ICT Anchored Market Structures with Validation [LuxAlgo]The ICT Anchored Market Structures with Validation indicator is an advanced iteration of the original Pure-Price-Action-Structures tool, designed for price action traders.
It systematically tracks and validates key price action structures, distinguishing between true structural shifts/breaks and short-term sweeps to enhance trend and reversal analysis. The indicator automatically highlights structural points, confirms breakouts, identifies sweeps, and provides clear visual cues for short-term, intermediate-term, and long-term market structures.
A distinctive feature of this indicator is its exclusive reliance on price patterns. It does not depend on any user-defined input, ensuring that its analysis remains robust, objective, and uninfluenced by user bias, making it an effective tool for understanding market dynamics.
🔶 USAGE
Market structure is a cornerstone of price action analysis. This script automatically detects real-time market structures across short-term, intermediate-term, and long-term levels, simplifying trend analysis for traders. It assists in identifying both trend reversals and continuations with greater clarity.
Market structure shifts and breaks help traders identify changes in trend direction. A shift signals a potential reversal, often occurring when a swing high or low is breached, suggesting a transition in trend. A break, on the other hand, confirms the continuation of an established trend, reinforcing the current direction. Recognizing these shifts and breaks allows traders to anticipate price movement with greater accuracy.
It’s important to note that while a CHoCH may signal a potential trend reversal and a BoS suggests a continuation of the prevailing trend, neither guarantees a complete reversal or continuation. In some cases, CHoCH and BoS levels may act as liquidity zones or areas of consolidation rather than indicating a clear shift or continuation in market direction. The indicator’s validation component helps confirm whether the detected CHoCH and BoS are true breakouts or merely liquidity sweeps.
🔶 DETAILS
🔹 Market Structures
Market structures are derived from price action analysis, focusing on identifying key levels and patterns in the market. Swing point detection, a fundamental concept in ICT trading methodologies and teachings, plays a central role in this approach.
Swing points are automatically identified based exclusively on market movements, without requiring any user-defined input.
🔹 Utilizing Swing Points
Swing points are not identified in real-time as they form. Short-term swing points may appear with a delay of up to one bar, while the identification of intermediate and long-term swing points is entirely dependent on subsequent market movements. Importantly, this detection process is not influenced by any user-defined input, relying solely on pure price action. As a result, swing points are generally not intended for real-time trading scenarios.
Instead, traders often analyze historical swing points to understand market trends and identify potential entry and exit opportunities. By examining swing highs and lows, traders can:
Recognize Trends: Swing highs and lows provide insight into trend direction. Higher swing highs and higher swing lows signify an uptrend, while lower swing highs and lower swing lows indicate a downtrend.
Identify Support and Resistance Levels: Swing highs often act as resistance levels, referred to as Buyside Liquidity Levels in ICT terminology, while swing lows function as support levels, also known as Sellside Liquidity Levels. Traders can leverage these levels to plan their trade entries and exits.
Spot Reversal Patterns: Swing points can form key reversal patterns, such as double tops or bottoms, head and shoulders, and triangles. Recognizing these patterns can indicate potential trend reversals, enabling traders to adjust their strategies effectively.
Set Stop Loss and Take Profit Levels: In ICT teachings, swing levels represent price points with expected clusters of buy or sell orders. Traders can target these liquidity levels/pools for position accumulation or distribution, using swing points to define stop loss and take profit levels in their trades.
Overall, swing points provide valuable information about market dynamics and can assist traders in making more informed trading decisions.
🔹 Logic of Validation
The validation process in this script determines whether a detected market structure shift or break represents a confirmed breakout or a sweep.
The breakout is confirmed when the close price is significantly outside the deviation range of the last detected structural price. This deviation range is defined by the 17-period Average True Range (ATR), which creates a buffer around the detected market structure shift or break.
A sweep occurs when the price breaches the structural level within the deviation range but does not confirm a breakout. In this case, the label is updated to 'SWEEP.'
A visual box is created to represent the price range where the breakout or sweep occurs. If the validation process continues, the box is updated. This box visually highlights the price range involved in a sweep, helping traders identify liquidity events on the chart.
🔶 SETTINGS
The settings for Short-Term, Intermediate-Term, and Long-Term Structures are organized into groups, allowing users to customize swing points, market structures, and visual styles for each.
🔹 Structures
Swings and Size: Enables or disables the display of swing highs and lows, assigns icons to represent the structures, and adjusts the size of the icons.
Market Structures: Toggles the visibility of market structure lines.
Market Structure Validation: Enable or disable validation to distinguish true breakouts from liquidity sweeps.
Market Structure Labels: Displays or hides labels indicating the type of market structure.
Line Style and Width: Allows customization of the style and width of the lines representing market structures.
Swing and Line Colors: Provides options to adjust the colors of swing icons, market structure lines, and labels for better visualization.
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Market-Structures-(Intrabar).
Göstergeler ve stratejiler
Scalper Pro Pattern Recognition & Price Action👑Scalper Pro®👑Pattern Recognition & Price Action
Introducing the ultimate trading robot designed for serious investors! Our advanced bot analyzes market cycles, tracks targets, sets stop losses, and expertly manages your capital. With powerful algorithms and real-time insights, it identifies opportunities and delivers accurate signals, ensuring you never miss a market move. Take control of your trading strategy and maximize your profits with our cutting-edge technology. Join the future of trading today—your expert assistant is ready to help you succeed!
💡 This is not just another indicator — it's a complete trading assistant that identifies structure, signals strength, and simplifies decision-making.
ILM Checklist [Nix]ILM Checklist and Ratings Indicator!
This is a checklist type guide for those that trade the ILM model and are having trouble rating setups on their own.
You can double click on the checklist to open its settings where you can select all the confluences you see on the chart while a setup is forming.
Then the checklist will give you a mechanical estimate of what rating would Nix give it.
