VWAP Fibonacci S&R with Bell CurveThis indicator is a sophisticated trading tool that combines three powerful technical analysis concepts to identify high-probability trading opportunities. Let me break down how it works:
Core Components:
1. VWAP (Volume Weighted Average Price)
Calculates the average price weighted by volume over a specified period
Acts as a dynamic support/resistance level that institutions often use
Can reset daily, weekly, or monthly depending on your trading timeframe
The yellow line on your chart represents the current VWAP
2. Bell Curve Probability Analysis
Measures how far the current price deviates from the VWAP in statistical terms
Calculates a Z-score (standard deviations away from the mean)
Creates probability bands around the VWAP based on price volatility
The theory: extreme deviations from VWAP tend to revert back to the mean
3. Fibonacci Retracement Levels
Uses recent highs and lows to calculate key Fibonacci levels (38.2%, 50%, 61.8%)
These levels often act as support and resistance zones
Combined with VWAP analysis for confluence trading
How the Signals Work:
BUY Signals (Green arrows below candles)
Generated when either condition is met:
Mean Reversion Buy: Price is below VWAP + high probability of reversion + extreme statistical deviation
Fibonacci Support Buy: Price is above VWAP + near key Fibonacci support levels (38.2% or 50%)
SELL Signals (Red arrows above candles)
Generated when either condition is met:
Mean Reversion Sell: Price is above VWAP + high probability of reversion + extreme statistical deviation
Fibonacci Resistance Sell: Price is below VWAP + near key Fibonacci resistance levels (61.8% or 50%)
Visual Elements
Yellow Line: Main VWAP
Blue Bands: Probability zones based on standard deviation
Orange/White/Purple Lines: Key Fibonacci levels (38.2%, 50%, 61.8%)
Yellow Background: High probability mean reversion zones
⚠ Symbol: Extreme deviation warning (Z-score > 2.5)
The Information Table
Shows real-time statistics:
VWAP: Current VWAP value
Distance: How far price is from VWAP (percentage)
Z-Score: Statistical measure of deviation (>2 is significant)
Reversion %: Probability of mean reversion
Fib 50%: Key Fibonacci midpoint level
Status: Current signal state
Trading Logic
The indicator works on the principle that:
Extreme deviations from VWAP are unsustainable and tend to revert
Fibonacci levels provide natural support/resistance zones
Volume confirmation ensures the move has institutional backing
Statistical probability helps time entries when odds are favorable
Best Use Cases
Scalping: Quick mean reversion trades when price gets too far from VWAP
Swing Trading: Using Fibonacci levels with VWAP for longer-term positions
Risk Management: Avoiding trades when probability is low
Confluence Trading: Waiting for multiple signals to align
Statistics
Eigenvector Centrality Drift (ECD) - Market State Network What is Eigenvector Centrality Drift (ECD)?
Eigenvector Centrality Drift (ECD) is a groundbreaking indicator that applies concepts from network science to financial markets. Instead of viewing price as a simple series, ECD models the market as a dynamic network of “micro-states”—distinct combinations of price, volatility, and volume. By tracking how the influence of these states changes over time, ECD helps you spot regime shifts and transitions in market character before they become obvious in price.
This is not another moving average or momentum oscillator. ECD is inspired by eigenvector centrality—a measure of influence in network theory—and adapts it to the world of price action, volatility, and volume. It’s about understanding which market states are “in control” and when that control is about to change.
Theoretical Foundation
Network Science: In complex systems, nodes (states) and edges (transitions) form a network. Eigenvector centrality measures how influential a node is, not just by its direct connections, but by the influence of the nodes it connects to.
Market Micro-States: Each bar is classified into a “state” based on price change, volatility, and volume. The market transitions between these states, forming a network of possible regimes.
Centrality Drift: By tracking the centrality (influence) of the current state, and how it changes (drifts) over time, ECD highlights when the market’s “center of gravity” is shifting—often a precursor to major moves or regime changes.
How ECD Works
State Classification: Each bar is assigned to one of N market micro-states, based on a weighted combination of normalized price change, volatility, and volume.
Transition Matrix: Over a rolling window, ECD tracks how often the market transitions from each state to every other state, forming a transition probability matrix.
Centrality Calculation: Using a simplified eigenvector approach, ECD calculates the “influence” score for each state, reflecting how central it is to the network of recent market behavior.
Centrality Drift: The indicator tracks the Z-score of the change in centrality for the current state. Rapid increases or decreases, or a shift in the dominant state, signal a potential regime shift.
Dominant State: ECD also highlights which state currently has the highest influence, providing insight into the prevailing market character.
Inputs:
🌐 Market State Configuration
Number of Market States (n_states, default 6): Number of distinct micro-states to track.
3–4: Simple (Up/Down/Sideways)
5–6: Balanced (recommended)
7–9: Complex, more nuanced
Price Change Weight (price_weight, default 0.4):
How much price movement defines a state. Higher = more directional.
Volatility Weight (vol_weight, default 0.3):
How much volatility defines a state. Higher = more regime focus.
Volume Weight (volume_weight, default 0.3):
How much volume defines a state. Higher = more participation focus.
🔗 Network Analysis
Transition Matrix Window (transition_window, default 50): Lookback for building the state transition matrix.
Shorter: Adapts quickly
Longer: More stable
Influence Decay Factor (influence_decay, default 0.85): How much influence propagates through the network.
Higher: Distant transitions matter more
Lower: Only immediate transitions matter
Drift Detection Sensitivity (drift_sensitivity, default 1.5): Z-score threshold for significant centrality drift.
Lower: More signals
Higher: Only major shifts
🎨 Visualization
Show Network Visualization (show_network, default true): Background color and effects based on network structure.
Show Centrality Score (show_centrality, default true): Plots the current state’s centrality measure.
Show Drift Indicator (show_drift, default true): Plots the centrality drift Z-score.
Show State Map (show_state_map, default true): Dashboard showing all state centralities and which is dominant.
Color Scheme (color_scheme, default "Quantum"):
“Quantum”: Cyan/Magenta
“Neural”: Green/Blue
“Plasma”: Yellow/Pink
“Matrix”: Green/Black
Color Schemes
Dynamic gradients reflect the current state’s centrality and drift, using your chosen color palette.
Background network effect: The more central the current state, the more intense the background.
Centrality and drift lines: Color-coded for clarity and regime shift detection.
Visual Logic
Centrality Score Line: Plots the influence of the current state, with glow for emphasis.
Drift Indicator: Histogram of centrality drift Z-score, green for positive, red for negative.
Threshold Lines: Dotted lines mark the drift sensitivity threshold for regime shift alerts.
State Map Dashboard: Top-right panel shows all state centralities, highlights the current and dominant state, and visualizes influence with bars.
Information Panel: Bottom-left panel summarizes current state, centrality, dominant state, drift Z-score, and regime shift status.
How to Use ECD
Centrality Score: High = current state is highly influential; low = state is peripheral.
Drift Z-Score:
Large positive/negative = rapid change in influence, regime shift likely.
Near zero = stable network, no major shift.
Dominant State: The state with the highest centrality is “in control” of the market’s transitions.
State Map: Use to see which states are rising or falling in influence.
Tips:
Use fewer states for simple markets, more for nuanced analysis.
Watch for drift Z-score crossing the threshold—these are your regime shift signals.
Combine with your own system for confirmation.
Alerts:
ECD Regime Shift: Significant centrality drift detected—potential regime change.
ECD State Change: Market state transition occurred.
ECD Dominance Shift: Dominant market state has changed.
