Ultimate Scalping Tool⚡[BullByte]Ultimate Scalping Tool⚡
A Multi-Dimensional Adaptive Oscillator for Precision Trading
Core Concept & Originality
This script is NOT a simple mashup of indicators. It introduces a proprietary "Quantum Flux Oscillator" that dynamically combines trend, momentum, volatility, and volume pressure into a single normalized score (-100 to +100), weighted adaptively based on market regime. Key innovations:
1. Adaptive Weighting System: Automatically adjusts component weights (Trend/Momentum/Volatility/Volume) based on real-time market conditions (e.g., increases trend weight during strong ADX phases).
2. Quantum Flux Candle Visualization: Translates oscillator values into candlestick-like structures for intuitive pattern recognition, with colors that shift based on confluence with higher timeframe filters.
3. Multi-Timeframe Smart Filtering: Implements a unique "Leading HTF Filter" that uses EMA crossovers (instead of lagging ADX) for faster trend confirmation.
4. Dynamic Thresholds: Auto-adjusts overbought/oversold levels using volatility-standard deviation, reducing false signals in choppy markets.
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🛠 How It Works
Component Integration Logic
1. Trend (ADX + DI):
- Normalized ADX (0-1 scale) with directional bias from DI crossover.
- Why? Isolates trending phases while filtering out sideways noise.
2. Momentum (RSI):
- Standard RSI normalized to oscillate around zero.
- Why? Confirms strength of moves identified by trend.
3. Volatility (ATR Ratio):
- ATR divided by price to detect abnormal volatility regimes.
- Why? Prevents false breakouts during low-volatility traps.
4. Volume Pressure (CMF):
- Chaikin Money Flow normalized to detect institutional activity.
- Why? Adds conviction by confirming retail vs. smart money participation.
Signal Generation
- Strong Buy/Sell: Requires oscillator >|25| AND trend alignment (DI+ > DI- for buys).
- Early Signals: Uses oscillator delta (>0.5) to detect momentum shifts before thresholds are hit.
- Pullback Signals: Triggers when oscillator retraces to neutral zone but trend remains intact.
Dashboard Components & Trader Actions
Trend (TF) displays normalized ADX/DI trend strength: green indicates bullish conditions at or above 0.4, gray signals a sideways market, and red denotes bearish readings at or below –0.4—traders should follow trades in the direction of green or red and avoid gray ranges.
Momentum (TF) shows the RSI‑based momentum component: green for strong momentum, yellow for neutral, and red for weak—enter trades on green signals and be cautious when yellow appears.
Volume (CMF) measures buying and selling pressure over the lookback period: dark green corresponds to high buying pressure and dark red to moderate selling—use green readings to confirm entries and exit on strong selling.
Basic Signal is the primary entry/exit trigger: pullback sell appears in red, strong buy in green, and neutral states indicate no trade—execute buys on green, sells on red, and skip neutral.
Advanced Signal refines guidance using oscillator peaks and delta smoothing: “ Caution – Momentum Weak” displays in yellow to warn of weakening momentum, while “Early Buy” appears in lime to suggest a building uptrend—exercise caution on yellow warnings and consider early setups on lime signals.
RSI lists the raw 14‑period RSI value to highlight overbought (above 70) and oversold (below 30) conditions—use it as a secondary filter for entry and exit decisions.
HTF Filter indicates the higher‑timeframe trend via EMA crossover or HTF‑ADX: green for bullish alignment and red for bearish—only follow signals aligned with the higher timeframe trend when the filter is enabled.
VWAP shows the volume‑weighted average price, colored green when price trades above it and red when below—bias long positions above VWAP and short positions below.
ADX displays the raw ADX reading along with an arrow showing its direction (up arrow if rising, down arrow if falling)—a rising ADX signals a trending market, while a flat ADX favors range‑trading strategies.
Mode denotes the preset market‑type profile (Custom, Crypto, Stocks, or Forex) , allowing traders to quickly load optimized default settings for different asset classes.
Regime indicates volatility regimes based on ATR ratio: green for low‑volatility environments and red for high‑volatility—favor mean‑reversion strategies in low‑volatility and trend‑following techniques in high‑volatility regimes.
⚙️ Filter Explanations
1. DI Reversal Filter:
- Requires 3-bar confirmation when ADX >30 (reduces whipsaws).
- Default: Off (Enable for conservative trading).
2. Dynamic Thresholds:
- Adjusts OB/OS levels using volatility (e.g., expands thresholds in high ATR regimes).
- Default: Off (Enable for crypto/volatile markets).
3. Leading HTF Filter:
- Uses faster EMA crossover (9/21) instead of ADX for HTF alignment.
- Default: On (Disable for pure mean-reversion strategies).
4. Adaptive Weighting
- Automatically adjusts the influence of Trend/Momentum/Volatility/Volume based on market
conditions.
-Increases trend weight during strong ADX phases, boosts volatility weight in choppy markets,
and reduces volume weight in low-liquidity instruments.
Default: On (Disable for fixed-weight strategies).
5. Early Signal
-Detects momentum shifts before the oscillator crosses thresholds using smoothed delta
values.
- Provides advance warnings (e.g., "Early Buy" when delta >0.5 + trend alignment)
- Default: Off (Enable for aggressive entries, but requires tighter risk management)
⚠️ Disclaimer & Usage
- Timeframe : Optimized for 5M-1H (scalping) and 4H-D (swing).
- Markets : Pre-configured modes for Crypto (volatile), Stocks (trending), Forex (ranging).
- Risk : Always use stop-losses. This tool generates confluence signals , not holy grail entries.
- Backtest : Adaptive weights perform best with >100 trades for statistical significance.
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🌟 What Makes This Different?
Unlike basic oscillator mashups:
- Context-Aware: Weights adjust to volatility (e.g., lowers volume weight in forex, boosts trend weight in stocks).
- Visual Intelligence: Quantum candles turn yellow/purple when HTF + LTF signals align.
- Early-Warning: Delta smoothing detects momentum shifts before crosses (e.g., "Early Buy" flags).
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🔗 For parameter tuning, refer to the tooltip explanations next to each input.