Obviously discretion is important as an A+ mechanical setup if still an F setup if you are executing it during a news event.
I have also added a dark / light mode theme toggle to suit your chart.
3D Candles (Zeiierman)█ Overview
3D Candles (Zeiierman) is a unique 3D take on classic candlesticks, offering a fresh, high-clarity way to visualize price action directly on your chart. Visualizing price in alternative ways can help traders interpret the same data differently and potentially gain a new perspective.
█ How It Works
⚪ 3D Body Construction
For each bar, the script computes the candle body (open/close bounds), then projects a top face offset by a depth amount. The depth is proportional to that candle’s high–low range, so it looks consistent across symbols with different prices/precisions.
rng = math.max(1e-10, high - low ) // candle range
depthMag = rng * depthPct * factorMag // % of range, shaped by tilt amount
depth = depthMag * factorSign // direction from dev (up/down)
depthPct → how “thick” the 3D effect is, as a % of each candle’s own range.
factorMag → scales the effect based on your tilt input (dev), with a smooth curve so small tilts still show.
factorSign → applies the direction of the tilt (up or down).
⚪ Tilt & Perspective
Tilt is controlled by dev and translated into a gentle perspective factor:
slope = (4.0 * math.abs(dev)) / width
factorMag = math.pow(math.min(1.0, slope), 0.5) // sqrt softens response
factorSign = dev == 0 ? 0.0 : math.sign(dev) // direction (up/down)
Larger dev → stronger 3D presence (up to a cap).
The square-root curve makes small dev values noticeable without overdoing it.
█ How to Use
Traders can use 3D Candles just like regular candlesticks. The difference is the 3D visualization, which can broaden your view and help you notice price behavior from a fresh perspective.
⚪ Quick setup (dual-view):
Split your TradingView layout into two synchronized charts.
Right pane: keep your standard candlestick or bar chart for live execution.
Left pane: add 3D Candles (Zeiierman) to compare the same symbol/timeframe.
Observe differences: the 3D rendering can make expansion/contraction and body emphasis easier to spot at a glance.
█ Go Full 3D
Take the experience further by pairing 3D Candles (Zeiierman) with Volume Profile 3D (Zeiierman) , a perfect complement that shows where activity is concentrated, while your 3D candles show how the price unfolded.
█ Settings
Candles — How many 3D candles to draw. Higher values draw more shapes and may impact performance on slower machines.
Block Width (bars) — Visual thickness of each 3D candle along the x-axis. Larger values look chunkier but can overlap more.
Up/Down — Controls the tilt and strength of the 3D top face.
3D depth (% of range) — Thickness of the 3D effect as a percentage of each candle’s own high–low range. Larger values exaggerate the depth.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
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.
WRSignalsTimeframe ADX Smoothing DI Length ADX Threshold
1–5 min 1–2 7–10 20–25
15m–1h 2–3 10–14 25–30
4h–1d 3–5 14–20 20–25
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.
MACD-V (Volatility-Normalized MACD)MACD-V with histogram and strength signals. It normalizes volatility across all assets and time frames.
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
Prop Algo Prop Algo — MTF Trend + Signals + SMC Toolkit
**What it is**
Prop Algo is a multi-tool trading assistant that blends trend following, contrarian timing, and Smart Money Concepts (SMC). It plots clean buy/sell labels, paints candles by momentum state, maps TP/SL levels automatically, shows a compact **Smart Panel** (dashboard), and draws **auto-trendlines**, **trend clouds**, and **institutional zones** (OB/BB/MB). It’s built to help discretionary traders make faster, rules-based decisions without drowning in settings.
---
Core Signals
* **Buy / Strong Buy** and **Sell / Strong Sell** labels driven by:
* **Supertrend** cross + confirmation stack (MACD slope, HMA(55) impulse, EMA150/EMA250 bias, channel direction).
* Optional **Contrarian Mode** via RSI “trend shifter” (fast/slow crossover with guardrails).
* Optional **High-Volume Filter** and **Consolidation Filter** (ADX).
* Optional **Trend Cloud Filter** (Smooth / Scalping / Scalping+ / Swing).
* **Trend Scalper preset** (5/9/21 EMA on HA-smoothed price) with color-filled momentum bands.
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Risk & Trade Management
* **Dynamic TP/SL** visuals: entry, stop, and **TP1/TP2/TP3** auto-projections.
* **ATR or %-based trailing stop** (toggle).
* **RSI-based TP markers** (cross levels for staged exits).
* Optional **market structure swings** (HH/HL/LH/LL labels).
Dashboard
A one-glance status block showing:
* **MTF bias:** 5m, 15m, 30m, 1h, 4h (green/red tiles based on 200-EMA state).
* **Market State:** Trending / Ranging / Inactive (TVR proxy).
* **Volatility %** (ATR/StdDev normalization).
* **Institutional Activity** (volume filter).
* **Current Session** (Sydney/Tokyo/London/New York).
* **Trend Pressure** (EMA9 slope: Bullish / Bearish / Flat).
---
Smart Money Concepts
* **Automated BoS** (Break of Structure) labeling.
* **Order Blocks:** Bu-OB / Be-OB with extend-right boxes.
* **Break Blocks / Mitigation Blocks:** Bu-BB / Be-BB and Bu-MB / Be-MB.
* **Auto maintenance:** zones extend, alert when price enters, and optionally delete when invalidated.
* **Minimal ZigZag** backbone (length-driven pivots) with Fib-based confirmation logic.
Trend Cloud & Candle Heatmap
* **Trend Cloud:** Smooth / Scalping / Scalping+ / Swing; optional EMA150/EMA250 fill for higher-timeframe bias.
* **MACD heatmap candles:** multi-tier green/red/yellow body coloring based on MACD and histogram progression.
