Metallic Retracement LevelsThere's something that's always bothered me about how traders use Fibonacci retracements. Everyone treats the golden ratio like it's the only game in town, but mathematically speaking, it's completely arbitrary. The golden ratio is just the first member of an infinite family of metallic means, and there's no particular reason why 1.618 should be special for markets when we have the silver ratio at 2.414, the bronze ratio at 3.303, and literally every other metallic mean extending to infinity. We just picked one and decided it was magical.
The metallic means are a sequence of mathematical constants that generalize the golden ratio. They're defined by the equation x² = kx + 1, where k is any positive integer. When k equals 1, you get the golden ratio. When k equals 2, you get the silver ratio. When k equals 3, you get bronze, and so on forever. Each metallic mean generates its own set of ratios through successive powers, just like how the golden ratio gives you 0.618, 0.382, 0.236 and so forth. The silver ratio produces a completely different set of retracement levels, as does bronze, as does any arbitrary metallic number you want to choose.
This indicator calculates these metallic means using the standard alpha and beta formulas. For any metallic number k, alpha equals (k + sqrt(k² + 4)) / 2, and we generate retracement ratios by raising alpha to various negative powers. The script algorithmically generates these levels instead of hardcoding them, which is how it should have been done from the start. It's genuinely silly that most fib tools just hardcode the ratios when the math to generate them is straightforward. Even worse, traditional fib retracements use 0.5 as a level, which isn't even a fibonacci ratio. It's just thrown in there because it seems like it should be important.
The indicator works by first detecting swing points using the Sylvain Zig-Zag . The zig-zag identifies significant price swings by combining percentage change with ATR adjustments, filtering out noise and connecting major pivot points. This is what drives the retracement levels. Once a new swing is confirmed, the script calculates the range between the last two pivot points and generates metallic retracement levels from the most recent swing low or high.
You can adjust which metallic number to use (golden, silver, bronze, or any positive integer), control how many power ratios to display above and below the 1.0 level, and set how many complete retracement cycles you want drawn. The levels extend from the swing point and show you where price might react based on whichever metallic mean you've selected. The zig-zag settings let you tune the sensitivity of swing detection through ATR period, ATR multiplier, percentage reversal, and additional absolute or tick-based reversal values.
What this really demonstrates is that retracement analysis is more flexible than most traders realize. There's no mathematical law that says markets must respect the golden ratio over any other metallic mean. They're all valid mathematical constructs with the same kind of recursive properties. By making this tool, I wanted to highlight that using fibonacci retracements involves an arbitrary choice, and maybe that choice should be more deliberate or at least tested against alternatives. You can experiment with different metallic numbers and see which ones seem to work better for your particular market or timeframe, or just use this to understand that the standard fib levels everyone uses aren't as fundamental as they appear.
Educational
Institutional Orderflow Pro — VWAP, Delta, and Liquidity
Institutional Orderflow Pro is a next-generation order flow analysis indicator designed to help traders identify institutional participation, directional bias, and exhaustion zones in real time.
Unlike traditional volume-based indicators, it merges VWAP dynamics, cumulative delta, relative volume, and liquidity proximity into a single unified dashboard that updates tick-by-tick — without repainting.
The indicator is open-source, transparent, and educational. It aims to provide traders with a clearer read on who controls the market — buyers or sellers — and where liquidity lies.
The indicator combines multiple institutional-grade analytics into one framework:
RVOL (Relative Volume) = Compares current volume against the average of recent bars to identify strong institutional participation.
zΔ (Delta Z-Score) = Normalizes the buying/selling delta to reveal unusually aggressive market behavior.
CVDΔ (Cumulative Volume Delta Change) = Shows which side (buyers/sellers) is dominating this bar’s order flow.
VWAP Direction & Slope = Determines whether price is trading above/below VWAP and whether VWAP is trending or flat.
PD Distance (Prev Day Confluence) = Measures the current price’s distance from previous day’s high, low, close, and VWAP in ATR units — highlighting liquidity zones.
ABS/EXH Detection = Identifies institutional absorption and exhaustion patterns where momentum may reverse.
Bias Computation = Combines VWAP direction + slope to give a simplified regime signal: UP, DOWN, or FLAT.
All metrics are displayed through a color-coded, non-repainting HUD:
🟢 = bullish / favorable conditions
🔴 = bearish / weak conditions
⚫ = neutral / flat
🟡 = absorption (potential trap zone)
🟠 = exhaustion (momentum fading)
| Metric | Signal | Meaning |
| ---------------------- | ------- | ---------------------------------------------- |
| **RVOL ≥ 1.3** | 🟢 | High institutional activity — valid setup zone |
| **zΔ ≥ 1.2 / ≤ -1.2** | 🟢 / 🔴 | Unusual buy/sell aggression |
| **CVDΔ > 0** | 🟢 | Buyers dominate this bar |
| **VWAP dir ↑ / ↓** | 🟢 / 🔴 | Institutional bias long/short |
| **Slope ok = YES** | 🟢 | Trending market |
| **PD dist ≤ 0.35 ATR** | 🟢 | Near key liquidity zones |
| **Bias = UP/DOWN** | 🟢 / 🔴 | Trend-aligned environment |
| **ABS/EXH active** | 🟡 / 🟠 | Caution — possible reversal zone |
How to Use
Confirm Volume Context → RVOL > 1.2
Align with Bias → Take longs only when Bias = UP, shorts only when Bias = DOWN.
Check Slope and VWAP Dir → Ensure trending context (Slope = YES).
Confirm CVD and zΔ → Flow should agree with price direction.
Avoid ABS/EXH Triggers → These signal exhaustion or absorption by large players.
Enter Near PD Zones → Ideal trade zones are within 0.35 ATR of prior-day levels.
This multi-factor confirmation reduces noise and focuses only on high-probability institutional setups.
Originality
This script was written from scratch in Pine v6.
It does not reuse existing public indicators except for standard built-ins (ta.vwap, ta.atr, etc.).
The unique combination of delta z-scoring, VWAP slope filtering, and real-time confluence zones distinguishes it from typical orderflow tools or cumulative delta overlays.
The core innovation is its merged real-time HUD that integrates institutional metrics and natural-language feedback directly on the chart, allowing traders to read market context intuitively rather than decode multiple subplots.
Notes & Disclaimers
This indicator does not repaint.
It’s intended for educational and analytical purposes only — not as financial advice or a guaranteed signal system.
Works best on liquid instruments (Futures, Indices, FX majors).
Avoid non-standard chart types (Heikin Ashi, Renko, etc.) for accurate readings.
Open-source, modifiable, and compatible with Pine v6.
Recommended Use
Apply it with clean charts and standard candles for the best clarity.
Use alongside a basic structure or volume profile to contextualize institutional bias zones.
Author: Dhawal Ranka
Category - Orderflow / VWAP / Institutional Analysis
Version: Pine Script™ v6
License: Open Source (Educational Use)
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
Dynamic Volume Based Key Price LevelsDescription
This indicator introduces a volume-based approach to detecting support and resistance zones.
Instead of relying on price swings or pivots, it analyzes where the most trading activity occurred within a selected lookback period, then marks those levels directly on the chart.
The result is a clear visual map of price areas with strong historical participation, which often act as reaction zones in future moves.
How It Works
The script divides the analyzed range into price bins, sums traded volume for each bin, and highlights the strongest levels based on their share of total volume.
It also includes an optional multi-timeframe mode, allowing traders to analyze higher timeframe volume structures on a lower timeframe chart.
Key Features
🔹 Volume-Based Key Levels Detection: Finds statistically meaningful price zones derived from raw volume data.
🔹 Multi-Timeframe Mode: Optionally use higher timeframe volume to identify key market structure levels.
🔹 Visual Customization: Configure colors, line styles, transparency, and label formatting.
🔹 Automatic Ranking: Highlights the strongest to weakest levels using a color gradient.
🔹 Dynamic Updates: Levels adapt automatically as new bars form.
Inputs Overview
Lookback Bars: Number of historical bars used for analysis.
Price Bins: Defines the precision of volume distribution.
Number of Lines: How many key levels to display.
Min Volume %: Filters out less relevant low-volume bins.
Extend Lines: Choose how lines are projected into the future.
Use Higher Timeframe: Pull data from a higher timeframe for broader perspective.
How to Use
Apply the indicator to your chart and adjust the lookback period.
Optionally enable higher timeframe mode for more stable long-term zones.
Observe the horizontal lines — these represent volume-weighted support and resistance areas.
Combine with your existing tools for trend or momentum confirmation.
This tool helps visualize where market participation was strongest, giving traders a clearer view of potential reaction zones for both intraday and swing analysis.
It’s intended as a visual analytical aid, not a signal generator.
⚠️Disclaimer:
This script is provided for educational and informational purposes only. It is not financial advice and should not be considered a recommendation to buy, sell, or hold any financial instrument. Trading involves significant risk of loss and is not suitable for every investor. Users should perform their own due diligence and consult with a licensed financial advisor before making any trading decisions. The author does not guarantee any profits or results from using this script, and assumes no liability for any losses incurred. Use this script at your own risk.
Adaptive Trend & Momentum Composite (ATMC)This script combines two well-established technical concepts—adaptive moving averages and normalized momentum oscillators—into a single, cohesive system designed to identify high-probability trend continuations with reduced noise.