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Note : This description intentionally avoids exaggerated claims ("100% accurate") and focuses on transparent methodology as required by TradingView guidelines.
Good luck!
BullByte
Oscylatory skupione
Institutional Composite Moving Average (ICMA) [Volume Vigilante]Institutional Composite Moving Average (ICMA)
The Next Evolution of Moving Averages — Built for Real Traders.
ICMA blends the strength of four powerful averages (SMA, EMA, WMA, HMA) into a single ultra-responsive, ultra-smooth signal.
It reacts faster than traditional MAs while filtering out noise, giving you clean trend direction with minimal lag.
🔹 Key Features:
• Faster reaction than SMA, EMA, or WMA individually
• Smoother and more stable than raw HMA
• Naturally adapts across trend, momentum, and consolidation conditions
• Zero gimmicks. Zero repainting. Full institutional quality.
🔹 Designed For:
• Scalping
• Swing trading
• Signal engines
• Algorithmic systems
📎 How to Use:
• Overlay it on any chart
• Fine-tune the length per timeframe
• Combine with your entries/exits for maximum edge
Created by Volume Vigilante 🧬 — Delivering Real-World Trading Tools.
RSI Strength & Consolidation Zones (Zeiierman)█ Overview
RSI Strength & Consolidation Zones (Zeiierman) is a hybrid momentum and volatility visualization tool that blends enhanced RSI interpretation with ADX-driven consolidation detection. This indicator doesn't just show where RSI is trending — it interprets how strong that trend is, when that strength changes, and where the market may be consolidating in anticipation of breakout movement.
Using a combination of Kalman-filtered RSI, custom-built DMI/ADX, and low-volatility zone recognition, it gives traders a dynamic RSI with strength-based coloring, while also highlighting consolidation zones to spot breakout opportunities.
█ Its uniqueness
Traditional RSI indicators lack context. They may show you when the market is overbought or oversold, but they won’t tell you how strong that condition is, or whether it’s likely to result in continuation or consolidation.
This tool aims to solve that by introducing adaptive strength metrics and structural compression zones, allowing traders to anticipate when the market is likely preparing for a move.
█ How It Works
⚪ Enhanced RSI
Combines traditional RSI and a custom RSI implementation
Smooths both through a Kalman filter for trend direction
Final RSI line reflects smoothed consensus between manual and built-in RSI
Adds an RSI + Strength overlay to show when the directional conviction is increasing
⚪ ADX-Driven Strength Layer
Directional Movement Index (DMI) is calculated both manually and with built-in smoothing
The average ADX value is used to calculate a strength modifier
When ADX exceeds 20, RSI is dynamically enhanced or dampened to reflect directional force
Resulting visual: RSI appears stronger or weaker based on confirmed trend conditions
⚪ Consolidation Zone Detection
When ADX falls below 20, the indicator enters a consolidation zone state
Boxes are drawn dynamically to contain the price within these low-volatility structures
Once the price breaks out of the zone, the indicator plots a breakout signal (▲ or ▼)
⚪ Breakouts
Breakout markers are placed at the first close outside the consolidation box
These signals serve as early indicators for potential trend continuation or reversal
█ How to Use
⚪ Confirm Momentum Strength
Use the RSI + Strength line to determine whether current momentum is backed by trend conviction. If strength expands alongside rising RSI, the move has confirmation.
⚪ Consolidations Zones
When RSI is around the midline, and a consolidation box appears, expect lower volatility and a range-bound market, followed by a breakout.
⚪ Use Breakout Signals for Entry
Look for ▲ or ▼ markers as early triggers. These often coincide with volume expansions or structural breaks.
█ Settings Explained
RSI Length – Number of bars used for RSI. Shorter = more sensitive.
DMI Length – Used in both custom and built-in ADX/DI calculations.
ADX Smoothing – Smooths the trend strength signal. Higher values = smoother strength detection.
Trend Confirmation (Filter Strength) – Adjusts the responsiveness of the Kalman filter.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pi Cycle | AlchimistOfCrypto Pi Cycle Top Indicator - A Powerful Market Phase Detector
Developed by AlchimistOfCrypto
🧪 The Pi Cycle uses mathematical harmony to identify Bitcoin market cycle tops
with remarkable precision. Just as elements react at specific temperatures,
Bitcoin price behaves predictably when these two moving averages converge! 🧬
⚗️ The formula measures when the 111-day SMA crosses below the 350-day SMA × 2,
creating a perfect alchemical reaction that has successfully identified the
major cycle tops in 2013, 2017, and 2021.
🔬 Like the Golden Ratio in nature, this indicator reveals the hidden
mathematical structure within Bitcoin's chaotic price movements.
🧮 When the reaction occurs, prepare for molecular breakdown! 🔥
Quad Rotation StochasticQuad Rotation Stochastic
The Quad Rotation Stochastic is a powerful and unique momentum oscillator that combines four different stochastic setups into one tool, providing an incredibly detailed view of market conditions. This multi-timeframe stochastic approach helps traders better anticipate trend continuations, reversals, and momentum shifts with greater precision than traditional single stochastic indicators.
Why this indicator is useful:
Multi-layered Momentum Analysis: Instead of relying on one stochastic, this script tracks four independent stochastic readings, smoothing out noise and confirming stronger signals.
Advanced Divergence Detection: It automatically identifies bullish and bearish divergences for each stochastic, helping traders spot potential reversals early.
Background Color Alerts: When a configurable number (e.g., 3 or 4) of the stochastics agree in direction and position (overbought/oversold), the background colors green (bullish) or red (bearish) to give instant visual cues.
ABCD Pattern Recognition: The script recognizes "shield" patterns when Stochastic 4 remains stuck at extreme levels (above 90 or below 10) for a set time, warning of potential trend continuation setups.
Super Signal Alerts: If all four stochastics align in extreme conditions and slope in the same direction, the indicator plots a special "Super Signal," offering high-confidence entry opportunities.
Why this indicator is unique:
Quad Confirmation Logic: Combining four different stochastics makes this tool much less prone to false signals compared to using a single stochastic.
Customizable Divergence Coloring: Traders can choose to have divergence lines automatically match the stochastic color for clear visual association.
