Delmar - Ichimoku & 3-8 Trap Ribbon ConceptsDelmar - Ichimoku & 3-8 Trap Ribbon Concepts
Indicator Description
The Delmar - Ichimoku & 3-8 Trap Ribbon Concepts indicator combines the traditional Ichimoku Kinkō Hyō system with a custom 3-8 Trap Ribbon candlestick coloring scheme. This powerful tool helps traders identify trends, momentum, and potential reversal points on any TradingView chart. The Ichimoku components provide a comprehensive view of price action, while the 3-8 Trap Ribbon enhances visualization by coloring candlesticks based on their position relative to key Ichimoku lines.
Key Features
Ichimoku Kinkō Hyō: Plots five lines (Tenkan Sen, Tenkan Sen Short, Kijun Sen, Chikou Span, Senkou Span A & B) and the Kumo (cloud) to identify trends, support/resistance, and momentum.
3-8 Trap Ribbon: Colors candlesticks based on the close price’s position relative to the Tenkan Sen Short (3 periods), Tenkan Sen (9 periods), and Kijun Sen (26 periods), highlighting bullish, bearish, or neutral market conditions.
Customizable Settings: Toggle visibility of Ichimoku lines and Kumo, and adjust calculation periods to suit different timeframes or markets.
Alerts: Generates alerts when candlestick colors change, signaling potential trend shifts or trading opportunities.
How to Use the Indicator
Adding the Indicator
Open TradingView: Log in to your TradingView account and navigate to the chart for your desired asset (e.g., stock, forex, crypto).
Access Indicators: Click the “Indicators, Metrics & Strategies” button (fx icon) at the top of the chart.
Search for the Indicator: Type “Delmar - Ichimoku & 3-8 Trap Ribbon Concepts” in the search bar and select it from the list of published indicators.
Add to Chart: Click the indicator name to apply it to your chart.
Configuring Settings
Once added, customize the indicator via the Settings panel:
Ichimoku Kinkō Hyō Group:
Show Ichimoku Lines: Enable/disable the display of Tenkan Sen, Tenkan Sen Short, Kijun Sen, and Chikou Span (default: enabled).
Show Kumo: Toggle the Kumo (cloud) formed by Senkou Span A and B (default: enabled).
Tenkan Sen Length: Set the period for Tenkan Sen calculation (default: 9).
Tenkan Sen Short Length: Set the period for the short Tenkan Sen (default: 3).
Kijun Sen Length: Set the period for Kijun Sen (default: 26).
Senkou Span B Length: Set the period for Senkou Span B (default: 52).
Chikou & Senkou Offset: Adjust the offset for Chikou Span (past) and Senkou Spans (future) (default: 26).
Adjust these settings based on your trading style or timeframe (e.g., shorter periods for intraday, longer for swing trading).
Interpreting the Indicator
Ichimoku Components:
Tenkan Sen (Red): Short-term trend (default 9 periods). Above Kijun Sen = bullish, below = bearish.
Tenkan Sen Short (Light Red): Ultra-short-term trend (default 3 periods) for faster signals.
Kijun Sen (Blue): Medium-term trend (default 26 periods). Acts as dynamic support/resistance.
Chikou Span (Gray): Close price plotted 26 periods back. Above past price = bullish, below = bearish.
Kumo (Cloud): Formed by Senkou Span A and B. Green cloud = bullish (Span A > Span B), red = bearish (Span A < Span B). Price above Kumo = bullish trend, below = bearish.
3-8 Trap Ribbon (Candlestick Colors):
Dark Green: Close is above all three lines (Tenkan Sen Short, Tenkan Sen, Kijun Sen) → Strong bullish momentum.
Light Green: Close is below Tenkan Sen Short but above Tenkan Sen and Kijun Sen → Moderate bullish signal.
Yellow: Close is between Tenkan Sen and Kijun Sen → Neutral or consolidation.
Dark Red: Close is below all three lines → Strong bearish momentum.
Light Red: Close is above Tenkan Sen Short but below Tenkan Sen and Kijun Sen → Moderate bearish signal.
Gray: Default for undefined conditions.
Setting Up Alerts
The indicator includes an alert system to notify you when candlestick colors change, indicating potential trend shifts.
Open Alert Menu: Click the “Alert” button (bell icon) on the TradingView toolbar.
Select the Indicator: Choose “Delmar - Ichimoku & 3-8 Trap Ribbon Concepts” as the condition.
Configure Alert:
Set the condition to “Any alert() function call” to capture color change alerts (e.g., “Candle color changed to Dark Green”).
Choose your notification method (e.g., email, SMS, webhook, or TradingView notification).
Set the frequency to “Once Per Bar Close” to avoid multiple alerts per bar.
Create Alert: Save the alert and ensure it’s active.
Use these alerts to monitor key market shifts, such as entering/exiting a trend or spotting consolidation.
Trading Strategies
Trend Following:
Bullish: Enter long when price is above the Kumo, Chikou Span is above past price, and candles are Dark Green or Light Green.
Bearish: Enter short when price is below the Kumo, Chikou Span is below past price, and candles are Dark Red or Light Red.
Reversal Signals:
Look for Tenkan Sen crossing above/below Kijun Sen, combined with a color change (e.g., from Yellow to Dark Green for bullish reversal).
Confirm reversals when price breaks through the Kumo with a color shift (e.g., Dark Red to Yellow or Light Green).
Consolidation: Yellow candles indicate price is between Tenkan Sen and Kijun Sen, suggesting a range-bound market. Avoid trend-based trades until a breakout occurs.
Combine with other indicators (e.g., RSI, volume) for confirmation.
Tips for Optimal Use
Timeframes: Use on higher timeframes (e.g., 1H, 4H, Daily) for swing trading, or lower timeframes (e.g., 5M, 15M) for day trading.
Markets: Works well on trending markets (forex, stocks, crypto). Adjust period lengths for volatile assets.
Customization: Experiment with Tenkan Sen Short (e.g., 3–5 periods) and offset values to match market speed.
Backtesting: Test the indicator on historical data to validate signals before live trading.
Limitations
Lagging Indicators: Ichimoku components are based on historical data, so signals may lag in fast-moving markets.
False Signals: Yellow candles (consolidation) may occur frequently in choppy markets, requiring confirmation from other tools.
Performance: On low-end devices, rendering the Kumo and multiple lines may slow down if zoomed out over large datasets.
Support
For questions or suggestions, contact the indicator author via TradingView’s messaging system or check the script’s comment section for updates. Happy trading!
Ciclos
FVG - Sweep [TradeWithRon]FVG – Sweep - A multi-layer liquidity and imbalance detection system designed to help traders identify high-probability zones where price is likely to react.
🔍 Overview
This indicator combines Sweep Detection , Fair Value Gap (FVG) logic, and Change in State of Delivery (CISD) confirmation into a single streamlined tool. It helps traders visually connect liquidity grabs, displacement imbalances, and continuation or reversal opportunities — all in one chart.
⚙️ How It Works
1. Sweep Detection (Liquidity Grabs)
Detects when price takes liquidity above a previous high or below a previous low, then rejects it.
Alerts trigger when a bullish or bearish sweep is confirmed.
2. CISD Confirmation (Change in State of Delivery)
Identifies structural shifts using candle body direction and previous swing breaks.
Confirms when price transitions from expansion to contraction or vice versa.
CISD alerts notify when new shifts occur on any selected timeframe.
3. Fair Value Gap (FVG) Detection
Automatically highlights the first valid FVG following a confirmed sweep optional or CISD.
Optional alert for IFVG confirmation.
🧩 Why It’s Powerful
Multiple conditions across separate tools — sweeps, imbalances, and structure shifts.
This indicator integrates all three into one system that can:
Detect liquidity grabs,
Confirm displacement through FVGs,
Validate momentum or reversals with CISD logic.
🧩 Ideal Use Case
Combine this tool with your existing strategy to:
Build liquidity + imbalance confluence zones
Spot reversal setups after sweeps
Track continuations after structural shifts
Automate alerts for precision entries
Time Line Indicator - by LMTime Line Indicator – by LM
Description:
The Time Line Indicator is a simple, clean, and customizable tool designed to visualize specific time periods within each hour directly in a dedicated indicator pane. It allows traders to mark important intraday minute ranges across multiple past hours, providing a clear visual reference for time-based analysis. This indicator is perfect for identifying recurring hourly windows, session patterns, or custom time-based events in your charts.
Unlike traditional overlays, this indicator does not interfere with price candles and draws its lines in a separate pane at the bottom of your chart for clarity.
Key Features:
Custom Hourly Lines:
Draw horizontal lines for a specific minute range within each hour, e.g., from the 45th minute to the 15th minute of the next hour.
Multi-Hour Support:
Choose how many past hours to display. The indicator will replicate the line for each selected hourly period, following the same minute logic.
Automatic Start/End Logic:
If your chosen start minute is in the previous hour, the line correctly begins at that time.
The end minute can cross into the next hour when applicable.
If the selected end minute does not yet exist in the current chart data, the line will extend to the latest available bar.
Dedicated Indicator Pane:
Lines appear in a fixed, non-intrusive y-axis within the indicator pane (overlay=false), keeping your price chart clean.
Customizable Appearance:
Line Color: Choose any color to match your chart theme.
Line Thickness: Adjust the width of the lines for better visibility.
Inputs:
Input Name Type Default Description
Line Color Color Orange The color of the horizontal lines.
Line Thickness Integer 2 The thickness of each line (1–5).
Start Minute Integer 5 The minute within the hour where the line begins (0–59).
End Minute Integer 25 The minute within the hour where the line ends (0–59).
