Fuzzy SMA with DCTI Confirmation[FibonacciFlux]FibonacciFlux: Advanced Fuzzy Logic System with Donchian Trend Confirmation
Institutional-grade trend analysis combining adaptive Fuzzy Logic with Donchian Channel Trend Intensity for superior signal quality
Conceptual Framework & Research Foundation
FibonacciFlux represents a significant advancement in quantitative technical analysis, merging two powerful analytical methodologies: normalized fuzzy logic systems and Donchian Channel Trend Intensity (DCTI). This sophisticated indicator addresses a fundamental challenge in market analysis – the inherent imprecision of trend identification in dynamic, multi-dimensional market environments.
While traditional indicators often produce simplistic binary signals, markets exist in states of continuous, graduated transition. FibonacciFlux embraces this complexity through its implementation of fuzzy set theory, enhanced by DCTI's structural trend confirmation capabilities. The result is an indicator that provides nuanced, probabilistic trend assessment with institutional-grade signal quality.
Core Technological Components
1. Advanced Fuzzy Logic System with Percentile Normalization
At the foundation of FibonacciFlux lies a comprehensive fuzzy logic system that transforms conventional technical metrics into degrees of membership in linguistic variables:
// Fuzzy triangular membership function with robust error handling
fuzzy_triangle(val, left, center, right) =>
if na(val)
0.0
float denominator1 = math.max(1e-10, center - left)
float denominator2 = math.max(1e-10, right - center)
math.max(0.0, math.min(left == center ? val <= center ? 1.0 : 0.0 : (val - left) / denominator1,
center == right ? val >= center ? 1.0 : 0.0 : (right - val) / denominator2))
The system employs percentile-based normalization for SMA deviation – a critical innovation that enables self-calibration across different assets and market regimes:
// Percentile-based normalization for adaptive calibration
raw_diff = price_src - sma_val
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff_raw = raw_diff / diff_abs_percentile
normalized_diff = useClamping ? math.max(-clampValue, math.min(clampValue, normalized_diff_raw)) : normalized_diff_raw
This normalization approach represents a significant advancement over fixed-threshold systems, allowing the indicator to automatically adapt to varying volatility environments and maintain consistent signal quality across diverse market conditions.
2. Donchian Channel Trend Intensity (DCTI) Integration
FibonacciFlux significantly enhances fuzzy logic analysis through the integration of Donchian Channel Trend Intensity (DCTI) – a sophisticated measure of trend strength based on the relationship between short-term and long-term price extremes:
// DCTI calculation for structural trend confirmation
f_dcti(src, majorPer, minorPer, sigPer) =>
H = ta.highest(high, majorPer) // Major period high
L = ta.lowest(low, majorPer) // Major period low
h = ta.highest(high, minorPer) // Minor period high
l = ta.lowest(low, minorPer) // Minor period low
float pdiv = not na(L) ? l - L : 0 // Positive divergence (low vs major low)
float ndiv = not na(H) ? H - h : 0 // Negative divergence (major high vs high)
float divisor = pdiv + ndiv
dctiValue = divisor == 0 ? 0 : 100 * ((pdiv - ndiv) / divisor) // Normalized to -100 to +100 range
sigValue = ta.ema(dctiValue, sigPer)
DCTI provides a complementary structural perspective on market trends by quantifying the relationship between short-term and long-term price extremes. This creates a multi-dimensional analysis framework that combines adaptive deviation measurement (fuzzy SMA) with channel-based trend intensity confirmation (DCTI).