Adaptive ABCD Shields: Innovative use of bar counting while a stochastic remains extreme acts as a "shield," offering a unique way to filter out minor fake-outs.
Flexible Configuration: Each stochastic's sensitivity, divergence settings, and visual styling can be fully customized, allowing traders to adapt it to their own strategy and asset.
Example Usage: Trading Bitcoin with Quad Rotation Stochastic
When trading Bitcoin (BTCUSD), you might set the minimum count (minCount) to 3, meaning three out of four stochastics must be in agreement to trigger a background color.
If the background turns green, and you notice an ABCD Bullish Shield (Green X), you might look for bullish candlestick patterns or moving average crossovers to enter a long trade.
Conversely, if the background turns red and a Super Down Signal appears, it suggests high probability for further downside, giving you strong confirmation to either short BTC or avoid entering new longs.
By combining divergence signals with background colors and the ABCD shields, the Quad Rotation Stochastic provides a layered confirmation system that gives traders greater confidence in their entries and exits — particularly in fast-moving, volatile markets like Bitcoin.
GER MCB V2My version of Market Cipher B. V1
Combination of oscillator, vwap, rsi all in one.
Multi-timeframe.
Dskyz Options Flow Flux (OFF) - FuturesDskyz Options Flow Flux (OFF) - Futures
*This is a repost due to moderator intervention on use of ™ in my scripts. I'm in the process of getting this rectified. This was originally posted around mid-night CDT.
🧠 The Dskyz Options Flow Flux (OFF) - Futures indicator is a game changer for futures traders looking to tap into institutional activity with limited resources. Designed for TradingView this tool simulates options flow data (call/put volume and open interest) for futures contracts like MNQ MES NQ and ES giving u actionable insights through volume spike detection volatility adjustments and stunning visuals like aurora flux bands and round number levels. Whether u’re a beginner learning the ropes or a pro hunting for an edge this indicator delivers real time market sentiment and key price levels to boost ur trading game
Key Features
⚡ Simulated Options Flow: Breaks down call/put volume and open interest using market momentum and volatility
📈 Spike Detection: Spots big moves in volume and open interest with customizable thresholds
🧠 Volatility Filter: Adapts to market conditions using ATR for smarter spike detection
✨ Aurora Flux Bands: Glows with market sentiment showing u bullish or bearish vibes at a glance
🎯 Round Number Levels: Marks key psychological levels where big players might step in
📊 Interactive Dashboard: Real time metrics like sentiment score and volatility factor right on ur chart
🚨 Alerts: Get notified of bullish or bearish spikes so u never miss a move
How It Works
🧠 This indicator is built to make complex options flow analysis simple even with the constraints of Pine Script. Here’s the step by step:
Simulated Volume Data (Dynamic Split):
Pulls daily volume for ur chosen futures contract (MNQ1! MES1! NQ1! ES1!)
Splits it into call and put volume based on momentum (ta.mom) and volatility (ATR vs its 20 period average)
Estimates open interest (OI) for calls and puts (1.15x for calls 1.1x for puts)
Formula: callRatio = 0.5 + (momentum / close) * 10 + (volatility - 1) * 0.1 capped between 0.3 and 0.7
Why It Matters: Mimics how big players might split their trades giving u a peek into institutional sentiment
Spike Detection:
Compares current volume/OI to short term (lookbackShort) and long term (lookbackLong) averages
Flags spikes when volume/OI exceeds the average by ur set threshold (spikeThreshold for regular highConfidenceThreshold for strong)
Adjusts for volatility so u’re not fooled by choppy markets
Output: optionsSignal (2 for strong bullish -2 for strong bearish 1 for bullish -1 for bearish 0 for neutral)
Why It Matters: Pinpoints where big money might be stepping in
Volatility Filter:
Uses ATR (10 periods) and its 20 period average to calculate a volatility factor (volFactor = ATR / avgAtr)
Scales spike thresholds based on market conditions (volAdjustedThreshold = spikeThreshold * max(1 volFactor * volFilter))
Why It Matters: Keeps ur signals reliable whether the market is calm or wild
Sentiment Score:
Calculates a call/put ratio (callVolume / putVolume) and adjusts for volatility
Converts it to a 0 to 100 score (higher = bullish lower = bearish)
Formula: sentimentScore = min(max((volAdjustedSentiment - 1) * 50 0) 100)
Why It Matters: Gives u a quick read on market bias
Round Number Detection:
Finds the nearest round number (e.g. 100 for MNQ1! 50 for MES1!)
Checks for volume spikes (volume > 3 period SMA * spikeThreshold) and if price is close (within ATR * atrMultiplier)
Updates the top activity level every 15 minutes when significant activity is detected
Why It Matters: Highlights psychological levels where price often reacts
Visuals and Dashboard:
Combines aurora flux bands glow effects round number lines and a dashboard to make insights pop (see Visual Elements below)
Plots triangles for call/put spikes (green/red for strong lime/orange for regular)
Sets up alerts for key market moves
Why It Matters: Makes complex data easy to read at a glance
Inputs and Customization
⚙️ Beginners can tweak these settings to match their trading style while pros can dig deeper for precision:
Futures Symbol (symbol): Pick ur contract (MNQ1! MES1! NQ1! ES1!). Default: MNQ1!
