All Forex Sessions (SAST Accurate) + LabelsFor traders in South Africa
Uses timestamp("Africa/Johannesburg", ...) — this locks the session window to true SAST time
The session now perfectly aligns from 14:00 to 18:00 local time no matter what time zone your TradingView chart is in
Also shows start and end vertical lines only when the session opens and closes
Bands and Channels
Fib BB on VWMA*ATRThis TradingView Pine Script is designed to plot Fibonacci Bollinger Bands on a Volume Weighted Moving Average (VWMA) using the Average True Range (ATR). The script takes a higher timeframe (HTF) approach, allowing traders to analyze price action and volatility from a broader market perspective.
🔹 How It Works
Higher Timeframe Data Integration
Users can select a specific timeframe to calculate the VWMA and ATR.
This allows for a more macro perspective, avoiding the noise of lower timeframes.
Volume Weighted Moving Average (VWMA)
Unlike the Simple Moving Average (SMA), VWMA gives higher weight to price movements with larger volume.
Calculation Formula:
𝑉𝑊𝑀𝐴=∑(𝐶𝑙𝑜𝑠𝑒×𝑉𝑜𝑙𝑢𝑚𝑒) / ∑𝑉𝑜𝑙𝑢𝑚𝑒
Since VWMA accounts for volume, it is more reactive to price zones with high buying or selling activity, making it useful for identifying liquidity zones.
ATR-Based Fibonacci Bollinger Bands
The Average True Range (ATR) is used to measure market volatility.
Instead of standard deviation-based Bollinger Bands, Fibonacci multipliers (2.618, 3.0, 3.414) are applied to ATR.
These bands adjust dynamically with market volatility.
🔹 Key Findings from Exploration
Through testing and analysis, this indicator seems to effectively detect supply and demand zones, particularly at the Fibonacci levels of 2.618 to 3.414.
Price frequently reacts at these bands, indicating that they capture key liquidity zones.
Potential Order Block Detection:
The ends of the Fibonacci Bollinger Bands (especially at 2.618, 3.0, and 3.414) tend to align with order blocks—areas where institutional traders previously accumulated or distributed positions.
This is particularly useful for order flow traders who focus on unfilled institutional orders.
🔹 How to Use This Indicator?
Identifying Order Blocks
When price reaches the upper or lower bands, check if there was a strong reaction (rejection or consolidation).
If price rapidly moves away from a band, that level might be an order block.
Spotting Liquidity Pools
VWMA’s nature enhances liquidity detection since it emphasizes high-volume price action.
If a price level repeatedly touches the band without breaking through, it suggests institutional orders may be absorbing liquidity there.
Trend Confirmation
If VWMA is trending upwards and price keeps rejecting the lower bands, it confirms a strong bullish trend.
Conversely, constant rejection from the upper bands suggests a bearish market.
This script is designed for open-source publication and offers traders a refined approach to detecting order blocks and liquidity zones using Fibonacci-based volatility bands.
📌 한글 설명 (상세 설명)
이 트레이딩뷰 파인스크립트는 거래량 가중 이동평균(VWMA)과 평균 실제 범위(ATR)를 활용하여 피보나치 볼린저 밴드를 표시하는 지표입니다.
또한, 고차 타임프레임(HTF) 데이터를 활용하여 시장의 큰 흐름을 분석할 수 있도록 설계되었습니다.
🔹 지표 작동 방식
고차 타임프레임(HTF) 데이터 적용
사용자가 원하는 타임프레임을 선택하여 VWMA와 ATR을 계산할 수 있습니다.
이를 통해 더 큰 시장 흐름을 분석할 수 있으며, 저타임프레임의 노이즈를 줄일 수 있습니다.
거래량 가중 이동평균(VWMA) 적용
VWMA는 단순 이동평균(SMA)보다 거래량이 많은 가격 움직임에 더 큰 가중치를 부여합니다.
계산 공식:
𝑉𝑊𝑀𝐴=∑(𝐶𝑙𝑜𝑠𝑒×𝑉𝑜𝑙𝑢𝑚𝑒) / ∑𝑉𝑜𝑙𝑢𝑚𝑒
거래량이 많이 발생한 가격 구간을 강조하는 특성이 있어, 시장의 유동성 구간을 더 정확히 포착할 수 있습니다.
ATR 기반 피보나치 볼린저 밴드 생성
ATR(Average True Range)를 활용하여 변동성을 측정합니다.
기존의 표준편차 기반 볼린저 밴드 대신, 피보나치 계수(2.618, 3.0, 3.414)를 ATR에 곱하여 밴드를 생성합니다.
이 밴드는 시장 변동성에 따라 유동적으로 조정됩니다.
🔹 탐구 결과: 매물대 및 오더블록 감지
테스트를 통해 Fibonacci 2.618 ~ 3.414 구간에서 매물대 및 오더블록을 포착하는 경향이 있음을 확인했습니다.
가격이 피보나치 밴드(특히 2.618, 3.0, 3.414)에 닿을 때 반응하는 경우가 많음
VWMA의 특성을 통해 오더블록을 감지할 가능성이 높음
🔹 오더블록(Order Block) 감지 원리
Fibonacci 밴드 끄트머리(2.618 ~ 3.414)에서 가격이 강하게 반응
이 영역에서 가격이 강하게 튀어 오르거나(매수 압력) 급락하는(매도 압력) 경우,
→ 기관들이 포지션을 청산하거나 추가 매집하는 구간일 가능성이 큼.
과거에 대량 주문이 체결된 가격 구간(= 오더블록)일 수 있음.
VWMA를 통한 유동성 감지
VWMA는 거래량이 집중된 가격을 기준으로 이동하기 때문에, 기관 주문이 많이 들어온 가격대를 강조하는 특징이 있음.
따라서 VWMA와 피보나치 밴드가 만나는 지점은 유동성이 높은 핵심 구간이 될 가능성이 큼.
매물대 및 청산 구간 분석
가격이 밴드에 도달했을 때 강한 반등이 나오는지를 확인 → 오더블록 가능성
가격이 밴드를 여러 번 테스트하면서 돌파하지 못한다면, 해당 지점은 강한 매물대일 가능성
🔹 활용 방법
✅ 오더블록 감지:
가격이 밴드(2.618~3.414)에 닿고 강하게 튕긴다면, 오더블록 가능성
해당 지점에서 거래량 증가 및 강한 반등 발생 시 매수 고려
✅ 유동성 풀 확인:
VWMA와 피보나치 밴드가 만나는 구간에서 반복적으로 거래량이 터진다면, 해당 지점은 기관 유동성 구간일 가능성
✅ 추세 확인:
VWMA가 상승하고 가격이 밴드 하단(지지선)에서 튕긴다면 강한 상승 추세
VWMA가 하락하고 가격이 밴드 상단(저항선)에서 거부당하면 하락 추세 지속
[NLR] - SweetSpot ZonesThe Sweet Spot Zone helps you find the best spots to enter a trade, inspired by the " Follow Line Indicator " by Dreadblitz (big thanks to him!). It draws a colored zone on your chart to show ideal entry points, with a Base Point to keep you on track.
What It Does
Blue Zone: Uptrend—buy when the price dips into the zone.
Red Zone: Downtrend—sell or short when the price climbs into the zone.
Base Point: A gray line showing the key level the zone is built on.
How to Use It
Look for the colored zone:
- Blue: Buy if the price dips into the zone but stays above the Base Point.