Auto Trendlines
* **Regression-style channel** from WMA/SMA blend with **±RMSE envelopes**, extended to the right for developing support/resistance rails.
Inputs
* **Signal Mode / Filters:** Trending, Contrarian, High Volume, Strong-only, and Cloud filters.
* **Sensitivity / Tuner:** Supertrend factor & length, Reversal Dot tuner.
* **Risk Management:** Use % or ATR, TP multipliers (TP1/2/3), Trailing SL toggle.
* **Market Structure:** Show swings, swing length.
* **Dashboard:** On/off, position, size.
* **Sessions:** Auto detection (Sydney/Tokyo/London/New York).
*(Default “Presets” is **All Signals**; you can still use the “Trend Scalper” subset by enabling the dedicated view inside the script.)*
Alerts
* **Normal Buy / Strong Buy**
* **Normal Sell / Strong Sell**
* **Stop-Loss Crossed**
* **Target 1 / Target 2 / Target 3 Crossed**
* **Cloud Turned Bullish / Bearish**
* **MSB (Market Structure Break)**
> Tip: set alerts on “Once Per Bar Close” for cleaner signals.
How to Use
1. **Pick a mode:** start with **Trending Signals ** + **Smooth Cloud** for swing/position, or **Scalping/Scalping+** for intraday.
2. **Confirm bias:** glance at the **MTF tiles** and **Trend Pressure**. Trade in alignment or deliberately fade (Contrarian Mode) with tight risk.
3. **Plan risk:** use the auto **Entry/SL/TP** lines; enable **Trailing SL** if you prefer dynamic exits.
4. **Watch zones:** when price enters **OB/BB/MB** boxes, expect reactions; combine with signal labels for confluence.
5. **Respect structure:** BoS prints are context—don’t fight fresh structure without a plan.
Best Practices
* Works on **crypto, indices, FX, commodities, stocks**.
* Timeframes: from **5m** up to **4H/1D**. Lower TFs benefit from Cloud filters or Strong-only mode.
* Avoid over-stacking filters at first; add filters only if you need fewer, higher-quality signals.
Notes & Limits
* This is **not** a standalone “autopilot.” It’s a **decision support** system.
* Past performance ≠ future results. Always test on **replay** and **paper** first.
* No financial advice. Manage risk like a professional.
Kalman Exponentialy Weighted Moving Average | MisinkoMasterThe Kalman Exponentialy Weighted Moving Average is a technical analysis tool providing users with more responsive and smoother signals, providing crystal-clear signals and giving investors valuable insights on market trends, however it could be used in many cases.
A deeper dive into the indicator:
When going through my creation of strategies, I had stumbled on an indicator called "EWMA", which worked decently, but it was far too simple in my opinion so I decided to combine the EMA & WMA, but with a little more complexity, and it has worked .
I began by learning how both MAs work, I already knew how WMA works, but EMA I did not.
After learning both I found out they were quite simple in principle and that there was a way to combine them in such way that you would get really good signals, however it was way too noisy.
While it could avoid major dumps that were not avoided by most indicators, it would lose that edge because of being too noisy.
After testing out many conditions, combinations & more, the best working one was this one:
WMA > KEWMA = long
WMA < KEWMA = short
I will explain this later, but this gave fast signals, and while it still was noisy it was better then before.
To smooth it out, I started testing price filters => Gaussian Filter and many more were tested out, but they either slowed it down to the point it was no longer of much use, or did not smooth it at all.
After testing the Kalman filter on this thing, I was shocked.
It was just right and made the indicator a lot better, smoothed it and kept most of the responsivness it had.
Now to the big question: "How is it calculated?"
Now first it needs to calculate the Kalman source, which smooths the source which will be used.
After that, we calculate the Weighted Moving Average for " n " period on the Kalman source.
Now that we have our WMA values, we need to calculate " a ".
a is calculated in the following formula:
a = 2/(1+ n )
where n is the user defined length
Now for the last part:
KEWMA = WMAyesterday * (1-a) + WMAtoday * a
This creates a very accurate and reactive indicator, that can prove useful in many uses, beyond those I will and did talk about.
For the trend logic as mentioned before:
Long = WMA > KEWMA
Short = WMA < KEWMA
This worked best, but you might find better ways of using it.
I think that is all I have to say about it, I left it open source so you can all code it in your strategies and play around with it.
Enjoy Gs!
TrendShield Pro | DinkanWorldSmart Trailing Trend System Powered by EMA + ATR
TrendShield Pro is a powerful trend detection and trailing stop indicator designed for traders who rely on pure price movement and volatility tracking.
It dynamically adapts to market conditions using a combination of EMA (Exponential Moving Average) and ATR (Average True Range) to identify the active trend and place a visual trailing stop line.
🔍 How It Works
TrendShield Pro combines trend direction and volatility to create a self-adjusting trailing system:
EMA (Exponential Moving Average):
Smooths price fluctuations and identifies the overall market bias.
ATR (Average True Range):
Measures volatility to determine how far the trailing stop should follow the trend.
Dynamic Bands:
Two invisible thresholds are formed — up and down — around the EMA using the ATR and your chosen Factor value.
Trailing Logic:
When the EMA is rising, the Trailing Stop (TUp) locks in higher lows.
When the EMA is falling, the Trailing Stop (TDown) locks in lower highs.
The indicator switches trend automatically based on price crossing these trailing levels.
🧭 Visuals & Features
Green Trailing Line (Demand Trend): Indicates an active bullish trend.
Red Trailing Line (Supply Trend): Indicates an active bearish trend.
Arrow Signals:
🟢 Up Arrow → Bullish Trend Reversal
🔴 Down Arrow → Bearish Trend Reversal
Diamond Markers: Show points where the trailing line shifts, marking dynamic volatility changes.
