RSI + Psy + ADX P2RSI + Psy + ADX
This indicator combines multi-length RSI analysis with the Psychological Line (PSY) and ADX trend strength to highlight reversal zones, emotional extremes, and trend conditions in a single unified panel.
🔹 Features
1️⃣ Triple RSI with Dynamic Colors
Displays Short / Mid / Long RSI values (9 / 26 / 52 by default)
Line color changes based on RSI levels:
🔴 Overbought (above 68)
🟢 Oversold (below 32)
⚪ Neutral market conditions
Fixed zone levels at 70 / 50 / 30 for simple visual analysis
2️⃣ Psychological Line (PSY) Extreme Signal
Measures the percentage of bearish candles in the selected period
Only highlights emotional extremes (overbought & oversold conditions)
Red/Green histogram makes market sentiment easy to read
3️⃣ ADX Trend Strength Detector
Confirms trend momentum using ADX
Color-coded levels:
🔵 Weak trend
🟡 Moderate trend
🔴 Strong trend (possible trend continuation)
Helps avoid counter-trend trades during strong momentum
4️⃣ RSI Background Highlight (Mid-term RSI Only)
Background turns RED in overbought area
Background turns GREEN in oversold area
Provides fast and clean recognition of reversal zones
🎯 Best Uses
Identifying low-risk reversal entry zones
Avoiding entries against strong trends
Confirming momentum and sentiment alignment
Useful for scalping, day-trading, and swing-trading strategies
💡 Tip
For higher precision, combine this indicator with:
🔹 Support/Resistance Levels
🔹 Candlestick Reversal Patterns
🔹 Volume Spikes or Breakout Tools
Phân tích Xu hướng
3 Lines RCI + Psy Signal + RSI Background📌 3 Lines RCI + Psy Signal + RSI Background
This indicator combines three RCI lines, Psychological Line signals, RSI-based background highlights, and ADX strength detection to visualize market momentum, trend strength, and potential reversal zones.
🔍 Main Features
📌 1. Triple RCI (Rank Correlation Index)
Displays Short / Mid / Long RCI
Detects momentum shifts and trend reversals
Highlight zones:
Overbought: +80 ~ +100 (Red Zone)
Oversold: -80 ~ -100 (Green Zone)
📌 2. Psychological Line Signal
Column bars appear only in extreme conditions:
Overbought → Red Bars
Oversold → Green Bars
Helps detect short-term sentiment extremes
📌 3. RSI Background Highlight
Red Background: RSI > Overbought threshold
Green Background: RSI < Oversold threshold
Provides a visual cue of underlying market pressure.
📌 4. ADX Trend Strength
ADX line color shows strength level:
Blue: Weak trend
Yellow: Moderate trend
Red: Strong trend
Useful to identify whether signals occur in a trend or range state.
🎯 Trading Usage Tips
RCI + RSI + Psy confluence can identify strong reversal timing.
Use signals only when ADX is weak or moderate to avoid counter-trading a strong trend.
Combine short/mid RCI crossovers with extreme zones for potential entry timing.
⚙️ Suitable For
Scalping, day trading, swing trading
Stocks, Forex, Crypto, Indices, Commodities
Omni-Divergence Pro [Hodldean]Omni-Divergence Pro
Most traders rely on a single indicator (like RSI or MACD) to make decisions. The problem? Single indicators are noisy, prone to false signals, and fail in changing market conditions.
Omni-Divergence Pro is different. It does not rely on one data point. Instead, it deploys a Consensus Engine—an underlying algorithm that aggregates 11 professional-grade market models into a single "Vote."
Only when the Price Action structurally disagrees with this Mathematical Consensus do you get a signal.
How It Works: The 3-Layer Filter
This script is designed to filter out 90% of market noise and only present high-probability setups using a proprietary 3-step validation process:
1. The Consensus Engine (11-Factor Model) Instead of just looking at momentum, we calculate a normalized score based on 11 distinct market dimensions, ranging from standard trend followers to advanced Digital Signal Processing (DSP):
Trend: Hull MA (HMA), Kaufman Adaptive MA (KAMA), Ichimoku Cloud.
Momentum: Smoothed RSI, Stochastic RSI, Donchian Channels.
Advanced DSP: Ehlers Super Smoother, Ehlers Fisher Transform, Ehlers Cyber Cycle.
Next-Gen Filters: Laguerre Filter, ALMA (Arnaud Legoux / JMA Proxy).
2. Structural Divergence (The Trigger) We do not look for simple "oversold" levels. We look for Structural Disagreement.
Bullish Signal: Price makes a Lower Low, but the Consensus of 11 indicators makes a Higher Low. The underlying data is screaming "Strength" while price is still dropping.
Bearish Signal: Price makes a Higher High, but the Consensus fails to confirm it.
3. The Volume Veto (The Confirmation) A divergence without volume is a trap. This system includes an integrated RVOL (Relative Volume) Filter.
If a signal forms on low volume (weekend/lunch hour), it is rejected.
Signals are only valid if Institutional Volume supports the move.
Features at a Glance
Clean Charts: No messy lines or oscillators. You only see "BUY" and "SELL" labels when a validated signal occurs.
Dual-Mode Detection:
Regular Divergence: For catching tops and bottoms (Reversals).
Hidden Divergence: For entering pullbacks in a strong trend (Trend Continuation).
Zero Repainting Logic: Signals are generated based on strict pivot confirmation. Once a signal is printed and the candle closes, it never disappears.
Technical Specifications
Confirmation Lag: This system prioritizes accuracy over speed. Signals appear upon the confirmation of a Pivot High/Low (default: 5 bars).
Visual Offset: Labels are plotted in the past (offset) to pinpoint exactly where the structural top/bottom occurred, providing clear context for stop-loss placement.
Best Timeframes: Optimized for 15m, 1H, 4H, and Daily charts. (For higher timeframes like 4H/Daily, consider lowering the Lookback setting to 3).
⛔ ACCESS & PRICING
This is an Invite-Only script. To protect the proprietary "Consensus Engine" logic, the source code is hidden.
