Dual MomentumEnter your assets using the data you got from the sheet and the indicator will tell you when to buy or get back to cash based off the momentum of these assets
Oscillateurs centrés
ROC-WMA bull bear indicatorROC-Weighted MA Oscillator
By Ludovic B
Modified source code of SeerQuant
The ROC-Weighted MA Oscillator (ROCWMA) is a momentum-driven oscillator designed to expose hidden acceleration and deceleration phases in price action by dynamically weighting a moving average with the normalized Rate of Change (ROC).
Instead of treating all price deviations equally, this indicator amplifies meaningful moves and suppresses low-energy noise, making it particularly effective in scalping, intraday trading, and momentum reversals.
🔧 Core Concept
A base moving average (SMA, EMA, TEMA, DEMA, HMA, ALMA, etc.)
Weighted by normalized ROC
Transformed into a Z-score oscillator for comparability across assets
Smoothed with a signal line for timing precision
Result: a context-aware oscillator that adapts to market intensity.
📊 What the Oscillator Shows
Bullish momentum when histogram is positive and expanding
Bearish momentum when histogram is negative and expanding
Neutral zone to filter chop and avoid over-trading
Automatic color logic to highlight regime changes
Optional candle coloring reflects the active momentum state.
🎯 Signal-Based Price Markers (Advanced Feature)
This script includes price-chart markers when:
The signal line retraces to X% of the maximum oscillator bar of the current momentum phase
AND the signal slope confirms exhaustion (rising or falling)
Key characteristics:
Adaptive thresholds (relative, not fixed)
Separate logic for bullish and bearish phases
Reset on each neutral-zone transition
Configurable number of markers per momentum cycle
This makes the indicator particularly useful for:
Pullback entries
Momentum fading
Timing partial exits
⚙️ Customization
Fully adjustable ROC length, MA type, signal length
Neutral zone threshold control
Multiple color schemes
Optional candle coloring
Adaptive signal-to-oscillator percentage logic
🧠 Best Use Cases
Scalping (M1–M5)
Intraday momentum confirmation
Pullback and exhaustion detection
Cross-asset trading (FX, indices, crypto, metals)
ROCWMA is not a lagging oscillator.
It is a momentum intensity detector built to reveal when price moves matter.
ATR-Based Z-Score (with Signal Line)The ATR-Based Z-Score is an advanced, volatility-normalized oscillator designed to identify extreme price deviations more reliably than the standard Z-Score.
By replacing the traditional Standard Deviation with the Average True Range (ATR) in the denominator, this indicator eliminates the "volatility paradox" where rapid price spikes cause standard oscillators to prematurely return to zero, even as the price continues to crash.
Why this version is superior
In a classic Z-Score calculation:
Z = (Price - SMA) / (Standard Deviation)
A sudden impulsive price drop causes the Standard Deviation to explode. Because you are dividing by a rapidly increasing number, the Z-Score often "rises" while the price is still falling.
The ATR-Based Solution:
Z = (Price - SMA) / ATR
By using a long-period ATR as the denominator, the volatility measure remains stable and "clean." This ensures that the indicator’s troughs align much more accurately with actual price bottoms, staying in the oversold territory until the momentum truly shifts.
Key Features
Volatility Cleaning: The ATR-normalization prevents the indicator from "flattening out" during impulsive price movements.
Integrated Signal Line: A customizable Moving Average of the Z-Score values helps filter noise and confirms entry/exit points.
Independent Periods: You can set the Price MA (responsiveness) and the ATR (volatility baseline) separately to fine-tune the indicator to different timeframes.
How to Trade with it
1. Mean Reversion (Buy the Dip / Sell the Rip)
Long: Wait for the Z-Score to drop below a significant level (e.g., -10.0). Enter when the Z-Score crosses back above its Signal Line.
Short: Wait for the Z-Score to rise above +10.0 and enter when it crosses below the Signal Line.
2. Breakout Trading
A strong push of the Z-Score beyond the +/- 7.0 levels can indicate a powerful trend breakout.
In this case, the Signal Line crossover serves as an effective Exit Signal, telling you that the initial momentum of the breakout is fading.
Summary
✅ This indicator is designed for traders who find standard oscillators too "nervous" during volatile periods. By decoupling price deviation from immediate variance spikes, the ATR-Based Z-Score provides a rock-solid foundation for identifying true market extremes and high-probability reversal points.
Bitterroot Trader RelVol vs SPYHelp understand specific stock momentum verses the market (SPY). This shows the relative volume at time and also the average trade range number.
ROC-WMA bull bear indicatorROC-Weighted MA Oscillator
based on Seequant indicator
The ROC-Weighted MA Oscillator (ROCWMA) is a momentum-driven oscillator designed to expose hidden acceleration and deceleration phases in price action by dynamically weighting a moving average with the normalized Rate of Change (ROC).
Instead of treating all price deviations equally, this indicator amplifies meaningful moves and suppresses low-energy noise, making it particularly effective in scalping, intraday trading, and momentum reversals.