Originality & Usefulness
ECD is not a mashup or rehash of standard indicators. It is a novel application of network science and eigenvector centrality to market microstructure, providing a new lens for understanding regime shifts and market transitions. The state network, centrality drift, and dashboard are unique to this script. ECD is designed for anticipation, not confirmation—helping you see the market’s “center of gravity” shift before price action makes it obvious.
Chart Info
Script Name: Eigenvector Centrality Drift (ECD) – Market State Network
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
See the market as a network. Anticipate the shift in influence.
— Dskyz , for DAFE Trading Systems
H4 Swing Grade Checklist English V.1✅ H4 Swing Grade Checklist – Auto Grading for Smart Money Setups
This script helps manual traders assess the quality of a Smart Money swing trade setup by checking 7 key criteria. The system assigns a grade (A+, A, A−, or B) based on how many and which checklist items are met.
📋 Checklist Items (7 total):
✅ Sweep occurs within 4 candles
✅ MSS (strong break candle)
✅ Entry is placed outside the wick of the sweep
✅ FVG is fresh (not previously used)
✅ FVG overlaps Fibonacci 0.705 level
✅ FVG lies within Premium or Discount zone
✅ Entry is placed at 0.705 Fibonacci retracement
🏅 Grading Criteria:
A+ → All 7 checklist items are satisfied
A → Only missing #5 (FVG Overlap with 0.705)
A− → Only missing #4 (FVG Fresh)
B → Only missing #2 (MSS – clear break of structure)
– → Any other combinations / fewer than 6 conditions met
⚙️ Features:
Toggle visibility with one click
Fixed display in top-right or bottom-right of the chart
Color-coded grading logic (Green, Yellow, Orange, Blue)
Clear checklist feedback for trade journaling or evaluation
🚀 Ideal For:
ICT / Smart Money traders
Prop firm evaluations
Swing trade quality control
Information Asymmetry Gradient (IAG) What is the Information Asymmetry Gradient (IAG)?
The Information Asymmetry Gradient (IAG) is a unique market regime and imbalance detector that quantifies the subtle, directional “information flow” in price and volume. Inspired by information theory and market microstructure, IAG is designed to help traders spot the early buildup of conviction or surprise—the kind of hidden imbalance that often precedes major price moves.
Unlike traditional volume or momentum indicators, IAG focuses on the efficiency and directionality of information transfer: how much “informational energy” is being revealed by up-moves versus down-moves, normalized by price movement. It’s not just about net flow, but about the quality and asymmetry of that flow.
Theoretical Foundation
Information Asymmetry: Markets move when new information is revealed. If one side (buyers or sellers) is consistently more “informationally efficient” per unit of price change, an imbalance is building—even if price hasn’t moved much yet.
Gradient: By tracking the rate of change (gradient) between fast and slow information flows, IAG highlights when a subtle imbalance is accelerating.
Volatility of Asymmetry: Sudden spikes in the volatility of information asymmetry often signal regime uncertainty or the approach of a “surprise” move.
How IAG Works
Directional Information Content: For each bar, IAG estimates the “information per unit of price change” for both up-moves and down-moves, using volume and price action.
Asymmetry Calculation: Computes the difference (or ratio) between up and down information content, revealing directional bias.
Gradient Detection: Calculates both a fast and slow EMA of the asymmetry, then measures their difference (the “gradient”), normalized as a Z-score.
Volatility of Asymmetry: Tracks the standard deviation of asymmetry over a rolling window, with Z-score normalization to spot “information shocks.”
Flow Strength: Quantifies the conviction of the current information flow on a 0–100 scale.
Regime Detection: Flags “extreme” asymmetry, “building” flow, and “high volatility” states.
Inputs:
🌌 Core Asymmetry Parameters
Fast Information Period (short_len, default 8): EMA period for detecting immediate information flow changes.
5–8: Scalping (1–5min)
8–12: Day trading (15min–1hr)
12–20: Swing trading (4hr+)
Slow Information Period (long_len, default 34): EMA period for baseline information context. Should be 3–5x fast period.
Default (34): Fibonacci number, stable for most assets.
Gradient Smoothing (gradient_smooth, default 3): Smooths the gradient calculation.
1–2: Raw, responsive
3–5: Balanced
6–10: Very smooth
📊 Asymmetry Method
Calculation Mode (calc_mode, default "Weighted"):
“Simple”: Basic volume split by direction
“Weighted”: Volume × price movement (default, most robust)
“Logarithmic”: Log-scaled for large moves
Use Ratio (show_ratio, default false):
“Difference”: UpInfo – DownInfo (additive)
“Ratio”: UpInfo / DownInfo (multiplicative, better for comparing volatility regimes)
🌊 Volatility Analysis
Volatility Window (stdev_len, default 21): Lookback for measuring asymmetry volatility.
Volatility Alert Level (vol_threshold, default 1.5): Z-score threshold for volatility alerts.
🎨 Visual Settings
Color Theme (color_theme, default "Starry Night"):
Van Gogh-inspired palettes:
“Starry Night”: Deep blues and yellows
“Sunflowers”: Warm yellows and browns
“Café Terrace”: Night blues and warm lights
“Wheat Field”: Golden and sky blue
Show Swirl Effects (show_swirls, default true): Adds swirling background to visualize information turbulence.
Show Signal Stars (show_stars, default true): Star markers at significant asymmetry points.
Show Info Dashboard (show_dashboard, default true): Top-right panel with current metrics and market state.
Show Flow Visualization (show_flow, default true): Main gradient line with artistic effects.
Color Schemes
Dynamic color gradients adapt to both the direction and intensity of the information gradient, using Van Gogh-inspired palettes for visual clarity and artistic flair.
Glow and aura effects: The main line is layered with glows for depth and to highlight strong signals.
Swirl background: Visualizes the “turbulence” of information flow, darker and more intense as flow strength and volatility rise.
Visual Logic
Main Gradient Line: Plots the normalized information gradient (Z-score), color-coded by direction and intensity.
Glow/Aura: Multiple layers for visual depth and to highlight strong signals.
Threshold Zones: Dotted lines and filled areas mark “Building” and “Extreme” asymmetry zones.
Volatility Ribbon: Area plot of volatility Z-score, highlighting information shocks.
Signal Stars: Circular markers at each “Extreme” event, color-coded for bullish/bearish; cross markers for volatility spikes.
Dashboard: Top-right panel shows current status (Extreme, Building, High Volatility, Balanced), gradient value, flow strength, information balance, and volatility status.
Trading Guide: Bottom-left panel explains all states and how to interpret them.
How to Use IAG
🌟 EXTREME: Major information imbalance—potential for explosive move or reversal.
🌙 BUILDING: Asymmetry is forming—watch for a breakout or trend acceleration.
🌪️ HIGH VOLATILITY: Information flow is unstable—expect regime uncertainty or “surprise” moves.
☁️ BALANCED: No clear bias—market is in equilibrium.
Positive Gradient: Bullish information flow (buyers have the edge).
Negative Gradient: Bearish information flow (sellers have the edge).
Flow >66%: Strong conviction—crowd is acting in unison.
Volatility Spike: Regime uncertainty—be alert for sudden moves.
Tips:
- Use lower periods for scalping, higher for swing trading.
- “Weighted” mode is most robust for most assets.
- Combine with price action or your own system for confirmation.
- Works on all assets and timeframes—tune to your style.
Alerts
IAG Extreme Asymmetry: Extreme information asymmetry detected.
IAG Building Flow: Information flow building.
IAG High Volatility: Information volatility spike.
