AI Adaptive Oscillator [PhenLabs]📊 Algorithmic Adaptive Oscillator
Version: PineScript™ v6
📌 Description
The AI Adaptive Oscillator is a sophisticated technical indicator that employs ensemble learning and adaptive weighting techniques to analyze market conditions. This innovative oscillator combines multiple traditional technical indicators through an AI-driven approach that continuously evaluates and adjusts component weights based on historical performance. By integrating statistical modeling with machine learning principles, the indicator adapts to changing market dynamics, providing traders with a responsive and reliable tool for market analysis.
🚀 Points of Innovation:
Ensemble learning framework with adaptive component weighting
Performance-based scoring system using directional accuracy
Dynamic volatility-adjusted smoothing mechanism
Intelligent signal filtering with cooldown and magnitude requirements
Signal confidence levels based on multi-factor analysis
🔧 Core Components
Ensemble Framework : Combines up to five technical indicators with performance-weighted integration
Adaptive Weighting : Continuous performance evaluation with automated weight adjustment
Volatility-Based Smoothing : Adapts sensitivity based on current market volatility
Pattern Recognition : Identifies potential reversal patterns with signal qualification criteria
Dynamic Visualization : Professional color schemes with gradient intensity representation
Signal Confidence : Three-tiered confidence assessment for trading signals
🔥 Key Features
The indicator provides comprehensive market analysis through:
Multi-Component Ensemble : Integrates RSI, CCI, Stochastic, MACD, and Volume-weighted momentum
Performance Scoring : Evaluates each component based on directional prediction accuracy
Adaptive Smoothing : Automatically adjusts based on market volatility
Pattern Detection : Identifies potential reversal patterns in overbought/oversold conditions
Signal Filtering : Prevents excessive signals through cooldown periods and minimum change requirements
Confidence Assessment : Displays signal strength through intuitive confidence indicators (average, above average, excellent)
🎨 Visualization
Gradient-Filled Oscillator : Color intensity reflects strength of market movement
Clear Signal Markers : Distinct bullish and bearish pattern signals with confidence indicators
Range Visualization : Clean representation of oscillator values from -6 to 6
Zero Line : Clear demarcation between bullish and bearish territory
Customizable Colors : Color schemes that can be adjusted to match your chart style
Confidence Symbols : Intuitive display of signal confidence (no symbol, +, or ++) alongside direction markers
📖 Usage Guidelines
⚙️ Settings Guide
Color Settings
Bullish Color
Default: #2b62fa (Blue)
This setting controls the color representation for bullish movements in the oscillator. The color appears when the oscillator value is positive (above zero), with intensity indicating the strength of the bullish momentum. A brighter shade indicates stronger bullish pressure.
Bearish Color
Default: #ce9851 (Amber)
This setting determines the color representation for bearish movements in the oscillator. The color appears when the oscillator value is negative (below zero), with intensity reflecting the strength of the bearish momentum. A more saturated shade indicates stronger bearish pressure.
Signal Settings
Signal Cooldown (bars)
Default: 10
Range: 1-50
This parameter sets the minimum number of bars that must pass before a new signal of the same type can be generated. Higher values reduce signal frequency and help prevent overtrading during choppy market conditions. Lower values increase signal sensitivity but may generate more false positives.
Min Change For New Signal
Default: 1.5
Range: 0.5-3.0
This setting defines the minimum required change in oscillator value between consecutive signals of the same type. It ensures that new signals represent meaningful changes in market conditions rather than minor fluctuations. Higher values produce fewer but potentially higher-quality signals, while lower values increase signal frequency.
AI Core Settings
Base Length
Default: 14
Minimum: 2
This fundamental setting determines the primary calculation period for all technical components in the ensemble (RSI, CCI, Stochastic, etc.). It represents the lookback window for each component’s base calculation. Shorter periods create a more responsive but potentially noisier oscillator, while longer periods produce smoother signals with potential lag.
Adaptive Speed
Default: 0.1
Range: 0.01-0.3
Controls how quickly the oscillator adapts to new market conditions through its volatility-adjusted smoothing mechanism. Higher values make the oscillator more responsive to recent price action but potentially more erratic. Lower values create smoother transitions but may lag during rapid market changes. This parameter directly influences the indicator’s adaptiveness to market volatility.
Learning Lookback Period
Default: 150
Minimum: 10
Determines the historical data range used to evaluate each ensemble component’s performance and calculate adaptive weights. This setting controls how far back the AI “learns” from past performance to optimize current signals. Longer periods provide more stable weight distribution but may be slower to adapt to regime changes. Shorter periods adapt more quickly but may overreact to recent anomalies.
Ensemble Size
Default: 5
Range: 2-5
Specifies how many technical components to include in the ensemble calculation.
Understanding The Interaction Between Settings
Base Length and Learning Lookback : The base length determines the reactivity of individual components, while the lookback period determines how their weights are adjusted. These should be balanced according to your timeframe - shorter timeframes benefit from shorter base lengths, while the lookback should generally be 10-15 times the base length for optimal learning.
Adaptive Speed and Signal Cooldown : These settings control sensitivity from different angles. Increasing adaptive speed makes the oscillator more responsive, while reducing signal cooldown increases signal frequency. For conservative trading, keep adaptive speed low and cooldown high; for aggressive trading, do the opposite.
Ensemble Size and Min Change : Larger ensembles provide more stable signals, allowing for a lower minimum change threshold. Smaller ensembles might benefit from a higher threshold to filter out noise.
Understanding Signal Confidence Levels
The indicator provides three distinct confidence levels for both bullish and bearish signals:
Average Confidence (▲ or ▼) : Basic signal that meets the minimum pattern and filtering criteria. These signals indicate potential reversals but with moderate confidence in the prediction. Consider using these as initial alerts that may require additional confirmation.
Above Average Confidence (▲+ or ▼+) : Higher reliability signal with stronger underlying metrics. These signals demonstrate greater consensus among the ensemble components and/or stronger historical performance. They offer increased probability of successful reversals and can be traded with less additional confirmation.
Excellent Confidence (▲++ or ▼++) : Highest quality signals with exceptional underlying metrics. These signals show strong agreement across oscillator components, excellent historical performance, and optimal signal strength. These represent the indicator’s highest conviction trade opportunities and can be prioritized in your trading decisions.
Confidence assessment is calculated through a multi-factor analysis including:
Historical performance of ensemble components
Degree of agreement between different oscillator components
Relative strength of the signal compared to historical thresholds
✅ Best Use Cases:
Identify potential market reversals through oscillator extremes
Filter trade signals based on AI-evaluated component weights
Monitor changing market conditions through oscillator direction and intensity
Confirm trade signals from other indicators with adaptive ensemble validation
Detect early momentum shifts through pattern recognition
Prioritize trading opportunities based on signal confidence levels
Adjust position sizing according to signal confidence (larger for ++ signals, smaller for standard signals)
⚠️ Limitations
Requires sufficient historical data for accurate performance scoring
Ensemble weights may lag during dramatic market condition changes
Higher ensemble sizes require more computational resources
Performance evaluation quality depends on the learning lookback period length
Even high confidence signals should be considered within broader market context
💡 What Makes This Unique
Adaptive Intelligence : Continuously adjusts component weights based on actual performance
Ensemble Methodology : Combines strength of multiple indicators while minimizing individual weaknesses
Volatility-Adjusted Smoothing : Provides appropriate sensitivity across different market conditions
Performance-Based Learning : Utilizes historical accuracy to improve future predictions
Intelligent Signal Filtering : Reduces noise and false signals through sophisticated filtering criteria
Multi-Level Confidence Assessment : Delivers nuanced signal quality information for optimized trading decisions
🔬 How It Works
The indicator processes market data through five main components:
Ensemble Component Calculation :
Normalizes traditional indicators to consistent scale
Includes RSI, CCI, Stochastic, MACD, and volume components
Adapts based on the selected ensemble size
Performance Evaluation :
Analyzes directional accuracy of each component
Calculates continuous performance scores
Determines adaptive component weights
Oscillator Integration :
Combines weighted components into unified oscillator
Applies volatility-based adaptive smoothing
Scales final values to -6 to 6 range
Signal Generation :
Detects potential reversal patterns
Applies cooldown and magnitude filters
Generates clear visual markers for qualified signals
Confidence Assessment :
Evaluates component agreement, historical accuracy, and signal strength
Classifies signals into three confidence tiers (average, above average, excellent)
Displays intuitive confidence indicators (no symbol, +, ++) alongside direction markers
💡 Note:
The AI Adaptive Oscillator performs optimally when used with appropriate timeframe selection and complementary indicators. Its adaptive nature makes it particularly valuable during changing market conditions, where traditional fixed-weight indicators often lose effectiveness. The ensemble approach provides a more robust analysis by leveraging the collective intelligence of multiple technical methodologies. Pay special attention to the signal confidence indicators to optimize your trading decisions - excellent (++) signals often represent the most reliable trade opportunities.
Wyszukaj w skryptach "oscillator"
Adaptive DEMA Momentum Oscillator (ADMO)Overview:
The Adaptive DEMA Momentum Oscillator (ADMO) is an open-source technical analysis tool developed to measure market momentum using a Double Exponential Moving Average (DEMA) and adaptive standard deviation. By dynamically combining price deviation from the moving average with normalized standard deviation, ADMO provides traders with a powerful way to interpret market conditions.
Key Features:
Double Exponential Moving Average (DEMA):
The core calculation of the indicator is based on DEMA, which is known for being more responsive to price changes compared to traditional moving averages. This makes the ADMO capable of capturing trend momentum effectively.
Standard Deviation Integration:
A normalized standard deviation is used to adaptively weight the oscillator. This makes the indicator more sensitive to market volatility, enhancing responsiveness during high volatility and reducing sensitivity during calmer periods.
Oscillator Representation:
The final oscillator value is derived from the combination of the DEMA-based Z-score and the normalized standard deviation. This final value is visualized as a color-coded histogram, reflecting bullish or bearish momentum.
Color-Coded Histogram:
Bullish Momentum: Values above zero are colored using a customizable bullish color (default: light green).
Bearish Momentum: Values below zero are colored using a customizable bearish color (default: red).