🔧 Core Concept
A base moving average (SMA, EMA, TEMA, DEMA, HMA, ALMA, etc.)
Weighted by normalized ROC
Transformed into a Z-score oscillator for comparability across assets
Smoothed with a signal line for timing precision
Result: a context-aware oscillator that adapts to market intensity.
📊 What the Oscillator Shows
Bullish momentum when histogram is positive and expanding
Bearish momentum when histogram is negative and expanding
Neutral zone to filter chop and avoid over-trading
Automatic color logic to highlight regime changes
Optional candle coloring reflects the active momentum state.
🎯 Signal-Based Price Markers (Advanced Feature)
This script includes price-chart markers when:
The signal line retraces to X% of the maximum oscillator bar of the current momentum phase
AND the signal slope confirms exhaustion (rising or falling)
Key characteristics:
Adaptive thresholds (relative, not fixed)
Separate logic for bullish and bearish phases
Reset on each neutral-zone transition
Configurable number of markers per momentum cycle
This makes the indicator particularly useful for:
Pullback entries
Momentum fading
Timing partial exits
⚙️ Customization
Fully adjustable ROC length, MA type, signal length
Neutral zone threshold control
Multiple color schemes
Optional candle coloring
Adaptive signal-to-oscillator percentage logic
🧠 Best Use Cases
Scalping (M1–M5)
Intraday momentum confirmation
Pullback and exhaustion detection
Cross-asset trading (FX, indices, crypto, metals)
ROCWMA is not a lagging oscillator.
It is a momentum intensity detector built to reveal when price moves matter.
Simple EFI + EMASimple Elder Force Index (EFI) with EMA Signal is a minimal momentum indicator that measures buying and selling pressure by combining price change and volume. The raw Force Index is smoothed with an Exponential Moving Average to reduce noise, and an additional EMA signal line helps visualize momentum shifts and trend strength. A zero line is included to quickly distinguish bullish (> 0) from bearish (< 0) conditions. This stripped-down version is designed for clarity and fast decision-making without extra filters or alerts.
Weighted Volume ROC OscillatorWeighted Volume ROC Oscillator (WVRO | MisinkoMaster)
The Weighted Volume ROC Oscillator is a sophisticated trend-following tool that leverages a volume-weighted Rate of Change (ROC) calculation on a double-smoothed source. Designed to capture both trend direction and strength with minimal noise, this oscillator also highlights potential reversal points, making it an effective tool for fast-moving markets like ETHUSD.
By combining volume weighting with advanced smoothing techniques, the WVRO provides a responsive yet stable indicator to help traders make more informed decisions during trending conditions.
🔍 Concept & Idea
The core idea behind the WVRO is to develop a high-speed oscillator capable of smoothly following trends while remaining sensitive to rapid changes. The ROC is a natural choice for momentum measurement, but raw ROC alone can be noisy.
To improve stability and responsiveness:
The input source is smoothed twice using Weighted Moving Averages (WMA) with a length proportional to the square root of the user-defined length, reducing noise while preserving fast reactions.
The ROC is then weighted by volume to emphasize price movements during high-volume periods, increasing the significance of meaningful trades.
Finally, a volume-weighted average of the ROC is calculated to normalize the signal.
This combination balances smoothness and speed, improving signal clarity in trending markets.
⚙️ How It Works
Double WMA Smoothing of Source:
First, apply a WMA with length √len to the selected source to filter noise but retain responsiveness.
Apply a second WMA with the same length to the first smoothed series for additional smoothing.
Volume-Weighted ROC Calculation:
Calculate ROC on the double-smoothed source over one bar.
Multiply the ROC by the current volume, weighting price changes by trading activity.
Normalization and Oscillator Computation:
Calculate an Exponential Moving Average (EMA) of the volume-weighted ROC over the full length.
Divide by the sum of volume over the same length to normalize, then scale to a range centered near zero.
Trend Logic:
Positive WVRO values indicate bullish momentum (trend up).
Negative values indicate bearish momentum (trend down).
Momentum Divergence:
The difference between the current WVRO and its prior value is smoothed with EMA and plotted as a histogram to help identify potential momentum shifts and reversals.
🧩 Inputs Overview
Oscillator Length – Controls the main smoothing and lookback length of the oscillator (default 17).
Source – The price source used for calculation, defaulting to the average of high, low, close, and close (hlcc4).
📌 Usage Notes
Responsive Yet Smooth: The double WMA smoothing ensures the oscillator is less prone to noise but remains quick to react to market changes.
Volume Weighting: Emphasizes price moves on higher volume bars, improving signal reliability in volatile markets.
Trend Identification: Positive and negative readings provide clear trend signals, while divergence histograms highlight potential turning points.
Visual Clarity: Color-coded plots and background highlighting assist quick interpretation.
Optimized for ETHUSD: Especially effective in high-liquidity, high-volatility assets like Ethereum.
Complement with Other Tools: Use alongside price action or other indicators to confirm trends and entry/exit points.