- Red: Sell/short if the price climbs into the zone but stays below the Base Point.
Important: Avoid entering trade beyond base point - you might see low returns and face big drawdowns.
Confirm with other signals (like RSI/MACD) before entering.
Settings
ATR Length (10): How far back it looks to calculate price movement.
ATR Multiplier (2.5): How wide the zone is.
Error Margin (5.0): Keeps the zone steady during small price wiggles.
Uptrend/Downtrend Colors: Change the zone colors if you’d like!
Credits
Inspired by the "Follow Line Indicator" by Dreadblitz—check out his work for more great ideas!
Dynamic Volume Profile Oscillator | AlphaAlgosDynamic Volume Profile Oscillator | AlphaAlgos
Overview
The Dynamic Volume Profile Oscillator is an advanced technical analysis tool that transforms traditional volume analysis into a responsive oscillator. By creating a dynamic volume profile and measuring price deviation from volume-weighted equilibrium levels, this indicator provides traders with powerful insights into market momentum and potential reversals.
Key Features
• Volume-weighted price deviation analysis
• Adaptive midline that adjusts to changing market conditions
• Beautiful gradient visualization with 10-level intensity zones
• Fast and slow signal lines for trend confirmation
• Mean reversion mode that identifies price extremes relative to volume
• Fully customizable sensitivity and smoothing parameters
Technical Components
1. Volume Profile Analysis
The indicator builds a dynamic volume profile by:
• Collecting recent price and volume data within a specified lookback period
• Calculating a volume-weighted mean price (similar to VWAP)
• Measuring how far current price has deviated from this weighted average
• Adjusting this deviation based on historical volatility
2. Oscillator Calculation
The oscillator offers two calculation methods:
• Mean Reversion Mode (default): Measures deviation from volume-weighted mean price, normalized to reflect potential overbought/oversold conditions
• Standard Mode : Normalizes volume activity to identify unusual volume patterns
3. Adaptive Zones
The indicator features dynamic zones that:
• Center around an adaptive midline that reflects the average oscillator value
• Expand and contract based on recent volatility (standard deviation)
• Visually represent intensity through multi-level gradient coloring
• Provide clear visualization of bullish/bearish extremes
4. Signal Generation
Trading signals are generated through:
• Main oscillator line position relative to the adaptive midline
• Crossovers between fast (5-period) and slow (15-period) signal lines
• Color changes that instantly identify trend direction
• Distance from the midline indicating trend strength
Configuration Options
Volume Analysis Settings:
• Price Source - Select which price data to analyze
• Volume Source - Define volume data source
• Lookback Period - Number of bars for main calculations
• Profile Calculation Periods - Frequency of profile recalculation
Oscillator Settings:
• Smoothing Length - Controls oscillator smoothness
• Sensitivity - Adjusts responsiveness to price/volume changes
• Mean Reversion Mode - Toggles calculation methodology
Threshold Settings:
• Adaptive Midline - Uses dynamic midline based on historical values
• Midline Period - Lookback period for midline calculation
• Zone Width Multiplier - Controls width of bullish/bearish zones
Display Settings:
• Color Bars - Option to color price bars based on trend direction
Trading Strategies
Trend Following:
• Enter long positions when the oscillator crosses above the adaptive midline
• Enter short positions when the oscillator crosses below the adaptive midline
• Use signal line crossovers for entry timing
• Monitor gradient intensity to gauge trend strength
Mean Reversion Trading:
• Look for oscillator extremes shown by intense gradient colors
• Prepare for potential reversals when the oscillator reaches upper/lower zones
• Use divergences between price and oscillator for confirmation
• Consider scaling positions based on gradient intensity
Volume Analysis:
• Use Standard Mode to identify unusual volume patterns
• Confirm breakouts when accompanied by strong oscillator readings
• Watch for divergences between price and volume-based readings
• Use extended periods in extreme zones as trend confirmation
Best Practices
• Adjust sensitivity based on the asset's typical volatility
• Use longer smoothing for swing trading, shorter for day trading
• Combine with support/resistance levels for optimal entry/exit points
• Consider multiple timeframe analysis for comprehensive market view
• Test different profile calculation periods to match your trading style
This indicator is provided for informational purposes only. Always use proper risk management when trading based on any technical indicator. Not financial advise.
Dynamic CAGR LineIndicator: Dynamic CAGR Line
Overview
This Pine Script (version 6) creates a custom indicator called "Dynamic CAGR Moving Line," designed to calculate and display the Compound Annual Growth Rate (CAGR) in percentage terms for a financial instrument, such as a stock or cryptocurrency, based on a user-defined lookback period (default: 5 years). Unlike traditional overlays that plot directly on the price chart, this indicator appears in a separate pane below the chart, providing a clear visual of how the CAGR evolves over time with each new candle.
Purpose
The indicator helps traders and investors analyze the annualized growth rate of an asset’s price over a specified historical period. By plotting the CAGR as a percentage in a separate pane, users can easily track how the growth rate changes as new price data is added, offering insights into long-term performance trends without cluttering the price chart.
How It Works
User Input:
The script begins with an input parameter, lookback_years, allowing users to define the number of years (e.g., 5) to look back for the CAGR calculation. This is a floating-point value with a minimum of 1 and a step of 0.5, adjustable via the indicator’s settings in TradingView.
Timeframe Conversion:
Assuming a daily chart, the script converts the lookback years into a number of bars using bars_per_year = 252 (the average number of trading days in a year). The total lookback period in bars is calculated as lookback_bars = math.round(lookback_years * bars_per_year). For example, 5 years equals approximately 1260 bars.
Price Data:
For each candle, the start_price is fetched from the closing price lookback_bars ago (e.g., the close price from 5 years prior), using close .
The end_price is the current candle’s closing price, accessed via close.
CAGR Calculation:
The total return is computed as (end_price - start_price) / start_price, measuring the percentage change from the start price to the current price.
To avoid division-by-zero errors, a conditional check ensures start_price != 0; if it is, the return defaults to 0.
The CAGR is then calculated using the formula: math.pow(1 + total_return, 1 / lookback_years) - 1, which annualizes the total return over the lookback period.
The result is converted to a percentage by multiplying by 100 (cagr_percent = cagr * 100).
Plotting:
The CAGR percentage is plotted as a blue line in a separate pane using plot(). The line only appears after enough data exists (bar_index >= lookback_bars), otherwise it plots na (not available).
A label is added for each candle, displaying the current CAGR percentage (e.g., "CAGR: 5.23%") near the plotted value, styled with a blue background and white text.
Usage
Chart Setup: Apply the indicator to a daily chart with sufficient historical data (e.g., more than 5 years for the default setting). It’s designed for daily timeframes but can be adapted for others by adjusting bars_per_year (e.g., 52 for weekly).
Interpretation: A positive CAGR (e.g., 5%) indicates annualized growth, while a negative value (e.g., -2%) shows an annualized decline. A flat line at 0% suggests no net change over the lookback period.
Customization: Adjust lookback_years in the settings to analyze different periods (e.g., 3 or 10 years).
Notes
Ensure your chart has enough data to cover the lookback period, or the line won’t appear until sufficient bars are available.
For debugging, you can temporarily plot start_price and end_price on the main chart to verify the calculation inputs.