How It Works:
Inputs:
DEMA Length: Defines the period used for calculating the Double Exponential Moving Average. It can be adjusted from 1 to 200 to suit different trading styles.
Standard Deviation Length: Sets the lookback period for standard deviation calculations, which influences the responsiveness of the oscillator.
Standard Deviation Weight (StdDev Weight): Controls the weight given to the normalized standard deviation, allowing customization of the oscillator's sensitivity to volatility.
Calculation Steps:
Double Exponential Moving Average Calculation:
The DEMA is calculated using two exponential moving averages, which helps in reducing lag compared to a simple moving average.
Z-score Calculation:
The Z-score is derived by comparing the difference between the DEMA and its smoothed average (LSMA) to the standard deviation. This indicates how far the current value is from the mean in units of standard deviation.
Normalized Standard Deviation:
The standard deviation is normalized by subtracting the mean standard deviation and dividing by the standard deviation of the values. This helps to make the oscillator adaptive to recent changes in volatility.
Final Oscillator Value:
The final value is calculated by multiplying the Z-score with a factor based on the normalized standard deviation, resulting in a momentum indicator that adapts to different market conditions.
Visualization:
Histogram: The oscillator is plotted as a histogram, with color-coded bars showing the strength and direction of market momentum.
Positive (bullish) values are shown in green, indicating upward momentum.
Negative (bearish) values are shown in red, indicating downward momentum.
Zero Line: A zero line is plotted to provide a reference point, helping users quickly determine whether the current momentum is bullish or bearish.
Example Use Cases:
Momentum Identification:
ADMO helps identify the current market momentum by dynamically adapting to changes in market volatility. When the histogram is above zero and green, it indicates bullish conditions, whereas values below zero and red suggest bearish momentum.
Volatility-Adjusted Signals:
The normalized standard deviation weighting allows the ADMO to provide more reliable signals during different market conditions. This makes it particularly useful for traders who want to be responsive to market volatility while avoiding false signals.
Trend Confirmation and Divergence:
ADMO can be used to confirm the strength of a trend or identify potential divergences between price and momentum. This helps traders spot potential reversal points or continuation signals.
Summary:
The Adaptive DEMA Momentum Oscillator (ADMO) offers a unique approach by combining momentum analysis with adaptive standard deviation. The integration of DEMA makes it responsive to price changes, while the standard deviation adjustment helps it stay relevant in both high and low volatility environments. It's a versatile tool for traders who need an adaptive, momentum-based approach to technical analysis.
Feel free to explore the code and adapt it to your trading strategy. The open-source nature of this tool allows you to adjust the settings and visualize the output to fit your personal trading preferences.
Momentum Oscillator, Divergences & Signals [TrendAlpha]The "Momentum, Real Time Divergences & Signals " indicator is designed to provide traders with insights into market momentum, identify potential divergences, and generate buy and sell signals. It offers a comprehensive set of features to assist traders in making informed trading decisions.
The indicator starts by calculating the momentum oscillator based on user-defined parameters.
- Traders can adjust the "Length" parameter to customize the sensitivity of the oscillator. The default value is set to 7, but it can be modified according to individual preferences.
- The "Source" parameter allows traders to select the input source for the oscillator calculation, with the default being the closing price of the asset.
- Traders have the option to display divergence lines by switching on the "Show Lines" parameter. This feature helps identify potential divergences between the oscillator and the price.
The oscillator is calculated using a two-step process. First, a smoothing function is applied to the source data using the "sma" (simple moving average) function. Then, the rate of change is computed over the specified length using the "mom" (momentum) function. Positive oscillator values indicate upward momentum, while negative values indicate downward momentum.
The indicator also generates buy and sell signals by identifying bullish and bearish divergences. A bullish divergence occurs when the oscillator is negative and crosses above zero, while a bearish divergence occurs when the oscillator is positive and crosses below zero. The indicator checks for specific conditions to confirm the divergences, such as comparing the current oscillator value with the previous value and validating the corresponding price action.
When a bullish or bearish divergence is detected, the indicator plots circles to highlight these signals on the chart. A green circle indicates a bullish signal, suggesting a potential buying opportunity, while a red circle indicates a bearish signal, suggesting a potential selling opportunity. In addition to circles, the indicator also displays labels to provide further clarity on the signals. A "Buy" label is shown for bullish signals, and a "Sell" label is shown for bearish signals.
To visually represent the divergences, the indicator plots lines connecting the corresponding points on the oscillator. A green line is drawn for bullish divergences, while a red line is drawn for bearish divergences. Traders can easily observe the divergence patterns and their relationships with the price action, aiding them in making trading decisions.
- The indicator also includes alert conditions for both bullish and bearish divergences. Traders can set up alerts to receive notifications when potential divergences occur, allowing them to take timely action.
SuperSmoother MA OscillatorSuperSmoother MA Oscillator - Ehlers-Inspired Lag-Minimized Signal Framework
Overview
The SuperSmoother MA Oscillator is a crossover and momentum detection framework built on the pioneering work of John F. Ehlers, who introduced digital signal processing (DSP) concepts into technical analysis. Traditional moving averages such as SMA and EMA are prone to two persistent flaws: excessive lag, which delays recognition of trend shifts, and high-frequency noise, which produces unreliable whipsaw signals. Ehlers’ SuperSmoother filter was designed to specifically address these flaws by creating a low-pass filter with minimal lag and superior noise suppression, inspired by engineering methods used in communications and radar systems.
This oscillator extends Ehlers’ foundation by combining the SuperSmoother filter with multi-length moving average oscillation, ATR-based normalization, and dynamic color coding. The result is a tool that helps traders identify market momentum, detect reliable crossovers earlier than conventional methods, and contextualize volatility and phase shifts without being distracted by transient price noise.
Unlike conventional oscillators, which either oversimplify price structure or overload the chart with reactive signals, the SuperSmoother MA Oscillator is designed to balance responsiveness and stability. By preprocessing price data with the SuperSmoother filter, traders gain a signal framework that is clean, robust, and adaptable across assets and timeframes.
Theoretical Foundation
Traditional MA oscillators such as MACD or dual-EMA systems react to raw or lightly smoothed price inputs. While effective in some conditions, these signals are often distorted by high-frequency oscillations inherent in market data, leading to false crossovers and poor timing. The SuperSmoother approach modifies this dynamic: by attenuating unwanted frequencies, it preserves structural price movements while eliminating meaningless noise.
This is particularly useful for traders who need to distinguish between genuine market cycles and random short-term price flickers. In practical terms, the oscillator helps identify:
Early trend continuations (when fast averages break cleanly above/below slower averages).
Preemptive breakout setups (when compressed oscillator ranges expand).
Exhaustion phases (when oscillator swings flatten despite continued price movement).
Its multi-purpose design allows traders to apply it flexibly across scalping, day trading, swing setups, and longer-term trend positioning, without needing separate tools for each.
The oscillator’s visual system - fast/slow lines, dynamic coloration, and zero-line crossovers - is structured to provide trend clarity without hiding nuance. Strong green/red momentum confirms directional conviction, while neutral gray phases emphasize uncertainty or low conviction. This ensures traders can quickly gauge the market state without losing access to subtle structural signals.
How It Works
The SuperSmoother MA Oscillator builds signals through a layered process:
SuperSmoother Filtering (Ehlers’ Method)
At its core lies Ehlers’ two-pole recursive filter, mathematically engineered to suppress high-frequency components while introducing minimal lag. Compared to traditional EMA smoothing, the SuperSmoother achieves better spectral separation - it allows meaningful cyclical market structures to pass through, while eliminating erratic spikes and aliasing. This makes it a superior preprocessing stage for oscillator inputs.
Fast and Slow Line Construction
Within the oscillator framework, the filtered price series is used to build two internal moving averages: a fast line (short-term momentum) and a slow line (longer-term directional bias). These are not plotted directly on the chart - instead, their relationship is transformed into the oscillator values you see.
The interaction between these two internal averages - crossovers, separation, and compression - forms the backbone of trend detection:
Uptrend Signal : Fast MA rises above the slow MA with expanding distance, generating a positive oscillator swing.
Downtrend Signal : Fast MA falls below the slow MA with widening divergence, producing a negative oscillator swing.
Neutral/Transition : Lines compress, flattening the oscillator near zero and often preceding volatility expansion.
This design ensures traders receive the information content of dual-MA crossovers while keeping the chart visually clean and focused on the oscillator’s dynamics.
ATR-Based Normalization
Markets vary in volatility. To ensure the oscillator behaves consistently across assets, ATR (Average True Range) normalization scales outputs relative to prevailing volatility conditions. This prevents the oscillator from appearing overly sensitive in calm markets or too flat during high-volatility regimes.
Dynamic Color Coding
Color transitions reflect underlying market states:
Strong Green : Bullish alignment, momentum expanding.
Strong Red : Bearish alignment, momentum expanding.
These visual cues allow traders to quickly gauge trend direction and strength at a glance, with expanding colors indicating increasing conviction in the underlying momentum.
Interpretation
The oscillator offers a multi-dimensional view of price dynamics:
Trend Analysis : Fast/slow line alignment and zero-line interactions reveal trend direction and strength. Expansions indicate momentum building; contractions flag weakening conditions or potential reversals.
Momentum & Volatility : Rapid divergence between lines reflects increasing momentum. Compression highlights periods of reduced volatility and possible upcoming expansion.
Cycle Awareness : Because of Ehlers’ DSP foundation, the oscillator captures market cycles more cleanly than conventional MA systems, allowing traders to anticipate turning points before raw price action confirms them.
Divergence Detection : When oscillator momentum fades while price continues in the same direction, it signals exhaustion - a cue to tighten stops or anticipate reversals.
By focusing on filtered, volatility-adjusted signals, traders avoid overreacting to noise while gaining early access to structural changes in momentum.
Strategy Integration
The SuperSmoother MA Oscillator adapts across multiple trading approaches:
Trend Following
Enter when fast/slow alignment is strong and expanding:
A fast line crossing above the slow line with expanding green signals confirms bullish continuation.
Use ATR-normalized expansion to filter entries in line with prevailing volatility.
Breakout Trading
Periods of compression often precede breakouts:
A breakout occurs when fast lines diverge decisively from slow lines with renewed green/red strength.
