts to volatility instead of using fixed-tick assumptions.
Strategy Properties
Initial capital: 10,000
Order size: 10% of equity per trade
Commission: 0.06%
Slippage: 1 tick
Pyramiding: 0
Orders processed on close
Originality Statement
This strategy is original in its use of a confluence gate that requires independent agreement from regime, pressure, delta, participation, structure, and optional HTF alignment before entries are allowed. It is published as an educational framework for multi-factor strategy construction rather than as a promise of future performance.
Disclaimer
This strategy is for educational and informational purposes only. Backtest results depend on symbol, timeframe, market regime, and execution assumptions. Historical results do not guarantee future returns. Always validate assumptions and use realistic risk controls.
Strategy
Indicator
Indicator
eXeTRADE Main Dual Score Signal Indicator# eXeTRADE-Main — Dual-Score Signal Indicator
**Trend • Support/Resistance • Higher-Timeframe • Backtest — all in one score**
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## What it does
eXeTRADE-Main is a multi-factor signal indicator built for medium-to-experienced traders on **1H, 4H, and Daily** timeframes. It calculates **Long and Short scores independently** from five weighted layers — Trend, Support/Resistance, Momentum, Higher Timeframe, and Risk/Reward — and produces three signal grades:
- **Strong Buy / Sell** — score ≥ 90
- **Normal Buy / Sell** — score ≥ 75
- **Range Buy / Sell** — when R:R ≥ 3.0
The indicator is designed for **plan-driven, low-risk trading**. It auto-detects trend lines and parallel channels, ranks the top three S/R levels by strength, runs a weekly Best-MA backtest, and applies a **Proximity Gate** that penalises signals fired too close to a strong opposing level — the most common cause of immediate reversals.
## Key features
- Dual scoring — Long and Short calculated independently (0–100 scale)
- 14-MA + Best-MA weekly backtest (Trade / Long / Short / S/R averages auto-tuned)
- 3-layer trend line + parallel channel auto-detection with break tracking
- Pivot-based S/R with touch counting and violation tracking; top 3 selected by strength
- HTF context — EMA50/200, RSI, pivot, Ichimoku cloud, and volume folded into the score
- **Proximity Gate** — soft-block or hard-block when entry sits within 0.5×ATR of opposing S/R
- Built-in backtest engine with S/R trailing stop
- Position-management panel for manual entry / TP / SL tracking
- Single consolidated master alert (one alert covers every signal and trail event)
## How to read the chart
Numbered markers on the cover image:
1. **Score Panel** — current Long/Short scores with delta arrows, ATR, and trail status
2. **Top S/R Levels** — three strongest levels, ranked by point score
3. **Backtest Results** — trade count, win/loss, win rate, total P/L, max drawdown
4. **Buy Signal** — green triangle marks Strong / Normal / Range Buy entries
5. **Trail Exit** — yellow × marks where the trailing stop was hit
6. **Auto Trend Lines** — multi-layer trend with parallel channels
## Important settings
- **Backtest Period** — 1 Mo / 3 Mo / 6 Mo / 1 Yr / All
- **Entry Mode** — Single (one position) or Multi (pyramiding)
- **Signal Levels** — Strong (default 90) and Buy/Sell (default 75) thresholds
- **Proximity Gate Mode** — Off / Warning / Soft Block / Hard Block
- **HTF Auto-Bump** — automatically lifts the HTF reference one level if the chart TF matches HTF
## Alerts
A single **master alert** is recommended — it fires for every signal and trail event in one channel. Individual alerts (Strong Buy, Strong Sell, Trail Hit, Channel Break, etc.) are also available if granular control is preferred.
## Best on
4H and Daily timeframes for **Forex pairs, XAUUSD, XAGUSD, and major equities**. Not recommended below 1H — short-timeframe noise reduces score reliability.
## Disclaimer
This indicator is a decision-support tool, not financial advice. **Always define stop-loss and exit plan before entry.** Past performance does not guarantee future results. Trade at your own risk.
---
*Comments and feedback are welcome.*
Indicator
IrishGOD PDH/PDL Zones + Pre-Market H/L + MA RibbonPDH/PDL Zones + Pre-Market H/L + MA Ribbon
A comprehensive overlay indicator for PulseWire (Pine Script v5) that combines three institutional-grade tools on a single chart: historical previous-day high/low zones drawn from full candle wicks, intraday pre-market extremes, and a fully configurable multi-timeframe moving average ribbon. Designed for intraday traders who need clean, actionable levels without switching between charts or timeframes.
Pine Script v5
Overlay
Intraday
Multi-Timeframe
Alerts Included
1
Previous Day High / Low Zones
Automatically identifies the highest and lowest candle of each prior session and draws a shaded zone that spans the full wick of that candle — from the wick tip (the session extreme) down to the candle body edge (max or min of open/close). This provides a realistically sized supply or demand zone rather than a single horizontal line, accurately representing the price range where the reversal originated. Zones are stored across up to 50 prior trading days and drawn efficiently on the last bar to avoid unnecessary repainting.