⚙️ Inputs
Input Description
EMA Period Length of the Exponential Moving Average
ATR Period Period used for Average True Range calculation
Factor Multiplier for ATR-based volatility expansion
☸Gap Detector [NHP]🔶This is a Pine Script code for a “Gap Detector” study in TradingView. The script scans for gaps in the price chart and labels them as either ‘🟢Bull gap’ or ‘🔴Bear gap’. Here’s a brief explanation of the code:
🔶Length and Width are user inputs that define the number of bars to look back and the width of the lines drawn, respectively.
➡️Gap_start and gap_end are variables that store the start and end of a gap.
➡️Gap_bull and gap_bear are boolean variables that indicate whether a bull or bear gap has been detected.
🔶Inf_gap and sup_gap are variables that store the lower and upper bounds of a gap.
The script then iterates over the specified length of bars. If a gap is detected (a high price that is lower than the previous bar’s low price for a bull gap, or a low price that is higher than the previous bar’s high price for a bear gap), it calculates the size of the gap and draws lines and labels on the chart if the gap is larger than 5 pips. ( pips meaning percentage in point)
🔶All content provided is for informational & educational purposes only. Past performance does not guarantee future results.
Lorentzian Harmonic Flow - Temporal Market Dynamic Lorentzian Harmonic Flow - Temporal Market Dynamic (⚡LHF)
By: DskyzInvestments
What this is
LHF Pro is a research‑grade analytical instrument that models market time as a compressible medium , extracts directional flow in curved time using heavy‑tailed kernels, and consults a history‑based memory bank for context before synthesizing a final, bounded probabilistic score . It is not a mashup; each subsystem is mathematically coupled to a single clock (time dilation via gamma) and a single lens (Lorentzian heavy‑tailed weighting). This script is dense in logic (and therefore heavy) because it prioritizes rigor, interpretability, and visual clarity.
Intended use
Education and research. This tool expresses state recognition and regime context—not guarantees. It does not place orders. It is fully functional as published and contains no placeholders. Nothing herein is financial advice.
Why this is original and useful
Curved time: Markets do not move at a constant pace. LHF Pro computes a Lorentz‑style gamma (γ) from relative speed so its analytical windows contract when the tape accelerates and relax when it slows.
Heavy‑tailed lens: Lorentzian kernels weight information with fat tails to respect rare but consequential extremes (unlike Gaussian decay).
Memory of regimes: A K‑nearest‑neighbors engine works in a multi‑feature space using Lorentz kernels per dimension and exponential age fade , returning a memory bias (directional expectation) and assurance (confidence mass).
One ecosystem: Squeeze, TCI, flow, acceleration, and memory live on the same clock and blend into a single final_score —visualized and documented on the dashboard.
Cognitive map: A 2D heat map projects memory resonance by age and flow regime, making “where the past is speaking” visible.
Shadow portfolio metaphor: Neighbor outcomes act like tiny hypothetical positions whose weighted average forms an educational pressure gauge (no execution, purely didactic).
Mathematical framework (full transparency)
1) Returns, volatility, and speed‑of‑market
Log return: rₜ = ln(closeₜ / closeₜ₋₁)
Realized vol: rv = stdev(r, vol_len); vol‑of‑vol: burst = |rv − rv |
Speed‑of‑market (analog to c): c = c_multiplier × (EMA(rv) + 0.5 × EMA(burst) + ε)
2) Trend velocity and Lorentz gamma (time dilation)
Trend velocity: v = |close − close | / (vel_len × ATR)
Relative speed: v_rel = v / c
Gamma: γ = 1 / √(1 − v_rel²), stabilized by caps (e.g., ≤10)
Interpretation: γ > 1 compresses market time → use shorter effective windows.
3) Adaptive temporal scale
Adaptive length: L = base_len / γ^power (bounded for safety)
Harmonic horizons: Lₛ = L × short_ratio, Lₘ = L × mid_ratio, Lₗ = L × long_ratio
4) Lorentzian smoothing and Harmonic Flow
Kernel weight per lag i: wᵢ = 1 / (1 + (d/γ)²), d = i/L
Horizon baselines: lw_h = Σ wᵢ·price / Σ wᵢ
Z‑deviation: z_h = (close − lw_h)/ATR
Harmonic Flow (HFL): HFL = (w_short·zₛ + w_mid·zₘ + w_long·zₗ) / (w_short + w_mid + w_long)
5) Flow kinematics
Velocity: HFL_vel = HFL − HFL
Acceleration (curvature): HFL_acc = HFL − 2·HFL + HFL
6) Squeeze and temporal compression
Bollinger width vs Keltner width using L
Squeeze: BB_width < KC_width × squeeze_mult
Temporal Compression Index: TCI = base_len / L; TCI > 1 ⇒ compressed time
7) Entropy (regime complexity)
Shannon‑inspired proxy on |log returns| with numerical safeguards and smoothing. Higher entropy → more chaotic regime.
8) Memory bank and Lorentzian k‑NN
Feature vector (5D):
Outcomes stored: forward returns at H5, H13, H34
Per‑dimension similarity: k(Δ) = 1 / (1 + Δ²), weighted by user’s feature weights
Age fading: weight_age = mem_fade^age_bars
Neighbor score: sᵢ = similarityᵢ × weight_ageᵢ
Memory bias: mem_bias = Σ sᵢ·outcomeᵢ / Σ sᵢ
Assurance: mem_assurance = Σ sᵢ (confidence mass)
Normalization: mem_bias normalized by ATR and clamped into band
Shadow portfolio metaphor: neighbors behave like micro‑positions; their weighted net forward return becomes a continuous, adaptive expectation.
9) Blended score and breakout proxy
Blend factor: α_mem = 0.45 + 0.15 × (γ − 1)
Final score: final_score = (1−α_mem)·tanh(HFL / (flow_thr·1.5)) + α_mem·tanh(mem_bias_norm)
Breakout probability (bounded): energy = cap(TCI−1) + |HFL_acc|×k + cap(γ−1)×k + cap(mem_assurance)×k; breakout_prob = sigmoid(energy). Caps avoid runaway “100%” readings.