Backtest and Validate: Always validate settings on your chosen asset and timeframe before live use.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only and does not constitute financial advice. Trading involves significant risk, and users should perform due diligence before trading.
Enjoy enhanced trend following with the Weighted Volume ROC Oscillator!
Filtered Percentile OscillatorFiltered Percentile Oscillator (FPO | MisinkoMaster)
The Filtered Percentile Oscillator is a modern trend-following tool designed to combine the power of percentile ranking with adaptive trend strength filtering. By integrating a filter based on ADX strength, this oscillator aims to reduce noise and improve signal quality, helping traders identify more reliable bullish and bearish momentum zones.
This indicator works well across different markets, especially where volatility and trend clarity fluctuate. Although it can be noisy at times, the intelligent filtering mechanism provides strong potential for spotting actionable trend signals.
🔍 Concept & Idea
The idea behind the Filtered Percentile Oscillator is to use the percentile rank of price changes as a normalized measure of momentum, then apply an adaptive filter based on the Average Directional Index (ADX) to adjust sensitivity dynamically.
By combining these two concepts:
The Percentile Oscillator captures how extreme the current price is relative to recent price history.
The ADX-based filter adjusts threshold levels and confirms if the market is trending strongly enough to trust these percentile signals.
This dual-filtering mechanism improves the indicator’s ability to avoid false signals caused by noisy or non-trending environments.
⚙️ How It Works
The indicator calculates the Percentile Rank of the user-selected price source over a defined length (len). This percentile oscillator oscillates between -100% and +100%, reflecting relative price positioning.
It calculates the ADX and its percentile rank over a separate filter length (adx_len and ap_len) to estimate trend strength and market activity.
A combined potential filter checks if the sum of the absolute percentile oscillator and ADX percentile exceeds a user-defined threshold (pot_t). This filter controls whether signals are considered valid.
Thresholds for long and short signals dynamically adapt based on whether the ADX percentile exceeds the filter threshold (adx_t):
When strong trend strength is detected (ADX percentile > threshold), tighter upper and lower thresholds (ut and lt) apply to capture sharper trend signals.
When trend strength is weaker, wider thresholds (utm and ltm) are used to filter noise and reduce false signals.
Trend states are determined by comparing the percentile oscillator to these adaptive thresholds and validating the potential filter condition.
Overbought and oversold zones are also plotted for identifying potential reversal or exhaustion areas.
🧩 Inputs Overview
Length – Controls the lookback period for the Percentile Oscillator calculation (default 29).
Source – The price data source used for oscillator calculation (default: close).
Filter Length – Lookback period for ADX calculation used as a filter (default 12).
Filter % Length – Length used to calculate the percentile rank of the ADX filter (default 8).
Trending Upper Threshold – Upper bound for bullish signals when trend strength is strong (default 10).
Trending Lower Threshold – Lower bound for bearish signals when trend strength is strong (default -10).
Ranging Upper Threshold – Upper bound for bullish signals when trend strength is weak (default 15).
Ranging Lower Threshold – Lower bound for bearish signals when trend strength is weak (default -15).
Sum Filter Threshold – Minimum combined percentile value required to validate signals (default 100).
Filter Threshold – Minimum ADX percentile value required to switch to tighter thresholds (default 50).
Overbought – Level indicating overbought conditions for the oscillator (default 80).
Oversold – Level indicating oversold conditions for the oscillator (default -80).
📌 Usage Notes
Adaptive Filtering: The indicator dynamically adjusts sensitivity to market trend strength, reducing false signals during ranging or low-activity periods.
Normalized Momentum: Using percentile ranks allows comparison across different instruments and timeframes on a consistent scale.
Trend Confirmation: The ADX percentile filter ensures signals are stronger and more reliable when the market is trending.
Visual Guidance: Colored plots, threshold lines, and background fills improve signal interpretation and decision-making.
Customization: Thresholds and lengths can be fine-tuned for different markets or trading styles.
Complementary Use: Best combined with volume analysis, price action, or other indicators for comprehensive trade confirmation.
Backtest First: Always validate settings on historical data to match your preferred instrument and timeframe before live trading.
⚠️ Disclaimer
This indicator is provided solely for educational and analytical use. It is not financial advice. Trading involves risk, and users should perform their own due diligence before making trading decisions.
Enjoy improved trend filtering with the Filtered Percentile Oscillator!
MACD Standard DeviationMACD Standard Deviation
The MACD Standard Deviation is a smoother, volatility-adjusted version of MACD designed to improve signal quality and reduce noise while preserving fast market responsiveness.
🚀 Benefits
• Strong performance on assets like BNBUSDT
• Faster entries with reduced signal noise
• Simple and efficient calculation method
• Improved trend clarity compared to classic MACD
💡 Core Idea
The objective is to create a cleaner MACD signal by measuring and adapting to its volatility. By accounting for dispersion, the indicator filters weak fluctuations and keeps meaningful momentum moves.
⚙️ How It Works
A standard MACD is calculated using selected moving averages.
