MO and Stoch GOLD H4 V1 – Kim TradingMO and Stoch GOLD H4 V1 – Kim Trading
Slogan: “Trading Is a Profession, Trading Is Life”
Market: XAUUSD (spot gold) • Timeframe: H4 (4 hours)
Entry/Exit Rules
When a B, B1★ … (buy) or S, S1★ … (sell) signal appears, first reference the prevailing trend and consider applying DCA in the direction of that trend. In addition, combine with other methods to build the most optimal setup.
Signal Confidence Tiers
B — S
B1★ — S1★
B2★ — S2★
B3★ — S3★
Enter trades only when one of the four signal types above is printed.
Author: Kim Trading • Version: V1 • Date: 2025-08-22
#XAUUSD #Gold #H4 #MO #Stoch #KimTrading
M-oscillator
MO and Stoch GOLD H4 – Kim Trading MO and Stoch GOLD H4 V1 – Kim Trading
Slogan: “Trading Is a Profession, Trading Is Life”
Market: XAUUSD (spot gold) • Timeframe: H4 (4 hours)
Entry/Exit Rules
When a B, B1★ … (buy) or S, S1★ … (sell) signal appears, first reference the prevailing trend and consider applying DCA in the direction of that trend. In addition, combine with other methods to build the most optimal setup.
Signal Confidence Tiers
B — S
B1★ — S1★
B2★ — S2★
B3★ — S3★
Enter trades only when one of the four signal types above is printed.
Author: Kim Trading • Version: V1 • Date: 2025-08-22
#XAUUSD #Gold #H4 #MO #Stoch #KimTrading
FUMO 200 MagnetWhat it does
FUMO Magnet measures how far price has stretched away from its long-term “magnet” — a blended EMA/SMA moving average (200 by default).
It plots a logarithmic deviation (optionally normalized) as an oscillator around zero.
Above 0** → price is above the magnet (stretched up)
Below 0** → price is below the magnet (stretched down)
Guide levels** highlight potential overbought/oversold zones
---
Why log deviation?
Log returns make extremes comparable across cycles and compress exponential trends — especially useful for BTC and other crypto assets.
Normalization modes further adjust the scale, keeping the oscillator readable on any chart.
---
Inputs
**Base**
* Source (default: Close)
* Base Length (default: 200 EMA/SMA)
* EMA vs SMA weight (%) — 0% = pure SMA, 100% = pure EMA, 50% = blended
* EMA smoothing of deviation — acts as a noise filter
**Normalization**
* None (Log Deviation) — raw log stretch in % terms
* Z-score — deviation in standard deviations (σ)
* Robust Z (MAD) — deviation vs median absolute deviation, resistant to outliers
* Tanh squash — smooth nonlinear squash of extremes for compact scale
* Normalization window (for Z / MAD)
* Tanh scale (lower = stronger squash)
* Clamp after normalization — hard cap at ±X
**Levels**
* Guide levels (Upper / Lower) — visual thresholds (default ±12)
* Zero line toggle
---
### How to read it
* **Trend bias**: sustained time above 0 = uptrend, below 0 = downtrend
* **Stretch / mean reversion**: the farther from 0, the higher the reversion risk
* **Cross-checks**: combine with structure (HH/HL, LH/LL), volume, or momentum (RSI, MACD)
---
### Recommended settings by timeframe
**Long-term (1D / 1W)**
* Normalization: None (Log Deviation)
* Base Length: 200
* EMA vs SMA weight: 50% (adjust 35–65% for faster/slower magnet)
* Deviation smoothing: 20 (10–30 range)
* Guide levels: ±12 to ±20
* Use case: cycle extremes, portfolio rebalancing, trim/add logic
**Swing (4H – 1D)**
* Normalization: Z-score
* Window: 200 (100–250)
* Smoothing: 14–20
* Guide levels: ±2σ to ±3σ
* Use case: stretched conditions across regimes; ±3σ is rare, often mean-reverts
**Intraday / Active swing (1H – 4H)**
* Normalization: Robust Z (MAD)
* Window: 200 (150 for faster response)
* Smoothing: 10–16
* Guide levels: ±3 to ±4 (robust units)
* Use case: handles spikes better than σ, fewer false overbought/oversold signals
**Scalping / Universal readability (15m – 1H)**
* Normalization: Tanh squash
* Tanh scale: 6–10 (start with 8)
* Smoothing: 8–12
* Guide levels: ±8 to ±12
* Use case: compact panel across assets and timeframes; not % or σ, but visually consistent
---
### Optional
* Clamp: enable ±20 (or ±25) for strict bounded range (useful for public charts)
---
### Quick setups
**BTC Daily (“cycle view”)**
* Normalization: None
* Blend: 50%
* Smooth: 20
* Levels: ±12–15
**BTC 4H (“swing”)**
* Normalization: Z-score
* Window: 200
* Smooth: 16
* Levels: ±2.5σ to ±3σ
**Alts 1H (“volatile”)**
* Normalization: Robust Z (MAD)
* Window: 200
* Smooth: 12
* Levels: ±3.5 to ±4.5
**Mixed assets 15m (“compact panel”)**
* Normalization: Tanh squash
* Scale: 8
* Smooth: 10
* Levels: ±8–12
* Clamp: ±20
MagnetOsc Turbo by ninZa.coMagnetOsc Turbo - Multi-timeframe momentum analysis
Unlike conventional oscillators, MagnetOsc Turbo analyzes momentum on two independent timeframes simultaneously (e.g., 100-tick & 5-minute).
Why it matters: Momentum alignment across timeframes is a key signal of trend strength or turning points.
Sniper-2025 Sniper-2025 Indicator Explanation
Overview
The Sniper-2025 indicator is a versatile technical analysis tool designed for TradingView, combining a Hyper Wave oscillator, Smart Money Flow analysis, divergence detection, reversal signals, confluence visualization, and a machine learning-based k-Nearest Neighbors (k-NN) prediction model. It provides traders with actionable buy and sell signals, trend insights, and confluence indicators to enhance decision-making across various trading strategies. The indicator is highly customizable, allowing users to adjust sensitivity, colors, and display options to suit their preferences.
Key Features
1. Hyper Wave Oscillator: A normalized oscillator based on price data, smoothed with either a Simple Moving Average (SMA) or Exponential Moving Average (EMA), highlighting momentum and potential reversal points.
2. Smart Money Flow: Tracks bullish and bearish money flow using a smoothed Money Flow Index (MFI), providing insights into market strength and direction.
3. Divergence Detection: Identifies bullish and bearish divergences between price and the oscillator, with optional labels displaying price levels.
4. Reversal Signals: Detects major and minor reversal conditions based on volume, oscillator values, and RSI, visualized as triangles and circles on the chart.
5. Confluence Meter and Areas: Visualizes alignment between the oscillator and MFI, indicating bullish or bearish confluence with customizable colors and shaded areas.
6. Signal and Divergence Labels: Displays labels for key oscillator levels (e.g., Z-Buy, Z-V-Sell) and money flow conditions (e.g., C-Buy, T-Sell) with customizable visibility and sizes.
7. Trend and Control Table: Shows the current trend (Bullish/Bearish) and control (Bull/Bear) in a customizable table positioned on the chart.
8. k-NN Prediction: Uses a k-Nearest Neighbors algorithm to predict price movement direction based on RSI indicators, with adjustable prediction sensitivity.
9. Gradient Fills and Alerts: Visualizes overbought and oversold zones with gradient fills and provides alert conditions for key crossovers and crossunders.
How It Works
- Hyper Wave Oscillator: The oscillator is calculated by normalizing the close price relative to the highest, lowest, and average prices over a user-defined length (default: 15). It is smoothed using SMA or EMA (default: SMA, length 3) to generate a signal line. Crossovers and crossunders of the oscillator and signal line are plotted as circles, indicating potential buy or sell signals.
- Smart Money Flow: The MFI is calculated over a user-defined length (default: 10) and smoothed (default: 6). It tracks bullish (positive) or bearish (negative) money flow, with colors changing based on direction (blue for bullish, red for bearish). The indicator compares current MFI to its historical average to identify strong trends.
- Divergence Detection: The script identifies divergences by comparing oscillator peaks/troughs with price highs/lows. Bullish divergences (price makes lower lows, oscillator does not) and bearish divergences (price makes higher highs, oscillator does not) are plotted as lines, with optional labels showing the divergence type and price.
- Reversal Signals: Major reversals are detected when volume exceeds a threshold (based on a 7-period SMA and reversal factor, default: 4) and the oscillator exceeds ±4. Minor reversals consider RSI (±20) and oscillator crossovers. Signals are plotted as triangles (major) or circles (minor), with blue for bullish and red for bearish.