Inputs — every control, purpose, mechanics, and tuning
🔮 Lorentz Core
Auto‑Adapt (Vol/Entropy): On = L responds to γ and entropy (breathes with regime), Off = static testing.
Base Length: Calm‑market anchor horizon. Lower (21–28) for fast tapes; higher (55–89+) for slow.
Velocity Window (vel_len): Bars used in v. Shorter = more reactive γ; longer = steadier.
Volatility Window (vol_len): Bars used for rv/burst (c). Shorter = more sensitive c.
Speed‑of‑Market Multiplier (c_multiplier): Raises/lowers c. Lower values → easier γ spikes (more adaptation). Aim for strong trends to peak around γ ≈ 2–4.
Gamma Compression Power: Exponent of γ in L. <1 softens; >1 amplifies adaptation swings.
Max Kernel Span: Upper bound on smoothing loop (quality vs CPU).
🎼 Harmonic Flow
Short/Mid/Long Horizon Ratios: Partition L into fast/medium/slow views. Smaller short_ratio → faster reaction; larger long_ratio → sturdier bias.
Weights (w_short/w_mid/w_long): Governs HFL blend. Higher w_short → nimble; higher w_long → stable.
📈 Signals
Squeeze Strictness: Threshold for BB1 = compressed (coiled spring); <1 = dilated.
v/c: Relative speed; near 1 denotes extreme pacing. Diagnostic only.
Entropy: Regime complexity; high entropy suggests caution, smaller size, or waiting for order to return.
HFL: Curved‑time directional flow; sign and magnitude are the instantaneous bias.
HFL_acc: Curvature; spikes often accompany regime ignition post‑squeeze.
Mem Bias: Directional expectation from historical analogs (ATR‑normalized, bounded). Aligns or conflicts with HFL.
Assurance: Confidence mass from neighbors; higher → more reliable memory bias.
Squeeze: ON/RELEASE/OFF from BB
Turtle Strategy - Triple EMA Trend with ADX and ATRDescription
The Triple EMA Trend strategy is a directional momentum system built on the alignment of three exponential moving averages and a strong ADX confirmation filter. It is designed to capture established trends while maintaining disciplined risk management through ATR-based stops and targets.
Core Logic
The system activates only under high-trend conditions, defined by the Average Directional Index (ADX) exceeding a configurable threshold (default: 43).
A bullish setup occurs when the short-term EMA is above the mid-term EMA, which in turn is above the long-term EMA, and price trades above the fastest EMA.
A bearish setup is the mirror condition.
Execution Rules
Entry:
• Long when ADX confirms trend strength and EMA alignment is bullish.
• Short when ADX confirms trend strength and EMA alignment is bearish.
Exit:
• Stop Loss: 1.8 × ATR below (for longs) or above (for shorts) the entry price.
• Take Profit: 3.3 × ATR in the direction of the trade.
Both parameters are configurable.
Additional Features
• Start/end date inputs for controlled backtesting.
• Selective activation of long or short trades.
• Built-in commission and position sizing (percent of equity).
• Full visual representation of EMAs, ADX, stop-loss, and target levels.
This strategy emphasizes clean trend participation, strict entry qualification, and consistent reward-to-risk structure. Ideal for swing or medium-term testing across trending assets.
Session Opens by TradeSeekersIt doesn't get much simpler than this indicator for futures traders wanting to track four key session open prices.
Sessions
1. ETH open - extended hours starts
2. Midnight open - new calendar day starts
3. CME open - Chicago exchange opens, data releases
4. RTH open - regular trading hours, volume cometh
Usage
All four of these prices / areas are important for futures traders to pay attention to.
RTH opens far below ETH sometimes will retrace, CME and RTH together can act as a powerful range.
Midnight open sometimes has little importance for the day, but then again it's provided beautiful bounces. Again each level I find to be impactful nearly every session, so I like to keep them close by in an understated manner.
Timezone
If you're not EST, adjust the timezone string accordingly (refer to TradingView docs for string formats).
Proximity Detection
Also, I added proximity detection that aims to keep level collisions from occurring. If a particular session open isn't shown it may be due to being exactly the same price as another open or it's too close to another open.
The proximity sensitivity can be adjusted in settings. The on chart appearance doesn't impact the alerting capability.
Aesthetics
I don't like boring charts so I added a fun "glow" effect, I went with a palette that reminded me of clear sky colors at those times of day (if you're EST).
Alerting
Alerting can be done with just a single alert, first open the indicator config and uncheck any session opens you don't want to be alerted on (why!?), and then use the standard alert menus in TradingView to set the alert on "Any alert() function call".
Why does this beautiful indicator exist?
While there are a handful of indicators that plot open prices with some overlap to this one, I didn't see any that alerted automatically without much fuss.
Initial Balance Breakout + FibThe IB High / Low + Auto-Fib indicator automatically plots the Initial Balance range and a Fibonacci projection for each trading day.
Define your IB start and end times (e.g., 09:30–10:30).
The indicator marks the IB High and IB Low from that session and extends them to the session close.
It keeps the last N days visible for context.
When price breaks outside the IB range, it automatically plots a Fibonacci retracement/extension from the opposite IB side to the breakout, using levels 0, 0.236, 0.382, 0.5, 0.618, 0.88, 1.
The Fib updates dynamically as the breakout extends, and labels are neatly aligned on the right side of the chart for clarity.
Ideal for traders who monitor Initial Balance breaks, range expansions, and Fibonacci reaction levels throughout the trading session.