Hours Back Integer 3 Number of past hours to display lines for.
Use Cases:
Intraday Analysis: Quickly visualize recurring minute ranges across multiple hours.
Session Tracking: Mark critical time windows for trading sessions or market events.
Pattern Recognition: Easily identify time-based patterns or setups without cluttering the price chart.
How It Works:
The indicator calculates the nearest bars corresponding to your start and end minutes.
It draws horizontal lines at a fixed y-axis value within the indicator pane.
Lines are drawn for each selected past hour, replicating the chosen minute span.
All logic respects the actual chart data; lines never extend into the future beyond the most recent bar.
Notes:
Overlay is set to false, so lines appear in a dedicated pane below the price chart.
The indicator is fully compatible with any timeframe. Lines adjust automatically to match the chart’s bar spacing.
You can change the number of hours displayed at any time without affecting existing lines.
If you want, I can also draft a shorter “TradingView Store / Public Library description” version under 500 characters for the “Short Description” field — concise and punchy for users scrolling through indicators.
Londen & New York Sessies (UTC+2)This script highlights the London and New York trading sessions on the chart, adjusted for UTC+2 timezone. It's designed to help traders easily visualize the most active and liquid periods of the Forex and global markets directly on their TradingView charts. The London session typically provides strong volatility, while the New York session brings increased momentum and overlaps with London for powerful trading opportunities. Ideal for intraday and session-based strategies.
Entry (MTF) - Three phase Reversal patternOf course. We can absolutely reframe the explanation to give the strategy a more unique or generalized name, focusing on the concepts rather than the specific mentor.
Here is a revised, in-depth guide for your "Entry(MTF)" indicator, presented as the **"Momentum Shift Entry Model."**
***
### Entry (MTF) Indicator: A Guide to the Momentum Shift Model
This powerful indicator is designed to automatically detect a high-probability **Momentum Shift Entry Pattern**. The core strategy is to identify moments where the market's direction is likely to make a significant and sustained reversal, often driven by institutional order flow.
The indicator's key advantage is its **Multi-Timeframe (MTF)** functionality. It allows you to find these robust setups on a higher timeframe (like the daily chart) and then projects those signals onto your active, lower timeframe chart (like the 15-minute), providing a clear strategic edge for timing your entries.
---
## The Core Logic: The Three-Phase Reversal Pattern
This indicator is not based on a simple lagging condition. It looks for a specific three-step sequence of events. This sequence validates a genuine shift in market control from sellers to buyers (or vice-versa), filtering out false moves.
### Step 1: The Liquidity Purge 🎯
First, the indicator identifies recent, significant swing highs and lows on the chart. These price levels are natural magnets for liquidity, as many traders place their stop-loss orders there.
* **A Bullish Setup** begins when the price first dips **below a recent swing low**. This action is often an engineered move to "purge" or "sweep" the sell-side liquidity resting there before a move higher.
* **A Bearish Setup** begins with a price spike **above a recent swing high**, clearing out the buy-side liquidity.
This initial phase is designed to trap traders on the wrong side of the market before the true move begins.
### Step 2: The Market Structure Shift (The Confirmation) 🔄
After the liquidity has been taken, the indicator needs confirmation that a real power shift has occurred. This is confirmed by a **Market Structure Shift (MSS)**.
* After a **bullish purge (of a low)**, an MSS is confirmed when the price aggressively rallies and closes **above a recent swing *high***. This proves that buyers have not only absorbed all the selling but are now strong enough to break previous resistance levels.
* After a **bearish purge (of a high)**, an MSS is confirmed when the price falls and closes **below a recent swing *low***, showing that sellers are now decisively in command.
### Step 3: The Price Imbalance (The Entry Zone) GAP) is created during the same powerful move that caused the Market Structure Shift. A Fair Value Gap, or **price imbalance**, is a three-candle pattern that signifies a very aggressive, one-sided move, leaving a gap in the market that price will often seek to re-fill.
This FVG acts as the signature of institutional activity and becomes a high-probability zone for planning a trade entry.
---
## How to Use the Indicator in Your Trading
The true strength of this indicator lies in combining the higher-timeframe signal with the immediate context of your trading timeframe.
### Reading the Signals and Visuals
* **`BUY` / `SELL` Labels:** These are your primary signals, generated from the **"Signal Timeframe"** you select (e.g., Daily). A "BUY" label indicates that the complete three-phase bullish pattern has been confirmed on that higher timeframe.
* **Dotted Lines (Liquidity Levels):** The red and green dotted lines on your chart mark the most recent swing high and low on your **current timeframe**. These are the levels to watch for a potential "Liquidity Purge."
* **Colored Boxes (Imbalance Zones):** The green (bullish) and red (bearish) boxes highlight the Fair Value Gaps on your **current timeframe**. These are your potential entry zones.
### A Potential Trading Strategy
1. **Set Your Signal Timeframe:** Choose a higher timeframe that you use to define the overall trend (e.g., 'D' for daily, '4H' for 4-hour).
2. **Wait for an HTF Signal:** Patiently wait for a `BUY` or `SELL` label to appear. This is your cue to begin actively looking for an entry.
3. **Find a Local Entry Zone:** Once a `BUY` signal from the higher timeframe appears, look for the price on your current chart to retrace into a nearby **bullish FVG (green box)**. For a `SELL` signal, look for a pullback into a **bearish FVG (red box)**.
4. **Entry:** Plan your entry as the price tests this imbalance zone.
5. **Stop Loss:** A logical stop loss is critical. For a buy trade, place your stop below the swing low that was formed during the MSS. For a sell trade, place it above the corresponding swing high.
6. **Take Profit:** Aim for a significant liquidity level on a higher timeframe or use a predetermined risk-to-reward ratio (e.g., 1:2, 1:3).
---
## Customizing the Settings
* **`Signal Timeframe`**: The most critical setting. It determines the timeframe from which the core buy/sell logic originates. A Daily signal will carry more weight than an H1 signal.
* **`Liquidity/MSS Lookback`**: This controls the significance of the swing points the indicator uses.
* **Higher value:** Finds major, long-term swing points, leading to fewer but more powerful signals.
* **Lower value:** Finds minor, short-term swing points, leading to more frequent but potentially less reliable signals.
* **`Show Current TF Fair Value Gaps`**: This toggles the visibility of the imbalance zones (FVG boxes) on your chart. It is highly recommended to keep this enabled to easily spot your entry areas.
Reversal Entries [akshaykiriti1443]Reversal Entries : An In-Depth Guide
This indicator is designed to identify high-probability trend reversal points. Its primary goal is to pinpoint moments where the price attempts to break a key level, fails, and then snaps back with force. These "fakeouts" or "liquidity grabs" are often powerful signals that the market is about to reverse course.
The indicator provides two clear signals:
* 🟢 **A Bullish "Bounce Point"**: A potential buy signal after price dips below support and recovers.
* 🔴 **A Bearish "Rejection Point"**: A potential sell signal after price spikes above resistance and is pushed back down.
---
## The Core Logic: What Makes a Signal?
The indicator doesn't just look at one factor. Instead, it requires **three key conditions** to be met simultaneously before it generates a signal. This multi-layered approach helps filter out noise and identify only the most promising setups.
### 1. The Price Action "Fakeout" 🕵️♂️
This is the foundation of the signal. The indicator first identifies a short-term support or resistance level.
* **Support:** The lowest price over the `Lookback` period.
* **Resistance:** The highest price over the `Lookback` period.
It then waits for a specific pattern:
* For a **Bullish Bounce**, the current candle's low must dip **below** the support level, but its closing price must be **above** that same support level. This shows that sellers tried to push the price down but buyers stepped in with overwhelming force.
* For a **Bearish Rejection**, the current candle's high must poke **above** the resistance level, but its closing price must be **below** that same resistance level. This shows that buyers tried to break out, but sellers took control and slammed the price back down.
### 2. Volume Confirmation 🔊
A true reversal is almost always accompanied by a surge in trading activity. The indicator confirms the price action by checking for a **volume spike**.
It calculates the recent average volume and only accepts the signal if the volume on the reversal candle is significantly higher than that average (the default is 1.5 times higher). This confirms that there is real conviction and money behind the move, making it much more reliable.
### 3. Recovery Strength & Probability Score 💯
This is the indicator's "secret sauce." It doesn't just see a reversal; it measures *how strong* that reversal is.
* **Measuring the Recovery:** It uses the Average True Range (ATR) to measure the size of the price's recovery. For a bullish bounce, it measures the distance from the candle's low to its close. For a bearish rejection, it measures the distance from the high to the close. A long wick in the direction of the reversal signifies a powerful rejection of lower or higher prices.
* **Calculating a Probability Score:** The indicator takes the volume spike confirmation and the recovery strength and feeds them into a mathematical formula (a sigmoid function) to generate a "probability score" between 0 and 1. Think of this as a confidence score.
* **Applying the Threshold:** A signal is only plotted on your chart if this confidence score is above the `Probability Threshold` (default is 0.7, or 70%). This is the final filter that ensures only high-conviction setups are shown.
---
## How to Use the Indicator in Your Trading
This indicator provides entry signals, but it should be used as part of a complete trading plan.
### Understanding the Signals
* **Green `+` (Bounce Point):** When you see this signal below a candle, it's a potential **BUY entry**. It suggests that the downward momentum has been rejected and the price may be ready to move higher.
* **Red `-` (Rejection Point):** When you see this signal above a candle, it's a potential **SELL entry**. It suggests that the upward momentum has failed and the price may be ready to fall.
### Example Trading Strategy
1. **Entry:** Enter a trade when a signal appears. For a green `+`, place a buy order. For a red `-`, place a sell order.