- Confluence Meter and Areas: The confluence meter, displayed on the right, shows alignment between the oscillator and MFI using a gradient from red (bearish) to blue (bullish). Shaded areas at ±55 highlight strong bullish or bearish confluence when both indicators align.
- Signal and Divergence Labels: Labels are plotted on the candlestick chart when the oscillator crosses key levels (±20, ±40) or when money flow conditions are met (e.g., MFI crossing 0 or ±20/±40). Users can toggle label visibility and adjust sizes (Small, Normal, Large, Huge).
- Trend and Control Table: A table displays the trend (based on oscillator SMA) and control (based on MFI direction), with customizable position (default: Top Right), text color, and background color. Sensitivity for trend and control calculations can be adjusted.
- k-NN Prediction: The k-NN algorithm predicts price movement direction by comparing current RSI values (5-period and 20-period WMAs) to historical data. The number of neighbors (default: 200) and trend length (default: 20) control prediction sensitivity. A green line shows the prediction, with gradient fills indicating overbought (lime) and oversold (red) zones.
- Gradient Fills and Alerts: Gradient fills highlight the prediction's position relative to overbought/oversold zones, calculated using a 2000-period lookback and standard deviation. Alerts are triggered for crossovers/crossunders of the prediction line with its WMA, overbought/oversold levels, or the zero line.
Usage Instructions
1. Add the Sniper-2025 indicator to your TradingView chart.
2. Interpret signals:
- Z-Buy/Z-V-Buy (green labels): Potential buy signals when the oscillator crosses below -20/-40.
- Z-Sell/Z-V-Sell (red labels): Potential sell signals when the oscillator crosses above 20/40.
- C-Buy/C-Sell (green/red labels): Money flow shifts to bullish/bearish when MFI crosses 0.
- T-Buy/T-Sell (green/red labels): Money flow crosses ±20, indicating stronger trends.
- T-V-Buy/T-V-Sell (green/red labels): Money flow crosses ±40, indicating very strong trends.
- Divergence Labels: Green (D-Bullish) or red (D-Bearish) labels indicate potential reversals.
- Reversal Signals: Blue triangles/circles for bullish reversals, red for bearish.
- Confluence Meter: Blue (bullish) or red (bearish) gradient indicates alignment strength.
- Table: Check "Trend" and "Control" for market direction (🟩/🟥 for trend, 🟢/🔴 for control).
- k-NN Prediction: Green line above 0 suggests bullish momentum; below 0 suggests bearish. Watch for crossovers with the WMA or overbought/oversold zones.
3. Set alerts for crossovers/crossunders of the prediction line, oscillator, or MFI to automate trading signals.
Customization Options
- Hyper Wave: Adjust Main Length (mL, default: 15) for oscillator sensitivity, Signal Type (sT, SMA/EMA), and Signal Length (sLHW, default: 3). Customize colors and transparency.
- Smart Money Flow: Set Money Flow Length (mfL, default: 10) and Smooth (mfS, default: 6) for MFI sensitivity. Choose bullish/bearish colors.
- Divergence: Modify Divergence Sensibility (dvT, default: 20) for short-term (lower) or long-term (higher) divergences. Toggle visibility and price display on labels.
- Reversal: Adjust Reversal Factor (rsF, default: 4) for signal strength (higher = fewer, stronger signals). Set colors for bullish/bearish signals.
- Confluence: Toggle Confluence Meter (sCNF) and Areas (sCNB), and customize colors.
- Labels: Enable/disable specific signal labels (e.g., showZBuy, showHSell) and adjust Label Size (default: Normal).
- Table: Toggle Trend and Control display, adjust sensitivities, and set position and colors.
- k-NN Prediction: Adjust Prediction Data (numNeighbors, default: 200) for sensitivity and Trend Length (momentumWindow, default: 20) for responsiveness.
Conclusion
The Sniper-2025 indicator is a powerful tool for traders seeking a comprehensive analysis of price momentum, money flow, divergences, reversals, and predictive signals. Its customizable settings and clear visualizations make it suitable for both novice and experienced traders. Use the indicator to identify high-probability trading opportunities, monitor market trends, and refine strategies with its machine learning-driven predictions.
ETH Valuation Indicator╔═══════════════════════ RUBIXCUBE ════════════════════════════╗
This indicator combines multiple on-chain and market-based metrics into a single valuation score for Ethereum. It highlights periods of relative undervaluation (green zones) and overvaluation (red zones) by normalising several metrics into a 0–1 range and averaging them.
Price chart signals (top panel): Green arrows mark points where the indicator flagged historically attractive buying opportunities.
Valuation oscillator (bottom panel): Shows the combined score over time, cycling between undervalued and overvalued extremes.
Metric breakdown (side panel): Displays the contribution of each metric, their rate of change, and their current score.
This tool is designed for macro insight, not short-term trading. It helps contextualise Ethereum’s position in the market cycle and provides a data-driven framework for long-term investors.
╚═══════════════════════════════════════════════════════════╝
BTC Valuation Indicator╔═══════════════════ RUBIXCUBE ══════════════════════╗
This indicator combines multiple on-chain and market-based metrics into a single valuation score for Bitcoin. It highlights periods of relative undervaluation (green zones) and overvaluation (red zones) by normalising several metrics into a 0–1 range and averaging them.
- Price chart signals (top panel): Green arrows mark points where the indicator flagged historically attractive buying opportunities.
- Valuation oscillator (bottom panel): Shows the combined score over time, cycling between undervalued and overvalued extremes.
- Metric breakdown (side panel): Displays the contribution of each metric, their rate of change, and their current score.
This tool is designed for macro insight, not short-term trading. It helps contextualise Bitcoin’s position in the market cycle and provides a data-driven framework for long-term investors.
╚═════════════════════════════════════════════════╝
VSOVSO
This is similar to LazyBear's WaveTrend oscillator but handles momentum calculation differently and has some extra components for trade analysis.
The oscillator calculates an adaptive mean, then measures how far price deviates from that mean. Instead of just looking at raw deviation, it normalizes this by dividing by smoothed absolute deviation values.
The key difference is how it separates momentum - it splits the deviation into positive (up) and negative (down) components, then applies directional strength smoothing to each separately before combining them:
100 * (up_strength - down_strength) / (up_strength + down_strength)
This directional strength calculation gives more weight to sustained moves in either direction rather than just price volatility. The result is the main Momentum Wave oscillating between -100 and +100. The Signal Wave is just a smoothed version of this. The Momentum Gap shows the difference between them.
You'll see the Momentum Wave as a colored area/line with four color states, the Signal Wave as a white area, the Momentum Gap as a yellow line, the Drip Rate as cyan/purple area, and Velocity as a colored line at the bottom. The overbought/oversold zones are shaded, volatility bands adapt to current conditions, and major/minor signals show up as circles when the waves cross.
For trading, the Drip Rate is your long-term signal for bigger shifts. When it makes lower lows into resistance, look for reversals. Works great across multiple timeframes. Volatility squeezes signal big moves coming - use these with support/resistance and divergences. Top/bottom signals show momentum shifts and usually lead to pumps or drops.
Velocity shows breakout speed or rejections. Higher readings mean faster moves, regardless of direction. Wave colors reveal continuation patterns - green to purple to green means strong continuation up, red to cyan to red means continuation down.
The Momentum Gap can signal divergence on its own. The angle it crosses zero often hints at how fast the next move will be. When momentum goes outside the volatility bands, watch the next wave for divergence or confirmation.
Works best when you combine the Drip Rate across timeframes with squeeze setups and color changes for high-probability entries.
Works well with Heikin Ashi candles, or use the smoothed candle mode in the settings to mimic them. You can set the candle colors to the momentum wave colors as well, it can be helpful.
Here is a trade setup and how you can use it to take trades.
Guitar Hero [theUltimator5]The Guitar Hero indicator transforms traditional oscillator signals into a visually engaging, game-like display reminiscent of the popular Guitar Hero video game. Instead of standard line plots, this indicator presents oscillator values as colored segments or blocks, making it easier to quickly identify market conditions at a glance.
Choose from 8 different technical oscillators:
RSI (Relative Strength Index)
Stochastic %K
Stochastic %D
Williams %R
CCI (Commodity Channel Index)
MFI (Money Flow Index)
TSI (True Strength Index)
Ultimate Oscillator
Visual Display Modes
1) Boxes Mode : Creates distinct rectangular boxes for each bar, providing a clean, segmented appearance. (default)
This visual display is limited by the amount of box plots that TradingView allows on each indictor, so it will only plot a limited history. If you want to view a similar visual display that has minor breaks between boxes, then use the fill mode.
2) Fill Mode : Uses filled areas between plot boundaries.