⚡ Hidden Impulse# ⚡ Hidden Impulse | Advanced Multi-Timeframe Trading System
## Overview
**Hidden Impulse** is a sophisticated multi-timeframe indicator that combines three powerful technical analysis tools to identify high-probability trading opportunities. The indicator uses Schaff Trend Cycle (STC), Force Index, and EMA filters to generate precise entry signals across multiple timeframes.
This indicator is designed for traders who want to catch momentum shifts early while filtering out false signals using multi-timeframe confirmation.
---
## Core Components
### 1. **Schaff Trend Cycle (STC)**
The STC is an advanced oscillator that combines MACD and Stochastic indicators to identify trend changes faster than traditional oscillators. It oscillates between 0 and 100:
- **Below 25**: Oversold zone (potential bullish reversal)
- **Above 75**: Overbought zone (potential bearish reversal)
- **Crossovers**: Signal potential trend changes
**Key Advantage**: The STC reacts faster to price changes than MACD while producing fewer false signals than Stochastic.
### 2. **Force Index**
Developed by Dr. Alexander Elder, the Force Index measures the strength behind price movements by combining:
- Price change
- Volume
It helps confirm the legitimacy of trends:
- **Positive values**: Bulls are in control
- **Negative values**: Bears are in control
- **Zero-line crosses**: Potential momentum shifts
### 3. **EMA Filter (50-period)**
Acts as a trend filter to ensure trades align with the broader market direction:
- Price above EMA → Look for LONG setups
- Price below EMA → Look for SHORT setups
---
## Three Trading Setups
### 📊 **Setup A: Classic (Most Frequent)**
**Entry Conditions - LONG:**
- Higher timeframe STC > 25 (bullish confirmation)
- Primary timeframe STC crosses above 25
- Force Index positive or crossing above zero
- Price above EMA 50
**Entry Conditions - SHORT:**
- Higher timeframe STC < 75 (bearish confirmation)
- Primary timeframe STC crosses below 75
- Force Index negative or crossing below zero
- Price below EMA 50
**Best for:** Catching trend continuations with multi-timeframe confirmation
---
### 💎 **Setup B: Divergence (Highest Win Rate)**
**Bullish Divergence:**
- Price makes a Lower Low (LL)
- Force Index makes a Higher Low (HL)
- STC in oversold zone (<25)
- Trigger: STC starts rising + Force Index crosses above zero
**Bearish Divergence:**
- Price makes a Higher High (HH)
- Force Index makes a Lower High (LH)
- STC in overbought zone (>75)
- Trigger: STC starts falling + Force Index crosses below zero
**Best for:** Identifying trend reversals with strong risk/reward ratios
---
### ⚡ **Setup C: Bounce (Fast Scalping)**
**LONG Bounce:**
- Price touches EMA 50 from above
- STC in extreme oversold (<15)
- Force Index positive
**SHORT Bounce:**
- Price touches EMA 50 from below
- STC in extreme overbought (>85)
- Force Index negative
**Best for:** Quick mean-reversion trades during strong trends
---
## Key Features
### ✅ **Multi-Timeframe Analysis**
- Choose any timeframe for primary STC calculation
- Select a higher timeframe for trend confirmation
- Visual display of both timeframes on one chart
### ✅ **Smart Signal Filtering**
- Only shows signals when all conditions align
- Filters out weak setups automatically
- Color-coded labels for easy identification
### ✅ **Comprehensive Information Panel**
Real-time dashboard showing:
- Current STC values for both timeframes
- Force Index direction
- Price position relative to EMA
- Active trend direction
- Current signal type
### ✅ **Visual Clarity**
- STC oscillator with oversold/overbought zones
- Force Index histogram (normalized for easy reading)
- Clear level lines at 25, 50, and 75
- Green/red background shading in extreme zones
### ✅ **Flexible Alerts**
- Individual alerts for each setup type (A, B, C)
- Separate LONG and SHORT alerts
- General "ANY LONG" and "ANY SHORT" alerts
- Custom alert messages for quick recognition
---
## Settings & Customization
### **Schaff Trend Cycle**
- **Length 1** (default: 23): Fast MACD period
- **Length 2** (default: 50): Slow MACD period
- **Smoothing** (default: 10): Stochastic smoothing period
- **Lower Level** (default: 25): Oversold threshold
- **Upper Level** (default: 75): Overbought threshold
### **Timeframes**
- **Primary Timeframe**: Leave empty for chart timeframe or select custom
- **Higher Timeframe** (default: 30min): For trend confirmation
### **Force Index**
- **EMA Period** (default: 13): Smoothing period for Force Index
### **EMA Filter**
- **Period** (default: 50): Trend filter period
### **Signal Controls**
- Toggle Setup A (Classic)
- Toggle Setup B (Divergence)
- Toggle Setup C (Bounce)
- Show/hide chart labels
- Show/hide higher timeframe STC
---
## How to Use
### **Step 1: Set Your Timeframes**
Choose your primary trading timeframe (current chart) and a higher timeframe for confirmation. Common combinations:
- 5min + 15min (scalping)
- 15min + 30min (day trading)
- 30min + 1H (swing trading)
- 1H + 4H (position trading)
### **Step 2: Wait for Signal**
The indicator will automatically display labeled signals when conditions align:
- 🟢 Green labels = LONG signals
- 🔴 Red labels = SHORT signals
- A/B/C prefix indicates setup type
### **Step 3: Check Information Panel**
Before entering, verify in the info panel:
- Both STC values confirm the direction
- Force Index aligns with signal
- Price position relative to EMA is correct
- Trend shows green (LONG) or red (SHORT)
### **Step 4: Set Alerts**
Create alerts for your preferred setup types:
- Setup B alerts for highest quality signals
- "ANY LONG/SHORT" for maximum opportunities
- Individual setup alerts for specific strategies
---
## Trading Tips
### **Best Practices:**
1. **Setup B (Divergence)** typically offers the best risk/reward ratios
2. Use **Setup A** for trend continuation in strong markets
3. **Setup C** works best in ranging markets with clear EMA respect
4. Always check higher timeframe confirmation before entering
5. Consider volume spikes when Force Index shows strong readings
### **Risk Management:**
- Place stops below/above recent swing points
- Use ATR-based position sizing
- Take partial profits at STC extreme levels (15/85)
- Avoid trading against higher timeframe STC direction
### **Market Conditions:**
- **Trending markets**: Focus on Setup A
- **Ranging markets**: Focus on Setup C
- **Reversal points**: Focus on Setup B
- **High volatility**: Increase timeframes for stability
---
## Technical Details
**Indicator Type:** Oscillator (separate window)
**Overlay:** No (displays in separate pane below chart)
**Repainting:** No - signals are confirmed on bar close
**Max Bars Back:** 500 (adjustable)
**Compatible with:** All markets (Forex, Stocks, Crypto, Futures)
---
## Credits
This indicator combines:
- **Schaff Trend Cycle** by Doug Schaff
- **Force Index** by Dr. Alexander Elder
- **EMA filtering** and multi-timeframe analysis
Original implementation and trading setups developed for TradingView.