Trading involves risk. This tool is designed to assist in analysis, not to guarantee profits. Past performance is not indicative of future results.
ChronoPulse MS-MACD Resonance StrategyChronoPulse MS-MACD Resonance Strategy
A systematic trading strategy that combines higher-timeframe market structure analysis with dual MACD momentum confirmation, ATR-based risk management, and real-time quality assurance monitoring.
Core Principles
The strategy operates on the principle of multi-timeframe confluence, requiring agreement between:
Market structure breaks (CHOCH/BOS) on a higher timeframe
Dual MACD momentum confirmation (classic and crypto-tuned profiles)
Trend alignment via directional EMAs
Volatility and volume filters
Quality score composite threshold
Strategy Components
Market Structure Engine : Detects Break of Structure (BOS) and Change of Character (CHOCH) events using confirmed pivots on a configurable higher timeframe. Default structure timeframe is 240 minutes (4H).
Dual MACD Fusion : Requires agreement between two MACD configurations:
Classic MACD: 12/26/9 (default)
Fusion MACD: 8/21/5 (default, optimized for crypto volatility)
Both must agree on direction before trade execution. This can be disabled to use single MACD confirmation.
Trend Alignment : Uses two EMAs for directional bias:
Directional EMA: 55 periods (default)
Execution Trend Guide: 34 periods (default)
Both must align with trade direction.
ATR Risk Management : All risk parameters are expressed in ATR multiples:
Stop Loss: 1.5 × ATR (default)
Take Profit: 3.0 × ATR (default)
Trail Activation: 1.0 × ATR profit required (default)
Trail Distance: 1.5 × ATR behind price (default)
Volume Surge Filter : Optional gate requiring current volume to exceed a multiple of the volume SMA. Default threshold is 1.4× the 20-period volume SMA.
Quality Score Gate : Composite score (0-1) combining:
Structure alignment (0.0-1.0)
Momentum strength (0.0-1.0)
Trend alignment (0.0-1.0)
ATR volatility score (0.0-1.0)
Volume intensity (0.0-1.0)
Default threshold: 0.62. Trades only execute when quality score exceeds this threshold.
Execution Discipline : Trade budgeting system:
Maximum trades per session: 6 (default)
Cooldown bars between entries: 5 (default)
Quality Assurance Console : Real-time monitoring panel displaying:
Structure status (pass/fail)
Momentum confirmation (pass/fail)
Volatility readiness (pass/fail)
Quality score (pass/fail)
Discipline compliance (pass/fail)
Performance metrics (win rate, profit factor)
Net PnL
Certification requires: Win Rate ≥ 40%, Profit Factor ≥ 1.4, Minimum 25 closed trades, and positive net profit.
Integrity Suite : Optional validation panel that audits:
Configuration sanity checks
ATR data readiness
EMA hierarchy validity
Performance realism checks
Strategy Settings
strategy(
title="ChronoPulse MS-MACD Resonance Strategy",
shorttitle="ChronPulse",
overlay=true,
max_labels_count=500,
max_lines_count=500,
initial_capital=100000,
currency=currency.USD,
pyramiding=0,
commission_type=strategy.commission.percent,
commission_value=0.015,
slippage=2,
default_qty_type=strategy.percent_of_equity,
default_qty_value=2.0,
calc_on_order_fills=true,
calc_on_every_tick=true,
process_orders_on_close=true
)
Key Input Parameters
Structure Timeframe : 240 (4H) - Higher timeframe for structure analysis
Structure Pivot Left/Right : 3/3 - Pivot confirmation periods
Structure Break Buffer : 0.15% - Buffer for structure break confirmation
MACD Fast/Slow/Signal : 12/26/9 - Classic MACD parameters
Fusion MACD Fast/Slow/Signal : 8/21/5 - Crypto-tuned MACD parameters
Directional EMA Length : 55 - Primary trend filter
Execution Trend Guide : 34 - Secondary trend filter
ATR Length : 14 - ATR calculation period
ATR Stop Multiplier : 1.5 - Stop loss in ATR units
ATR Target Multiplier : 3.0 - Take profit in ATR units
Trail Activation : 1.0 ATR - Profit required before trailing
Trail Distance : 1.5 ATR - Distance behind price
Volume Threshold : 1.4× - Volume surge multiplier
Quality Threshold : 0.62 - Minimum quality score (0-1)
Max Trades Per Session : 6 - Daily trade limit
Cooldown Bars : 5 - Bars between entries
Win-Rate Target : 40% - Minimum for QA certification
Profit Factor Target : 1.4 - Minimum for QA certification
Minimum Trades for QA : 25 - Required closed trades
Signal Generation Logic
A trade signal is generated when ALL of the following conditions are met:
Higher timeframe structure shows bullish (CHOCH/BOS) or bearish structure break
Both MACD profiles agree on direction (if fusion enabled)
Price is above both EMAs for longs (below for shorts)
ATR data is ready and above minimum threshold
Volume exceeds threshold × SMA (if volume gate enabled)
Quality score ≥ quality threshold
Trade budget available (under max trades per day)
Cooldown period satisfied
Risk Management
Stop loss and take profit are set immediately on entry
Trailing stop activates after 1.0 ATR of profit
Trailing stop maintains 1.5 ATR distance behind highest profit point
Position sizing uses 2% of equity per trade (default)
No pyramiding (single position per direction)
Limitations and Considerations
The strategy requires sufficient historical data for higher timeframe structure analysis
Quality gate may filter out many potential trades, reducing trade frequency
Performance metrics are based on historical backtesting and do not guarantee future results
Commission and slippage assumptions (0.015% + 2 ticks) may vary by broker
The strategy is optimized for trending markets with clear structure breaks
Choppy or ranging markets may produce false signals
Crypto markets may require different parameter tuning than traditional assets
Optimization Notes
The strategy includes several parameters that can be tuned for different market conditions:
Quality Threshold : Lower values (0.50-0.60) allow more trades but may reduce average quality. Higher values (0.70+) are more selective but may miss opportunities.