What it does:
The indicator dynamically adjusts its sensitivity based on market volatility (using an ATR-based filter) and overlays a smoothed momentum signal that highlights potential exhaustion points within the prevailing trend. Unlike generic "trend-following" scripts, this implementation uses the Kaufman Adaptive Moving Average (KAMA) for price filtering and a rate-of-change (ROC) oscillator normalized between -1 and +1 to gauge momentum strength.
How it works:
Trend Filter: KAMA adapts its smoothing factor based on market efficiency—reacting quickly in trending markets and slowing down in choppy conditions.
Momentum Confirmation: A 9-period ROC is scaled to a fixed range to avoid amplitude distortion across assets. When momentum aligns with the KAMA direction and exceeds a volatility-adjusted threshold, the script paints a colored background (green for long bias, red for short bias).
Noise Reduction: Signals are only displayed when the 14-period ATR is above its 50-period moving average, ensuring trades occur in sufficiently active markets.
How to use it:
Long setups: Look for green background zones after a pullback, ideally near dynamic support (e.g., previous swing low or KAMA line).
Short setups: Red zones after rallies near resistance.
Avoid trading when no background is shown—this indicates either low volatility or conflicting signals.
Why this mashup is useful:
Many traders combine trend and momentum indicators, but often without synchronization logic. Here, both components are interdependent: momentum must confirm the adaptive trend and pass a volatility gate. This reduces false signals common in sideways markets—a frequent pain point with standard MACD or EMA crossovers.
This script is not investment advice. Test it thoroughly in your own strategy before live use.
RSI VWAP v1 [JopAlgo]RSI VWAP v1.1 made stronger by volume-aware!
We know there's nothing new and the original RSI already does an excellent job. We're just working on small, practical improvements – here's our take: The same basic idea, clearer display, and a single, specially developed rolling line: a VWAP of the RSI that incorporates volume (participation) into the calculation.
Do you prefer the pure classic?
You can still use Wilder or Cutler engines –
but the star here is the VW-RSI + rolling line.
This RSI also offers the possibility of illustrating a possible
POC (Point of Control - or the HAL or VAL) level.
However, the indicator does NOT plot any of these levels itself.
We have included an illustration in the chart for this!
We hope this version makes your decision-making easier.
What you’ll see
The RSI line with a 50 midline and optional bands: either static 70/30 or adaptive μ±k·σ of the Rolling Line.
One smoothing concept only: the Rolling Line (light blue) = VWAP of RSI.
Shadow shading between RSI and the Rolling Line (green when RSI > line, red when RSI < line).
A lighter tint only on the parts of that shadow that sit above the upper band or below the lower band (quick overbought/oversold context).
Simple divergence lines drawn from RSI pivots (green for regular bullish, red for regular bearish). No labels, no buy/sell text—kept deliberately clean.
What’s new, and why it helps
VW-RSI engine (default):
RSI can be computed from volume-weighted up/down moves, so momentum reflects how much traded when price moved—not just the direction.
Rolling Line (VWAP of RSI) with pure VWAP adaptation:
Low volume: blends toward a faster VWAP so early, thin starts aren’t missed.
Volume spikes: blends toward a slower VWAP so a single heavy bar doesn’t whip the curve.
You can reveal the Base Rolling (pre-adaptation) line to see exactly how much adaptation is happening.
Adaptive bands (optional):
Instead of fixed 70/30, use mean ± k·stdev of the Rolling Line over a lookback. Levels breathe with the market—useful in strong trends where static bounds stay pinned.
Minimal, readable panel:
One smoothing, one story. The shadow tells you who’s in control; the lighter highlight shows stretch beyond your lines.
How to read it (fast)
Bias: RSI above 50 (and a rising Rolling Line) → bullish bias; below 50 → bearish bias.
Trigger: RSI crossing the Rolling Line with the bias (e.g., above 50 and crossing up).
Stretch: Near/above the upper band, avoid chasing; near/below the lower band, avoid panic—prefer a cross back through the line.
Divergence lines: Use as context, not as standalone signals. They often help you wait for the next cross or avoid late entries into exhaustion.
Settings that actually matter
RSI Engine: VW-RSI (default), Wilder, or Cutler.
Rolling Line Length: the VWAP length on RSI (higher = calmer, lower = earlier).
Adaptive behavior (pure VWAP):
Speed-up on Low Volume → blends toward fast VWAP (factor of your length).
Dampen Spikes (volume z-score) → blends toward slow VWAP.
Fast/Slow Factors → how far those fast/slow variants sit from the base length.
Bands: choose Static 70/30 or Adaptive μ±k·σ (set the lookback and k).
Visuals: show/hide Base Rolling (ref), main shadow, and highlight beyond bands.
Signal gating: optional “ignore first bars” per day/session if you dislike open noise.
Starter presets
Scalp (1–5m): RSI 9–12, Rolling 12–18, FastFactor ~0.5, SlowFactor ~2.0, Adaptive on.
Intraday (15m–1H): RSI 10–14, Rolling 18–26, Bands k = 1.0–1.4.
Swing (4H–1D): RSI 14–20, Rolling 26–40, Bands k = 1.2–1.8, Adaptive on.
Where it shines (and limits)
Best: liquid markets where volume structure matters (majors, indices, large caps).
Works elsewhere: even with imperfect volume, the shadow + bands remain useful.
Limits: very thin/illiquid assets reduce the benefit of volume-weighting—lengthen settings if needed.
Attribution & License
Based on the concept and baseline implementation of the “Relative Strength Index” by TradingView (Pine v6 built-in).
Released as Open-source (MPL-2.0). Please keep the license header and attribution intact.
Disclaimer
For educational purposes only; not financial advice. Markets carry risk. Test first, use clear levels, and manage risk. This project is independent and not affiliated with or endorsed by TradingView.
Squeeze Momentum IndicatorThis indicator identifies periods of low market volatility—commonly referred to as a "squeeze"—by comparing Bollinger Bands and Keltner Channels. When volatility compresses, price often prepares for a directional breakout. The histogram visualizes momentum strength and direction once the squeeze ends.
**How it works:**
- **Squeeze detection**: A squeeze is active when Bollinger Bands are fully contained within Keltner Channels. This appears as black crosses on the zero line.
- **Volatility expansion**: When Bollinger Bands move outside Keltner Channels, volatility is increasing. This state is marked with blue crosses.
- **Momentum histogram**: The core signal is a linear regression of price relative to a dynamic baseline (average of the highest high, lowest low, and SMA over the lookback period).
- **Aqua**: Positive momentum that is accelerating.
- **Bright blue**: Positive momentum that is decelerating.
- **Yellow**: Negative momentum that is accelerating downward.
- **Orange**: Negative momentum that is decelerating (potential reversal zone).
**Usage notes:**
Traders often monitor the transition from squeeze (black) to expansion (blue) combined with a strong histogram move away from zero as a potential entry signal. Color changes in the histogram help assess momentum shifts before price makes large moves.
This script is designed for educational and analytical purposes. It does not constitute investment advice. Always test strategies in a simulated environment before applying them to live trading.
🚀 Ultimate Trading Tool + Strat Method🚀 Ultimate Trading Tool + Strat Method - Complete Breakdown
Let me give you a comprehensive overview of this powerful indicator!
🎯 What This Indicator Does:
This is a professional-grade, all-in-one trading system that combines two proven methodologies:
1️⃣ Technical Analysis System (Original)
Advanced trend detection using multiple EMAs
Momentum analysis with MACD
RSI multi-timeframe analysis
Volume surge detection
Automated trendline drawing
2️⃣ Strat Method (Pattern Recognition)
Inside bars, outside bars, directional bars
Classic patterns: 2-2, 1-2-2
Advanced patterns: 3-1-2, 2-1-2, F2→3
Timeframe continuity filters
📊 How It Generates Signals:
Technical Analysis Signals (Green/Red Triangles):
Buy Signal Triggers When:
✅ Price above EMA 21 & 50 (uptrend)
✅ MACD histogram rising (momentum)
✅ RSI between 30-70 (not overbought/oversold)
✅ Volume surge above 20-period average
✅ Price breaks above resistance trendline
Scoring System:
Trend alignment: +1 point
Momentum: +1 point
RSI favorable: +1 point
Trendline breakout: +2 points
Minimum score required based on sensitivity setting
Strat Method Signals (Blue/Orange Labels):
Pattern Recognition:
2-2 Setup: Down bar → Up bar (or reverse)
1-2-2 Setup: Inside bar → Down bar → Up bar
3-1-2 Setup: Outside bar → Inside bar → Up bar
2-1-2 Setup: Down bar → Inside bar → Up bar
F2→3 Setup: Failed directional bar becomes outside bar
Confirmation Required:
Must break previous bar's high (buy) or low (sell)
Optional timeframe continuity (daily & weekly aligned)
💰 Risk Management Features:
Dynamic Stop Loss & Take Profit:
ATR-Based: Adapts to market volatility
Stop Loss: Entry - (ATR × 1.5) by default
Take Profit: Entry + (ATR × 3.0) by default
Risk:Reward: Customizable 1:2 to 1:5 ratios
Visual Risk Zones:
Colored boxes show risk/reward area
Dark, bold lines for easy identification
Clear entry, stop, and target levels
🎨 What You See On Screen:
Main Signals:
🟢 Green Triangle "BUY" - Technical analysis long signal
🔴 Red Triangle "SELL" - Technical analysis short signal
🎯 Blue Label "STRAT" - Strat method long signal
🎯 Orange Label "STRAT" - Strat method short signal
Trendlines:
Green lines - Support trendlines (bullish)
Red lines - Resistance trendlines (bearish)
Automatically drawn from pivot points
Extended forward to predict future levels
Stop/Target Levels:
Bold crosses at stop loss levels (red color)
Bold crosses at take profit levels (green color)
Line width = 3 for maximum visibility
Trade Zones:
Light green boxes - Long trade risk/reward zone
Light red boxes - Short trade risk/reward zone
Shows potential profit vs risk visually
📊 Information Dashboard (Top Right):
Shows real-time market conditions:
Main Signal: Current technical signal status
Strat Method: Active Strat pattern
Trend: Bullish/Bearish/Neutral
Momentum: Strong/Weak based on MACD
Volume: High/Normal compared to average
TF Continuity: Daily/Weekly alignment
RSI: Current RSI value with color coding
Support/Resistance: Current trendline levels
🔔 Alert System:
Entry Alerts:
Technical Signals:
🚀 BUY SIGNAL TRIGGERED!