Exhaustion and Reversals
Oscillator divergence signals weakening trends:
Flattening momentum while price continues trending may indicate overextension.
Traders can exit or hedge positions in anticipation of corrective phases.
Multi-Timeframe Confluence
Apply the oscillator on higher timeframes to confirm the directional bias.
Use lower timeframes for refined entries during compression → expansion transitions.
Technical Implementation Details
SuperSmoother Algorithm (Ehlers) : Recursive two-pole filter minimizes lag while removing high-frequency noise.
Oscillator Framework : Fast/slow MAs derived from filtered prices.
ATR Normalization : Ensures consistent amplitude across market regimes.
Dynamic Color Engine : Aligns visual cues with structural states (expansion and contraction).
Multi-Factor Analysis : Combines crossover logic, volatility context, and cycle detection for robust outputs.
This layered approach ensures the oscillator is highly responsive without overloading charts with noise.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Normalize with moderate ATR scaling; focus on slow-line confirmation.
Equities : Balance responsiveness with smoothing; useful for capturing sector rotations.
Cryptocurrency : Higher ATR multipliers recommended due to volatility.
Futures/Indices : Lower frequency settings highlight structural trends.
Timeframe Optimization:
Scalping (1-5min) : Higher sensitivity, prioritize fast-line signals.
Intraday (15m-1h) : Balance between fast/slow expansions.
Swing (4h-Daily) : Focus on slow-line momentum with fast-line timing.
Position (Daily-Weekly) : Slow lines dominate; fast lines highlight cycle shifts.
Performance Characteristics
High Effectiveness:
Trending environments with moderate-to-high volatility.
Assets with steady liquidity and clear cyclical structures.
Reduced Effectiveness:
Flat/choppy conditions with little directional bias.
Ultra-short timeframes (<1m), where noise dominates.
Integration Guidelines
Confluence : Combine with liquidity zones, order blocks, and volume-based indicators for confirmation.
Risk Management : Place stops beyond slow-line thresholds or ATR-defined zones.
Dynamic Trade Management : Use expansions/contractions to scale position sizes or tighten stops.
Multi-Timeframe Confirmation : Filter lower-timeframe entries with higher-timeframe momentum states.
Disclaimer
The SuperSmoother MA Oscillator is an advanced trend and momentum analysis tool, not a guaranteed profit system. Its effectiveness depends on proper parameter settings per asset and disciplined risk management. Traders should use it as part of a broader technical framework and not in isolation.
S2BU2 Volume Oscillator (Improved)Fair Use:
Please do not take my work and sell it under your own name. This was created to benefit everyone - not one person. Feel free however to use it as part of whatever work you wish to sell (of course i would applaud also giving ideas away for free - your choice though ;)
What it is:
The Basis for this Indicator was the original Volume Oscillator. I added Averages for Highs and Lows to make it easier to see relatively over- or undersupplied zones.
I also modified the oscillator to use a fast and a slow moving average à la MACD on itself to get a cleaner and earlier signal for when to expect a big move.
How it works:
A falling MA-line - especially if beneath the Signal-line indicates weakening Strength. Movements made during this time will barely move the needle.
A rising MA-line - especially if above the Signal-line, indicates increasing strength. Movements made during this time will be relatively considerable.
Crossovers above the average High/ below the average Low are especially relevant.
How to use:
Note this is only a recommendation and not advice. Feel free to experiment and adjust the indicator to fit your tradingstyle. This is only my personal setup. Feel free to share your findings.
Best used in combination with another Indicator that gives impulse direction, like for example my Stochastic Momentum Convergence Divergence (). You may also use any other indicator that works for you for this purpose - i am biased towards my own work though :D
What you want to see is a fresh direction-signal followed by a rising MA-line in the Volume Oscillator. For confirmation you can wait until the Volume Oscillator also has a crossover(up only, do not use the crossdown!) between MA- and Signal-line. Best results should be achieved if the MA-line was well below the averageLow-line. Trenddirection may change even while the Volume continuously goes up. Volume is direction agnostic. Always keep an eye on your direction indicator as changes can and will occur. These will be equally as violent and often longer lived than the previous direction you caught - you will lose a lot more than you gain if you do not keep track of that! This Indicator will help you to identify when not to waste your time on a trade, it will not be a magic pill that you can use to set and forget.
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.
Aroon Oscillator [BigBeluga]Aroon Oscillator with Mean Reversion & Trend Signals is a versatile tool that helps traders identify both trend direction and potential mean reversion points. The core Aroon Oscillator tracks the strength of a trend by measuring how long it has been since a high or low price occurred within a specified period. This oscillator provides trend-following signals (LONG/SHORT) along with mean reversion signals, giving traders both the ability to ride trends and anticipate reversals.
The unique feature of this indicator is the Mean Reversion Signals, marked with dots on the main chart, indicating potential points where the trend might reverse or retrace. In addition, trend-following signals (LONG and SHORT) are plotted directly on the chart, providing clear entry and exit points when a trend is beginning or ending.
🔵 IDEA
The Aroon Oscillator with Mean Reversion indicator provides a combined approach of trend analysis and mean reversion. The core idea is to track the health and momentum of trends, while also identifying when those trends might reverse or slow down. This dual approach allows traders to both follow the prevailing market direction and also capture mean reversion opportunities.
The oscillator is smoothed with John Ehlers' Zero Lag function , which helps reduce noise and improves signal clarity by removing lag without sacrificing the indicator's responsiveness.
The indicator uses color-coded signals and an easy-to-read oscillator to visually represent different types of signals on the chart. This makes it easy for traders to spot important changes in market trends and take action based on both the trend-following and mean reversion aspects of the indicator.
🔵 KEY FEATURES & USAGE
Trend Following Signals (LONG/SHORT):
In addition to mean reversion signals, the indicator also provides clear trend-following signals. LONG signals (green arrows) are plotted when the oscillator crosses above zero, indicating a potential uptrend. Conversely, SHORT signals (blue arrows) are plotted when the oscillator crosses below zero, signaling a potential downtrend.
Mean Reversion Signals:
This indicator features unique mean reversion signals, represented by dots on the main chart. These signals occur when the oscillator crosses over or under a smoother signal line, indicating that the current trend might be losing strength and a reversal or retracement is possible. Green dots represent a possible upward reversion, while blue dots signal a potential downward reversion.
Color-Coded Signals and Oscillator:
The Aroon Oscillator is color-coded to make it visually easier for traders to differentiate between trends and mean reversion signals. When the oscillator is above zero, the area is filled with green, and when it is below zero, the area is filled with blue. This visual representation helps traders quickly identify the current market condition at a glance.
🔵 CUSTOMIZATION
Aroon Length & Smoothing: Control the sensitivity of the Aroon Oscillator by adjusting the lookback period and smoothing settings, allowing traders to fine-tune the indicator to match different market conditions.
Mean Reversion Signals: Enable or disable mean reversion signals based on your trading preferences. Adjust the signal line length to control when these reversal signals are triggered.
Color Customization: Customize the colors for the oscillator and signals to match your chart’s color scheme for better visual clarity.
Advanced Keltner Channel/Oscillator [MyTradingCoder]This indicator combines a traditional Keltner Channel overlay with an oscillator, providing a comprehensive view of price action, trend, and momentum. The core of this indicator is its advanced ATR calculation, which uses statistical methods to provide a more robust measure of volatility.
Starting with the overlay component, the center line is created using a biquad low-pass filter applied to the chosen price source. This provides a smoother representation of price than a simple moving average. The upper and lower channel lines are then calculated using the statistically derived ATR, with an additional set of mid-lines between the center and outer lines. This creates a more nuanced view of price action within the channel.
The color coding of the center line provides an immediate visual cue of the current price momentum. As the price moves up relative to the ATR, the line shifts towards the bullish color, and vice versa for downward moves. This color gradient allows for quick assessment of the current market sentiment.
The oscillator component transforms the channel into a different perspective. It takes the price's position within the channel and maps it to either a normalized -100 to +100 scale or displays it in price units, depending on your settings. This oscillator essentially shows where the current price is in relation to the channel boundaries.
The oscillator includes two key lines: the main oscillator line and a signal line. The main line represents the current position within the channel, smoothed by an exponential moving average (EMA). The signal line is a further smoothed version of the oscillator line. The interaction between these two lines can provide trading signals, similar to how MACD is often used.
When the oscillator line crosses above the signal line, it might indicate bullish momentum, especially if this occurs in the lower half of the oscillator range. Conversely, the oscillator line crossing below the signal line could signal bearish momentum, particularly if it happens in the upper half of the range.
The oscillator's position relative to its own range is also informative. Values near the top of the range (close to 100 if normalized) suggest that price is near the upper Keltner Channel band, indicating potential overbought conditions. Values near the bottom of the range (close to -100 if normalized) suggest proximity to the lower band, potentially indicating oversold conditions.
One of the strengths of this indicator is how the overlay and oscillator work together. For example, if the price is touching the upper band on the overlay, you'd see the oscillator at or near its maximum value. This confluence of signals can provide stronger evidence of overbought conditions. Similarly, the oscillator hitting extremes can draw your attention to price action at the channel boundaries on the overlay.
The mid-lines on both the overlay and oscillator provide additional nuance. On the overlay, price action between the mid-line and outer line might suggest strong but not extreme momentum. On the oscillator, this would correspond to readings in the outer quartiles of the range.
The customizable visual settings allow you to adjust the indicator to your preferences. The glow effects and color coding can make it easier to quickly interpret the current market conditions at a glance.
Overlay Component:
The overlay displays Keltner Channel bands dynamically adapting to market conditions, providing clear visual cues for potential trend reversals, breakouts, and overbought/oversold zones.
The center line is a biquad low-pass filter applied to the chosen price source.
Upper and lower channel lines are calculated using a statistically derived ATR.
Includes mid-lines between the center and outer channel lines.
Color-coded based on price movement relative to the ATR.
Oscillator Component:
The oscillator component complements the overlay, highlighting momentum and potential turning points.
Normalized values make it easy to compare across different assets and timeframes.
Signal line crossovers generate potential buy/sell signals.