Use this mode when you want to view the plots further back in history without the strict drawing limitations.
Five-Level Color-Coded System
The indicator normalizes all oscillator values to a 0-100 scale and categorizes them into five distinct levels:
Level 1 (Red): Very Oversold (0-19)
Level 2 (Orange): Oversold (20-29)
Level 3 (Yellow): Neutral (30-70)
Level 4 (Aqua): Overbought (71-80)
Level 5 (Lime): Very Overbought (81-100)
Customization Options
Signal Parameters
Signal Length: Primary period for oscillator calculation (default: 14)
Signal Length 2: Secondary period for Stochastic %D and TSI (default: 3)
Signal Length 3: Tertiary period for TSI calculation (default: 25)
Display Controls
Show Horizontal Reference Lines: Toggle grid lines for better level identification
Show Information Table: Display current signal type, value, and normalized value
Table Position: Choose from 9 different screen positions for the info table
Display Mode: Switch between Boxes and Fills visualization
Max Bars to Display: Control how many historical bars to show (50-450 range)
Normalization Process
The indicator automatically normalizes different oscillator ranges to a consistent 0-100 scale:
Williams %R: Converts from -100/0 range to 0-100
CCI: Maps typical -300/+300 range to 0-100
TSI: Transforms -100/+100 range to 0-100
Other oscillators: Already use 0-100 scale (RSI, Stochastic, MFI, Ultimate Oscillator)
This was designed as an educational tool
The gamified approach makes learning about oscillators more engaging for new traders.
CandelaCharts - Contango Slope Index 📝 Overview
The Contango Slope Index (CSI) is a volatility term structure analysis tool designed to quantify the slope of the VIX futures curve over time.
By measuring the rate of change in implied volatility across multiple tenors—such as VIX1D, VIX (1M), VIX3M, VIX6M, and VIX1Y—the CSI provides traders and analysts with real-time insights into market sentiment, risk appetite, and potential turning points in equity markets.
Developed by CandelaCharts, the CSI draws from established financial research on volatility term structures, particularly focusing on how contango (upward-sloping curve) and backwardation (downward-sloping curve) regimes correlate with future market behavior.
The index computes a normalized slope using linear regression across available VIX futures, offering a dynamic view of evolving market expectations. The core output a slope value expressed in annualized percentage points per year (%/yr)—represents the steepness of the volatility curve:
Positive slope: Contango regime, typically associated with market stability and complacency.
Negative slope: Backwardation, historically linked to fear, near-term uncertainty, and often preceding market rallies.
Slope crossing zero or key thresholds: Generates regime shifts and alert conditions.
📦 Features
The Contango Slope Index offers a comprehensive set of features for analyzing volatility dynamics:
Multi-Tenor Volatility Input: Users can select which VIX futures contracts to include in the slope calculation: VIX, VIX1D, etc
Dynamic Slope Calculation: The indicator calculates the slope of the VIX term structure using linear regression on time-to-maturity (TTM) vs. volatility levels.
Moving Average Overlay: A configurable moving average (SMA, EMA, RMA, WMA, VWMA) is applied to the smoothed slope to identify trend direction and momentum shifts.
Regime Classification: Based on the slope value and its relationship to the moving average, the CSI classifies current market conditions into distinct regimes.
Visual Enhancements: Color-coded slope line, background shading, etc
Real-Time Label & Tooltip: On the last bar, a dynamic label displays: Current regime, Slope value and direction, etc
⚙️ Settings
VIX: Toggles use of spot VIX index (CBOE_DLY:VIX).
VIX1D: Toggles use of 1-day VIX futures (CBOE_DLY:VIX1D).
VIX3M: Toggles use of 3-month VIX futures (CBOE_DLY:VIX3M).
VIX6M: Toggles use of 6-month VIX futures (CBOE_DLY:VIX6M).
VIX1Y: Toggles use of 1-year VIX futures (CBOE_DLY:VIX1Y).
MA: Enables moving average filter; options include type (SMA, etc.) and period length.
Slope: Defines slope calculation line thickness and colors.
Bg: Enables background shading with customizable colors.
⚡️ Showcase
Slope Line
Customizable Moving Average
Regime Shift Zones
📒 Usage
The CSI is plotted as a standalone oscillator beneath the price chart (non-overlay mode). Key interpretation guidelines:
Slope Direction
Slope < 0 - Backwardation: Indicates near-term volatility is higher than long-term expectations. Historically, this has preceded equity market rallies, as panic subsides and fear peaks.
Slope > 0 - Contango: Reflects normal market conditions where longer-dated volatility is priced higher. Persistent high contango may signal complacency.
Magnitude of Slope
Slope > 0.0232 (%/yr) - Elevated complacency: The term structure is steeper than historical average—caution advised ahead of potential corrections.
Slope near 0 - Neutral or transitioning regime: Markets may be at inflection points.
Slope vs. MA Crossover
Slope crosses above MA: Improving confidence, potential upside acceleration
Slope crosses below MA: Deteriorating structure, rising stress
🚨 Alerts
Six pre-configured alerts are available for integration into trading systems:
🚨 Backwardation Detected – Slope turns negative
🔚 Exit Backwardation – Slope crosses above zero
⚠️ Elevated Complacency – Slope exceeds 2.32%/yr
📈 Potential Bullish Setup – Slope crosses below zero
✅ Slope Crosses Above MA – Momentum improves
⚠️ Slope Crosses Below MA – Momentum deteriorates
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
CandelaCharts - Dip Index 📝 Overview
The Dip Index (DIPX) is a market breadth oscillator designed to identify market dips by measuring the percentage of assets within a chosen index or asset class that are trading above a specified moving average (such as the 50, 100, 150, or 200-period).
By highlighting when fewer assets remain above their averages, DIPX helps traders detect potential dip opportunities and assess overall market strength or weakness.
While commonly applied to equities, the indicator is adaptable to various financial instruments, including exchange-traded funds (ETFs), commodities, cryptocurrencies, and even fixed-income securities.
Assess the overall health of a market by measuring internal participation in price moves.
Detect overbought or oversold conditions when momentum becomes concentrated or overly extended.
Generate actionable signals when the index exits extreme levels, suggesting renewed momentum or potential exhaustion.
📦 Features
Multiple Indices: Supports SP500, Nasdaq, DJI, Russel2000, and sector-specific S&P indices.
Dynamic MA Selection: Choose from SMA, EMA, RMA, WMA, VWMA with configurable lengths.
Visual Customization: Full control over colors, line styles, text size, and branding.
Signal Markers: Triangle markers appear when exiting overbought/oversold zones.
Gradient & Background Fill: Visual highlighting of extreme market conditions.
Overlay Mode Option: Can display OB/OS background as chart overlay.
⚙️ Settings
Market: Chooses the index or asset class to measure.
MA: Enables moving average filter; options include type (SMA, EMA, etc.) and period length.
Oversold: Defines the lower threshold (default: 20) with customizable color.
Overbought: Defines the upper threshold (default: 80) with customizable color.
DIPX Line: Sets the thickness and color of the Dip Index line.
Mode: Selects display type (Line, Cross, Circle, Stepline, etc.).
Signals: Toggles buy/sell signal markers with customizable colors.
OB/OS Zones: Enables highlighting of Overbought/Oversold zones.
OB/OS Overlay: Toggles overlay shading for Overbought/Oversold zones.
⚡️ Showcase
Overbought/Oversold
Modes
Overbought/Oversold Zones
Signals
Overlay
📒 Usage
How to use DIPX effectively in trading and analysis, including interpretation, signal usage, strategic applications, and best practices.
DIPX outputs values from 0% to 100%, reflecting how widely participation extends across the underlying assets in an index or basket.
1. Assessing Market Health
Use DIPX to evaluate whether price moves are supported by broad participation:
In a bull trend, confirm strength by checking if DIPX stays above 50%.
In a bear trend, watch for rebounds in DIPX to spot temporary relief rallies.
2. Detecting Divergences
Divergence occurs when the price trend and DIPX trend disagree — often a precursor to reversal.
Bearish Divergence: Price makes higher highs; DIPX makes lower highs -> Momentum weakening - potential top
Bullish Divergence: Price makes lower lows; DIPX makes higher lows -> Selling pressure fading - potential bottom
How to Spot It:
Overlay DIPX on the same chart as the index price.
Use trendlines or horizontal markers to compare swing points.
Focus on weekly or daily timeframes for reliability.