Lookback
Up to 50 previous days retained and displayed simultaneously
Zone geometry
Wick tip → candle body edge; minimum 4-tick thickness for doji candles
Extension
Most recent zone optionally extends to the right edge of the chart
Labels
PDH / PDL price labels on the latest zone; four size options
Color picker
Border width 0–4px
Adjustable opacity
Toggle on/off
2
Pre-Market High / Low
Tracks the highest high and lowest low recorded during the configurable pre-market window (default 4:00–9:30 AM Eastern Time) and draws horizontal lines at those levels the moment the regular session opens. These levels are widely watched by professional traders as the first potential support and resistance areas of the day, and are particularly relevant on gap-up or gap-down open days. All time calculations are anchored to America/New_York to handle daylight saving time correctly.
Session window
Fully configurable start hour, end hour, and end minute (24h ET)
Line style
Solid, dashed, or dotted; line width 1–4px
Extension
Lines optionally extend rightward through the rest of the session
Labels
"PM High" / "PM Low" labels with exact price values
Requires a PulseWire subscription that includes extended-hours data. Levels reset each new trading day.
3
Multi-Timeframe MA Ribbon
A ribbon of up to 8 independent moving averages rendered directly on the price chart. Each MA is fully self-contained: it has its own toggle, length, color, and — critically — its own timeframe selector. This allows a single ribbon to simultaneously display a short-term trend on the current chart timeframe alongside higher-timeframe MAs (e.g. a daily 21 EMA or a weekly 50 SMA) without opening additional chart panes. When an alternate timeframe is active, the value label automatically appends a tag for instant visual identification.
MA types available
SMA
EMA
WMA
VWMA
HMA
DEMA
TEMA
RMA
LSMA
Ribbon count
8 MAs; MAs 1–5 enabled by default (lengths 8, 13, 21, 34, 55)
Per-MA timeframe
Each MA resolves on its own timeframe via request.security(); blank = current chart
Fill
Gradient color fill between consecutive MA lines; adjustable opacity
Value labels
Live price labels pinned to the right edge; show tag for HTF MAs
Source
Configurable price source: close, open, high, low, hl2, hlc3, ohlc4, etc.
Line width
Global line width control (1–4px) applied to all active MAs
lookahead=barmerge.lookahead_off is enforced on all request.security() calls to prevent higher-timeframe data leakage into historical bars.
4
Alerts
Five built-in alert conditions, configurable from PulseWire's alert dialog:
Price enters the most recent PDH zone (within 0.1%)
Price enters the most recent PDL zone (within 0.1%)
Price enters either PDH or PDL zone
MA1 crosses above MA2 — bullish signal
MA1 crosses below MA2 — bearish signal
5
Technical notes
Compatibility
Intraday charts (1m – 4h). Requires extended-hours data for pre-market feature.
Object limits
max_boxes_count 500 · max_lines_count 500 · max_labels_count 200
Rendering
PDH/PDL boxes drawn only on barstate.islast to eliminate per-tick redraw overhead
DST handling
All session time logic uses America/New_York timezone natively Indicator
Caldera Relative Pressure [JOAT]Caldera Relative Pressure
Introduction
Caldera Relative Pressure is an open-source effort-versus-result oscillator designed to measure whether price movement is being supported by participation, directional efficiency, and close location within the bar. It is built to distinguish clean directional drive from absorption, exhaustion, and two-way rotation.
The problem this script solves is that raw price movement does not explain whether a move is efficient, forced, rejected, or fading. A wide candle on low participation is not the same as a wide candle with expanding participation and strong close location. Caldera converts candle anatomy, relative volume, range behavior, and baseline context into a structured pressure model that is easier to read in real time.
Core Concepts
1. Effort-Versus-Result Framework
The script blends three weighted components:
Effort: candle body and directional spread relative to true range
Result: directional efficiency relative to ATR
Location: where the bar closes inside its own range, adjusted by wick pressure
Those three parts are multiplied by relative volume so that quiet moves and committed moves do not receive the same score.
2. Directional Drive Detection
Bull and bear drive states require a sufficiently large composite pressure reading, positive spread between the composite and its signal line, and close location agreement. This keeps small or conflicted moves from being treated as decisive tape control.
3. Absorption Detection
Absorption is identified by unusually strong volume combined with limited body progress and asymmetric wick behavior. In practical terms, that means participation increased but result did not expand proportionally. This is often a useful clue that one side is meeting aggressive pressure with passive liquidity.