Type: Technical Analysis
Entry: 45.23
Stop: 43.87
Target: 48.95
```
**Strat Signals:**
```
🎯 STRAT BUY TRIGGER!
Pattern: 3-1-2
Entry: 45.23
Trigger Level: 44.56
Exit Alerts:
Target hit notifications
Stop loss hit warnings
Helps maintain discipline
⚙️ Customization Options:
Signal Settings:
Sensitivity: High/Medium/Low (controls how many signals)
Volume Filter: Require volume surge or not
Momentum Filter: Require momentum confirmation
Strat Settings:
TF Continuity: Require daily/weekly alignment
Pattern Selection: Enable/disable specific patterns
Confirmation Mode: Show only confirmed triggers
Risk Settings:
ATR Multiplier: Adjust stop/target distance
Risk:Reward: Set preferred ratio
Visual Elements: Show/hide any component
Visual Settings:
Colors: Customize all signal colors
Display Options: Toggle signals, levels, zones
Trendline Length: Adjust pivot detection period
🎯 Best Use Cases:
Day Trading:
Use low sensitivity setting
Enable all Strat patterns
Watch for high volume signals
Quick in/out trades
Swing Trading:
Use medium sensitivity
Require timeframe continuity
Focus on trendline breakouts
Hold for target levels
Position Trading:
Use high sensitivity (fewer signals)
Require strong momentum
Focus on weekly/daily alignment
Larger ATR multipliers
💡 Trading Strategy Tips:
High-Probability Setups:
Double Confirmation: Technical + Strat signal together
Trend Alignment: All timeframes agree
Volume Surge: Institutional participation
Trendline Break: Clear level breakout
Risk Management:
Always use stops - System provides them
Position sizing - Risk 1-2% per trade
Don't chase - Wait for signal confirmation
Take profits - System provides targets
What Makes Signals Strong:
✅ Both technical AND Strat signals fire together
✅ Timeframe continuity (daily & weekly aligned)
✅ Volume surge confirms institutional interest
✅ Multiple indicators align (trend + momentum + RSI)
✅ Clean trendline breakout with no resistance above (or support below)
⚠️ Common Mistakes to Avoid:
Don't ignore stops - System calculates them for a reason
Don't overtrade - Wait for quality setups
Don't disable volume filter - Unless you know what you're doing
Don't use max sensitivity - You'll get too many signals
Don't ignore timeframe continuity - It filters bad trades
🚀 Why This Indicator is Powerful:
Combines Multiple Edge Sources:
Technical analysis (trend, momentum, volume)
Pattern recognition (Strat method)
Risk management (dynamic stops/targets)
Market structure (trendlines, support/resistance)
Professional Features:
No repainting - signals are final when bar closes
Clear risk/reward before entry
Multiple confirmation layers
Adaptable to any market or timeframe
Beginner Friendly:
Clear visual signals
Automatic calculations
Built-in risk management
Comprehensive dashboard
This indicator essentially gives you everything a professional trader uses - trend analysis, momentum, patterns, volume, risk management - all in one clean package!
Any specific aspect you'd like me to explain in more detail? 🎯RetryClaude can make mistakes. Please double-check responses. Sonnet 4.5
VWAP + Multi-Condition RSI Signals + FibonacciPlatform / System
Platform: TradingView
Language: Pine Script® v6
Purpose: This script is an overlay indicator for technical analysis on charts. It combines multiple tools: VWAP, RSI signals, and Fibonacci levels.
1️⃣ VWAP (Volume Weighted Average Price)
What it does:
Plots the VWAP line on the chart, which is a weighted average price based on volume.
Can be anchored to different periods: Session, Week, Month, Quarter, Year, Decade, Century, or corporate events like Earnings, Dividends, Splits.
Optionally plots bands above and below VWAP based on standard deviation or a percentage.
Supports up to 3 bands with customizable multipliers.
Will not display if the timeframe is daily or higher and the hideonDWM option is enabled.
Visual on chart: A main VWAP line with optional shaded bands.
2️⃣ RSI (Relative Strength Index) Signals
What it does:
Calculates RSI with a configurable period.
Identifies overbought and oversold zones using user-defined levels.
Generates buy/sell signals based on:
RSI crossing above oversold → Buy
RSI crossing below overbought → Sell
Detects strong signals using divergences:
Bullish divergence: Price makes lower low, RSI makes higher low → Strong Buy
Bearish divergence: Price makes higher high, RSI makes lower high → Strong Sell
Optional momentum signals when RSI crosses 50 after recent overbought/oversold conditions.
Visual on chart:
Triangles for buy/sell
Different color triangles/circles for strong and momentum signals
Background shading in RSI overbought/oversold zones
Alerts: The script can trigger alerts when any of these signals occur.
3️⃣ Fibonacci Levels
What it does:
Calculates Fibonacci retracement and extension levels based on the highest high and lowest low over a configurable lookback period.
Plots standard Fibonacci levels: 0.146, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0
Plots extension levels: 1.272, 1.618, 2.0, 2.618
Helps identify potential support/resistance zones.
Visual on chart: Horizontal lines at each Fibonacci level, shaded with different transparencies.
Summary
This script is essentially a multi-tool trading indicator that combines:
VWAP with dynamic bands for trend analysis and price positioning
RSI signals with divergences for entry/exit points
Fibonacci retracement and extension levels for support/resistance
It is interactive and visual, providing both chart overlays and alert functionality for active trading strategies.
This code is provided for training and educational purposes only. It is not financial advice and should not be used for live trading without proper testing and professional guidance.
Intrinsic Value AnalyzerThe Intrinsic Value Analyzer is an all-in-one valuation tool that automatically calculates the fair value of a stock using industry-standard valuation techniques. It estimates intrinsic value through Discounted Cash Flow (DCF), Enterprise Value to Revenue (EV/REV), Enterprise Value to EBITDA (EV/EBITDA), and Price to Earnings (P/EPS). The model features adjustable parameters and a built-in alert system that notifies investors in real time when valuation multiples reach predefined thresholds. It also includes a comprehensive, color-coded table that compares the company’s historical average growth rates, valuation multiples, and financial ratios with the most recent values, helping investors quickly assess how current values align with historical averages.
The model calculates the historical Compounded Annual Growth Rates (CAGR) and average valuation multiples over the selected Lookback Period. It then projects Revenue, Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA), Earnings per Share (EPS), and Free Cash Flow (FCF) for the selected Forecast Period and discounts their future values back to the present using the Weighted Average Cost of Capital (WACC) or the Cost of Equity. By default, the model automatically applies the historical averages displayed in the table as the growth forecasts and target multiples. These assumptions can be modified in the menu by entering custom REV-G, EBITDA-G, EPS-G, and FCF-G growth forecasts, as well as EV/REV, EV/EBITDA, and P/EPS target multiples. When new input values are entered, the model recalculates the fair value in real time, allowing users to see how changes in these assumptions affect the company’s fair value.
DCF = (Sum of (FCF × (1 + FCF-G) ^ t ÷ (1 + WACC) ^ t) for each year t until Forecast Period + ((FCF × (1 + FCF-G) ^ Forecast Period × (1 + LT Growth)) ÷ ((WACC - LT Growth) × (1 + WACC) ^ Forecast Period)) + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
EV/REV = ((Revenue × (1 + REV-G) ^ Forecast Period × EV/REV Target) ÷ (1 + WACC) ^ Forecast Period + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
EV/EBITDA = ((EBITDA × (1 + EBITDA-G) ^ Forecast Period × EV/EBITDA Target) ÷ (1 + WACC) ^ Forecast Period + Cash - Debt - Preferred Equity - Minority Interest) ÷ Shares Outstanding
P/EPS = (EPS × (1 + EPS-G) ^ Forecast Period × P/EPS Target) ÷ (1 + Cost of Equity) ^ Forecast Period
The discounted one-year average analyst price target (1Y PT) is also displayed alongside the valuation labels to provide an overview of consensus estimates. For the DCF model, the terminal long-term FCF growth rate (LT Growth) is based on the selected country to reflect expected long-term nominal GDP growth and can be modified in the menu. For metrics involving FCF, users can choose between reported FCF, calculated as Cash From Operations (CFO) - Capital Expenditures (CAPEX), or standardized FCF, calculated as Earnings Before Interest and Taxes (EBIT) × (1 - Average Tax Rate) + Depreciation and Amortization - Change in Net Working Capital - CAPEX. Historical average values displayed in the left column of the table are based on Fiscal Year (FY) data, while the latest values in the right column use the most recent Trailing Twelve Month (TTM) or Fiscal Quarter (FQ) data. The indicator displays color-coded price labels for each fair value estimate, showing the percentage upside or downside from the current price. Green indicates undervaluation, while red indicates overvaluation. The table follows a separate color logic:
REV-G, EBITDA-G, EPS-G, FCF-G = Green indicates positive annual growth when the CAGR is positive. Red indicates negative annual growth when the CAGR is negative.