3. Signal-Based Entries/Exits
When enabled (Signals = true) , DIPX generates triangle markers when exiting extreme zones:
Bullish Triangle (▲): DIPX crosses above Oversold Value (e.g., 20%, 30%) -> Green upward triangle
Bearish Triangle (▼): DIPX crosses below Overbought Value (e.g., 80%, 70%) -> Red downward triangle
4. Timeframe Guidance
1m – 4h: ❌ Not Recommended - DIPX uses daily-aggregated data;
Daily (D): ✅ Strongly Recommended - Matches data frequency; clearest signals
Weekly (W): ✅ Acceptable - Ideal for macro analysis and long-term positioning
Monthly (M): ⚠️ Limited Use - Too slow for active trading; useful for big-picture context
By integrating DIPX into your analysis, you gain a powerful lens into market internals — helping you distinguish between broad-based strength and narrow leadership, regardless of asset class.
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
Trusty RSI v2The 'Trusty RSI' indicator is based off a simple RSI but has additional trust power. For those who have trust issues in their trading, the flashy background colors and the 'Trusty' signals help you trade with infinite confidence! This indicator might revolutionize your trading and will help you become generationally wealthy! Please have fun with it!
On a more serious note, The Trusty RSI is a streamlined RSI-based oscillator designed to highlight only meaningful extremes. The pane is colored red when RSI > 80 and green when RSI < 30, while “Trusty Sell/Buy” labels appear only after three consecutive bars in those zones to reduce noise. It includes 80/55/30 guide levels with pane fill and offers optional smoothing of the RSI line via SMA or EMA (user-selectable length). Suitable for any symbol and timeframe; thresholds and lengths are configurable to fit different risk tolerances.
FluidFlow OscillatorFluidFlow Oscillator: Study Material for Traders
Overview
The FluidFlow Oscillator is a custom technical indicator designed to measure price momentum and market flow dynamics by simulating fluid motion concepts such as velocity, viscosity, and turbulence. It helps traders identify potential buy and sell signals along with trend strength, momentum direction, and volatility conditions.
This study explains the underlying calculation concepts, signal logic, visual cues, and how to interpret the professional dashboard table that summarizes key indicator readings.
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How the FluidFlow Oscillator Works
Core Mechanisms
1. Price Flow Velocity
o Measures the rate of change of price over a specified flow length (default 40 bars).
o Calculated as a percentage change of closing price: roc=close−closelen_flowcloselen_flow×100\text{roc} = \frac{\text{close} - \text{close}_{len\_flow}}{\text{close}_{len\_flow}} \times 100roc=closelen_flowclose−closelen_flow×100
o Smoothed by an EMA (Exponential Moving Average) to reduce noise, generating a "flow velocity" value.
2. Viscosity Factor
o Analogous to fluid viscosity, it adjusts the flow velocity based on recent price volatility.
o Volatility is computed as the standard deviation of close prices over the flow length.
o The viscosity acts as a damping factor to slow down the flow velocity in highly volatile conditions.
o This results in a "flow with viscosity" value, that smooths out the velocity considering market turbulence.
3. Turbulence Burst
o Captures sudden changes or bursts in the flow by measuring changes between successive viscosity-adjusted flows.
o The turbulence value is a smoothed absolute change in flow.
o A burst boost factor is added to the oscillator to incorporate this rapid change component, amplifying signals during sudden shifts.
4. Oscillator Calculation
o The raw oscillator value is the sum of flow with viscosity plus burst boost, scaled by 10.
o Clamped between -100 and +100 to limit extremes.
o Finally, smoothed again by EMA for cleaner visualization.
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Signal Logic
The oscillator works with complementary components to produce actionable signals:
• Signal Line: An EMA-smoothed version of the oscillator for generating crossover-based signals.
• Momentum: The rate of change of the oscillator itself, smoothed by EMA.
• Trend: Uses fast (21-period EMA) and slow (50-period EMA) moving averages of price to identify market trend direction (uptrend, downtrend, or sideways).
Signal Conditions
• Bullish Signal (Buy): Oscillator crosses above the oversold threshold with positive momentum.
• Bearish Signal (Sell): Oscillator crosses below the overbought threshold with negative momentum.
Statuses
The oscillator provides descriptive market states based on level and momentum:
• Overbought
• Oversold
• Buy Signal
• Sell Signal
• Bullish / Bearish (momentum-driven)
• Neutral (no clear trend)
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Color System and Visualization
The oscillator uses a sophisticated HSV color model adapting hues according to:
• Oscillator value magnitude and sign (positive or negative)
• Acceleration of oscillator changes
• Smooth color gradients to facilitate intuitive understanding of trend strength and momentum shifts
Background colors highlight overbought (red tint) and oversold (green tint) zones with transparency.
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How to Understand the Professional Dashboard Table
The FluidFlow Oscillator offers an integrated table at the bottom center of the chart. This dashboard summarizes critical indicator readings in 8 columns across 3 rows:
Column Description
SIGNAL Current signal status (e.g., Buy, Sell, Overbought) with color coding
OSCILLATOR Current oscillator value (-100 to +100) with color reflecting intensity and direction
MOMENTUM Momentum bias indicating strength/direction of oscillator changes (Strong Up, Up, Sideways, Down, Strong Down)
TREND Current trend status based on EMAs (Strong Uptrend, Uptrend, Sideways, Downtrend, Strong Downtrend)
VOLATILITY Volatility percentage relative to average, indicating market activity level
FLOW Flow velocity value describing price momentum magnitude and direction
TURBULENCE Turbulence level indicating sudden bursts or spikes in price movement
PROGRESS Oscillator's position mapped as a percentage (0% to 100%) showing proximity to extreme levels
Rows Explained
• Row 1 (Header): Labels for each metric.
• Row 2 (Values): Current numerical or descriptive values color-coded along a professional scheme:
o Green or lime tones indicate positive or bullish conditions.
o Red or orange tones indicate caution, sell signals, or bearish conditions.
o Blue tones indicate neutral or stable conditions.
• Row 3 (Status Indicators): Emoji-like icons and bars provide a quick visual gauge of each metric's intensity or signal strength:
o For example, "🟢🟢🟢" suggests very strong bullish momentum, while "🔴🔴🔴" suggests strong bearish momentum.
o Progress bar visually demonstrates oscillator movement toward oversold or overbought extremes.
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Practical Interpretation Tips
• A Buy signal with green colors and strong momentum usually precedes upward price moves.
• An Overbought status with red background and red table colors warns of potential price corrections or reversals.
• Watch the Turbulence to gauge market instability; spikes may precede price shocks or volatility bursts.
• Confirm signals with the Trend and Momentum columns to avoid false entries.
• Use the Progress bar to anticipate oscillations approaching key threshold levels for timing trades.
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Alerts
The oscillator supports alerts for:
• Buy and sell signals based on oscillator crossovers.
• Overbought and oversold levels reached.
These help traders automate awareness of important market conditions.
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Disclaimer
The FluidFlow Oscillator and its signals are for educational and informational purposes only. They do not guarantee profits and should not be considered as financial advice. Always conduct your own research and use proper risk management when trading. Past performance is not indicative of future results.
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This detailed explanation should help you understand the workings of the FluidFlow Oscillator, its components, signal logic, and how to analyze its professional dashboard for informed trading decisions.
Trendlines Oscillator [LuxAlgo]The Trendlines Oscillator helps traders identify trends and momentum based on the normalized distances between the current price and the most recently detected bullish and bearish trend lines.
The indicator features bullish and bearish momentum, a signal line with crossings, and multiple smoothing options.
🔶 USAGE
The indicator displays three lines: two for momentum and one for the signal. When one of the momentum lines (bullish or bearish) crosses the signal line, the tool displays a dot to indicate which momentum is gaining strength.
As a general rule, when the green bullish momentum line is above the red bearish momentum line, it indicates buyer strength. This means that the actual prices are farther from the support trend lines than the resistance trend lines. The opposite is true for seller strength.
To calculate bullish momentum, the tool first identifies bullish trend lines acting as support below the price. Then, it measures the delta between the price and those trend lines and normalizes the reading into the displayed momentum values.
The same process is used for bearish momentum, but with bearish trendlines acting as resistance above the price.
🔹 Length & Memory
Modifying the Length and Memory values will cause the tool to display different momentum values.
Traders can adjust the length to detect larger trendlines and adjust the memory to indicate how many trendlines the tool should consider.
As the chart above shows, smaller values make the tool more responsive, while larger values are useful for detecting larger trends.
🔹 Smoothing
By default, the data is not smoothed, and the signal uses a triangular moving average with a length of 10. Traders can smooth both the data and the signal line.
Traders can choose from up to ten different methods, or none. Some examples are shown on the chart above.