Multi-Dimensional Fuzzy Input Variables
FibonacciFlux processes four distinct technical dimensions through its fuzzy system:
Normalized SMA Deviation: Measures price displacement relative to historical volatility context
Rate of Change (ROC): Captures price momentum over configurable timeframes
Relative Strength Index (RSI): Evaluates cyclical overbought/oversold conditions
Donchian Channel Trend Intensity (DCTI): Provides structural trend confirmation through channel analysis
Each dimension is processed through comprehensive fuzzy sets that transform crisp numerical values into linguistic variables:
// Normalized SMA Deviation - Self-calibrating to volatility regimes
ndiff_LP := fuzzy_triangle(normalized_diff, norm_scale * 0.3, norm_scale * 0.7, norm_scale * 1.1)
ndiff_SP := fuzzy_triangle(normalized_diff, norm_scale * 0.05, norm_scale * 0.25, norm_scale * 0.5)
ndiff_NZ := fuzzy_triangle(normalized_diff, -norm_scale * 0.1, 0.0, norm_scale * 0.1)
ndiff_SN := fuzzy_triangle(normalized_diff, -norm_scale * 0.5, -norm_scale * 0.25, -norm_scale * 0.05)
ndiff_LN := fuzzy_triangle(normalized_diff, -norm_scale * 1.1, -norm_scale * 0.7, -norm_scale * 0.3)
// DCTI - Structural trend measurement
dcti_SP := fuzzy_triangle(dcti_val, 60.0, 85.0, 101.0) // Strong Positive Trend (> ~85)
dcti_WP := fuzzy_triangle(dcti_val, 20.0, 45.0, 70.0) // Weak Positive Trend (~30-60)
dcti_Z := fuzzy_triangle(dcti_val, -30.0, 0.0, 30.0) // Near Zero / Trendless (~+/- 20)
dcti_WN := fuzzy_triangle(dcti_val, -70.0, -45.0, -20.0) // Weak Negative Trend (~-30 - -60)
dcti_SN := fuzzy_triangle(dcti_val, -101.0, -85.0, -60.0) // Strong Negative Trend (< ~-85)
Advanced Fuzzy Rule System with DCTI Confirmation
The core intelligence of FibonacciFlux lies in its sophisticated fuzzy rule system – a structured knowledge representation that encodes expert understanding of market dynamics:
// Base Trend Rules with DCTI Confirmation
cond1 = math.min(ndiff_LP, roc_HP, rsi_M)
strength_SB := math.max(strength_SB, cond1 * (dcti_SP > 0.5 ? 1.2 : dcti_Z > 0.1 ? 0.5 : 1.0))
// DCTI Override Rules - Structural trend confirmation with momentum alignment
cond14 = math.min(ndiff_NZ, roc_HP, dcti_SP)
strength_SB := math.max(strength_SB, cond14 * 0.5)
The rule system implements 15 distinct fuzzy rules that evaluate various market conditions including:
Established Trends: Strong deviations with confirming momentum and DCTI alignment
Emerging Trends: Early deviation patterns with initial momentum and DCTI confirmation
Weakening Trends: Divergent signals between deviation, momentum, and DCTI
Reversal Conditions: Counter-trend signals with DCTI confirmation
Neutral Consolidations: Minimal deviation with low momentum and neutral DCTI
A key innovation is the weighted influence of DCTI on rule activation. When strong DCTI readings align with other indicators, rule strength is amplified (up to 1.2x). Conversely, when DCTI contradicts other indicators, rule impact is reduced (as low as 0.5x). This creates a dynamic, self-adjusting system that prioritizes high-conviction signals.
Defuzzification & Signal Generation
The final step transforms fuzzy outputs into a precise trend score through center-of-gravity defuzzification:
// Defuzzification with precise floating-point handling
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10
fuzzyTrendScore := (strength_SB * STRONG_BULL + strength_WB * WEAK_BULL +
strength_N * NEUTRAL + strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1.0 (Strong Bear) to +1.0 (Strong Bull), with critical threshold zones at ±0.3 (Weak trend) and ±0.7 (Strong trend). The histogram visualization employs intuitive color-coding for immediate trend assessment.
Strategic Applications for Institutional Trading
FibonacciFlux provides substantial advantages for sophisticated trading operations:
Multi-Timeframe Signal Confirmation: Institutional-grade signal validation across multiple technical dimensions
Trend Strength Quantification: Precise measurement of trend conviction with noise filtration
Early Trend Identification: Detection of emerging trends before traditional indicators through fuzzy pattern recognition
Adaptive Market Regime Analysis: Self-calibrating analysis across varying volatility environments
Algorithmic Strategy Integration: Well-defined numerical output suitable for systematic trading frameworks
Risk Management Enhancement: Superior signal fidelity for risk exposure optimization
Customization Parameters
FibonacciFlux offers extensive customization to align with specific trading mandates and market conditions:
Fuzzy SMA Settings: Configure baseline trend identification parameters including SMA, ROC, and RSI lengths
Normalization Settings: Fine-tune the self-calibration mechanism with adjustable lookback period, percentile rank, and optional clamping
DCTI Parameters: Optimize trend structure confirmation with adjustable major/minor periods and signal smoothing
Visualization Controls: Customize display transparency for optimal chart integration
These parameters enable precise calibration for different asset classes, timeframes, and market regimes while maintaining the core analytical framework.
Implementation Notes
For optimal implementation, consider the following guidance:
Higher timeframes (4H+) benefit from increased normalization lookback (800+) for stability
Volatile assets may require adjusted clamping values (2.5-4.0) for optimal signal sensitivity
DCTI parameters should be aligned with chart timeframe (higher timeframes require increased major/minor periods)
The indicator performs exceptionally well as a trend filter for systematic trading strategies
Acknowledgments
FibonacciFlux builds upon the pioneering work of Donovan Wall in Donchian Channel Trend Intensity analysis. The normalization approach draws inspiration from percentile-based statistical techniques in quantitative finance. This indicator is shared for educational and analytical purposes under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Past performance does not guarantee future results. All trading involves risk. This indicator should be used as one component of a comprehensive analysis framework.
