SA_ORB_ONR_CLOUD_vwapBandsSIGNAL ARCHITECT™ — ORB / ONR Cloud with VWAP Bands
Optimized for the 15-Minute Timeframe
Overview
The Signal Architect™ ORB / ONR Cloud is a session-structure and probability framework designed to help traders understand where price is statistically compressed, transitioning, or escaping value during the regular trading session.
On the 15-minute chart, this study excels at identifying:
High-probability consolidation zones
Early session directional intent
Fade vs continuation environments
Context for VWAP-based mean reversion or trend extension
Rather than predicting price, the indicator classifies market behavior using time-anchored ranges and volume-weighted statistics.
Core Components (15-Minute Context)
1️⃣ Overnight Range (ONR)
The Overnight Range captures price extremes formed before the regular session opens.
On the 15-minute timeframe, ONR acts as:
A higher-timeframe reference level
A source of institutional liquidity memory
A boundary where early session reactions often occur
2️⃣ Opening Range (ORB)
The Opening Range is defined as the first X minutes after the session open (default: 15 minutes).
On a 15-minute chart:
The ORB often forms entirely within a single candle
It represents initial institutional positioning
It helps differentiate initiative vs responsive behavior
3️⃣ ORB–ONR Cloud (Key Feature)
The Cloud is the overlapping area between the Overnight Range and the Opening Range.
This zone is critical on the 15-minute timeframe because it often represents:
Compressed auction
Balance / indecision
Liquidity absorption
Interpretation:
Price inside the cloud → Higher probability of consolidation, fade, or contraction
Price exiting the cloud → Transition toward expansion or trend resolution
The cloud is not a signal — it is a probability environment.
4️⃣ VWAP with Session-Weighted σ Bands
The study plots VWAP starting from the regular session open, along with true volume-weighted standard deviation bands (±1σ, ±2σ).
On the 15-minute timeframe:
VWAP defines fair value
σ bands help distinguish normal rotation vs statistical extension
Interaction with VWAP while inside the cloud often suggests mean-reverting conditions
Interaction with VWAP after leaving the cloud often confirms trend continuation
5️⃣ Breakout Classification (BRK)
A BRK event occurs when price closes outside BOTH:
The Overnight Range
The Opening Range
On the 15-minute chart:
BRK events often mark session regime changes
They are contextual markers, not entries
Arrows are color-matched to the candle (green candle → green arrow, red candle → red arrow)
To avoid clutter, breakouts can be limited to first-occurrence only.
Probability Layer (15-Minute Edge)
The indicator includes rolling probability calculations to quantify market behavior:
📊 Inside-Cloud Probability
Shows how often price remains inside the ORB–ONR cloud over the selected lookback.
Higher values → balance / compression dominant
Lower values → trend / expansion dominant
📉 Fade / Contraction Probability (Inside Cloud)
When price is inside the cloud, the study measures volatility contraction using ATR behavior.
Higher contraction % → Greater likelihood of rotation or fade
Lower contraction % → Cloud acting as launchpad rather than balance
📈 State Occupancy (5-State Model)
Tracks how price distributes its time across:
Above both ranges
Below both ranges
Inside ORB only
Inside ONR only
Inside the Cloud
This helps traders understand where the market statistically prefers to trade on the 15-minute structure.
Best Use Cases (15-Minute Chart)
✔ Contextual bias for intraday swing trades
✔ Identifying fade vs trend conditions
✔ VWAP-based execution alignment
✔ Avoiding low-probability entries inside compression
✔ Session structure awareness without lower-timeframe noise
What This Indicator Is NOT
❌ Not a buy/sell system
❌ Not predictive
❌ Not a guarantee of outcomes
It is a market structure and probability framework — designed to improve decision quality, not replace risk management.
Recommended Settings (15-Minute)
ORB Length: 15 minutes
VWAP Bands: ±1σ / ±2σ
Probability Lookback: 100–200 bars
Breakout Mode: First-occurrence only
Cloud Enabled: Yes
Risk & Compliance Notice
This tool is provided for educational and informational purposes only.
It does not constitute financial advice, investment recommendations, or trade instructions.
All trading involves risk, including the possible loss of capital.
Standalone Signal - trianchor.gumroad.com
chatgpt.com
chatgpt.com
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NeuraCloud - Ichimoku (Purple Kumo) + Alerts (Minimal)NeuraCloud is a clean, modern interpretation of the Ichimoku Cloud, designed to identify trend direction, market structure, and key support/resistance zones at a glance.
The purple cloud (Kumo) acts as a dynamic trend filter:
• Price above the cloud indicates bullish conditions
• Price below the cloud indicates bearish conditions
• Price inside the cloud signals consolidation or uncertainty
NeuraCloud combines the cloud with Tenkan-sen and Kijun-sen to highlight momentum shifts, pullbacks, and trend continuation opportunities. Built-in alerts notify you of price/cloud breaks, momentum crosses, and cloud flips, helping you stay aligned with high-probability market structure.