🔶 DETAILS
The steps for the calculations are as follows:
1. Gather the pivots, highs, and lows.
ph = fixnan(ta.pivothigh(lengthInput, lengthInput))
pl = fixnan(ta.pivotlow(lengthInput, lengthInput))
2. Calculate the slope and y-intercept for each trendline between contiguous lower highs (resistance) or higher lows (support).
if ph < ph
slope = (ph - ph )/(n-lengthInput - phx1)
res.unshift(l.new(ph - slope * phx1, slope))
if pl > pl
slope = (pl - pl )/(n-lengthInput - plx1)
sup.unshift(l.new(pl - slope * plx1, slope))
3. Calculate the value of each trendline on the current bar, then calculate the difference with the current price (delta). To calculate the relative sum of deltas, only consider trendlines below the price for support or above the price for resistance.
method get_point(l id, x)=>
id.slope * x + id.intercept
for element in sup
point = element.get_point(n)
if sourceInput > point
sup_sum += sourceInput - point
sup_den += math.abs(sourceInput - point)
for element in res
point = element.get_point(n)
if sourceInput < point
res_sum += point - sourceInput
res_den += math.abs(point - sourceInput)
4. Normalize the value from 0 to 100 by taking the sum of the relative values of the deltas divided by the sum of the absolute values of the deltas.
float supportLine = sup_sum / sup_den * 100
float resistanceLine = res_sum / res_den * 100
5. Smooth both values, then calculate the signal line as the difference between them.
float smoothSupport = smooth(supportLine,dataSmoothingInput,dataSmoothingLengthInput)
float smoothResistance = smooth(resistanceLine,dataSmoothingInput,dataSmoothingLengthInput)
float signal = math.abs(smoothSupport - smoothResistance)
float signalLine = smooth(signal,smoothingInput,smoothingLengthInput)
6. Calculate the crossing signals against the signal line, using only the first signal from each series of bullish or bearish crossings.
bullSignal = smoothSupport > signalLine and smoothSupport < signalLine
bearSignal = smoothResistance > signalLine and smoothResistance < signalLine
lastSignal := bullSignal and lastSignal == BEAR ? BULL : bearSignal and lastSignal == BULL ? BEAR : lastSignal
firstBull = ta.change(lastSignal) > 0
firstBear = ta.change(lastSignal) < 0
🔶 SETTINGS
Length: The size of the market structure used for trendline detection.
Memory: The number of trendlines used in calculations.
Source: The source for the calculations is closing prices by default.
🔹 Smoothing
Data Smoothing: Choose the smoothing method and length
Signal Smoothing: Choose the smoothing method and length
RSI Dynamic Bands█ OVERVIEW
The "RSI Dynamic Bands" indicator is a variant of the Relative Strength Index (RSI) oscillator that brings its signals directly onto the price chart. It displays dynamic bands around the price, adjusted based on RSI levels, enabling easy identification of potential overbought or oversold conditions. The indicator also integrates a multi-timeframe RSI table, facilitating the analysis of trend strength across different timeframes.
█ CONCEPTS
The "RSI Dynamic Bands" indicator is designed to simplify the interpretation of price levels in the context of support and resistance zones, which can be correlated with other technical indicators and RSI values. Since the price itself does not display RSI values, a table showing RSI for four selected timeframes has been added, allowing traders to quickly assess trend strength across different time intervals. The most effective approach is to combine the indicator with other technical analysis tools, such as Fibonacci levels or pivot points, to confirm signals when the price approaches the bands and RSI values indicate a potential reversal.
Band Calculation
The bands are calculated based on the current closing price and RSI values, incorporating dynamic scaling to better adapt to market conditions. The formulas for the bands are as follows:
• Upper Band: close + (rsiUpper - rsi) * scaleFactor, where rsiUpper is the upper RSI level (default: 70), and scaleFactor accounts for market volatility.
• Lower Band: close + (rsiLower - rsi) * scaleFactor, where rsiLower is the lower RSI level (default: 30).
• Midline: The arithmetic average of the upper and lower bands: (upperBand + lowerBand) / 2.
Why Scaling? Without scaling, the bands would be chaotic and jagged, making them difficult to interpret. Scaling smooths the bands, making them wider during periods of high volatility and narrower during consolidation, better reflecting potential support and resistance levels.
Indicator Features
• Dynamic Price Bands: The bands adapt to market conditions, facilitating the identification of key price levels.
• Multi-Timeframe RSI Table: Displays RSI values for four selected timeframes (default: 15m, 1h, 4h, Daily), enabling comparison of trend strength across different perspectives.
• Style Customization: Users can adjust band colors, line thickness, and toggle the visibility of bands, fills, and the table.
How to Set Up the Indicator
1 — Add the "RSI Dynamic Bands" indicator to your TradingView chart.
2 — Configure parameters in the settings, such as RSI length, upper/lower levels, and scaling multiplier, to match your trading style.
3 — Enable or disable the display of bands, fills, or the RSI table based on your needs.
4 — Adjust band and table colors in the input section and line thickness in the "Style" section to better align the indicator with your chart.
█ OTHER SECTIONS
FEATURES
• RSI Length: The period for calculating RSI (default: 14).
• RSI Levels: Thresholds for overbought (default: 70) and oversold (default: 30).
• Scaling Multiplier: Adjusts bands based on market volatility (default: 0.15).
• Table Timeframes: Select four timeframes for the RSI table (default: 15m, 1h, 4h, Daily).
• Style Options: Customize band colors, fills, table, and line thickness.
HOW TO USE
Add the indicator to your chart, configure the parameters, and observe price interactions with the bands to identify potential entry and exit points. The RSI table allows you to compare RSI values across different timeframes, aiding in trading decisions. The most effective approach is to combine the indicator with other technical analysis tools, such as Fibonacci levels or pivot points, to confirm signals when the price approaches the bands and RSI values indicate a potential reversal.
Trading Strategies:
• Scalping: Use lower timeframes (e.g., 5m, 15m) in the RSI table to quickly identify short-term lows and highs. Wait for the price to approach the lower band in the RSI oversold zone, with RSI on lower timeframes starting to rise, and other tools, such as Fibonacci levels (e.g., 38.2%) or pivot points, confirming support.
• Medium-Term Trading: Focus on 1h and 4h timeframes. Look for confirmation of a low on a lower timeframe (e.g., 1h), where RSI indicates oversold conditions or starts rising, then check if RSI on a higher timeframe (e.g., 4h) confirms the trend. Confirmation from other tools, such as a Fibonacci level (e.g., 50%) or pivot point near the bands, strengthens the signal.
• Long-Term Trading: Use Daily and higher timeframes (e.g., Weekly). Wait for all relevant timeframes to confirm a low (e.g., RSI near oversold and price at the lower band), with lower timeframes (e.g., 4h) showing rising RSI. Other tools, such as Fibonacci levels (e.g., 61.8%) or pivot points near the bands, can further confirm a trend reversal signal.
SigmoidCycle Oscillator [LuminoAlgo]Purpose:
The SineCycle Oscillator measures price momentum using sigmoid function mathematics (S-curve transformation) borrowed from neural network theory. It generates an oscillator that fluctuates around 1.0, identifying momentum shifts and potential reversal points.
Mathematical Foundation:
This indicator applies the sigmoid logistic function concept: y = 1/(1+e^-x) , which creates an S-shaped curve. In financial markets context, this transformation:
- Maps price changes to a bounded range (-1 to +1)
- Provides non-linear sensitivity (high near zero, low at extremes)
- Naturally filters outliers without lag penalty
Calculation Process:
1. Statistical Normalization: Price deviations are measured from a moving average baseline and scaled by recent volatility (standard deviation over N periods)
2. Sigmoid Transformation: Normalized values undergo S-curve transformation, which weights small movements linearly but compresses large movements logarithmically
3. Dual Timeframe Analysis:
• Short window: User-defined period (N)
• Long window: Double period (2N)
• Ratio calculation: Short sigmoid average ÷ Long sigmoid average
4. Volatility-Weighted Smoothing: Final values use exponential smoothing where the smoothing factor adjusts based on the coefficient of variation (volatility/mean ratio)
What Makes This Different:
Unlike linear momentum oscillators (RSI, Stochastic) that use fixed mathematical relationships, the sigmoid transformation creates variable sensitivity zones. This mimics how professional traders mentally weight price movements.
Trading Application:
Signal Types:
- Momentum: Green (>1.0) = bullish, Red (<1.0) = bearish
- Reversals: 1.0 line crosses with volume confirmation
- Divergence: Price makes new high/low, oscillator doesn't
- Exhaustion: Extended readings (>1.2 or <0.8) suggest overextension
Optimal Conditions:
- Works best: Trending markets with clear swings
- Avoid: Low volume, ranging markets under 1% daily movement
- Timeframes: 4H and above for reliability
Parameter Guidelines:
- Length 8-10: Day trading (expect more whipsaws)
- Length 14-20: Swing trading (balanced signals)
- Length 25-30: Position trading (fewer, stronger signals)
Limitations:
- Lag increases with higher length settings
- Can give false signals during news-driven spikes
- Requires additional confirmation in choppy markets
Trading Framework:
Based on momentum persistence theory - assumes trends continue until sigmoid curve flattens (indicating momentum exhaustion). The mathematical model captures both mean reversion (extreme readings) and trend following (mid-range readings) characteristics.