Shout out @DonovanWall
Oscillators
Fuzzy SMA Trend Analyzer (experimental)[FibonacciFlux]Fuzzy SMA Trend Analyzer (Normalized): Advanced Market Trend Detection Using Fuzzy Logic Theory
Elevate your technical analysis with institutional-grade fuzzy logic implementation
Research Genesis & Conceptual Framework
This indicator represents the culmination of extensive research into applying fuzzy logic theory to financial markets. While traditional technical indicators often produce binary outcomes, market conditions exist on a continuous spectrum. The Fuzzy SMA Trend Analyzer addresses this limitation by implementing a sophisticated fuzzy logic system that captures the nuanced, multi-dimensional nature of market trends.
Core Fuzzy Logic Principles
At the heart of this indicator lies fuzzy logic theory - a mathematical framework designed to handle imprecision and uncertainty:
// Improved fuzzy_triangle function with guard clauses for NA and invalid parameters.
fuzzy_triangle(val, left, center, right) =>
if na(val) or na(left) or na(center) or na(right) or left > center or center > right // Guard checks
0.0
else if left == center and center == right // Crisp set (single point)
val == center ? 1.0 : 0.0
else if left == center // Left-shoulder shape (ramp down from 1 at center to 0 at right)
val >= right ? 0.0 : val <= center ? 1.0 : (right - val) / (right - center)
else if center == right // Right-shoulder shape (ramp up from 0 at left to 1 at center)
val <= left ? 0.0 : val >= center ? 1.0 : (val - left) / (center - left)
else // Standard triangle
math.max(0.0, math.min((val - left) / (center - left), (right - val) / (right - center)))
This implementation of triangular membership functions enables the indicator to transform crisp numerical values into degrees of membership in linguistic variables like "Large Positive" or "Small Negative," creating a more nuanced representation of market conditions.
Dynamic Percentile Normalization
A critical innovation in this indicator is the implementation of percentile-based normalization for SMA deviation:
// ----- Deviation Scale Estimation using Percentile -----
// Calculate the percentile rank of the *absolute* deviation over the lookback period.
// This gives an estimate of the 'typical maximum' deviation magnitude recently.
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
// ----- Normalize the Raw Deviation -----
// Divide the raw deviation by the estimated 'typical max' magnitude.
normalized_diff = raw_diff / diff_abs_percentile
// ----- Clamp the Normalized Deviation -----
normalized_diff_clamped = math.max(-3.0, math.min(3.0, normalized_diff))
This percentile normalization approach creates a self-adapting system that automatically calibrates to different assets and market regimes. Rather than using fixed thresholds, the indicator dynamically adjusts based on recent volatility patterns, significantly enhancing signal quality across diverse market environments.
Multi-Factor Fuzzy Rule System
The indicator implements a comprehensive fuzzy rule system that evaluates multiple technical factors:
SMA Deviation (Normalized): Measures price displacement from the Simple Moving Average
Rate of Change (ROC): Captures price momentum over a specified period
Relative Strength Index (RSI): Assesses overbought/oversold conditions
These factors are processed through a sophisticated fuzzy inference system with linguistic variables:
// ----- 3.1 Fuzzy Sets for Normalized Deviation -----
diffN_LP := fuzzy_triangle(normalized_diff_clamped, 0.7, 1.5, 3.0) // Large Positive (around/above percentile)
diffN_SP := fuzzy_triangle(normalized_diff_clamped, 0.1, 0.5, 0.9) // Small Positive
diffN_NZ := fuzzy_triangle(normalized_diff_clamped, -0.2, 0.0, 0.2) // Near Zero
diffN_SN := fuzzy_triangle(normalized_diff_clamped, -0.9, -0.5, -0.1) // Small Negative
diffN_LN := fuzzy_triangle(normalized_diff_clamped, -3.0, -1.5, -0.7) // Large Negative (around/below percentile)
// ----- 3.2 Fuzzy Sets for ROC -----
roc_HN := fuzzy_triangle(roc_val, -8.0, -5.0, -2.0)
roc_WN := fuzzy_triangle(roc_val, -3.0, -1.0, -0.1)
roc_NZ := fuzzy_triangle(roc_val, -0.3, 0.0, 0.3)
roc_WP := fuzzy_triangle(roc_val, 0.1, 1.0, 3.0)
roc_HP := fuzzy_triangle(roc_val, 2.0, 5.0, 8.0)
// ----- 3.3 Fuzzy Sets for RSI -----
rsi_L := fuzzy_triangle(rsi_val, 0.0, 25.0, 40.0)
rsi_M := fuzzy_triangle(rsi_val, 35.0, 50.0, 65.0)
rsi_H := fuzzy_triangle(rsi_val, 60.0, 75.0, 100.0)
Advanced Fuzzy Inference Rules
The indicator employs a comprehensive set of fuzzy rules that encode expert knowledge about market behavior:
// --- Fuzzy Rules using Normalized Deviation (diffN_*) ---
cond1 = math.min(diffN_LP, roc_HP, math.max(rsi_M, rsi_H)) // Strong Bullish: Large pos dev, strong pos roc, rsi ok
strength_SB := math.max(strength_SB, cond1)
cond2 = math.min(diffN_SP, roc_WP, rsi_M) // Weak Bullish: Small pos dev, weak pos roc, rsi mid
strength_WB := math.max(strength_WB, cond2)
cond3 = math.min(diffN_SP, roc_NZ, rsi_H) // Weakening Bullish: Small pos dev, flat roc, rsi high
strength_N := math.max(strength_N, cond3 * 0.6) // More neutral
strength_WB := math.max(strength_WB, cond3 * 0.2) // Less weak bullish
This rule system evaluates multiple conditions simultaneously, weighting them by their degree of membership to produce a comprehensive trend assessment. The rules are designed to identify various market conditions including strong trends, weakening trends, potential reversals, and neutral consolidations.