Short Lookback (lookbackShort): Days for short term averages. Smaller = more sensitive. Range: 1+. Default: 5
Long Lookback (lookbackLong): Days for long term averages. Range: 5+. Default: 10
Spike Threshold (spikeThreshold): How big a spike needs to be (e.g. 1.1 = 10% above average). Range: 1.0+. Default: 1.1
High Confidence Threshold (highConfidenceThreshold): For strong spikes (e.g. 3.0 = 3x average). Range: 2.0+. Default: 3.0
Volatility Filter (volFilter): Adjusts for market volatility (e.g. 1.2 = 20% stricter in volatile markets). Range: 1.0+. Default: 1.2
Aurora Flux Transparency (glowOpacity): Controls band transparency (0 = solid 100 = invisible). Range: 0 to 100. Default: 65
Show Show OFF Dashboard (showDashboard): Toggles the dashboard with key metrics. Default: true
Show Nearest Round Number (showRoundNumbers): Displays round number levels. Default: true
ATR Multiplier for Proximity (atrMultiplier): How close price needs to be to a round number (e.g. 1.5 = within 1.5x ATR). Range: 0.5+. Default: 1.5
Functions and Logic
🧠 Here’s the techy stuff pros will love:
Simulated Volume Data : Splits daily volume into call/put volume and OI using momentum and volatility
Volatility Filter: Scales thresholds with volFactor = atr / avgAtr for adaptive detection
Spike Detection: Flags spikes and assigns optionsSignal (2, -2, 1, -1, 0) for sentiment
Sentiment Score: Converts call/put ratio into a 0-100 score for quick bias reads
Round Number Detection: Identifies key levels and significant activity for trading zones
Dashboard Display: Updates real time metrics like sentiment score and volatility factor
Visual Elements
✨ These visuals make data come alive:
Gradient Background: Green (bullish) red (bearish) or yellow (neutral/choppy) at 95% transparency to show trend
Aurora Flux Bands: Stepped bands (linewidth 3) around a 14 period EMA ± ATR * 1.8. Colors shift with sentiment (green red lime orange gray) with glow effects at 85% transparency
Round Number Visualization: Stepped lines (linewidth 2) at key levels (solid if active dashed if not) with labels (black background white text size.normal)
Visual Signals: Triangles above/below bars for spikes (size.small for strong size.tiny for regular)
Dashboard: Bottom left table (2 columns 10 rows) with a black background (29% transparency) gray border and metrics:
⚡ Round Number Activity: “Detected” or “None”
📈 Trend: “Bullish” “Bearish” or “Neutral” (colored green/red/gray)
🧠 ATR: Current 10 period ATR
📊 ATR Avg: 20 period SMA of ATR
📉 Volume Spike: “YES” (green) or “NO” (red)
📋 Call/Put Ratio: Current ratio
✨ Flux Signal: “Strong Bullish” “Strong Bearish” “Bullish” “Bearish” or “Neutral” (colored green/red/gray)
⚙️ Volatility Factor: Current volFactor
📈 Sentiment Score: 0-100 score
Usage and Strategy Recommendations
🎯 For Beginners: Use high confidence spikes (green/red triangles) for easy entries. Check the dashboard for a quick market read (sentiment score above 60 = bullish below 40 = bearish). Watch round number levels for support/resistance
💡 For Pros: Combine flux signals with round number activity for high probability setups. Adjust lookbackShort/lookbackLong for trending vs choppy markets. Use volFactor for position sizing (higher = smaller positions)
cabreras Dynamic TRIX Heatmap OscillatorKey Features
TRIX Calculation
Computes three successive EMAs of your chosen source (default: close) over a user-configurable length
Expresses momentum as the percent change from one bar to the next
Heatmap Coloring
Automatically blends between three colors (weak, neutral, strong) based on how far TRIX sits within your defined range
“Weak” zone (low momentum), “neutral” midpoint, “strong” zone (high momentum)
Fully customizable color inputs and thresholds
Reference Lines
Zero Line: quickly see bullish vs. bearish momentum
High/Low Bands: optional overbought/oversold or custom momentum limits
Flexible Inputs
Source (e.g. close, hlc3, typical) and TRIX Length
Color Inputs for all three momentum zones
Normalization Range (minTRIX / maxTRIX) to match expected volatility
Neutral Threshold (midPointLevel) to split “weak” vs. “strong”
High/Low Line Levels and toggles for all reference lines
How to Use
Add to Chart
Paste the script into TradingView’s Pine Editor (v6) and hit “Add to Chart.”
Customize Ranges
Match minTRIX/maxTRIX to the typical swing of your market (e.g. ±0.05) so you see full red→yellow→green gradients.
Set Color Zones
Pick distinct “weak,” “neutral,” and “strong” colors for clear visual contrast.
Interpret
Green bars = accelerating bullish momentum
Red bars = strong bearish momentum
Yellow bars = indecision or transition
Use Reference Lines
Reset midPointLevel to shift neutrality, or add high/low bands to highlight extreme momentum conditions and trigger alerts.
With its intuitive color-blending and flexible thresholds, this oscillator makes it easy to spot momentum build-ups, exhaustion phases, and cross-threshold reversals—all at a single glance.
MACD DualScope※日本語説明もあります。
📌 MACD DualScope – Fusion of Higher & Lower Timeframes
MACD DualScope is a multi-timeframe visualization tool that combines the power of two MACD readings in one view.
The background color reflects the trend direction of the higher timeframe MACD, while the indicator window shows the MACD of the current chart timeframe.
✅ Key Features
Visual background showing higher timeframe MACD direction (Green = Bullish, Red = Bearish)
Full MACD (MACD line, Signal line, Histogram) display for the lower/current timeframe
Separate parameter settings for higher and lower timeframes
Customizable higher timeframe (e.g., 1H, 4H, D, etc.)
Adjustable background transparency
Perfect for traders who want to capture the broader trend while timing precise entries on lower timeframes.
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📌 MACD DualScope - 上位足 × 下位足の融合ビジョン
MACD DualScopeは、異なる時間軸のMACDを同時に視覚化するインジケーターです。
背景には上位足のMACDの方向性をカラーで表示し、インジケーターウィンドウには現在の足（下位足）のMACDを表示します。
✅ 主な機能
上位足のMACD方向を背景色で表示（上昇：緑 / 下降：赤）
下位足のMACD、シグナル、ヒストグラムをチャートで視覚化
上位・下位それぞれでMACDのパラメーターを個別設定可能
上位足の時間足を自由に選択可能（例：1H, 4H, Dなど）
背景の透明度もカスタマイズ可能
トレンドの大きな流れと短期の変化を同時に捉えたいトレーダーにおすすめのツールです！
Scalping Súper Oscilador by Rouro [Actualizado]This scalping strategy is designed to detect overbought and oversold zones using a custom Super Oscillator that combines five classic indicators: RSI, Stochastic, CCI, ROC, and Williams %R, with adjustable thresholds.