2. **Stop Loss:** A logical stop loss is crucial.
* For a **buy trade**, place your stop loss just below the low of the signal candle. If the price breaks this low, the reversal idea is invalidated.
* For a **sell trade**, place your stop loss just above the high of the signal candle. If the price breaks this high, the setup has failed.
3. **Take Profit:** Your take profit should be based on your own strategy. A common approach is to target the next significant support or resistance level or use a fixed risk-to-reward ratio (e.g., 1:1.5 or 1:2).
**Important:** Always consider the overall market context. These signals tend to be more powerful when they align with the broader trend or occur at major, higher-timeframe support and resistance zones.
---
## Customizing the Settings
You can fine-tune the indicator's sensitivity in the settings menu to match your trading style and the asset you are trading.
* **`Support/Resistance Lookback`**: Controls how far back the indicator looks to find support and resistance. A **smaller number** makes it more sensitive to very recent price action. A **larger number** will focus on more significant, longer-term levels.
* **`Volume Spike Multiplier`**: Defines what counts as a "spike." Increasing this value (e.g., to 2.0) will demand a much larger volume surge, leading to fewer but potentially more reliable signals.
* **`ATR for Recovery`**: This sets the period for the ATR calculation, which is used to measure the recovery strength. It's generally best to leave this at its default unless you are an advanced user.
* **`Probability Threshold`**: This is the most important sensitivity setting.
* **Increase it** (e.g., to 0.85) for fewer, very high-quality signals.
* **Decrease it** (e.g., to 0.60) to see more potential setups, though some may be less reliable.
Wyckoff Stage Approximator (MTF Alerts)Wyckoff Stage Approximator (MTF Context)
This indicator is a powerful tool designed for traders who use a top-down, multi-timeframe approach based on Wyckoff principles. Its primary function is to identify the market's current stage—consolidation (Stage 1) or trend (Stage 2)—on a higher Context (C) timeframe and project that analysis onto your lower Validation (V) and Entry (E) charts.
This ensures you are always trading in alignment with the "big picture" trend, preventing you from taking low-probability trades based on lower-timeframe noise.
Core Concept: Top-Down Analysis
The script solves a common problem for multi-timeframe traders: losing sight of the primary trend. By locking the background color to your chosen Context timeframe (e.g., 15-minute), you are constantly reminded of the market's true state.
🟡 Yellow Background (Stage 1): The Context timeframe is in consolidation. This is a time to be patient and wait for a clear directional bias to emerge.
🟢 Green Background (Stage 2 - Markup): The Context timeframe is in a confirmed uptrend. This is your green light to look for bullish pullback opportunities on your lower timeframes.
🔴 Red Background (Stage 2 - Markdown): The Context timeframe is in a confirmed downtrend. This is your signal to look for bearish rally opportunities.
How It Works
The indicator uses a combination of moving averages and trend strength to objectively define each stage:
Trend Alignment: It checks if the 5 EMA, 10 EMA, and 20 EMA are properly stacked above or below the 50 SMA to determine the potential trend direction.
Trend Strength: It uses the ADX to measure the strength of the trend. A trend is only confirmed as Stage 2 if the ADX is above a user-defined threshold (default is 23), filtering out weak or choppy moves.
Stage Definition: Any period that is not a confirmed, strong Stage 2 Markup or Markdown is classified as a Stage 1 consolidation phase.
Key Features
Multi-Timeframe (MTF) Projection: Select your master "Context" timeframe, and its analysis will be displayed on any chart you view.
Customizable Inputs: Easily adjust the moving average lengths and ADX threshold to fit your specific strategy and the asset you are trading.
Clear Visual Cues: The intuitive background coloring makes it easy to assess the market environment at a glance.
Stage Transition Alerts: Set up specific alerts to be notified the moment your Context timeframe shifts from a Stage 1 consolidation to a Stage 2 trend, ensuring you never miss a potential setup.
How to Use This Indicator
Add the indicator to your chart.
In the settings, set the "Context Timeframe" to your highest timeframe (e.g., "15" for 15-minute).
Create alerts for the "Stage 1 -> Stage 2" conditions.
When you receive an alert, it signals that a potential trend is beginning on your Context chart.
Switch to your lower Validation and Entry timeframes. The background color will confirm the higher-timeframe trend, giving you the confidence to look for your specific entry patterns.
Disclaimer: This tool is designed for confluence and environmental analysis. It is not a standalone signal generator. It should be used in conjunction with your own price action, volume, or order flow analysis to validate trade entries.
TDS9 Counting (Red & Blue, Offset Labels)Here’s a polished, **publication‑ready narrative** for your *TDS9 Counting (Red & Blue, Offset Labels)* indicator, written in the same style as the previous ones:
---
**TDS9 Counting (Red & Blue, Offset Labels)**
This indicator implements a sequential counting method to help traders identify potential exhaustion points in ongoing trends. It tracks sequences of price closes relative to the prior 4 bars, building up to a **9‑count structure** that often signals areas where momentum may be weakening and a reversal or pause could occur.
The script automatically labels counts **6 through 9** directly on the chart, with clear **color‑coded markers**:
- **Red numbers** for downward sequences (bearish setups)
- **Dark blue numbers** for upward sequences (bullish setups)
- A **red “9”** highlights a potential exhaustion point in an uptrend, while a **blue “9”** marks exhaustion in a downtrend
To maintain chart clarity, labels are **offset slightly above or below candles** using dynamic spacing, ensuring signals remain visible without overlapping price action. This makes it easy to track the progression of counts in real time while keeping the chart clean and readable.
By combining structured sequential logic with intuitive visual cues, this tool helps traders:
- Monitor developing **trend exhaustion patterns**
- Anticipate potential **reversal or consolidation zones**
- Add a **systematic layer of confirmation** to existing strategies
- Keep charts uncluttered with offset, color‑coded labels
Whether you’re a discretionary trader looking for exhaustion confirmation or a systematic trader layering signals into a broader strategy, this indicator provides a **clear, structured framework** for spotting potential turning points in price action.
Wyckoff Accumulation / Distribution Detector (v3)🌱 Spring (Bullish Wyckoff Signature)
🧠 Definition
A Spring happens when price dips below a well-defined support level, usually near the end of an accumulation phase, then quickly reverses back above support.
This is not ordinary volatility — it's usually intentional by large operators (“Composite Man”) to:
Trigger stop-losses of weak holders
Create the illusion of a breakdown to scare late sellers in
Absorb all remaining supply at low prices
Launch the next markup leg once weak hands are flushed out
🧭 Typical Spring Characteristics
Feature Behavior
Location Near the bottom of a trading range after a decline
Price Action Temporary breakdown below support, then sharp reversal above
Volume Usually low to average on the break, indicating lack of real selling pressure. Sometimes a volume surge on the reversal as strong hands step in
Candle Often shows a long lower wick, closes back inside the range
Intent Shakeout of weak holders, allow institutions to accumulate more quietly
📈 Why It's Bullish
Springs typically mark the final test of supply. If price can dip below support and immediately recover, it means:
Selling pressure is exhausted (no follow-through)
Strong hands are absorbing remaining shares
A bullish breakout is often imminent
🪤 Upthrust (Bearish Wyckoff Signature)
🧠 Definition
An Upthrust is the mirror image of a Spring. It happens when price pokes above a resistance level, usually near the end of a distribution phase, but then fails to hold above it and falls back inside the range.
This is typically smart money distributing to eager buyers:
Late breakout traders pile in
Institutions sell into that strength
Price collapses back into the range, trapping breakout buyers
🧭 Typical Upthrust Characteristics
Feature Behavior
Location Near the top of a trading range after a rally
Price Action Temporary breakout above resistance, then quick reversal down
Volume Frequently low on the breakout, suggesting a lack of real buying interest — or sometimes high but with no progress, showing hidden selling
Candle Often shows a long upper wick, closes back inside the range
Intent Trap breakout buyers, provide liquidity for institutional sellers to unload near highs
📉 Why It's Bearish
Upthrusts show demand failure and supply swamping:
Buyers cannot sustain the breakout.
The sharp reversal signals large players are exiting.
Typically precedes markdown phases or sharp declines.
📝 Trading Implications
Spring → Often followed by a sign of strength rally → good long entry if confirmed with volume expansion and follow-through.
Upthrust → Often followed by a sign of weakness → short setups, especially if the next rally fails at lower highs.
The script looks for:
🌱 Spring:
Price makes a low below recent pivot support,
Closes back above,
Does so on low volume → likely a shakeout.
🪤 Upthrust:
Price makes a high above recent pivot resistance,
Closes back below,
On low volume → likely a bull trap.
The Crypteller LEVELSAutomatically shows key highs and lows from the previous day, week, and month — no need to mark them manually.
Keeps your chart clean — only the latest levels are visible.
Works on any timeframe, so you can instantly see where major liquidity sits.
Relative Volume at TimeIt tells you whether current trading activity is unusually high or low compared to typical levels at that same time in past sessions.
For example:
A reading of 2.0 means volume is twice the usual amount for this moment in the trading day.
A reading below 1.0 means volume is quieter than normal.
QUANTUM MOMENTUMOverview
Quantum Momentum is a sophisticated technical analysis tool designed to help traders identify relative strength between assets through advanced momentum comparison. This cyberpunk-themed indicator visualizes momentum dynamics between your current trading symbol and any comparison asset of your choice, making it ideal for pairs trading, crypto correlation analysis, and multi-asset portfolio management.