Defuzzification Process
The final step transforms the fuzzy result back into a crisp numerical value representing the overall trend strength:
// --- Step 6: Defuzzification ---
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10 // Use small epsilon instead of != 0.0 for float comparison
fuzzyTrendScore := (strength_SB * STRONG_BULL +
strength_WB * WEAK_BULL +
strength_N * NEUTRAL +
strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1 (strong bearish) to +1 (strong bullish), providing a smooth, continuous evaluation of market conditions that avoids the abrupt signal changes common in traditional indicators.
Advanced Visualization with Rainbow Gradient
The indicator incorporates sophisticated visualization using a rainbow gradient coloring system:
// Normalize score to for gradient function
normalizedScore = na(fuzzyTrendScore) ? 0.5 : math.max(0.0, math.min(1.0, (fuzzyTrendScore + 1) / 2))
// Get the color based on gradient setting and normalized score
final_color = get_gradient(normalizedScore, gradient_type)
This color-coding system provides intuitive visual feedback, with color intensity reflecting trend strength and direction. The gradient can be customized between Red-to-Green or Red-to-Blue configurations based on user preference.
Practical Applications
The Fuzzy SMA Trend Analyzer excels in several key applications:
Trend Identification: Precisely identifies market trend direction and strength with nuanced gradation
Market Regime Detection: Distinguishes between trending markets and consolidation phases
Divergence Analysis: Highlights potential reversals when price action and fuzzy trend score diverge
Filter for Trading Systems: Provides high-quality trend filtering for other trading strategies
Risk Management: Offers early warning of potential trend weakening or reversal
Parameter Customization
The indicator offers extensive customization options:
SMA Length: Adjusts the baseline moving average period
ROC Length: Controls momentum sensitivity
RSI Length: Configures overbought/oversold sensitivity
Normalization Lookback: Determines the adaptive calculation window for percentile normalization
Percentile Rank: Sets the statistical threshold for deviation normalization
Gradient Type: Selects the preferred color scheme for visualization
These parameters enable fine-tuning to specific market conditions, trading styles, and timeframes.
Acknowledgments
The rainbow gradient visualization component draws inspiration from LuxAlgo's "Rainbow Adaptive RSI" (used under CC BY-NC-SA 4.0 license). This implementation of fuzzy logic in technical analysis builds upon Fermi estimation principles to overcome the inherent limitations of crisp binary indicators.
This indicator is shared under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Remember that past performance does not guarantee future results. Always conduct thorough testing before implementing any technical indicator in live trading.
NUPL Z-Score | Vistula LabsWhat is NUPL?
NUPL (Net Unrealized Profit/Loss) is a fundamental on-chain metric used to evaluate the profit or loss state of a cryptocurrency's market participants, such as Bitcoin (BTC) and Ethereum (ETH). It compares the current market capitalization—the total value of all coins at their current price—to the realized capitalization, which represents the average price at which all coins were last transacted on-chain.
Market Capitalization: Current price × circulating supply.
Realized Capitalization: The sum of the value of all coins based on the price at their last on-chain movement.
For Bitcoin (BTC):
NUPL = (Market Cap - Realized Cap) / Market Cap * 100
For Ethereum (ETH):
NUPL = (Market Cap - Realized Cap) / Market Cap
A positive NUPL indicates that the market holds unrealized profits, meaning the current value exceeds the price at which coins were last moved. A negative NUPL signals unrealized losses. Extreme NUPL values—high positives or low negatives—can suggest overvaluation (potential market tops) or undervaluation (potential market bottoms), respectively.
How NUPL is Calculated for BTC & ETH
This indicator calculates NUPL using data sourced from Glassnode and CoinMetrics:
For Bitcoin:
Market Cap: GLASSNODE:BTC_MARKETCAP
Realized Cap: COINMETRICS:BTC_MARKETCAPREAL
Formula: ((btc_market_cap - btc_market_cap_real) / btc_market_cap) * 100
For Ethereum:
Market Cap: GLASSNODE:ETH_MARKETCAP
Realized Cap: COINMETRICS:ETH_MARKETCAPREAL
Formula: ((eth_market_cap - eth_market_cap_real) / eth_market_cap) * 100
The indicator then transforms these NUPL values into a Z-Score, which measures how many standard deviations the current NUPL deviates from its historical average. The Z-Score calculation incorporates:
A customizable moving average of NUPL (options: SMA, EMA, DEMA, RMA, WMA, VWMA) over a user-defined length (default: 220 periods).