Triple SRSI-MFI Ⅲ - Multi TimeframeTriple SRSI-MFI Ⅲ - Multi Timeframe Indicator
Description
The Triple SRSI-MFI Ⅲ - Multi Timeframe indicator is a powerful tool designed to combine Stochastic RSI (SRSI) and Money Flow Index (MFI) across multiple timeframes (higher, current, and lower). It provides a comprehensive view of market momentum and potential overbought/oversold conditions by calculating a weighted hybrid of SRSI-MFI values from three different timeframes. The indicator also integrates Bollinger Bands to help identify trend direction and volatility.
This indicator is ideal for traders who want to analyze market conditions across multiple timeframes without switching charts. It automatically adjusts settings based on the current timeframe and includes a dynamic weighting system optimized for Bitcoin volatility. Additionally, a real-time information panel displays the market state (buy/sell) and signal strength.
Key Features
Multi-Timeframe Analysis: Combines SRSI-MFI from higher, current, and lower timeframes for a holistic view.
Dynamic Weighting: Automatically adjusts weights for each timeframe based on Bitcoin volatility, with an option for manual customization.
Bollinger Bands Integration: Visualizes trend direction and volatility using Bollinger Bands, with customizable source selection.
Real-Time Info Panel: Displays market state (buy/sell) and signal strength (%) in the top-right corner of the chart.
Customizable Settings: Allows users to tweak MFI source, Bollinger Bands parameters, and visibility of individual components.
How to Use
Add to Chart: Add the "Triple SRSI-MFI Ⅲ - Multi Timeframe" indicator to your chart.
Interpret Signals:
Market State (Buy/Sell): Shown in the info panel. "Buy" when the average SRSI-MFI is above the Bollinger Bands basis, "Sell" when below.
Strength (%): The relative position of the average SRSI-MFI within the Bollinger Bands, scaled from 0% to 100%.
Overbought/Oversold Levels: The indicator plots horizontal lines at 80 (overbought) and 20 (oversold). Use these as potential reversal zones.
Combine with Price Action: Use the indicator in conjunction with price action or other tools for better decision-making.
Adjust Settings: Customize the settings (e.g., Bollinger Bands length, weights, visibility) to match your trading style.
Settings
MFI Source: Select the source for MFI calculation (default: "hlc3"). Options include "close", "open", "high", "low", "hl2", "hlc3", "ohlc4".
Bollinger Bands:
Length: Period for Bollinger Bands calculation (default: 20).
Multiplier: Standard deviation multiplier for the bands (default: 2.0).
Source: Choose which SRSI-MFI value to use for Bollinger Bands ("averageHybrid", "hybrid_higher", "hybrid_current", "hybrid_lower"; default: "hybrid_higher").
Weights:
Auto Weight Enabled: Enable/disable automatic weights based on Bitcoin volatility (default: true).
Higher/Current/Lower Weights: Manually set weights for each timeframe if auto-weight is disabled (defaults: 1.5, 1.0, 0.5).
Indicator On/Off:
Toggle visibility for Higher SRSI-MFI, Current SRSI-MFI, Lower SRSI-MFI, Average SRSI-MFI, and Bollinger Bands.
How It Works
SRSI-MFI Calculation:
Stochastic RSI (SRSI) and Money Flow Index (MFI) are calculated for three timeframes: higher, current, and lower.
The hybrid value (SRSI * (MFI / 100)) is computed for each timeframe.
Weighted Average:
The hybrid values are combined into a weighted average (averageHybrid) using dynamic or manual weights.
Bollinger Bands:
Bollinger Bands are applied to the selected source (e.g., hybrid_higher) to identify trend direction and volatility.
Relative Position:
The position of averageHybrid within the Bollinger Bands is scaled to a percentage (0% to 100%) for strength assessment.
Visualization:
Plots individual SRSI-MFI lines, Bollinger Bands, and overbought/oversold levels.
A real-time info panel provides market state and signal strength.
Notes
This indicator is best used as part of a broader trading strategy. It is not a standalone signal generator and should be combined with other forms of analysis.
The automatic weights are optimized for Bitcoin (BTC) volatility. For other assets, you may need to adjust the weights manually.
The indicator may require sufficient historical data to calculate higher and lower timeframe values accurately.
Support & Resistance with RSI BreakoutsThe script is a TradingView Pine Script (v5) indicator that identifies support and resistance levels using RSI (Relative Strength Index) breakouts. Here’s a breakdown of what it does:
Features:
RSI Calculation:
The script calculates the 14-period RSI (default) using the closing price.
The user can modify the RSI period through an input setting.
Buy and Sell Signals:
A buy signal is triggered when RSI drops below 20 (indicating oversold conditions).
A sell signal is triggered when RSI rises above 80 (indicating overbought conditions).
Visual Representation:
Buy signals are marked with a green upward arrow (↑) below the price bars.
Sell signals are marked with a red downward arrow (↓) above the price bars.
The arrows help traders easily spot potential trade opportunities.
Usage:
This script is useful for traders looking to buy at oversold conditions and sell at overbought conditions based on RSI.
It works best when combined with other indicators or price action strategies to confirm signals.
5-Min ORB with Volume SpikeThis indicator identifies Opening Range Breakouts (ORB) based on the high and low of the first 5 minutes of the trading day and confirms the breakout with a volume spike.
🔍 What It Does:
Automatically captures the Opening Range High and Low from 9:30 AM to 9:35 AM (configurable).
Plots green (high) and red (low) lines across the chart once the opening range is set.
Highlights long breakout signals when price breaks above the OR High with above-average volume.
Highlights short breakout signals when price breaks below the OR Low with above-average volume.
Volume confirmation is based on a customizable 20-period simple moving average (SMA) of volume.
⚙️ Best Used On:
5-minute or lower intraday charts (e.g., SPY, QQQ, futures, etc.)
Highly liquid, high-volatility instruments
U.S. equity market open (customizable for other sessions)
📈 Trading Edge: This strategy helps traders identify strong, momentum-driven breakouts early in the trading session — especially when confirmed by increased institutional activity (volume spike).
HILo Ema Squeeze BandsThis indicator combines uses ema to identify price squeeze before a big move.
The ema gets initialised at new high low. It used 3 ema's lengths. For result use x, 2x ,4x ie 50, 100, 200 or 100,200,400 and so on . On more volatile asset use a higher settings like 100,200,400. The inner band is divided into 4 zones, which can give support resistance. As you use it you will become aware of subtle information that it can give at times. Like you may be able to find steps at which prices move, when the market is trending
Just like in Bollinger bands, in a trending market the price stays within sd=1 and sd=2 so does in the inner band the price will remain in band1 and band2. But Bollinger band cannot print steps this indicator shows steps
Daily & Multi-Day High/LowDaily & Multi-Candle High/Low Indicator
This indicator clearly highlights essential price levels directly on your chart, significantly improving your trading decisions:
First Candle High/Low (Session Open):
Quickly identify the high and low of the first candle each trading day, ideal for session-open traders.
Previous Day's High/Low:
Automatically plots the highest and lowest prices from the previous trading day, crucial for daily breakout or reversal strategies.
Multi-Candle High/Low (Customizable Period):
Easily track the highest and lowest points of the last X candles (default: 108 candles). Perfect for spotting key support and resistance zones.
Customization Options:
Adjust colors, line styles (solid, dashed, dotted), and line thickness directly from the settings for personalized visibility.
Ideal for day traders, swing traders, and price-action traders looking for clear and actionable daily levels on their charts.