VWAP For Loop [BackQuant]VWAP For Loop
What this tool does—in one sentence
A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts.
Plain-English overview
Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context.
Under the hood
• Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls:
Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year.
• For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP .
– If VWAP > VWAP , add +1.
– Else, add −1.
The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45.
• Signal logic (stateful)
– Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags).
– Short on crossunder of lower (e.g., dropping below −10).
– A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence.
Why VWAP + a breadth score?
• VWAP aggregates both price and volume—where participants actually traded.
• The breadth-style count rewards consistency of the anchored trend, not one-off spikes.
• Thresholds give you binary structure when you need it (alerts, automation), without complex math.
What you’ll see on the chart
• Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral).
• Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors).
• Threshold guides — Horizontal lines for the long/short bands (toggle).
• Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors.
Input map (quick reference)
• VWAP Anchor Period — Day, Week, Month, Quarter, Year.
• Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons.
• Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below).
• UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors.
Interpreting the score
• Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength.
• Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness.
• Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise.
Why the asymmetric default thresholds?
• Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.”
• Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to:
– Capture sustained uptrends only when they’re very strong.
– Flag downside turns as they occur, rather than waiting for an extreme negative breadth.
Tuning guide
Choose an anchor that matches your horizon
– Intraday scalps : Day anchor on intraday charts.
– Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles.
Pick the for-loop window
– Larger N (bigger end) = stronger evidence requirement, smoother oscillator.
– Smaller N = faster, more reactive score.
Set achievable thresholds
– Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger.
– Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior.
Match visuals to intent
– Enabling VWAP coloring lets you see regime directly on price.
– Background shading is useful for discretionary reading; turn it off for cleaner automation displays.
Playbook examples
• Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing.
• Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off.
• Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder.
Behavior around resets (important)
Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes.
Alerts included
• VWAP FL Long — Fires when the long condition is true (score > upper and not in short).
• VWAP FL Short — Fires on crossunder of the lower threshold (event-driven).
Messages include {{ticker}} and {{interval}} placeholders for routing.
Strengths
• Simple, transparent math — Easy to reason about and validate.
• Volume-aware by construction — Decisions reference VWAP, not just price.
• Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output).
Limitations & cautions
• Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N.
• Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N.
• Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature.
• VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic.
Suggested starting profiles
• Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON.
• Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF.
• Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired.
Implementation notes
• The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss).
• HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range.
• For-loop cap is kept modest (≤50) for performance and clarity.
How to use this responsibly
Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns.
Summary
VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.
samc's - Keltner OscillatorThe KELTNER CHANNEL is a widely used technical indicator developed in the 60's by Chester W. Keltner who described it in his 1960 book How To Make Money in Commodities.
so i took the logic, simplified the code and made into an oscillator.
to add a flavor of modern times you can choose among 10 different colorways themes in the settings. (so traders can adjust it for dark or light charts)
Although the initial idea was developed for stocks and commodities, I've carefully back tested this as an oscillator across FX MAJORS , MINORS and high liquidity stocks for the use case of scalping and Medium term trade ideas.
now, this indicator works successfully over all time frames, custom time frames and all assets.
This script builds on the same approach as my earlier session tool — keeping things clean, visual, and easy to read.
I intend to publish more of my work as i develop them from Beta ideas into stable scripts, and i welcome feedback.
Six Meridian Divine Swords [theUltimator5]The Six Meridian Divine Sword is a legendary martial arts technique in the classic wuxia novel “Demi-Gods and Semi-Devils” (天龙八部) by Jin Yong (金庸). The technique uses powerful internal energy (qi) to shoot invisible sword-like energy beams from the six meridians of the hand. Each of the six fingers/meridians corresponds to a “sword,” giving six different sword energies.
The Six Meridian Divine Swords indicator is a compact “signal dashboard” that fuses six classic indicators (fingers)—MACD, KDJ, RSI, LWR (Williams %R), BBI, and MTM—into one pane. Each row is a traffic-light dot (green/bullish, red/bearish, gray/neutral). When all six align, the script draws a confirmation line (“All Bullish” or “All Bearish”). It’s designed for quick consensus reads across trend, momentum, and overbought/oversold conditions.
How to Read the Dashboard
The pane has 6 horizontal rows (explained in depth later):
MACD
KDJ
RSI
LWR (Larry Williams %R)
BBI (Bull & Bear Index)
MTM (Momentum)
Each tick in the row is a dot, with sentiment identified by a color.
Green = bullish condition met
Red = bearish condition met
Gray = inside a neutral band (filtering chop), shown when Use Neutral (Gray) Colors is ON
There are two lines that track the dots on the top or bottom of the pane.
All Bullish Signal Line: appears only if all 6 are strongly bullish (default color = white)
All Bearish Signal Line: appears only if all 6 are strongly bearish (default color = fuchsia)
The Six Meridians (Indicators) — What They Mean:
1) MACD — Trend & Momentum
What it is: A trend-following momentum indicator based on the relationship between two moving averages (typically 12-EMA and 26-EMA)
Logic used: Classic MACD line (EMA12−EMA26) vs its 9-EMA signal.
Bullish: MACD > Signal and |MACD−Signal| > Neutral Threshold
Bearish: MACD < Signal and |diff| > threshold
Neutral: |diff| ≤ threshold
Why: Small crosses can whipsaw. The neutral band ignores tiny separations to reduce noise.
Inputs: Fast/Slow/Signal lengths, Neutral Threshold.
2) KDJ — Stochastic with J-line boost
What it is: A variation of the stochastic oscillator popular in Chinese trading systems
Logic used: K = SMA(Stochastic, smooth), D = SMA(K, smooth), J = 3K − 2D.
Bullish: K > D and |K−D| > 2
Bearish: K < D and |K−D| > 2
Neutral: |K−D| ≤ 2
Why: K–D separation filters tiny wiggles; J offers an “extreme” early-warning context in the value label.
Inputs: Length, Smoothing.
3) RSI — Momentum balance (0–100)
What it is: A momentum oscillator measuring speed and magnitude of price changes (0–100)
Logic used: RSI(N).
Bullish: RSI > 50 + Neutral Zone
Bearish: RSI < 50 − Neutral Zone
Neutral: Between those bands
Why: Centerline/adaptive bands (around 50) give a directional bias without relying on fixed 70/30.
Inputs: Length, Neutral Zone (± around 50).
4) LWR (Williams %R) — Overbought/Oversold
What it is: An oscillator similar to stochastic, measuring how close the close is to the high-low range over N periods
Logic used: %R over N bars (0 to −100).
Bullish: %R > −50 + Neutral Zone
Bearish: %R < −50 − Neutral Zone
Neutral: Between those bands
Why: Uses a centered band around −50 instead of only −20/−80, making it act like a directional filter.
Inputs: Length, Neutral Zone (± around −50).
5) BBI (Bull & Bear Index) — Smoothed trend bias
What it is: A composite moving average, essentially the average of several different moving averages (often 3, 6, 12, 24 periods)
Logic used: Average of 4 SMAs (3/6/12/24 by default):
BBI = (MA3 + MA6 + MA12 + MA24) / 4
Bullish: Close > BBI and |Close−BBI| > 0.2% of BBI
Bearish: Close < BBI and |diff| > threshold
Neutral: |diff| ≤ threshold
Why: Multiple MAs blended together reduce single-MA whipsaw. A dynamic 0.2% band ignores tiny drift.
Inputs: 4 lengths (default 3/6/12/24). Threshold is auto-scaled at 0.2% of BBI.
6) MTM (Momentum) — Rate of change in price
What it is: A simple measure of rate of change
Logic used: MTM = Close − Close
Bullish: MTM > 0.5% of Close
Bearish: MTM < −0.5% of Close
Neutral: |MTM| ≤ threshold
Why: A percent-based gate adapts across prices (e.g., $5 vs $500) and mutes insignificant moves.
Inputs: Length. Threshold auto-scaled to 0.5% of current Close.
Display & Inputs You Can Tweak
🎨 Use Neutral (Gray) Colors
ON (default): 3-color mode with clear “no-trade”/“weak” states.
OFF: classic binary (green/red) without neutral filtering.
Z Distance from VWAP Enhanced (ZVWAP)The "Z Distance from VWAP Enhanced" (ZVWAP) indicator is a comprehensive oscillator that provides deep insights into market dynamics. It calculates a Z-score, which tells you how many standard deviations the current price is away from the VWAP. This normalization makes it a consistent and reliable tool for identifying market extremes.