IAG Bullish/Bearish Extreme: Directional extreme detected.
Originality & Usefulness
IAG is not a mashup of existing indicators. It is a novel approach to quantifying the “surprise” or “conviction” element in market moves, focusing on the efficiency and directionality of information transfer per unit of price change. The multi-layered color logic, artistic visual effects, and regime dashboard are unique to this script. IAG is designed for anticipation, not confirmation—helping you see subtle imbalances before they become obvious in price.
Chart Info
Script Name: Information Asymmetry Gradient (IAG) – Starry Night
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
multi-tf standard devs [keypoems]Multi-Timeframe Standard Deviations Levels
A visual map of “how far is too far” across any three higher time-frames.
1. What it does
This script plots dynamic price “rails” built from standard deviation (StDev)—the same math that underpins the bell curve—on up to three higher-time-frames (HTFs) at once.
• It measures the volatility of intraday open-to-close increments, reaching back as far as 5000 bars (≈ 20 years on daily data).
• Each HTF can be extended to the next session or truncated at session close for tidy dashboards.
• Lines can be mirrored so you see symmetric positive/negative bands, and optional background fills shade the “probability cone.”
Because ≈ 68 % of moves live inside ±1 StDev, ≈ 95 % inside ±2, and ≈ 99.7 % inside ±3, the plot instantly shows when price is statistically stretched or compressed.
3. Key settings
Higher Time-Frame #1-3 Turn each HTF on/off, pick the interval (anything from 1 min to 1 year), and decide whether lines should extend into the next period.
Show levels for last X days Keep your chart clean by limiting how many historical sessions are displayed (1-50).
Based on last X periods Length of the StDev sample. Long look-backs (e.g. 5 000) iron-out day-to-day noise; short look-backs make the bands flex with recent volatility.
Fib Settings Toggle each multiple, line thickness/style/colour, label size, whether to print the numeric level, the live price, the HTF label, and whether to tint the background (choose your own opacity).
4. Under-the-hood notes
StDev is calculated on (close – open) / open rather than absolute prices, making the band width scale-agnostic.
Watch for tests of ±1:
Momentum traders ride the breakout with a target at the next band.
Mean-reversion traders wait for the first stall candle and trade back to zero line or VWAP.
Bottom line: Multi-Timeframe Standard-Deviations turns raw volatility math into an intuitive “price terrain map,” helping you instantly judge whether a move is ordinary, stretched, or extreme—across the time-frames that matter to you.
Original code by fadizeidan and stats by NQStats's ProbableChris.
Bullish Volume AnomalyAnomaly is designed to spot hidden bullish accumulation before price actually breaks out, by blending a trend-aware volume measure with a volatility-adjusted price channel. Here’s how it works:
First, it runs a simple ATR-based zigzag to identify the current swing direction. Volume is then signed (+ for up-trends, – for down-trends) and cumulatively summed. By converting that cumulative signed volume into a z-score over the past 480 bars, we get a sense of when buying or selling pressure is unusually strong relative to its own history.
At the same time, price itself is normalized into a z-score over the same 480-bar window, and its change over that period is also tracked. These two measures—volume z-score (s) and price z-score (p)—are compared, and the indicator looks for moments when s outpaces p by at least two standard deviations (s – p > 2), while price momentum change remains low (c < 1) and the net volume is positive (s > 0). That combination flags instances where heavy buying is taking place but price hasn’t yet reacted.
To define a dynamic trading zone, it plots a 288-bar EMA of price as the middle band (t2), and builds upper and lower bands around it using the average close-to-open range multiplied by a user-set factor. The lower band (t1) sits beneath the EMA by that volatility-based margin. A signal fires only when the bar’s high stays below t1—meaning price is still “sleeping” under the lower volatility boundary even as bullish volume builds up.
Together, these filters home in on anomalies: strong, trend-aligned volume surges that outstrip price movement, occurring while price sits below its lower volatility band. In practice, that often marks early accumulation before a breakout. You can tweak the ATR length and multiplier for the zigzag, as well as the channel period and range factor, to suit different markets or timeframes.
Normalized DXY+Custom USD Index (DXY+) – Normalized Dollar Strength with Bitcoin, Gold, and Yuan.
This custom USD strength index replicates the structure of the official U.S. Dollar Index (DXY), while expanding it to include modern financial assets such as Bitcoin (BTC), Ethereum (ETH), gold (XAU), and the Chinese yuan (CNY).
Weights for the core fiat currencies (EUR, JPY, GBP, CAD, SEK, CHF) follow the official ICE DXY methodology. Additional components are weighted proportionally based on their estimated global economic influence.
The index is normalized from its initial valid data point, meaning it starts at 100 on the first day all asset inputs are available. From that point forward, it tracks the relative strength of the U.S. dollar against this expanded basket.
This provides a more comprehensive and modernized view of the dollar's strength—not only against traditional fiat currencies, but also in the context of rising decentralized assets and non-Western trade power.
HGDA Hany Ghazy Digital Analytics area zone'sIndicator Name: HGDA Hany Ghazy Digital Analytics area zones
Description:
This indicator plots several key price zones based on the highest high and lowest low over a user-defined lookback period.
The plotted zones represent dynamic support and resistance levels calculated using specific ratios of the price range (High - Low), as follows:
- Zone 1 (Light Red): Represents an upper resistance zone.
- Zone 2 (Medium Green): Represents a medium support zone.
- Zone 3 (Dark Red): Represents a lower resistance zone.
- Zone 4 (Dark Green): Represents a strong support zone.
Additionally, the indicator plots a yellow "Zero" line representing the midpoint price of the selected period, serving as a balance point for price action.
This indicator is ideal for identifying the overall market trend, as prices typically move from the upper resistance zones (light red) downwards to the end of the wave in the lower zones (dark green). This helps traders better understand wave nature and direction.
Usage:
- The colored zones assist in identifying potential reversal or continuation areas.
- These zones can be used to plan entries, exits, and risk management.
- Default lookback period is 20 bars, adjustable in the settings to suit the timeframe.
Notes:
- This indicator relies on historical price data and does not guarantee market predictions.
- It is recommended to combine it with other indicators and analytical tools for improved trading decisions.
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Developed by Hany Ghazy Digital Analytics (HGDA).
Custom USD IndexThis is a modernized, expanded version of the U.S. Dollar Index (DXY), designed to provide a more accurate representation of the dollar’s global strength in today’s diversified economy.
Unlike the traditional DXY, which excludes major players like China and entirely omits real-world stores of value, this custom index (DXY+) includes:
Fiat Currencies (78.3% total weight):
EUR, JPY, GBP, CAD, AUD, CHF, and CNY — equally weighted to reflect the global currency landscape.
Gold (17.5%):
Gold (XAUUSD) is included as a traditional reserve asset and inflation hedge, acknowledging its continued monetary relevance.
Cryptocurrencies (2.8% total weight):
Bitcoin (BTC) and Ethereum (ETH) represent the emerging digital monetary layer.
The index rises when the U.S. dollar strengthens relative to this blended basket, and falls when the dollar weakens against it. This is ideal for traders, economists, and macro analysts seeking a more inclusive and up-to-date measure of dollar performance.
Float, Daily % Change & Short %This TradingView Pine Script displays a compact table on your chart showing four key metrics for any stock:
📊 What It Shows:
Float – Number of publicly available shares, formatted in K/M/B.
Daily % Change – Price change from yesterday’s close to the current price.
Intraday % Change – Price change from today’s open to the current price.
Short Volume % – Estimated short volume as a percentage of total daily volume.