Double Bollinger Bands MTF and Price projectionI did this script because I wanted to project prices over future bars quickly because I am a options trader.
Options:
Time frame: Default is Chart
Some times I prefer using 15 m with period 200 on a daily chart in a fast moving market. But you can chose what suites you
BB inner deviation 1 is default
When BB inner deviation=1 the outer will be 2X if its 0.5 outer will be 1
Moving Average type : Default EMA
Project next bar in label Default is off
This will calculate a linear projection of price of each band for the number of bars requested and print them in the label. It does not plot the future values
Using: in a trending market the prices will be generally be between band1 and band 2
and other times between -band1 and +band1. The projection can assist in optimal option strategy. Also in a fast moving market I would use 10 period ema for accurate price projections and others 20
Adaptive Regression Channel [MissouriTim]The Adaptive Regression Channel (ARC) is a technical indicator designed to empower traders with a clear, adaptable, and precise view of market trends and price boundaries. By blending advanced statistical techniques with real-time market data, ARC delivers a comprehensive tool that dynamically adjusts to price action, volatility, volume, and momentum. Whether you’re navigating the fast-paced world of cryptocurrencies, the steady trends of stocks, or the intricate movements of FOREX pairs, ARC provides a robust framework for identifying opportunities and managing risk.
Core Components
1. Color-Coded Regression Line
ARC’s centerpiece is a linear regression line derived from a Weighted Moving Average (WMA) of closing prices. This line adapts its calculation period based on market volatility (via ATR) and is capped between a minimum of 20 bars and a maximum of 1.5 times the user-defined base length (default 100). Visually, it shifts colors to reflect trend direction: green for an upward slope (bullish) and red for a downward slope (bearish), offering an instant snapshot of market sentiment.
2. Dynamic Residual Channels
Surrounding the regression line are upper (red) and lower (green) channels, calculated using the standard deviation of residuals—the difference between actual closing prices and the regression line. This approach ensures the channels precisely track how closely prices follow the trend, rather than relying solely on overall price volatility. The channel width is dynamically adjusted by a multiplier that factors in:
Volatility: Measured through the Average True Range (ATR), widening channels during turbulent markets.
Trend Strength: Based on the regression slope, expanding channels in strong trends and contracting them in consolidation phases.
3. Volume-Weighted Moving Average (VWMA)
Plotted in orange, the VWMA overlays a volume-weighted price trend, emphasizing movements backed by significant trading activity. This complements the regression line, providing additional confirmation of trend validity and potential breakout strength.
4. Scaled RSI Overlay
ARC features a Relative Strength Index (RSI) overlay, plotted in purple and scaled to hover closely around the regression line. This compact display reflects momentum shifts within the trend’s context, keeping RSI visible on the price chart without excessive swings. User-defined overbought (default 70) and oversold (default 30) levels offer reference points for momentum analysis."
Technical Highlights
ARC leverages a volatility-adjusted lookback period, residual-based channel construction, and multi-indicator integration to achieve high accuracy. Its parameters—such as base length, channel width, ATR period, and RSI length—are fully customizable, allowing traders to tailor it to their specific needs.
Why Choose ARC?
ARC stands out for its adaptability and precision. The residual-based channels offer tighter, more relevant support and resistance levels compared to standard volatility measures, while the dynamic adjustments ensure it performs well in both trending and ranging markets. The inclusion of VWMA and scaled RSI adds depth, merging trend, volume, and momentum into a single, cohesive overlay. For traders seeking a versatile, all-in-one indicator, ARC delivers actionable insights with minimal noise.
Best Ways to Use the Adaptive Regression Channel (ARC)
The Adaptive Regression Channel (ARC) is a flexible tool that supports a variety of trading strategies, from trend-following to breakout detection. Below are the most effective ways to use ARC, along with practical tips for maximizing its potential. Adjustments to its settings may be necessary depending on the timeframe (e.g., intraday vs. daily) and the asset being traded (e.g., stocks, FOREX, cryptocurrencies), as each market exhibits unique volatility and behavior.
1. Trend Following
• How to Use: Rely on the regression line’s color to guide your trades. A green line (upward slope) signals a bullish trend—consider entering or holding long positions. A red line (downward slope) indicates a bearish trend—look to short or exit longs.
• Best Practice: Confirm the trend with the VWMA (orange line). Price above the VWMA in a green uptrend strengthens the bullish case; price below in a red downtrend reinforces bearish momentum.
• Adjustment: For short timeframes like 15-minute crypto charts, lower the Base Regression Length (e.g., to 50) for quicker trend detection. For weekly stock charts, increase it (e.g., to 200) to capture broader movements.
2. Channel-Based Trades
• How to Use: Use the upper channel (red) as resistance and the lower channel (green) as support. Buy when the price bounces off the lower channel in an uptrend, and sell or short when it rejects the upper channel in a downtrend.
• Best Practice: Check the scaled RSI (purple line) for momentum cues. A low RSI (e.g., near 30) at the lower channel suggests a stronger buy signal; a high RSI (e.g., near 70) at the upper channel supports a sell.
• Adjustment: In volatile crypto markets, widen the Base Channel Width Coefficient (e.g., to 2.5) to reduce false signals. For stable FOREX pairs (e.g., EUR/USD), a narrower width (e.g., 1.5) may work better.
3. Breakout Detection
• How to Use: Watch for price breaking above the upper channel (bullish breakout) or below the lower channel (bearish breakout). These moves often signal strong momentum shifts.
• Best Practice: Validate breakouts with VWMA position—price above VWMA for bullish breaks, below for bearish—and ensure the regression line’s slope aligns (green for up, red for down).
• Adjustment: For fast-moving assets like crypto on 1-hour charts, shorten ATR Length (e.g., to 7) to make channels more reactive. For stocks on daily charts, keep it at 14 or higher for reliability.
4. Momentum Analysis
• How to Use: The scaled RSI overlay shows momentum relative to the regression line. Rising RSI in a green uptrend confirms bullish strength; falling RSI in a red downtrend supports bearish pressure.
• Best Practice: Look for RSI divergences—e.g., price hitting new highs at the upper channel while RSI flattens or drops could signal an impending reversal.
• Adjustment: Reduce RSI Length (e.g., to 7) for intraday trading in FOREX or crypto to catch short-term momentum shifts. Increase it (e.g., to 21) for longer-term stock trades.
5. Range Trading
• How to Use: When the regression line’s slope is near zero (flat) and channels are tight, ARC indicates a ranging market. Buy near the lower channel and sell near the upper channel, targeting the regression line as the mean price.
• Best Practice: Ensure VWMA hovers close to the regression line to confirm the range-bound state.
• Adjustment: For low-volatility stocks on daily charts, use a moderate Base Regression Length (e.g., 100) and tight Base Channel Width (e.g., 1.5). For choppy crypto markets, test shorter settings.
Optimization Strategies
• Timeframe Customization: Adjust ARC’s parameters to match your trading horizon. Short timeframes (e.g., 1-minute to 1-hour) benefit from lower Base Regression Length (20–50) and ATR Length (7–10) for agility, while longer timeframes (e.g., daily, weekly) favor higher values (100–200 and 14–21) for stability.
• Asset-Specific Tuning:
○ Stocks: Use longer lengths (e.g., 100–200) and moderate widths (e.g., 1.8) for stable equities; tweak ATR Length based on sector volatility (shorter for tech, longer for utilities).