The indicator comes packed with features, including:
Customizable Overbought & Oversold Zones
Built-in Bullish & Bearish Divergence Detection
Automatic Trendline Plotting
A Moving Exponential Average (MEA) for crossover signals
Fully customizable alerts for every key event.
How to Use It - The BTC Dominance Strategy for Altcoins
As shown in the screenshot, this indicator is an exceptional tool for trading altcoins by analyzing the BTC Dominance (BTC.D) chart. The relationship is typically inverse:
When ZVWAP on BTC.D is RISING (or Overbought) ➔ It's BEARISH for Altcoins.
This means Bitcoin is gaining dominance, and capital is flowing out of altcoins and into Bitcoin. This is a time to be cautious with or short altcoins.
When ZVWAP on BTC.D is FALLING (or Oversold) ➔ It's BULLISH for Altcoins.
This means Bitcoin is losing dominance, and capital is flowing into altcoins, often starting an "altcoin season." This is a great time to look for long entries on your favorite altcoins.
Key Signals on the BTC.D Chart:
Zone Entries: When ZVWAP enters the red (Overbought) zone, prepare for altcoins to weaken. When it enters the blue (Oversold) zone, look for altcoin strength.
MEA Crossover: A crossover of the yellow ZVWAP line below the cyan MEA line is a strong confirmation that dominance is falling and the trend is becoming bullish for altcoins.
Divergences: A bearish divergence on the BTC.D chart can be an early warning that dominance is about to fall, signaling a potential bullish move for altcoins.
Key Features Explained
Overbought / Oversold Zones: The red and blue shaded areas clearly define when an asset is statistically over-extended. These are prime areas to look for mean reversion or trend exhaustion.
Divergence Detection: The script automatically detects and plots divergences between price and the ZVWAP.
• Bullish Divergence: Price makes a lower low, but ZVWAP makes a higher low. (Potential buy signal).
• Bearish Divergence: Price makes a higher high, but ZVWAP makes a lower high. (Potential sell signal).
The Reference Lines (+1 / -1): These gray lines represent one standard deviation from the VWAP. They act as an early warning system. When the ZVWAP crosses these lines, it shows that momentum is building, and the price is starting to deviate significantly from its average.
Automatic Trendlines: The indicator can automatically draw and manage trendlines based on recent pivots in the ZVWAP, helping you visualize the current momentum and potential breakout points. This feature can be turned off if you prefer a cleaner chart.
Customization and Alerts
The indicator is fully customizable. You can adjust the lengths, zone levels, and visual settings to fit your trading style. Most importantly, it includes a comprehensive set of alerts:
Enter Overbought Zone
Enter Oversold Zone
Bullish Divergence Detected
Bearish Divergence Detected
Enter Any Zone (OB/OS) - a single alert for either condition.
Any Divergence (Bull/Bear) - a single alert for any divergence.
This allows you to stay informed of every important signal without having to watch the charts all day.
i.imgur.com
TASC 2025.09 The Continuation Index
█ OVERVIEW
This script implements the "Continuation Index" as described by John F. Ehlers in the September 2025 edition of TASC's Trader's Tips . The Continuation Index uses Laguerre filters (featured in the July 2025 edition) to provide an early indication of trend direction, continuation, and exhaustion.
█ CONCEPTS
The idea for the Continuation Index was formed from an observation about Laguerre filters. In his article, Ehlers notes that when price is in trend, it tends to stay to one side of the filter. When considering smoothing, the UltimateSmoother was an obvious choice to reduce lag. With that in mind, The Continuation Index normalizes the difference between UltimateSmoother and the Laguerre filter to produce a two-state oscillator.
To minimize lag, the UltimateSmoother length in this indicator is fixed to half the length of the Laguerre filter.
█ USAGE
The Continuation Index consists of two primary states.
+1 suggests that the trader should position on the long side.
-1 suggests that the user should position on the short side.
Other readings can imply other opportunities, such as:
High Value Fluctuation could be used as a "buy the dip" opportunity.
Low Value Fluctuation could be used as a "sell the pop" opportunity.
█ INPUTS
By understanding the inputs and adjusting them as needed, each trader can benefit more from this indicator:
Gamma : Controls the Laguerre filter's response. This can be set anywhere between 0 and 1. If set to 0, the filter’s value will be the same as the UltimateSmoother.
Order : Controls the lag of the Laguerre filter, which is important when considering the timing of the system for spotting reversals. This can be set from 1 to 10, with lower values typically producing faster timing.
Length : Affects the smoothing of the display. Ehlers recommends starting with this value set to the intended amount of time you plan to hold a position. Consider your chart timeframe when setting this input. For example, on a daily chart, if you intend to hold a position for one month, set a value of 20.
Machine Learning BBPct [BackQuant]Machine Learning BBPct
What this is (in one line)
A Bollinger Band %B oscillator enhanced with a simplified K-Nearest Neighbors (KNN) pattern matcher. The model compares today’s context (volatility, momentum, volume, and position inside the bands) to similar situations in recent history and blends that historical consensus back into the raw %B to reduce noise and improve context awareness. It is informational and diagnostic—designed to describe market state, not to sell a trading system.
Background: %B in plain terms
Bollinger %B measures where price sits inside its dynamic envelope: 0 at the lower band, 1 at the upper band, ~ 0.5 near the basis (the moving average). Readings toward 1 indicate pressure near the envelope’s upper edge (often strength or stretch), while readings toward 0 indicate pressure near the lower edge (often weakness or stretch). Because bands adapt to volatility, %B is naturally comparable across regimes.
Why add (simplified) KNN?
Classic %B is reactive and can be whippy in fast regimes. The simplified KNN layer builds a “nearest-neighbor memory” of recent market states and asks: “When the market looked like this before, where did %B tend to be next bar?” It then blends that estimate with the current %B. Key ideas:
• Feature vector . Each bar is summarized by up to five normalized features:
– %B itself (normalized)
– Band width (volatility proxy)
– Price momentum (ROC)
– Volume momentum (ROC of volume)
– Price position within the bands
• Distance metric . Euclidean distance ranks the most similar recent bars.
• Prediction . Average the neighbors’ prior %B (lagged to avoid lookahead), inverse-weighted by distance.
• Blend . Linearly combine raw %B and KNN-predicted %B with a configurable weight; optional filtering then adapts to confidence.
This remains “simplified” KNN: no training/validation split, no KD-trees, no scaling beyond windowed min-max, and no probabilistic calibration.
How the script is organized (by input groups)
1) BBPct Settings
• Price Source – Which price to evaluate (%B is computed from this).
• Calculation Period – Lookback for SMA basis and standard deviation.
• Multiplier – Standard deviation width (e.g., 2.0).
• Apply Smoothing / Type / Length – Optional smoothing of the %B stream before ML (EMA, RMA, DEMA, TEMA, LINREG, HMA, etc.). Turning this off gives you the raw %B.
2) Thresholds
• Overbought/Oversold – Default 0.8 / 0.2 (inside ).
• Extreme OB/OS – Stricter zones (e.g., 0.95 / 0.05) to flag stretch conditions.
3) KNN Machine Learning
• Enable KNN – Switch between pure %B and hybrid.
• K (neighbors) – How many historical analogs to blend (default 8).
• Historical Period – Size of the search window for neighbors.
• ML Weight – Blend between raw %B and KNN estimate.
• Number of Features – Use 2–5 features; higher counts add context but raise the risk of overfitting in short windows.
4) Filtering
• Method – None, Adaptive, Kalman-style (first-order),
or Hull smoothing.
• Strength – How aggressively to smooth. “Adaptive” uses model confidence to modulate its alpha: higher confidence → stronger reliance on the ML estimate.
5) Performance Tracking
• Win-rate Period – Simple running score of past signal outcomes based on target/stop/time-out logic (informational, not a robust backtest).
• Early Entry Lookback – Horizon for forecasting a potential threshold cross.
• Profit Target / Stop Loss – Used only by the internal win-rate heuristic.
6) Self-Optimization
• Enable Self-Optimization – Lightweight, rolling comparison of a few canned settings (K = 8/14/21 via simple rules on %B extremes).
• Optimization Window & Stability Threshold – Governs how quickly preferred K changes and how sensitive the overfitting alarm is.
• Adaptive Thresholds – Adjust the OB/OS lines with volatility regime (ATR ratio), widening in calm markets and tightening in turbulent ones (bounded 0.7–0.9 and 0.1–0.3).
7) UI Settings
• Show Table / Zones / ML Prediction / Early Signals – Toggle informational overlays.
