Swing-Based Volatility IndexSwing-Based Volatility Index
This indicator helps traders quickly determine whether the market has moved enough over the past few hours to justify scalping.
It measures the percentage price swing (high to low) over a configurable time window (e.g., last 4–8 hours) and compares it to a minimum threshold (e.g., 1%).
✅ If the percent move exceeds the threshold → Market is volatile enough to scalp (green background).
🚫 If it's below the threshold → Market is too quiet (red background).
Features:
Adjustable lookback period in hours
Custom threshold for volatility sensitivity
Automatically adapts to the current chart timeframe
This tool is ideal for scalpers and short-term traders who want to avoid entering trades in low-volatility environments.
Indicators and strategies
Multi-EnvelopeRMA Multi-Envelope Indicator
The RMA Multi-Envelope Indicator is a technical analysis tool designed for TradingView, utilizing Pine Script v6. It creates eight customizable envelope bands around a 200-period Running Moving Average (RMA) on a 5-minute timeframe, based on current market measurements. Each band has independent upper and lower percentage deviations, preset to: Band 1 (0.42%, 0.46%), Band 2 (0.78%, 0.69%), Band 3 (1.01%, 1.03%), Band 4 (1.36%, 1.39%), Band 5 (1.80%, 1.62%), Band 6 (2.15%, 2.13%), Band 7 (2.93%, 2.81%), and Band 8 (4.65%, 4.18%). Users can adjust the timeframe, moving average type (RMA, SMA, or EMA), length, and colors for the basis line and bands via hex codes (e.g., #FF6D00 for the basis and Band 8) with semi-transparent color.rgb fills. Ideal for identifying support/resistance, overbought/oversold conditions, or trend boundaries on a 5-minute chart.
Quarter ICT Theo TradeQuarter ICT | Theo Trade
The "Multi-Level Yearly Divisions" indicator is a visual tool designed for TradingView charts. Its primary purpose is to help traders and analysts visualize and analyze price action within a structured, hierarchical breakdown of the year. It divides each year into progressively smaller, equal time segments, allowing for detailed observation of how markets behave during specific portions of the year, quarters, and even finer sub-divisions.
Yearly Detection: It first identifies the start of each new year on the chart.
Four Levels of Division:
Level 0: Marks the beginning of the year with a distinct line.
Level 1 (Quarters): Divides the entire year into four equal parts (quarters).
Level 2: Each quarter is then further divided into four equal smaller segments.
Level 3: Each of these Level 2 segments is again divided into four equal parts.
Level 4: Finally, each Level 3 segment is divided into four more equal parts.
multi-tf standard devs [keypoems]Multi-Timeframe Standard Deviations Levels
A visual map of “how far is too far” across any three higher time-frames.
1. What it does
This script plots dynamic price “rails” built from standard deviation (StDev)—the same math that underpins the bell curve—on up to three higher-time-frames (HTFs) at once.
• It measures the volatility of intraday open-to-close increments, reaching back as far as 5000 bars (≈ 20 years on daily data).
• Each HTF can be extended to the next session or truncated at session close for tidy dashboards.
• Lines can be mirrored so you see symmetric positive/negative bands, and optional background fills shade the “probability cone.”
Because ≈ 68 % of moves live inside ±1 StDev, ≈ 95 % inside ±2, and ≈ 99.7 % inside ±3, the plot instantly shows when price is statistically stretched or compressed.
3. Key settings
Higher Time-Frame #1-3 Turn each HTF on/off, pick the interval (anything from 1 min to 1 year), and decide whether lines should extend into the next period.
Show levels for last X days Keep your chart clean by limiting how many historical sessions are displayed (1-50).
Based on last X periods Length of the StDev sample. Long look-backs (e.g. 5 000) iron-out day-to-day noise; short look-backs make the bands flex with recent volatility.
Fib Settings Toggle each multiple, line thickness/style/colour, label size, whether to print the numeric level, the live price, the HTF label, and whether to tint the background (choose your own opacity).
4. Under-the-hood notes
StDev is calculated on (close – open) / open rather than absolute prices, making the band width scale-agnostic.