Ideal for trend traders, swing traders, and multi-timeframe analysis, NeuraCloud keeps charts clean while delivering clear market context.
Triple Stochastic RSI [XYZ-Trades]Triple Stochastic RSI (original work from XYZ-Trades) with some minor additions to allow user to move table.
Multi Asset & Multi Timeframe Trend DashboardOverview
The Multi-Asset & Multi-Timeframe Trend Dashboard is a comprehensive visual data terminal designed to provide a bird's-eye view of market sentiment across five different assets and seven distinct timeframes simultaneously. By consolidating 10 core technical indicators into a single table, it eliminates the need for "chart hopping" and helps traders identify high-probability trend alignment.
How It Works
The dashboard evaluates each asset based on a Scoring System ($-10$ to $+10$). For every timeframe, the script analyzes the following 10 conditions:
Trend: EMA 20 > EMA 50Macro
Trend: EMA 50 > EMA 200
Position: Price > EMA 200
MACD: MACD Line > Signal Line
MACD Momentum: MACD Histogram > 0
RSI Momentum: RSI(14) > RSI SMA(14)
RSI Level: RSI(14) > 50
Stochastics: Stoch K > D
CCI: Commodity Channel Index > 0
Awesome Oscillator: AO > 0
Visual Logic & Features
Indicator Dots (■): Represent the 10 individual technical conditions. Green indicates a bullish state; Red indicates a bearish state.
Trend Arrows (▲/▼): Displays the aggregate directional bias of a timeframe based on the sum of the 10 dots.
Neutral State (✖): If indicators are split 50/50 (Score of 0), a grey cross is displayed to indicate total market indecision.
"ALL" Column: A macro-summary that aggregates scores across all four primary timeframes.
Volatility Marker (•): A dot appearing next to the symbol name indicates that current ATR is higher than the historical average (user-defined threshold).
Market Status Color: The symbol name background turns Green if the market is currently open and active, and Red if it is closed or stagnant.
Technical Implementation
This script utilizes request.security calls to fetch data across timeframes. To ensure performance and prevent repainting issues, all security calls are handled using the barstate.islast flag to only render the dashboard on the most recent bar.
How to Use
Alignment Trading: Look for "Full House" scenarios where all arrows (15m through Daily) are the same color.
Scalping Bias: Use the "Mini Timeframes" (1m, 3m, 5m) to find entries that align with the higher timeframe trend shown in the main table.
Volatility Filter: Only take trades when the volatility marker (•) is active to ensure there is enough "power" in the move.
Keltner-Aroon-EFI FlowKeltner-Aroon-EFI Flow - |K| |A| |E| |F|
KAE Flow is a quantitative trend-aggregation engine designed to determine the dominant market bias by fusing three distinct market dimensions: Volatility, Trend Strength, and Volume.
This script does not rely on a single metric. Instead, it creates a composite "Flow" score derived from the Daily timeframe to act as a high-level bias filter for intraday or swing trading.
1. The Quantitative Logic (The Engine)
The core of this indicator is the KAE Engine, which polls data from the Daily timeframe (by default) to ensure you are always trading in alignment with the macro trend. It aggregates three logical components:
K (Keltner Channels): Measures Volatility Breakouts.
Logic: Returns bullish if price closes above the Upper Channel, bearish if below the Lower Channel. This captures the expansion phase of price action.
A (Aroon): Measures Trend Age & Strength.
Logic: Returns bullish only if the Aroon Up is > 70 and dominating the Aroon Down. This ensures the trend is not just present, but mathematically strong.
E (Elder’s Force Index): Measures Volume-Weighted Momentum.
Logic: Uses volume pressure to confirm price moves. Positive smoothed force indicates bullish accumulation.
2. Signal Processing (ALMA)
Raw data is noisy. The KAE Flow takes the aggregated raw score from the components above and runs it through an ALMA (Arnaud Legoux Moving Average).
Why ALMA? It offers the best balance between smoothness and responsiveness, removing "false flips" in the trend bias while reacting quickly to genuine reversals.
The Color (The Bias):
Deep Blue: Strong Bullish Flow (KAE Score > 0.1). Look for Long entries .
White: Strong Bearish Flow (KAE Score < -0.1). Look for Short entries.
Gray: Neutral/Transition. Volatility is contracting or the trend is conflicting.
5. Settings & Configuration
Keltner/Aroon/EFI Lengths: Fully customizable to fit different asset classes (Crypto vs. Forex).
Active Smoothing: Toggle ALMA on/off.
Active Components: You can toggle specific engines (K, A, or E) on or off. Default uses Keltner + Aroon for a pure Price/Time analysis.
Risk Warning: This indicator pulls higher-timeframe data (Daily) to color lower-timeframes. While this provides a powerful macro view, be aware that closed candle data is used to prevent repainting issues in real-time.