The standard deviation of NUPL over a specified lookback period (default: 200 periods).
Z-Score Formula:
Z-Score = (Current NUPL - Moving Average of NUPL) / Standard Deviation of NUPL
This normalization allows the indicator to highlight extreme market conditions regardless of the raw NUPL scale.
How This Indicator Can Be Used
Trend Following
The NUPL Z-Score indicator employs a trend-following system with adjustable thresholds to generate trading signals:
Long Signals: Triggered when the Z-Score crosses above the Long Threshold (default: 0.26).
Short Signals: Triggered when the Z-Score crosses below the Short Threshold (default: -0.62).
Visual Representations:
Green up-triangles: Indicate long entry points (plotted below the bar).
Red down-triangles: Indicate short entry points (plotted above the bar).
Color-coded elements:
Candles and Z-Score plot turn teal (#00ffdd) for long positions.
Candles and Z-Score plot turn magenta (#ff00bf) for short positions.
These signals leverage historical NUPL trends to identify potential momentum shifts, aiding traders in timing entries and exits.
Overbought/Oversold Conditions
The indicator flags extreme market states using additional thresholds:
Overbought Threshold (default: 3.0): When the Z-Score exceeds this level, the market may be significantly overvalued, hinting at potential selling pressure. Highlighted with a light magenta background (#ff00bf with 75% transparency).
Oversold Threshold (default: -2.0): When the Z-Score drops below this level, the market may be significantly undervalued, suggesting buying opportunities. Highlighted with a light teal background (#00ffdd with 75% transparency).
These extreme Z-Score levels have historically aligned with major market peaks and troughs, making them useful for medium- to long-term position management.
Customization Options
Traders can tailor the indicator to their preferences:
Cryptocurrency Source: Choose between BTC or ETH.
Moving Average Type: Select from SMA, EMA, DEMA, RMA, WMA, or VWMA.
Moving Average Length: Adjust the period for the NUPL moving average (default: 220).
Z-Score Lookback Period: Set the historical window for Z-Score calculation (default: 200).
Thresholds: Fine-tune values for: Long Threshold (default: 0.26), Short Threshold (default: -0.62), Overbought Threshold (default: 3.0), Oversold Threshold (default: -2.0)
These options enable users to adapt the indicator to various trading strategies and risk profiles.
Alerts
The indicator supports four alert conditions to keep traders informed:
NUPL Long Opportunity: Alerts when a long signal is triggered.
NUPL Short Opportunity: Alerts when a short signal is triggered.
NUPL Overbought Condition: Alerts when the Z-Score exceeds the overbought threshold.
NUPL Oversold Condition: Alerts when the Z-Score falls below the oversold threshold.
These alerts allow traders to monitor key opportunities without constantly watching the chart.
leo.usdt RSIThis is a custom RSI-based indicator enhanced with Bollinger Band logic to give early visual signals and potential trading alerts. It’s designed to help traders identify:
• Overbought/oversold conditions
• Potential reversals
• Areas of market neutrality or retracement
• Strong or weak trade signal zones
• RSI-based alerts in combination with price volatility (via Bollinger Bands)
⸻
Key Components:
1. RSI Calculation
• Standard Relative Strength Index (RSI) with a default length of 21.
• Source: close price.
• Output RSI is color-coded:
• Red if RSI > 62 (overbought)
• Blue if RSI < 24 (oversold)
• Green otherwise
2. RSI Zones and Visual Labels
• Horizontal lines mark 6 key RSI zones:
• 80 = Upper Bound (extreme overbought)
• 62 = Strong Sell
• 50 = Possible Retrace
• 38 = Neutral
• 24 = Possible Reversal
• 16 = Strong Buy
• Backgrounds between these zones are color-shaded to visually differentiate them.
• Optional labels (controlled via checkbox) appear on the RSI chart to show zone names.
3. Bollinger Bands Logic
• Bollinger Bands use:
• Length = 20 (default)
• Multiplier = 2.0 (default)
• The BB logic categorizes price position relative to bands:
• BB = 71: Price above upper band
• BB = 56: Price in upper half
• BB = 44: Price in middle
• BB = 31: Price in lower half
• BB = 20: Price below lower band
4. Combined RSI + BB Signal Circles
• Two types of visual circles appear on the RSI chart:
• Small Signal (line width = 2):
• RSI > 50 and price > BB upper band → small sell signal (red)
• RSI < 38 and price < BB lower band → small buy signal (blue)
• Strong Signal (line width = 4):
• RSI > 62 and price > BB upper band → strong sell
• RSI < 24 and price < BB lower band → strong buy
5. Alerts
This script includes 4 alert conditions:
• Small Sell: RSI > 50 and price above BB upper band
• Small Buy: RSI < 38 and price below BB lower band
• Strong Sell: RSI > 62 and price above BB upper band
• Strong Buy: RSI < 24 and price below BB lower band
⸻
User Controls:
• Change RSI length.