Structure Timeframe : Use 240 (4H) for intraday trading, Daily for swing trading, Weekly for position trading
Volume Gate : Disable for low-liquidity pairs or when volume data is unreliable
Dual MACD Fusion : Disable for mean-reverting markets where single MACD may be more responsive
Trade Discipline : Adjust max trades and cooldown based on your risk tolerance and market volatility
Non-Repainting Guarantee
All higher timeframe data requests use lookahead=barmerge.lookahead_off to prevent repainting. Pivot detection waits for full confirmation before registering structure breaks. All visual elements (tables, labels) update only on closed bars.
Alerts
Three alert conditions are available:
ChronoPulse Long Setup : Fires when all long entry conditions are met
ChronoPulse Short Setup : Fires when all short entry conditions are met
ChronoPulse QA Certification : Fires when Quality Assurance console reaches CERTIFIED status
Configure alerts with "Once Per Bar Close" delivery to match the non-repainting design.
Visual Elements
Structure Labels : CHOCH↑, CHOCH↓, BOS↑, BOS↓ markers on structure breaks
Directional EMA : Orange line showing trend bias
Trailing Stop Lines : Green (long) and red (short) trailing stop levels
Dashboard Panel : Real-time status display (structure, MACD, ATR, quality, PnL)
QA Console : Quality assurance monitoring panel
Integrity Suite Panel : Optional validation status display
Recommended Usage
Forward test with paper trading before live deployment
Monitor the QA console until it reaches CERTIFIED status
Adjust parameters based on your specific market and timeframe
Respect the trade discipline limits to avoid over-trading
Review quality scores and adjust threshold if needed
Use appropriate commission and slippage settings for your broker
Technical Implementation
The strategy uses Pine Script v6 with the following key features:
Multi-timeframe data requests with lookahead protection
Confirmed pivot detection for structure analysis
Dynamic trailing stop management
Real-time quality score calculation
Trade budgeting and cooldown enforcement
Comprehensive dashboard and monitoring panels
All source code is open and available for review and modification.
Disclaimer
This script is for educational and informational purposes only. It is not intended as financial, investment, or trading advice. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author and TradingView are not responsible for any losses incurred from using this strategy.
VWAP From Pivots Lows and Highs
This script starts automatically VWAP from pivot lows and highs.
Parameter allows you to enable up to 3 VWAP (default).
If you use 3, the VWAP from the last three pivots point will be drawn.
If you use 1, just the last pivot point will be used.
You can also just enable VWAPs starting from pivot lows or highs.
Let me know if there are any problems.
VWolf – Slope GuardOVERVIEW
Slope Guard combines a momentum core (WaveTrend + RSI/MFI + QQE family) with a directional bias (EMA/DEMA and a DEMA-slope filter). Trade direction can be constrained by the Supertrend regime (Normal or Pivot). Risk is managed with ATR-based stops and targets, optional Supertrend-anchored dynamic levels, and a two-stage take-profit that can shift the stop to break-even after the first partial. The strategy supports explicit Backtest and Forward-test windows and adapts certain thresholds by market type (Forex vs. Stocks).
RECOMMENDED USE
Markets: Forex and equities; use Market Type to properly scale the DEMA-slope gate.
Timeframes: M15–H4 for intraday-swing and H1–D1 for slower swing; avoid ultra-low TFs without tightening ADX/QQE.
Assets: Instruments with persistent trends and orderly pullbacks; avoid flat ranges without sufficient ADX.
Strengths
Multi-layer confluence: trend bias + momentum + regime + strength.
Flexible risk engine: ATR vs. Supertrend anchoring, staged exits, and automatic break-even.
Clean research workflow: separated Backtest and Forward-test windows.
Precautions
Structural latency: Pivot-based constructs confirm with delay; validate with Forward-test.
Filter interaction: QQE Strict + ADX + WT zero-line can become overly selective; calibrate by asset/TF.
Overfitting risk: Prefer simple, portable parameter sets and validate across symbols/TFs.
CONCLUSION
Slope Guard is a “trend + momentum” framework with risk control at its core. By enforcing a baseline bias, validating momentum with the Vuman composite, and offering ATR or Supertrend-anchored exits—plus staged profits and break-even shifts—it seeks to capture the core of directional swings while compressing drawdowns. Keep testing windows isolated, start with moderate filters (QQE Normal, ADX ~20–25), and only add stricter gates (WT zero-line, DEMA slope) once they demonstrably improve stability without starving signals.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Shadow PulseOVERVIEW
The Trend Momentum Breakout Strategy is a rule-based trading system designed to identify high-probability entries in trending markets using a combination of trend confirmation, momentum filtering, and precise trigger conditions. The strategy is suitable for intermediate to advanced traders who prefer mechanical systems with clear entry/exit logic and configurable risk management options.
At its core, this strategy seeks to enter pullbacks within strong trends, capitalizing on momentum continuation after brief pauses in price movement. By integrating multiple moving averages (MAs) for trend validation, ADX (Average Directional Index) as a strength filter, and Stochastic RSI as an entry trigger, the strategy filters out weak trends and avoids overextended market conditions. Exit logic is based on a customizable fixed stop-loss (SL) and take-profit (TP) framework, with optional dynamic risk-reduction mechanisms powered by the Supertrend indicator.
This strategy is designed to perform best in clearly trending markets and is especially effective in avoiding false breakouts or choppy sideways action thanks to its ADX-based filtering. It can be deployed across a variety of asset classes, including forex, stocks, cryptocurrencies, and indices, and is optimized for intra-day to swing trading timeframes.
RECOMMENDED USE
This strategy is designed to be flexible across multiple markets, but it performs best under certain conditions:
Best Suited For:
Trending markets with clear directional momentum.
High-volume instruments that avoid erratic price action.
Assets with intraday volatility and swing patterns.
Recommended Asset Classes:
Forex pairs (e.g., EUR/USD, GBP/JPY)
Cryptocurrencies (e.g., BTC/USD, ETH/USDT)
Major indices (e.g., S&P 500, NASDAQ, DAX)
Large-cap stocks (especially those with consistent liquidity)
Suggested Timeframes:
15-minute to 1-hour charts for intraday setups.