D_Quant --- Trade With Discipline
S/R-Zones [SouthEast]Autro Support/ Resistance zones, drawn by default on 1 hr timeframe for last 3 months
LogTrend Retest EngineLogTrend Retest Engine (LTRE)
LogTrend Retest Engine (LTRE) is an advanced trend-continuation overlay designed to identify high-probability breakout retests using logarithmic regression , volatility-adjusted deviation bands , and market regime filtering .
Unlike traditional channels or moving averages, LTRE models price behavior in log space , allowing it to adapt naturally to exponential market moves common in crypto, indices, and long-term trends.
🔹 How It Works
Logarithmic Regression Core
Performs linear regression on log-transformed price and time
Produces a structurally accurate trend midline that scales with price growth
Volatility-Adjusted Deviation Bands
Dynamic upper and lower zones based on statistical deviation
ATR weighting expands or contracts bands as volatility changes
Adaptive Lookback (Optional)
Automatically adjusts regression length using volatility pressure
Faster response in high-volatility environments, smoother in consolidation
🔹 Market Regime Detection
LTRE actively filters conditions using:
R² trend strength (trend quality, not just slope)
Volatility compression vs expansion
User-defined minimum trend strength threshold
Signals are disabled during ranging or low-quality conditions .
🔹 Breakout → Retest Signal Logic
LTRE does not chase breakouts.
Signals trigger only when:
1. Price breaks cleanly outside the deviation band
2. Market regime is confirmed as trending
3. Price performs a controlled retest within a user-defined tolerance
BUY
Break above upper band → retest → trend confirmed
SELL
Break below lower band → retest → trend confirmed
This structure is designed to reduce false breakouts and late entries.
🔹 Visual & Projection Tools
Clean midline and deviation bands
Optional filled zones
Optional future trend projection for forward structure planning
On-chart statistics for trend strength and volatility compression
🔹 Best Use Cases
Trend continuation & pullback strategies
Crypto, Forex, Indices, and equities
Works best on 15m and higher timeframes
⚠️ Disclaimer
LTRE is a decision-support tool , not a complete trading system. Always use proper risk management and confirm signals with additional structure, volume, or higher-timeframe context.
Built for traders who wait for structure — not noise.
Quality-Controlled Trend StrategyOverview
This strategy demonstrates a clean, execution-aware trend framework with fully isolated risk management.
Entry conditions and risk logic are intentionally separated so risk parameters can be adjusted without altering signal behavior.
All calculations are evaluated on confirmed bars to ensure backtest behavior reflects real-time execution.
Design intent
Many scripts mix entries and exits in ways that make results fragile or misleading.
This strategy focuses on structural clarity by enforcing:
confirmed-bar logic only
fixed and transparent risk handling
consistent indicator calculations
one position at a time
It is intended as a baseline framework rather than an optimized system.
Trading logic (high level)
Trend context
EMA 50 vs EMA 200 defines directional bias
Entry
Price alignment with EMA 50
RSI used as a momentum confirmation, not as an overbought/oversold signal
Risk management
Stop-loss based on ATR
Fixed risk–reward structure
Risk logic is isolated from entry logic
Editing risk without affecting signals
All stop-loss and take-profit calculations are handled in a dedicated block.
Users can adjust:
ATR length
stop-loss multiplier
risk–reward ratio
without modifying entry conditions.
This allows controlled experimentation while preserving signal integrity.
Usage notes
Results vary by market, timeframe, and volatility conditions.
This script is provided for testing and educational purposes and should be validated across multiple symbols and forward-tested before use in live environments.
Smart Money Flow Cloud [BOSWaves]Smart Money Flow Cloud - Volume-Weighted Trend Detection with Adaptive Volatility Bands
Overview
Smart Money Flow Cloud is a volume flow-aware trend detection system that identifies directional market regimes through money flow analysis, constructing adaptive volatility bands that expand and contract based on institutional pressure intensity.
Instead of relying on traditional moving average crossovers or fixed-width channels, trend direction, band width, and signal generation are determined through volume-weighted money flow calculation, nonlinear flow strength modulation, and volatility-adaptive band construction.
This creates dynamic trend boundaries that reflect actual institutional buying and selling pressure rather than price momentum alone - tightening during periods of weak flow conviction, expanding during strong directional moves, and incorporating flow strength statistics to reveal whether regimes formed under accumulation or distribution conditions.
Price is therefore evaluated relative to adaptive bands anchored at a flow-informed baseline rather than conventional trend-following indicators.
Conceptual Framework
Smart Money Flow Cloud is founded on the principle that sustainable trends emerge where volume-weighted money flow confirms directional price movement rather than where price alone creates patterns.
Traditional trend indicators identify regime changes through price crossovers or slope analysis, which often ignore the underlying volume dynamics that validate or contradict those movements.This framework replaces price-centric logic with flow-driven regime detection informed by actual buying and selling volume.
Three core principles guide the design:
Trend direction should correspond to volume-weighted flow dominance, not price movement alone.
Band width must adapt dynamically to current flow strength and volatility conditions.
Flow intensity context reveals whether regimes formed under conviction or uncertainty.
This shifts trend analysis from static moving averages into adaptive, flow-anchored regime boundaries.