• Change Bollinger Band length and multiplier.
• Toggle signals (circles) on/off.
• Toggle RSI zone labels on/off.
• Optional RSI zone background shading for easy visualization.
⸻
Use Case:
This script is ideal for:
• Traders looking to combine momentum (RSI) with volatility (BB) for better signal accuracy.
• Spotting potential trend reversals, retracement zones, and extreme conditions.
• Getting visual and audible alerts to act faster during key moments.
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.
Momentum Based RSIThe Momentum Based RSI is an enhancement to the RSI. it incorporates 2 sections:
MA Ratio (Fast/Slow)
RSI
at the end both of those are multiplied to create a more responsive RSI which reacts fast to market moves while still providing a whip ressistant tool.
Momentum Calculation
The "MA Ratio" as i like to call it results from comparing 2 MAs (both can be set to whatever type you like) against eachother, which, in the end, provides a Ratio that visualizes the difference. It is simple yet effective
RSI
An Old yet popular tool which dates back to 1978. In and out of itself it is a great tool, however it still can be enhanced.
The Combination
The RSI and the MARatio are multiplied together, which results in an RSI that is ampliefied by the speed of the market movements.
This proves highly effective, since the MA Ratio is hovering around at the same level. However during trends, it picks up speed in either of both directions which marginally increases the RSI's response the said movement.
Why its Creative, New and Good
While it is a super simple concept, it still holds a lot of power relative to its sophistication. Traders may use it like they used the Vanilla RSI (e.g Trend following, Mean-reversion or other).
Unlike RSI with momentum overlays, this indicator actively uses an MA Ratio multiplier for simplicity and responsiveness.
At last, Its primary goal is to detect trends faster while not creating more noise & false signals.
What not to do
if youre using this indicator, please do NOT change the Fast MA to be slower than to Slow MA or vice versa, since you'll be getting broken & noise induced signals which may not align with your goals.
Great inventions require great Care
As with anything, you should not use this tool without any other confluence. As great as the backtests may be, you dont know what the future holds, be careful!
This indicator is not a guaranteed predicition tool. If youre going to use it for investment decisions, please use it in coherence with other tools.
Thank you for reading!
ADX BoxDescription:
The ADX Box indicator provides traders with a quick and intuitive way to monitor the current trend strength based on the Average Directional Index (ADX), calculated with a customisable period (default: 7 periods).
This compact indicator neatly displays the current ADX value rounded to one decimal place, along with a clear directional arrow:
Green upward triangle (▲): Indicates that ADX is rising above its moving average, signaling increasing trend strength.
Red downward triangle (▼): Indicates that ADX is declining below its moving average, signaling weakening trend strength.
Key Features:
Small and clean visual representation.
Dynamically updates in real-time directly on the chart.
Ideal for quick trend strength assessment without cluttering your workspace.
Recommended Usage:
Quickly identifying whether market trends are strengthening or weakening.
Enhancing decision-making for trend-following or breakout trading strategies.
Complementing other indicators such as ATR boxes for volatility measurement.
Feel free to use, share, and incorporate this indicator into your trading setups for clearer insights and more confident trading decisions!
Multi-Fibonacci Trend Average[FibonacciFlux]Multi-Fibonacci Trend Average (MFTA): An Institutional-Grade Trend Confluence Indicator for Discerning Market Participants
My original indicator/Strategy:
Engineered for the sophisticated demands of institutional and advanced traders, the Multi-Fibonacci Trend Average (MFTA) indicator represents a paradigm shift in technical analysis. This meticulously crafted tool is designed to furnish high-definition trend signals within the complexities of modern financial markets. Anchored in the rigorous principles of Fibonacci ratios and augmented by advanced averaging methodologies, MFTA delivers a granular perspective on trend dynamics. Its integration of Multi-Timeframe (MTF) filters provides unparalleled signal robustness, empowering strategic decision-making with a heightened degree of confidence.
MFTA indicator on BTCUSDT 15min chart with 1min RSI and MACD filters enabled. Note the refined signal generation with reduced noise.
MFTA indicator on BTCUSDT 15min chart without MTF filters. While capturing more potential trading opportunities, it also generates a higher frequency of signals, including potential false positives.
Core Innovation: Proprietary Fibonacci-Enhanced Supertrend Averaging Engine
The MFTA indicator’s core innovation lies in its proprietary implementation of Supertrend analysis, strategically fortified by Fibonacci ratios to construct a truly dynamic volatility envelope. Departing from conventional Supertrend methodologies, MFTA autonomously computes not one, but three distinct Supertrend lines. Each of these lines is uniquely parameterized by a specific Fibonacci factor: 0.618 (Weak), 1.618 (Medium/Golden Ratio), and 2.618 (Strong/Extended Fibonacci).