4-hour and daily charts for swing trading.
Lower timeframes (1–5 min) may generate too much noise unless fine-tuned.
Market Conditions to Avoid:
Ranging or sideways markets with low ADX values.
Assets with irregular price structures or low liquidity.
News-heavy periods with unpredictable price spikes.
CONCLUSION
This strategy stands out for its robust and modular approach to trend-following trading, offering a high level of customization while maintaining clear logic and structural discipline in entries and exits. By combining three distinct layers of confirmation—trend identification (via configurable moving averages), trend strength validation (via the DMI filter), and timing (via the Stochastic RSI trigger)—it aims to reduce noise and increase the probability of entering trades with directional bias and momentum on its side.
Its flexibility is one of its strongest points: users can tailor the strategy to fit various trading styles and market conditions. Whether the trader prefers conservative setups using only the slowest moving average, or more aggressive entries requiring full alignment of fast, medium, and slow MAs, the system adjusts accordingly. Likewise, exit management offers both static and dynamic methods—such as ATR-based stop losses, Supertrend-based adaptive exits, and partial profit-taking mechanisms—allowing risk to be managed with precision.
This makes the strategy particularly suitable for trend-driven markets, such as major currency pairs, indices, or volatile stocks that demonstrate clear directional moves. It is not ideal for sideways or choppy markets, where multiple filters may reduce the number of trades or result in whipsaws.
From a practical standpoint, the strategy also incorporates real-world trading mechanics, like time-based filters and account risk control, which elevate it from a purely theoretical model to a more execution-ready system.
In summary, this is a well-structured, modular trend strategy ideal for intermediate to advanced traders who want to maintain control over their system parameters while still benefiting from layered signal confirmation. With proper calibration, it has the potential to become a reliable tool in any trader’s arsenal—particularly in markets where trends emerge clearly and sustainably.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Raptor ClawOVERVIEW
The 'VWolf - Raptor Claw' is a straightforward scalping strategy designed for high-frequency trades based on the Stochastic RSI indicator. It focuses exclusively on identifying potential trend reversals through stochastic cross signals in extreme zones, without the need for additional confirmations. This makes it highly responsive to market movements, capturing rapid price shifts while maintaining simplicity.
This strategy is best suited for highly liquid and volatile markets like forex, indices, and major cryptocurrencies, where quick momentum shifts are common. It is ideal for experienced scalpers who prioritize fast entries and exits, but it can also be adapted for swing trading in lower timeframes.
Entry Conditions:
Long Entry:Stochastic RSI crosses above the oversold threshold (typically 20), indicating a potential bullish reversal.
Short Entry:Stochastic RSI crosses below the overbought threshold (typically 80), indicating a potential bearish reversal.
Exit Conditions:
Stop Loss: Set at the minimum (for longs) or maximum (for shorts) within a configurable lookback window to reduce risk.
Take Profit: Defined by a risk-reward ratio (RRR) input to optimize potential gains relative to risk.
CONCLUSION
The 'VWolf - Raptor Claw' strategy is perfect for traders seeking a simple yet aggressive approach to the markets. It capitalizes on sharp momentum shifts in extreme zones, relying on precise stop loss and take profit settings to capture rapid profits while minimizing risk. This approach is highly effective in high-volatility environments where quick decision-making is essential.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Quantum DriftOVERVIEW
The Quantum Drift strategy is a sophisticated, highly customizable trading approach designed to identify market entries and exits by leveraging multiple technical indicators. The strategy uniquely combines the Dynamic Exponential Moving Average (DEMA), QQE indicators, Volume Oscillator, and Hull Moving Average (HULL), enabling precise detection of trend direction, momentum shifts, and volatility adjustments. It stands out due to its adaptability across different market conditions by allowing significant user customization through various input parameters.
RECOMMENDED USE
Markets: Ideal for Forex and Stocks due to the strategy's volatility-sensitive and trend-following nature.
Timeframes: Best suited for medium to higher timeframes (15m, 1H, 4H), where clearer trend signals and less noise occur, enhancing strategy reliability.
CONCLUSION
The Quantum Drift strategy is tailored for intermediate to advanced traders seeking a versatile and adaptive system. Its strength lies in combining momentum, volatility, and trend-following components, providing robust entry and exit signals. However, its effectiveness relies significantly on accurate parameter tuning by traders familiar with the underlying indicators and market behavior.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf – Pivot VumanSkewOVERVIEW
This strategy blends a lightweight trend scaffold (EMA/DEMA) with a skew-of-volatility filter and VuManchu/WaveTrend momentum signals. It’s designed to participate only when trending structure, momentum alignment, and volatility asymmetry converge, while delegating execution management to either a standard SuperTrend or a Pivot-based SuperTrend. Position sizing is risk‑based, with optional two‑step profit taking and automatic stop movement once price confirms in favor.
RECOMMENDED USE
Markets: Designed for Forex and equities, and readily adaptable to indices or liquid futures.
Timeframes: Performs best from 15m to 4h where momentum and trend layers both matter; daily can be used for confirmation/context.
Conditions: Trending or range‑expansion phases with clear volatility asymmetry. Avoid extremely compressed sessions unless thresholds are relaxed.
Strengths
Multi‑layer confluence (trend + skew + momentum) reduces random signals.
Dual SuperTrend modes provide flexible trailing and regime control.
Built‑in hygiene (ADX/DMI, lockout after loss, ATR gap) curbs over‑trading.
Risk‑% sizing and two‑step exits support consistent, plan‑driven execution.
Precautions
Over‑tight thresholds can lead to missed opportunities; start from defaults and tune gradually.
High sensitivity in momentum settings may overfit to a single instrument/timeframe.
In very low volatility, ATR‑gap or skew filters may block entries—consider adaptive thresholds.