Key Features
📊 Multi-Asset Momentum Comparison
Dual Symbol Analysis: Compare momentum between your chart symbol and any other tradable asset
Real-Time Tracking: Monitor relative momentum strength as market conditions evolve
Difference Visualization: Clear histogram display showing which asset has stronger momentum
🎯 Multiple Momentum Calculation Methods
Choose from four different momentum calculation types:
ROC (Rate of Change): Traditional percentage-based momentum measurement
RSI (Relative Strength Index): Oscillator-based momentum from 0-100 range
Percent Change: Simple percentage change over the lookback period
Raw Change: Absolute price change in native currency units
📈 Advanced Trend Filtering System
Enable optional trend filters to align momentum signals with prevailing market direction:
SMA (Simple Moving Average): Classic trend identification
EMA (Exponential Moving Average): Responsive trend detection
Price Action: Identifies trends through higher highs/lows or lower highs/lows patterns
ADX (Average Directional Index): Measures trend strength with customizable threshold
🎨 Futuristic Cyberpunk Design
Neon Color Scheme: Eye-catching cyan, magenta, and matrix green color palette
Glowing Visual Effects: Enhanced visibility with luminescent plot lines
Dynamic Background Shading: Subtle trend state visualization
Real-Time Data Table: Sleek information panel displaying current momentum values and trend status
How It Works
The indicator calculates momentum for both your current chart symbol and a comparison symbol (default: BTC/USDT) using your selected method and lookback period. The difference between these momentum values reveals which asset is exhibiting stronger momentum at any given time.
Positive Difference (Green): Your chart symbol has stronger momentum than the comparison asset
Negative Difference (Pink/Red): The comparison asset has stronger momentum than your chart symbol
When the trend filter is enabled, the indicator will only display signals that align with the detected market trend, helping filter out counter-trend noise.
Settings Guide
Symbol Settings
Compare Symbol: Choose any tradable asset to compare against (e.g., major indices, cryptocurrencies, forex pairs)
Momentum Settings
Momentum Length: Lookback period for momentum calculations (default: 14 bars)
Momentum Type: Select your preferred momentum calculation method
Display Options
Toggle visibility of current symbol momentum line
Toggle visibility of comparison symbol momentum line
Toggle visibility of momentum difference histogram
Optional zero line reference
Trend Filter Settings
Use Trend Filter: Enable/disable trend-based signal filtering
Trend Method: Choose from SMA, EMA, Price Action, or ADX
Trend Length: Period for trend calculations (default: 50)
ADX Threshold: Minimum ADX value to confirm trend strength (default: 25)
Best Use Cases
✅ Pairs Trading: Identify divergences in momentum between correlated assets
✅ Crypto Market Analysis: Compare altcoin momentum against Bitcoin or Ethereum
✅ Stock Market Rotation: Track sector or index relative strength
✅ Forex Strength Analysis: Monitor currency pair momentum relationships
✅ Multi-Timeframe Confirmation: Use alongside other indicators for confluence
✅ Mean Reversion Strategies: Spot extreme momentum divergences for potential reversals
Visual Indicators
⚡ Cyan Line: Your chart symbol's momentum
⚡ Magenta Line: Comparison symbol's momentum
📊 Green/Pink Histogram: Momentum difference (positive = green, negative = pink)
▲ Green Triangle: Bullish trend detected (when filter enabled)
▼ Red Triangle: Bearish trend detected (when filter enabled)
◈ Yellow Diamond: Neutral/sideways trend (when filter enabled)
Pro Tips
💡 Look for crossovers between the momentum lines as potential trade signals
💡 Combine with volume analysis for stronger confirmation
💡 Use momentum divergence (price making new highs/lows while momentum doesn't) for reversal signals
💡 Enable trend filter during ranging markets to reduce false signals
💡 Experiment with different momentum types to find what works best for your trading style
Technical Requirements
TradingView Pine Script Version: v6
Chart Type: Works on all chart types
Indicator Placement: Separate pane (overlay=false)
Data Requirements: Needs access to comparison symbol data
Forecast PriceTime Oracle [CHE] Forecast PriceTime Oracle — Prioritizes quality over quantity by using Power Pivots via RSI %B metric to forecast future pivot highs/lows in price and time
Summary
This indicator identifies potential pivot highs and lows based on out-of-bounds conditions in a modified RSI %B metric, then projects future occurrences by estimating time intervals and price changes from historical medians. It provides visual forecasts via diagonal and horizontal lines, tracks achievement with color changes and symbols, and displays a dashboard for statistical overview including hit rates. Signals are robust due to median-based aggregation, which reduces outlier influence, and optional tolerance settings for near-misses, making it suitable for anticipating reversals in ranging or trending markets.
Motivation: Why this design?
Standard pivot detection often lags or generates false signals in volatile conditions, missing the timing of true extrema. This design leverages out-of-bounds excursions in RSI %B to capture "Power Pivots" early—focusing on quality over quantity by prioritizing significant extrema rather than every minor swing—then uses historical deltas in time and price to forecast the next ones, addressing the need for proactive rather than reactive analysis. It assumes that pivot spacing follows statistical patterns, allowing users to prepare entries or exits ahead of confirmation.
What’s different vs. standard approaches?
- Reference baseline: Diverges from traditional ta.pivothigh/low, which require fixed left/right lengths and confirm only after bars close, often too late for dynamic markets.
- Architecture differences:
- Detects extrema during OOB runs rather than post-bar symmetry.
- Aggregates deltas via medians (or alternatives) over a user-defined history, capping arrays to manage resources.
- Applies tolerance thresholds for hit detection, with options for percentage, absolute, or volatility-adjusted (ATR) flexibility.
- Freezes achieved forecasts with visual states to avoid clutter.
- Practical effect: Charts show proactive dashed projections instead of retrospective dots; the dashboard reveals evolving hit rates, helping users gauge reliability over time without manual calculation.
How it works (technical)
The indicator first computes a smoothed RSI over a specified length, then applies Bollinger Bands to derive %B, flagging out-of-bounds below zero or above one hundred as potential run starts. During these runs, it tracks the extreme high or low price and bar index. Upon exit from the OOB state, it confirms the Power Pivot at that extreme and records the time delta (bars since prior) and price change percentage to rolling arrays.
For forecasts, it calculates the median (or selected statistic) of recent deltas, subtracts the confirmation delay (bars from apex to exit), and projects ahead by that adjusted amount. Price targets use the median change applied to the origin pivot value. Lines are drawn from the apex to the target bar and price, with a short horizontal at the endpoint. Arrays store up to five active forecasts, pruning oldest on overflow.
Tolerance adjusts hit checks: for highs, if the high reaches or exceeds the target (adjusted by tolerance); for lows, if the low drops to or below. Once hit, the forecast freezes, changing colors and symbols, and extends the horizontal to the hit bar. Persistent variables maintain last pivot states across bars; arrays initialize empty and grow until capped at history length.
Parameter Guide
Source: Specifies the data input for the RSI computation, influencing how price action is captured. Default is close. For conservative signals in noisy environments, switch to high; using low boosts responsiveness but may increase false positives.
RSI Length: Sets the smoothing period for the RSI calculation, with longer values helping to filter out whipsaws. Default is 32. Opt for shorter lengths like 14 to 21 on faster timeframes for quicker reactions, or extend to 50 or more in strong trends to enhance stability at the cost of some lag.
BB Length: Defines the period for the Bollinger Bands applied to %B, directly affecting how often out-of-bounds conditions are triggered. Default is 20. Align it with the RSI length: shorter periods detect more potential runs but risk added noise, while longer ones provide better filtering yet might overlook emerging extrema.
BB StdDev: Controls the multiplier for the standard deviation in the bands, where wider settings reduce false out-of-bounds alerts. Default is 2.0. Narrow it to 1.5 for highly volatile assets to catch more signals, or broaden to 2.5 or higher to emphasize only major movements.
Show Price Forecast: Enables or disables the display of diagonal and target lines along with their updates. Default is true. Turn it off for simpler chart views, or keep it on to aid in trade planning.
History Length: Determines the number of recent pivot samples used for median-based statistics, where more history leads to smoother but potentially less current estimates. Default is 50. Start with a minimum of 5 to build data; limit to 100 to 200 to prevent outdated regimes from skewing results.
Max Lookahead: Limits the number of bars projected forward to avoid overly extended lines. Default is 500. Reduce to 100 to 200 for intraday focus, or increase for longer swing horizons.
Stat Method: Selects the aggregation technique for time and price deltas: Median for robustness against outliers, Trimmed Mean (20%) for a balanced trim of extremes, or 75th Percentile for a conservative upward tilt. Default is Median. Use Median for even distributions; switch to Percentile when emphasizing potential upside in trending conditions.
Tolerance Type: Chooses the approach for flexible hit detection: None for exact matches, Percentage for relative adjustments, Absolute for fixed point offsets, or ATR for scaling with volatility. Default is None. Begin with Percentage at 0.5 percent for currency pairs, or ATR for adapting to cryptocurrency swings.
Tolerance %: Provides the relative buffer when using Percentage mode, forgiving small deviations. Default is 0.5. Set between 0.2 and 1.0 percent; higher values accommodate gaps but can overstate hit counts.
Tolerance Points: Establishes a fixed offset in price units for Absolute mode. Default is 0.0010. Tailor to the asset, such as 0.0001 for forex pairs, and validate against past wick behavior.
ATR Length: Specifies the period for the Average True Range in dynamic tolerance calculations. Default is 14. This is the standard setting; shorten to 10 to reflect more recent volatility.
ATR Multiplier: Adjusts the ATR scale for tolerance width in ATR mode. Default is 0.5. Range from 0.3 for tighter precision to 0.8 for greater leniency.
Dashboard Location: Positions the summary table on the chart. Default is Bottom Right. Consider Top Left for better visibility on mobile devices.