⚙️ How does it work? Entry signal: Buy: when the oscillator rises from the oversold zone (-0.8) and the candlestick is bullish. Sell: when the oscillator goes down from the overbought zone (0.8) and the candlestick is bearish. Time filter: possibility to operate only in a configurable time slot (e.g. from 10:00 to 12:00 local time). Dynamic SL/TP: Stop Loss is calculated using the low/high of the last X candles, and the Take Profit according to a configurable Risk/Reward Ratio. One operation per signal, with no overlaps.
🧠 Visuals and Panels: Visual oscillator with smooth EMA. Indicator traffic light that shows the individual status (green, red or grey) on the screen. Real-time statistics table: Backtest start date.
🧩 Full customization:
Periods and levels for each indicator.
Oscillator top/bottom level.
Schedule settings.
Option to show or hide the oscillator baseline.
Matinator 2min -v2.1ATR with ZLSMA exit
Uses ATR reversal for trends and ZLSMA for exit and filtering
Express Generator StrategyExpress Generator Strategy
Pine Script™ v6
The Express Generator Strategy is an algorithmic trading system that harnesses confluence from multiple technical indicators to optimize trade entries and dynamic risk management. Developed in Pine Script v6, it is designed to operate within a user-defined backtesting period—ensuring that trades are executed only during chosen historical windows for targeted analysis.
How It Works:
- Entry Conditions:
The strategy relies on a dual confirmation approach:- A moving average crossover system where a fast (default 9-period SMA) crossing above or below a slower (default 21-period SMA) average signals a potential trend reversal.
- MACD confirmation; trades are only initiated when the MACD line crosses its signal line in the direction of the moving average signal.
- An RSI filter refines these signals by preventing entries when the market might be overextended—ensuring that long entries only occur when the RSI is below an overbought level (default 70) and short entries when above an oversold level (default 30).
- Risk Management & Dynamic Position Sizing:
The strategy takes a calculated approach to risk by enabling the adjustment of position sizes using:- A pre-defined percentage of equity risk per trade (default 1%, adjustable between 0.5% to 3%).
- A stop-loss set in pips (default 100 pips, with customizable ranges), which is then adjusted by market volatility measured through the ATR.
- Trailing stops (default 50 pips) to help protect profits as the market moves favorably.
This combination of volatility-adjusted risk and equity-based position sizing aims to harmonize trade exposure with prevailing market conditions.
- Backtest Period Flexibility:
Users can define the start and end dates for backtesting (e.g., January 1, 2020 to December 31, 2025). This ensures that the strategy only opens trades within the intended analysis window. Moreover, if the strategy is still holding a position outside this period, it automatically closes all trades to prevent unwanted exposure.
- Visual Insights:
For clarity, the strategy plots the fast (blue) and slow (red) moving averages directly on the chart, allowing for visual confirmation of crossovers and trend shifts.
By integrating multiple technical indicators with robust risk management and adaptable position sizing, the Express Generator Strategy provides a comprehensive framework for capturing trending moves while prudently managing downside risk. It’s ideally suited for traders looking to combine systematic entries with a disciplined and dynamic risk approach.
Clenow MomentumClenow Momentum Method
The Clenow Momentum Method, developed by Andreas Clenow, is a systematic, quantitative trading strategy focused on capturing medium- to long-term price trends in financial markets. Popularized through Clenow’s book, Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies, the method leverages momentum—an empirically observed phenomenon where assets that have performed well in the recent past tend to continue performing well in the near future.
Theoretical Foundation
Momentum investing is grounded in behavioral finance and market inefficiencies. Investors often exhibit herding behavior, underreact to new information, or chase trends, causing prices to trend beyond fundamental values. Clenow’s method builds on academic research, such as Jegadeesh and Titman (1993), which demonstrated that stocks with high returns over 3–12 months outperform those with low returns over similar periods.
Clenow’s approach specifically uses **annualized momentum**, calculated as the rate of return over a lookback period (typically 90 days), annualized to reflect a yearly percentage. The formula is:
Momentum=(((Close N periods agoCurrent Close)^N252)−1)×100
- Current Close: The most recent closing price.
- Close N periods ago: The closing price N periods back (e.g., 90 days).
- N: Lookback period (commonly 90 days).
- 252: Approximate trading days in a year for annualization.
This metric ranks stocks by their momentum, prioritizing those with the strongest upward trends. Clenow’s method also incorporates risk management, diversification, and volatility adjustments to enhance robustness.
Methodology
The Clenow Momentum Method involves the following steps:
1. Universe Selection:
- A broad universe of liquid stocks is chosen, often from major indices (e.g., S&P 500, Nasdaq 100) or global exchanges.
- Filters should exclude illiquid stocks (e.g., low average daily volume) or those with extreme volatility.
2. Momentum Calculation:
- Stocks are ranked based on their annualized momentum over a lookback period (typically 90 days, though 60–120 days can be common tests).
- The top-ranked stocks (e.g., top 10–20%) are selected for the portfolio.
3. Volatility Adjustment (Optional):
- Clenow sometimes adjusts momentum scores by volatility (e.g., dividing by the standard deviation of returns) to favor stocks with smoother trends.
- This reduces exposure to erratic price movements.
4. Portfolio Construction:
- A diversified portfolio of 10–25 stocks is constructed, with equal or volatility-weighted allocations.
- Position sizes are often adjusted based on risk (e.g., 1% of capital per position).
5. Rebalancing:
- The portfolio is rebalanced periodically (e.g., weekly or monthly) to maintain exposure to high-momentum stocks.
- Stocks falling below a momentum threshold are replaced with higher-ranked candidates.
6. Risk Management:
- Stop-losses or trailing stops may be applied to limit downside risk.
- Diversification across sectors reduces concentration risk.
Implementation in TradingView
Key features include:
- Customizable Lookback: Users can adjust the lookback period in pinescript (e.g., 90 days) to align with Clenow’s methodology.
- Visual Cues: Background colors (green for positive, red for negative momentum) and a zero line help identify trend strength.
- Integration with Screeners: TradingView’s stock screener can filter high-momentum stocks, which can then be analyzed with the custom indicator.