Theoretical Foundation
The indicator combines adaptive baseline smoothing, close location value (CLV) methodology, volume-weighted flow tracking, and nonlinear strength amplification.
A smoothed trend baseline (EMA or ALMA) establishes the core directional reference, while close location value measures where price settled within each bar's range. Volume weighting applies directional magnitude to flow calculation, which accumulates into a normalized money flow ratio. Flow strength undergoes nonlinear power transformation to amplify strong conviction periods and dampen weak flow environments. Average True Range (ATR) provides volatility-responsive band sizing, with final width determined by the interaction between base volatility and flow-modulated multipliers.
Four internal systems operate in tandem:
Adaptive Baseline Engine : Computes smoothed trend reference using either EMA or ALMA methodology with configurable secondary smoothing.
Money Flow Calculation System : Measures volume-weighted directional pressure through CLV analysis and ratio normalization.
Nonlinear Flow Strength Modulation : Applies power transformation to flow intensity, creating dynamic sensitivity scaling.
Volatility-Adaptive Band Construction : Scales band width using ATR measurement combined with flow-strength multipliers that range from minimum (calm) to maximum (strong flow) expansion.
This design allows bands to reflect actual institutional behavior rather than reacting mechanically to price volatility alone.
How It Works
Smart Money Flow Cloud evaluates price through a sequence of flow-aware processes:
Close Location Value (CLV) Calculation : Each bar's closing position within its high-low range is measured, creating a directional bias indicator ranging from -1 (closed at low) to +1 (closed at high).
Volume-Weighted Flow Tracking : CLV is multiplied by bar volume, then accumulated and normalized over a configurable flow window to produce a money flow ratio between -1 and +1.
Flow Smoothing and Strength Extraction : The raw money flow ratio undergoes optional smoothing, then nonlinear power transformation to amplify strong flow periods and compress weak flow environments.
Adaptive Baseline Construction : Price (both open and close) is smoothed using either EMA or ALMA methodology with optional secondary smoothing to create a stable trend reference.
Dynamic Band Sizing : ATR measurement is multiplied by a flow-strength-modulated factor that interpolates between minimum (tight) and maximum (wide) multipliers based on current flow conviction.
Regime Detection and Visualization : Price crossing above the upper band triggers bullish regime, crossing below the lower band triggers bearish regime. The baseline cloud visualizes open-close relationship within the current trend.
Retest Signal Generation : Price touching the baseline from within an established regime generates retest signals with configurable cooldown periods to prevent noise.
Together, these elements form a continuously updating trend framework anchored in volume flow reality.
Interpretation
Smart Money Flow Cloud should be interpreted as flow-confirmed trend boundaries:
Bullish Regime (Blue) : Activated when price crosses above the upper adaptive band, indicating volume-confirmed buying pressure exceeding volatility-adjusted resistance.
Bearish Regime (Red) : Established when price crosses below the lower adaptive band, identifying volume-confirmed selling pressure breaking volatility-adjusted support.
Baseline Cloud : The gap between smoothed open and smoothed close within the baseline visualizes intrabar directional bias - wider clouds indicate stronger intrabar momentum.
Adaptive Band Width : Reflects combined volatility and flow strength - wider bands during high-conviction institutional activity, tighter bands during consolidation or weak flow periods.
Buy/Sell Labels : Appear at regime switches when price crosses from one band to the other, marking potential trend inception points.
Retest Signals (✦) : Diamond markers indicate price touching the baseline within an established regime, often occurring during healthy pullbacks in trending markets.
Trend Strength Gauge : Visual meter displays current regime strength as a percentage, calculated from price position within the active band relative to baseline.
Background Gradient : Optional coloring intensity reflects flow strength magnitude, darkening during high-conviction periods.
Flow strength, band width adaptation, and baseline relationship outweigh isolated price fluctuations.
Signal Logic & Visual Cues
Smart Money Flow Cloud presents three primary interaction signals:
Regime Switch - Buy : Blue "Buy" label appears when price crosses above the upper band after previously being in a bearish regime, suggesting volume-confirmed bullish transition.
Regime Switch - Sell : Red "Sell" label displays when price crosses below the lower band after previously being in a bullish regime, indicating volume-confirmed bearish transition.
Trend Retest : Diamond (✦) markers appear when price touches the baseline within an established regime, with configurable cooldown periods to filter noise.
Alert generation covers regime switches and retest events for systematic monitoring.
Strategy Integration
Smart Money Flow Cloud fits within volume-informed and institutional flow trading approaches:
Flow-Confirmed Entry : Use regime switches as primary trend inception signals where volume validates directional breakouts.
Retest-Based Refinement : Enter on baseline retest signals within established regimes for improved risk-reward positioning during pullbacks.
Band Width Context : Expect wider price swings when bands expand (high flow strength), tighter ranges when bands contract (weak flow).
Baseline Cloud Confirmation : Favor trades where baseline cloud width confirms intrabar momentum alignment with regime direction.