⚙️ How to Use:
Add the script to your TradingView chart.
Choose table size and screen position from the settings panel.
The values update in real-time on the latest candle only, so they stay out of the way but always visible.
Ideal for momentum traders, short float hunters, and day traders who need quick access to real-time float, price action, and short volume stats.
SOFR Spread (proxy: FEDFUNDS - US03MY)📊 SOFR Spread (Proxy: FEDFUNDS - US03MY) – Monitoring USD Money Market Liquidity
In 2008, the spread exhibits a sharp vertical spike, signaling a severe liquidity dislocation: investors rushed into short-term U.S. Treasuries, pushing their yields down dramatically, while the FEDFUNDS rate remained relatively high.
This behavior indicates extreme systemic stress in the interbank lending market, preceding massive Federal Reserve interventions such as rate cuts, emergency liquidity operations, and the launch of quantitative easing (QE).
Description:
This indicator plots the spread between the Effective Federal Funds Rate (FEDFUNDS) and the 3-Month US Treasury Bill yield (US03MY), used here as a proxy for the SOFR spread.
It serves as a simple yet powerful tool to detect liquidity dislocations and stress signals in the US short-term funding markets.
Interpretation:
🔴 Spread > 0.20% → Possible liquidity stress: elevated repo rates, cash shortage, interbank distrust.
🟡 Spread ≈ 0% → Normal market conditions, balanced liquidity.
🟢 Spread < 0% → Excess liquidity: strong demand for T-Bills, “flight to safety”, or distortion due to expansionary monetary policy.
Ideal for:
Monitoring Fed policy impact
Anticipating market-wide liquidity squeezes
Correlation with DXY, SPX, VIX, MOVE Index, and risk sentiment
🧠 Note: As SOFR is not directly available on TradingView, FEDFUNDS is used as a reliable proxy, closely tracking the same trends in most macro conditions.
LANZ Strategy 2.0 [Backtest]🔷 LANZ Strategy 2.0 — Structural Breakout Logic with Dynamic Swing Protection
LANZ Strategy 2.0 is a precision-focused backtesting system built for intraday traders who rely on structural confirmations before the London session to guide directional bias. This tool uses smart swing detection, risk-defined position sizing, and strict time-based execution to simulate real trading conditions with clarity and control.
🧠 Core Components:
Structural Confirmation (Trend & BoS): Detects trend direction and break of structure (BoS) using a three-swing logic, aligning trade entries with valid structural movement.
Time-Based Execution: Trades are triggered exclusively at 02:00 a.m. New York time, ensuring disciplined and repeatable intraday testing.
Swing-Based SL Models: Traders can select between three stop-loss protection types:
First Swing: Most recent structural level
Second Swing: Prior level
Full Coverage: All recent swing levels + configurable pip buffer
Dynamic TP Calculation: Take-Profit is projected as a risk-based multiple (RR), fully adjustable via input.
Capital-Based Risk Management: Risk is defined as a percentage of a fixed account size (e.g., $100 per trade from $10,000), and lot size is automatically calculated based on SL distance.
Fallback Entry Logic: If structural breakout is present but trend is not confirmed, a secondary entry is triggered.
End-of-Session Management: Any open trades are automatically closed at 11:45 a.m. NY time, with optional manual labeling or review.
📊 Visual Features (Optional in Indicator Version):
(Note: Visuals apply to the indicator version of LANZ 2.0, not this backtest script)
Swing level labels (1st, 2nd) and dynamic SL/TP lines.
Real-time session coloring for clarity: Pre-London, Entry Window, and NY Close.
Outcome labels: +RR, -RR, or net % at close.
Auto-cleanup of previous drawings for a clean chart per session.
⚙️ How It Works:
Detects last trend and BoS using swing logic before 02:00 a.m. NY.
At 02:00 a.m., evaluates directional bias and executes BUY or SELL if confirmed.
Applies selected SL logic (1st, 2nd, or full swing protection).
Sets TP based on the RR multiplier.
Closes the trade either on SL, TP, or at 11:45 a.m. NY manually.
🔔 Alerts:
Time-of-day alert at 02:00 a.m. NY to monitor execution.
Can be extended to cover SL/TP triggers or new BoS events.
📝 Notes:
Designed for backtesting precision and discretionary decision-making.
Ideal for Forex pairs, indices, or assets active during the London session.
Fully customizable: session timing, swing logic, SL buffer, and RR.
👤 Credits:
Strategy built by @rau_u_lanz using Pine Script v6, combining structural logic, capital-based risk control, and London-session timing in a backtest-ready framework for traders who demand accuracy and structure.
Statistical Pairs Trading IndicatorZ-Score Stat Trading — Statistical Pairs Trading Indicator
📊🔗
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What is it?
Z-Score Stat Trading is a powerful indicator for statistical pairs trading and quantitative analysis of two correlated assets.
It calculates the Z-Score of the log-price spread between any two symbols you choose, providing both long-term and short-term Z-Score signals.
You’ll also see real-time correlation, volatility, spread, and the number of long/short signals in a handy on-chart table!
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How to Use 🛠️
1. Add the indicator to your chart.
2. Select two assets (symbols) to analyze in the settings.
3. Watch the Z-Score plots (blue and orange lines) and threshold levels (+2, -2 by default).
4. Check the info table for:
- Correlation
- Volatility
- Spread
- Number of long (NL) and short (NS) signals in the last 1000 bars
5. Set up alerts for signal generation or threshold crossings if you want to be notified automatically.
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Trading Strategy 💡
- This indicator is designed for statistical arbitrage (mean reversion) strategies.
- Long Signal (🟢):
When both Z-Scores drop below the negative threshold (e.g., -2), a long signal is generated.
→ Buy Symbol A, Sell Symbol B, expecting the spread to revert to the mean.
- Short Signal (🔴):
When both Z-Scores rise above the positive threshold (e.g., +2), a short signal is generated.
→ Sell Symbol A, Buy Symbol B, again expecting mean reversion.
- The info table helps you quickly assess the frequency of signals and the current statistical relationship between your chosen assets.
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Best Practices & Warnings 🚦
- Avoid high leverage! Pairs trading can be risky, especially during periods of divergence. Use conservative position sizing.
- Check for cointegration: Before using this indicator, make sure both assets are cointegrated or have a strong historical relationship. This increases the reliability of mean reversion signals.
- Check correlation: Only use asset pairs with a high correlation (preferably 0.8–0.9 or higher) for best results. The correlation value is shown in the info table.
- Scale in and out gradually: When entering or exiting positions, consider doing so in parts rather than all at once. This helps manage slippage and risk, especially in volatile markets.
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⚠️ Note on Performance:
This indicator may work a bit slowly, especially on large timeframes or long chart histories, because the calculation of NL and NS (number of long/short signals) is computationally intensive.
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Disclaimer ⚠️
This script is provided for educational and informational purposes only .
It is not financial advice or a recommendation to buy or sell any asset.
Use at your own risk. The author assumes no responsibility for any trading decisions or losses.
Fibo Normalized RSI & RSI RibbonPlots both standard and Z-score normalized RSI ribbons using Fibonacci-based periods. Supports adjustable normalization, optional 0–100 scaling, and multi-line visualizations for momentum and deviation analysis.
This tool is designed for traders who want to go beyond standard RSI by adding:
Statistical normalization (Z-score)
Multi-period analysis (Fibonacci structure)
Advanced divergence and exhaustion detection
It gives you both classical momentum context and mathematically rigorous deviation insight, making it ideal for:
Swing traders
Quant-inclined discretionary traders
Multi-timeframe analysts
Trend Confirmation
When both RSI and normalized RSI across short and long periods are stacked in the same direction (e.g., above 50 or with high Z-scores), the trend is likely strong.