Strengths
1. Simplicity: The method is straightforward, relying on a single metric (momentum) that’s easy to calculate and interpret.
2. Empirical Support: Backed by decades of academic research and real-world hedge fund performance.
3. Adaptability: Applicable to stocks, ETFs, or other asset classes, with flexible lookback periods.
4. Risk Management: Diversification and periodic rebalancing reduce idiosyncratic risk.
5. TradingView Integration: Pine Script implementation enables real-time visualization, enhancing decision-making for stocks like NVDA or SPY.
Limitations
1. Mean Reversion Risk: Momentum can reverse sharply in bear markets or during sector rotations, leading to drawdowns.
2. Transaction Costs: Frequent rebalancing increases trading costs, especially for retail traders with high commissions. This is not as prevalent with commission free trading becoming more available.
3. Overfitting Risk: Over-optimizing lookback periods or filters can reduce out-of-sample performance.
4. Market Conditions: Underperforms in low-momentum or highly volatile markets.
Practical Applications
The Clenow Momentum Method is ideal for:
Retail Traders: Use TradingView’s screener to identify high-momentum stocks, then apply the Pine Script indicator to confirm trends.
Portfolio Managers: Build diversified momentum portfolios, rebalancing monthly to capture trends.
Swing Traders: Combine with volume filters to target short-term breakouts in high-momentum stocks.
Cross-Platform Workflow: Integrate with Python scanners to rank stocks, then visualize on TradingView for trade execution.
Comparison to Other Strategies
Vs. Minervini’s VCP: Clenow’s method is purely quantitative, while Minervini’s Volatility Contraction Pattern (your April 11, 2025 query) combines momentum with chart patterns. Clenow is more systematic but less discretionary.
Vs. Mean Reversion: Momentum bets on trend continuation, unlike mean reversion strategies that target oversold conditions.
Vs. Value Investing: Momentum outperforms in bull markets but may lag value strategies in recovery phases.
Conclusion
The Clenow Momentum Method is a robust, evidence-based strategy that capitalizes on price trends while managing risk through diversification and rebalancing. Its simplicity and adaptability make it accessible to retail traders, especially when implemented on platforms like TradingView with custom Pine Script indicators. Traders must be mindful of transaction costs, mean reversion risks, and market conditions. By combining Clenow’s momentum with volume filters and alerts, you can optimize its application for swing or position trading.
StochRSI+ LiteStochRSI+ Lite is an enhanced version of the classic Stochastic RSI.
It includes:
✅ Adaptive smoothing using ATR
✅ EMA-based trend filter to reduce false signals
✅ RSI calculated on HLC3 for smoother response
✅ Transparent 20–80 range highlight
✅ Basic divergence detection with visual markers
Ideal for crypto and volatile markets.
Open source & free to use — if you like it, tips are appreciated 🙏
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RSI and MA Band📊 RSI with Gradient Fill
🔧 Features:
1) Two Customizable RSIs
-RSI1 (default length: 5)
-RSI2 (default length: 21)
Both are calculated separately and displayed in black.
2) Dynamic Gradient Fill between RSI1-RSI2 and MA1-MA2
Helps visually identify divergence and convergence behavior between the RSIs.
3) Overbought and Oversold Zones with Visual Gradients
✅ Classic Zones:
-Overbought above 70
-Oversold below 30
✅ Extended Zones:
-Extreme Overbought above 85
-Extreme Oversold below 15
Horizontal Support/Resistance Lines for RSI
Lines at 15, 30, 50, 70, and 85 clearly mark RSI ranges.
4) Moving Averages on RSI:
Ability to enable two MAs on RSI1 and RSI2:
-Selectable type (SMA, EMA, SMMA, WMA, VWMA)
-Customizable lengths
-Displayed in yellow.
5) Fill Between MAs
Highlights divergence or alignment between moving averages applied to RSI.
6) Crossover Detection with Visual Indicators
🟣 Purple triangles when RSI1 crosses RSI2.
🟢 Green triangles when MA1 crosses MA2.
-------------------------------------------- --------------------------------------------
1) Identifying Trend Strength or Potential Reversals
2) Crossovers between RSI1 and RSI2 may indicate short-term momentum shifts.
3) Gradient fills help easily visualize significant divergences.
4) Entry/Exit SL and TP Signals
5) Overbought/Oversold zones (especially extended ones) offer early signals for possible reversals or sideways phases.
6) Momentum Filtering with Moving Averages
7) Smooths out RSI "noise" and reveals more sustained RSI trends.
8) MA crossovers provide stronger confirmation of momentum.
9) Dual RSIs + gradients + colored zones allow for quick market state interpretation at a glance, without visual clutter.
-----🌟 Extremely intuitive and trader-friendly visual representation — built for quick decisions without sacrificing depth.-----
Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
SMT SwiftEdge PowerhouseSMT SwiftEdge Powerhouse: Precision Trading with Divergence, Liquidity Grabs, and OTE Zones
The SMT SwiftEdge Powerhouse is a powerful trading tool designed to help traders identify high-probability entry points during the most active market sessions—London and New York. By combining Smart Money Technique (SMT) Divergence, Liquidity Grabs, and Optimal Trade Entry (OTE) Zones, this script provides a unique and cohesive strategy for capturing market reversals with precision. Whether you're a scalper or a swing trader, this indicator offers clear visual signals to enhance your trading decisions on any timeframe.
What Does This Script Do?
This script integrates three key concepts to identify potential trading opportunities:
SMT Divergence:
SMT Divergence compares the price action of two correlated assets (e.g., Nasdaq and S&P 500 futures) to detect hidden market reversals. When one asset makes a higher high while the other makes a lower high (bearish divergence), or one makes a lower low while the other makes a higher low (bullish divergence), it signals a potential reversal. This technique leverages institutional "smart money" behavior to anticipate market shifts.
Liquidity Grabs:
Liquidity Grabs occur when price breaks above recent highs or below recent lows on higher timeframes (5m and 15m), often triggering stop-loss orders from retail traders. These breakouts are identified using pivot points and confirm institutional activity, setting the stage for a reversal. The script focuses on liquidity grabs during the London and New York sessions for maximum market activity.