4. Exhaustion Detection
The script also tracks exhaustion. It compares the current pressure state with recent pressure extremes and short-term momentum fade. A move can still be directionally positive or negative while simultaneously losing efficiency.
5. Multi-Layer Pressure Visualization
The pane includes a histogram, composite line, signal line, drive quality line, balance line, participation band, efficiency band, location band, rotation ribbon, and reference ladders. These are separate on purpose:
The histogram shows raw directional pressure
The composite and signal lines show state and rotation
Drive quality shows how healthy the move is
Participation, efficiency, and location bands show what is contributing to the reading
Features
Composite pressure engine: Candle anatomy, ATR efficiency, location, and relative participation
Bull and bear drive states: Measures directional initiative
Bull and bear absorption states: Flags high-effort / low-result behavior
Bull and bear exhaustion states: Flags fading pressure after prior extremes
Baseline context filter: Can require price to align with a directional baseline
Drive quality and balance lines: Separate force from quality
Participation, efficiency, and location bands: Show what is driving the current reading
Rotation ribbon: Highlights positive and negative carry
Dashboard summary: State, bias, strength, regime, context, participation, quality, balance, rotation, and compression
Input Parameters
Core Engine:
Relative Volume Length
Range Normalization Length
Baseline Context Length
Signal Smoothing
Pressure Model:
Effort Weight
Result Weight
Location Weight
Drive Threshold
Expansion Threshold
State Logic:
Absorption Volume Z
Absorption Range Cap
Exhaustion Lookback
Recent State Window
Baseline Context Filter toggle
How to Use This Indicator
Step 1: Read the State Row
The State row tells you whether the market is currently showing directional drive, absorption, exhaustion, or balance. This is the first layer of interpretation.
Step 2: Compare Pressure With Quality
A strong pressure reading with weak drive quality can be unstable. A smaller pressure reading with improving quality can be more constructive. Use those two together rather than treating histogram height alone as the answer.
Step 3: Inspect Participation, Efficiency, and Location
These bands explain why the model is leaning in one direction. If participation is strong but efficiency is weak, the move may be absorption. If efficiency and location are strong but participation is weak, the move may be less durable.
Step 4: Watch the Rotation Ribbon
Rotation tells you whether pressure is continuing, stabilizing, or turning. This can be useful for early changes in internal character even when the headline state has not fully flipped yet.
Indicator Limitations
Relative volume is broker and instrument dependent, so the same thresholds may not transfer perfectly across markets
Absorption and exhaustion are contextual states, not guaranteed turning points
High-volatility event bars can temporarily distort effort-versus-result relationships
A baseline filter improves context but can delay state recognition during sharp reversals
Originality Statement
Caldera Relative Pressure is original in the way it turns candle anatomy, participation, efficiency, and location into a layered pressure model with separate drive, absorption, and exhaustion states. The script is not a simple volume oscillator or candle-coloring tool. Its design is centered on explaining how price is moving, not only how far it moved.
Disclaimer
This script is provided for educational and informational purposes only. It is not financial advice. Pressure readings are based on historical bar data and can misclassify conditions during abnormal liquidity or fast event-driven moves. Always use independent confirmation and prudent risk management.
Indicator
Volatility Compression Oscillator [JOAT]Volatility Compression Oscillator
Introduction
Volatility Compression Oscillator is a two-line momentum oscillator that measures where price is trading inside a dynamic volatility envelope, then tracks the compression and release of that positioning through line crosses, histogram rotation, and divergence. It is designed to show when price is quietly loading pressure, when that pressure starts to expand, and when expansion may be exhausting.
This script is useful for traders who want more than a standard bounded oscillator. It combines normalized price location, dual smoothing, histogram analysis, and divergence into one compact pane.
Why This Indicator Exists
Adaptive Normalization: Measures price against a volatility-sensitive envelope instead of a fixed formula
Two-Speed Momentum Read: Uses fast and slow lines to reveal early shifts in pressure
Compression / Release Logic: The histogram shows whether momentum is accelerating or fading
Exhaustion Markers: Histogram peaks and troughs help spot unstable extensions
Divergence Layer: Tracks when price makes a new swing but oscillator pressure does not confirm
Core Components Explained
1. Dynamic Volatility Envelope
offset = avgRange * scale * (1 + avgBody / avgRange)
The script centers the envelope around the candle midpoint average, then expands it with both average range and average body contribution. This makes the oscillator adaptive to both volatility and candle conviction.
2. Normalized Oscillator Calculation
rawOsc = 100 * (close - lowerBand) / bandWidth - 50
Price is transformed into a centered oscillator that measures whether price is trading in the upper or lower half of the active volatility envelope.