Advanced ATR Calculation:
Uses a unique method to compute ATR, incorporating concepts like root mean square (RMS) and z-score clamping.
Provides both an average and mode-based ATR value.
Customizable Visual Settings:
Adjustable colors for bullish and bearish moves, oscillator lines, and channel components.
Options for line width, transparency, and glow effects.
Ability to display overlay, oscillator, or both simultaneously.
Flexible Parameters:
Customizable inputs for channel width multiplier, ATR period, smoothing factors, and oscillator settings.
Adjustable Q factor for the biquad filter.
Key Advantages:
Advanced ATR Calculation: Utilizes a statistical method to generate ATR, ensuring greater responsiveness and accuracy in volatile markets.
Overlay and Oscillator: Provides a comprehensive view of price action, combining trend and momentum analysis.
Customizable: Adjust settings to fine-tune the indicator to your specific needs and trading style.
Visually Appealing: Clear and concise design for easy interpretation.
The ATR (Average True Range) in this indicator is derived using a sophisticated statistical method that differs from the traditional ATR calculation. It begins by calculating the True Range (TR) as the difference between the high and low of each bar. Instead of a simple moving average, it computes the Root Mean Square (RMS) of the TR over the specified period, giving more weight to larger price movements. The indicator then calculates a Z-score by dividing the TR by the RMS, which standardizes the TR relative to recent volatility. This Z-score is clamped to a maximum value (10 in this case) to prevent extreme outliers from skewing the results, and then rounded to a specified number of decimal places (2 in this script).
These rounded Z-scores are collected in an array, keeping track of how many times each value occurs. From this array, two key values are derived: the mode, which is the most frequently occurring Z-score, and the average, which is the weighted average of all Z-scores. These values are then scaled back to price units by multiplying by the RMS.
Now, let's examine how these values are used in the indicator. For the Keltner Channel lines, the mid lines (top and bottom) use the mode of the ATR, representing the most common volatility state. The max lines (top and bottom) use the average of the ATR, incorporating all volatility states, including less common but larger moves. By using the mode for the mid lines and the average for the max lines, the indicator provides a nuanced view of volatility. The mid lines represent the "typical" market state, while the max lines account for less frequent but significant price movements.
For the color coding of the center line, the mode of the ATR is used to normalize the price movement. The script calculates the difference between the current price and the price 'degree' bars ago (default is 2), and then divides this difference by the mode of the ATR. The resulting value is passed through an arctangent function and scaled to a 0-1 range. This scaled value is used to create a color gradient between the bearish and bullish colors.
Using the mode of the ATR for this color coding ensures that the color changes are based on the most typical volatility state of the market. This means that the color will change more quickly in low volatility environments and more slowly in high volatility environments, providing a consistent visual representation of price momentum relative to current market conditions.
Using a good IIR (Infinite Impulse Response) low-pass filter, such as the biquad filter implemented in this indicator, offers significant advantages over simpler moving averages like the EMA (Exponential Moving Average) or other basic moving averages.
At its core, an EMA is indeed a simple, single-pole IIR filter, but it has limitations in terms of its frequency response and phase delay characteristics. The biquad filter, on the other hand, is a two-pole, two-zero filter that provides superior control over the frequency response curve. This allows for a much sharper cutoff between the passband and stopband, meaning it can more effectively separate the signal (in this case, the underlying price trend) from the noise (short-term price fluctuations).
The improved frequency response of a well-designed biquad filter means it can achieve a better balance between smoothness and responsiveness. While an EMA might need a longer period to sufficiently smooth out price noise, potentially leading to more lag, a biquad filter can achieve similar or better smoothing with less lag. This is crucial in financial markets where timely information is vital for making trading decisions.
Moreover, the biquad filter allows for independent control of the cutoff frequency and the Q factor. The Q factor, in particular, is a powerful parameter that affects the filter's resonance at the cutoff frequency. By adjusting the Q factor, users can fine-tune the filter's behavior to suit different market conditions or trading styles. This level of control is simply not available with basic moving averages.
Another advantage of the biquad filter is its superior phase response. In the context of financial data, this translates to more consistent lag across different frequency components of the price action. This can lead to more reliable signals, especially when it comes to identifying trend changes or price reversals.
The computational efficiency of biquad filters is also worth noting. Despite their more complex mathematical foundation, biquad filters can be implemented very efficiently, often requiring only a few operations per sample. This makes them suitable for real-time applications and high-frequency trading scenarios.
Furthermore, the use of a more sophisticated filter like the biquad can help in reducing false signals. The improved noise rejection capabilities mean that minor price fluctuations are less likely to cause unnecessary crossovers or indicator movements, potentially leading to fewer false breakouts or reversal signals.
In the specific context of a Keltner Channel, using a biquad filter for the center line can provide a more stable and reliable basis for the entire indicator. It can help in better defining the overall trend, which is crucial since the Keltner Channel is often used for trend-following strategies. The smoother, yet more responsive center line can lead to more accurate channel boundaries, potentially improving the reliability of overbought/oversold signals and breakout indications.
In conclusion, this advanced Keltner Channel indicator represents a significant evolution in technical analysis tools, combining the power of traditional Keltner Channels with modern statistical methods and signal processing techniques. By integrating a sophisticated ATR calculation, a biquad low-pass filter, and a complementary oscillator component, this indicator offers traders a comprehensive and nuanced view of market dynamics.
The indicator's strength lies in its ability to adapt to varying market conditions, providing clear visual cues for trend identification, momentum assessment, and potential reversal points. The use of statistically derived ATR values for channel construction and the implementation of a biquad filter for the center line result in a more responsive and accurate representation of price action compared to traditional methods.
Furthermore, the dual nature of this indicator – functioning as both an overlay and an oscillator – allows traders to simultaneously analyze price trends and momentum from different perspectives. This multifaceted approach can lead to more informed decision-making and potentially more reliable trading signals.
The high degree of customization available in the indicator's settings enables traders to fine-tune its performance to suit their specific trading styles and market preferences. From adjustable visual elements to flexible parameter inputs, users can optimize the indicator for various trading scenarios and time frames.
Ultimately, while no indicator can predict market movements with certainty, this advanced Keltner Channel provides traders with a powerful tool for market analysis. By offering a more sophisticated approach to measuring volatility, trend, and momentum, it equips traders with valuable insights to navigate the complex world of financial markets. As with any trading tool, it should be used in conjunction with other forms of analysis and within a well-defined risk management framework to maximize its potential benefits.
Ichimoku Oscillator With Divergences [ChartPrime]The Ichimoku Oscillator is a trading indicator designed to streamline the interpretation of Ichimoku clouds. It aims to refine and condense the complexities of the Chikou (the lag line), presenting its implications in real-time through an oscillator format, beneficial for those familiar with Ichimoku components but to have a new interpretation of their indicators.
The basics of an Ichimoku:
Conversion Line (Tenkan-Sen): It represents a midpoint of the highest and lowest prices over a specific period, usually 9 periods, reflecting short-term price movements.
Base Line (Kijun-Sen): It acts similarly to the Conversion Line but over a longer period, typically 26 periods, representing medium-term price movements.
Leading Span A & B (Kumo): Span A is the average of the Conversion Line and Base Line, and Span B is the midpoint of the highest and lowest prices over a usually longer period, typically 52 periods. Their interaction denotes trend direction, and the cloud color changes depending on whether Span A is above or below Span B, indicating bullish or bearish market conditions, respectively.
Lagging Span (Chikou Span): It is the current closing price plotted 26 periods behind, assisting in confirming the trend direction and potential momentum.
Advantage of an Oscillator:
Utilizing the oscillator format allows traders to interpret market dynamics more efficiently by visualizing the momentum and trend strength in a bounded range, enabling quick assessments of overbought or oversold conditions. Creating this oscillator provides multiple advantageous; particularly in sideway markets, helping to identify potential reversal points and offering insights on market entries and exits. When building this oscillator we've put a focus on unique interpretations such as overbought and sold areas and divergences; otherwise not found in traditional Ichimoku techniques. It is important to note these divergences are naturally not 100% real time.
When the oscillator turns green; the market is in an uptrend, red for downtrend and yellow for a transitioning market. The center line and the inner most cloud represent a balanced market state.
Key Features & Input Parameters:
Signal Source: Allows the selection of the price data source for signal generation, such as closing prices, and it’s the foundational parameter upon which the oscillator functions.
Normalization Settings: Users can select the normalization mode (“All”, “Window”, or “Disabled”), influencing how the oscillator scales its values. When enabled, it will scale from 100 to -100, allowing the user to understand better the relative positioning of price data.
Smoothing: This indicator offers advanced smoothing features, with options for additional smoothing, allowing traders to adjust the signal's sensitivity to price movements.
Kumo & Chikou Visibility: Traders can customize the visibility settings of Kumo and Chikou, tailoring the display of each component to their preference, enabling a cleaner and more intuitive view of market conditions.
Color Coding: Each component and condition, like bullish or bearish states, can be color-coded, providing visual cues to enhance the interpretability of market trends and states.
Color on Conversion: The oscillator provides an option to color the signal based on the crossover of the conversion and base lines.
Divergence: The oscillator can detect and highlight regular and hidden bullish and bearish divergences between the signal and price, aiding traders in identifying potential trend reversals or continuations.
Alerts:
The list of inbuilt alerts are provided below:
Inside Cloud: The signal line is inside the cloud.
Up Out of Cloud: The signal line crossed above the cloud.
Down Out of Cloud: The signal line crossed below the cloud.
Future Kumo Cross Bullish: The future Kumo lines have crossed in a bullish manner.
Future Kumo Cross Bearish: The future Kumo lines have crossed in a bearish manner.
Current Kumo Cross Bullish: The current Kumo lines have crossed in a bullish manner.
Current Kumo Cross Bearish: The current Kumo lines have crossed in a bearish manner.
Conversion Base Bullish: The conversion line crossed above the base line.
Conversion Base Bearish: The conversion line crossed below the base line.
Signal Bullish on Conversion Base: The signal line crossed above the maximum of conversion and base lines.
Signal Bearish on Conversion Base: The signal line crossed below the minimum of conversion and base lines.
Chikou Bullish: The Chikou line crossed above zero.