EV/REV = Green indicates undervaluation when EV/REV ÷ REV-G is below 1. Red indicates overvaluation when EV/REV ÷ REV-G is above 2. Gray indicates fair value.
EV/EBITDA = Green indicates undervaluation when EV/EBITDA ÷ EBITDA-G is below 1. Red indicates overvaluation when EV/EBITDA ÷ EBITDA-G is above 2. Gray indicates fair value.
P/EPS = Green indicates undervaluation when P/EPS ÷ EPS-G is below 1. Red indicates overvaluation when P/EPS ÷ EPS-G is above 2. Gray indicates fair value.
EBITDA% = Green indicates profitable operations when the EBITDA margin is positive. Red indicates unprofitable operations when the EBITDA margin is negative.
FCF% = Green indicates strong cash conversion when FCF/EBITDA > 50%. Red indicates unsustainable FCF when FCF/EBITDA is negative. Gray indicates normal cash conversion.
ROIC = Green indicates value creation when ROIC > WACC. Red indicates value destruction when ROIC is negative. Gray indicates positive but insufficient returns.
ND/EBITDA = Green indicates low leverage when ND/EBITDA is below 1. Red indicates high leverage when ND/EBITDA is above 3. Gray indicates moderate leverage.
YIELD = Green indicates positive shareholder return when Shareholder Yield > 1%. Red indicates negative shareholder return when Shareholder Yield < -1%.
The Return on Invested Capital (ROIC) is calculated as EBIT × (1 - Average Tax Rate) ÷ (Average Debt + Average Equity - Average Cash). Shareholder Yield (YIELD) is calculated as the CAGR of Dividend Yield - Change in Shares Outstanding. The Weighted Average Cost of Capital (WACC) is displayed at the top left of the table and is derived from the current Market Cap (MC), Debt, Cost of Equity, and Cost of Debt. The Cost of Equity is calculated using the Equity Beta, Index Return, and Risk-Free Rate, which are based on the selected country. The Equity Beta (β) is calculated as the 5-year Blume-adjusted beta between the weekly logarithmic returns of the underlying stock and the selected country’s stock market index. For accurate calculations, it is recommended to use the stock ticker listed on the primary exchange corresponding to the company’s main index.
Cost of Debt = (Interest Expense on Debt ÷ Average Debt) × (1 - Average Tax Rate)
Cost of Equity = Risk-Free Rate + Equity Beta (β) × (Index Return - Risk-Free Rate)
WACC = (MC ÷ (MC + Debt)) × Cost of Equity + (Debt ÷ (MC + Debt)) × Cost of Debt
This indicator works best for operationally stable and profitable companies that are primarily valued based on fundamentals rather than speculative growth, such as those in the industrial, consumer, technology, and healthcare sectors. It is less suitable for early-stage, unprofitable, or highly cyclical companies, including energy, real estate, and financial institutions, as these often have irregular cash flows or distorted balance sheets. It is also worth noting that TradingView’s financial data provider, FactSet, standardizes financial data from official company filings to align with a consistent accounting framework. While this improves comparability across companies, industries, and countries, it may also result in differences from officially reported figures.
In summary, the Intrinsic Value Analyzer is a comprehensive valuation tool designed to help long-term investors estimate a company’s fair value while comparing historical averages with the latest values. Fair value estimates are driven by growth forecasts, target multiples, and discount rates, and should always be interpreted within the context of the underlying assumptions. By default, the model applies historical averages and current discount rates, which may not accurately reflect future conditions. Investors are therefore encouraged to adjust inputs in the menu to better understand how changes in these key assumptions influence the company’s fair value.
XAUUSD Watchdog — FVG + BOS (Lite, v6)smart-money structure and FVG alert tool for XAUUSD with auto 1 : R targets.
Simplified Percentile ClusteringSimplified Percentile Clustering (SPC) is a clustering system for trend regime analysis.
Instead of relying on heavy iterative algorithms such as k-means, SPC takes a deterministic approach: it uses percentiles and running averages to form cluster centers directly from the data, producing smooth, interpretable market state segmentation that updates live with every bar.
Most clustering algorithms are designed for offline datasets, they require recomputation, multiple iterations, and fixed sample sizes.
SPC borrows from both statistical normalization and distance-based clustering theory , but simplifies them. Percentiles ensure that cluster centers are resistant to outliers , while the running mean provides a stable mid-point reference.
Unlike iterative methods, SPC’s centers evolve smoothly with time, ideal for charts that must update in real time without sudden reclassification noise.
SPC provides a simple yet powerful clustering heuristic that:
Runs continuously in a charting environment,
Remains interpretable and reproducible,
And allows traders to see how close the current market state is to transitioning between regimes.
Clustering by Percentiles
Traditional clustering methods find centers through iteration. SPC defines them deterministically using three simple statistics within a moving window:
Lower percentile (p_low) → captures the lower basin of feature values.
Upper percentile (p_high) → captures the upper basin.
Mean (mid) → represents the central tendency.
From these, SPC computes stable “centers”:
// K = 2 → two regimes (e.g., bullish / bearish)
=
// K = 3 → adds a neutral zone
=
These centers move gradually with the market, forming live regime boundaries without ever needing convergence steps.
Two clusters capture directional bias; three clusters add a neutral ‘range’ state.
Multi-Feature Fusion
While SPC can cluster a single feature such as RSI, CCI, Fisher Transform, DMI, Z-Score, or the price-to-MA ratio (MAR), its real strength lies in feature fusion. Each feature adds a unique lens to the clustering system. By toggling features on or off, traders can test how each dimension contributes to the regime structure.
In “Clusters” mode, SPC measures how far the current bar is from each cluster center across all enabled features, averages these distances, and assigns the bar to the nearest combined center. This effectively creates a multi-dimensional regime map , where each feature contributes equally to defining the overall market state.
The fusion distance is computed as:
dist := (rsi_d * on_off(use_rsi) + cci_d * on_off(use_cci) + fis_d * on_off(use_fis) + dmi_d * on_off(use_dmi) + zsc_d * on_off(use_zsc) + mar_d * on_off(use_mar)) / (on_off(use_rsi) + on_off(use_cci) + on_off(use_fis) + on_off(use_dmi) + on_off(use_zsc) + on_off(use_mar))
Because each feature can be standardized (Z-Score), the distances remain comparable across different scales.
Fusion mode combines multiple standardized features into a single smooth regime signal.
Visualizing Proximity - The Transition Gradient
Most indicators show binary or discrete conditions (e.g., bullish/bearish). SPC goes further, it quantifies how close the current value is to flipping into the next cluster.
It measures the distances to the two nearest cluster centers and interpolates between them:
rel_pos = min_dist / (min_dist + second_min_dist)
real_clust = cluster_val + (second_val - cluster_val) * rel_pos
This real_clust output forms a continuous line that moves smoothly between clusters:
Near 0.0 → firmly within the current regime
Around 0.5 → balanced between clusters (transition zone)
Near 1.0 → about to flip into the next regime
Smooth interpolation reveals when the market is close to a regime change.
How to Tune the Parameters
SPC includes intuitive parameters to adapt sensitivity and stability:
K Clusters (2–3): Defines the number of regimes. K = 2 for trend/range distinction, K = 3 for trend/neutral transitions.
Lookback: Determines the number of past bars used for percentile and mean calculations. Higher = smoother, more stable clusters. Lower = faster reaction to new trends.
Lower / Upper Percentiles: Define what counts as “low” and “high” states. Adjust to widen or tighten cluster ranges.
Shorter lookbacks react quickly to shifts; longer lookbacks smooth the clusters.
Visual Interpretation
In “Clusters” mode, SPC plots:
A colored histogram for each cluster (red, orange, green depending on K)
Horizontal guide lines separating cluster levels
Smooth proximity transitions between states
Each bar’s color also changes based on its assigned cluster, allowing quick recognition of when the market transitions between regimes.
Cluster bands visualize regime structure and transitions at a glance.
Practical Applications
Identify market regimes (bullish, neutral, bearish) in real time
Detect early transition phases before a trend flip occurs
Fuse multiple indicators into a single consistent signal
Engineer interpretable features for machine-learning research
Build adaptive filters or hybrid signals based on cluster proximity
Final Notes
Simplified Percentile Clustering (SPC) provides a balance between mathematical rigor and visual intuition. It replaces complex iterative algorithms with a clear, deterministic logic that any trader can understand, and yet retains the multidimensional insight of a fusion-based clustering system.
Use SPC to study how different indicators align, how regimes evolve, and how transitions emerge in real time. It’s not about predicting; it’s about seeing the structure of the market unfold.
Disclaimer
This indicator is intended for educational and analytical use.
It does not generate buy or sell signals.
Historical regime transitions are not indicative of future performance.