Dashboard Size: Controls the text scaling for dashboard readability. Default is Normal. Choose Tiny for dense overlays or Large for detailed review sessions.
Text/Frame Color: Sets the color scheme for dashboard text and borders. Default is gray. Align with your chart theme, opting for lighter shades on dark backgrounds.
Reading & Interpretation
Forecast lines appear as dashed diagonals from confirmed pivots to projected targets, with solid horizontals at endpoints marking price levels. Open targets show a target symbol (🎯); achieved ones switch to a trophy symbol (🏆) in gray, with lines fading to gray. The dashboard summarizes median time/price deltas, sample counts, and hit rates—rising rates indicate improving forecast alignment. Colors differentiate highs (red) from lows (lime); frozen states signal validated projections.
Practical Workflows & Combinations
- Trend following: Enter long on low forecast hits during uptrends (higher highs/lower lows structure); filter with EMA crossovers to ignore counter-trend signals.
- Reversal setups: Short above high projections in overextended rallies; use volume spikes as confirmation to reduce false breaks.
- Exits/Stops: Trail stops to prior pivot lows; conservative on low hit rates (below 50%), aggressive above 70% with tight tolerance.
- Multi-TF: Apply on 1H for entries, 4H for time projections; combine with Ichimoku clouds for confluence on targets.
- Risk management: Position size inversely to delta uncertainty (wider history = smaller bets); avoid low-liquidity sessions.
Behavior, Constraints & Performance
Confirmation occurs on OOB exit, so live-bar pivots may adjust until close, but projections update only on events to minimize repaint. No security or HTF calls, so no external lookahead issues. Arrays cap at history length with shifts; forecasts limited to five active, pruning FIFO. Loops iterate over small fixed sizes (e.g., up to 50 for stats), efficient on most hardware. Max lines/labels at 500 prevent overflow.
Known limits: Sensitive to OOB parameter tuning—too tight misses runs; assumes stationary pivot stats, which may shift in regime changes like low vol. Gaps or holidays distort time deltas.
Sensible Defaults & Quick Tuning
Defaults suit forex/crypto on 1H–4H: RSI 32/BB 20 for balanced detection, Median stats over 50 samples, None tolerance for exactness.
- Too many false runs: Increase BB StdDev to 2.5 or RSI Length to 50 for filtering.
- Lagging forecasts: Shorten History Length to 20; switch to 75th Percentile for forward bias.
- Missed near-hits: Enable Percentage tolerance at 0.3% to capture wicks without overcounting.
- Cluttered charts: Reduce Max Lookahead to 200; disable dashboard on lower TFs.
What this indicator is—and isn’t
This is a forecasting visualization layer for pivot-based analysis, highlighting statistical projections from historical patterns. It is not a standalone system—pair with price action, volume, and risk rules. Not predictive of all turns; focuses on OOB-derived extrema, ignoring volume or news impacts.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Herd Flow Oscillator — Volume Distribution Herd Flow Oscillator — Scientific Volume Distribution (herd-accurate rev)
A composite order-flow oscillator designed to surface true herding behavior — not just random bursts of buying or selling.
It’s built to detect when market participants start acting together, showing persistent, one-sided activity that statistically breaks away from normal market randomness.
Unlike traditional volume or momentum indicators, this tool doesn’t just look for “who’s buying” or “who’s selling.”
It tries to quantify crowd behavior by blending multiple statistical tests that describe how collective sentiment and coordination unfold in price and volume dynamics.
What it shows
The Herd Flow Oscillator works as a multi-layer detector of crowd-driven flow in the market. It examines how signed volume (buy vs. sell pressure) evolves, how persistent it is, and whether those actions are unusually coordinated compared to random expectations.
HerdFlow Composite (z) — the main signal line, showing how statistically extreme the current herding pressure is.
When this crosses above or below your set thresholds, it suggests a high probability of collective buying or selling.
You can optionally reveal component panels for deeper insight into why herding is detected:
DVI (Directional Volume Imbalance): Measures the ratio of bullish vs. bearish volume.
If it’s strongly positive, more volume is hitting the ask (buying); if negative, more is hitting the bid (selling).
LSV-style Herd Index : Inspired by academic finance measures of “herding.”
It compares how often volume is buying vs. selling versus what would happen by random chance.
If the result is significantly above chance, it means traders are collectively biased in one direction.
O rder-Flow Persistence (ρ 1..K): Averages autocorrelation of signed volume over several lags.
In simpler terms: checks if buying/selling pressure tends to continue in the same direction across bars.
Positive persistence = ongoing coordination, not just isolated trades.
Runs-Test Herding (−Z) : Statistical test that checks how often trade direction flips.
When there are fewer direction changes than expected, it means trades are clustering — a hallmark of herd behavior.
Skew (signed volume): Measures whether signed volume is heavily tilted to one side.
A positive skew means more aggressive buying bursts; a negative skew means more intense selling bursts.
CVD Slope (z): Looks at the slope of the Cumulative Volume Delta — essentially how quickly buy/sell pressure is accelerating.
It’s a short-term flow acceleration measure.
Shapes & background
▲ “BH” at the bottom = Bull Herding; ▼ “BH-” at the top = Bear Herding.
These markers appear when all conditions align to confirm a herding regime.
Persistence and clustering both confirm coordinated downside flow.
Core Windows
Primary Window (N) — the main sample length for herding calculations.
It’s like the "memory span" for detecting coordinated behavior. A longer N means smoother, more reliable signals.
Short Window (Nshort) — used for short-term measurements like imbalance and slope.
Smaller values react faster but can be noisy; larger values are steadier but slower.
Long Window (Nlong) — used for z-score normalization (statistical scaling).
This helps the indicator understand what’s “normal” behavior over a longer horizon, so it can spot when things deviate too far.
Autocorr lags (acLags) — how many steps to check when measuring persistence.
Higher values (e.g., 3–5) look further back to see if trends are truly continuing.
Calculation Options
Price Proxy for Tick Rule — defines how to decide if a trade is “buy” or “sell.”
hlc3 (average of high, low, and close) works as a neutral, smooth price proxy.
Use ATR for scaling — keeps signals comparable across assets and timeframes by dividing by volatility (ATR).
Prevents high-volatility periods from dominating the signal.
Median Filter (bars) — smooths out erratic data spikes without heavily lagging the response.
Odd values like 3 or 5 work best.
Signal Thresholds
Composite z-threshold — determines how extreme behavior must be before it counts as “herding.”
Higher values = fewer, more confident signals.
Imbalance threshold — the minimum directional volume imbalance to trigger interest.
Plotting
Show component panels — useful for analysts and developers who want to inspect the math behind signals.
Fill strong herding zones — purely visual aid to highlight key periods of coordinated trading.
How to use it (practical tips)
Understand the purpose: This is not just a “buy/sell” tool.
It’s a behavioral detector that identifies when traders or algorithms start acting in the same direction.
Timeframe flexibility:
15m–1h: reveals short-term crowd shifts.
4h–1D: better for swing-trade context and institutional positioning.
Combine with structure or trend:
When HerdFlow confirms a bullish regime during a breakout or retest, it adds confidence.
Conversely, a bearish cluster at resistance may hint at a crowd-driven rejection.
Threshold tuning:
To make it more selective, increase zThr and imbThr.
To make it more sensitive, lower those thresholds but expand your primary window N for smoother results.
Cross-market consistency:
Keep “Use ATR for scaling” enabled to maintain consistency across different instruments or timeframes.
Denoising:
A small median filter (3–5 bars) removes flicker from volume spikes but still preserves the essential crowd patterns.
Reading the components (why signals fire)
Each sub-metric describes a unique “dimension” of crowd behavior:
DVI: how imbalanced buying vs selling is.
Herd Index: how biased that imbalance is compared to random expectation.
Persistence (ρ): how continuous those flows are.
Runs-Test: how clumped together trades are — clustering means the crowd’s acting in sync.
Skew: how lopsided the volume distribution is — sudden surges of one-sided aggression.
CVD Slope: how strongly accelerating the current directional flow is.
When all of these line up, you’re seeing evidence that market participants are collectively moving in the same direction — i.e., true herding.
Quarterly Theory True Opens by Mr. ConsistentQuarterly Theory True Opens (MTF)
This indicator plots key institutional price levels known as "True Opens" based on the principles of Quarterly Theory, as taught by Trader Daye. It is designed to identify the start of Q2 manipulation cycles across yearly, monthly, weekly, daily, and intra-day session timeframes.
The levels are drawn as clean horizontal rays and are anchored to the 1-minute timeframe, ensuring they are perfectly accurate and consistent on ANY chart timeframe you view.
🎯 Core Concepts
Each line represents the "True Open" at the start of a new Q2 cycle:
📅 Yearly True Open: The open of the first trading day of April.
🗓️ Monthly True Open: The open of the second Monday of each month.
Weekly True Open: The open of the Monday 6:00 PM EST session.
🏙️ Daily True Open: The open at Midnight EST.
⏰ Session True Opens: The open at the start of the second 90-minute quarter of each session (1:30 AM, 7:30 AM, 1:30 PM, 7:30 PM EST).
✨ Key Features
Multi-Timeframe (MTF) Accuracy: Lines are anchored to the 1-minute open price, ensuring they remain perfectly consistent on any chart timeframe (e.g., the 7:30 AM open is the same on the 5min, 1-hour, and Daily charts).
Clean Horizontal Rays: Plots clean horizontal rays that extend forward, avoiding chart clutter. Old lines are automatically removed as new ones form.
Right-Aligned Labels: Text labels are positioned on the right edge of your screen, so they are always visible and never covered by price action.