Standard deviation of the MACD is computed over a chosen period.
Upper and lower dynamic levels are derived from MACD median and volatility.
These adaptive bands help filter false signals and better capture trend direction.
The result is a smoother, more stable MACD-based trend tool.
📌 Usage Notes
• Crosses around the zero line indicate potential trend shifts.
• Expanding band distance suggests rising momentum volatility.
• Contracting distance often signals consolidation phases.
• Histogram changes help visualize acceleration or weakening momentum.
Luminous Trend Wave [Pineify]```
Luminous Trend Wave - Hull MA Based Normalized Momentum Oscillator
The Luminous Trend Wave (Pineify) is a momentum oscillator designed to provide clear, responsive trend signals while minimizing the lag commonly associated with traditional momentum indicators. By combining Hull Moving Average (HMA) calculations with ATR-based normalization and hyperbolic tangent transformation, LTW delivers a bounded oscillator that works consistently across different assets and timeframes.
Key Features
Hull Moving Average foundation for reduced lag trend detection
ATR normalization for universal applicability across all markets
Bounded output range (-100 to +100) using mathematical tanh transformation
Dynamic gradient coloring that reflects momentum intensity
Built-in signal line for momentum confirmation
Automatic alerts for trend reversals and momentum shifts
How It Works
The indicator operates through a four-stage calculation process:
Trend Basis Calculation: The indicator first calculates a Hull Moving Average (HMA) of the closing price. HMA was chosen specifically because it provides significantly less lag compared to Simple or Exponential Moving Averages while maintaining smoothness. This allows the oscillator to respond quickly to genuine price movements.
Distance Measurement: The raw distance between the current close price and the HMA trend line is calculated. This distance represents how far price has deviated from its smoothed trend.
ATR Normalization: The distance is then divided by the Average True Range (ATR) over the same lookback period. This normalization step is crucial - it makes the oscillator readings comparable across different assets regardless of their price levels or typical volatility. A stock trading at $500 and one at $5 will produce equivalent readings when their relative movements are similar.
Tanh Transformation: Finally, the normalized value is passed through a hyperbolic tangent function scaled by a sensitivity multiplier. The mathematical formula (e^2x - 1) / (e^2x + 1) naturally bounds the output between -100 and +100, preventing extreme spikes while preserving the directional information.
Trading Ideas and Insights
Zero Line Crossovers: When the oscillator crosses above zero, it indicates a shift from bearish to bullish momentum. Conversely, crossing below zero signals bearish momentum. These crossovers can be used as entry triggers when confirmed by other analysis.
Overbought/Oversold Levels: Readings above +80 suggest overbought conditions where price has extended significantly above its trend. Readings below -80 indicate oversold conditions. These extremes often precede mean reversion moves.
Signal Line Divergence: When the main oscillator (histogram) is above the signal line, momentum is increasing. When below, momentum is decreasing. This relationship helps identify the strength of the current move.
Momentum Fading: The indicator automatically fades the color intensity when the oscillator value is closer to the signal line than to the extremes, visually indicating weakening momentum before potential reversals.
How Multiple Indicators Work Together
LTW integrates three distinct technical concepts into a cohesive system:
Hull MA + ATR Integration: The Hull Moving Average provides the trend direction while ATR provides the volatility context. Together, they answer not just "where is the trend?" but "how significant is the current deviation relative to normal market movement?"
Mathematical Bounding + Visual Mapping: The tanh transformation ensures readings stay within predictable bounds, while the gradient coloring maps these bounded values to intuitive visual feedback. Strong bullish readings appear in bright green, strong bearish in bright red, with smooth transitions between.
Oscillator + Signal Line System: Similar to MACD's relationship between the MACD line and signal line, LTW uses a WMA-smoothed signal line to filter noise and confirm momentum direction. The interplay between the faster oscillator and slower signal creates actionable crossover signals.
Unique Aspects
Universal Normalization: Unlike many oscillators that produce different reading ranges on different assets, LTW's ATR normalization ensures consistent interpretation whether trading forex, crypto, stocks, or commodities.
Sensitivity Control: The sensitivity parameter allows traders to adjust how aggressively the oscillator responds to price changes. Higher values make it more responsive (useful for scalping), while lower values smooth out noise (better for swing trading).
Visual Momentum Feedback: The gradient coloring and transparency adjustments provide immediate visual feedback about trend strength without requiring traders to interpret numerical values.
How to Use
Add the indicator to your chart - it displays in a separate pane below price.
Watch for zero line crossovers as primary trend signals. Bullish when crossing above, bearish when crossing below.
Use the ±80 levels as caution zones where reversals become more likely.
Monitor the relationship between the histogram and signal line - histogram above signal indicates strengthening momentum.
Pay attention to color intensity - faded colors indicate weakening momentum and potential reversal zones.
Set alerts for automated notifications on trend changes and momentum shifts.
Customization
Trend Lookback (default: 21): Controls the HMA period. Lower values increase responsiveness but may generate more false signals. Higher values provide smoother trends but with more lag.