Disagreement between the two ribbons (e.g., RSI high but normalized RSI flat) may indicate late-stage trend or false strength.
Mean Reversion Trades
Look for normalized RSI values > +2 or < -2 (i.e., ~2 standard deviations).
Cross-check with standard RSI to see if the move aligns with a traditional overbought/oversold level.
Great for fade/reversal setups when Z-score RSI is extreme but classic RSI is just beginning to turn.
Divergence Detection
Compare the slope of RSI vs. normalized RSI over same period:
If RSI is rising but normalized RSI is falling → momentum is fading despite apparent strength.
Excellent for early warnings before reversals.
Multi-Timeframe Confluence
Use short-period ribbons (e.g., 3–13) for tactical entries/exits.
Use long-period ribbons (e.g., 55–233) for macro trend bias.
Alignment across both = high-confidence zone.
ATS DELTABAR V5.0ATS DeltaBar Indicator: Volume Trend Momentum Analysis System
——Precisely Capturing "Price-Volume Resonance" Signals for Trend Reversals
Core Positioning
The ATS DeltaBar is a sub-chart indicator focused on the synergy between volume trends and price action. It dynamically monitors changes in volume momentum and price deviations to identify trend strengthening, exhaustion, and reversal signals. Its core value lies in:
Red/Green Bars: Visually reflect volume increases/decreases, revealing capital flow direction.
Divergence Signals: Warn of potential trend reversals (top/bottom divergence).
Resonance Breakouts/Breakdowns: Confirm high-probability trend continuation signals.
Red/Green Zones: Clearly define bullish/bearish phases (red = bearish, green = bullish).
I. Core Logic & Algorithm
1. Volume Trend Visualization
Bar Color Volume State Market Implication
Green Bar Volume ↑ vs. prior period Capital inflow, trend momentum strengthens
Red Bar Volume ↓ vs. prior period Capital outflow, trend momentum weakens
Bar Height Magnitude of volume change Quantifies intensity (higher = stronger shift)
📌 Key Insight:
Green bars + rising price = Healthy uptrend.
Red bars + price新高 = Potential top divergence risk.
2. Divergence Detection
Top Divergence: Price makes higher highs, but DeltaBar peaks lower (red bars accumulate) → Bullish exhaustion.
Bottom Divergence: Price makes lower lows, but DeltaBar troughs rise (green bars accumulate) → Bearish exhaustion.
3. Resonance Signal System
Resonance Breakout: Price breaks resistance + DeltaBar green volume spike → Confirmed uptrend acceleration.
Resonance Breakdown: Price breaks support + DeltaBar red volume spike → Confirmed downtrend weakness.
4. Bullish/Bearish Zone划分
Green Zone: DeltaBar consistently above neutral line → Bullish dominance (favor longs).
Red Zone: DeltaBar consistently below neutral line → Bearish dominance (caution for downside).
II. Signal Types & Practical Applications
1. Basic Trading Signals
Signal Type DeltaBar Behavior Trading Suggestion
Green Zone + Green Bar Price & volume rise together Hold/add to longs
Red Zone + Red Bar Price & volume decline together Short/exit longs
Top Divergence Price ↑ + DeltaBar peaks ↓ (red bars) Reduce longs/test shorts
Bottom Divergence Price ↓ + DeltaBar troughs ↑ (green bars) Prepare for reversal/cover shorts
2. Advanced Resonance Strategies
Breakout Trade: Enter when price breaks a key level + DeltaBar shows green volume spike (resonance breakout) → High-probability long.
Breakdown Trade: Enter when price breaks support + DeltaBar shows red volume spike (resonance breakdown) → High-probability short.
III. Comparison with Traditional Indicators
Aspect Traditional Volume (e.g., OBV) ATS DeltaBar
Signal Dimension Single cumulative volume direction 3D analysis: divergence + resonance + zone划分
Visualization Monotonic curve Dynamic dual-color bars + zones + threshold lines
Practicality Lags price action Real-time捕捉 divergence/resonance points
IV. Usage Scenarios & Tips
1. Trend Following
In Green Zone: Price above MA + DeltaBar green bars expanding → Hold longs.
In Red Zone: Price below MA + DeltaBar red bars expanding → Stay short/avoid longs.
2. Reversal Trading
Top Divergence + Bearish candlestick (e.g., Evening Star) + red bars → Short.
Bottom Divergence + Bullish engulfing + green bars → Long.
3. Breakout Filtering
Only trade breakouts where price and DeltaBar confirm共振 (avoids false breakouts).
V. Case Study (BTC/USDT 1H Chart)
Successful Long: Price broke resistance + DeltaBar green volume spike → 15% rally.
Successful Short: Price consolidated with red bar accumulation (top divergence) → 8% drop.
VI.注意事项
Combine with price structure (support/resistance) for higher accuracy.
Prioritize divergence in ranging markets; focus on共振 signals in trending markets.
"Volume is the fuel of price" — ATS DeltaBar quantifies this relationship to pinpoint trend ignition and reversal points.
ATS Net Volume V5.0ATS Net Volume V5.0
Smart Net Volume Analysis System
Overview
ATS Net Volume V5.0 is an advanced volume-based indicator designed for institutional-level capital flow analysis. By monitoring net buying/selling pressure, it identifies the movements of major market players. The system integrates large-order filtering and dynamic price-volume equilibrium algorithms to distinguish genuine demand from market noise, providing traders with clear signals for capital inflow/outflow.
Key Features
🔹 Net Volume Dynamics
Real-time calculation of the difference between buy-side vs. sell-side volume (units: millions/billions)
Positive values indicate capital inflow (green), negative values indicate outflow (red)
🔹 Large Order Detection
Automatically filters out retail-sized trades, focusing on institutional block orders (e.g., "60M" = 60 million, "05B" = 5 billion)
Evaluates accumulation/distribution behavior relative to price levels
🔹 Multi-Timeframe Compatibility
Supports analysis from tick data to daily charts
🔹 Visual Signals
Histogram + numerical labels for intuitive net volume strength display
Threshold-based alerts (e.g., extreme values trigger overbought/oversold signals)
Data Interpretation
Use Cases
✅ Trend Confirmation
Price rise + expanding net buys → Healthy trend
Price rise + net sells → Potential bull trap
✅ Reversal Warning
Price新高 + net volume divergence → Possible topping signal
✅ Institutional Activity
Sustained large net inflows → Smart money accumulation
Sudden massive outflows → Emergency liquidation event
Signal Classification
Net Volume Range Market Implication
Above +50M Strong inflow (bullish)
+10M to +50M Moderate buying
-10M to +10M Balanced market
-10M to -50M Moderate selling
Below -50M Extreme outflow (bearish)
Advantages
🚨 Filters False Breakouts: Responds only to large-order-driven price movements
📊 Price-Volume Synergy: Avoids "low-volume rally" traps
💡 Universal Applicability: Stocks/Futures/Cryptocurrencies
Note: Always combine with price structure (support/resistance). Not a standalone trading signal.
Sentival | QuantEdgeBIntroducing Sentival by QuantEdgeB.
An Adaptive Multi-Factor Indicator for Market Valuation & Trend Strength
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Overview
The Sentival Valuation System is a medium-term, multi-factor valuation tool designed to assess market conditions using a combination of momentum, mean reversion, and risk-adjusted metrics. It provides traders and investors with a dynamic score reflecting market valuation, ranging from strongly oversold to strongly overbought conditions.