Strength Gauge Filtering : Use trend strength percentage to gauge continuation probability - higher readings suggest stronger institutional conviction.
Multi-Timeframe Regime Alignment : Apply higher-timeframe regime context to filter lower-timeframe entries, taking only setups aligned with dominant flow direction.
Technical Implementation Details
Core Engine : Configurable EMA or ALMA baseline with secondary smoothing
Flow Model : Close Location Value (CLV) with volume weighting and ratio normalization
Strength Transformation : Configurable power function for nonlinear flow amplification
Band Construction : ATR-scaled width with flow-strength-interpolated multipliers
Visualization : Dual-line baseline cloud with gradient fills, regime-colored bands, and embedded strength gauge
Signal Logic : Band crossover detection with baseline retest identification and cooldown management
Performance Profile : Optimized for real-time execution with minimal computational overhead
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-structure regime detection for scalping and intraday reversals
15 - 60 min : Intraday trend identification with flow-validated swings
4H - Daily : Swing and position-level regime analysis with institutional flow context
Suggested Baseline Configuration:
Trend Length : 34
Trend Engine : EMA
Trend Smoothing : 3
Flow Window : 24
Flow Smoothing : 5
Flow Boost : 1.2
ATR Length : 14
Band Tightness (Calm) : 0.9
Band Expansion (Strong Flow) : 2.2
Reset Cooldown : 12
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volume profile, volatility characteristics, and preferred signal frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Bands too wide/frequent whipsaws : Reduce "Band Expansion (Strong Flow)" to limit maximum band width, or increase "Band Tightness (Calm)" to widen minimum bands and reduce noise sensitivity.
Trend baseline too choppy : Increase "Trend Length" for smoother baseline, or increase "Trend Smoothing" for additional filtering.
Flow readings unstable : Increase "Flow Smoothing" to reduce bar-to-bar noise in money flow calculation.
Missing legitimate regime changes : Decrease "Trend Length" for faster baseline response, or reduce "Band Tightness (Calm)" for earlier breakout detection.
Too many retest signals : Increase "Reset Cooldown" to space out retest markers, or disable retest signals entirely if not using pullback entries.
Flow strength not responding : Increase "Flow Boost" (power factor) to amplify strong flow differentiation, or decrease "Flow Window" to emphasize recent volume activity.
Prefer different smoothing characteristics : Switch "Trend Engine" to ALMA and adjust "ALMA Offset" (higher = more recent weighting) and "ALMA Sigma" (higher = smoother) for alternative baseline behavior.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Markets with consistent volume participation and institutional flow
Instruments where volume accurately reflects true liquidity and conviction
Trending environments where flow confirms directional price movement
Mean-reversion strategies using retest signals within established regimes
Reduced Effectiveness:
Extremely low volume environments where flow calculations become unreliable
News-driven or gapped markets with discontinuous volume patterns
Highly manipulated or thinly traded instruments with erratic volume distribution
Ranging markets where price oscillates within bands without conviction
Integration Guidelines
Confluence : Combine with BOSWaves structure, order flow analysis, or traditional volume profile
Flow Validation : Trust regime switches accompanied by strong flow readings and wide band expansion
Context Awareness : Consider whether current market regime matches historical flow patterns
Retest Discipline : Use baseline retest signals as confirmation within trends, not standalone entries
Breach Management : Exit regime-aligned positions when price crosses opposing band with volume confirmation
Disclaimer
Smart Money Flow Cloud is a professional-grade volume flow and trend analysis tool. Results depend on market conditions, volume reliability, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, market context, and comprehensive risk management.
Fibonacci Sequence Grid [BigBeluga]🔵 OVERVIEW
A geometric price mapping tool that projects Fibonacci sequence levels and grid structures from recent price swings to help traders visualize natural expansion and reversion zones.
This indicator overlays Fibonacci-based structures directly on the chart, utilizing both grid projections and horizontal levels based on the classic Fibonacci integer sequence (0, 1, 1, 2, 3, 5, 8, ...). It identifies recent swing highs or lows and builds precision-aligned levels based on the trend direction.
🔵 CONCEPTS
Uses the Fibonacci integer sequence (not ratios) to define distances from the most recent swing point.
Identifies a trend based on EMA cross of fast and slow periods.
Projects two types of Fibonacci tools:
A grid projection from the swing point, displaying multiple sloped levels based on the sequence.
A set of horizontal Fibonacci levels for clean structural references.
Levels can be plotted from either swing low or high depending on the current trend direction.
Adjustable “Size” inputs control spacing between levels for better price alignment.
Lookback period defines how far the script searches for recent swing extremes.
🔵 FEATURES
Fibonacci Grid Projection:
Draws two mirrored Fibonacci grids—one expanding away from the swing high/low, the other converging toward price.
Swing-Based Trend Detection:
Uses a fast/slow EMA crossover to determine trend direction and reference swing points for projections.
Fibonacci Sequence Levels:
Displays horizontal levels based on the Fibonacci number sequence (0, 1, 2, 3, 5, 8, 13, 21...) for natural price targets.