CONCLUSION
VWolf – Pivot VumanSkew is a disciplined trend‑participation strategy that waits for directional structure, volatility asymmetry, and synchronized momentum before acting. Its execution layer—selectable between Normal and Pivot SuperTrend—keeps management pragmatic: scale out early when appropriate, trail intelligently, and defend capital with volatility‑aware stops. For users building a diversified playbook, Pivot VumanSkew serves as a trend‑continuation workhorse that can be tightened for precision or relaxed for higher participation depending on the market’s rhythm.
VWolf – Momentum TwinOVERVIEW
VWolf – Momentum Twin is designed to identify high-probability momentum reversals emerging from overbought or oversold market conditions. It employs a double confirmation from the Stochastic RSI oscillator, optionally filtered by trend and directional movement conditions, before executing trades.
The strategy emphasizes consistent risk management by scaling stop-loss and take-profit targets according to market volatility (ATR), and it provides advanced position management features such as partial profit-taking and automated stop-loss adjustments.
RECOMMENDED USE
Markets: Major FX pairs, index futures, large-cap stocks, and top-volume cryptocurrencies.
Timeframes: Best suited for M15–H4; adaptable for swing trading on daily charts.
Trader Profile: Traders who value structured, volatility-adjusted momentum reversal setups.
Strengths:
Double confirmation filters out many false signals.
Multiple filter options allow strategic flexibility.
ATR scaling maintains consistent risk across assets.
Trade management tools improve adaptability in dynamic markets.
Precautions:
May produce fewer trades in strong one-direction trends.
Over-filtering can reduce trade frequency.
Requires validation across instruments and timeframes before deployment.
CONCLUSION
The VWolf – Momentum Twin offers a disciplined framework for capturing momentum reversals while preserving flexibility through its customizable filters and risk controls. Its double confirmation logic filters out a significant portion of false reversals, while ATR-based scaling ensures consistency across varying market conditions. The optional trade management features, including partial profit-taking and automatic stop adjustments, allow the strategy to adapt to both trending and ranging environments. This makes it a versatile tool for traders who value structured entries, robust risk control, and adaptable management in a variety of markets and timeframes.
VWolf – Hull VectorOVERVIEW
VWolf – Hull Vector is a momentum-driven trend strategy centered on the Hull Moving Average (HMA) angle. It layers optional confirmations from EMA/DEMA alignment, DMI/ADX strength, and Supertrend triggers to filter lower-quality entries and improve trade quality.
Risk is controlled through capital-based position sizing, ATR-anchored stops and targets, and dynamic trade management (partial exits and stop movement). The strategy supports Backtest and Forwardtest modes with configurable date ranges, and a market profile toggle (Forex vs. Stocks) to adjust internal scaling for price behavior.
RECOMMENDED USE
Markets: Major Forex pairs, index CFDs/futures, and liquid stocks with clean trend legs.
Styles: Intraday and swing applications where momentum continuation is common.
Volatility Regimes: Performs best in trending or expanding-volatility environments; consider tightening thresholds in choppy phases.
Workflow Tips:Start with HMA angle + ST trigger only; then layer DEMA and DMI/ADX if you need more selectivity.
Use Forwardtest dates to simulate out-of-sample performance after tuning Backtest parameters.
Re-evaluate angle thresholds when switching between Forex and Stocks modes.
Strengths
Clear momentum core (HMA angle) with optional, orthogonal filters (trend alignment, strength, trigger).
Robust risk tooling: ATR/ST stops, two-step profits, and capital-based sizing.
Testing discipline: Native Backtest/Forwardtest scoping supports walk-forward validation.
Broad portability: Works across instruments thanks to market-aware scaling.
Precautions
Over-filtering risk: Enabling all gates simultaneously may under-trade; calibrate selectivity to your timeframe.
Sideways markets: Expect more whipsaws when slope hovers near zero; raise angle threshold or rely more on ADX gating.
Overfitting hazard: Tune on one regime, then verify with Forwardtest windows and alternative markets/timeframes.
VWolf – Hulk StrikeOVERVIEW
VWolf – Hullk Strike is a dynamic trend-following strategy designed to capture pullbacks within established moves. It combines a configurable Moving Average (HULL, EMA, SMA, or DEMA) trend filter with DMI/ADX confirmation and a Stochastic RSI timing trigger. Risk is managed through ATR- or Supertrend-based stops, optional partial profit-taking, and automatic stop adjustments. The strategy aims to rejoin momentum after controlled retracements while maintaining consistent, quantified risk
RECOMMENDED USE
Markets: Liquid indices, major FX pairs, large-cap equities, high-liquidity crypto pairs.
Timeframes: M15 to D1 (stricter filters for lower timeframes, looser for higher).
Profiles: Traders seeking structured trend participation with systematic timing.
Strengths
Highly flexible trend engine adaptable to multiple markets.
Dual confirmation reduces false signals during pullbacks.
Risk-first design with multiple stop models and partial exits.
Precautions
Over-filtering may reduce trade frequency and miss fast continuations.
Under-filtering may increase whipsaw risk in choppy markets.
Backtest vs forward-test differences if date/session filters are inconsistent.
CONCLUSION
VWolf – Hullk Strike is designed to capture the “second leg” of a trend after a controlled retracement. With configurable MA strictness, DMI/ADX strength filters, and precise Stoch RSI timing, it enhances selectivity while keeping responsiveness. Its stop/target framework—anchored stops, proportional targets, partial exits, and dynamic stop moves—offers disciplined risk control and upside preservation.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf – EquinoxOVERVIEW
The VWolf – Equinox strategy integrates multiple technical filters, skew deviation logic, and advanced momentum indicators to identify high-probability trend continuation and reversal setups. Built upon the Vumanchu framework, this strategy applies filters such as EMA, DEMA, Supertrend, QQE, ADX/DMI, and customized skew thresholds. It combines these with divergence detection, volatility conditions, and risk-managed trade execution for dynamic adaptability across market conditions.
Its architecture is designed to provide flexibility for both backtesting and forward testing periods, while allowing traders to fine-tune entry confirmations and risk management tools based on their preferred market or timeframe.