Optimal Trade Entry (OTE) Zones:
OTE Zones are Fibonacci-based retracement areas (e.g., 61.8%) calculated after a liquidity grab. These zones highlight where price is likely to retrace before continuing in the direction of the reversal, offering a high-probability entry point. The script adjusts the width of these zones using the Average True Range (ATR) to adapt to market volatility.
By combining these components, the script identifies when institutional activity (liquidity grabs) aligns with market reversals (SMT divergence) and pinpoints precise entry points (OTE zones) during high-liquidity sessions.
Why Combine These Components?
The integration of SMT Divergence, Liquidity Grabs, and OTE Zones creates a robust trading system for several reasons:
Synergy of Institutional Signals: SMT Divergence and Liquidity Grabs both reflect "smart money" behavior—divergence shows hidden reversals, while liquidity grabs confirm institutional intent to trap retail traders. Together, they provide a strong foundation for identifying high-probability setups.
Session-Based Precision: Focusing on the London and New York sessions ensures signals occur during periods of high volatility and liquidity, increasing their reliability.
Precision Entries with OTE: After confirming a setup with divergence and liquidity grabs, OTE zones provide a clear entry area, reducing guesswork and improving trade accuracy.
Adaptability: The script works on any timeframe, with adjustable settings for signal sensitivity, session times, and Fibonacci levels, making it versatile for different trading styles.
This combination makes the script unique by aligning institutional insights with actionable entry points, tailored to the most active market hours.
How to Use the Script
Setup:
Add the script to your chart (works on any timeframe, e.g., 1m, 5m, 15m).
Configure the settings in the indicator's inputs:
Session Settings: Adjust the start/end times for London and New York sessions (default: London 8-11 UTC, New York 13-16 UTC). You can disable session restrictions if desired.
Asset Settings: Set the primary and secondary assets for SMT Divergence (default: NQ1! and ES1!). Ensure the assets are correlated.
Signal Settings: Adjust the lookback period, ATR period, and signal sensitivity (Low/Medium/High) to control the frequency of signals.
OTE Settings: Choose the Fibonacci level for OTE zones (default: 61.8%).
Visual Settings: Enable/disable OTE zones, SMT labels, and debug labels for troubleshooting.
Interpreting Signals:
Blue Circles: Indicate a liquidity grab (price breaking a 5m or 15m pivot high/low), marking the start of a potential setup.
Blue OTE Zones: Appear after a liquidity grab, showing the retracement area (e.g., 61.8% Fibonacci level) where price is likely to enter for a reversal trade. The label "OTE Trigger 5m/15m" confirms the direction (Short/Long) and session.
Green/Red Entry Boxes: Mark precise entry points when price enters the OTE zone and confirms the SMT Divergence. Green boxes indicate a long entry, red boxes a short entry.
Trading Example:
On a 1m chart, a blue circle appears when price breaks a 5m pivot high during the London session.
A blue OTE zone forms, showing a retracement area (e.g., 61.8% Fibonacci level) with the label "OTE Trigger 5m/15m (Short, London)".
Price retraces into the OTE zone, and a red "Short Entry" box appears, confirming a bearish SMT Divergence.
Enter a short trade at the red box, with a stop-loss above the OTE zone and a take-profit at the next support level.
Originality and Utility
The SMT SwiftEdge Powerhouse stands out by merging SMT Divergence, Liquidity Grabs, and OTE Zones into a single, session-focused indicator. Unlike traditional indicators that focus on one aspect of price action, this script combines institutional reversal signals with precise entry zones, tailored to the most active market hours. Its adaptability across timeframes, customizable settings, and clear visual cues make it a versatile tool for traders seeking to capitalize on smart money movements with confidence.
Tips for Best Results
Use on correlated assets like NQ1! (Nasdaq futures) and ES1! (S&P 500 futures) for accurate SMT Divergence.
Test on lower timeframes (1m, 5m) for scalping or higher timeframes (15m, 1H) for swing trading.
Adjust the "Signal Sensitivity" to "High" for more signals or "Low" for fewer, high-quality setups.
Enable "Show Debug Labels" if signals are not appearing as expected, to troubleshoot pivot points and liquidity grabs.
Custom IndicatorThis indicator indicated the 10 EMA and 20 EMA
When Ema 20 Goes Over My 10 Sell When Ema 10 Goes Below 20 Buy
Smart Multi-Signal Indicator1. 200 EMA – Filters trades by trend (only buys above EMA, sells below).
2. RSI (14) – Spots overbought/oversold momentum for reversal opportunities.
3. Volume Spike – Confirms strong interest by checking if volume is 1.5× above average.
4. Impulse Candle – Looks for strong price moves (body > 1.5% of price).
When all these conditions align, it plots a BUY or SELL label directly on the chart.
MG Thrust Indicator🚀 Explanation 🚀
The MG thrust indicator uses thrust momentum in price with some smoothing to detect uptrend and downtrend shifts.
✨ Key Features ✨
🗡smoothing_length (default: 37): length for smoothing price and thrust values (EMA or SMA).
🗡thrust_threshold (default: 1.5): multiples of ATR to identify significant thrusts.
🗡use_ema (default: true): toggle between EMA (faster response) and SMA (smoother) for smoothing.
🗡lookback_atr (default: 14): lookback period for ATR to normalize thrust.
📈 Thrust Calculation 📈
Thrust = (close - smoothed_price) / atr: measures how far the current price deviates from the smoothed price, normalized by ATR to account for volatility.
Background Highlights: colors the background faintly green/red for bullish/bearish thrusts.
❓ Seeing a bug or an issue ❓
Feel free to DM me if you see a component that seems badly calculated.
I will be happy to fix it.
❗❗ Disclaimer ❗❗
This is a single indicator, even though it's aggregating many, do not use it as a standalone.
Past performance is not indicative of future results.
Always backtest, check, and align parameters before live trading.
MACD & Stochastic AlertThis code detects if the following combination has occured in the chart
if MACD has crossed over MACD Signal in the last 4 candles
and
whether the Fast Stochastic K% has exited the channel 80 & 23
Then you can set an alert based on the function call.