Chikou Bearish: The Chikou line crossed below zero.
Signal Over Max: The signal line crossed above the max level.
Signal Over High: The signal line crossed above the high level.
Signal Under Min: The signal line crossed below the min level.
Signal Under Low: The signal line crossed below the low level.
Chikou Over Max: The Chikou line crossed above the max level.
Chikou Over High: The Chikou line crossed above the high level.
Chikou Under Min: The Chikou line crossed below the min level.
Chikou Under Low: The Chikou line crossed below the low level.
Signal Crossover MA: The signal line crossed over the moving average.
Signal Crossunder MA: The signal line crossed under the moving average.
Regular Bullish Divergence: Regular bullish divergence detected.
Hidden Bullish Divergence: Hidden bullish divergence detected.
Regular Bearish Divergence: Regular bearish divergence detected.
Hidden Bearish Divergence: Hidden bearish divergence detected.
Bounce off of Kumo Up: Bullish Bounce off of Kumo.
Bounce off of Kumo Down: Bearish Bounce off of Kumo.
By providing a cohesive visualization of the Ichimoku elements and market momentum within a bounded range, this oscillator is a unique tool and insight into markets.
Algorithmic Value Oscillator [CRYPTIK1]Algorithmic Value Oscillator
Introduction: What is the AVO? Welcome to the Algorithmic Value Oscillator (AVO), a powerful, modern momentum indicator that reframes the classic "overbought" and "oversold" concept. Instead of relying on a fixed lookback period like a standard RSI, the AVO measures the current price relative to a significant, higher-timeframe Value Zone .
This gives you a more contextual and structural understanding of price. The core question it answers is not just "Is the price moving up or down quickly?" but rather, " Where is the current price in relation to its recently established area of value? "
This allows traders to identify true "premium" (overbought) and "discount" (oversold) levels with greater accuracy, all presented with a clean, futuristic aesthetic designed for the modern trader.
The Core Concept: Price vs. Value The market is constantly trying to find equilibrium. The AVO is built on the principle that the high and low of a significant prior period (like the previous day or week) create a powerful area of perceived value.
The Value Zone: The range between the high and low of the selected higher timeframe.
Premium Territory (Distribution Zone): When the oscillator moves into the glowing pink/purple zone above +100, it is trading at a premium.
Discount Territory (Accumulation Zone): When the oscillator moves into the glowing teal/blue zone below -100, it is trading at a discount.
Key Features
1. Glowing Gradient Oscillator: The main oscillator line is a dynamic visual guide to momentum.
The line changes color smoothly from light blue to neon teal as bullish momentum increases.
It shifts from hot pink to bright purple as bearish momentum increases.
Multiple transparent layers create a professional "glow" effect, making the trend easy to see at a glance.
2. Dynamic Volatility Histogram: This histogram at the bottom of the indicator is a custom volatility meter. It has been engineered to be adaptive, ensuring that the visual differences between high and low volatility are always clear and dramatic, no matter your zoom level. It uses a multi-color gradient to visualize the intensity of market volatility.
3. Volatility Regime Dashboard: This simple on-screen table analyzes the histogram and provides a clear, one-word summary of the current market state: Compressing, Stable, or Expanding.
How to Use the AVO: Trading Strategies
1. Reversion Trading This is the most direct way to use the indicator.
Look for Buys: When the AVO line drops into the teal "Accumulation Zone" (below -100), the price is trading at a discount. Watch for the oscillator to form a bottom and start turning up as a signal that buying pressure is returning.
Look for Sells: When the AVO line moves into the pink "Distribution Zone" (above +100), the price is trading at a premium. Watch for the oscillator to form a peak and start turning down as a signal that selling pressure is increasing.
2. Best Practices & Settings
Timeframe Synergy: The AVO is most effective when your chart timeframe is lower than your selected "Value Zone Source." For example, if you trade on the 1-hour chart, set your Value Zone to "Previous Day."
Confirmation is Key: This indicator provides powerful context, but it should not be used in isolation. Always combine its readings with your primary analysis, such as market structure and support/resistance levels.
Sinusoidal Cycles OscillatorTitle: Sinusoidal Cycles Oscillator – Multi-Cycle Market Indicator
Description:
Discover market rhythm with the Sinusoidal Cycles Oscillator, a powerful tool for technical analysis and cyclical trading.
Three customizable cycles track short, medium, and long-term market oscillations.
Cycle 1 serves as the main reference wave with an optional mirror envelope.
Cycles 2 & 3 provide supporting harmonics for deeper insight.
Composite wave averages all cycles to reveal overall market phase.
Features:
Fully adjustable periods and amplitude.
Visualize tops, bottoms, and turning points at a glance.
Oscillator ranges from -1 to +1 with clear threshold guides.
Ideal for traders using cycle analysis, harmonic trading, or market timing.
Easy-to-read visual overlay and separate panel option.
Use it to:
Identify potential price reversals.
Compare market cycles across multiple timeframes.
Enhance timing and entry/exit decisions.
Smooth Price Oscillator [BigBeluga]The Smooth Price Oscillator by BigBeluga leverages John Ehlers' SuperSmoother filter to produce a clear and smooth oscillator for identifying market trends and mean reversion points. By filtering price data over two distinct periods, this indicator effectively removes noise, allowing traders to focus on significant signals without the clutter of market fluctuations.
🔵 KEY FEATURES & USAGE
● SuperSmoother-Based Oscillator:
This oscillator uses Ehlers' SuperSmoother filter, applied to two different periods, to create a smooth output that highlights price momentum and reduces market noise. The dual-period application enables a comparison of long-term and short-term price movements, making it suitable for both trend-following and reversion strategies.
// @function SuperSmoother filter based on Ehlers Filter
// @param price (float) The price series to be smoothed
// @param period (int) The smoothing period
// @returns Smoothed price
method smoother_F(float price, int period) =>
float step = 2.0 * math.pi / period
float a1 = math.exp(-math.sqrt(2) * math.pi / period)
float b1 = 2 * a1 * math.cos(math.sqrt(2) * step / period)
float c2 = b1
float c3 = -a1 * a1
float c1 = 1 - c2 - c3
float smoothed = 0.0
smoothed := bar_index >= 4
? c1 * (price + price ) / 2 + c2 * smoothed + c3 * smoothed
: price
smoothed
● Mean Reversion Signals:
The indicator identifies two types of mean reversion signals:
Simple Mean Reversion Signals: Triggered when the oscillator moves between thresholds of 1 and Overbought or between thresholds -1 and Ovesold, providing additional reversion opportunities. These signals are useful for capturing shorter-term corrections in trending markets.
Strong Mean Reversion Signals: Triggered when the oscillator above the overbought (upper band) or below oversold (lower band) thresholds, indicating a strong reversal point. These signals are marked with a "+" symbol on the chart for clear visibility.
Both types of signals are plotted on the oscillator and the main chart, helping traders to quickly identify potential trade entries or exits.
● Dynamic Bands and Thresholds:
The oscillator includes overbought and oversold bands based on a dynamically calculated standard deviation and EMA. These bands provide visual boundaries for identifying extreme price conditions, helping traders anticipate potential reversals at these levels.
● Real-Time Labels:
Labels are displayed at key thresholds and bands to indicate the oscillator’s status: "Overbought," "Oversold," and "Neutral". Mean reversion signals are also displayed on the main chart, providing an at-a-glance summary of current indicator conditions.
● Customizable Threshold Levels:
Traders can adjust the primary threshold and smoothing length according to their trading style. A higher threshold can reduce signal frequency, while a lower setting will provide more sensitivity to market reversals.
The Smooth Price Oscillator by BigBeluga is a refined, noise-filtered indicator designed to highlight mean reversion points with enhanced clarity. By providing both strong and simple reversion signals, as well as dynamic overbought/oversold bands, this tool allows traders to spot potential reversals and trend continuations with ease. Its dual representation on the oscillator and the main price chart offers flexibility and precision for any trading strategy focused on capturing cyclical market movements.
Dynamic Rate of Change OscillatorDynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram
Detailed Description for Publication
The Dynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram is a sophisticated technical analysis tool designed to enhance your understanding of market momentum. Created using Pine Script v5 on the TradingView platform, this indicator integrates multiple Rate of Change (RoC) calculations into a unified momentum oscillator. The resulting data is displayed as a color-coded histogram, providing a clear visual representation of momentum changes.
Key Features and Functionality
Multi-Length RoC Calculation:
Short-term RoC: Calculated over a user-defined period (shortRoCLength), this captures variations in price momentum over a shorter duration, offering insights into the immediate price action.
Long-term RoC: This uses a longer period (longRoCLength) to provide a broader view of momentum, helping to smooth out short-term fluctuations and highlight more established trends.
Mid-term RoC: A weighted average of the short-term and long-term RoCs, the mid-term RoC (midRoCWeight) allows you to balance sensitivity and stability in the oscillator's behavior.
Weighted RoC Calculation:
The indicator calculates a single weighted average RoC by integrating short-term, long-term, and mid-term RoCs. The weighting factor can be adjusted to prioritize different market dynamics according to the trader’s strategy. This flexible approach enables the oscillator to remain applicable across diverse market conditions.
Oscillator Calculation and Smoothing:
The oscillator value is computed by subtracting a 14-period Weighted Moving Average (WMA) from the weighted RoC, which helps to normalize the oscillator, making it more responsive to changes in momentum.
The oscillator is then smoothed using a Simple Moving Average (SMA) over a user-defined period (smoothLength). This process reduces market noise, making the oscillator's signals clearer and easier to interpret.
Color-Coded Histogram:
The smoothed oscillator is displayed as a histogram, which is color-coded to reflect bullish or bearish momentum. You can customize the colors to match your charting style, with green typically representing upward momentum and red representing downward momentum.
The color-coded histogram allows for quick visual identification of momentum changes on the chart, aiding in your market analysis.
Zero-Line Reference:
A horizontal line at the zero level is plotted as a reference point. This zero-line helps in identifying when the histogram shifts from positive to negative or vice versa, which can be useful in understanding momentum shifts.
The zero-line offers a straightforward visual cue, making it easier to interpret the oscillator's signals in relation to market movements.