○ FOREX: Set Base Regression Length to 50–100 and Base Channel Width to 1.5–2.0 for smoother trends; adjust RSI Length (e.g., 10–14) based on pair volatility.
○ Crypto: Opt for shorter lengths (e.g., 20–50) and wider widths (e.g., 2.0–3.0) to handle rapid price swings; use a shorter ATR Length (e.g., 7) for quick adaptation.
• Backtesting: Test ARC on historical data for your asset and timeframe to optimize settings. Evaluate how often price respects channels and whether breakouts yield profitable trades.
• Enhancements: Pair ARC with volume surges, key support/resistance levels, or candlestick patterns (e.g., doji at channel edges) for higher-probability setups.
Practical Considerations
ARC’s adaptability makes it suitable for diverse markets, but its performance hinges on proper calibration. Cryptocurrencies, with their high volatility, may require shorter, wider settings to capture rapid moves, while stocks on longer timeframes benefit from broader, smoother configurations. FOREX pairs often fall in between, depending on their inherent volatility. Experiment with the adjustable parameters to align ARC with your trading style and market conditions, ensuring it delivers the precision and reliability you need.
Deviation ChannelsIndicator Name: Deviation Channels (Dev Chan)
Why Use This Indicator?
Visualize Volatility Ranges:
The indicator plots Keltner Channels at four levels above and below an average line, letting you easily see how far price has deviated from a typical range. Each “dev” line highlights potential support or resistance during pullbacks or surges.
Color-Coded Clarity:
Each band shifts color intensity depending on whether the current price is trading above or below it, letting you spot breakouts and rejections at a glance. Meanwhile, the Fast SMA (default 10) also changes color – green if price is above, red if below – adding a quick momentum read.
Adjustable Source & Length:
Choose your input source (open, close, ohlc4, or hlc3) and set your Keltner length to suit different asset classes or timeframes. Whether you want a tighter, more reactive channel or a smoother, longer-term reading, the script adapts with minimal effort.
A Simple Trading Approach
Identify Trend with Fast SMA:
If the Fast SMA (default length 10) is green (price above it), treat that as a bullish environment. If it’s red (price below), favor bearish or neutral stances.
Wait for Price to Reach Lower/Upper Deviations:
In a bullish setup (Fast SMA green), watch for price to dip into one of the lower channels (e.g., -1 Dev or -2 Dev). Such pullbacks can become potential “buy the dip” zones if price stabilizes and resumes upward momentum.
Conversely, if the Fast SMA is red, watch for price to test the upper channels (1 Dev or 2 Dev). That might be a short opportunity or a place to close out any remaining longs before a deeper correction.
Manage Risk with Channel Levels:
Place stop-losses just beyond the next “dev” band to protect against volatility. For example, if you enter on a bounce at -1 Dev, consider placing a stop near -2 Dev or -3 Dev, depending on your risk tolerance.
Take Profits Gradually:
In an uptrend, you might scale out of positions as price moves toward higher lines (e.g., 1 Dev or 2 Dev). Conversely, if price fails to hold above the Fast SMA or repeatedly closes below a key band, it might be time to exit.
Disclaimer: No single indicator is foolproof. Always combine with sound risk management, observe multiple timeframes, and consider fundamental factors before making trading decisions. Experiment with the Keltner length and Fast SMA fastLength to find the sweet spot for your market and time horizon.
Keltner Channel StrategyOverview
The Keltner Channel Strategy is a powerful trend-following and mean-reversion system that leverages the Keltner Channels, EMA crossovers, and ATR-based stop-losses to optimize trade entries and exits. This strategy has proven to be highly effective, particularly when applied to Gold (XAUUSD) and other commodities with strong trend characteristics.
📈 How It Works
This strategy incorporates two trading approaches: 1️⃣ Keltner Channel Reversal Trades – Identifies overbought and oversold conditions when price touches the outer bands.
2️⃣ Trend Following Trades – Uses the 9 EMA & 21 EMA crossover, with confirmation from the 50 EMA, to enter trades in the direction of the trend.
🔍 Entry & Exit Criteria
📊 Keltner Channel Entries (Reversal Strategy)
✅ Long Entry: When the price crosses below the lower Keltner Band (potential reversal).
✅ Short Entry: When the price crosses above the upper Keltner Band (potential reversal).
⏳ Exit Conditions:
Long positions close when price crosses back above the mid-band (EMA-based).
Short positions close when price crosses back below the mid-band (EMA-based).
📈 Trend Following Entries (Momentum Strategy)
✅ Long Entry: When the 9 EMA crosses above the 21 EMA, and price is above the 50 EMA (bullish momentum).
✅ Short Entry: When the 9 EMA crosses below the 21 EMA, and price is below the 50 EMA (bearish momentum).
⏳ Exit Conditions:
Long positions close when the 9 EMA crosses back below the 21 EMA.
Short positions close when the 9 EMA crosses back above the 21 EMA.
📌 Risk Management & Profit Targeting
ATR-based Stop-Losses:
Long trades: Stop set at 1.5x ATR below entry price.
Short trades: Stop set at 1.5x ATR above entry price.
Take-Profit Levels:
Long trades: Profit target 2x ATR above entry price.
Short trades: Profit target 2x ATR below entry price.
🚀 Why Use This Strategy?
✅ Works exceptionally well on Gold (XAUUSD) due to high volatility.
✅ Combines reversal & trend strategies for improved adaptability.
✅ Uses ATR-based risk management for dynamic position sizing.
✅ Fully automated alerts for trade entries and exits.
🔔 Alerts
This script includes automated TradingView alerts for:
🔹 Keltner Band touches (Reversal signals).
🔹 EMA crossovers (Momentum trades).
🔹 Stop-loss & Take-profit activations.
📊 Ideal Markets & Timeframes
Best for: Gold (XAUUSD), NASDAQ (NQ), Crude Oil (CL), and trending assets.
Recommended Timeframes: 15m, 1H, 4H, Daily.
⚡️ How to Use
1️⃣ Add this script to your TradingView chart.
2️⃣ Select a 15m, 1H, or 4H timeframe for optimal results.
3️⃣ Enable alerts to receive trade notifications in real time.
4️⃣ Backtest and tweak ATR settings to fit your trading style.
🚀 Optimize your Gold trading with this Keltner Channel Strategy! Let me know how it performs for you. 💰📊
Adaptive Bollinger BandsAdaptive Bollinger Bands
This indicator displays Bollinger Bands with parameters that dynamically adjust based on market volatility. Unlike standard Bollinger Bands with fixed parameters, this version adaptively modifies both the period and standard deviation multiplier in real-time based on measured market conditions.
Key Features
Dynamic adjustment of period and standard deviation based on normalized volatility
Color-coded visualization of current volatility regime (expanding, normal, contracting)
Integration with Keltner Channels for band refinement
Bandwidth analysis for volatility regime identification
Optional on-chart parameter labels showing current settings
Band cross alerts and visual markers
Volatility Visualization
The indicator uses color-coding to display different volatility regimes:
Red: Expanding volatility regime (higher measured volatility)
Blue: Normal volatility regime (average measurements)
Green: Contracting volatility regime (lower measured volatility)
Technical Information
The indicator calculates volatility by analyzing price returns over a configurable lookback period (default 50 bars). The standard deviation of returns is normalized against historical extremes to create an adaptive scaling factor.