• Signal Line Width, Candle Painting, Colors – Visual preferences.
Step-by-step logic
A) Compute %B
Basis = SMA(source, len); dev = stdev(source, len) × multiplier; Upper/Lower = Basis ± dev.
%B = (price − Lower) / (Upper − Lower). Optional smoothing yields standardBB .
B) Build the feature vector
All features are min-max normalized over the KNN window so distances are in comparable units. Features include normalized %B, normalized band width, normalized price ROC, normalized volume ROC, and normalized position within bands. You can limit to the first N features (2–5).
C) Find nearest neighbors
For each bar inside the lookback window, compute the Euclidean distance between current features and that bar’s features. Sort by distance, keep the top K .
D) Predict and blend
Use inverse-distance weights (with a strong cap for near-zero distances) to average neighbors’ prior %B (lagged by one bar). This becomes the KNN estimate. Blend it with raw %B via the ML weight. A variance of neighbor %B around the prediction becomes an uncertainty proxy ; combined with a stability score (how long parameters remain unchanged), it forms mlConfidence ∈ . The Adaptive filter optionally transforms that confidence into a smoothing coefficient.
E) Adaptive thresholds
Volatility regime (ATR(14) divided by its 50-bar SMA) nudges OB/OS thresholds wider or narrower within fixed bounds. The aim: comparable extremeness across regimes.
F) Early entry heuristic
A tiny two-step slope/acceleration probe extrapolates finalBB forward a few bars. If it is on track to cross OB/OS soon (and slope/acceleration agree), it flags an EARLY_BUY/SELL candidate with an internal confidence score. This is explicitly a heuristic—use as an attention cue, not a signal by itself.
G) Informational win-rate
The script keeps a rolling array of trade outcomes derived from signal transitions + rudimentary exits (target/stop/time). The percentage shown is a rough diagnostic , not a validated backtest.
Outputs and visual language
• ML Bollinger %B (finalBB) – The main line after KNN blending and optional filtering.
• Gradient fill – Greenish tones above 0.5, reddish below, with intensity following distance from the midline.
• Adaptive zones – Overbought/oversold and extreme bands; shaded backgrounds appear at extremes.
• ML Prediction (dots) – The KNN estimate plotted as faint circles; becomes bright white when confidence > 0.7.
• Early arrows – Optional small triangles for approaching OB/OS.
• Candle painting – Light green above the midline, light red below (optional).
• Info panel – Current value, signal classification, ML confidence, optimized K, stability, volatility regime, adaptive thresholds, overfitting flag, early-entry status, and total signals processed.
Signal classification (informational)
The indicator does not fire trade commands; it labels state:
• STRONG_BUY / STRONG_SELL – finalBB beyond extreme OS/OB thresholds.
• BUY / SELL – finalBB beyond adaptive OS/OB.
• EARLY_BUY / EARLY_SELL – forecast suggests a near-term cross with decent internal confidence.
• NEUTRAL – between adaptive bands.
Alerts (what you can automate)
• Entering adaptive OB/OS and extreme OB/OS.
• Midline cross (0.5).
• Overfitting detected (frequent parameter flipping).
• Early signals when early confidence > 0.7.
These are purely descriptive triggers around the indicator’s state.
Practical interpretation
• Mean-reversion context – In range markets, adaptive OS/OB with ML smoothing can reduce whipsaws relative to raw %B.
• Trend context – In persistent trends, the KNN blend can keep finalBB nearer the mid/upper region during healthy pullbacks if history supports similar contexts.
• Regime awareness – Watch the volatility regime and adaptive thresholds. If thresholds compress (high vol), “OB/OS” comes sooner; if thresholds widen (calm), it takes more stretch to flag.
• Confidence as a weight – High mlConfidence implies neighbors agree; you may rely more on the ML curve. Low confidence argues for de-emphasizing ML and leaning on raw %B or other tools.
• Stability score – Rising stability indicates consistent parameter selection and fewer flips; dropping stability hints at a shifting backdrop.
Methodological notes
• Normalization uses rolling min-max over the KNN window. This is simple and scale-agnostic but sensitive to outliers; the distance metric will reflect that.
• Distance is unweighted Euclidean. If you raise featureCount, you increase dimensionality; consider keeping K larger and lookback ample to avoid sparse-neighbor artifacts.
• Lag handling intentionally uses neighbors’ previous %B for prediction to avoid lookahead bias.
• Self-optimization is deliberately modest: it only compares a few canned K/threshold choices using simple “did an extreme anticipate movement?” scoring, then enforces a stability regime and an overfitting guard. It is not a grid search or GA.
• Kalman option is a first-order recursive filter (fixed gain), not a full state-space estimator.
• Hull option derives a dynamic length from 1/strength; it is a convenience smoothing alternative.
Limitations and cautions
• Non-stationarity – Nearest neighbors from the recent window may not represent the future under structural breaks (policy shifts, liquidity shocks).
• Curse of dimensionality – Adding features without sufficient lookback can make genuine neighbors rare.
• Overfitting risk – The script includes a crude overfitting detector (frequent parameter flips) and will fall back to defaults when triggered, but this is only a guardrail.
• Win-rate display – The internal score is illustrative; it does not constitute a tradable backtest.
• Latency vs. smoothness – Smoothing and ML blending reduce noise but add lag; tune to your timeframe and objectives.
Tuning guide
• Short-term scalping – Lower len (10–14), slightly lower multiplier (1.8–2.0), small K (5–8), featureCount 3–4, Adaptive filter ON, moderate strength.
• Swing trading – len (20–30), multiplier ~2.0, K (8–14), featureCount 4–5, Adaptive thresholds ON, filter modest.
• Strong trends – Consider higher adaptive_upper/lower bounds (or let volatility regime do it), keep ML weight moderate so raw %B still reflects surges.
• Chop – Higher ML weight and stronger Adaptive filtering; accept lag in exchange for fewer false extremes.
How to use it responsibly
Treat this as a state descriptor and context filter. Pair it with your execution signals (structure breaks, volume footprints, higher-timeframe bias) and risk management. If mlConfidence is low or stability is falling, lean less on the ML line and more on raw %B or external confirmation.
Summary
Machine Learning BBPct augments a familiar oscillator with a transparent, simplified KNN memory of recent conditions. By blending neighbors’ behavior into %B and adapting thresholds to volatility regime—while exposing confidence, stability, and a plain early-entry heuristic—it provides an informational, probability-minded view of stretch and reversion that you can interpret alongside your own process.
MTF Oscillator Stack [BigBeluga]🔵 OVERVIEW
The MTF Oscillator Stack brings powerful multi-timeframe momentum analysis directly into your price chart. You can select one oscillator— RSI , MFI , or Stochastic RSI —and display it across up to 4 different timeframes. Each panel is neatly stacked horizontally above price , offering quick insight into cross-timeframe conditions like trend direction, exhaustion zones, and momentum shifts.
🔵 CONCEPTS
Single Oscillator Mode: Select one oscillator type (RSI, MFI, or Stoch RSI) to analyze across all selected timeframes.
Top-Chart Horizontal Panels: Oscillator plots are aligned horizontally at the top of the chart for seamless top-down reading.
Signal Comparison Arrows: Arrows (🢁 / 🢃) indicate oscillator position relative to its signal line.
Overbought/Oversold Zones: Transparent 30–70 fill zones highlight key reversal areas.
Dynamic Display Logic: Only enabled panels are shown; spacing adjusts based on active timeframes.
Timeframe Tagging: Each oscillator panel is labeled with its corresponding timeframe (e.g., 1H, 2H, 4H).
🔵 FEATURES
Choose one oscillator (RSI, MFI, or Stoch RSI) and apply it across up to 4 timeframes.
Each oscillator panel includes: price-synced plot, signal line, and zone shading.
Scale alignment allows users to place charts at the bottom or top.
Clear arrow signals show whether oscillator is bullish or bearish.
Individual length and signal settings per timeframe.
Toggle for alignment mode: evenly spaced or floating layout.
All panels use a consistent layout for faster decision-making.
🔵 HOW TO USE
Select your preferred oscillator and activate 2–4 key timeframes (e.g., 1H, 4H, D1, W1).
Use signal crossovers as a bullish (🢁) or bearish (🢃) trend cue.
Look for aligned extremes (e.g., all timeframes overbought) to spot momentum exhaustion.
Ideal for momentum confluence strategies and top-down confirmation.
Use horizontal layout to stay focused on price while assessing broader structure.
🔵 CONCLUSION
MTF Oscillator Stack simplifies complex multi-timeframe momentum analysis into one clean, actionable visual. Whether you're tracking RSI, MFI, or Stoch RSI, this tool helps you stay aligned with the broader trend—without ever leaving your main chart.