Always validate insights with independent analysis before making trading decisions.
Major Rotation System -> PROFABIGHI_CAPITAL🌟 Overview
The Major Rotation System → PROFABIGHI_CAPITAL indicator evaluates multiple assets using a blend of momentum, volatility, and relative strength metrics to identify rotation opportunities. It scores and ranks assets for potential long positions, simulates backtested performance with customizable leverage and costs, and visualizes results through dynamic tables for quick decision-making in portfolio rotation strategies.
📅 Backtest Settings
- Leverage multiplier to scale position sizes during simulated trading
- Starting date to define the historical period for performance calculations
- Slippage percentage to account for execution delays in entries/exits
- Commission percentage to factor in trading fees for realistic equity tracking
📊 Table Visibility
- Toggle for overall metrics tables showing drawdown, ratios, and returns
- Enable ranking table to highlight top-scoring assets by score and beta
- Display main table for indicator values and condition scores across assets
- Show strategy table for system vs. buy-and-hold comparisons
- Activate relative strength ranking table for asset outperformance hierarchy
⚙️ General Settings
- Evaluation mode selection between aggressive (threshold-based averaging) and conservative (all-conditions-met) scoring
- Number of assets to analyze, up to a maximum for multi-symbol rotation
- Count of top assets to feature in summary rankings
- Bullish threshold for minimum average score to qualify as a rotation candidate
- Weighting factor for specific asset indicators in overall scoring
🔧 Indicator Selection
- Enable short-period RSI for quick momentum detection
- Include longer-period RSI for trend confirmation
- Activate Sharpe ratio for risk-adjusted performance evaluation
- Use short-term rate of change for immediate price acceleration signals
- Incorporate medium-term rate of change for sustained momentum
- Add long-term rate of change for broader trend alignment
- Toggle momentum-applied RSI for velocity-based insights
- Enable price delta RSI for change-rate momentum
- Include relative strength for comparative outperformance scoring
🎯 Specific Indicators
- Custom signal toggle for leading asset like BTC with RSI and median deviation logic
- Dedicated indicator enable for ETH using ALMA, HMA, and volatility stops
- Specialized signal activation for SOL combining RSI, median, ALMA, and parabolic SAR
📈 RSI Parameters
- Source selection for RSI base calculation
- Period adjustment for sensitivity in each RSI variant
- First smoothing MA type and length for noise reduction
- Second MA type and length for dual-line crossover confirmation
- Enable second MA comparison for directional bias scoring
- VIDYA volatility lookback for adaptive smoothing in variable markets
📈 ROC Parameters
- Period settings for short, medium, and long rate-of-change measurements
📊 Sharpe Ratio Parameters
- Lookback period for return and volatility computation
- Smoothing period to stabilize ratio readings
- Buy and sell thresholds for bullish/bearish signal generation
📊 Momentum RSI Parameters
- Momentum period for underlying velocity input
- RSI period applied to momentum for oscillator creation
- Smoothing options including dual MA types and lengths
- Second MA enable for comparative scoring
- VIDYA volatility adjustment for dynamic response
📊 Price Delta RSI Parameters
- Condition type choice between raw delta or RSI-applied delta
- Delta period for price change measurement
- RSI period for delta transformation
- Smoothing MA configurations for refined signals
- Dual MA enable and VIDYA volatility for adaptability
📊 Relative Strength Parameters
- Period for RS ratio computation against benchmark
- Primary MA type and length for RS smoothing
- Second MA enable for enhanced confirmation
- VIDYA volatility lookback for market-adaptive RS
📊 Beta Parameters
- Benchmark symbol for market correlation assessment
- Lookback period for covariance and variance calculations
💱 Assets
- Up to seven customizable symbol inputs for rotation candidates
- Automatic security requests for close prices across selected assets
📊 Scoring & Ranking Logic
- Individual condition checks for each enabled indicator yielding binary scores
- Aggregation into average score with optional specific indicator weighting
- Conservative mode requires unanimous condition satisfaction; aggressive uses thresholded averages
- Relative strength ranking via array-based sorting for top performer identification
- Beta integration as tiebreaker in final asset prioritization
🏆 Backtest Framework
- Dynamic long signals based on top eligible assets exceeding score threshold
- Equal weighting across qualified assets for diversified rotation
- Equity curve simulation incorporating leverage, slippage, and commissions
- HODL baseline for equal-weighted buy-and-hold comparison
- Performance metrics computation including drawdown, Sharpe, Sortino, and Omega ratios
📉 Visualization
- Equity curve plot with filled area highlighting returns from inception
- Vertical line and label at backtest start for reference
- RS ranking table at top center showing ranks, assets, and scores
- Main indicator table at top right with values and condition binaries
- Ranking table at bottom left for top assets by score and beta
- Metrics tables at bottom center/right comparing system, HODL, and individual asset stats
- Signal table at top left for specific asset custom indicators
✅ Key Takeaways
- Multi-asset rotation via scored technical confluence for opportunistic longs
- Flexible modes balance aggression with conservatism in signal generation
- Comprehensive backtesting reveals edge over passive holding strategies
- Table-driven insights streamline asset selection without chart overload
- Customizable indicators and thresholds adapt to varying market regimes
Too many secretsTOO MANY SECRETS - Extreme Condition Signal Detector
This indicator identifies extreme market conditions and provides clear TOP and BOTTOM signals when specific criteria are met. Designed for traders who want reliable entry points without the noise.
KEY FEATURES:
No Repaint - Once a signal prints, it's locked in and will not disappear or change
Smart Filtering - The Blackbox and other proprietary modules prevent signal spam, ensuring only high-quality setups trigger alerts
Customizable Alerts - Use as a multi-symbol screener across different timeframes
Visual Strike Lines - Optional vertical lines mark exact signal locations with adjustable transparency
Clean Interface - Minimal chart clutter with maximum information
CLASSIFIED METHODOLOGY:
The internal workings of this indicator, including the Blackbox module and other signal processing components, are intentionally classified. The specific calculations, timeframes, and confluence requirements remain undisclosed.
RECOMMENDED USAGE:
Best viewed on 5 minute charts
Configure alerts to monitor multiple symbols simultaneously
Adjustable Blackbox parameter allows fine-tuning for your trading style
IMPORTANT NOTES:
Bar Replay: Signals only appear on 5x or faster speeds during replay. In live trading, signals appear instantly in real-time.
This is highly experimental. Not financial advice - trade at your own risk.
WHAT YOU GET:
TOP signals (red triangles) for potential bearish reversals
BOTTOM signals (green triangles) for potential bullish reversals
Alert conditions for automated notifications
Splash screen with setup guidance (can be toggled off)
The Eligible Asset Power Table (Backtest) -> PROFABIGHI_CAPITAL🌟 Overview
The Eligible Asset Power Table (Backtest) → PROFABIGHI_CAPITAL indicator evaluates a portfolio of assets using multi-indicator scoring to identify eligible performers for rotational strategies, generating dynamic rankings and condition breakdowns while simulating backtested equity curves with cost modeling and comparative metrics for systematic asset selection.