Band adaptation occurs through two primary mechanisms:
1. Period adjustment: Higher volatility uses shorter periods (more responsive), while lower volatility uses longer periods (more stable)
2. Standard deviation multiplier adjustment: Higher volatility increases the multiplier (wider bands), while lower volatility decreases it (tighter bands)
The middle band uses a simple moving average with the adaptive period. Additional refinement occurs through Keltner Channel integration, which can tighten bands when contained within Keltner boundaries.
Volatility regimes are determined by analyzing Bollinger Bandwidth relative to its recent history, providing contextual information about the current market state.
Settings Customization
The indicator provides extensive customization options:
- Base parameters (period and standard deviation)
- Adaptive range limits (min/max period and standard deviation)
- Keltner Channel parameters for band refinement
- Bandwidth analysis settings
- Display options for visual elements
Limitations and Considerations
All technical indicators have inherent limitations and should not be used in isolation
Past performance does not guarantee future results
The indicator requires sufficient historical data for proper volatility normalization
Smaller timeframes may produce more noise in the adaptive calculations
Parameters may require adjustment for different markets and trading styles
Band crosses are not trading signals on their own and should be evaluated with other factors
This indicator is designed to provide objective information about market volatility conditions and potential support/resistance zones. Always combine with other analysis methods within a comprehensive trading approach.
Wall Street Ai**Wall Street Ai – Advanced Technical Indicator for Market Analysis**
**Overview**
Wall Street Ai is an advanced, AI-powered technical indicator meticulously engineered to provide traders with in-depth market analysis and insight. By leveraging state-of-the-art artificial intelligence algorithms and comprehensive historical price data, Wall Street Ai is designed to identify significant market turning points and key price levels. Its sophisticated analytical framework enables traders to uncover potential shifts in market momentum, assisting in the formulation of strategic trading decisions while maintaining the highest standards of objectivity and reliability.
**Key Features**
- **Intelligent Pattern Recognition:**
Wall Street Ai employs advanced machine learning techniques to analyze historical price movements and detect recurring patterns. This capability allows it to differentiate between typical market noise and meaningful signals indicative of potential trend reversals.
- **Robust Noise Reduction:**
The indicator incorporates a refined volatility filtering system that minimizes the impact of minor price fluctuations. By isolating significant price movements, it ensures that the analytical output focuses on substantial market shifts rather than ephemeral variations.
- **Customizable Analytical Parameters:**
With a wide range of adjustable settings, Wall Street Ai can be fine-tuned to align with diverse trading strategies and risk appetites. Traders can modify sensitivity, threshold levels, and other critical parameters to optimize the indicator’s performance under various market conditions.
- **Comprehensive Data Analysis:**
By harnessing the power of artificial intelligence, Wall Street Ai performs a deep analysis of historical data, identifying statistically significant highs and lows. This analysis not only reflects past market behavior but also provides valuable insights into potential future turning points, thereby enhancing the predictive aspect of your trading strategy.
- **Adaptive Market Insights:**
The indicator’s dynamic algorithm continuously adjusts to current market conditions, adapting its analysis based on real-time data inputs. This adaptive quality ensures that the indicator remains relevant and effective across different market environments, whether the market is trending strongly, consolidating, or experiencing volatility.
- **Objective and Reliable Analysis:**
Wall Street Ai is built on a foundation of robust statistical methods and rigorous data validation. Its outputs are designed to be objective and free from any exaggerated claims, ensuring that traders receive a clear, unbiased view of market conditions.
**How It Works**
Wall Street Ai integrates advanced AI and deep learning methodologies to analyze a vast array of historical price data. Its core algorithm identifies and evaluates critical market levels by detecting patterns that have historically preceded significant market movements. By filtering out non-essential fluctuations, the indicator emphasizes key price extremes and trend changes that are likely to impact market behavior. The system’s adaptive nature allows it to recalibrate its analytical parameters in response to evolving market dynamics, providing a consistently reliable framework for market analysis.
**Usage Recommendations**
- **Optimal Timeframes:**
For the most effective application, it is recommended to utilize Wall Street Ai on higher timeframe charts, such as hourly (H1) or higher. This approach enhances the clarity of the detected patterns and provides a more comprehensive view of long-term market trends.
- **Market Versatility:**
Wall Street Ai is versatile and can be applied across a broad range of financial markets, including Forex, indices, commodities, cryptocurrencies, and equities. Its adaptable design ensures consistent performance regardless of the asset class being analyzed.
- **Complementary Analytical Tools:**
While Wall Street Ai provides profound insights into market behavior, it is best utilized in combination with other analytical tools and techniques. Integrating its analysis with additional indicators—such as trend lines, support/resistance levels, or momentum oscillators—can further refine your trading strategy and enhance decision-making.
- **Strategy Testing and Optimization:**
Traders are encouraged to test Wall Street Ai extensively in a simulated trading environment before deploying it in live markets. This allows for thorough calibration of its settings according to individual trading styles and risk management strategies, ensuring optimal performance across diverse market conditions.
**Risk Management and Best Practices**
Wall Street Ai is intended to serve as an analytical tool that supports informed trading decisions. However, as with any technical indicator, its outputs should be interpreted as part of a comprehensive trading strategy that includes robust risk management practices. Traders should continuously validate the indicator’s findings with additional analysis and maintain a disciplined approach to position sizing and risk control. Regular review and adjustment of trading strategies in response to market changes are essential to mitigate potential losses.
**Conclusion**
Wall Street Ai offers a cutting-edge, AI-driven approach to technical analysis, empowering traders with detailed market insights and the ability to identify potential turning points with precision. Its intelligent pattern recognition, adaptive analytical capabilities, and extensive noise reduction make it a valuable asset for both experienced traders and those new to market analysis. By integrating Wall Street Ai into your trading toolkit, you can enhance your understanding of market dynamics and develop a more robust, data-driven trading strategy—all while adhering to the highest standards of analytical integrity and performance.
Elastic Volume-Weighted Student-T TensionOverview
The Elastic Volume-Weighted Student-T Tension Bands indicator dynamically adapts to market conditions using an advanced statistical model based on the Student-T distribution. Unlike traditional Bollinger Bands or Keltner Channels, this indicator leverages elastic volume-weighted averaging to compute real-time dispersion and location parameters, making it highly responsive to volatility changes while maintaining robustness against price fluctuations.
This methodology is inspired by incremental calculation techniques for weighted mean and variance, as outlined in the paper by Tony Finch:
📄 "Incremental Calculation of Weighted Mean and Variance" .
Key Features
✅ Adaptive Volatility Estimation – Uses an exponentially weighted Student-T model to dynamically adjust band width.
✅ Volume-Weighted Mean & Dispersion – Incorporates real-time volume weighting, ensuring a more accurate representation of market sentiment.
✅ High-Timeframe Volume Normalization – Provides an option to smooth volume impact by referencing a higher timeframe’s cumulative volume, reducing noise from high-variability bars.
✅ Customizable Tension Parameters – Configurable standard deviation multipliers (σ) allow for fine-tuned volatility sensitivity.
✅ %B-Like Oscillator for Relative Price Positioning – The main indicator is in form of a dedicated oscillator pane that normalizes price position within the sigma ranges, helping identify overbought/oversold conditions and potential momentum shifts.
✅ Robust Statistical Foundation – Utilizes kurtosis-based degree-of-freedom estimation, enhancing responsiveness across different market conditions.
How It Works
Volume-Weighted Elastic Mean (eμ) – Computes a dynamic mean price using an elastic weighted moving average approach, influenced by trade volume, if not volume detected in series, study takes true range as replacement.