3. Dual-Smoothing Engine
The raw oscillator is processed through fast and slow smoothing chains. Their relationship drives the main trend reading:
Fast above slow = bullish pressure
Fast below slow = bearish pressure
Histogram expanding = pressure increasing
Histogram fading = pressure weakening
4. Signal Layers
The indicator produces several distinct signal families:
MA Cross Signals: Momentum handoff between fast and slow lines
OB/OS Crosses: Stretch events when Line 1 crosses the thresholds
Histogram Peaks / Troughs: Local exhaustion cues
Divergences: Price making a stronger swing while oscillator pressure weakens
5. Chart Cleanliness Controls
Divergence lines are retained with an internal cap so the script does not keep drawing indefinitely. This keeps the pane readable and reduces object-limit risk on long-running charts.
Visual Elements
Histogram Columns: Momentum spread between fast and slow lines
Fast Line: Main directional pressure line
Slow Line: Reference trend line
Zero Fill: Directional fill from Line 1 to the centerline
OB/OS Background: Soft shading in stretch conditions
Signal Markers: Circles, triangles, diamonds, and squares for different event types
Dashboard: Trend, line values, histogram value, regime, and divergence state
Input Parameters
Volatility Window: Lookback for midpoint, body, and range normalization
Band Scale %: Width multiplier for the adaptive envelope
OB / OS Levels: Stretch boundaries for Line 1
Line 1 / Line 2 Smoothing: Controls responsiveness of the dual-line engine
Pivot Length: Sensitivity for divergence and histogram turning points
Histogram Peak Levels: Defines stronger exhaustion zones
How to Use This Indicator
Step 1: Determine whether fast is above or below slow.
Step 2: Watch the histogram for acceleration or decay.
Step 3: Use MA crosses for timing only when they occur in sensible zones.
Step 4: Treat OB/OS signals as context for stretch, not automatic reversal commands.
Step 5: Respect divergences most when they align with histogram exhaustion.
Best Practices
Use higher pivot lengths when markets are noisy
Treat histogram turns near extremes as better-quality warnings
Use line crosses in the direction of the higher-timeframe trend
Avoid overreacting to every divergence in strong trends
Keep marker display on only if you actively trade the signal layer
Indicator Limitations
Oscillators can stay overbought or oversold in strong trends
Divergences are warning signs, not standalone trade systems
Short smoothing lengths will create more noise
Compression readings can fail to expand immediately
Signal quality depends heavily on market structure and instrument behavior
Technical Implementation
Built in Pine Script v6 using:
Adaptive volatility-band normalization
Dual-smoothed oscillator lines
Histogram spread calculation
Pivot-based divergence detection
Object-retention caps for divergence lines
Confirmed-bar signal logic
Originality Statement
This indicator is original in how it frames volatility compression and release through normalized envelope location, dual-line momentum, histogram exhaustion, and divergence management in one pane. Its value comes from synthesis and signal layering rather than from any single oscillator component alone.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Oscillator signals can fail, especially in volatile or trendless conditions. Always use proper risk management and independent judgment.
-Made with passion by officialjackofalltrades
Indicator
Fracture Threshold Strategy [JOAT]Fracture Threshold Strategy
Introduction
Fracture Threshold Strategy (FTS) is an open-source, automated Pine Script v6 trading strategy that combines three independent filters — a seven-condition MasterTrend EMA alignment score, a relative volume regime gate, and a session time restriction — into a single, unified entry system. Entry is triggered by an EMA 4/5 crossover when all three filters are simultaneously satisfied. Stop loss is placed at 1.5× ATR from entry. Take profit is set at a 3:1 reward-to-risk ratio by default. All orders are executed on bar close (process_orders_on_close=false), and signals are gated on barstate.isconfirmed to eliminate intrabar repainting.
FTS is designed to demonstrate how institutional-grade filtering layers can be combined into a programmatic strategy with realistic, auditable results. It is not a black box — every condition is visible in the dashboard and the source code is fully open. The strategy description explains the exact logic, the default backtesting parameters, and the limitations of any backtesting approach.
Core Concepts
1. MasterTrend Seven-EMA Alignment Score
Seven trend conditions are evaluated on each bar. Each satisfied condition contributes one point to a bull or bear score (0–7):
EMA 4 above/below EMA 5 — fast momentum direction
RSI above/below 50 — momentum confirmation
Price above/below EMA 21 — short-term trend
EMA 21 above/below SMA 50 — medium-term structure
SMA 50 above/below EMA 55 — medium-to-intermediate trend
EMA 55 above/below EMA 89 — intermediate trend
Price above/below EMA 750 — long-term macro trend
Entry requires the bull or bear score to equal or exceed the configurable minimum (default: 5 out of 7). This prevents entries during low-conviction, mixed-alignment market conditions.