This system leverages a diverse range of technical indicators, including momentum oscillators, volatility measures, risk ratios, and mean-reversion metrics, providing a holistic view of market conditions.
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1. Key Features
🛠 Multi-Factor Valuation Model
Sentival aggregates nine different indicators, normalizing and rescaling them into a standardized z-score-based valuation system. The final output represents an average of the selected indicators, allowing for flexible customization based on the user’s preference.
📊 Customizable Indicator Selection
Users can enable or disable any of the nine valuation factors, ensuring the system adapts to different market environments, trading styles, and assets.
🔄 Multi-Timeframe Adaptability
Sentival can be used across different time horizons, making it suitable for short-term mean reversion, medium-term traders, or long-term valuation analysis by simply adjusting the timeframe and indicator settings. This flexibility allows traders to adapt Sentival to various market conditions and trading objectives.
🎨 Intuitive Dashboard & Color Coding
- Dynamic Heatmap & Dashboard: Displays valuation strength across multiple factors.
- Gradient-Based Overbought/Oversold Signals: Clear color-coded signals for easy interpretation.
- Background Highlighting: Optional oversold/overbought background zones.
🏆 Statistical & Risk-Based Insights
- Standardized Rescaling & Z-Score Analysis to prevent bias from individual indicators.
- Risk-Adjusted Metrics such as Sharpe, Sortino, and Omega Ratios help assess the overall market risk appetite.
- Trend Following Mode (TF Display): Users can enable the "Trend Following" option to display the trend direction, helping to align valuation signals with the broader market trend.
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2. How It Works
Sentival is a multi-factor trend and momentum analysis system, designed to track market cycle shifts using a combination of volatility, momentum, risk assessment, and valuation mechanisms. Instead of focusing on one dimension of the market, Sentival integrates multiple methodologies to cross-validate signals and reduce noise. Each indicator in Sentival plays a specific role, ensuring confirmation across different market conditions.
How Each Component Works Together
1️⃣ Chande Momentum Oscillator (CMO)
• A momentum-based measure that determines whether price action is dominated by upward or downward forces.
• Works well in combination with volatility measures to confirm whether a move is sustainable.
2️⃣ Disparity Index
• Measures the distance between price and its moving average, acting as an overextension filter.
• Ensures that trend-following signals are not driven by short-term spikes but sustained trends.
3️⃣ Bollinger Bands % (BB%)
• A volatility measure that indicates how far price is from the statistical mean.
• Helps identify trend exhaustion points where price moves become unstable.
4️⃣ Relative Strength Index (RSI)
• A trend confirmation layer, ensuring that momentum strength aligns with price movement.
• Adds an additional check to prevent false breakouts.
5️⃣ Rate of Change (RoC)
• Captures the speed of price movement, ensuring that the market has enough momentum for trend continuation.
• Works well with risk indicators to filter weaker moves.
6️⃣ Price Z-Score
• A statistical tool to measure how far price is from its long-term equilibrium.
• Helps prevent entering overstretched trends too late.
7️⃣ Risk Ratios (Sharpe, Sortino, Omega)
• This is the risk-adjusted performance component, ensuring that trends have a healthy risk-reward balance.
• Helps determine when a trend has structurally strong backing rather than speculative movement.
8️⃣ Hurst Cycle Analysis
• Measures the persistence of trends by analyzing price fractals.
• Ensures that the market regime is either trending or mean-reverting, improving trade confidence.
9️⃣ Commodity Channel Index (CCI)
• Helps identify strong trend conditions, adding another layer of momentum confirmation.
• Works well with other oscillators to prevent misreading counter-trends.
🔗 Why These Components Work Well Together
• Momentum + Volatility + Risk → Instead of relying on a single category, Sentival merges multiple dimensions of market behavior into a cohesive signal.
• Filters Out False Signals → Combining momentum oscillators, volatility measures, and risk-adjusted metrics ensures high-confidence entries.
• Adaptability Across Market Regimes → Whether the market is trending, consolidating, or volatile, the system adjusts dynamically.
• Cross-Validation for Trend Strength → If multiple components align, it increases certainty that a trend is real and sustainable.
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3. Sentival Scanner - table breakdown
The dashboard-style table generated is designed to give traders a holistic market view at a glance. It processes a variety of technical signals and distills them into readable labels, visual strength bars, and actionable trend states. Here's a breakdown of what each section means:
1. Direction
This section analyzes whether the average Z-score (a composite of several indicators) is increasing, decreasing, or neutral over time. It does this using a smoothed trend of the Z-score, comparing recent values to older ones.
2. Momentum
Momentum is derived from the rate of change (RoC) of the average Z-score. It evaluates how strong the current move is. If momentum is above a certain positive threshold, it’s considered positive, if below a negative threshold, it’s negative, otherwise it’s neutral.
3. Impulse
Impulse reflects the velocity of momentum — in other words, is the market speeding up or slowing down? High positive values suggest strong acceleration (strong impulse), while negative values show deceleration or stalling.
4. Drive
This metric combines momentum and velocity to create a descriptive phrase that captures the market’s behavior. For example:
• “Strong Upside” means strong momentum with acceleration.
• “Fading Downside” means bearish momentum losing steam.
• “Neutral” appears when momentum is indecisive.
5. Deviation Distance
This represents how far the market price is from fair value in terms of standard deviation units (σ). It’s calculated using Z-scores and classified as:
• +1σ, +2σ, etc., for overvalued regions.
• −1σ, −2σ, etc., for undervalued areas.
• “At Fair Value” if close to the mean.
6. Bull and Bear Strength Bars
The system computes both bullish and bearish strength, using distance from fair value, the rate of change, and the velocity. These strengths are displayed as progress bars, giving a quick visual cue of conviction. The table labels them as:
• “Bull Conviction” if there's a long bias.
• “Bull Potential” if bullish but undecided.
• “Bear Conviction” or “Bear Potential” for short-side equivalents.
7. Trend Signal
This is a simple label that tells you if the scanner recommends a Long, Short, or Cash (neutral) stance based on threshold logic. It is based on whether the average Z-score crosses above a long threshold or below a short one.
8. Stage
The “Stage” label summarizes the valuation environment based on the composite Z-score:
• Strong Undervalued
• Moderately Undervalued
• Fair Value
• Overvalued, etc.
This stage helps traders know whether they are operating in cheap or expensive territory statistically.
Summary
Overall, this table merges advanced technical signals like momentum, volatility, valuation, and risk into a digestible format that updates dynamically with each bar. The goal is to provide traders with a 360° perspective on market conditions, tailored for both trend-following and mean-reversion strategies.
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4. Sentival Valuation Score & Interpretation
🔹 Sentival Score Ranges
- 📉 Strongly Oversold (-2 and below) → Market is extremely undervalued; potential reversal.
- 📉 Moderately Oversold (-1.5 to -2) → Discounted market conditions, buying interest may emerge.
- 📉 Slightly Oversold (-0.5 to -1.5) → Possible accumulation phase.
- ⚖ Fair Value (-0.5 to +0.5) → Market trading at equilibrium.
- 📈 Slightly Overbought (+0.5 to +1.5) → Initial signs of market strength.
- 📈 Moderately Overbought (+1.5 to +2) → Market heating up, caution warranted, selling interest may emerge.
- 📈 Strongly Overbought (+2 and above) → Extreme valuation, increased risk of correction.
This classification helps traders gauge overall market sentiment and make better allocation decisions.