Dynamic Labels and Coloring:
Each level is labeled with its sequence value and colored based on trend direction (e.g., red = downtrend, green = uptrend).
Both grids and levels can be toggled on/off independently.
Sizing controls allow tighter or looser clustering of levels depending on chart scale.
🔵 HOW TO USE
Enable Fibonacci Grid to visualize price expansion zones during impulsive trends.
Use Fibonacci Levels as horizontal support/resistance or target zones.
A label below price means the current trend is up and levels are projected from swing low.
A label above price means trend is down and levels are projected from swing high.
Adjust “Size” input to fit grid/level projection to your preferred chart scale or instrument volatility.
Use in confluence with price action, trend indicators, or volume tools for layered trading decisions.
🔵 CONCLUSION
Fibonacci Sequence Grid reimagines Fibonacci analysis using whole-number spacing from natural math progressions. Whether used for projecting grid-based expansions or horizontal support/resistance zones, it provides a powerful and intuitive structure to trade within. Perfect for traders who rely on symmetry, market geometry, and mathematically consistent levels.
Price Line with SMA & StdDev ChannelIndicator Synopsis
This indicator is a stand-alone price-based oscillator that mirrors market price action in a separate pane, allowing traders to analyze structure, momentum, and volatility without the visual noise of the main chart.
The indicator plots a raw price line as its core component, creating a one-to-one representation of price movement detached from candlesticks. A 14-period Simple Moving Average (SMA) smooths this price line to help identify short-term momentum shifts and directional bias.
A volatility channel is constructed around a 20-period SMA, which serves as the channel’s equilibrium (mean). The upper and lower channel boundaries are positioned one standard deviation above and below the 20-period SMA, dynamically adapting to changes in market volatility.
This structure allows traders to:
Identify mean reversion opportunities when price stretches beyond the channel
Observe trend strength and continuation when price holds above or below the channel midline
Detect volatility expansion and contraction through channel width
Use the SMA 14 as a momentum filter against the broader 20-period mean
By isolating price behavior into a separate pane, the indicator provides a clear, uncluttered framework for reading price dynamics, making it suitable for discretionary analysis, momentum confirmation, and volatility-based trade planning.
Opening Range {basic}Introduction
Opening range {basic} is a clean and reliable indicator designed to help traders visualize the opening range of a trading session with minimal setup and visual clutter.
This version focuses on the core components of opening range analysis, making it ideal for traders who want a simple, effective framework for identifying early-session structure across futures, forex and crypto markets.
Description
The indicator automatically calculates the opening range high, low and midpoint over a user-defined opening window (5m, 15m, 30m or 60m) within a selected trading session (default: NY session).
During the opening range window, the indicator dynamically tracks price to form the range. Once the opening range is complete, the high, low and midpoint are extended forward for the remainder of the session, providing clear reference levels that can be used for bias, mean reversion or breakout-based decision making.
A shaded fill highlights the opening range area, with an optional size display showing the total range in price units. Styling and logic are intentionally simplified to keep the chart clean and easy to interpret.
Features
Configurable opening range length
Choose between 5m, 15m, 30m or 60m opening ranges.
Session-based calculation
Opening range is calculated only within the selected trading session.
Opening range levels
Opening range high, low and midpoint.
Range fill & size display
Shaded fill between the opening range high and low.
Text showing total opening range size.
Clean, minimal design
Fixed line styles and thickness for clarity.
Dark and light theme support.
Minimal settings for fast, intuitive use.
Optimized performance
Designed for intraday timeframes compatible with the selected opening range length.
Terms & Conditions
This indicator is provided for educational and informational purposes only and does not constitute financial advice.
Trading involves risk and past performance is not indicative of future results.
The user assumes full responsibility for any trading decisions made using this indicator.
EMA BBEMA BB is a chart overlay indicator that combines EMA 9, EMA 20, SMA 50, SMA 200, and VWAP with Bollinger Bands to visualize trend direction and volatility.
It highlights volatility squeeze zones by comparing Bollinger Bands with ATR, helping traders spot consolidation phases that often precede strong price moves. Designed for quick trend confirmation, support/resistance awareness, and breakout setups.
Orion Time Matrix | ICT Macros [by AK]ORION TIME MATRIX | ICT MACRO SUITE
The Orion Time Matrix is a precision timing instrument designed to decipher the algorithmic "Heartbeat" and the timing of institutional order flow in US Index Futures markets, specifically Nasdaq (NQ) and S&P 500 (ES).
Inspired by the "Time & Price" teachings of Michael J. Huddleston (The Inner Circle Trader), this tool maps out the specific time windows where algorithms seek liquidity and price delivery is most efficient.
Adaptive Log Trend Zones + Retest SignalsAdaptive Log Trend Zones + Retest Signals
Adaptive Log Trend Zones is a trend-following overlay built to identify high-probability breakout retests in strong market conditions. It combines logarithmic regression , volatility-adaptive behavior , and ATR-based trend zones to help traders stay aligned with dominant momentum while avoiding chop.