// Fibonacci-based factors for multiple Supertrend calculations
factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval=0.01, step=0.01, tooltip='Factor 1 (Weak/Fibonacci)', group="Fibonacci Supertrend")
factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval=0.01, step=0.01, tooltip='Factor 2 (Medium/Golden Ratio)', group="Fibonacci Supertrend")
factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval=0.01, step=0.01, tooltip='Factor 3 (Strong/Extended Fib)', group="Fibonacci Supertrend")
This multi-faceted architecture adeptly captures a spectrum of market volatility sensitivities, ensuring a comprehensive assessment of prevailing conditions. Subsequently, the indicator algorithmically synthesizes these disparate Supertrend lines through arithmetic averaging. To achieve optimal signal fidelity and mitigate inherent market noise, this composite average is further refined utilizing an Exponential Moving Average (EMA).
// Calculate average of the three supertends and a smoothed version
superlength = input.int(21, 'Smoothing Length', tooltip='Smoothing Length for Average Supertrend', group="Fibonacci Supertrend")
average_trend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_trend = ta.ema(average_trend, superlength)
The resultant ‘Smoothed Trend’ line emerges as a remarkably responsive yet stable trend demarcation, offering demonstrably superior clarity and precision compared to singular Supertrend implementations, particularly within the turbulent dynamics of high-volatility markets.
Elevated Signal Confluence: Integrated Multi-Timeframe (MTF) Validation Suite
MFTA transcends the limitations of conventional trend indicators by incorporating an advanced suite of three independent MTF filters: RSI, MACD, and Volume. These filters function as sophisticated validation protocols, rigorously ensuring that only signals exhibiting a confluence of high-probability factors are brought to the forefront.
1. Granular Lower Timeframe RSI Momentum Filter
The Relative Strength Index (RSI) filter, computed from a user-defined lower timeframe, furnishes critical momentum-based signal validation. By meticulously monitoring RSI dynamics on an accelerated timeframe, traders gain the capacity to evaluate underlying momentum strength with precision, prior to committing to signal execution on the primary chart timeframe.
// --- Lower Timeframe RSI Filter ---
ltf_rsi_filter_enable = input.bool(false, title="Enable RSI Filter", group="MTF Filters", tooltip="Use RSI from lower timeframe as a filter")
ltf_rsi_timeframe = input.timeframe("1", title="RSI Timeframe", group="MTF Filters", tooltip="Timeframe for RSI calculation")
ltf_rsi_length = input.int(14, title="RSI Length", minval=1, group="MTF Filters", tooltip="Length for RSI calculation")
ltf_rsi_threshold = input.int(30, title="RSI Threshold", minval=0, maxval=100, group="MTF Filters", tooltip="RSI value threshold for filtering signals")
2. Convergent Lower Timeframe MACD Trend-Momentum Filter
The Moving Average Convergence Divergence (MACD) filter, also calculated on a lower timeframe basis, introduces a critical layer of trend-momentum convergence confirmation. The bullish signal configuration rigorously mandates that the MACD line be definitively positioned above the Signal line on the designated lower timeframe. This stringent condition ensures a robust indication of converging momentum that aligns synergistically with the prevailing trend identified on the primary timeframe.
// --- Lower Timeframe MACD Filter ---
ltf_macd_filter_enable = input.bool(false, title="Enable MACD Filter", group="MTF Filters", tooltip="Use MACD from lower timeframe as a filter")
ltf_macd_timeframe = input.timeframe("1", title="MACD Timeframe", group="MTF Filters", tooltip="Timeframe for MACD calculation")
ltf_macd_fast_length = input.int(12, title="MACD Fast Length", minval=1, group="MTF Filters", tooltip="Fast EMA length for MACD")
ltf_macd_slow_length = input.int(26, title="MACD Slow Length", minval=1, group="MTF Filters", tooltip="Slow EMA length for MACD")
ltf_macd_signal_length = input.int(9, title="MACD Signal Length", minval=1, group="MTF Filters", tooltip="Signal SMA length for MACD")
3. Definitive Volume Confirmation Filter
The Volume Filter functions as an indispensable arbiter of trade conviction. By establishing a dynamic volume threshold, defined as a percentage relative to the average volume over a user-specified lookback period, traders can effectively ensure that all generated signals are rigorously validated by demonstrably increased trading activity. This pivotal validation step signifies robust market participation, substantially diminishing the potential for spurious or false breakout signals.
// --- Volume Filter ---
volume_filter_enable = input.bool(false, title="Enable Volume Filter", group="MTF Filters", tooltip="Use volume level as a filter")
volume_threshold_percent = input.int(title="Volume Threshold (%)", defval=150, minval=100, group="MTF Filters", tooltip="Minimum volume percentage compared to average volume to allow signal (100% = average)")
These meticulously engineered filters operate in synergistic confluence, requiring all enabled filters to definitively satisfy their pre-defined conditions before a Buy or Sell signal is generated. This stringent multi-layered validation process drastically minimizes the incidence of false positive signals, thereby significantly enhancing entry precision and overall signal reliability.