Note: Past valuations and buy/sell signals generated by Sentival do not guarantee future performance. Market conditions can change, and proper risk management should always be applied.
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5. Use Cases & Applications
🔹 📊 Market Rotation & Asset Allocation
- Used as a valuation model to determine if a market or asset is undervalued or overvalued.
- Rotational strategies can benefit from the valuation score by switching exposure between assets.
🔹 📈 Medium-Term Trend Identification
- Detects overbought and oversold conditions while filtering out short-term noise.
- Can be combined with other trend-following indicators for confluence-based strategies.
🔹 🔄 Mean Reversion & Momentum Trading
- Provides statistical validation for momentum breakouts or mean reversion signals.
- Useful for long-short trading strategies, determining optimal entry & exit points.
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Conclusion
Sentival is a powerful universal valuation system for traders and investors seeking a data-driven, multi-factor approach to market valuation. With its combination of momentum, trend, risk-adjusted, and mean-reversion indicators, it provides a robust, adaptable, and statistically sound framework for making informed market decisions.
🔹 Who Should Use Sentival?
✅ Swing Traders & Medium-Term Investors looking for structured valuation metrics.
✅ Quantitative & Systematic Traders incorporating multi-factor models.
✅ Portfolio Managers optimizing exposure to different market regimes.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
AMR-AQR-VolSD-Loc**Dynamic Volatility Bands**
The **Dynamic Volatility Bands** indicator is a powerful tool designed to visualize price volatility and key support/resistance levels based on Average Monthly/Quarterly Range (AMR/AQR) and standard deviation calculations. It plots a base volatility line with customizable upper and lower bands (Vol +1 to +5 and Vol -1 to -5), using a vibrant color progression from blue (#2563EB) to red (#EF4444) for clear visual distinction on dark chart backgrounds like #131722.
**Key Features:**
- **Flexible Volatility Calculation**: Choose between manual standard deviation input or automatic calculation using AMR/AQR ranges, with a scaling factor for fine-tuning.
- **Customizable Levels**: Plot up to 5 upper and 5 lower volatility bands, with options for intermediate (half-step) lines.
- **AMR/AQR Integration**: Displays High, Low, 50% High, 50% Low, and Zero Point levels based on monthly or quarterly ranges, with optional monthly/quarterly open reference.
- **Visual Customization**: Configure line styles, widths, colors, and label positions (right, left, or center). Labels show price levels and can be offset for clarity.
- **Informative Table**: A dynamic table summarizes AMR/AQR levels, volatility settings, and key metrics, with customizable position and appearance.
- **Alerts**: Built-in alerts notify when the price approaches AMR/AQR levels, aiding in timely trading decisions.
**How to Use:**
1. Apply the indicator to your chart and adjust the settings under "Standard Deviation Calculation" to set the volatility source (Manual or AMR/AQR).
2. Customize the number of upper/lower bands and their appearance in the "Volatility Settings" group.
3. Enable the table and alerts to monitor key levels and price movements.
4. Use the vibrant color progression to identify volatility zones: blue for low volatility (Vol ±1) and red for high volatility (Vol ±5).
This indicator is ideal for traders seeking to identify potential support/resistance zones and gauge market volatility dynamically. It’s fully customizable to suit various trading strategies and timeframes.
**Note**: Best viewed on dark chart backgrounds (#131722) for optimal color contrast. Ensure sufficient historical data for accurate AMR/AQR calculations.
GOD Complex Analysis Table By QTX Algo SystemsGOD Complex Analysis Table by QTX Algo Systems
Overview
The GOD Complex Analysis Table is a powerful visual companion for traders using the GOD Complex ecosystem. It displays detailed confluence scores for each trade type (Reversal Long, Reversal Short, Continuation Long, Continuation Short), offering a breakdown of required vs. extra signals, as well as multi-timeframe (MTF) scores and bias.
This tool is designed to help discretionary traders better understand how multiple conditions across timeframes align to support high-quality trade setups. It is not a standalone signal generator but rather an advanced diagnostic table that reveals the logic driving the GOD Complex entries.
How It Works
Each row in the table represents a trade type (e.g., Reversal Long), and includes:
Required Score – Based on must-have conditions for that trade type (e.g., oversold levels, statistical extremes, key momentum shifts).
Extra Score – Bonus confluence points from higher timeframe agreement, slope shifts, or secondary confirmation indicators.
Total Score – Combined Required + Extra score (max 200), useful for comparing relative strength across trade types.
Breakdown Columns – Show exactly which conditions are currently satisfied or missing, categorized as Required or Extra.
MTF Scores – Score-based analysis across 5m to 1M timeframes, highlighting how confluence changes with zoomed-out perspectives.
MTF Bias Row – Net bullish vs. bearish confluence per timeframe (positive = green, negative = red).
Indicators Used (All Proprietary QTX Tools)
VBM (Volatility-Based Momentum): Confirms directional trend and volatility environment.
VBSMI (Volatility-Based SMI): Adapts momentum oscillator based on market conditions and tilt logic.
SEA (Statistically Extreme Areas): Identifies when price reaches statistically rare volatility/range zones.
SPB (Statistical Price Bands): Tracks dynamically adjusted support/resistance based on percentile deviation.
COI (Continuation Opportunity Indicator): Detects pullback exhaustion and momentum re-acceleration opportunities.
Each trade type (Reversal or Continuation) is scored based on these tools across local and higher timeframes.
Key Table Features
🔍 Reversal Scoring Logic
Reversal trades must meet key oversold/overbought criteria (e.g., VBSMI extremes, SEA/SPB triggers) and be supported by trend weakness or exhaustion in the COI/VBM logic. High confluence across timeframes boosts the score.
📈 Continuation Scoring Logic
Continuations require strong trend alignment (VBM, COI), confirmation of momentum (VBSMI cross + slope), and lack of statistical extremes (no SEA/SPB hits). HTF agreement increases the score further.
🧠 Multi-Timeframe (MTF) Scoring
MTF scores are generated by evaluating each trade type’s core confluence across timeframes (e.g., 5m, 1H, 1D, etc.). This helps traders gauge how well a setup aligns with the broader market structure.
📊 Bias Coloring
The MTF Bias row shows net directional strength. Green = bullish bias. Red = bearish bias. Gray = neutral.
🔎 Factors Breakdown
View factors for each trade type. These factors explain which required and extra conditions are currently contributing or missing.
Customization Options
Table position (top/bottom, left/right)
Table size (small, medium, large)
Show/hide trade type rows
Enable/disable breakdown details
Toggle MTF Score section
Use Cases
Analyze high-confluence setups for discretionary trade planning
Cross-check live trades to understand setup quality
Confirm MTF alignment before entries
Study historical patterns to build intuition and strategy
Disclaimer
This indicator is for educational purposes only. It does not provide financial advice or trade recommendations. Always backtest and validate strategies before use.
GOD Complex Trading By QTX Algo SystemsGOD Complex Trading by QTX Algo Systems
Overview
GOD Complex Trading is a comprehensive signal engine that combines multiple QTX Algo Systems indicators into a unified framework for identifying high-confluence reversal and continuation setups. It includes dynamic entry detection, adaptive stop loss logic, multi-timeframe analysis, score-based risk scaling, and real-time trade visualization.
This script is designed for discretionary traders who want to see structured trade logic unfold directly on the chart, with visual labeling of entry type, dynamic stop loss placement, exit score computation, and key trade metrics shown in an on-chart table.