Dispersion (eσ) via Student-T Distribution – Instead of assuming a fixed normal distribution, the bands adapt to heavy-tailed distributions using kurtosis-driven degrees of freedom.
Incremental Calculation of Variance – The indicator applies Tony Finch’s incremental method for computing weighted variance instead of arithmetic sum's of fixed bar window or arrays, improving efficiency and numerical stability.
Tension Calculation – There are 2 dispersion custom "zones" that are computed based on the weighted mean and dynamically adjusted standard student-t deviation.
%B-Like Oscillator Calculation – The oscillator normalizes the price within the band structure, with values between 0 and 1:
* 0.00 → Price is at the lower band (-2σ).
* 0.50 → Price is at the volume-weighted mean (eμ).
* 1.00 → Price is at the upper band (+2σ).
* Readings above 1.00 or below 0.00 suggest extreme movements or possible breakouts.
Recommended Usage
For scalping in lower timeframes, it is recommended to use the fixed α Decay Factor, it is in raw format for better control, but you can easily make a like of transformation to N-bar size window like in EMA-1 bar dividing 2 / decayFactor or like an RMA dividing 1 / decayFactor.
The HTF selector catch quite well Higher Time Frame analysis, for example using a Daily chart and using as HTF the 200-day timeframe, weekly or monthly.
Suitable for trend confirmation, breakout detection, and mean reversion plays.
The %B-like oscillator helps gauge momentum strength and detect divergences in price action if user prefer a clean chart without bands, this thanks to pineScript v6 force overlay feature.
Ideal for markets with volume-driven momentum shifts (e.g., futures, forex, crypto).
Customization Parameters
Fixed α Decay Factor – Controls the rate of volume weighting influence for an approximation EWMA approach instead of using sum of series or arrays, making the code lightweight & computing fast O(1).
HTF Volume Smoothing – Instead of a fixed denominator for computing α , a volume sum of the last 2 higher timeframe closed candles are used as denominator for our α weight factor. This is useful to review mayor trends like in daily, weekly, monthly.
Tension Multipliers (±σ) – Adjusts sensitivity to dispersion sigma parameter (volatility).
Oscillator Zone Fills – Visual cues for price positioning within the cloud range.
Posible Interpretations
As market within indicators relay on each individual edge, this are just some key ideas to glimpse how the indicator could be interpreted by the user:
📌 Price inside bands – Market is considered somehow "stable"; price is like resting from tension or "charging batteries" for volume spike moves.
📌 Price breaking outer bands – Potential breakout or extreme movement; watch for reversals or continuation from strong moves. Market is already in tension or generating it.
📌 Narrowing Bands – Decreasing volatility; expect contraction before expansion.
📌 Widening Bands – Increased volatility; prepare for high probability pull-back moves, specially to the center location of the bands (the mean) or the other side of them.
📌 Oscillator is just the interpretation of the price normalized across the Student-T distribution fitting "curve" using the location parameter, our Elastic Volume weighted mean (eμ) fixed at 0.5 value.
Final Thoughts
The Elastic Volume-Weighted Student-T Tension indicator provides a powerful, volume-sensitive alternative to traditional volatility bands. By integrating real-time volume analysis with an adaptive statistical model, incremental variance computation, in a relative price oscillator that can be overlayed in the chart as bands, it offers traders an edge in identifying momentum shifts, trend strength, and breakout potential. Think of the distribution as a relative "tension" rubber band in which price never leave so far alone.
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is, following TradingView's regulations. Use of indicator and their code are published for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED FOR TESTING. The models included in the indicator have been taken from open sources on the web and some of them has been modified by the author, problems could occur at diverse data sceneries, compiler version, or any other externality.
Mswing HommaThe Mswing is a momentum oscillator that calculates the rate of price change over 20 and 50 periods (days/weeks). Apart from quantifying momentum, it can be used for assessing relative strength, sectoral rotation & entry/exit signals.
Quantifying Momentum Strength
The Mswing's relationship with its EMA (e.g., 5-period or 9-period) is used for momentum analysis:
• M Swing >0 and Above EMA: Momentum is positive and accelerating (ideal for entries).
• M Swing >0 and Below EMA: Momentum is positive but decelerating (caution).
• M Swing <0 and Above EMA: Momentum is negative but improving (watch for reversals).
• M Swing <0 and Below EMA: Momentum is negative and worsening (exit or avoid).
Relative Strength Scanning (M Score)
Sort stocks by their M Swing using TradingView’s Pine scanner.
Compare the Mswing scores of indices/sectors to allocate capital to stronger groups (e.g., renewables vs. traditional energy).
Stocks with strong Mswing scores tend to outperform during bullish phases, while weak ones collapse faster in downtrends.
Entry and Exit Signals
Entry: Buy when Mswing crosses above 0 + price breaks key moving averages (50-day SMA). Use Mswing >0 to confirm valid breakouts. Buy dips when Mswing holds above EMA during retracements.
Exit: Mswing can be used for exiting a stock in 2 ways:
• Sell in Strength: Mswing >4 (overbought).
• Sell in Weakness: Mswing <0 + price below 50-day SMA.
Multi-Timeframe Analysis
• Daily: For swing trades.
• Weekly: For trend confirmation.
• Monthly: For long-term portfolio adjustments.
Rolling Pivot PointsThe "Rolling Pivot Points" indicator, built in Pine Script (version 6) for TradingView, overlays dynamic pivot levels on a price chart. It calculates a 24-hour lookback period (length = 1440 / (timeframe.in_seconds() / 60)) using the prior period’s high, low, and close to determine a Pivot Point (vPP) and three resistance (vR1, vR2, vR3) and support (vS1, vS2, vS3) levels. Plotted lines include vPP (yellow), vR1 (red), and vS1 (blue) in a cross style, with a customizable reset time (default: 8 AM) to refresh levels daily.
The indicator updates at the specified resetTime (minute = 0), otherwise retaining prior levels, making it ideal for intraday traders. The averageDays input (default: 5) is present but unclear in function. Suited for identifying key price zones, it adapts across timeframes, offering a concise, color-coded tool for technical analysis on TradingView.
Price and Volume Breakout - Jemmy TradeThe "Price and Volume Breakout" indicator is designed to identify potential breakout opportunities by analyzing both price and volume trends. It uses a combination of historical price highs, volume peaks, and a customizable Simple Moving Average (SMA) to signal bullish breakouts. When the price exceeds the highest price of the defined breakout period and is supported by high volume, the indicator triggers visual alerts on the chart. These include dotted lines, labels, and boxes highlighting accumulation zones, along with dynamically calculated stop loss and take profit levels.
Key Features:
• Breakout Detection: Compares the current closing price to the highest price and volume over specified periods to signal a breakout.
• Customizable Stop Loss Options: Offers three methods for setting stop loss levels:
o Below SMA: Positions stop loss a user-defined percentage below the SMA.
o Lowest Low: Uses the lowest low over a specific look-back period.
o Range Average: Calculates an average based on the previous price range.
• Dynamic Take Profit Calculation: Automatically computes take profit levels based on the defined risk-to-reward ratio.
• Visual Chart Elements: Draws breakout lines, stop loss and take profit indicators, labels (e.g., "🚀 Breakout Buy", "🔴 Stop Loss", "🟢 Take Profit"), and boxes marking accumulation zones for easy visualization.