---
## Disclaimer
This indicator is a technical analysis tool and does not guarantee profitable trades. Always use proper risk management, combine with your own analysis, and never risk more than you can afford to lose. Past performance does not indicate future results.
---
## Support & Updates
For questions, suggestions, or bug reports, please use the comments section below. Regular updates and improvements are planned based on user feedback.
**Happy Trading! 📈**
Directional Indicator Crossovers v1[JopAlgo]Directional Indicator Crossovers v1 — the classic DMI, made clearer and easier to act on
We'd like to introduce you to a more relaxed, streamlined version of DI. While it may not seem like it at first glance, we've taken the D+/D- method as a starting point and developed our own version of this indicator: two lines, a smooth green/red field indicating who's in control, and clear crossover alerts for a flip. We deliberately chose the step line representation because it closely matches the candlestick patterns on the chart. Designed to help you react faster—without clutter.
What you’ll see
+DI (green) and −DI (red) using classic Wilder smoothing.
A soft control zone between the lines: green when +DI dominates, red when −DI dominates.
Crossover alerts (no labels, no background flooding)—just the turning points.
Why this helps
Instant bias: the shaded field tells you who’s in control without reading values.
Cleaner execution: minimal visuals keep focus on the handoff (+DI↔−DI) and your price levels.
Actionable by design: built-in alerts fire right at the flip to route into your workflow.
How to read it
Bias: Green zone → buyers lead. Red zone → sellers lead.
Trigger: Consider entries on the DI crossover that aligns with your higher-timeframe context (trend, S/R, OB).
Patience in chop: If flips are frequent in tight ranges, wait for sustained zone dominance or confirm on a higher TF.
Exit/flip: Opposite crossover or a clear loss of dominance.
Settings that matter
DI Length (default 14): Higher = calmer, fewer flips. Lower = faster, more signals.
Visuals: Keep the control zone on for quick reads; hide crossover marks if you prefer pure lines.
Alerts: Enable bullish and bearish DI cross alerts; connect to notifications or webhooks as needed.
Starter presets
Intraday (15m–1H): DI Length 12–14 for quicker handoffs.
Swing (4H–1D): DI Length 14–20 for cleaner signals.
Choppy assets: Nudge length higher to dampen noise.
Where it shines (and limits)
Best: Liquid markets (crypto majors, indices, large caps) where handoffs matter.
Works elsewhere: Still useful on slower pairs; extend length for stability.
Limit: Frequent flips in low-range sessions—pair with HTF bias or structure.
Alerts included
Bullish DI Crossover: +DI crosses above −DI.
Bearish DI Crossover: −DI crosses above +DI.
Attribution & License
Built on the Directional Movement Index concept by J. Welles Wilder Jr. (1978).
Independent Pine v6 implementation (not derived from TradingView’s built-in source).
Released as Open Source (MPL-2.0)—please keep the license header intact.
Disclaimer
For educational purposes only; not financial advice. Trading involves risk. Test first, use clear levels, and manage risk. This project is independent and not affiliated with or endorsed by TradingView.
Chart Fusion Line SND Detection & Signals by TitikSona### Overview
Fusion Line Momentum Analyzer merges Double Stochastic and RSI into a single adaptive oscillator that visualizes momentum direction and strength.
It helps identify overbought and oversold conditions through a smooth blended curve that adapts across timeframes.
Designed for analytical purposes and to simplify momentum reading without complex triggers or repainting methods.
---
### Core Idea
The indicator fuses three classical momentum tools:
- Fast Stochastic (12,3,3) for short-term swings
- Slow Stochastic (100,8,8) for long-term momentum stability
- RSI (26) for measuring internal strength between buyers and sellers
These three are normalized and averaged into one unified line called the **Fusion Line**.
A secondary smoothing layer, the **Signal Line**, refines the direction and removes minor fluctuations.
---
### Features
- Unified momentum line combining Fast and Slow Stochastic with RSI
- Real-time momentum strength percentage (adaptive scale)
- Color-coded momentum bias for easy interpretation
- Optional info box showing component strength and overall state
- Background shading to visualize dominant momentum direction
- Optional alerts when Fusion Line crosses common momentum zones (20 and 80)
---
### Default Parameters
Fast Stochastic (12,3,3)
Slow Stochastic (100,8,8)
RSI Length (26)
Signal Line Smoothing (9)
All parameters can be modified to match volatility or personal style.
---
### How to Read
- A rising Fusion Line often reflects strengthening bullish momentum.
- A falling Fusion Line often reflects increasing bearish pressure.
- Strength percentage represents how dominant the current bias is.
- Extreme levels (near 20 or 80) indicate potential exhaustion or recovery areas.