🔧 Imports & Colors
- Library integration for advanced plotting and performance calculations
- Custom palette setup ensuring consistent visual themes for tables and curves
📅 Backtest Settings
- Leverage multiplier for scaling simulated position sizes
- Start date to initiate backtest period for focused analysis
- Slippage percentage to incorporate realistic execution friction
- Commission percentage for accurate fee deduction in simulations
- Toggle for displaying detailed metrics tables on the chart
- Toggle for showing per-asset condition score breakdowns
⚙️ General Settings
- Evaluation mode between aggressive averaging or conservative full-consensus
- Number of assets to screen and score for the portfolio
- Count of top-ranked assets to feature in the display table
- Bullish threshold minimum for eligibility in aggressive evaluations
📊 Indicator Selection
- Toggle for short-period RSI inclusion in asset evaluations
- Toggle for longer-period RSI for broader trend assessment
- Toggle for Sharpe ratio to factor risk-adjusted returns
- Toggles for multiple ROC horizons to layer momentum signals
- Toggle for momentum-applied RSI for velocity confirmation
- Toggle for price delta RSI to capture directional shifts
📈 RSI #1 Parameters
- Data source choice for the first RSI oscillator
- Period length for short-term RSI calculation
- First smoothing MA type and length for noise reduction
- Second smoothing MA type and length for crossover signals
- Enable option for dual-MA comparison logic
- VIDYA volatility lookback for adaptive response
📈 RSI #2 Parameters
- Period length for medium-term RSI calculation
- First smoothing MA type and length for noise reduction
- Second smoothing MA type and length for crossover signals
- Enable option for dual-MA comparison logic
- VIDYA volatility lookback for adaptive response
📈 ROC Parameters
- Short, medium, and long lookback periods for rate-of-change measures
📊 Sharpe Ratio Parameters
- Lookback for return and volatility sampling in ratio computation
- Smoothing period to refine raw Sharpe values
- Buy threshold for positive efficiency signals
- Sell threshold for underperformance flags
📈 Momentum RSI Parameters
- Momentum calculation period for input to RSI
- RSI period applied to momentum series
- First smoothing MA type and length for refinement
- Second smoothing MA type and length for crossover signals
- Enable option for dual-MA comparison logic
- VIDYA volatility lookback for adaptive response
📈 Price Delta RSI Parameters
- Condition type between raw delta or RSI-transformed
- Price delta lookback period
- RSI period for delta series
- First smoothing MA type and length for refinement
- Second smoothing MA type and length for crossover signals
- Enable option for dual-MA comparison logic
- VIDYA volatility lookback for adaptive response
🛡️ Beta Parameters
- Benchmark symbol for relative volatility calculation
- Lookback period for covariance and variance in beta
💰 Assets
- Up to 39 customizable symbols for portfolio screening
- Sequential inputs for straightforward watchlist assembly
🔧 Technical Indicators Functions
- Multi-type MA application including adaptive VIDYA for smoothing
- Sharpe ratio with annualization and smoothing for efficiency
- Layered ROC computations for momentum across scales
- Beta calculation via benchmark covariance for relative risk
📊 Asset Metrics & Conditions
- Per-asset indicator evaluation with mode-specific binary scoring
- Dynamic aggregation counting only enabled conditions
- Average or consensus logic based on evaluation mode
- Final eligibility blending for comprehensive ranking
📦 Instrument Variables
- Persistent price series storage for all assets
- Array handling for scalable instrument management
💾 Data Storage
- Arrays capturing names, values, scores, and flags for indicators
- Comprehensive tracking across RSI, ROC, Sharpe, momentum, delta, beta
📥 Data Fetching
- Conditional security calls per enabled asset
- Parallel metrics computation and array population
- Robust handling for varying asset counts
📋 Asset Conditions Table
- Multi-column top-center display of assets and indicator passes
- Color-coded cells for quick pass/fail scanning
- Beta shown as N/A if unavailable
- Score highlighting for threshold exceedance
🏆 Backtest Logic & Ranking
- Descending score sort for top-performer prioritization
- Threshold filtering to build eligible pool
- Long signal assignment to ranked assets
- Position state arrays for tracking changes
📊 HODL Calculations
- Equal-weight hold simulation across all assets
- Cumulative performance from start date
💹 Equity Calculations
- Rotational equity paths based on eligible signals
- Leveraged position simulations per asset
📈 Change Calculations
- Daily percentage shifts for weighted return aggregation
⚖️ Weights Calculations
- Equal allocation among top eligible assets
- Dynamic sizing based on ranking pool
📊 Prev Weights
- Persistent array for prior period allocations in cost modeling
💰 Corrected Equity with Costs
- Slippage and commission deduction on position changes
- Weighted base return using previous allocations
- Compounded equity growth with cost adjustments
- Previous state updates for next iteration
📊 Performance Metrics
- Drawdown, Sharpe, Sortino, Omega across system and individuals
- Array aggregation for table population
🏆 Ranking Table
- Bottom-left sorted display of top assets by score
- Clean name extraction for readability
- Score formatting to three decimals
📈 Visualization
- Equity curve with shaded growth and return label
- Inception line and label at start date
- Dynamic bar labeling for cumulative returns
📊 Metrics Tables
- Split panels for asset performance breakdown
- Columns covering drawdown, Sharpe, Sortino, Omega, returns
- System summary and hold comparison rows
- Full/simple modes for detail control
- Compact view when tables disabled
📊 Benchmark Hold Table
- Right-side comparison of hold strategy metrics
- Threshold-based cell coloring for performance
- Benchmark-specific Sharpe, Sortino, Omega, drawdown, returns
🔔 Alerts
- Confirmed bar notifications of top eligible assets
- Fallback for no qualifiers
- Comma-separated list for easy reference
✅ Key Takeaways
- Multi-indicator eligibility scoring ranks assets for rotation
- Backtest with costs models realistic portfolio performance
- Condition tables expose signal contributions per asset
- Toggle flexibility suits aggressive or conservative approaches
- Metrics compare against holds and benchmarks for validation
- Visual curves track simulated growth with clear markers
ALISH WEEK LABELS THE ALISH WEEK LABELS
Overview
This indicator programmatically delineates each trading week and encapsulates its realized price range in a live-updating, filled rectangle. A week is defined in America/Toronto time from Monday 00:00 to Friday 16:00. Weekly market open to market close, For every week, the script draws:
a vertical start line at the first bar of Monday 00:00,
a vertical end line at the first bar at/after Friday 16:00, and
a white, semi-transparent box whose top tracks the highest price and whose bottom tracks the lowest price observed between those two temporal boundaries.
The drawing is timeframe-agnostic (M1 → 1D): the box expands in real time while the week is open and freezes at the close boundary.
Time Reference and Session Boundaries
All scheduling decisions are computed with time functions called using the fixed timezone string "America/Toronto", ensuring correct behavior across DST transitions without relying on chart timezone. The start condition is met at the first bar where (dayofweek == Monday && hour == 0 && minute == 0); on higher timeframes where an exact 00:00 bar may not exist, a fallback checks for the first Monday bar using ta.change(dayofweek). The close condition is met on the first bar at or after Friday 16:00 (Toronto), which guarantees deterministic closure on intraday and higher timeframes.
State Model
The indicator maintains minimal persistent state using var globals:
week_open (bool): whether the current weekly session is active.
wk_hi / wk_lo (float): rolling extrema for the active week.
wk_box (box): the graphical rectangle spanning × .
wk_start_line and a transient wk_end_line (line): vertical delimiters at the week’s start and end.
Two dynamic arrays (boxes, vlines) store object handles to support bounded history and deterministic garbage collection.
Update Cycle (Per Bar)
On each bar the script executes the following pipeline:
Start Check: If no week is open and the start condition is satisfied, instantiate wk_box anchored at the current bar_index, prime wk_hi/wk_lo with the bar’s high/low, create the start line, and push both handles to their arrays.
Accrual (while week_open): Update wk_hi/wk_lo using math.max/min with current bar extremes. Propagate those values to the active wk_box via box.set_top/bottom and slide box.set_right to the current bar_index to keep the box flush with live price.
Close Check: If at/after Friday 16:00, finalize the week by freezing the right edge (box.set_right), drawing the end line, pushing its handle, and flipping week_open false.
Retention Pruning: Enforce a hard cap on historical elements by deleting the oldest objects when counts exceed configured limits.
Drawing Semantics
The range container is a filled white rectangle (bgcolor = color.new(color.white, 100 − opacity)), with a solid white border for clear contrast on dark or light themes. Start/end boundaries are full-height vertical white lines (y1=+1e10, y2=−1e10) to guarantee visibility across auto-scaled y-axes. This approach avoids reliance on price-dependent anchors for the lines and is robust to large volatility spikes.
Multi-Timeframe Behavior
Because session logic is driven by wall-clock time in the Toronto zone, the indicator remains consistent across chart resolutions. On coarse timeframes where an exact boundary bar might not exist, the script legally approximates by triggering on the first available bar within or immediately after the boundary (e.g., Friday 16:00 occurs between two 4-hour bars). The box therefore represents the true realized high/low of the bars present in that timeframe, which is the correct visual for that resolution.
Inputs and Defaults
Weeks to keep (show_weeks_back): integer, default 40. Controls retention of historical boxes/lines to avoid UI clutter and resource overhead.
Fill opacity (fill_opacity): integer 0–100, default 88. Controls how solid the white fill appears; border color is fixed pure white for crisp edges.
Time zone is intentionally fixed to "America/Toronto" to match the strategy definition and maintain consistent historical backtesting.
Performance and Limits
Objects are reused only within a week; upon closure, handles are stored and later purged when history limits are exceeded. The script sets generous but safe caps (max_boxes_count/max_lines_count) to accommodate 40 weeks while preserving Editor constraints. Per-bar work is O(1), and pruning loops are bounded by the configured history length, keeping runtime predictable on long histories.
Edge Cases and Guarantees
DST Transitions: Using a fixed IANA time zone ensures Friday 16:00 and Monday 00:00 boundaries shift correctly when DST changes in Toronto.
Weekend Gaps/Holidays: If the market lacks bars exactly at boundaries, the nearest subsequent bar triggers the start/close logic; range statistics still reflect observed prices.
Live vs Historical: During live sessions the box edge advances every bar; when replaying history or backtesting, the same rules apply deterministically.
Scope (Intentional Simplicity)
This tool is strictly a visual framing indicator. It does not compute labels, statistics, alerts, or extended S/R projections. Its single responsibility is to clearly present the week’s realized range in the Toronto session window so you can layer your own execution or analytics on top.
ATEŞ-19 TARAMA MODÜLÜ)This published scanning module is intended for support and educational purposes only.
It does not constitute investment advice under any circumstances.
You should make your buy and sell decisions based on your own strategies and risk management.
This module may be used as a supportive tool to assist in your investment process.
EMA Fractal and vwap - FIMIDOIt is a testing only strategy with alerts - FOR MNQ and MES Futures
This script implements a multi-indicator-based approach to generate long (buy) and short (sell) signals, incorporating elements like Exponential Moving Averages (EMAs), WaveTrend, volume filters, Cumulative Volume Delta (CVD) trends, fractal prime zones, and Volume Weighted Average Price (VWAP) with trend-based coloring. It includes risk management features such as stop-loss, take-profit, position sizing based on account risk, daily loss limits, and trade pauses after losses. The strategy is highly configurable through user inputs, allowing traders to enable/disable various filters and trade types.
Important Note: This script is still in the testing phase. It has not been fully optimized or backtested across various market conditions, instruments, or timeframes. Users should thoroughly test it in a simulated environment before applying it to live trading, as it may contain bugs, inefficiencies, or unintended behaviors. Past performance in backtests does not guarantee future results, and trading involves significant financial risk.