Watch for tests of ±1:
Momentum traders ride the breakout with a target at the next band.
Mean-reversion traders wait for the first stall candle and trade back to zero line or VWAP.
Bottom line: Multi-Timeframe Standard-Deviations turns raw volatility math into an intuitive “price terrain map,” helping you instantly judge whether a move is ordinary, stretched, or extreme—across the time-frames that matter to you.
Original code by fadizeidan and stats by NQStats's ProbableChris.
Swing High/Low by %REnglish Description
Swing High/Low by %R
This indicator identifies potential swing high and swing low points by combining William %R overbought/oversold turning points with classic swing price structures.
Swing High: Detected when William %R turns down from overbought territory and the price forms a local high (higher than both neighboring bars).
Swing Low: Detected when William %R turns up from oversold territory and the price forms a local low (lower than both neighboring bars).
This tool is designed to help traders spot possible market reversals and better time their entries and exits.
Customizable parameters:
Williams %R period
Overbought & Oversold thresholds
The indicator plots clear signals above/below price bars for easy visualization.
For educational purposes. Please use with proper risk management!
คำอธิบายภาษาไทย
Swing High/Low by %R
อินดิเคเตอร์นี้ใช้ระบุจุด Swing High และ Swing Low ที่มีโอกาสเป็นจุดกลับตัวของตลาด โดยอาศัยสัญญาณจาก William %R ที่พลิกกลับตัวบริเวณ overbought/oversold ร่วมกับโครงสร้างราคาแบบ swing
Swing High: เกิดเมื่อ William %R พลิกกลับลงจากเขต Overbought และราคาแท่งกลางสูงกว่าทั้งสองแท่งข้างเคียง
Swing Low: เกิดเมื่อ William %R พลิกกลับขึ้นจากเขต Oversold และราคาแท่งกลางต่ำกว่าทั้งสองแท่งข้างเคียง
ช่วยให้เทรดเดอร์สามารถมองเห็นโอกาสในการกลับตัวของราคา และใช้ประกอบการวางแผนจังหวะเข้าหรือออกจากตลาดได้อย่างแม่นยำมากขึ้น
ตั้งค่าได้:
ระยะเวลา Williams %R
ค่าขอบเขต Overbought & Oversold
อินดิเคเตอร์จะแสดงสัญลักษณ์อย่างชัดเจนบนกราฟเพื่อความสะดวกในการใช้งาน
ควรใช้ร่วมกับการบริหารความเสี่ยง
5:30 AM IST Close + Offset Lines + TablesDescription:
This script captures the 5:30 AM IST close price and plots it on the chart along with dynamic offset levels above and below (±5, ±20, ±40, ±60, ±80 points). It also displays these levels in neatly organized tables at the top-right and bottom-right corners for quick reference.
🔹 Timezone: Asia/Kolkata (IST)
🔹 Useful for: Intraday traders who reference early morning levels
🔹 Visual aids:
Orange line for 5:30 AM close
Green lines for points above
Red lines for points below
Tables summarizing all levels
This tool helps identify key early-morning reference zones that can act as support/resistance or breakout targets.
Multi-Timeframe Session HighlighterWhat is the Multi-Timeframe Session Highlighter?
It’s a simple Pine Script indicator that paints two special candles on your chart, no matter what timeframe you’re looking at. Think of it as a highlighter pen for session starts and ends—can be used for session-based strategies or just keeping an eye on key turning points.
How it works:
Green Bar (Session Open): Marks the exact bar when your chosen higher-timeframe session kicks off. If you select “4H,” on the indicator, you’ll see green on every 4-hour open, even if you’re staring at a 15-minute chart.
Red Bar (Session Close): Highlights the very last lower-timeframe candle immediately before that session wraps up. So on a 1H chart with “Daily” selected, you’ll get a red band on the 23:00 hour before the new daily bar at midnight.
Customizable: Pick your own colors and transparency level to match your chart theme.
Getting started:
Add the indicator to your chart.
In the inputs, select the session timeframe (for example, “240” for 4H or “D” for daily).
Choose your favorite green and red shades.
That’s it.