Signal Smoothing (default: 5): Adjusts the WMA period for the signal line. Higher values create a slower signal line with fewer crossovers.
Sensitivity (default: 1.5): Multiplier for the tanh transformation. Increase for more reactive signals, decrease for smoother readings.
Colors: Fully customizable bullish and bearish colors to match your chart theme.
Gradients: Toggle gradient coloring on/off based on preference.
Conclusion
The Luminous Trend Wave indicator offers traders a mathematically sound approach to momentum analysis. By combining the low-lag properties of Hull Moving Average with ATR-based normalization and bounded output transformation, LTW provides consistent, interpretable signals across any market. The visual feedback system makes trend strength immediately apparent, while the signal line crossovers offer clear entry and exit timing. Whether used as a standalone tool or combined with price action analysis, LTW helps traders identify trend direction, momentum strength, and potential reversal zones with clarity.
```
Serhan deneme 2Sadece deneme için yapılan bir çalışma, geliştirdikçe paylaşacağm, lütfen fazla dikkate almayınız.
Crypto Momentum OscillatorThe indicator uses an adaptive weighting system that dynamically adjusts component importance based on rolling correlations with BTC, creating a composite master score that signals optimal entry/exit conditions when macro tailwinds align with crypto momentum.
Trend-cycle reversion (multi-timeframe)Trend-cycle reversion (multi-timeframe) is a mean-reversion “stretch” gauge built around a simple idea: price often deviates from its recent path (trend + dominant swing rhythm), and those deviations become more actionable when you scale them by volatility and express them as a standardized score.
This script models the last N bars as:
1) a linear trend (to capture drift), plus
2) a single dominant cycle (to capture the most prominent oscillation inside the same window).
It then measures how far current price is from the model’s next-bar projection, normalizes that distance by ATR (volatility), and finally converts the result into a rolling Z-score. The output is displayed as a multi-timeframe dashboard so you can see “stretch vs. fit” across several time compressions at once.
------------------------------------------------------------
What you see on the chart
------------------------------------------------------------
The indicator draws a table (overlay) with up to 12 rows (configurable), one per timeframe from your CSV list.
Each row shows:
• TF: The timeframe being evaluated (e.g., 1, 5, 15, 60, 240, D).
• Z: The current Z-score of the volatility-scaled model gap on that timeframe.
• State: A simple interpretation using your Z threshold:
- “Short ▼” when Z > +threshold (price is extended above the model path)
- “Long ▲” when Z < −threshold (price is extended below the model path)
- “Hold •” when inside the band (not unusually stretched)
Colors follow the same logic: red for high positive Z, green for high negative Z, gray when neutral or unavailable.
Important: “Long/Short” here describes the direction of mean-reversion pressure (over/under the fitted path), not a complete trading system by itself.
------------------------------------------------------------
How it works (plain-English math)
------------------------------------------------------------
1) Optional log transform
If “Fit on log(price)” is enabled, the model runs on log(price) instead of raw price. This is often useful for markets that behave multiplicatively (large percentage moves, long-term exponential growth), because distances become closer to “percent-like” rather than absolute dollars.
2) Trend fit (linear regression in the window)
Over the last Window Length bars, the script estimates a straight-line trend. Think of this as the baseline path that best explains the window if you ignore swings.
3) Cycle search (best period by least-squares error)
After removing the linear trend, the script searches for a single sinusoidal cycle period between:
• Min Period and Max Period (in bars), stepping by Period Step.
For each candidate period, it computes the best-fitting sine+cosine components and measures the remaining error (SSE). The period with the smallest SSE is selected as the “best” cycle for that window.
To reduce recalculation cost and to keep the chosen cycle from flapping every bar, the script re-runs this period search only every “Re-search best period every N bars”. Between searches, it keeps using the last best period.
4) Next-bar projection and “gap”
Using the fitted trend + fitted cycle, the script projects the model value one bar ahead (relative to the window indexing). It then computes:
gap = (current value) − (projected value)
If “Invert sign” is enabled, the gap is multiplied by −1. This doesn’t change magnitude, it only flips interpretation (useful if you prefer the opposite sign convention).
5) Volatility scaling via ATR
The raw gap is divided by ATR to make it comparable across symbols and regimes. If you are fitting on log(price), ATR is also computed in log space using a log-based true range, then smoothed similarly (so the scale is consistent).
This produces a “gap in ATR units”.
6) Z-score standardization
Finally, the script computes a rolling Z-score of the ATR-scaled gap over “Z-score length”:
Z = (gapATR − mean(gapATR)) / stdev(gapATR)
This is what appears in the table. The Z-score answers: “How unusual is today’s model deviation compared to the last Z-score length observations?”
------------------------------------------------------------
How to interpret the Z-score
------------------------------------------------------------
Z near 0:
Price is close to the model path relative to recent volatility (nothing unusual).
Z above +threshold:
Price is meaningfully ABOVE the fitted path (stretched up). This can be read as elevated downside mean-reversion pressure — but it can also persist during strong trends.