How It Works
Each trade is classified into one of four categories:
Reversal Long
Reversal Short
Continuation Long
Continuation Short
Each trade type has a distinct confluence requirement involving real-time and higher-timeframe inputs. The indicator calculates a confluence score out of 200 and determines HTF (high-timeframe) directional bias across three layers (HTF1, HTF2, HTF3), which are configurable.
QTX Indicators Used
This script integrates internal logic from the following proprietary QTX tools:
VBM (Volatility-Based Momentum) – Confirms directional bias using momentum slope and volatility increase.
VBSMI (Volatility-Based SMI) – Detects early momentum shifts via band exits and crossovers of adaptive smoothed SMI values.
SEA (Statistically Extreme Areas) – Highlights exhaustion zones using normalized volatility, smoothed range deviation, and SMI divergence.
SPB (Statistical Price Bands) – Uses volatility and trend-adjusted percentiles to define dynamic overbought/oversold zones.
COI (Continuation Opportunity Indicator) – Validates re-entry opportunities following a pullback during trend continuation.
Signal Logic – Examples
Each entry type is built from layered logic:
Reversal Long (Example)
Triggers when:
VBSMI is in dynamic oversold and crosses up
SEA level is at or below threshold (signaling statistical exhaustion)
SPB confirms recent low percentile hit
VBM and COI do not indicate trend continuation in the opposite direction
Continuation Long (Example)
Triggers when:
No recent extreme zones (SPB or SEA) are present
VBM confirms continued trend momentum
VBSMI crosses up and confirms strength
COI may confirm re-entry conditions
High-timeframe bias scores show alignment
All entries are subject to filter checks, including:
Minimum confluence score
HTF bias thresholds (HTF1, HTF2, HTF3)
Position type and trade history
Key Features
Trade Type Auto-Labeling
Each signal is labeled (“Rev Long”, “Cont Short”, etc.) directly on the chart for instant identification.
Stop Loss Visualization
Stop loss levels are calculated using a weighted average of ATR-based padding and prior swing highs/lows. Ghost lines are drawn for Add trades.
TP1 / TP2 Logic
TP1: Fires on opposite VBSMI crossover (momentum loss).
TP2: Fires when the opposite side’s reversal score exceeds a user-defined threshold.
Position Size & Risk Table
The on-chart table shows estimated trade size (based on max risk input), stop loss price, and calculated exit score. Reversal trades scale based on confluence score, while continuation trades use linear scaling.
Multi-Timeframe Confluence
The script uses three automatic higher timeframes to calculate directional bias and exit score amplification. This allows scoring logic to reflect broader trend alignment.
Add Trade Logic
The indicator detects both same-style and cross-style Add setups. Add signals are labeled and visualized, but should be used cautiously.
Auto-Close on Opposite Signal
When an opposite entry signal is triggered (e.g. Cont Short after Rev Long), the current trade is automatically considered closed, resetting tracking variables and metrics.
Additional Features
Fully bar-closed logic: no repainting or mid-bar recalculation.
High-precision control over alert triggering using bias filters and score ranges.
Dedicated alert conditions for all key trade types and TP/SL events.
Score-based position sizing using dynamic confluence score caps.
Table remains visible for a configurable number of bars after trade close.
Use Cases
Manual discretionary entries with clearly labeled setups and real-time validation
Score-based trade review and journaling using TP1/TP2 and exit score
Optimizing trade filters using alerts with HTF bias and confluence thresholds
Data-driven strategy refinement by observing which trades reach full exits
Disclaimer
This tool is provided for educational and informational purposes only. It does not guarantee any particular outcome or profitability. Always use proper risk management, backtest thoroughly, and consult a financial professional if needed.
Grid Trade Helper📌 Grid Trade Helper – Range-Based Grid Planning Tool
This tool is designed for range-based traders and manual grid strategy operators, providing a framework to balance execution efficiency and risk exposure.
By referencing historical weekly volatility, it helps estimate a reasonable grid width, visualizes key levels, and supports position management with quantitative guidance.
🧭 Design Philosophy:
In multi-entry systems like grid trading, there's always a tradeoff:
"Tighter grids improve opportunity density but increase risk; wider grids reduce risk but lower efficiency."
This tool seeks to provide a dynamic equilibrium between the two, using past volatility to determine practical grid intervals and suggest safe leverage thresholds.
✨ Core Features:
Weekly open level tracking (custom time + time zone support)
Volatility-based suggestions for grid width and safe grid count
Visual range plotting with optional stop-line overlay
Compact live table showing key metrics: average range, grid width, grid count, leverage cap
🔧 Customizable Parameters:
Time zone and custom weekly open hour
Max number of visual elements (lines, boxes)
Color and line style options
📈 Suggested Use Cases:
Planning manual grid structures with volatility-adjusted intervals
Visual support for range-bound or sideways market strategies
Estimating leverage exposure and grid density for better position control
⚠️ This indicator is intended as a strategic support tool and does not constitute financial advice. Use according to your own risk framework and market understanding.
Z-Score IndicatorWhat it does:
Calculates the Z-Score: (Current Price - Average Price) / Standard Deviation
Plots the Z-Score in a separate panel below your main chart.
Allows you to customize the Lookback Period (default is 30 bars) to suit your trading style and the asset's characteristics. A shorter period is more sensitive, while a longer period provides a smoother output.
Key Features:
Clear Z-Score Line: Visualizes the current Z-Score value.
Reference Lines:
Zero Line (Gray, Dotted): Indicates the price is at its average for the lookback period.
+2 Standard Deviations (Red, Dotted): Highlights when the price is significantly above its recent average. Often interpreted as potentially overbought.
-2 Standard Deviations (Red, Dotted): Highlights when the price is significantly below its recent average. Often interpreted as potentially oversold.
How to use it:
Look for Z-Score values moving towards or beyond the +2 or -2 standard deviation lines. These extremes can signal that the price has moved unusually far from its mean and might be due for a reversion or a pause.
Use it in conjunction with other indicators and your overall market analysis to make more informed trading decisions.
Experiment with the "Lookback Period" setting to find what works best for different assets and timeframes.
Feigenbaum Projection Zones [ALLDYN]🔷 Feigenbaum Projection Zones
This tool visualizes non-overlapping projection zones above and below a manually defined price range (C.E. – Center Equilibrium) using Feigenbaum constants as spacing multipliers. It’s ideal for traders who prefer structured, mathematically grounded projection layers over standard Fibonacci tools.
📌 Features:
Manual high/low range input (C.E. zone)
Feigenbaum-based zone scaling with interleaved gaps
Color-coded zones (🟥 below CE, 🟩 above CE, 🟨 CE range)
Dotted midlines through each zone
Timeframe-restricted to 15m and below for clarity
Clean label/box/line management for minimal clutter
🔒 Source code is protected to preserve custom zone spacing logic.
🧠 Designed for advanced technical analysts who want mathematical projection zones based on deterministic scaling constants.
🔍 Feigenbaum Projections: Overview
Feigenbaum Projections are derived from chaos theory, specifically Mitchell Feigenbaum’s work on bifurcations and the universality of nonlinear systems. In market terms, they attempt to map fractal or recursive structures in price movements, especially those that might echo repeating patterns in chaotic systems.
✅ Benefits:
Captures fractal and nonlinear dynamics better than Fibonacci.
Self-similarity and scaling laws can offer insights into repeating structures not seen with classical tools.
Can help model transitions between trend and consolidation through bifurcation patterns.
Tied to mathematical constants (Feigenbaum constants), offering theoretical rigor in modeling chaotic price movement.
***Compact chart view to show the full range of the FGBZ Calculations***