Key Features and Structure
The script is structured into sections: inputs, functions, calculations, trading filters, strategy logic, plots, alerts, and visual elements. It operates as a strategy overlay on price charts, meaning it plots indicators directly on the main chart and executes hypothetical trades based on defined rules.
Strategy Parameters:
Initial capital: Starts with $50,000 (configurable).
Margin: 1% for both long and short positions.
Overlay: True, so it displays on the price chart.
Inputs
The script provides extensive user-configurable inputs grouped by category for ease of use:
Risk Management:
Risk % of Account: Percentage of equity risked per trade (default: 2%).
Risk-Reward Ratio: Multiplier for take-profit relative to stop-loss (default: 1.7).
Max Daily Loss %: Stops trading if daily losses exceed this threshold (default: 0.4%).
Stop-Loss Points Buffer: Adjusts stop-loss placement (default: -8.1 points).
Max Trades per Day: Limits trades per session (default: 3).
Pause Candles After Loss: Halts trading for a set number of bars after a losing trade (default: 19).
Trading Hours:
Start/End Hour: Restricts trading to specific hours (default: 6 AM to 9 AM, in 24-hour format).
Trade Types:
Enable Long/Short Trades: Toggles long (buy) or short (sell) positions (both default: true).
VWAP Filter Settings:
Use VWAP Filter: Requires buys above VWAP and sells below (default: true).
VWAP Trend Length: Period for trend calculation (default: 5 bars).
VWAP Trend Threshold: Minimum change for considering a trend (default: 0.0 points).
Disable Trades on Flat VWAP: Prevents trades when VWAP is gray (flat trend) (default: true).
EMA Settings:
EMA Master Length: A base EMA for general filtering (default: 6).
Separate EMA configurations for long and short trades, including smoothing types (RMA, SMA, EMA, WMA) and fast/slow lengths.
WaveTrend Settings:
Use WaveTrend: Enables momentum-based signals (default: false).
Channel, Average, and MA lengths for customization.
Volume Filter Settings:
Separate filters for long/short with MA lengths and threshold multipliers to ensure high-volume conditions.
CVD Trend Settings:
Use CVD for long/short: Filters based on volume delta trends using ATR multipliers and lengths.
Fractal Prime Zones Settings:
Use Fractal: Enables support/resistance zones based on fractals (default: true).
Length, sensitivity, and options to include volume delta or show labels.
These inputs allow for fine-tuning the strategy to different assets or market conditions.
Functions
Two main helper functions are defined:
f_wavetrend: Calculates WaveTrend values using EMAs on a custom source, producing two lines (WT1 and WT2) for crossover detection.
f_ema: A simple EMA wrapper (though it uses built-in ta.ema).
ma_function: A versatile moving average calculator supporting RMA, SMA, EMA, or WMA based on user selection.
Calculations
The core of the script involves computing multiple indicators:
VWAP: Based on HLC3 (high-low-close average), anchored daily. It's plotted with dynamic coloring: green for upward trend, red for downward, and gray for flat (based on slope over the trend length and threshold).
Volume Filters: SMA-based checks to ensure volume exceeds a threshold multiple.
EMAs: Custom fast/slow EMAs for long/short, with crossovers/crossunders generating signals.
WaveTrend: Momentum oscillator with cross detection for up/down signals.
CVD Trends: Bollinger-like bands using SMA and ATR multiples to detect uptrends (close above upper band) or downtrends.
Fractal Prime Zones: Advanced zones using prime numbers, ATR, and optional CVD. Calculates density-based upper/lower zones, identifies support/resistance, and generates buy/sell signals on zone breaks.
Trading Window and Counters: Checks time of day, resets daily trade counts, and manages pause after losses.
Risk Calculations: Dynamically computes position size based on risk amount, stop-loss distance, and equity.
Entry signals (buyTriangle and sellTriangle) combine these: All enabled filters must pass (e.g., EMA crossover, high volume, CVD trend, fractal signal, VWAP position, and trending VWAP if filtered).
Strategy Logic
Entry Conditions: Triggers long/short entries only if signals align, within trading hours, under max trades/day, not paused, and daily loss not exceeded.
Stop-loss: Placed below low (long) or above high (short) with buffer.
Position Size: Floored to nearest integer based on risk amount divided by per-unit risk.
Take-Profit: Set at entry price plus/minus (risk distance * RR ratio).
Exits: Via strategy.exit with stop and limit orders.
Loss Handling: Updates daily loss on trade close; pauses if loss occurs.
No Trades on Flat VWAP: If enabled, skips entries when VWAP trend is neutral (gray).
Plots and Visuals
Shapes: Triangles for buy (blue, below bar) and sell (red, above bar) signals.
VWAP Line: Colored dynamically.
Fractal Zones: Plotted with fill and optional labels for support/resistance.
Debug Plots: Characters for trading window, pause, and max trades exceeded.
TP/SL Lines: Drawn as arrows on entries.
Daily Loss Table: Displays current loss and limit in a bottom-right table.
Alerts
Generates alerts on entries with details: entry price, SL, TP.
This strategy emphasizes trend-following with filters to reduce false signals, but its complexity may lead to over-optimization. Again, as it is still in the testing phase, users are advised to backtest extensively, forward-test on demo accounts, and monitor for issues like slippage, commissions, or market regime changes before real-world use. If you need modifications or further analysis, let me know!
SEVENX Free|SuperFundedSEVENX — Modular Multi-Signal Scanner (SuperFunded)
What it is
SEVENX combines seven classic signals—MACD, OBV, RSI, Stochastics, CCI, Momentum, and an optional ATR volatility filter—into a modular gate. You can toggle each condition on/off, and a BUY/SELL arrow prints only when all enabled conditions agree. Text labels are optional.
Why this is not a simple mashup
・Most “combo” scripts just overlay indicators. SEVENX is a strict consensus engine:
・Each condition is binary and user-switchable.
・The final signal is the logical AND of all enabled checks (no hidden weights).
・Signals fire only on confirmed events (e.g., RSI crossing a level, Stoch K/D cross), which makes entries rule-driven and reproducible.
This yields a transparent, vendor-grade workflow where traders can start simple (2–3 gates) and tighten selectivity by enabling more gates.
How it works (concise)
・MACD: macd_line > signal_line (buy) / < (sell).
・OBV trend: OBV > OBV_MA (buy) / < (sell).
・RSI bounce/drop: crossover(RSI, Oversold) (buy) / crossunder(RSI, Overbought) (sell).
・Stoch cross: %K crosses above %D (buy) / below (sell).
・CCI rebound/pullback: crossover(CCI, -Level) (buy) / crossunder(CCI, +Level) (sell).
・Momentum: Momentum > 0 (buy) / < 0 (sell).
・ATR filter (optional): ATR > ATR_MA must also be true (both sides).
・Final signal: AND of all enabled conditions. If you enable none on a side, that side will not print.
Parameters (UI mapping)
Buy Signal (group: “— Buy Signal —”)
・MACD Golden Cross / OBV Uptrend / RSI Bounce from Oversold / Stochastic Golden Cross / CCI Rebound from Oversold / Momentum > 0 / ATR Volatility Filter (on/off)
Sell Signal (group: “— Sell Signal —”)
・MACD Dead Cross / OBV Downtrend / RSI Drop from Overbought / Stochastic Dead Cross / CCI Pullback from Overbought / Momentum < 0 / ATR Volatility Filter (on/off)
Indicator Settings
・MACD: Fast/Slow/Signal lengths.
・RSI: Length, Overbought/Oversold levels.
・Stochastics: %K length, %D smoothing, overall smoothing.
・CCI: Length, Level (±Level used).
・Momentum: Length.
・OBV: MA length for trend baseline.
・ATR: ATR length, ATR MA length (for the filter).
Display
・Show Text (BUY/SELL text on the markers), Buy/Sell Text Colors.
Practical usage
・Start simple: Enable 2 conditions (e.g., MACD + RSI). If signals are too frequent, add OBV or Momentum; if still frequent, enable ATR filter.
・Mean-reversion vs trend:
・For trend-following, prefer MACD/OBV/Momentum gates.
・For reversal bounces, add RSI/CCI gates and keep Stoch for timing.
・Tuning sensitivity:
・Raise RSI Oversold/Overbought thresholds to make bounces rarer.
・Increase ATR_MA length to smooth the volatility baseline.
・Risk first: Plan SL/TP independently (e.g., structure levels or R-multiples). SEVENX focuses on entry qualification, not exits.
Repainting & confirmation
Signals depend on cross events and are best treated on bar close. Intrabar flips can occur before a bar closes; for strict rules, confirm on closed bars in your strategy.
Disclaimer
No indicator can guarantee outcomes. News, liquidity, and spread conditions can invalidate signals. Trade responsibly and manage risk.
This indicator is being released on a trial basis and may be discontinued at our discretion.