Z below −threshold:
Price is meaningfully BELOW the fitted path (stretched down). This can be read as elevated upside mean-reversion pressure — but it can also persist during fast selloffs.
A practical way to use this indicator is to treat it as a “context filter” or “risk tool”:
• Fading extremes: look for mean-reversion setups when Z is beyond the threshold and price action confirms (e.g., momentum stalls, structure breaks, volatility contraction/expansion cues).
• Trend-aware reversion: only take “reversion” signals in the direction permitted by your separate trend filter (higher-timeframe trend, moving average regime, market structure, etc.).
• Take-profit / risk management: in a trend-following strategy, extremes can be used as partial profit zones or as “don’t chase here” warnings.
------------------------------------------------------------
Multi-timeframe (MTF) notes
------------------------------------------------------------
Each table row is computed with request.security() on that timeframe with no lookahead, so it is not using future bars to form the value.
However, like any live indicator, the value for an actively forming bar can change until that bar closes (especially on the lower timeframes). Also, higher-timeframe rows update when that higher-timeframe bar updates/closes.
------------------------------------------------------------
Inputs (what to change first)
------------------------------------------------------------
If you only change a few settings, start here:
• Window Length:
Controls how much history the model uses. Larger = smoother/stabler, but slower to adapt.
• Min/Max Period + Step:
Controls the cycle search range and granularity.
- Wider ranges can capture more possibilities but cost more computation.
- Smaller steps can find a closer match but also cost more.
• Re-search every N bars:
Higher = faster performance and more stability; lower = more adaptive but can be noisier.
• ATR length (scale gap):
Controls the volatility scale. Shorter reacts faster to volatility changes; longer is steadier.
• Z-score length:
Controls how “rare” extremes are. Longer lengths make Z more stable, but require more history and adapt slower to regime shifts.
• Z threshold:
Defines when the table labels “Long/Short”. Common choices are 1.5–2.5 depending on how selective you want extremes to be.
• Timeframes (CSV) + Max table rows:
Controls what you see in the dashboard.
------------------------------------------------------------
Limitations and expectations
------------------------------------------------------------
This is a single-cycle, windowed model. Markets can be multi-cycle, non-sinusoidal, or structurally shifting; in those cases the “best period” is simply the best approximation inside the window, not a guarantee of a true underlying rhythm.
Z-score extremes are not automatic reversal calls. In strong trends or during volatility shocks, Z can stay extreme longer than expected. Use this as a measurement tool, then combine it with your own confirmation and risk management.
This indicator is for analysis/education and does not provide financial advice.
Green Trend, Red Chop Zone [rambijey]This indicator offers a fresh perspective on the classic ADX. Instead of looking at the absolute ADX value, it focuses on the ADX Slope (Velocity).
The goal is to visually filter out market noise (Chop) and pinpoint exactly when a trend is accelerating.
The 4 Market Phases:
🟢 Green (Strong Bullish): ADX is rising fast, and Bulls are in control (+DI > -DI).
🔴 Red (Strong Bearish): ADX is rising fast, and Bears are in control (-DI > +DI).
🟡 Yellow (Neutral): ADX is flat or moving slowly. Transition phase.
⚪ Gray (Chop Zone): ADX is falling rapidly. The trend is dying, leading to consolidation or ranging markets.
Usage Tips: Avoid trading during Gray zones to prevent whipsaws. Look for entries when the histogram bursts into Green or Red, indicating a fresh surge in trend strength.
RSI Level Candles [fmb]RSI Level Candles
What it is
RSI Level Candles is a minimal, high-signal overlay that keeps your attention on price. It paints candles by RSI regime and adds tiny edge dots to highlight extreme momentum. The design goal is speed and clarity with no clutter.
Why it was built
Most RSI tools sit in a separate pane and introduce noise with extra lines, labels, and overlapping thresholds. This indicator moves the information onto price itself. You see regime directly on the candles and only the most important alerts when RSI is in extreme territory.
What it does
Candles change color according to RSI. Above the neutral high (default 60) they turn green. At the high extreme (default 70, or 80 if you prefer) they turn lime. Between 40 and 60 you may show a soft yellow neutral band or leave candles unpainted. Below the neutral low (default 40) candles turn red, and at or below the low extreme (default 30, or 20 if you prefer) they turn maroon. The indicator also prints small dots at the top and bottom of the pane to spotlight extremes. A green dot appears at the top on any bar with RSI at or above the high extreme. A red dot appears at the bottom on any bar with RSI at or below the low extreme.
How this helps
You get an instant read on momentum regime without leaving the price chart. Extremes are easy to spot which helps manage chase or exhaustion risk. The neutral band behavior helps distinguish trend days from range days and supports cleaner add or trim decisions within an existing trend.