2. Relative Volume Regime Gate
Volume regime is measured as the ratio of a short-term volume MA to a long-term volume MA, smoothed by an EMA:
float volRatio = ta.ema(volShort / math.max(volLong, 1.0), i_volSmth)
bool volOK = volRatio >= i_volMin
The default minimum ratio is 0.90 — entries are blocked when recent volume is more than 10% below the long-term average. This prevents the strategy from entering trades during dead, low-participation conditions where institutional order flow is absent.
3. Session Filter
Trading is restricted to the London session (08:00–17:00) and New York session (14:00–21:00) in the selected timezone, with both independently toggleable. Entries outside the active sessions are blocked. This keeps the strategy focused on the highest-liquidity periods of the trading day.
4. EMA 4/5 Crossover Entry Trigger
The entry trigger is an EMA 4 crossover above EMA 5 (for longs) or crossunder (for shorts), evaluated on confirmed bar closes. The crossover is a fast momentum signal — it fires at the beginning of a new short-term directional move. Combined with the full filter stack, it identifies the specific bar where momentum begins aligning with the broader structural trend.
5. ATR Stop Loss and 3:1 Take Profit
Stop loss is placed at 1.5× ATR from entry. Take profit is placed at 3× the stop distance (configurable). Both levels are computed at entry and fixed — they do not trail. The strategy uses Pine Script's strategy.exit() function with explicit stop and limit prices for clean, non-discretionary execution.
Default Backtesting Properties
The strategy has been published with the following default Properties settings. These values are used in all performance metrics shown on the chart:
Initial Capital: $10,000 (realistic for an individual trader)
Position Size: 2% of equity per trade (risk-managed sizing)
Commission: 0.05% per side (representative of standard exchange or broker fees)
Slippage: 2 ticks
Pyramiding: 0 (one trade open at a time)
process_orders_on_close: false (orders execute on the next bar open, not at the signal bar close)
Using 2% of equity per trade with a 1.5× ATR stop means the maximum percentage of equity at risk per trade scales with position size dynamically — at a 3:1 RR ratio, three losing trades in a row lose approximately 6% of equity, which is within the PulseWire recommended range. A dataset that generates at least 100 trades is recommended for meaningful statistical evaluation. On lower timeframes (5m, 15m) on major equity indices or forex pairs with London and NY sessions active, the default settings typically produce sufficient trade counts.
Features
Three-Layer Entry Filter: MasterTrend score, volume regime, and session — all three must be satisfied simultaneously
Configurable Minimum Score: Adjustable minimum MasterTrend alignment score threshold (1–7, default: 5)
EMA 4/5 Crossover Trigger: Fast momentum crossover as entry signal within aligned conditions
ATR Stop Loss: Dynamic stop placement based on current ATR — adapts to instrument volatility
Fixed Ratio Take Profit: 3:1 default reward-to-risk — adjustable
Session Restriction: London and New York sessions independently configurable with timezone setting
Volume Regime Gate: Minimum volume ratio filter blocks entries during low-participation conditions
TP/SL Visualization: Active trade TP and SL boxes drawn from entry and extended on each bar — color changes on outcome
Entry Markers: Triangle plotshapes at long and short entry bars for clear chart identification
EMA Reference Plots: EMA 4, EMA 5, EMA 21, and EMA 750 plotted as reference
Non-Repainting: process_orders_on_close=false; all entry conditions gated on barstate.isconfirmed
Dashboard (Top Right): Live MasterTrend state, volume regime, session, current position, net P&L, win rate, profit factor, max drawdown, average win/loss, and RR ratio
Entry Context Labels: Each entry label now shows the MasterTrend score and volume regime tag at the moment of entry in the format "L 6/7 | V:HI" — full entry context visible on the chart without needing to consult the dashboard
Position Candle Tint: Candles colored green while a long position is open, red while a short position is open — provides an immediate visual record of all trade durations across the full chart history
Per-Session Performance Breakdown: London and New York win rates tracked and displayed separately in the dashboard — identifies which session produces the strongest historical edge for the current instrument and timeframe
Expanded Dashboard (15 Rows): Dashboard expanded to 15 rows — now includes a full session performance section with London and NY win rates alongside the existing strategy performance metrics
Input Parameters
MasterTrend EMA Stack:
EMA 4, EMA 5, EMA 21, SMA 50, EMA 55, EMA 89, EMA 750: All periods individually configurable
RSI Length: RSI period for momentum condition (default: 14)
Volume Regime Filter:
Short Vol MA / Long Vol MA: Volume baseline calculation periods (default: 10, 40)
Vol Smooth: EMA smoothing for ratio (default: 3)
Min Vol Ratio: Minimum ratio threshold for entry permission (default: 0.90)
Session Filter:
Timezone: Session evaluation timezone (default: America/New_York)
Session Filter: Master toggle (default: enabled)
Allow London / Allow NY: Independent session toggles (both default: enabled)
Entry Trigger:
EMA4/5 Cross Entry: Use crossover as trigger (default: enabled)
Min MasterTrend Score: Minimum score required for entry (default: 5)
Risk Management:
ATR Length: ATR period (default: 14)
ATR SL Multiplier: Stop distance as ATR multiple (default: 1.5)
Reward:Risk Ratio: TP multiple (default: 3.0)
How to Use This Strategy
Step 1: Verify the Filter Stack is Active
The dashboard shows MasterTrend state, volume regime, and current session at all times. Before a trade can occur, all three must be aligned — a bull score ≥ 5, volume ratio ≥ 0.90, and an active London or NY session window.