SEVENX — モジュラー型マルチシグナル・スキャナー（日本語）
概要
SEVENXは、MACD / OBV / RSI / ストキャス / CCI / モメンタム / ATRフィルターの7条件を個別オン・オフで制御し、有効化した条件がすべて満たされたときだけBUY/SELL矢印を表示する、合意（AND）型シグナルインジです。テキスト表示も任意。
独自性・新規性
・各条件はブラックボックスではなく明示的なブール判定で、最終シグナルは有効化した条件のAND。
・RSIのレベルクロスやStochのK/Dクロスなど、確定イベントで判定するため、再現性の高いルール運用が可能。少数条件から始めて、必要に応じて段階的に厳格化できます。
動作要点
・MACD：線がシグナル上/下。
・OBV：OBVがOBVのMAより上/下。
・RSI：RSIがOSを上抜け（買い）/OBを下抜け（売り）。
・Stoch：%Kが%Dを上抜け/下抜け。
・CCI：CCIが**−Levelを上抜け**（買い）/+Levelを下抜け（売り）。
・Momentum：0より上/下。
・ATRフィルター（任意）：ATR > ATR_MA を満たすこと（買い/売り共通）。
・最終サイン：有効化した条件のAND。そのサイドで1つも有効化していなければサインは出ません。
実践ヒント
・まずは2条件（例：MACD＋RSI）でテスト → 多すぎるならOBV/MomentumやATRフィルターを追加。
・トレンド重視：MACD/OBV/Momentumを主軸に。
・押し目・戻り目狙い：RSI/CCIを追加、Stochでタイミング調整。
・感度調整：RSIのOB/OSを広げる、ATR_MAを長くする等で厳しめに。
・出口は別設計：SL/TPは価格帯やR倍数などで管理を。
再描画と確定
確定足基準で判断すると安定します。足確定前はクロスが行き来することがあります。
免責
シグナルの機能は保証されません。イベントや流動性で無効化する場合があります。資金管理のうえ自己責任でご利用ください。
このインジケーターは試験公開のため、弊社の裁量で公開を停止する場合があります。
ICT Smart Entry - Auto Adaptive Dual Gold & BTC (v6 Light)Publication Description (English first, detailed)
What this script does (originality & concept):
This is a closed-form ICT-style Smart Entry helper designed specifically for Gold (XAUUSD) and Bitcoin (BTCUSD). It fuses four components into a single flow: (1) swing-based market structure (BOS up/down), (2) fair-value-gap presence to filter weak breaks, (3) liquidity sweep context using recent local extremes, and (4) an auto-adaptive threshold that scales with ATR to avoid false breaks in calm markets and over-sensitivity in volatile regimes. When a valid BOS aligns with context (FVG + sweep), the tool derives the most recent opposite candle and builds an Order Block (OB) zone. Entries are signaled only when price revisits the OB and a cooldown is respected.
How the components work together:
Adaptive threshold (ATR): compares current ATR to a long ATR average and sets the BOS strength dynamically (Calm/Normal/Volatile).
BOS & swings: detects last swing high/low and requires the close to exceed it by a dynamic ATR multiple.
FVG filter: requires a simple two-bar imbalance (bull/bear) around the break to represent displacement.
Liquidity sweep: checks if recent local highs/lows were swept before the break to bias entries.
OB derivation: finds the last opposite candle within a lookback window and builds a forward-extended box.
Execution helper: when price trades back inside the OB, it prints an entry label plus SL at the opposite side of the box and two fixed R targets (1R and 2R). Alerts are provided for BUY/SELL entries.
How to use it:
Add to any chart (built for XAUUSD & BTCUSD; works on others too).
Choose your session, swing lengths, lookback, and cooldown. Leave “Enable Auto Adaptation” on by default.
Wait for an OB to appear after a valid BOS+FVG+sweep.
When price returns to the box, consider the printed entry with SL at the other side of the box and 1R/2R targets.
Optional: Use higher-TF bias confluence and your own risk rules.
Notes & limits:
This is an execution assistant, not a full strategy. It does not place orders or guarantee results.
OBs are regenerated; only the latest box is kept for clarity.
Alerts fire on entry confirmation only.
Past performance is not indicative of future results.
Inputs (summary): ATR period; swing lengths; OB lookback & extension; session filter; cooldown bars.
Arabic (for convenience):
هذا المؤشر يجمع هيكلة السوق (BOS)، وفجوة القيمة العادلة (FVG)، وسياق سحب السيولة، مع عتبة متكيفة بالـATR. عند تحقق BOS قوي مع FVG وسحب سيولة، يحدد آخر شمعة معاكسة ويُنشئ منطقة OB. عند عودة السعر للصندوق، يظهر دخول مع SL عند الجهة المقابلة وهدفين 1R/2R. يفضّل استخدامه مع تأكيدات من فريم أعلى وإدارة مخاطر صارمة. هذا أداة مساعدة وليست إستراتيجية تنفيذ أوامر.
Quick compliance checklist
✅ Title: English, ASCII only (no emoji, no fancy dash).
✅ UI text: English, ASCII only here.
✅ No ALL CAPS in title/description (only acronyms like ICT/BTC).
✅ Description: Detailed, explains originality + how parts interact + how to use.
✅ Chart info: Script adds a small header label with Symbol/TF/Script name.
✅ No mashup-without-purpose: Description justifies each component and why they’re combined.
MARITradesGold Indicator A - BUY AND SELL ModelThe MARITrades Gold Indicator A – BOS Model is a professional charting tool designed to help traders visually identify structure breaks (BOS) and potential Fibonacci retracement zones during key market sessions on XAU/USD.
It combines session timing filters, Break of Structure logic, and a WMA160 trend bias to help users study clean continuation or reversal setups with precision.
This indicator is intended for traders who are learning or refining their market structure and session-based gold strategy.
KEY FEATURES AND HOW TO USE
Apply the indicator to XAU/USD on a preferred timeframe
Wait for a Break of Structure (BOS) during valid session hours.
Watch for retracement into 0.5–0.618 Fib levels for possible continuation zones which are marked out with coloured lines. you can edit the colours to your preference
Confirm direction with Moving average160 trend bias.
Use Stop loss and take profit levels for educational visualization — not for direct trade execution.
you can keep the indicator free or lines which optional to view the BUY and SELL signals
📊 BOS Detection: Marks bullish or bearish structure breaks after key levels.
📈 Fibonacci Zones: Auto-calculates retracement zones and gives you signal bias
🕒 Session Filters: Includes Sydney, Asian, London, and New York session timing tools.
🧭 Trend Filter: Moving Average (MA160) helps define directional bias.
🧩 Clean Visualization: retracement zones, and structure markers for chart clarity.
🚨 Optional Alerts: Alerts can be added when structure breaks align with session filters.
Session High/Low Marker Advanced -> PROFABIGHI_CAPITAL🌟 Overview
The Session High/Low Marker Advanced → PROFABIGHI_CAPITAL indicator tracks and visualizes the highest and lowest prices during major global trading sessions, helping traders identify key support/resistance levels formed in each period.
It supports live updates for active sessions and post-session lines with labels, plus a summary table for quick reference across markets like forex or indices.
👁️ Display Options
– Show London Session : Toggle visibility of London high/low markers for European market opens.
– Show New York Session : Enable markers for New York volatility and trend continuations.
– Show Tokyo Session : Activate Tokyo levels for Asian session analysis.
– Show Sydney Session : Optional markers for early Pacific trading influences.
– Show Frankfurt Session : Include Frankfurt for pre-London European insights.
– Show Session Table : Display a compact overview of all session extremes.
– Live Mode : Update highs/lows in real-time during sessions, rather than finalizing at close.
🎨 Session Styles
– London/New York/Tokyo/Sydney/Frankfurt Line Color : Custom transparency and hues for each session's lines and labels.
– Line Width : Adjustable thickness for session high/low extensions to match chart clarity.
📊 Table Styles
– Accent/Bull/Bear/Neutral Colors : Tints for table headers, positive/negative values, and balanced readings.
⏰ Session Detection
– Time-Based Boundaries : Defines sessions in UTC—London (08:00-17:00), New York (13:00-22:00), Tokyo (00:00-09:00), Sydney (22:00-07:00 next day), Frankfurt (07:00-16:00)—adjusting for date transitions.
– Start/End Triggers : Detects session openings and closings to reset or finalize high/low tracking.
🔄 Session Updates
– High/Low Tracking : Continuously monitors price extremes within each active session, storing bar indices for precise labeling.
– Live Visualization : Draws temporary solid lines and labels during sessions when enabled, updating on every bar.
– Post-Session Finalization : Switches to dashed extending lines and fixed labels at session end for historical reference.
📊 Session Table
– Dynamic Summary : Right-side panel listing high/low values per session with color-coded cells—bullish green for highs, bearish red for lows, neutral gray for inactive.
– Real-Time Refresh : Updates on the last bar to reflect current or completed session data.
🔔 Alerts
– High/Low Breaks : Notifies when price crosses above a session high or below a low for breakout opportunities.
– Session Starts : Announces openings of selected sessions for timing entries.
✅ Key Takeaways
– Pinpoints intraday support/resistance from global sessions to frame trades.
– Live mode enables real-time monitoring, while post-session lines aid planning.
– Custom colors and table condense multi-session data for efficient scanning.
– Alerts on breaks keep traders responsive to session-driven volatility.
NiftyScreenerNifty 50 stock screener that displays real-time technical signals for the top 10 weighted stocks. It shows key indicators like RSI, ADX, SuperTrend, EMA crossovers, price position, and MACD signals in a tabular format on the chart. Users can customize stock visibility, display position, and text size, making it a handy tool for quick, multi-indicator analysis of Indian blue-chip stocks. Perfect for intraday and swing trading, it helps identify trend strength, momentum shifts, and buy or sell signals efficiently.