Realtime ATR-Based Stop Loss Numerical OverlayRealtime ATR-Based Stop Loss Numerical Overlay
A simple, effective tool for dynamic risk management based on ATR (Average True Range) without adding cluttered and distracting lines all over your chart.
📌 Description
This script plots a real-time stop loss level using the Average True Range (ATR) on your chart, helping you set consistent, volatility-based stops. It supports both:
✅ Current chart timeframe
✅ Custom fixed timeframe inputs (1m, 5m, 15m, 1h, etc.)
The stop level is calculated as:
Stop = ATR × Multiplier
and updates in real-time. An overlay table displays on the bottom-right of your chart with the calculated stop value in a clean, simple way.
⚙️ Settings
ATR Timeframe Source:
Choose between using the current chart's timeframe or a fixed one (e.g. 5, 15, 60, D, etc).
ATR Length:
Period used to calculate the ATR (default is 14).
Stop Loss Multiplier:
Multiplies the ATR value to define your stop (e.g., 1.5 × ATR).
Wait for Timeframe Closes:
If enabled, the ATR value waits for the selected timeframe’s candle to close before updating. If unselected, it will update in real time.
🛠️ How to Use
Add this script to your chart from your indicators list.
Configure your desired timeframe, ATR length, and multiplier in the settings panel.
Use the value shown in the table overlay as your suggested stop loss distance from entry.
Adjust your position sizing accordingly to fit your risk tolerance.
This tool is especially useful for traders looking for adaptive risk management that evolves with market volatility — whether scalping intraday or swing trading.
💡 Pro Tip
The ATR stop can also be used to dynamically trail your stop behind price movement.
Adaptive Momentum Flow (AMF)Overview
The Adaptive Momentum Flow (AMF) indicator is a powerful, multi-faceted tool designed to provide a comprehensive and adaptive view of market momentum and trend strength. Unlike traditional oscillators with fixed settings, AMF dynamically adjusts its calculations based on market volatility , ensuring its signals remain relevant across varying market conditions. By combining advanced Double Exponential Moving Averages (DEMA) with a powerful volume analysis component and a customizable scoring system, AMF offers a unique perspective on price action and underlying buying/selling pressure.
Key Features & How It Works
1. Adaptive DEMA Trend Strength:
At its core, AMF utilizes three DEMA lines (Fast, Medium, Slow) to assess the current trend's alignment and strength.
The indicator dynamically adjusts the lengths of these DEMA lines based on real-time market volatility, measured by Average True Range (ATR). This means AMF becomes more responsive in volatile markets and smoother in calmer periods.
A "Volatility Sensitivity" input allows you to fine-tune how aggressively the indicator adapts to these changes.
2. Volume Analysis (Buying/Selling Pressure):
AMF incorporates a dedicated volume analysis module to gauge whether volume is predominantly supporting upward or downward price movements. This helps identify periods of significant buying or selling pressure.
This volume analysis component is smoothed with an adjustable Moving Average (SMA, EMA, WMA, or DEMA) and contributes to the overall momentum score, adding a crucial layer of volume-driven confirmation to the analysis.
3. Comprehensive Scoring System:
The indicator generates a normalized "Oscillator Score" that ranges from -100 to 100. This score is a weighted sum of:
Price's relationship to the Fast DEMA.
The Fast DEMA's relationship to the Medium DEMA.
The Medium DEMA's relationship to the Slow DEMA.
The smoothed value from the volume analysis.
Each component's influence on the final score can be individually adjusted via input weights, allowing for deep customization.
Signal Line & Crossovers:
A smoothed "Signal Line" provides additional confirmation for momentum shifts. Crossovers between the main AMF line and its Signal Line can indicate potential changes in market direction.
Overbought/Oversold Levels:
Adjustable Overbought (default 70) and Oversold (default -70) levels visually highlight extreme momentum conditions.
These zones are enhanced with a color fill effect (bright red for overbought, bright cyan for oversold), making it easy to spot when the market is entering potentially exhausted states.
Crucially, these extreme zones can often be further validated by combining them with volatility bands (like Bollinger Bands or Keltner Channels as shown in the chart above) or other confluence indicators, offering stronger signals for potential reversals or exhaustion.