Step 2: Observe the EMA 4/5 Crossover
The entry trigger is the EMA 4 crossing EMA 5. With all filters active, the next crossover in the trend direction will generate an entry. The entry is executed at the open of the following bar (process_orders_on_close=false), which is the realistic execution point.
Step 3: Manage the Open Trade
The TP/SL boxes extend from the entry bar and update on each subsequent bar. The strategy's exit function manages the trade automatically — no manual management is required. The dashboard shows the current position state (LONG / SHORT / FLAT) at all times.
Step 4: Evaluate Backtesting Results Critically
Past results do not predict future performance. Before drawing conclusions from any backtest, ensure the trade count is at least 100. A small sample (under 50 trades) produces unreliable win rate and profit factor estimates. Test across multiple instruments and timeframes — a strategy that performs well on one asset in one period may not generalize.
Strategy Limitations
The EMA 750 requires 750 bars of chart history. On timeframes or instruments with limited bar history, the 750-period EMA will be inaccurate for the first 750 bars — backtest results including those bars should be discounted
Backtesting does not account for liquidity, market impact, or partial fills on real orders. The 2-tick slippage setting is an approximation — on illiquid instruments or during news events, actual slippage may be significantly higher
The EMA 4/5 crossover is a fast signal. In choppy, sideways markets where EMAs cross frequently, the strategy may enter multiple trades quickly that all exit at stop loss before the filter stack re-assesses. The session and volume filters reduce but do not eliminate this behavior
A fixed 3:1 RR ratio requires the market to travel 3× the initial risk without reversing. On short timeframes or on instruments with narrow average ranges relative to ATR, achieving the full TP target may be less frequent than on smoother-trending assets
Commissions, taxes, and regulatory fees vary by broker, instrument, and jurisdiction. The 0.05% commission default is a general estimate — actual trading costs should be substituted with broker-specific values before drawing performance conclusions
This strategy is one specific configuration of the underlying filter system. Adjusting the minimum MasterTrend score, volume threshold, session windows, or RR ratio will produce different results. Any configuration change constitutes a separate strategy with its own performance characteristics
Originality Statement
FTS implements a programmatic entry system by combining a seven-condition quantitative trend score, a relative volume regime gate, and a session time restriction into a unified, fully transparent open-source strategy. This is original for the following reasons:
The MasterTrend alignment score functions as a structural quality gate — rather than entering on any EMA crossover, the strategy explicitly requires a minimum number of the seven structural conditions to be simultaneously satisfied, producing a much stricter entry criterion than a standard crossover system
The volume regime gate uses a normalized ratio (not a raw volume level) to block entries during low-participation conditions — making the filter relevant across instruments and timeframes without requiring instrument-specific volume threshold calibration
The combination of structural alignment (EMA stack), activity quality (volume regime), and time context (session filter) as three independent prerequisites creates a compounding selectivity effect — the strategy only enters the specific intersection of all three conditions, which is a smaller, higher-conviction subset than any single filter alone
The live dashboard displaying all filter states, position context, and key performance metrics simultaneously provides full transparency into why any given bar does or does not produce a signal, making the strategy auditable in real time
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Backtesting results shown are based on historical data and do not guarantee or predict future performance. Past results are not indicative of future results. Commission and slippage values used in backtesting are estimates — actual trading costs will vary. The strategy does not account for all real-world execution factors. Always use proper risk management and consult a qualified financial professional before making trading decisions. The author is not responsible for any trading losses resulting from the use of this strategy.
-Made with passion by jackofalltrades Strategy
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
Indicator
Indicator
Sovereign Trend Strategy [JOAT]Sovereign Trend Strategy
Introduction
The Sovereign Trend Strategy is a systematic, rules-based trend-following strategy built on the SMEMA (SMA of EMA) crossover engine — a double-smoothed moving average system that removes the erratic noise of raw EMA crossovers while remaining faster to respond than pure SMA systems. It enters long and short trades on SMEMA fast/slow crossovers, applies four optional confirmation filters (ADX, RSI, volatility ratio, and baseline), and manages each trade through a full exit framework: stop loss, two take-profit levels with partial close at TP1, a dynamic trailing stop, a trend-reversal exit, and a maximum bars cap that forces turnover.