RECOMMENDED USE
Markets: Forex, equities, and potentially crypto markets due to skew/volatility adaptability.
Timeframes: Works best on intraday (15m–1H) and swing-trading (4H–1D) horizons.
Trader Profile: Suited for intermediate to advanced traders who value multiple confirmation layers and dynamic risk management.
Strengths:
Robust filter system reduces false signals.
Flexible exit strategies with dynamic profit-taking.
Adaptability across different assets and timeframes.
Precautions:
Complexity may overwhelm beginners; careful parameter tuning is recommended.
Too many active filters can reduce signal frequency, potentially missing opportunities.
Divergence and skew thresholds require calibration to each market’s volatility regime.
CONCLUSION
The VWolf – Equinox stands out as one of the most comprehensive strategies in the VWolf library, combining skew deviation with a wide array of technical filters. Its layered confirmation system reduces noise and improves reliability across volatile markets. While powerful, its effectiveness depends on thoughtful parameter selection and disciplined risk management. This makes it a strong candidate for experienced traders seeking depth, adaptability, and dynamic trade control.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Basic EdgeOVERVIEW
VWolf - Basic Edge is a clean and accessible crossover strategy built on the core principle of moving average convergence. Designed for simplicity and ease of use, it allows traders to select from multiple types of moving averages—including EMA, SMA, HULL, and DEMA—and defines entry points strictly based on the crossover of two user-defined MAs.
This strategy is ideal for traders seeking a minimal, no-frills trend-following system with flexible exit conditions. Upon crossover in the selected direction (e.g., fast MA crossing above slow MA for a long entry), the strategy opens a trade and then manages the exit based on the user’s chosen method:
Signal-Based Exit:Trades are closed on the opposite crossover signal (e.g., long is exited when the fast MA crosses below the slow MA).
Fixed SL/TP Exit:The trade is closed based on fixed Stop Loss and Take Profit levels.Both SL and TP values are customizable via the strategy’s input settings.Once either the TP or SL is reached, the position is exited.
Additional filters such as date ranges and session times are available for backtesting control, but no extra indicators are used—staying true to the “basic edge” philosophy. This strategy works well as a starting framework for beginners or as a reliable, lightweight system for experienced traders wanting clean, rule-based entries and exits.
RECOMMENDED FOR
- Beginner to intermediate traders who want a transparent and easy-to-follow system.
- Traders looking to understand or build upon classic moving average crossover logic.
- Users who want a customizable but uncluttered strategy framework.
🌍 Markets & Instruments:
Well-suited for liquid and trending markets, including:Major forex pairs
Stock indices
Commodities (e.g., gold, oil)
Cryptocurrencies with stable trends (e.g., BTC, ETH)
⏱ Recommended Timeframes:
Performs best on higher intraday or swing trading timeframes, such as:15m, 1h, 4h, and 1D
Avoid low-timeframe noise (e.g., 1m, 3m) unless paired with strict filters or volatility controls.
FOR MORE INFORMATION VISIT vwolftrading.com
Non-Repainting Dynamic EMA SystemDynamic EMA System - Detailed Explanation
Overview
This indicator creates four adaptive Exponential Moving Averages (EMAs) that automatically adjust their periods based on current market conditions. Unlike traditional fixed-period EMAs, these lines dynamically become faster or slower to better match the market's behavior.
Core Components
1. Base EMA Lengths (Starting Points)
EMA 1: Base period of 10 (fastest)
EMA 2: Base period of 20 (fast-medium)
EMA 3: Base period of 30 (medium)
EMA 4: Base period of 200 (trend identifier)
These base values are not fixed—they serve as starting points that get multiplied by various market condition factors.
Market Analysis Features
The indicator analyzes 12 different market characteristics to understand current conditions:
Technical Indicators Used:
RSI (Relative Strength Index)
Measures momentum and overbought/oversold conditions
Normalized to 0-1 scale
ADX (Average Directional Index)
Measures trend strength
Higher values = stronger trends
Bollinger Bands Position
Shows where price sits relative to volatility bands
Indicates potential reversals or breakouts
VWAP (Volume Weighted Average Price)
Institutional trading benchmark
Signals if price is above/below average weighted price
Ichimoku Cloud
Japanese indicator showing support/resistance
Tenkan-Kijun relationship indicates trend direction
TRAMA (Triangular Moving Average)
Advanced adaptive moving average
Responds to genuine price movements
Volume Analysis
Compares current volume to 20-period average
Higher volume = more significant moves
ATR-Based Volatility
Weighted by volume for accuracy
Adjusts EMAs to market speed
Shannon Entropy
Measures market randomness vs. order
High entropy = choppy; Low entropy = trending
Price Correlation (Short-term)
How consistent price movements are
Detects momentum shifts
Price Correlation (Long-term)
Broader trend consistency
Confirms regime stability
Volume Strength
Normalized volume ratio
Validates price movements
How Length Adaptation Works
Market Regimes Identified:
The system identifies 4 distinct market conditions based on the 12 features:
Regime 1 (Green): Calm, ranging market → Shorter EMAs (more responsive)
Regime 2 (Blue): Strong trending market → Medium-length EMAs (balance speed/noise)
Regime 3 (Red): High volatility/choppy → Longer EMAs (filter noise)
Regime 4 (Gray): Transitional/neutral → Moderate EMAs (adaptive middle ground)
Adaptation Formula:
Each EMA length is calculated as:
Final Length = Base Length × Regime Multiplier × Volatility Adjustment × Momentum Adjustment × Entropy Adjustment
Where:
Regime Multiplier: 0.3x to 2.5x depending on market type
Volatility Adjustment: Increases length during high volatility (filters noise)
Momentum Adjustment: Based on RSI - extreme readings adjust sensitivity
Entropy Adjustment: Lower entropy (trending) = tighter EMAs
Key Adaptive Features
1. Volatility Response
When market volatility increases:
EMAs lengthen automatically to avoid whipsaws
Calculated using ATR weighted by volume
2. Volume Integration
Higher volume makes the system:
React faster to price changes
Increase learning rate
Trust the current move more
3. Correlation Analysis
Short-term correlation: Detects immediate momentum
Long-term correlation: Confirms overall trend stability
Adjusts EMA sensitivity accordingly
4. Entropy Monitoring
Measures market "disorder"
Trending markets → Tighter EMAs (follow trend)
Choppy markets → Wider EMAs (reduce noise)
Non-Repainting Design
Critical Safety Features:
Confirmed Data Only
All calculations use close , high , low , etc.