Benefits for Traders
Reduced Lag: DEMA's inherent design helps minimize lag compared to traditional moving averages, providing more timely signals.
Adaptive Intelligence: Automatically adjusts to market volatility, ensuring the indicator's sensitivity is appropriate for current conditions.
Holistic Momentum View: Combines price-based trend alignment with volume-based pressure for a more robust assessment of market flow.
Clear Visual Cues: Intuitive plots, signal line, and vibrant overbought/oversold zone fills make interpretation straightforward.
Customizable: Extensive input options allow traders to tailor the indicator to their specific trading style, asset, and timeframe.
How to Use
Trend Confirmation: Look for the AMF line and its Signal Line to align with the price trend.
Momentum Shifts: Crossovers between the AMF line and its Signal Line can indicate shifts in momentum.
Extreme Conditions: Pay attention when the AMF line enters the neon-highlighted overbought or oversold zones, signaling potential reversals or pauses in the current momentum. Always consider confirming these signals with other analysis tools, such as price action, chart patterns, support/resistance levels, or volatility indicators.
Customization: Experiment with the "Volatility Sensitivity," DEMA multipliers, and scoring weights to find the optimal settings for your trading strategy.
Median True Range {Darkoexe}Simple and sweet, this is the median true range. It reviews the size of the previous period amount of candles, and displays the candle size value that is the median of those previous values.
//Darkoexe
CME Futures RTH net change % levelsRTH Session time calculated for AMERICAN FUTURES ONLY.
Plots the net change % from the last session's RTH close, a.k.a daily % change for that specific instrument. Best used as support and resistance zones in confluence with other analysis, and also serve as a gauge for how volatile the session is.
Beta Tracker [theUltimator5]This script calculates the Pearson correlation coefficient between the charted symbol and a dynamic composite of up to four other user-defined tickers. The goal is to track how closely the current asset’s normalized price behavior aligns with, or diverges from, the selected group (or basket)
How can this indicator be valuable?
You can compare the correlation of your current symbol against a basket of other tickers to see if it is moving independently, or being pulled with the basket.... or is it moving against the basket.
It can be used to help identify 'swap' baskets of stocks or other tickers that tend to generally move together and visually show when your current ticker diverges from the basket.
It can be used to track beta (or negative beta) with the market or with a specific ticker.
This is best used as a supplement to other trading signals to give a more complete picture of the external forces potentially pulling or pushing the price action of the ticker.
🛠️ How It Works
The current symbol and each selected comparison ticker are normalized over a custom lookback window, allowing fair pattern-based comparison regardless of price scale.
The normalized values from 1 to 4 selected tickers are averaged into a composite, which represents the group’s collective movement.
A Pearson correlation coefficient is computed over a separate correlation lookback period, measuring the relationship between the current asset and the composite.
The result is plotted as a dynamic line, with color gradients:
Blue = strongly correlated (near +1)
Orange = strongly inverse correlation (near –1)
Intermediate values fade proportionally
A highlighted background appears when the correlation drops below a user-defined threshold (e.g. –0.7), helping identify strong negative beta periods visually.
A toggleable info table displays which tickers are currently being compared, along with customizable screen positioning.
⚙️ User Inputs
Ticker 1–4: Symbols to compare the current asset against (blank = ignored)
Normalization Lookback: Period to normalize each series
Correlation Lookback: Period over which correlation is calculated
Negative Correlation Highlight: Toggle for background alert and threshold level
Comparison Table: Toggle and position controls for an on-screen summary of selected tickers
imgur.com
⚠️ Notes
The script uses request.security() to pull data from external symbols; these must be available for the selected chart timeframe.
A minimum of one valid ticker must be provided for the script to calculate a composite and render correlation.
Bullish Volume AnomalyAnomaly is designed to spot hidden bullish accumulation before price actually breaks out, by blending a trend-aware volume measure with a volatility-adjusted price channel. Here’s how it works:
First, it runs a simple ATR-based zigzag to identify the current swing direction. Volume is then signed (+ for up-trends, – for down-trends) and cumulatively summed. By converting that cumulative signed volume into a z-score over the past 480 bars, we get a sense of when buying or selling pressure is unusually strong relative to its own history.