Volume-Price Momentum IndicatorVolume-Price Momentum Indicator (VPMI)
Overview
The Volume-Price Momentum Indicator (VPMI), developed by Kevin Svenson , is a powerful technical analysis tool designed to identify strong bullish and bearish momentum in price movements, driven by volume dynamics. By analyzing price changes and volume surges over a user-defined lookback period, VPMI highlights potential trend shifts and continuation patterns through a smoothed histogram, optional labels, and background highlights. Ideal for traders seeking to capture momentum-driven opportunities, VPMI is suitable for various markets, including stocks, forex, and cryptocurrencies.
How It Works
VPMI calculates the difference between volume-weighted buying and selling pressure based on price changes over a specified lookback period. It amplifies signals during high-volume periods, applies smoothing to reduce noise, and uses momentum checks to detect sustained trends.
Indicator display:
A histogram that oscillates above (bullish) or below (bearish) a zero line, with brighter colors indicating stronger momentum and faded colors for weaker signals.
Optional labels ("Bullish" or "Bearish") to mark significant momentum shifts.
Optional background highlights to visually emphasize strong trend conditions.
Alerts to notify users when strong bullish or bearish momentum is detected.
Key Features
Customizable Settings:
Adjust the lookback period, volume threshold, momentum length, and smoothing to suit your trading style.
Volume Sensitivity:
Emphasizes price movements during high-volume surges, enhancing signal reliability.
Momentum Detection: Uses linear regression and momentum change to confirm sustained trends, reducing false signals.
Visual Clarity:
Offers a clear histogram with color-coded signals, plus optional labels and backgrounds for enhanced chart readability.
Alerts:
Configurable alerts for strong momentum signals, enabling timely trade decisions.
Inputs and Customization
Lookback Period (Default: 9):
Sets the number of bars to analyze price changes. Higher values smooth signals but may lag.
Volume Threshold (Default: 1.4):
Defines the volume level (relative to a 20-period SMA) that qualifies as a surge, amplifying signals.
High Volume Multiplier (Default: 1.5):
Boosts histogram values during high-volume periods for stronger signals.
Histogram Smoothing Length (Default: 4):
Controls the EMA smoothing applied to the histogram, reducing noise.
Momentum Check Length (Default: 4):
Sets the period for momentum trend analysis (recommended to be less than Lookback Period).
Momentum Threshold (Default: 6):
Defines the minimum momentum change required for strong signals.
Show Labels (Default: Off):
Toggle to display "Bullish" or "Bearish" labels on significant momentum shifts.
Show Backgrounds (Default: Off):
Toggle to highlight chart backgrounds during strong momentum periods.
Bullish/Bearish Colors:
Customize colors for bullish (default: green) and bearish (default: red) signals.
Faded Transparency (Default: 40):
Adjusts the transparency of weaker signals for visual distinction.
How to Use
Interpret Signals:
Above Zero (Green):
Indicates bullish momentum. Bright green suggests strong, sustained buying pressure.
Below Zero (Red):
Indicates bearish momentum. Bright red suggests strong, sustained selling pressure.
Faded Colors:
Weaker momentum, potentially signaling consolidation or trend exhaustion.
Enable Visuals:
Turn on "Show Labels" and "Show Backgrounds" in the settings for additional context on strong momentum signals.
Set Alerts:
Use the built-in alert conditions ("Strong Bullish Momentum" or "Strong Bearish Momentum") to receive notifications when significant trends emerge.
Combine with Other Tools:
Pair VPMI with support/resistance levels, trendlines, or other indicators (e.g., RSI, MACD) for confirmation.
Best Practices
Timeframe:
VPMI works on all timeframes, but shorter timeframes (e.g., 5m, 15m) may produce more signals, while longer timeframes (e.g., 1h, 4h, 1D) offer higher reliability.
Market Conditions:
Most effective in trending markets. In choppy or sideways markets, consider increasing the smoothing length or momentum threshold to filter noise.
Risk Management:
Always use VPMI signals in conjunction with a robust trading plan, including stop-losses and position sizing.
Limitations
Lagging Nature:
As a momentum indicator, VPMI may lag in fast-moving markets due to smoothing and lookback calculations.
False Signals:
In low-volume or ranging markets, signals may be less reliable. Adjust the volume threshold or momentum settings to improve accuracy.
Customization Required:
Optimal settings vary by asset and timeframe. Experiment with inputs to align with your trading strategy.
Why Use VPMI?
VPMI offers a unique blend of volume and price momentum analysis, making it a versatile tool for traders seeking to identify high-probability trend opportunities. Its customizable inputs, clear visuals, and alert capabilities empower users to tailor the indicator to their needs, whether for day trading, swing trading, or long-term analysis.
Get Started
Apply VPMI to your chart, tweak the settings to match your trading style, and start exploring momentum-driven opportunities. For questions or feedback, consult TradingView’s community forums or documentation. Happy trading!
Momentum Table - Felipe📊 Momentum Table – By Felipe
This multi-timeframe momentum dashboard displays a clean and color-coded overview of key trend and momentum indicators across 6 major timeframes (5m to 1W), directly on your chart. It’s ideal for quickly identifying market strength, trend alignment, and potential reversals at a glance.
🔍 Features:
EMA Trend Check (EMA 9, 20, 100, 200):
Compares the current close against each EMA.
✅ Green check = price is above the EMA (bullish bias).
🔻 Red arrow = price is below the EMA (bearish bias).
Visual trend alignment helps you spot strong directional setups.
RSI (Relative Strength Index):
Displays current RSI (14) value per timeframe.
Background color highlights momentum conditions:
🔴 Red = Overbought (>70)
🟢 Green = Oversold (<30)
⚪ Gray = Neutral
Stochastic RSI:
Uses Stoch RSI applied to RSI (14) for sensitivity.
Background color follows the same logic as RSI for quick visual cues.
Compact Visual Table:
Located in the bottom-right corner.
Clean design with headers and rows labeled by timeframe.
Helps traders monitor trend and momentum confluence across multiple timeframes in real time.
This tool supports momentum-based strategies, EMA stacking confirmation, and multi-timeframe alignment, making it ideal for scalpers, swing traders, and trend followers alike.