This is a strategy designed to trade constantly — the default configuration is tuned for maximum trade frequency across all assets and timeframes, with all optional filters disabled so that every valid SMEMA crossover generates a signal. Traders seeking higher-quality entries can enable the ADX, RSI, baseline, or volatility filters individually to raise the bar.
Core Concepts
SMEMA — Double-Smoothed Moving Average Engine
The SMEMA construction applies a simple moving average on top of an exponential moving average, producing a line that is more responsive than a plain SMA but smoother than a raw EMA:
smema(float src, int len) =>
ta.sma(ta.ema(src, len), len)
float fast = smema(close, smFast)
float slow = smema(close, smSlow)
float baseline = smema(close, smBase)
Three SMEMA lines are computed: a fast line (default length 2), a slow line (default length 5), and a longer baseline (default length 15). Crossovers between fast and slow generate the entry signals. The baseline provides an optional directional filter when enabled.
Entry Conditions
Long entries fire when the fast SMEMA crosses above the slow SMEMA with all active filters passing:
bool xUp = ta.crossover(fast, slow)
bool longOk = xUp and adxOk and rsiLongOk and volOk and baseOk
and warmed and inDateRange and barstate.isconfirmed and doLong
Short entries mirror this on downward crossovers. Entries only fire when there are no open trades (pyramiding disabled), ensuring clean one-trade-at-a-time management.
Trade Management Framework
Each trade uses ATR-based levels calculated at entry:
| Level | Default Multiplier | Purpose |
|-------|-------------------|---------|
| Stop Loss | 1.8× ATR | Full position stop |
| TP1 | 2.5× ATR | 50% partial close, breakeven stop move |
| TP2 | 4.5× ATR | Full position close |
| Trailing Stop | 1.5× ATR | Activated after TP1 hit |
After TP1 triggers, the stop-loss is moved to the entry price (breakeven). The trailing stop then follows price by 1.5× ATR, locking in profit while letting the remaining position run toward TP2. This staged approach captures quick-reaction profits at TP1 and rides momentum toward TP2.
Six Exit Paths
// Priority order for long exits:
// 1. Stop Loss — low <= entrySL
// 2. TP1 — high >= entryTP1 (50% partial, breakeven stop set)
// 3. TP2 — high >= entryTP2 (full close after TP1 hit)
// 4. Trailing — low <= trlStop (after TP1 hit)
// 5. Reversal — fast SMEMA crosses below slow (xDn confirmed)
// 6. Max Bars — barsInTrd >= maxBars
The max bars exit (default 10) is particularly important for trade frequency — it guarantees no position is held longer than 10 bars regardless of whether any other exit triggers, creating rapid capital recycling and enabling 100+ trade sample sizes even on daily timeframes.
Optional Confirmation Filters
All four filters are disabled by default and can be enabled individually:
ADX Filter — requires ADX above a minimum threshold before entry. Prevents entries in ranging, low-momentum markets.
RSI Filter — requires RSI above the bull minimum for longs (default 52) or below the bear maximum for shorts (default 48). Confirms momentum alignment with direction.
Volatility Ratio Filter — requires current ATR to be at least a configurable fraction of its own SMA. Filters out squeeze conditions where ATR is compressed.
Baseline Filter — requires close to be above the baseline SMEMA for longs and below for shorts. Adds a medium-term trend confirmation layer.
Strategy Parameters (Backtesting Standards)
Initial capital: $10,000 (realistic for the average retail trader)
Position size: 100% of equity (maximizes trade count visibility in backtest)
Commission: 0.05% per side (appropriate for most spot and futures markets)
Slippage: 2 ticks (conservative estimate for liquid instruments)
Pyramiding: 0 (no compounding positions)
Features
SMEMA fast/slow crossover entry engine with three configurable period lengths
Full trade management: ATR-based SL, TP1 (50% partial), TP2 (full), trailing stop, reversal exit, max bars exit
Breakeven stop migration to entry price after TP1 hit
Four optional confirmation filters: ADX, RSI, volatility ratio, and SMEMA baseline
Long-only, short-only, or both directions configurable
Date range filter for restricted backtesting windows
Live SL, TP1, and TP2 dashed lines drawn on the chart while a trade is open
SMEMA ribbon fill between fast and slow lines, colored by crossover direction
▲ LONG / ▼ SHORT signal labels at every entry signal
Dashboard: position, SMEMA cross direction, ADX, RSI, vol ratio, trade count, win rate, net P&L, bars in trade, settings summary
Alerts for long entry and short entry signals
Webhook JSON alert format
Watermark
Input Parameters
SMEMA Engine
Fast SMEMA Length — period for the fast crossover line (default 2)
Slow SMEMA Length — period for the slow crossover line (default 5)
Baseline SMEMA — period for the optional trend baseline (default 15)
Trend Filter
ADX Length — period for ADX / DMI calculation (default 14)
Min ADX — minimum ADX value required before entry (default 18)
Enable ADX Filter — master toggle (default off)
RSI Filter
RSI Length — period for RSI calculation (default 14)