Customization and Versatility
The Dynamic RoC Oscillator with Histogram is designed with flexibility in mind, making it suitable for a wide range of trading styles, from short-term trading to longer-term analysis. Users have the ability to fine-tune the indicator’s input parameters to align with their specific needs:
Adjustable RoC Periods: Customize the short-term and long-term RoC lengths to match the timeframes you focus on.
Weighted Sensitivity: Adjust the mid-term RoC weight to emphasize different aspects of momentum according to your analysis approach.
Smoothing Options: Modify the smoothing moving average length to control the sensitivity of the oscillator, allowing you to balance responsiveness with noise reduction.
Use Cases
Momentum Analysis: Gain a clearer understanding of momentum changes within the market, which can aid in the evaluation of market trends.
Trend Analysis: The oscillator can help in assessing trends by highlighting when momentum is increasing or decreasing.
Chart Visualization: The color-coded histogram provides a visually intuitive method for monitoring momentum, helping you to more easily interpret market behavior.
Conclusion
The Dynamic Rate of Change (RoC) Oscillator with Color-Coded Histogram is a versatile and powerful tool for traders who seek a deeper analysis of market momentum. With its dynamic calculation methods and high degree of customization, this indicator can be tailored to suit a variety of trading strategies. By integrating it into your TradingView charts, you can enhance your technical analysis capabilities, gaining valuable insights into market momentum.
This indicator is easy to use and highly customizable, making it a valuable addition to any trader’s toolkit. Add it to your charts on the TradingView platform and start exploring its potential to enrich your market analysis.
KNN OscillatorOverview
The KNN Oscillator is an advanced technical analysis tool designed to help traders identify potential trend reversals and market momentum. Using the K-Nearest Neighbors (KNN) algorithm, this oscillator normalizes KNN values to create a dynamic and responsive indicator. The oscillator line changes color to reflect the market sentiment, providing clear visual cues for trading decisions.
Key Features
Dynamic Color Oscillator: The line changes color based on the oscillator value – green for positive, red for negative, and grey for neutral.
Advanced KNN Algorithm: Utilizes the K-Nearest Neighbors algorithm for precise trend detection.
Normalized Values: Ensures the oscillator values are normalized to align with the stock price range, making it applicable to various assets.
Easy Integration: Can be easily added to any TradingView chart for enhanced analysis.
How It Works
The KNN Oscillator leverages the K-Nearest Neighbors algorithm to calculate the average distance of the nearest neighbors over a specified period. These values are then normalized to match the stock price range, ensuring they are comparable across different assets. The oscillator value is derived by taking the difference between the normalized KNN values and the source price. The line's color changes dynamically to provide an immediate visual indication of the market's state:
Green: Positive values indicate upward momentum.
Red: Negative values indicate downward momentum.
Grey: Neutral values indicate a stable or consolidating market.
Usage Instructions
Trend Reversal Detection: Use the color changes to identify potential trend reversals. A shift from red to green suggests a bullish reversal, while a shift from green to red indicates a bearish reversal.
Momentum Analysis: The oscillator's value and color help gauge market momentum. Strong positive values (green) indicate strong upward momentum, while strong negative values (red) indicate strong downward momentum.
Market Sentiment: The dynamic color changes provide an easy-to-understand visual representation of market sentiment, helping traders make informed decisions quickly.
Confirmation Tool: Use the KNN Oscillator in conjunction with other technical indicators to confirm signals and improve the accuracy of your trades.
Scalability: Applicable to various timeframes and asset classes, making it a versatile tool for all types of traders.
Ultimate Balance OscillatorIntroducing the Ultimate Balance Oscillator: A Powerful Trading Indicator
Built upon the renowned Rate of Change (ROC), Relative Strength Index (RSI), Commodity Channel Index (CCI), Williams Percent Range, and Average Directional Index (ADX) from TradingView, this indicator equips traders with an unparalleled understanding of market dynamics.
What sets the Ultimate Balance Oscillator apart is its meticulous approach to weighting. Each component is assigned a weight that reflects its individual significance, while carefully mitigating the influence of highly correlated signals. This strategic weighting methodology ensures an unbiased and comprehensive representation of market sentiment, eliminating dominance by any single indicator.
Key Features and Benefits:
1. Comprehensive Market Analysis: The Ultimate Balance Oscillator provides a comprehensive view of market conditions, enabling traders to discern price trends, evaluate momentum shifts, identify overbought or oversold levels, and gauge the strength of prevailing trends. This holistic perspective empowers traders to make well-informed decisions based on a thorough understanding of the market.
2. Enhanced Signal Accuracy: With its refined weighting approach, the Ultimate Balance Oscillator filters out noise and emphasizes the most relevant information. This results in heightened signal accuracy, providing traders with a distinct advantage in identifying optimal entry and exit points. Say goodbye to unreliable signals and welcome a more precise and dependable trading experience.
3. Adaptability to Various Trading Scenarios: The Ultimate Balance Oscillator transcends the constraints of specific markets or timeframes. It seamlessly adapts to diverse trading scenarios, accommodating both short-term trades and long-term investments. Traders can customize this indicator to suit their preferred trading style and effortlessly navigate ever-changing market conditions.
4. Simplicity and Ease of Use: The Ultimate Balance Oscillator simplifies trading analysis by providing a single line on the chart. Its straightforward interpretation and seamless integration into trading strategies make decision-making effortless. By observing bullish or bearish crossovers with the moving average, recognizing overbought or oversold levels, and tracking the overall trend of the oscillator, traders can make well-informed decisions with confidence.
5. Real-time Alerts: Stay ahead of the game with the Ultimate Balance Oscillator's customizable alert system. Traders can set up personalized alerts for bullish or bearish crossovers, breaches of overbought or oversold thresholds, or any specific events that align with their trading strategy. Real-time notifications enable timely action, ensuring traders never miss lucrative trading opportunities.
The Ultimate Balance Oscillator is a robust trading companion, empowering traders to make shrewd and calculated decisions. Embrace its power and elevate your trading endeavors to new heights of precision and success. Discover the potential of the Ultimate Balance Oscillator and unlock a world of trading possibilities.
T3 OscillatorTL;DR - An Oscillator based on T3 moving average
The T3 moving average is a well known moving average created by Tim TIllson. Oscillator values are created by using the simple formula "source (close by default) - T3 moving average". Tim Tillson used a "volume factor" of 0.7 in his original T3 calculation. I changed this value to 0.618 and added the option to change it if needed/wanted. I also added alarms for zero line crossing upwards and downward, a smoothing option and custom time frames.
Compared to other oscillators like TSI, MACD etc. I observed better signals, especially in trending market situations, from the T3 oscillator (I tested Forex and Crypto).
Usage is simple: If the oscillator is above 0 it indicates a bearish trend. If below 0 it indicates a bullish trend. -> Really simple to use. However it can also be used to determine micro trends and reversals when combined with price action analysis. To keeps things simple I have not added a moving average like many other oscillators because I think it is confusing and does not help (in this particular case).
P.S. I haven't found a T3 oscillator on Trading View. Code is free - do whatever you want with it ;)
Bull/Bear Candle % Oscillator█ OVERVIEW
This script determines the proportion of bullish and bearish candles in a given sample size. It will produce an oscillator that fluctuates between 100 and -100, where values > 0 indicate more bullish candles in the sample and values < 0 indicate more bearish candles in the sample. Data produced by this oscillator is normalized around the 50% value, meaning that an even 50/50 split between bullish and bearish candles makes this oscillator produce 0; this oscillator indirectly represents the percent proportion of bullish and bearish candles in the sample (see HOW TO USE/INTERPRETATION OF DATA ).
It has two overarching settings: 'classic' and 'range'.
█ CONCEPTS
This script will cover concepts related to candlestick analysis, volumetric analysis, and lower timeframes.
Candlestick Analysis - The idea behind this script is to solely look at the candlesticks themselves and derive information from them in a given sample. It separates candles into two categories, bullish (close > open) and bearish (close < open).
If the indicator's setting is set to 'classic', the size of candles do not matter and all are assigned a value of 1 or 0.
If the indicator's setting is set to 'range', specific candle ranges modify the proportion of bullish/bearish values. Bullish candle values include all bullish candles in the set from their lows to the close, plus the lower wicks of all bearish candles. Bearish candle values include all bearish candles in the set from their highs to the close, plus the upper wicks of all bullish candles.
Volumetric Analysis - One of this script's features allows the user to modify the bullish and bearish candle proportions by its 'weight' determined by its volume compared to the sample set's total volume. Volumetric analysis for the 'range' setting are more complex than 'classic' as described below.
Lower Timeframes - For volumetric analysis to be done on candle wicks, there needed to be a way to determine how much volume had occurred in the wick by itself to find the weight of upper and lower wicks. To accomplish this, I employed PineScrypt's request.security_lower_tf function to grab OHLC values of lower timeframe candles (as well as volume) to determine how much volume had occurred in the wicks of the chart resolution's candle. The default OHLC values used here are the lows for upper wicks and highs for lower wicks. These OHLC values are then compared to the chart resolution candle's close to determine if the volume of that lower timeframe candle should be shifted to the wick weight or stay in the current weight of that candle. The reason 'low' and 'high' are used here is to guarantee that 100% of the volume of a lower timeframe candle had occurred in the wick of the candle at the current resolution (see LIMITATIONS ).
Bullish candles will exclude volume of all lower timeframe candles whose lows were greater than that candle's close. Bearish candles will exclude volume of all lower timeframe candles whose highs were less than that candle's close. These wick volumes are then divided by the volume of the sample set, and wick sizes are then multiplied by this weight before being added to their specific bullish/bearish sums (lower wicks to bullish and upper wicks to bearish).
█ FEATURES
There are 13 inputs for the user to modify the behavior/visual representation of this script.
Sample Length - This determines how many candles are in the sample set to find the proportion of bullish and bearish candles.
Colors and Invert Colors - There are three colors set by the user: a bullish color, neutral color, and bearish color. The oscillator plots two lines, one at 0 and another that represents the proportion of bullish or bearish candles in the sample set (we'll call this the 'signal line'). If the oscillator is above 0, bullish color is used, bearish otherwise. This script generates a gradient to color a filled area between the 0 line and the signal line based on the historical values of the oscillator itself and the signal line. For bullish values, the closer the signal line is to the max (or restricted max described below) that the oscillator has experienced, the more colored toward bullish color the shaded area will be, using the neutral color as a starting point. The same is applied to the bearish values using the bearish color.