🔹 Core Features
Logarithmic Regression Midline
Uses linear regression on log price to better handle exponential market moves
Produces smoother, more realistic trend structure on higher timeframes
Volatility-Adaptive Lookback
Automatically expands or contracts the regression length based on ATR volatility
Reacts faster in high volatility, smoother in consolidation
Dynamic Trend Zones
Upper and lower bands are ATR-adjusted and trend-colored
Optional future projection for visual trend guidance
Breakout → Retest Signal Logic
Detects clean breakouts beyond the trend zone
Waits for a controlled pullback (retest) before signaling
Signals only trigger when trend strength is confirmed
Trend Quality Filter
Internal regime detection filters out low-quality, sideways conditions
Uses slope strength and volatility compression to validate entries
🔹 Signals
BUY : Bullish breakout followed by a valid retest in a trending regime
SELL : Bearish breakout followed by a valid retest in a trending regime
Signals are designed for trend continuation , not mean reversion.
🔹 Best Use Cases
Crypto, Forex, and Index markets
Higher timeframes (15m+ recommended)
Trend continuation and pullback strategies
⚠️ Notes
This indicator is not a standalone trading system . Always use proper risk management and confirm signals with structure, volume, or higher-timeframe context.
Designed for traders who prefer structure, patience, and momentum alignment.
COT + SMI Dual Strategy (Rev/Trend)I use this script to test whether stochastic COT report filtering for trade direction makes a difference or not for forex.
It seems it does! Feel free to test and comment. I am always happy to see to be proven wrong.
EMA Angle Average by Eric ValerianoThis indicator determines market direction by calculating the angle of an exponential moving average and smoothing that angle over several bars. By averaging the EMA’s slope, it reduces noise and clearly classifies the market as bullish, bearish, or neutral based on trend strength rather than short term price fluctuations.
It is best used as a trend filter to confirm direction, avoid choppy conditions, and add context to entries based on other signals such as pullbacks, breakouts, or momentum setups.
Pulsar Heatmap CVD/OBV [by Oberlunar]Pulsar Heatmap CVD/OBV is a flow/price-consensus dashboard that turns OBV, CVD and their combination blend into a compact “heatmap + bias/signal” view, with optional main-chart candle coloring and HUD overlays.
What it shows
The panel is split into 3 horizontal lanes (OBV / CVD / COMBO). Each lane is further split into two halves:
Flow half: the normalized OBV/CVD/COMBO component (either per-bar Delta or Cumulative series).
PriceΔ half: the normalized divergence between price and the lane (price unit − flow unit), highlighting when price moves with or against the flow proxy.
Colors use intensity-based transparency so you can quickly spot pressure, compression, and disagreement between lanes.
Core engines
Normalization: Z-Score→tanh, Z-Score→clamp, MinMax, or None (unit range ≈ ).
Bias engine (6 halves): builds a directional BIAS from the six components (OBV/CVD/COMBO × Flow/PriceΔ), with optional hysteresis to reduce flicker.
Signal engine: triggers LONG/SHORT only on full alignment (all 6 halves agree), with confirm-bars and optional sticky behavior.
ROC/Acceleration layers: optional impulse context (ROC + ACC) to gate signals and/or boost bias strength when momentum is supportive.
AST filter: a strict directional filter combining volatility regime, BB expansion/contraction, MTF RSI prior and Kalman-smoothed evidence. When AST is directional, it can block opposite signals to enforce coherence.
Visual tools
Bias/Signal bands: top/bottom bands render BIAS strength and SIGNAL state; yellow highlights indicate disagreement/blocked states.
Candle colouring (main chart): optionally colours chart candles from LaneScore / Bias / Signal / Bias+Signal (uses overlay drawing where supported).
Signal labels: optional LONG/SHORT markers (with “better price than last shown” logic).
Triangle HUD: right-side geometric HUD summarising OBV/CVD/COMBO consensus + disagreement cues.
Timed Exhaustion / Absorption table: compact state machine that flags momentum exhaustion and absorption-like conditions using tight range + ROC/ACC behaviour.
How to use
Start with Lane data = Delta for faster microstructure timing; switch to Cumulative for macro context.
Choose a normalisation that fits your symbol’s volatility (ZScore→tanh is usually stable).
Read BIAS as the current dominant direction/strength; treat SIGNAL as the strict “all lanes aligned” confirmation.
If you want stricter coherence, keep the AST filter enabled (it is integrated by design and blocks opposite-direction signals when directional).
Setup 1 — Long Signal (Clean Alignment + Impulse)
In this example, Pulsar Heatmap transitions into a clear long setup when the system prints a LONG SIGNAL. The key idea is simple: the indicator does not enter on “bias” alone. It waits for full alignment across the internal lanes, optionally reinforced by the ROC/Acceleration impulse layer, and only then does it confirm a signal on a closed bar (Safe Mode)
Setup 2 — Short Signal After Compression (Absorption → Release)
In this screenshot, the short trade idea is not coming from “red candles” alone, but from a very specific sequence: the heatmap shows a shift into bearish alignment, the system prints a SHORT SIGNAL, and the timed module confirms that the market was in a tight range while sell pressure started to dominate.