RSI Bull Min — minimum RSI for long entries (default 52)
RSI Bear Max — maximum RSI for short entries (default 48)
Enable RSI Filter — master toggle (default off)
Volatility Filter
ATR Length — lookback for ATR (default 14)
ATR Smooth — lookback for the ATR average used in ratio (default 20)
Min Vol Ratio — ATR/AvgATR minimum threshold (default 0.8)
Enable Vol Ratio Filter — master toggle (default off)
Baseline Filter
Enable Baseline Filter — when on, requires close above baseline for longs and below for shorts (default off)
Trade Management
Stop-Loss ATR Mult — distance of initial stop from entry in ATR units (default 1.8)
TP1 ATR Mult — distance of first take-profit from entry (default 2.5)
TP2 ATR Mult — distance of second take-profit from entry (default 4.5)
Use Trailing Stop — enables dynamic trailing after TP1 (default on)
Trailing Stop ATR Mult — trail distance in ATR units (default 1.5)
Max Bars in Trade — maximum bars before forced exit (default 10)
Trade Direction
Allow Long Trades — toggles long entry signals (default on)
Allow Short Trades — toggles short entry signals (default on)
Date Range
Enable Date Filter — restricts backtesting to a specific window
From Date / To Date — start and end of the active period
Visuals
Bull Color — cyan default for upside elements
Bear Color — red default for downside elements
Neutral Color — gray for baseline and neutral dashboard text
Show Dashboard — live performance and settings panel
Show Watermark
Show Signal Labels — ▲ LONG / ▼ SHORT markers on entry bars
Show SMEMA Bands — toggles the ribbon and three SMEMA line plots
How to Use
Add the strategy to any chart. The default settings are tuned for high trade frequency — no filters enabled, fast periods of 2/5, max bars 10.
Run the Strategy Tester to review backtest performance. Check that the trade count is above 100 on your chosen timeframe and symbol before drawing any performance conclusions.
To increase signal quality at the cost of trade frequency, enable filters one at a time: start with the ADX filter to eliminate ranging entries, then add RSI if you want additional momentum confirmation.
Use the SL/TP dashed lines drawn on-chart during live trades to monitor your risk levels visually in real time.
Set the Long Entry and Short Entry alerts to receive notifications. Use Webhook JSON format to route signals to automation platforms.
Adjust the ATR multipliers to fit the volatility profile of your market. Higher-volatility assets like altcoins benefit from wider stops (2.0–2.5×) and wider TP levels. Lower-volatility assets like indices may work better with tighter parameters.
The Max Bars in Trade parameter is the most powerful lever for trade frequency. Reducing it to 5–7 generates very high trade counts. Increasing it to 20–40 gives trades more room to develop but reduces total trade count.
Indicator Limitations
SMEMA crossovers are inherently lagging — by definition, the crossover confirms a direction change after it has already begun. In fast-moving markets this means entries will not be at the exact turning point.
The default configuration (all filters off, max bars 10) optimizes for trade count and sample size rather than highest possible win rate. Enabling filters will reduce trade count but may improve per-trade quality — test thoroughly on your symbol and timeframe before live use.
The 100% equity position sizing in the backtest is chosen to keep commission effects proportional and performance metrics visible at small capital sizes. This does not represent a recommendation to risk your entire account on any trade.
Backtested results are not a guarantee of future performance. Past performance under any parameters does not imply future results.
The strategy uses `calc_on_every_tick=false` — all orders execute at bar close, which is more realistic than tick-by-tick simulation but means intrabar SL/TP wicks may not be captured accurately in the backtest.
Originality Statement
The Sovereign Trend Strategy is an original Pine Script v6 strategy publication. The SMEMA (SMA of EMA) double-smoothing construction is an original baseline engineering choice that produces a distinct crossover behavior not replicated by standard EMA or SMA crossover systems. The six-path exit framework, the staged TP1/breakeven/trailing/TP2 management sequence, and the modular optional filter architecture are original design decisions. The strategy.position_size derivation of position state (avoiding the Pine Script v6 timing bug with strategy.opentrades and manual boolean flags) is an original technical solution developed for this publication.
Disclaimer
This is a backtested strategy provided for educational purposes only. It does not constitute financial advice or a recommendation to trade any specific instrument. All trading involves risk of capital loss. Backtested performance does not guarantee future results. Commission, slippage, and real-world execution conditions will differ from backtest simulations. Always perform your own analysis and consult a licensed financial professional before trading with real capital.
-Made with passion by jackofalltrades
Strategy