At the same time, price itself is normalized into a z-score over the same 480-bar window, and its change over that period is also tracked. These two measures—volume z-score (s) and price z-score (p)—are compared, and the indicator looks for moments when s outpaces p by at least two standard deviations (s – p > 2), while price momentum change remains low (c < 1) and the net volume is positive (s > 0). That combination flags instances where heavy buying is taking place but price hasn’t yet reacted.
To define a dynamic trading zone, it plots a 288-bar EMA of price as the middle band (t2), and builds upper and lower bands around it using the average close-to-open range multiplied by a user-set factor. The lower band (t1) sits beneath the EMA by that volatility-based margin. A signal fires only when the bar’s high stays below t1—meaning price is still “sleeping” under the lower volatility boundary even as bullish volume builds up.
Together, these filters home in on anomalies: strong, trend-aligned volume surges that outstrip price movement, occurring while price sits below its lower volatility band. In practice, that often marks early accumulation before a breakout. You can tweak the ATR length and multiplier for the zigzag, as well as the channel period and range factor, to suit different markets or timeframes.
Footprint BoxesThe Footprint Boxes indicator takes each higher-timeframe candle and builds a mini “footprint” map of where buying and selling happened within that bar’s range. You choose how many price bins to split the candle into and which lower timeframe to sample. For each small interval it grabs the signed volume (positive when the close is above the open, negative when below) and distributes that volume evenly across every bin touched by the price move in that interval.
Once the bar closes , the script finds the true high and low of all the lower-timeframe candles that make up the parent bar, divides that span into your chosen number of bins, and sums up the signed volume in each bin. It then draws a row of colored boxes beside the bar: green-tinted boxes for net buying and red-tinted ones for net selling, with shade intensity proportional to the percentage of total volume in that bin . Each box is labeled with its percentage of the bar’s total volume delta.
Finally, it draws one extra box with a bold white border showing the bar’s overall delta (net buying minus selling) as an absolute number. This gives you both a granular view of intra-bar activity and a quick glance at whether the buyers or sellers dominated the entire candle.
MA OrderlinessMA Orderliness measures how well a series of simple moving averages (SMAs) are stacked in the expected order for a trending market and turns that measurement into a normalized oscillator. You choose how many MAs to include and the shortest and longest lengths. The script generates a family of evenly spaced SMAs between those lengths, then compares each pair: shorter MAs should lie above longer ones in an uptrend and below in a downtrend. When any pair is out of order, a “violation” score is accumulated, but violations between nearby MAs count more heavily than those between MAs that are far apart. All weights are summed, and the total weighted violations are converted into a score from –1 (completely reversed) to +1 (perfectly ordered).
This orderliness score is plotted as a line oscillator. A fixed horizontal line at +1 marks perfect order, and another at –1 marks perfect reversal. To smooth the raw oscillator and generate trading signals, the script also plots a simple moving average of the orderliness score over a user-defined period. When the unsmoothed score crosses above its moving average, a bullish crossover alert fires. When it crosses below, a bearish crossover alert fires.
Everything is calculated on each bar so you can see the oscillator evolve in real time. You can customize the number of MAs, their minimum and maximum lengths, and the length of the signal-line SMA to suit different timeframes or markets.
Normalized DXY+Custom USD Index (DXY+) – Normalized Dollar Strength with Bitcoin, Gold, and Yuan.
This custom USD strength index replicates the structure of the official U.S. Dollar Index (DXY), while expanding it to include modern financial assets such as Bitcoin (BTC), Ethereum (ETH), gold (XAU), and the Chinese yuan (CNY).
Weights for the core fiat currencies (EUR, JPY, GBP, CAD, SEK, CHF) follow the official ICE DXY methodology. Additional components are weighted proportionally based on their estimated global economic influence.
The index is normalized from its initial valid data point, meaning it starts at 100 on the first day all asset inputs are available. From that point forward, it tracks the relative strength of the U.S. dollar against this expanded basket.
This provides a more comprehensive and modernized view of the dollar's strength—not only against traditional fiat currencies, but also in the context of rising decentralized assets and non-Western trade power.