Fully Customizable: Toggle the visibility of each True Open line (Yearly, Monthly, etc.) and their labels individually in the settings. You can also customize colors and line width.
New York (EST) Timezone: All calculations are hard-coded to the America/New_York timezone for consistency.
⚙️ How to Use
Use these levels as key points of interest for potential support, resistance, or areas where price may show a significant reaction.
Observe how price interacts with these levels after they are established.
Customize the indicator in the settings (⚙️ icon) to show only the levels relevant to your trading style.
⚠️ Troubleshooting: Lines Not Showing Correctly?
If the indicator lines don't seem to plot at the correct price levels when you first add it to your chart, it's almost always a scaling issue.
Hover over the indicator's name on your chart and click the three dots (...) for "More".
Scroll down to "Pin to Scale".
Select "Pin to Right Scale" (or whichever scale your price is on). The indicator levels must be pinned to the same scale as the price to display accurately.
If it is set to "No Scale," the levels will not reflect their true price values.
This tool was developed based on the public teachings of Trader Daye. All credit for the underlying concepts of Quarterly Theory belongs to him. This indicator is for educational and analytical purposes only.
Mark the New York trading session hours（纽约交易时间段标注）Apply background shading for New York time.
（纽约时间背景着色）
04：00 ~ 09：00
09：00 ~ 09：30
09：30 ~ 12：00
No shading needed after 12 AM as I'll be asleep.
（12点我睡觉了就不着色了。）
TFPV — FULL Radial Kernel MA (Short/Long, Time Folding, Colored)TFPV is a pair of adaptive moving averages built with a radial kernel (Gaussian/Laplacian/Cauchy) on a joint metric of time, price, and volume. It can “fold” time along the market’s dominant cycle so that bars separated by entire cycles still contribute as if they were near each other—helpful for cyclical or range-bound markets. The short/long lines auto-color by regime and include cross alerts.
What it does
Radial-kernel averaging: Weights past bars by their distance from the current bar in a 3-axis space:
Time (αₜ): linear distance or cycle-aware phase distance
Price (αₚ): normalized by robust price scale
Volume (αᵥ): normalized by (log) volume scale
Time folding: Choose Linear (standard) or Circular using:
Homodyne (Hilbert) dominant period, or
ACF (autocorrelation) dominant period
This compresses distances for bars that are one or more full cycles apart, improving smoothing without lagging trends.
Adaptive scales: Price/volume bandwidths use Robust MAD, Stdev, or ATR. Optional Super Smoother center reduces noise before measuring distances.
Visual regime coloring: Short above Long → teal (bullish). Short below Long → orange (bearish). Optional fill highlights the spread.
How to read it
Trend filter: Trade in the direction of the color (teal bullish, orange bearish).
Crossovers: Short crossing above Long often marks early trend continuation after pullbacks; crossing below can warn of weakening momentum.
Spread width: A widening gap suggests strengthening trend; a shrinking gap hints at consolidation or a possible regime change.
Key settings
Lengths
Short/Long window: Lookback for each radial MA. Short reacts faster; Long stabilizes the regime.
Kernel & Metric
Kernel: Gaussian, Laplacian, or Cauchy (default). Cauchy is heavier-tailed (keeps more outliers), Gaussian is tighter.
Axis weights (αₜ, αₚ, αᵥ): Importance of time/price/volume distances. Increase a weight to make that axis matter more.
Ignore weights below: Hard cutoff for tiny kernel weights to speed up/clean contributions.
Time Folding
Topology: Linear (standard MA behavior) or Circular (Homodyne/ACF) (cycle-aware).
Cycle floor/ceil: Bounds for the dominant period search.
σₜ mode: Auto sets time bandwidth from the detected period (or length in Linear mode) × multiplier; Manual fixes σₜ in bars.
Price/Volume Scaling
Price scale: Robust MAD (outlier-resistant), Stdev, or ATR (trend-aware).
σₚ/σᵥ multipliers: Bandwidths for price/volume axes. Larger values = looser matching (smoother, more lag).
Use log(volume): Stabilizes volume’s scale across regimes; recommended.
Kernel Center
Price center: Raw (close) or Super Smoother to reduce noise before measuring price distance.
Plotting
Plot source: Show/hide the input source.
Fill between lines: Visual emphasis of the short/long spread.
Tips
Start with defaults: Cauchy, Circular (Homodyne), Robust MAD, log-volume on.
For choppy/cyclical symbols, Circular time folding often reduces false flips.
If signals feel too twitchy, either increase Short/Long lengths or raise σₚ/σᵥ multipliers (looser kernel).
For strong trends with regime shifts, try ATR price scaling.
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.
Volume Rate of Change (VROC)# Volume Rate of Change (VROC)
**What it is:** VROC measures the rate of change in trading volume over a specified period, typically expressed as a percentage. Formula: `((Current Volume - Volume n periods ago) / Volume n periods ago) × 100`
## **Obvious Uses**
**1. Confirming Price Trends**
- Rising VROC with rising prices = strong bullish trend
- Rising VROC with falling prices = strong bearish trend
- Validates that price movements have conviction behind them
**2. Spotting Divergences**
- Price makes new highs but VROC doesn't = weakening momentum
- Price makes new lows but VROC doesn't = potential reversal
**3. Identifying Breakouts**
- Sudden VROC spikes often accompany legitimate breakouts from consolidation patterns
- Helps distinguish real breakouts from false ones
**4. Overbought/Oversold Conditions**
- Extreme VROC readings (very high or very low) suggest exhaustion
- Mean reversion opportunities when volume extremes occur
---
## **Non-Obvious Uses**
**1. Smart Money vs. Dumb Money Detection**
- Declining VROC during price rallies may indicate retail FOMO while institutions distribute
- Rising VROC during selloffs with price stability suggests institutional accumulation
**2. News Impact Measurement**
- Compare VROC before/after earnings or announcements
- Low VROC on "significant" news = market doesn't care (fade the move)
- High VROC = genuine market reaction (respect the move)
**3. Market Regime Changes**
- Persistent shifts in average VROC levels can signal transitions between bull/bear markets
- Declining baseline VROC over months = waning market participation/topping process
**4. Intraday Liquidity Profiling**
- VROC patterns across trading sessions identify best execution times
- Avoid trading when VROC is abnormally low (wider spreads, poor fills)
**5. Sector Rotation Analysis**
- Compare VROC across sector ETFs to identify where capital is flowing
- Rising VROC in defensive sectors + falling VROC in cyclicals = risk-off rotation
**6. Options Expiration Effects**
- VROC typically drops significantly post-options expiration
- Helps avoid false signals from mechanically-driven volume changes
**7. Algorithmic Activity Detection**
- Unusual VROC patterns (regular spikes at specific times) may indicate algo programs
- Can front-run or avoid periods of heavy algorithmic interference
**8. Liquidity Crisis Early Warning**
- Sharp, sustained VROC decline across multiple assets = liquidity withdrawal
- Can precede market stress events before price volatility emerges
**9. Cryptocurrency Wash Trading Detection**
- Comparing VROC across exchanges for same asset
- Discrepancies suggest artificial volume on certain platforms
**10. Pair Trading Optimization**
- Use relative VROC between correlated pairs
- Enter when VROC divergence is extreme, exit when it normalizes
The key to advanced VROC usage is context: combining it with price action, market structure, and other indicators rather than using it in isolation.
Seasonality Forecast 4H A seasonality indicator shows recurring patterns in data that occur at the same time each year, such as retail sales peaking during the holidays or demand for ice cream rising in the summer. These indicators are used in fields like business, economics, and finance to identify predictable, time-based fluctuations, allowing for better forecasting and strategic planning, like adjusting inventory or staffing levels. In trading, a seasonality indicator can show historical patterns, like an asset's tendency to rise or fall in a specific month, to provide additional context for decision-making.
Seasonality reasoning basically seasonality works most stably on the daily frame with the input parameter being trading day 254 or calendar day 365, ..
Use seasonal effects such as sell in May, buy Christmas season, or exploit factors such as sell on Friday, ... to track the price movement.
The lower the time frame, the more parameters need to be calculated and the more complicated. I have tried to code the version with 1 hour, 15 minutes and 4 hours time frames
On the statistical language R and Python, Pine script
Tradingview uses the exclusive and unique Pine language. There is a parameter limit, just need to change the number of forecast days or calculate shorter or only calculate the basic end time value, we seasonality still works
but the overall results are easily noisy and related to controlling the number of orders per week/month and risk management.
The 4-hour frame version works well because we exploit the seasonal factor according to the 4-hour trading session as a trading session
Every 4 hours we have an input value that corresponds to the Asian, European, and American trading sessions
4 hours - half a morning Asian session.4 hours - half an afternoon Asian session, 4 hours - half a morning European session, 4 hours - half an afternoon European session, similar to the US and repeat the cycle.
Input Parameter Declaration
Tradingview does not exist declaration form day_of_year = dayofyear(time) Pine Script v5:
Instead of using dayofyear, we manually calculate the number of days in a year from the time components.
// Extract year, month, day, hour
year_now = year(time)
month_now = month(time)
day_now = dayofmonth(time)
hour_now = hour(time)
// Precomputed cumulative days per month (non-leap year)
days_before_month = array.from(0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334)
// Calculate day-of-year
day_of_year = array.get(days_before_month, month_now - 1) + day_now
Input parameter customization window
Lookback period years default is 10, max - the number of historical bars we have, should only be 5 years, 10 years, 15 years, 20 years, 30 years.