Always interpret readings with market context such as trend direction, structure, and volume.
---
### Interpretation Guide
Low Fusion levels may indicate possible accumulation or recovery.
High Fusion levels may signal overextension or slowing momentum.
Neutral mid-levels represent balance between buying and selling pressure.
---
### Disclaimer
This script is an analytical visualization tool for studying market momentum.
It does not generate trading signals or predict market direction.
Always combine with structure, volume, and higher-timeframe context before making any trading decisions.
---
### Developer
Created by **TitikSona** — Research & Fusion Concept Designer
Built using **Pine Script v6**
Type: Open-source educational script
---
### Short Description
Adaptive momentum analyzer combining Double Stochastic and RSI into one Fusion Line with real-time strength visualization.
Dobrusky Volume PulseWhat it does & who it’s for
Volume Pulse is a lightweight, customizable volume profile overlay that shows traders how volume is distributed across price levels over a chosen lookback window. Unlike standard profiles, it also maps cumulative buy/sell pressure at each level, so you see not just where volume clustered, but which side dominated.
Core ideas
Cumulative volume by price: Builds a horizontal profile of traded volume at each level, based on user-defined depth and resolution.
Directional pressure mapping: At every price level, the script accumulates bullish vs. bearish volume based on candle closes vs. opens, providing a directional read on whether buyers or sellers had the upper hand.
POC: Automatically highlights the Point of Control (POC) — the level with the most activity.
Customizable presentation: Adjustable profile resolution, bar width, offset, colors, and whether to show cumulative, directional, or both.
How the components work together
The profile provides the “where,” while the buy/sell mapping adds the “who.” By combining these, traders can see whether a high-volume node was buyer-driven absorption or seller-driven distribution — a distinction classic profiles don’t reveal. This directional overlay reduces the guesswork of interpreting raw volume clusters.
How to use
Apply the overlay to your chart.
Watch the POC and areas of significant increase or decrease in volume (and pressure) as natural magnets or rejection areas.
When trading intraday, I've found that higher timeframe volume levels act as strong magnets. In the chart, you can see the volume levels I've drawn on the SPY daily chart. These levels are targets I use when trading the 5-minute chart.
Pay attention to color dominance at those zones — green-heavy nodes suggest buyer control; red-heavy nodes suggest seller control.
Combine with time-based volume tools and price-action for a more comprehensive trade plan.
Settings overview
Lookback depth: Number of bars used for profile calculation.
Profile resolution: Number of horizontal bars to split volume across price.
Bar style: Width, offset, and multiplier for scaling.
Toggle layers: Choose cumulative, directional, or both.
POC display: Optional highlight of the most traded level.
Limitations & best practices
This is a contextual overlay, not a trade-signal system.
Works best on liquid instruments (indices, futures, major stocks, liquid crypto) where volume distribution is meaningful.
Directional mapping uses candle body bias (close vs. open), not raw order flow. For full tape analysis, pair with actual order flow data.
Originality justification
Dual profile: combines cumulative volume-by-price and buyer/seller pressure per bin (close vs. open) — not a standard VP clone.
From-scratch binning + POC in a single pass for speed; no reused libraries.
Flexible display (cumulative / directional / both) with independent resolution, width, and offset for intraday or HTF use.
Clear visuals (optional POC, balanced node coloring) and open-source code so traders can audit and extend.
Image Plotter [theUltimator5]Image Plotter is a visual alerting tool that drops fun, high-contrast ASCII (braille) art (e.g., Rocket, Cat “hang in there”, Babe Ruth, etc.) directly on your price chart when a technical trigger fires. It’s designed for quick, glanceable callouts without cluttering your chart with lines or sub-indicators.
If there are any specific images you would like to be able to add to your plot, please comment with the image you want to see and if it is reasonable, I will add it.
How it works
On each bar close, the script evaluates your selected Trigger Source. When the condition is true, it places a label that contains the selected ASCII art at a configurable offset above or below the candle.
You can choose to only keep the most recent art on the chart, or accumulate every trigger as a historical breadcrumb trail.
Positioning uses either the bar’s high (for above-candle placements) or low (for below-candle placements), then applies your vertical % offset and horizontal bar shift.
Inputs & Controls
Trigger Source
Select which condition will fire the ASCII placement:
RSI Oversold / Overbought — Triggers on cross through the threshold (under/over).
MACD Bullish Cross / Bearish Cross — MACD line crossing the Signal line.
BB Lower Touch / BB Upper Touch — Price crossing below the lower band / above the upper band.
Stochastic Oversold / Overbought — %K crossing through your thresholds.
Volume Spike — Current volume > (Volume MA × Spike Multiplier).
Price Cross MA — Close crossing above the chosen moving average (bullish only).
Custom Condition — Optional user condition (see “Custom Condition” below).
Plot Mode
Latest Only — The indicator deletes the previous label and keeps only the newest trigger on chart.
Every Trigger — Leaves all triggered labels on the chart (historical markers).
Note: TradingView caps the number of labels per script; this indicator sets max_labels_count=500. Heavy triggering can still hit limits.
Practical usage tips
Choose “Latest Only” for cleanliness if your trigger is frequent. Use “Every Trigger” when you want a visual audit trail.
Tune vertical offset by symbol — low-priced tickers may need a smaller %; volatile names may need more spacing.
Quick start
Add the indicator to any chart (any timeframe).
Pick a Trigger Source (e.g., RSI Oversold) and set thresholds/lengths.
Choose ASCII Image, Position Above/Below, Offsets, and Plot Mode.
(Optional) Enable Custom Condition and select your Custom Plot Source.
Create an Alert on “ASCII Trigger Alert” using Once Per Bar Close.
Have a variant you’d like (e.g., bearish MA cross, multi-alert pack by trigger, or time-window filters)? Tell me what workflow you want and I’ll tailor the script/description to match.