There is an additional input to invert the colors so that the bearish color is associated with bullish values and vise-versa.
Calculation Type - This determines the overarching behavior of the oscillator and has two settings:
Classic - The weight of candles are either 1 if they occurred and 0 if not.
Range - The weight of candles is determined by the size of specific sections as described in CONCEPTS - Candlestick Analysis .
Volume Weighted - This enables modifying the weights of candles as described in CONCEPTS - Volumetric Analysis and Lower Timeframes based on which Calculation Type is used.
Wick Slice Resolution - This is the lower timeframe resolution that will be used to slice the chart resolution's candle when determining the volumetric weight of wicks. Lower timeframe resolutions like '1 minute' will yield more precise results as they will give more data points to go off of (see LIMITATIONS ).
Upper/Lower Wick Source - These two inputs allow the user to select which OHLC values to compare against the chart resolution's candle close when determining which lower timeframe candles will have their volumes associated with the wicks of candles being analyzed at the chart's resolution.
Restrict Min/Max Data and Restriction - This will restrict the maximum and minimum values that will be used for the signal line when comparing its value to previous oscillator values and change how the color gradient is generated for the indicator. Restriction is the number of candles back that will determine these maximum and minimum values.
Display Min/Max Guide - This will plot two lines that are colored the corresponding bullish and bearish colors which follow what the maximum and minimum values are currently for the oscillator.
█ HOW TO USE/INTERPRETATION OF DATA
As mentioned in the OVERVIEW section, this oscillator provides an indirect representation of the percent proportion of bullish or bearish candles in a given sample. If the oscillator reads 80, this does not mean that 80% of all candles in the sample were bullish . To find the percentage of candles that were bullish or bearish, the user needs to perform the following:
50% + ((|oscillator value| / 100) * 50)%
If the oscillator value is negative, the value from above will represent the percentage of bearish candles in the sample. If it is positive, this value represents the percentage of bullish candles in the sample.
Example 1 (oscillator value = 80):
50% + ((|80| / 100) * 50)%
50% + ((0.80) * 50)%
50% + 40% = 90%
90% of the candles in the sample were bullish.
Example 2 (oscillator value = -43):
50% + ((|-43| / 100) * 50)%
50% + ((0.43) * 50)%
50% + 21.5% = 71.5%
71.5% of the candles in the sample were bearish.
An example use of this indicator would be to put in a 'buy' order when its value shows a significant proportion of the sampled candles were bearish, and put in a 'sell' order when a significant proportion of candles were bullish. Potential divergences of this oscillator may also be used to plan trades accordingly such as bearish divergence - price continues higher as the oscillator decreases in value and vise-versa.*
* Nothing in this script constitutes any form of financial advice. The user is solely responsible for their trading decisions and I will not be held liable for any losses or gains incurred with the use of this script. Please proceed with caution when using this script to assist with trading decisions.
█ LIMITATIONS
Range Volumetric Weights :
Because of the conditions that must be met in order for volume to be considered part of wicks, it is possible that the default settings and their intended reasoning will not produce reliable results. If all lower timeframe candles have highs or lows that are within the body of the candle at the chart's resolution, the volume for the wicks will effectively be 0, which is not an accurate representation of those wicks. This is one of the reasons why I included the ability to change the source values used for these conditions as certain OHLC values may produce more reliable/intended results under these conditions.
Wick Slice Resolution :
PineScript restricts the number of intrabar references to 100,000 total. This script uses 3 separate request.security_lower_tf calls and has a default resolution of 1 minute. This means that if the user were to set the oscillator to the Range setting, enable volume weighted, and had the Wick Slice Resolution set to 1 minute, this script will exceed this 100,000 reference restriction within 24 days of data and will not produce any results beyond the previous 23.14 days.
Below are example uses of all the different settings of this script, these are done on the 1D chart of COINBASE:BTCUSD :
Default Settings:
Classic - Volume Weighted:
Range - no Volume Weight:
Range - Volume Weighted (1 min slices):
Range - Volume Weighted (1 hour slices):
Display Min/Max Guide - No Restriction:
Display Min/Max Guide - Restriction:
Invert Colors:
Infiten's Return Candle OscillatorInfiten's Return Candle Oscillator is an oscillator which shows the percentage return on the open, high, close and low over a customizable period in the form of candlesticks. It may be helpful for seeing volatility, swing trading, or mean reversion trading.
The RCO consists of two plotted elements :
RCO Candles (short length): candlesticks which are plotted with low = the product of the percentage changes in the low over a period, high = the product of the percentage changes in the high over a period, close = the product of the percent changes in close over a period, and open = the product of the percentage changes in return over a period. Similarly to with standard candlesticks, if the percentage change on the close is higher than the percentage change on the open, the candlestick is green, otherwise it is red.
Smoothed RCO Line (long length) : a moving average of the average of the low, close, open and high calculated for the RCO Candles. The line's transparency is determined by the percentage difference between the RCO and the highest or lowest RCO over the long length. A more transparent line means that the RCO is closer to the highest or lowest RCO, and may be indicative of a reversal, or weakening trend.
MACD-RSI Divergence OscillatorMACD-RSI Divergence Oscillator: Dual Confirmation with Momentum + Divergence Signals
This powerful oscillator combines MACD and RSI into a single normalized visual tool, enriched with automatic divergence detection and smart signal alerts. It’s designed to give traders advanced insights into momentum shifts and trend reversals.
Key Features:
• MACD + RSI Combo: Both indicators are scaled and merged into one oscillator for clearer interpretation.
• Automatic Divergence Detection:
• Bullish & Bearish divergences on both MACD and RSI
• Highlights strong divergences when both confirm
• Trading Signals:
• Detects MACD crossovers and RSI reversals
• Smart buy/sell signals based on momentum + divergence
• Custom Oscillator View:
• Plots MACD and RSI on the same scale
• Visual zero-line, overbought/oversold levels, and customizable colors
• Optional Dashboard Table:
• Displays live indicator values, signal states, and divergence status
Ideal For:
• Spotting early trend reversals
• Confirming trade entries/exits
• Avoiding false signals using dual indicator logic
Highly customizable and suitable for all timeframes and asset types.
Momentum Trail Oscillator [AlgoAlpha]🟠 OVERVIEW
This script builds a Momentum Trail Oscillator designed to measure directional momentum strength and dynamically track shifts in trend bias using a combination of smoothed price change calculations and adaptive trailing bands. The oscillator aims to help traders visualize when momentum is expanding or contracting and to identify transitions between bullish and bearish conditions.
🟠 CONCEPTS
The core idea combines two methods. First, the script calculates a normalized momentum measure by smoothing price changes relative to their absolute values, which creates a bounded oscillator that highlights whether moves are directional or choppy. Second, it uses a trailing band mechanism inspired by volatility stops, where bands adapt to the oscillator’s volatility, adjusting the thresholds that define a shift in directional bias. This dual approach seeks to address both the magnitude and persistence of momentum, reducing false signals in ranging markets.
🟠 FEATURES
The momentum calculation applies Hull Moving Averages and double EMA smoothing to price changes, producing a smooth, responsive oscillator.
The trailing bands are derived by offsetting a weighted moving average of the oscillator by a multiple of recent momentum volatility. A directional state variable tracks whether the oscillator is above or below the bands, updating when the momentum crosses these dynamic thresholds.
Overbought and oversold zones are visually marked between fixed levels (+30/+40 and -30/-40), with color fills to highlight when momentum is in extreme areas. The script plots signals on both the oscillator pane and optionally overlays markers on the main price chart for clarity.
🟠 USAGE
To use the indicator, apply it to any symbol and timeframe. The “Oscillator Length” controls how sensitive the momentum line is to recent price changes—lower values react faster, higher values smooth out noise. The “Trail Multiplier” sets how far the adaptive bands sit from the oscillator mid-line, which affects how often trend state changes occur. When the momentum line rises into the upper filled area and then crosses back below +40, it signals potential overbought exhaustion. The opposite applies for the oversold zone below -40. The plotted trailing bands switch visibility depending on the current directional state: when momentum is trending up, the lower band acts as the active trailing stop, and when trending down, the upper band becomes active. Trend changes are marked with circular symbols when the direction variable flips, and optional overlay arrows appear on the price chart to highlight overbought or oversold reversals. Traders can combine these signals with their own price action or volume analysis to confirm entries or exits.
Bitcoin Polynomial Regression OscillatorThis is the oscillator version of the script. Click here for the other part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Dynamic Volume Profile Oscillator | AlphaAlgosDynamic Volume Profile Oscillator | AlphaAlgos
Overview
The Dynamic Volume Profile Oscillator is an advanced technical analysis tool that transforms traditional volume analysis into a responsive oscillator. By creating a dynamic volume profile and measuring price deviation from volume-weighted equilibrium levels, this indicator provides traders with powerful insights into market momentum and potential reversals.