Future project bar default is 180 bars - 1 month. We can adjust arbitrarily 6*24*254 - day/month/year
smoothingLength Smooth the data (1 = no smoothing)
offsetBars Move the forecast line left/right to check the past
How to use
Combine seasonality with Supply Demand, Footprint volume profile to find long-term trends or potential reversal points
day_of_year := day_of_year + ((is_leap and month_now > 2) ? 1 : 0)
// Compute bin index
binIndex = (day_of_year * sessionsPerDay) + math.floor(hour_now / 4)
binIndex := binIndex % binsPerYear // Keep within array bounds
The above is the manual code to replace day of year
LEGEND IsoPulse Fusion Universal Volume Trend Buy Sell RadarLEGEND IsoPulse Fusion • Universal Volume Trend Buy Sell Radar
One line summary
LEGEND IsoPulse Fusion reads intent from price and volume together, learns which features matter most on your symbol, blends them into a single signed Fusion line in a stable unit range, and emits clear Buy Sell Close events with a structure gate and a liquidity safety gate so you act only when the tape is favorable.
What this script is and why it exists
Many traders keep separate windows for trend, volume, volatility, and regime filters. The result can feel fragmented. This script merges two complementary engines into one consistent view that is easy to read and simple to act on.
LEGEND Tensor estimates directional quality from five causally computed features that are normalized for stationarity. The features are Flow, Tail Pressure with Volume Mix, Path Curvature, Streak Persistence, and Entropy Order.
IsoPulse transforms raw volume into two decaying reservoirs for buy effort and sell effort using body location and wick geometry, then measures price travel per unit volume for efficiency, and detects volume bursts with a recency memory.
Both engines are mapped into the same unit range and fused by a regime aware mixer. When the tape is orderly the mixer leans toward trend features. When the tape is messy but a true push appears in volume efficiency with bursts the mixer allows IsoPulse to speak louder. The outcome is a single Fusion line that lives in a familiar range with calm behavior in quiet periods and expressive pushes when energy concentrates.
What makes it original and useful
Two reservoir volume split . The script assigns a portion of the bar volume to up effort and down effort using body location and wick geometry together. Effort decays through time using a forgetting factor so memory is present without becoming sticky.
Efficiency of move . Price travel per unit volume is often more informative than raw volume or raw range. The script normalizes both sides and centers the efficiency so it becomes signed fuel when multiplied by flow skew.
Burst detection with recency memory . Percent rank of volume highlights bursts. An exponential memory of how recently bursts clustered converts isolated blips into useful context.
Causal adaptive weighting . The LEGEND features do not receive static weights. The script learns, causally, which features have correlated with future returns on your symbol over a rolling window. Only positive contributions are allowed and weights are normalized for interpretability.
Regime aware fusion . Entropy based order and persistence create a mixer that blends IsoPulse with LEGEND. You see a single line rather than two competing panels, which reduces decision conflict.
How to read the screen in seconds
Fusion area . The pane fills above and below zero with a soft gradient. Deeper fill means stronger conviction. The white Fusion line sits on top for precise crossings.
Entry guides and exit guides . Two entry guides draw symmetrically at the active fused entry level. Two exit guides sit inside at a fraction of the entry. Think of them as an adaptive envelope.
Letters . B prints once when the script flips from flat to long. S prints once when the script flips from flat to short. C prints when a held position ends on the appropriate side. T prints when the structure gate first opens. A prints when the liquidity safety flag first appears.
Price bar paint . Bars tint green while long and red while short on the chart to mirror your virtual position.
HUD . A compact dashboard in the corner shows Fusion, IsoPulse, LEGEND, active entry and exit levels, regime status, current virtual position, and the vacuum z value with its avoid threshold.
What signals actually mean
Buy . A Buy prints when the Fusion line crosses above the active entry level while gates are open and the previous state was flat.
Sell . A Sell prints when the Fusion line crosses below the negative entry level while gates are open and the previous state was flat.
Close . A Close prints when Fusion cools back inside the exit envelope or when an opposite cross would occur or when a gate forces a stop, and the previous state was a hold.
Gates . The Trend gate requires sufficient entropy order or significant persistence. The Avoid gate uses a liquidity vacuum z score. Gates exist to protect you from weak tape and poor liquidity.
Inputs and practical tuning
Every input has a tooltip in the script. This section provides a concise reference that you can keep in mind while you work.
Setup
Core window . Controls statistics across features. Scalping often prefers the thirties or low fifties. Intraday often prefers the fifties to eighties. Swing often prefers the eighties to low hundreds. Smaller responds faster with more noise. Larger is calmer.
Smoothing . Short EMA on noisy features. A small value catches micro shifts. A larger value reduces whipsaw.
Fusion and thresholds
Weight lookback . Sample size for weight learning. Use at least five times the horizon. Larger is slower and more confident. Smaller is nimble and more reactive.
Weight horizon . How far ahead return is measured to assess feature value. Smaller favors quick reversion impulses. Larger favors continuation.
Adaptive thresholds . Entry and exit levels from rolling percentiles of the absolute LEGEND score. This self scales across assets and timeframes.
Entry percentile . Eighty selects the top quintile of pushes. Lower to seventy five for more signals. Raise for cleanliness.
Exit percentile . Mid fifties keeps trades honest without overstaying. Sixty holds longer with wider give back.
Order threshold . Minimum structure to trade. Zero point fifteen is a reasonable start. Lower to trade more. Raise to filter chop.
Avoid if Vac z . Liquidity safety level. One point two five is a good default on liquid markets. Thin markets may prefer a slightly higher setting to avoid permanent avoid mode.
IsoPulse
Iso forgetting per bar . Memory for the two reservoirs. Values near zero point nine eight to zero point nine nine five work across many symbols.
Wick weight in effort split . Balance between body location and wick geometry. Values near zero point three to zero point six capture useful behavior.
Efficiency window . Travel per volume window. Lower for snappy symbols. Higher for stability.
Burst percent rank window . Window for percent rank of volume. Around one hundred to three hundred covers most use cases.
Burst recency half life . How long burst clusters matter. Lower for quick fades. Higher for cluster memory.
IsoPulse gain . Pre compression gain before the atan mapping. Tune until the Fusion line lives inside a calm band most of the time with expressive spikes on true pushes.
Continuation and Reversal guides . Visual rails for IsoPulse that help you sense continuation or exhaustion zones. They do not force events.
Entry sensitivity and exit fraction
Entry sensitivity . Loose multiplies the fused entry level by a smaller factor which prints more trades. Strict multiplies by a larger factor which selects fewer and cleaner trades. Balanced is neutral.
Exit fraction . Exit level relative to the entry level in fused unit space. Values around one half to two thirds fit most symbols.
Visuals and UX
Columns and line . Use both to see context and precise crossings. If you present a very clean chart you can turn columns off and keep the line.
HUD . Keep it on while you learn the script. It teaches you how the gates and thresholds respond to your market.
Letters . B S C T A are informative and compact. For screenshots you can toggle them off.
Debug triggers . Show raw crosses even when gates block entries. This is useful when you tune the gates. Turn them off for normal use.
Quick start recipes
Scalping one to five minutes
Core window in the thirties to low fifties.
Horizon around five to eight.
Entry percentile around seventy five.
Exit fraction around zero point five five.
Order threshold around zero point one zero.
Avoid level around one point three zero.
Tune IsoPulse gain until normal Fusion sits inside a calm band and true squeezes push outside.
Intraday five to thirty minutes
Core window around fifty to eighty.
Horizon around ten to twelve.
Entry percentile around eighty.
Exit fraction around zero point five five to zero point six zero.
Order threshold around zero point one five.
Avoid level around one point two five.
Swing one hour to daily
Core window around eighty to one hundred twenty.
Horizon around twelve to twenty.
Entry percentile around eighty to eighty five.
Exit fraction around zero point six zero to zero point seven zero.
Order threshold around zero point two zero.
Avoid level around one point two zero.
How to connect signals to your risk plan
This is an indicator. You remain in control of orders and risk.
Stops . A simple choice is an ATR multiple measured on your chart timeframe. Intraday often prefers one point two five to one point five ATR. Swing often prefers one point five to two ATR. Adjust to symbol behavior and personal risk tolerance.
Exits . The script already prints a Close when Fusion cools inside the exit envelope. If you prefer targets you can mirror the entry envelope distance and convert that to points or percent in your own plan.
Position size . Fixed fractional or fixed risk per trade remains a sound baseline. One percent or less per trade is a common starting point for testing.
Sessions and news . Even with self scaling, some traders prefer to skip the first minutes after an open or scheduled news. Gate with your own session logic if needed.
Limitations and honest notes
No look ahead . The script is causal. The adaptive learner uses a shifted correlation, crosses are evaluated without peeking into the future, and no lookahead security calls are used. If you enable intrabar calculations a letter may appear then disappear before the close if the condition fails. This is normal for any cross based logic in real time.
No performance promises . Markets change. This is a decision aid, not a prediction machine. It will not win every sequence and it cannot guarantee statistical outcomes.
No dependence on other indicators . The chart should remain clean. You can add personal tools in private use but publications should keep the example chart readable.
Standard candles only for public signals . Non standard chart types can change event timing and produce unrealistic sequences. Use regular candles for demonstrations and publications.
Internal logic walkthrough
LEGEND feature block
Flow . Current return normalized by ATR then smoothed by a short EMA. This gives directional intent scaled to recent volatility.
Tail pressure with volume mix . The relative sizes of upper and lower wicks inside the high to low range produce a tail asymmetry. A volume based mix can emphasize wick information when volume is meaningful.
Path curvature . Second difference of close normalized by ATR and smoothed. This captures changes in impulse shape that can precede pushes or fades.
Streak persistence . Up and down close streaks are counted and netted. The result is normalized for the window length to keep behavior stable across symbols.