• Alert Conditions: Includes alert functionality to notify traders when breakout conditions are met, enabling timely trading decisions.
How to Use:
1. Customization: Adjust settings such as the breakout periods for price and volume, the length of the SMA, stop loss options, and the risk-to-reward ratio to fit your trading strategy.
2. Signal Identification: When the price exceeds the highest value from the previous period, accompanied by high volume and confirmation from the SMA, the indicator displays a "Breakout Buy" signal.
3. Risk Management: The indicator calculates appropriate stop loss and take profit levels automatically based on your selected parameters, ensuring a balanced risk/reward setup.
4. Alerts: Utilize the built-in alert conditions to receive notifications whenever the breakout criteria are satisfied, helping you act promptly.
PLEASE USE IT AS PER YOUR OWN RISK MANAGEMENT STRATEGIES.
Keywords:
#Breakout #Trading #VolumeAnalysis #TechnicalAnalysis #PriceAction #RiskManagement #TrendFollowing #TradingSignals #PriceBreakout #SmartTrading #JemmyTrade
Lowess Channel + (RSI) [ChartPrime]The Lowess Channel + (RSI) indicator applies the LOWESS (Locally Weighted Scatterplot Smoothing) algorithm to filter price fluctuations and construct a dynamic channel. LOWESS is a non-parametric regression method that smooths noisy data by fitting weighted linear regressions at localized segments. This technique is widely used in statistical analysis to reveal trends while preserving data structure.
In this indicator, the LOWESS algorithm is used to create a central trend line and deviation-based bands. The midline changes color based on trend direction, and diamonds are plotted when a trend shift occurs. Additionally, an RSI gauge is positioned at the end of the channel to display the current RSI level in relation to the price bands.
lowess_smooth(src, length, bandwidth) =>
sum_weights = 0.0
sum_weighted_y = 0.0
sum_weighted_xy = 0.0
sum_weighted_x2 = 0.0
sum_weighted_x = 0.0
for i = 0 to length - 1
x = float(i)
weight = math.exp(-0.5 * (x / bandwidth) * (x / bandwidth))
y = nz(src , 0)
sum_weights := sum_weights + weight
sum_weighted_x := sum_weighted_x + weight * x
sum_weighted_y := sum_weighted_y + weight * y
sum_weighted_xy := sum_weighted_xy + weight * x * y
sum_weighted_x2 := sum_weighted_x2 + weight * x * x
mean_x = sum_weighted_x / sum_weights
mean_y = sum_weighted_y / sum_weights
beta = (sum_weighted_xy - mean_x * mean_y * sum_weights) / (sum_weighted_x2 - mean_x * mean_x * sum_weights)
alpha = mean_y - beta * mean_x
alpha + beta * float(length / 2) // Centered smoothing
⯁ KEY FEATURES
LOWESS Price Filtering – Smooths price fluctuations to reveal the underlying trend with minimal lag.
Dynamic Trend Coloring – The midline changes color based on trend direction (e.g., bullish or bearish).
Trend Shift Diamonds – Marks points where the midline color changes, indicating a possible trend shift.
Deviation-Based Bands – Expands above and below the midline using ATR-based multipliers for volatility tracking.
RSI Gauge Display – A vertical gauge at the right side of the chart shows the current RSI level relative to the price channel.
Fully Customizable – Users can adjust LOWESS length, band width, colors, and enable or disable the RSI gauge and adjust RSIlength.
⯁ HOW TO USE
Use the LOWESS midline as a trend filter —bullish when green, bearish when purple.
Watch for trend shift diamonds as potential entry or exit signals.
Utilize the price bands to gauge overbought and oversold zones based on volatility.
Monitor the RSI gauge to confirm trend strength—high RSI near upper bands suggests overbought conditions, while low RSI near lower bands indicates oversold conditions.
⯁ CONCLUSION
The Lowess Channel + (RSI) indicator offers a powerful way to analyze market trends by applying a statistically robust smoothing algorithm. Unlike traditional moving averages, LOWESS filtering provides a flexible, responsive trendline that adapts to price movements. The integrated RSI gauge enhances decision-making by displaying momentum conditions alongside trend dynamics. Whether used for trend-following or mean reversion strategies, this indicator provides traders with a well-rounded perspective on market behavior.
Logarithmic Regression Channel-Trend [BigBeluga]
This indicator utilizes logarithmic regression to track price trends and identify overbought and oversold conditions within a trend. It provides traders with a dynamic channel based on logarithmic regression, offering insights into trend strength and potential reversal zones.
🔵Key Features:
Logarithmic Regression Trend Tracking: Uses log regression to model price trends and determine trend direction dynamically.
f_log_regression(src, length) =>
float sumX = 0.0
float sumY = 0.0
float sumXSqr = 0.0
float sumXY = 0.0
for i = 0 to length - 1
val = math.log(src )
per = i + 1.0
sumX += per
sumY += val
sumXSqr += per * per
sumXY += val * per
slope = (length * sumXY - sumX * sumY) / (length * sumXSqr - sumX * sumX)
average = sumY / length
intercept = average - slope * sumX / length + slope
Regression-Based Channel: Plots a log regression channel around the price to highlight overbought and oversold conditions.
Adaptive Trend Colors: The color of the regression trend adjusts dynamically based on price movement.
Trend Shift Signals: Marks trend reversals when the log regression line cross the log regression line 3 bars back.
Dashboard for Key Insights: Displays:
- The regression slope (multiplied by 100 for better scale).
- The direction of the regression channel.
- The trend status of the logarithmic regression band.
🔵Usage:
Trend Identification: Observe the regression slope and channel direction to determine bullish or bearish trends.
Overbought/Oversold Conditions: Use the channel boundaries to spot potential reversal zones when price deviates significantly.
Breakout & Continuation Signals: Price breaking outside the channel may indicate strong trend continuation or exhaustion.
Confirmation with Other Indicators: Combine with volume or momentum indicators to strengthen trend confirmation.
Customizable Display: Users can modify the lookback period, channel width, midline visibility, and color preferences.
Logarithmic Regression Channel-Trend is an essential tool for traders who want a dynamic, regression-based approach to market trends while monitoring potential price extremes.
NIFTY VWAP DistanceNIFTY Futures VWAP Distance Indicator
Track price deviation from Volume-Weighted Average Price in real-time
📈 Key Features:
Measures absolute (points) and percentage distance from VWAP
Daily session reset aligned with NSE trading hours
Dual-axis visualization with clear zero reference line
Real-time data table display for instant analysis
Typical price calculation: (H+L+C)/3 formula
Built-in safeguards against division errors
🎯 Ideal For:
Intraday traders monitoring mean reversion opportunities
Algorithmic traders needing VWAP deviation metrics
Swing traders identifying overextended price moves
Market profile analysts studying auction theory
📊 How to Use:
Apply to NIFTY Futures chart (1m-1h timeframes recommended)
Blue line = Points above/below VWAP
Red line = Percentage deviation
Positive values = Price > VWAP (bullish territory)
Negative values = Price < VWAP (bearish territory)
💡 Pro Tips:
Combine with volume profile for confirmation
Watch for >1% deviations for potential reversals
Use divergence patterns for early trend change signals
Works best with raw futures data (not continuous contracts)
🔧 Technical Specs:
Pine Script v5+
No repainting
Low latency calculations
Mobile-friendly display
"Know when price strays too far from fair value"