Best practices
Treat 60 and 40 as momentum gates. Above 60 favors a long bias and additive entries on pullbacks. Below 40 favors a defensive posture on longs or a short bias. Use extremes for management rather than automatic reversal calls. In strong trends RSI can remain extreme for extended periods. Look for a change in market structure or a clear reclaim of 60 or 40 before shifting bias. Combine this overlay with simple structure and trend filters such as support and resistance, a 20 or 50 period moving average, and volume or volatility context.
Inputs
You can set RSI source and length, choose neutral low and high, and choose extreme low and high. The neutral band can be shown in soft yellow between 40 and 60 or turned off entirely. You can also toggle candle painting on or off if you only want the extreme dots.
Reading the colors
Lime indicates the extreme bullish zone. Green indicates bullish momentum. Yellow indicates the optional neutral band. Red indicates bearish momentum. Maroon indicates the extreme bearish zone. A small green dot at the top means the bar is in the high extreme. A small red dot at the bottom means the bar is in the low extreme.
Use cases
For trend following, stay aligned with the prevailing regime while avoiding overreactions to small fluctuations. For swing entries, buy pullbacks while RSI holds above 40 in uptrends, and fade bounces that stall under 60 in downtrends. For risk control, trim strength that pushes into extremes and stalls, then re-add on momentum reclaims.
Limitations
RSI measures momentum, not direction by itself. Do not use it in isolation. Extremes can persist during strong trends, so wait for structure or momentum re-tests before changing bias. Very illiquid symbols can create noisy signals.
Notes
Dots are designed to appear on every bar that sits inside the extreme zones. If you prefer single entry dots, change the logic to look for crosses rather than conditions. There is no separate RSI pane, no text labels, and no cross markers. The objective is simplicity and speed.
MACD Cross Overlay v.6d.mark165's MACD Cross Overlay updated to Pine Editor ver. 6 with a Timeframe option added. All credit to him. Shows MACD crossovers as well as MACD status (positive/negative) overlay.
For some reason the overlay is striped when viewed on a lower timeframe than the MACD (i.e. 1 minute MACD on 10 second chart). If anyone knows how to fix this please tell me.
BTC/M2 Fire Sniffer (Liquidity Range Z-Score)Howdy Fella. Great to see you here, exploring the true data in CRYPTOCAP:BTC analysis.
To ensure a perfect view on the markets, here are a few tips on how to fine tune the Fire Sniffer:
- Z-Score Lookback: 40
- Liquidity Ratio SuperSmoother Length: 8
- Z-score SuperSmoother Length: 132
Set the ranges as following:
Mean: -0.53
Liquidity Cycle Top: 0.8
Liquidity Cycle Bottom: -0.65
With that, you are set to go. Enjoy and make sure to let me know your thoughts on the script. You can contact me on X: @thebitcoinfrontier
MACD/PPO ALMA EditionMACD – a trend-following indicator that "always too late" indicates what's happening on the chart.
To make this indicator traditionally considered "good but too late" based on the ALMA moving average:
The Arnaud Legoux Moving Average (ALMA) is a technical indicator designed to reduce lag and noise in price data by applying a Gaussian filter, offering a smoother and more responsive alternative to traditional SMAs and EMAs.
Key Aspects of ALMA:
Key Parameters: ALMA uses three main settings: Window Size (length), Offset (offsets focus on recent prices, typically 0.85), and Sigma (controls the smoothness of the curve, typically 6).
Reduced Latency: By shifting the Gaussian distribution toward the most recent data (offset to 1), ALMA responds faster to price changes, helping to avoid false signals in uncertain, low-volatility conditions.
Using ALMA instead of EMA/SMA in the code significantly improves the smoothness and speed of signal appearance, which facilitates decision-making.
The code features three significant changes compared to traditional methods:
1. The price is determined based on (open+close)/2 - why is this? - theoretically, the volume-weighted asset value is always between the opening and closing prices, so I considered averaging it to be a good value.
2. Additional coloring of the trend change after the curves intersect to indicate an increase or decrease in trend strength.
3. Using PPO normalization allows for comparison of the dynamics of different stocks, as its values are normalized percentages and not absolute MACD values.
I most often use Heikin Ashi – the chart is very smooth and does not significantly affect the quick identification of trend changes.
EMA Crossover Arrows (6 EMA & 20 EMA)EMA Crossover Arrows (6 EMA & 20 EMA) - Quick Signal Detector
📊 OVERVIEW
A simple yet powerful indicator that automatically marks exact moments when the 6 EMA crosses the 20 EMA - giving you clear visual signals for potential trend changes without any chart clutter.
🎯 WHAT IT SHOWS
Two precise crossover signals:
- Blue Triangle Up (↑): 6 EMA crosses ABOVE 20 EMA (Bullish signal)
- Pink Triangle Down (↓): 6 EMA crosses BELOW 20 EMA (Bearish signal)
✨ KEY FEATURES
✓ Clean arrow markers appear only at crossover moments
✓ No lag - signals appear in real-time as crossovers occur
✓ Works on ANY timeframe (1min, 5min, 1H, daily, etc.)