Current bar data is only used if barstate.isconfirmed
Locked Updates
EMA lengths only change when bar closes
Variables prefixed with confirmed_ store locked values
No Look-Ahead
System learns from past bars only
Future data cannot influence current values
Historical Consistency
Once a bar closes, its EMA values never change
Alerts and signals are reliable
Visual Interpretation
Background Colors:
Green: Calm/ranging market (Regime 1)
Blue: Strong trend (Regime 2)
Red: High volatility/choppy (Regime 3)
Gray: Transitional state (Regime 4)
Color transparency indicates confidence:
Solid color = High confidence in regime identification
Faint color = Lower confidence, potential transition
EMA Lines:
Red EMA (fastest): Short-term momentum
Orange EMA: Medium-term trend
Yellow EMA: Intermediate trend confirmation
Blue EMA: Long-term trend direction
Information Dashboard
The top-right table displays:
Metric Purpose
Regime Strength How strongly current conditions match the identified regime (0-1)
Silhouette Score Quality of regime identification (>0.5 = Excellent, >0.2 = Good)
EMA Values & Lengths Current price level and adaptive period for each EMA
Vol Volatility Volume-weighted volatility measure
Entropy Market randomness level (0 = trending, 1 = random)
Volume Strength Current volume relative to average
Learning Rate How quickly the system adapts (higher = faster adaptation)
Trading Applications
Trend Following:
EMAs aligned in order (1 > 2 > 3 > 4) = Strong uptrend
EMAs aligned reversed = Strong downtrend
Use EMA 4 as major trend filter
Entry Signals:
Fast EMA crosses medium EMA in trend direction
Price pullback to EMA 3 in trending regime
All EMAs converging in ranging regime
Exit Signals:
Fast EMA crosses below medium EMA
Regime change (background color shift)
Silhouette score drops (poor quality)
Regime-Based Strategy:
Green Background: Range trading, fade extremes
Blue Background: Trend following, ride momentum
Red Background: Reduce position size, wait for clarity
Gray Background: Cautious, potential regime shift
Advantages Over Standard EMAs
Automatic Adjustment: No manual tweaking needed for different markets
Context Aware: Understands if market is trending, ranging, or volatile
Volume Integration: Respects institutional involvement
Multi-Factor Analysis: Uses 12 indicators, not just price
Quality Metrics: Silhouette score shows when to trust signals
Non-Repainting: Reliable for backtesting and live trading
Best Practices
Do:
Wait for bar close before acting on signals
Check Silhouette score (>0.2 is reliable)
Use regime color as risk filter
Combine with your trading system
Don't:
Trade against EMA 4 in strong trends
Ignore regime changes
Use in extremely low liquidity
Expect perfection in all conditions
Summary
This is an intelligent, self-adjusting EMA system that reads 12 different market characteristics to automatically optimize its speed. It identifies whether the market is trending, ranging, volatile, or transitional, then adjusts all four EMAs accordingly. The non-repainting design ensures historical accuracy, while the quality metrics (Silhouette score, regime strength) tell you when to trust the signals most.
RSI 14 Cross Up SMA(14) With Volume FiltersUpgrade previous script to show crossover volume strength
RSI 14 Cross Up SMA(14) Within Last 4 BarsMomentum based crossover, seems to be best for swing trades
ATR ZigZag BreakoutATR ZigZag Breakout
This strategy uses my ATR ZigZag indicator (powered by the ZigZagCore library) to scalp breakouts at volatility-filtered highs and lows.
Everyone knows stops cluster around clear swing highs and lows. Breakout traders often pile in there, too. These levels are predictable areas where aggressive orders hit the tape. The idea here is simple:
→ Let ATR ZigZag define clean, volatility-filtered pivots
→ Arm a stop market order at those pivots
→ Join the breakout when the crowd hits the level
The key to greater success in this simple strategy lies in the ZigZag. Because the pivots are filtered by ATR instead of fixed bar counts or fractals, the levels tend to be more meaningful and less noisy.
This approach is especially suited for intraday trading on volatile instruments (e.g., NQ, GC, liquid crypto pairs).
How It Works
1. Pivot detection
The ATR ZigZag uses an ATR-based threshold to confirm swing highs and lows. Only when price has moved far enough in the opposite direction does a pivot become “official.”
2. Candidate breakout level
When a new swing direction is detected and the most recent high/low has not yet been broken in the current leg, the strategy arms a stop market order at that pivot.
• Long candidate → most recent swing high
• Short candidate → most recent swing low
These “candidate trades” are shown as dotted lines.
3. Entry, SL, and TP
If price breaks through the level, the stop order is filled and a bracket is placed:
• Stop loss = ATR × SL multiplier
• Take profit = SL distance × RR multiplier
Once a level has traded, it is not reused in the same swing leg.
4. Cancel & rotate
If the market reverses and forms a new swing in the opposite direction before the level is hit, the pending order is cancelled and a new candidate is considered in the new direction.
Additional Features
• Optional session filter for backtesting specific trading hours
MMBS HkOrE FX [V5.11]The Multi-Model Bias System (MMBS) is a composite bias-detection framework that evaluates price behavior using three independent analytical engines: structural confirmation, normalized volatility expansion, and momentum velocity dynamics. The goal of the tool is not to generate trading signals, but to identify the dominant directional bias through multi-factor validation.
🔧 1. Structural Recognition Engine (Multi-Pivot Confirmation)
MMBS identifies market structure using a multi-confirmation pivot model rather than a single swing point.
A Swing High/Low is only confirmed when several consecutive pivot conditions align.