Entropy order . Shannon entropy of the probability of an up close. Lower entropy means more order. The value is oriented by Flow to preserve sign.
Causal weights . Each feature becomes a z score. A shifted correlation against future returns over the horizon produces a positive weight per feature. Weights are normalized so they sum to one for clarity. The result is angle mapped into a compact unit.
IsoPulse block
Effort split . The script estimates up effort and down effort per bar using both body location and wick geometry. Effort is integrated through time into two reservoirs using a forgetting factor.
Skew . The reservoir difference over the sum yields a stable skew in a known range. A short EMA smooths it.
Efficiency . Move size divided by average volume produces travel per unit volume. Normalization and centering around zero produce a symmetric measure.
Bursts and recency . Percent rank of volume highlights bursts. An exponential function of bars since last burst adds the notion of cluster memory.
IsoPulse unit . Skew multiplied by centered efficiency then scaled by the burst factor produces the raw IsoPulse that is angle mapped into the unit range.
Fusion and events
Regime factor . Entropy order and streak persistence form a mixer. Low structure favors IsoPulse. Higher structure favors LEGEND. The blend is convex so it remains interpretable.
Blended guides . Entry and exit guides are blended in the same way as the line so they stay consistent when regimes change. The envelope does not jump unexpectedly.
Virtual position . The script maintains state. Buy and Sell require a cross while flat and gates open. Close requires an exit or force condition while holding. Letters print once at the state change.
Disclosures
This script and description are educational. They do not constitute investment advice. Markets involve risk. You are responsible for your own decisions and for compliance with local rules. The logic is causal and does not look ahead. Signals on non standard chart types can be misleading and are not recommended for publication. When you test a strategy wrapper, use realistic commission and slippage, moderate risk per trade, and enough trades to form a meaningful sample, then document those assumptions if you share results.
Closing thoughts
Clarity builds confidence. The Fusion line gives a single view of intent. The letters communicate action without clutter. The HUD confirms context at a glance. The gates protect you from weak tape and poor liquidity. Tune it to your instrument, observe it across regimes, and use it as a consistent lens rather than a prediction oracle. The goal is not to trade every wiggle. The goal is to pick your spots with a calm process and to stand aside when the tape is not inviting.
FVG Buy/Sell [Multi-TF] by akshaykiriti1443The FVG Buy/Sell indicator is a precision trading tool designed for traders who operate with a clear directional bias. It excels at identifying high-probability entry points by detecting when price interacts with Fair Value Gaps (FVGs).
This indicator is built on a core principle: instead of predicting the market's direction, it provides the timing for an entry after you, the trader, have established your market bias. By automatically pinpointing bullish and bearish imbalances on both the current and a higher timeframe, it allows you to wait for the market to pull back to a key level and then provides a clear signal for execution.
The Core Strategy: Bias First, Entry Second
This indicator is most powerful when used as part of a two-step trading process. It is not a standalone signal generator; it is an entry confirmation tool.
Step 1: Determine Your Directional Bias
Before looking for any signals from this indicator, you must first have an opinion on the market's most likely direction. This bias should be derived from your primary analysis method, such as:
The Golden Rule:
If your bias is BULLISH, you will ONLY look for BUY signals generated by bullish (green/blue) FVGs. You will ignore all SELL signals.
If your bias is BEARISH, you will ONLY look for SELL signals generated by bearish (pink/orange) FVGs. You will ignore all BUY signals.
Step 2: Execute with the FVG Tap-In Signal
Once your bias is set, the indicator does the rest of the work. You simply wait for the price to pull back into an FVG zone that aligns with your bias and then wait for the confirmation arrow to appear.
A green up arrow confirms that price has tapped a bullish FVG and closed above it, signaling that support has held and it's a valid moment to enter a long position.
A red down arrow confirms that price has tapped a bearish FVG and closed below it, signaling that resistance has held and it's a valid moment to enter a short position.
How to Take a Trade (Step-by-Step Examples)
Example of a Bullish (Long) Trade Setup:
Establish Bias: Your primary analysis shows the market is in a clear uptrend. Your bias is Bullish. You are now only looking for buying opportunities.
Identify Zone: The indicator draws a bullish FVG (a green or blue box) during an impulsive up-move.
Wait for Pullback: Be patient and let the price retrace down into this FVG zone. Do not chase the price.
Confirmation Signal: A green UP arrow appears below a candle. This is your signal. It confirms that buyers have stepped in at the FVG level and defended it.
Entry: Enter a long (buy) position at the open of the candle immediately following the signal candle.
Stop Loss: Place your stop loss below the low of the signal candle or, for a safer stop, below the bottom of the FVG zone itself.
Take Profit: Target a previous high, a higher-timeframe resistance level, or use a risk-to-reward ratio like 1:2 or 1:3.
Example of a Bearish (Short) Trade Setup:
Establish Bias: Your primary analysis shows the market is breaking down into a downtrend. Your bias is Bearish. You are now only looking for selling opportunities.
Identify Zone: The indicator draws a bearish FVG (a pink or orange box) during an impulsive down-move.
Wait for Pullback: Patiently wait for the price to rally back up into this FVG zone.
Confirmation Signal: A red DOWN arrow appears above a candle. This is your confirmation that sellers have rejected the price at this level.
Entry: Enter a short (sell) position at the open of the next candle.
Stop Loss: Place your stop loss above the high of the signal candle or above the top of the FVG zone.
Take Profit: Target a previous low, a key support level, or the next major FVG below.
Features Explained in Detail
Multi-Timeframe (MTF) Analysis: HTF zones (dotted lines) carry more weight. A signal from a 4-hour FVG while you are on a 15-minute chart is significantly more powerful than a signal from a 15-minute FVG alone. Use HTF zones as major points of interest.
Confirmed Tap-In Logic: The arrow only appears after price has touched the zone and then closed outside of it in the expected direction. This built-in confirmation filters out wicks that simply pass through a zone without a real market reaction.
Dual Alert System:
Entry Alert ("Price has entered..."): This is a heads-up alert. It tells you to pay attention because price is now in your pre-defined zone of interest.
Tap-In Alert ("Confirmed tap-in..."): This is the execution alert. It signals that the conditions for a trade have been met according to the indicator's logic.
Fade on Tapped: When enabled, a zone will become transparent after a confirmed signal. This visually cleans up your chart, showing you which zones have already been tested and "mitigated."
Minimum FVG Size (Ticks): In volatile or ranging markets, many tiny, insignificant FVGs can form. Use this setting to filter out the noise. Increase the value to only display larger, more significant imbalances.
Disclaimer: Trading involves substantial risk. This indicator is a tool for analysis and should not be used as a sole reason to enter a trade. Always practice robust risk management and use this tool in conjunction with your own trading plan. Past performance is not indicative of future results.
Market Tension Map v2📊 Market Tension Map v2 — Detailed Description
core concept
market tension map v2 measures market "tension" through a combination of three independent metrics: volatility, volume, and open interest changes. the indicator operates on the compressed spring principle—when the market enters a state of low volatility with high volume and growing OI, it creates "tension" that predicts a potential sharp price movement.
calculation methodology
component 1: volatility score (0-100)
relative volatility is measured through price standard deviation over a specified period. key distinction—inversion: low volatility produces a high score because range compression creates energy for future movement.
component 2: volume score (0-100)
normalization of current volume relative to the period range. high volume during low volatility signals accumulation of positions by large players before a move.
component 3: open interest score (0-100)
evaluation of open interest changes (available only for futures). rising OI confirms new positions entering the market rather than just redistribution of existing ones.
final tension index
arithmetic mean of three components (or two if OI unavailable). values above threshold (default 70) signal spring "compression".
signal types
compression signal (🔴 red diamond)
appears when tension index exceeds threshold with normal candle size. this is a predictive signal—market is compressed but explosion hasn't occurred yet. optimal for entry before movement with tight stop.
climax signal (⚠️ orange diamond)
occurs when threshold crossed + large candle (size > ATR × multiplier). this is a reactive signal of culmination—energy already released. often indicates short-term reversal or move exhaustion.
uniqueness of approach
unlike classic compression indicators (bollinger bands squeeze, keltner channels), mtm v2 doesn't rely solely on volatility. adding volume and OI scores creates a multidimensional picture of market microstructure. volatility score inversion is original logic where calm is interpreted as tension.
the algorithm distinguishes two breakout types:
compression without movement (compression)—anticipation trading
compression with large candle (climax)—reversal trading
this separation is absent in standard indicators.
parameter settings
calculation period (20)—normalization window length. lower = more sensitive to short-term changes.
tension threshold (70)—signal activation level. higher = fewer signals but better quality.
atr length (14) + atr multiplier (2.0)—large candle detection parameters for climax signals. increasing multiplier makes filter stricter.
colors and style—full customization of visual elements to adapt to your chart theme.
how to use
main chart: histogram shows current tension level. yellow = rising, gray = falling.
signals on price chart:
red diamond above candle = prepare for entry (compression)
orange diamond = move occurred, watch for reversal (climax)
background highlight: tinted background shows high tension zones.
data table: real-time monitoring of all components + bar status (live/closed).
alerts: configure notifications for compression or climax signals for automatic monitoring.
limitations
open interest available only for futures. for spot markets indicator works with two components.
requires sufficient bar history (>= calculation period) for correct calculations.
on live bar (not closed) values may repaint—use confirmed signals for trading.
recommended timeframes
1h-4h: optimal for swing trading, signals more reliable.
15m-30m: suitable for intraday but requires false breakout filtering.
d: strategic positions, high risk/reward ratio.
license: mozilla public license 2.0
version: pinescript v6