✓ Non-intrusive - arrows don't clutter your chart
✓ Perfect for swing trading and trend following
✓ Zero configuration required
⚙️ TECHNICAL DETAILS
- 6 EMA: Fast-moving average for quick trend detection
- 20 EMA: Slower average providing trend confirmation
- Crossover detection uses Pine Script's built-in ta.crossover/crossunder functions
- No repainting - signals are final once the bar closes
Market Breadth MomentumThe indicator operates by fetching data from external tickers (usually market internal symbols like ATHI and ATLO) and processing them through a momentum filter. It aims to identify "breadth thrusts" or exhaustion points before they become obvious on a standard price chart.
Key ComponentsCustom Data Inputs: By default, it uses New Highs and New Lows tickers. You can toggle between calculating the Net difference (Highs minus Lows) or a Ratio (Highs divided by Lows).
Dual Mode Logic:Raw Mode: Visualizes the raw spread between highs and lows.Momentum Mode: Applies a McClellan-style calculation (Fast EMA minus Slow EMA) to show the rate of change in market breadth.Signal Line: Includes a 9-period EMA (Signal Line) to help identify trend shifts and provide crossover alerts.
Visual InterpretationThe indicator is displayed in a separate pane below the price chart:ElementDescription
Teal ColumnsIndicate that the breadth momentum is increasing (bullish divergence or strengthening trend).
Maroon Columns Indicate that the breadth momentum is decreasing (bearish divergence or weakening trend).Orange LineThe Signal Line; used to smooth out noise and provide entry/exit triggers.Zero LineThe "neutral" mark. Values above zero generally suggest bullish internal health; values below suggest bearish.
Identifying Divergences
If the S&P 500 is making new price highs, but the Breadth Momentum histogram is making lower highs, it suggests the rally is losing participation. This is often a precursor to a market correction.
Momentum Crossovers
A common signal is the "Signal Line Cross." When the columns cross above the orange Signal Line, it indicates a short-term surge in market participation (a "Thrust").
Mean Reversion
Extreme extensions away from the Zero Line (either positive or negative) can signal that the market is overbought or oversold on an internal level, regardless of what the price action looks like.
Settings & Inputs
New Highs/Lows Ticker: Ensure these match the symbols provided by your broker (e.g., HI_NY or ATHI).
Fast/Slow EMA: Standard settings are 19 and 39 (McClellan defaults), but these can be tightened for faster scalping or widened for long-term trend following.
Show Momentum: Toggle this off if you simply want to see the raw "Net Highs" data without the EMA smoothing.
Dynamic Gann Fan & Cycle - Lite FrameworkFree Lite edition of a Gann-inspired structure framework.
Plots pivot-based Gann fan angles to visualize potential support/resistance “rails,” and highlights momentum regimes when price rides key angles (2x1 / 3x1).
This is not a buy/sell signal tool — it’s designed to provide chart context for discretionary traders studying structure.
Dual-Scale MACDDual-Scale MACD is a dual-timeframe momentum indicator that displays a scaled short-term MACD together with a long-term MACD in the same pane.
The short-term MACD can be amplified by a configurable scale ratio, allowing its momentum structure to be visually aligned with the long-term MACD.
All EMA parameters are fully configurable, making this indicator suitable for experimentation with multi-cycle momentum resonance.
Features
Two independent MACD systems (short-term + long-term)
Fully configurable EMA parameters
Adjustable scale ratio for visual alignment
Clean histogram + top-layer signal line
Use cases
Multi-cycle momentum comparison
Trend confirmation & divergence analysis
Studying MACD resonance across time scales
This indicator is intended for analytical and educational purposes.
Apex Wallet - Adaptive Commodity Channel Index (CCI) & HTF TrendOverview The Apex Wallet Commodity Channel Index (CCI) is a professional-grade momentum oscillator designed to identify cyclical trends and overbought/oversold conditions with an integrated trend-filtering engine. This script enhances the classic CCI by adding multi-timeframe trend analysis and adaptive calculation modes.
Adaptive Trading Presets The indicator automatically recalibrates its internal periods based on your selected Trading Mode:
Scalping: Uses fast-response settings (CCI 14, Signal 6, Trend 50) for lower timeframes.
Day Trading: Standard balanced settings (CCI 20, Signal 9, Trend 100).
Swing: Long-term filters (CCI 34, Signal 14, Trend 200) to capture major market waves.
Key Features:
Higher Timeframe (HTF) Trend Bias: Optional background shading based on a customizable Higher Timeframe (e.g., 1H trend while trading on 5m) to ensure you always trade in the direction of the "Big Picture".
Market Trend Coloring: The CCI Signal line dynamically changes color (Green/Red/Gray) based on local market momentum relative to its moving average.
Visual Clarity: Features standard CCI level bands (+100, 0, -100) with professional aesthetics for easy reading.
How to Use:
Select your preferred Trading Mode in the settings.
Enable HTF Background to visualize the dominant trend from a higher timeframe.
Look for CCI crosses or signal line color changes while the background confirms the overall market bias.