This reduces noise and produces a “stable structure map.”
A bullish bias requires sequential higher-low and higher-high confirmations; bearish bias requires the opposite.
Because this model relies on progressive confirmation, it behaves differently from common fractal-based structure indicators.
This approach allows the bias to remain stable during minor price fluctuations.
🔧 2. Normalized Volatility Boundary (Modified ATR Model)
Volatility is processed using a custom ATR-based normalization:
The script calculates a rolling ATR range, then scales it using a smoothing function to prevent extreme expansion.
This produces a volatility boundary line that adapts proportionally to recent market conditions.
When price approaches this boundary while structural strength weakens, the system flags reduced confidence in the existing bias.
This method differs from standard ATR bands because it compresses outlier volatility instead of amplifying it.
🔧 3. Momentum Velocity Engine (Smoothed ROC Filter)
The momentum module measures acceleration rather than raw momentum:
A smoothed Rate-of-Change curve evaluates whether price velocity is supporting or diverging from the current structure.
Deceleration near the volatility boundary is interpreted as potential instability.
No buy/sell signals are generated—momentum is used strictly for bias confidence filtering.
By focusing on velocity shifts instead of momentum direction alone, the system captures early structural weakening.
🔗 How the Components Interact
A directional bias is assigned only when:
Structure confirmation
Volatility normalization
Momentum velocity
are aligned in the same direction.
If any module diverges, MMBS defaults to a neutral (no-bias) state.
This behavior distinguishes it from single-module indicators that rely solely on trend, volatility, or momentum.
📊 Visual Output
Bias Color Bar — shows the dominant directional bias (bullish / bearish / neutral).
Volatility Boundary Line — reflects the normalized ATR range used for stability validation.
Momentum Markers — point to areas where velocity divergence may invalidate the bias.
These components are informational only and do not represent entry or exit signals.
⚙️ User-Adjustable Inputs
Structure Sensitivity — modifies how many pivot confirmations are required.
Volatility Scaling — adjusts ATR normalization strength.
Momentum Smoothing — controls responsiveness to short-term velocity changes.
🔒 Why the Script Is Invite-Only
The script uses custom structural logic, a custom-developed ATR normalization method, and a ROC-based velocity filter that differs from publicly available tools.
Invite-only access is maintained to ensure responsible use and preserve controlled distribution of the multi-factor bias-model framework.
The script does not rely on any publicly available template and integrates multiple independent computational layers, which justifies restricted visibility under TradingView’s policies.
CK: Locked Session H/L + Volume Profile (1m Fixed)The session roadmap every futures trader needs — without the clutter.
This tool automatically locks the previous session’s structure and gives you the five most important institutional levels:
✅ Locked Session High
✅ Locked Session Low
✅ Session POC (Point of Control)
✅ VAH – Value Area High
✅ VAL – Value Area Low
Everything is calculated using 1-minute data only, so your levels are accurate, consistent, and never repaint.
💡 What It Does
Tracks the entire session from the RTH close to the next RTH close.
Builds a volume-by-price profile for that session.
Automatically freezes the session’s:
Highest price
Lowest price
Most-traded price (POC)
70% value area (VAH/VAL)
Plots all levels as clean horizontal lines for today’s trading.
🚀 Why Traders Use This
These 5 levels control most algorithmic and institutional activity.
This indicator shows you exactly where price reacted yesterday, so you can:
Catch retests and bounces with confidence
Avoid trading in the middle of nowhere
Anticipate reversals, breakouts, and liquidity grabs
Build a consistent plan around the same fixed levels every day
TradePulse ProTradepulse is a proprietary trading tool that combines a directional signal engine, a trend-adaptive trailing stop system, and a momentum confirmation oscillator into a unified decision framework. Instead of simply stacking separate indicators on a chart, TradePulse integrates these components into a single rules-based system designed to help traders act with structure rather than emotion by identifying conditions where trend and momentum are aligning.
How It Works:
Directional Signals - TradePulse uses a custom price-average model with ATR-based volatility thresholds to detect transitions between bullish and bearish environments. Buy and Sell markers appear only when price strength and volatility conditions confirm a shift. Reducing noise and late entries.
Trend-Adaptive Trailing Stop - A dynamic trailing system combines smoothed moving averages with ATR expansion logic. As price develops, the trailing level adjusts automatically and target projections update based on symmetry extensions. Helping guide structured exits and trade management.
Momentum Confirmation - A proprietary oscillator blends stochastic positioning with center-of-gravity transformation and dual smoothing. It highlights whether momentum aligns with the directional shift, helping traders avoid weaker setups and focus on higher-quality conditions.
Key Features:
- Clear Buy/Sell transitions based on multi-factor confluence
- Adaptive trailing stop + projected targets for structured management
- Momentum filtering to support higher-quality opportunities
- Sensitivity adjustments to suit different markets & styles
TradePulse is original work protected under invite-only access. It is provided for educational and informational purposes only. Trading involves risk, and signals should always be validated with your own analysis and risk management.
Green to Red Money RailsWhat this indicator does
Green to Red Money Rails (G2R Rails) is a price-action tool that draws dynamic “rails” from recent swing lows and highs. It tracks how support and resistance are shifting so you can see where trend pressure is building or weakening.
Core logic (high level)
Detects pivot lows and stores the last three (L1, L2, L3).
Builds green support “fans”: inner dotted rails L1→L2 and L2→L3, plus a main solid base rail L1→L3.
Detects pivot highs and, when the last high is lower than the previous one, draws a red resistance rail from H2→H3.
Optional labels mark the most recent swing low (“L”) and swing high (“H”).
How to use it
Use the green rails as dynamic support zones for trend-following, pullback entries, or stop placement.
Use the red rail as a visual ceiling in downtrends: breaks above it can signal the end of a sell-off; rejections at it confirm sellers still in control.
Works best on liquid markets and swing-trading timeframes (for example, 1h–1D). Always combine with your own risk management and higher-timeframe context.
This script does not auto-generate signals or manage risk for you; it is a visual framework for reading structure and building your own trading plans.