Key Features
• Volume-weighted price deviation analysis
• Adaptive midline that adjusts to changing market conditions
• Beautiful gradient visualization with 10-level intensity zones
• Fast and slow signal lines for trend confirmation
• Mean reversion mode that identifies price extremes relative to volume
• Fully customizable sensitivity and smoothing parameters
Technical Components
1. Volume Profile Analysis
The indicator builds a dynamic volume profile by:
• Collecting recent price and volume data within a specified lookback period
• Calculating a volume-weighted mean price (similar to VWAP)
• Measuring how far current price has deviated from this weighted average
• Adjusting this deviation based on historical volatility
2. Oscillator Calculation
The oscillator offers two calculation methods:
• Mean Reversion Mode (default): Measures deviation from volume-weighted mean price, normalized to reflect potential overbought/oversold conditions
• Standard Mode : Normalizes volume activity to identify unusual volume patterns
3. Adaptive Zones
The indicator features dynamic zones that:
• Center around an adaptive midline that reflects the average oscillator value
• Expand and contract based on recent volatility (standard deviation)
• Visually represent intensity through multi-level gradient coloring
• Provide clear visualization of bullish/bearish extremes
4. Signal Generation
Trading signals are generated through:
• Main oscillator line position relative to the adaptive midline
• Crossovers between fast (5-period) and slow (15-period) signal lines
• Color changes that instantly identify trend direction
• Distance from the midline indicating trend strength
Configuration Options
Volume Analysis Settings:
• Price Source - Select which price data to analyze
• Volume Source - Define volume data source
• Lookback Period - Number of bars for main calculations
• Profile Calculation Periods - Frequency of profile recalculation
Oscillator Settings:
• Smoothing Length - Controls oscillator smoothness
• Sensitivity - Adjusts responsiveness to price/volume changes
• Mean Reversion Mode - Toggles calculation methodology
Threshold Settings:
• Adaptive Midline - Uses dynamic midline based on historical values
• Midline Period - Lookback period for midline calculation
• Zone Width Multiplier - Controls width of bullish/bearish zones
Display Settings:
• Color Bars - Option to color price bars based on trend direction
Trading Strategies
Trend Following:
• Enter long positions when the oscillator crosses above the adaptive midline
• Enter short positions when the oscillator crosses below the adaptive midline
• Use signal line crossovers for entry timing
• Monitor gradient intensity to gauge trend strength
Mean Reversion Trading:
• Look for oscillator extremes shown by intense gradient colors
• Prepare for potential reversals when the oscillator reaches upper/lower zones
• Use divergences between price and oscillator for confirmation
• Consider scaling positions based on gradient intensity
Volume Analysis:
• Use Standard Mode to identify unusual volume patterns
• Confirm breakouts when accompanied by strong oscillator readings
• Watch for divergences between price and volume-based readings
• Use extended periods in extreme zones as trend confirmation
Best Practices
• Adjust sensitivity based on the asset's typical volatility
• Use longer smoothing for swing trading, shorter for day trading
• Combine with support/resistance levels for optimal entry/exit points
• Consider multiple timeframe analysis for comprehensive market view
• Test different profile calculation periods to match your trading style
This indicator is provided for informational purposes only. Always use proper risk management when trading based on any technical indicator. Not financial advise.
GMO (Gyroscopic Momentum Oscillator) GMO
Overview
This indicator fuses multiple advanced concepts to give traders a comprehensive view of market momentum, volatility, and potential turning points. It leverages the Gyroscopic Momentum Oscillator (GMO) foundation and layers on IQR-based bands, dynamic ATR-adjusted OB/OS levels, torque filtering, and divergence detection. The outcome is a versatile tool that can assist in identifying both short-term squeezes and long-term reversal zones while detecting subtle shifts in momentum acceleration.
Key Components:
Gyroscopic Momentum Oscillator (GMO) – A physics-inspired metric capturing trend stability and momentum by treating price dynamics as “angle,” “angular velocity,” and “inertia.”
IQR Bands – Highlight statistically typical oscillation ranges, providing insight into short-term squeezes and potential near-term trend shifts.
ATR-Adjusted OB/OS Levels – Dynamic thresholds for overbought/oversold conditions, adapting to volatility, aiding in identifying long-term potential reversal zones.
Torque Filtering & Scaling – Smooths and thresholds torque (the rate of change of momentum) and visually scales it for clarity, indicating sudden force changes that may precede volatility adjustments.
Divergence Detection – Highlights potential reversal cues by comparing oscillator swings against price swings, revealing regular and hidden bullish/bearish divergences.
Conceptual Insights
IQR Bands (Short-Term Squeeze & Trend Direction):
Short-Term Momentum and Squeeze: The IQR (Interquartile Range) bands show where the oscillator tends to “live” statistically. When the GMO line hovers within compressed IQR bands, it can signal a momentum squeeze phase. Exiting these tight ranges often correlates with short-term breakout opportunities.
Trend Reversals: If the oscillator pushes beyond these IQR ranges, it may indicate an emerging short-term trend change. Traders can watch for GMO escaping the IQR “comfort zone” to anticipate a new directional move.
Dynamic OB/OS Levels (Long-Term Reversal Zones):
ATR-Based Adaptive Thresholds: Instead of static overbought/oversold lines, this tool uses ATR to adjust OB/OS boundaries. In calm markets, these lines remain closer to ±90. As volatility rises, they approach ±100, reflecting greater permissible swings.
Long-Term Trend Reversal Potential: If GMO hits these dynamically adjusted OB/OS extremes, it suggests conditions ripe for possible long-term trend reversals. Traders seeking major inflection points may find these adaptive levels more reliable than fixed thresholds.
Torque (Sudden Force & Directional Shifts):
Momentum Acceleration Insight: Torque represents the second derivative of momentum, highlighting how quickly momentum is changing. High positive torque suggests a rapidly strengthening bullish force, while high negative torque warns of sudden bearish pressure.
Early Warning & Stability/Volatility Adjustments: By monitoring torque spikes, traders can anticipate momentum shifts before price fully confirms them. This can signal imminent changes in stability or increased volatility phases.
Indicator Parameters and Usage
GMO-Related Inputs:
lenPivot (Default 100): Length for calculating the pivot line (slow market axis).
lenSmoothAngle (Default 200): Smooths the angle measure, reducing noise.
lenATR (Default 14): ATR period for scaling factor, linking price changes to volatility.
useVolatility (Default true): If true, volatility (ATR) influences inertia, adjusting momentum calculations.
useVolume (Default false): If true, volume affects inertia, adding a liquidity dimension to momentum.
lenVolSmoothing (Default 50): Smooths volume calculations if useVolume is enabled.
lenMomentumSmooth (Default 20): EMA smoothing of GMO for a cleaner oscillator line.
normalizeRange (Default true): Normalizes GMO to a fixed range for consistent interpretation.
lenNorm (Default 100): Length for normalization window, ensuring GMO’s scale adapts to recent extremes.
IQR Bands Settings:
iqrLength (Default 14): Period to compute the oscillator’s statistical IQR.
iqrMult (Default 1.5): Multiplier to define the upper and lower IQR-based bands.
ATR-Adjusted OB/OS Settings:
baseOBLevel (Fixed at 90) and baseOSLevel (Fixed at 90): Base lines for OB/OS.
atrPeriodForOBOS (Default 50): ATR length for adjusting OB/OS thresholds dynamically.
atrScaling (Default 0.2): Controls how strongly volatility affects OB/OS lines.
Torque Filtering & Visualization:
torqueSmoothLength (Default 10): EMA length to smooth raw torque values.
atrPeriodForTorque (Default 14): ATR period to determine torque threshold.
atrTorqueScaling (Default 0.5): Scales ATR for determining torque’s “significant” threshold.
torqueScaleFactor (Default 10.0): Multiplies the torque values for better visual prominence on the chart.
Divergence Inputs:
showDivergences (Default true): Toggles divergence signals.
lbR, lbL (Defaults 5): Pivot lookback periods to identify swing highs and lows.
rangeUpper, rangeLower: Bar constraints to validate potential divergences.
plotBull, plotHiddenBull, plotBear, plotHiddenBear: Toggles for each divergence type.
Visual Elements on the Chart
GMO Line (Blue) & Zero Line (Gray):
GMO line oscillates around zero. Positive territory hints bullish momentum, negative suggests bearish.
IQR Bands (Teal Lines & Yellow Fill):
Upper/lower bands form a statistical “normal range” for GMO. The median line (purple) provides a central reference. Contraction near these bands indicates a short-term squeeze, expansions beyond them can signal emerging short-term trend changes.
Dynamic OB/OS (Red & Green Lines):
Red line near +90 to +100: Overbought zone (dynamic).
Green line near -90 to -100: Oversold zone (dynamic).
Movement into these zones may mark significant, longer-term reversal potential.
Torque Histogram (Colored Bars):
Plotted below GMO. Green bars = torque above positive threshold (bullish acceleration).
Red bars = torque below negative threshold (bearish acceleration).
Gray bars = neutral range.
This provides early warnings of momentum shifts before price responds fully.
Precession (Orange Line):
Scaled for visibility, adds context to long-term angular shifts in the oscillator.
Divergence Signals (Shapes):
Circles and offset lines highlight regular or hidden bullish/bearish divergences, offering potential reversal signals.
Practical Interpretation & Strategy
Short-Term Opportunities (IQR Focus):
If GMO compresses within IQR bands, the market might be “winding up.” A break above/below these bands can signal a short-term trade opportunity.
Long-Term Reversal Zones (Dynamic OB/OS):
When GMO approaches these dynamically adjusted extremes, conditions may be ripe for a major trend shift. This is particularly useful for swing or position traders looking for significant turnarounds.
Monitoring Torque for Acceleration Cues:
Torque spikes can precede price action, serving as an early catalyst signal. If torque turns strongly positive, anticipate bullish acceleration; strongly negative torque may warn of upcoming bearish pressure.
Confirm with Divergences:
Divergences between price and GMO reinforce potential reversal or continuation signals identified by IQR, OB/OS, or torque. Use them to increase confidence in setups.
Tips and Best Practices
Combine with Price & Volume Action:
While the indicator is powerful, always confirm signals with actual price structure, volume patterns, or other trend-following tools.
Adjust Lengths & Periods as Needed:
Shorter lengths = more responsiveness but more noise. Longer lengths = smoother signals but greater lag. Tune parameters to match your trading style and timeframe.
Use ATR and Volume Settings Wisely:
If markets are highly volatile, consider useVolatility to refine momentum readings. If liquidity is key, enable useVolume.
Scaling Torque:
If torque bars are hard to read, increase torqueScaleFactor further. The scaling doesn’t affect logic—only visibility.
Conclusion
The “GMO + IQR Bands + ATR-Adjusted OB/OS + Torque Filtering (Scaled)” indicator presents a holistic framework for understanding market momentum across multiple timescales and conditions. By interpreting short-term squeezes via IQR bands, long-term reversal zones via adaptive OB/OS, and subtle acceleration changes through torque, traders can gain advanced insights into when to anticipate breakouts, manage risk around potential reversals, and fine-tune timing for entries and exits.
This integrated approach helps navigate complex market dynamics, making it a valuable addition to any technical analysis toolkit.