Setup 3 — Neutral State (Stand-By Zone, No Trade Yet)
In the following screenshot, Pulsar Heatmap is doing something very important: it is clearly saying NEUTRAL 0%. Even if, visually, price could “look” like it might resume upward, the indicator is not providing a directional edge yet.
If you are already short, treat DISAGREE as a signal to take profit, tighten the stop, or scale out.
Setup 4 — When similar conditions return
Setup 4 — Impulse + Exhaustion conditions
In this screenshot, you’re basically seeing a “timing warning” configuration. Price prints a sharp bearish extension, but Pulsar Heatmap is not presenting it as a clean continuation setup: the center read is NEUTRAL 0%, while the timed engine shows both Absorption = SHORT and Exhaustion = SHORT. That combination often means: the downside pressure was real, but the move is already in a late/fragile phase (good for managing an existing short, not for opening a new one).
This tool uses available volume data from your data provider and approximates flow via OBV/CVD-style logic; results can differ across symbols/brokers and sessions. This script is for educational/analytical purposes and is not financial advice.
by Oberlunar 👁️ ⭐
EDUVEST Lorentzian ClassificationEDUVEST Lorentzian Classification - Machine Learning Signal Detection
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█ ORIGINALITY
This indicator enhances the original Lorentzian Classification concept by jdehorty with EduVest's visual modifications and alert system integration. The core innovation is using Lorentzian distance instead of Euclidean distance for k-NN classification, providing more robust pattern recognition in financial markets.
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█ WHAT IT DOES
- Generates BUY/SELL signals using machine learning classification
- Displays kernel regression estimate for trend visualization
- Shows prediction values on each bar
- Provides trade statistics (Win Rate, W/L Ratio)
- Includes multiple filter options (Volatility, Regime, ADX, EMA, SMA)
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█ HOW IT WORKS
【Lorentzian Distance Calculation】
Unlike Euclidean distance, Lorentzian distance uses logarithmic transformation:
d = Σ log(1 + |xi - yi|)
This provides:
- Better handling of outliers
- More stable distance measurements
- Reduced sensitivity to extreme values
【Feature Engineering】
The classifier uses up to 5 configurable features:
- RSI (Relative Strength Index)
- WT (WaveTrend)
- CCI (Commodity Channel Index)
- ADX (Average Directional Index)
Each feature is normalized using the n_rsi, n_wt, n_cci, or n_adx functions.
【k-Nearest Neighbors Classification】
1. Calculate Lorentzian distance between current bar and historical bars
2. Find k nearest neighbors (default: 8)
3. Sum predictions from neighbors
4. Generate signal based on prediction sum (>0 = Long, <0 = Short)
【Kernel Regression】
Uses Rational Quadratic kernel for smooth trend estimation:
- Lookback Window: 8
- Relative Weighting: 8
- Regression Level: 25
【Filters】
- Volatility Filter: Filters signals during extreme volatility
- Regime Filter: Identifies market regime using threshold
- ADX Filter: Confirms trend strength
- EMA/SMA Filter: Trend direction confirmation
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 15M, 1H, 4H, Daily
- Neighbors Count: 8 (default)
- Feature Count: 5 for comprehensive analysis
【Signal Interpretation】
- Green BUY label: Long entry signal
- Red SELL label: Short entry signal
- Bar colors: Green (bullish) / Red (bearish) prediction strength
【Trade Statistics Panel】
- Winrate: Historical win percentage
- Trades: Total (Wins|Losses)
- WL Ratio: Win/Loss ratio
- Early Signal Flips: Premature signal changes
【Filter Recommendations】
- Enable Volatility Filter for ranging markets
- Enable Regime Filter for trend confirmation
- Use EMA Filter (200) for higher timeframes
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█ CREDITS
Original Lorentzian Classification concept and MLExtensions library by jdehorty.
Enhanced with visual modifications and alert integration by EduVest.
License: Mozilla Public License 2.0
DEMA MACD BUY signal confirmationDEMA MACD – Trend Continuation Signals
Okay I made this script and wrote this description using AI. I was inspired by the HAP MACD indicator so I made signal confirmation indicator based on that.
This indicator is a momentum-based signal tool built around a DEMA MACD model.
It is designed to help identify potential continuation entries within an existing trend.
Important notes
This indicator works best in clear uptrend conditions.
It is not suitable for consolidation or downtrend markets.
Higher timeframes (Daily / Weekly) generally provide more reliable signals than lower timeframes.
Signals
BUY
Indicates a potential entry in the direction of the current trend.
SELL
Indicates an exit from the previous BUY.
This is not a short or sell-to-open signal.
Usage
Use this tool as a confirmation, not as a standalone decision maker.
Always consider overall market context and basic price structure.
Risk management is essential.
This indicator is shared for educational purposes and reflects one possible approach to trend continuation trading.