Intuitive Visual Architecture & Actionable Intelligence
MFTA provides a demonstrably intuitive and visually rich charting environment, meticulously delineating trend direction and momentum through precisely color-coded plots:
Average Supertrend: Thin line, green/red for uptrend/downtrend, immediate directional bias.
Smoothed Supertrend: Bold line, teal/purple for uptrend/downtrend, cleaner, institutionally robust trend.
Dynamic Trend Fill: Green/red fill between Supertrends quantifies trend strength and momentum.
Adaptive Background Coloring: Light green/red background mirrors Smoothed Supertrend direction, holistic trend perspective.
Precision Buy/Sell Signals: ‘BUY’/‘SELL’ labels appear on chart when trend touch and MTF filter confluence are satisfied, facilitating high-conviction trade action.
MFTA indicator applied to BTCUSDT 4-hour chart, showcasing its effectiveness on higher timeframes. The Smoothed Length parameter is increased to 200 for enhanced smoothness on this timeframe, coupled with 1min RSI and Volume filters for signal refinement. This illustrates the indicator's adaptability across different timeframes and market conditions.
Strategic Applications for Institutional Mandates
MFTA’s sophisticated design provides distinct advantages for advanced trading operations and institutional investment mandates. Key strategic applications include:
High-Probability Trend Identification: Fibonacci-averaged Supertrend with MTF filters robustly identifies high-probability trend continuations and reversals, enhancing alpha generation.
Precision Entry/Exit Signals: Volume and momentum-filtered signals enable institutional-grade precision for optimized risk-adjusted returns.
Algorithmic Trading Integration: Clear signal logic facilitates seamless integration into automated trading systems for scalable strategy deployment.
Multi-Asset/Timeframe Versatility: Adaptable parameters ensure applicability across diverse asset classes and timeframes, catering to varied trading mandates.
Enhanced Risk Management: Superior signal fidelity from MTF filters inherently reduces false signals, supporting robust risk management protocols.
Granular Customization and Parameterized Control
MFTA offers unparalleled customization, empowering users to fine-tune parameters for precise alignment with specific trading styles and market conditions. Key adjustable parameters include:
Fibonacci Factors: Adjust Supertrend sensitivity to volatility regimes.
ATR Length: Control volatility responsiveness in Supertrend calculations.
Smoothing Length: Refine Smoothed Trend line responsiveness and noise reduction.
MTF Filter Parameters: Independently configure timeframes, lookback periods, and thresholds for RSI, MACD, and Volume filters for optimal signal filtering.
Disclaimer
MFTA is meticulously engineered for high-quality trend signals; however, no indicator guarantees profit. Market conditions are unpredictable, and trading involves substantial risk. Rigorous backtesting and forward testing across diverse datasets, alongside a comprehensive understanding of the indicator's logic, are essential before live deployment. Past performance is not indicative of future results. MFTA is for informational and analytical purposes only and is not financial or investment advice.
Trend Magnet ProTrend Magnet Pro – Advanced Adaptive Trend & Oscillator Indicator
Overview:
Trend Magnet Pro is a powerful, fully customizable indicator that combines adaptive moving averages with a dynamic oscillator to provide a comprehensive view of market trends and potential reversal points. It integrates multiple analytical layers—volatility, volume, multi-timeframe analysis, and divergence detection—to help traders make informed decisions.
Key Features & Competitive Advantages:
Adaptive Moving Average (MA):
The indicator calculates an adaptive MA by blending your chosen MA type (SMA, EMA, WMA, VWMA, KAMA, or LSMA) with Kaufman’s Adaptive Moving Average (KAMA). This hybrid approach adjusts dynamically to market volatility, ensuring smoother trend detection and reducing noise during erratic periods.
Custom Oscillator Calculation:
A separate oscillator is computed based on the difference between the closing price and a dedicated oscillator MA. This difference is normalized using an ATR-based volatility measure and then smoothed with the Hull MA. This process enhances signal precision by filtering out minor fluctuations.
ATR & Volume Integration:
Using the Average True Range (ATR) for volatility and a volume spike detection mechanism, the indicator filters out weak signals. These features ensure that only significant market moves trigger trading signals.
Multi-Timeframe Analysis:
By incorporating an oscillator analysis on a higher timeframe, Trend Magnet Pro provides an extra layer of confirmation. This multi-timeframe approach improves the reliability of signals, making it easier to identify sustained trends.
Divergence Detection:
The indicator automatically detects bullish and bearish divergences between price movements and the oscillator. These divergences can serve as early warnings for potential trend reversals, adding further depth to your market analysis.
Visual Clarity & Customization:
Trend Magnet Pro offers:
A separate oscillator panel with color-coded histograms.
Overlay plots of the adaptive MA on the price chart.
Clear visual markers for buy and sell signals.
Adjustable parameters for pivot detection and oscillator pressure thresholds.
How to Use Trend Magnet Pro:
Main MA Settings:
Choose your preferred MA type and set the MA length for the main trend analysis.
The adaptive algorithm will blend this with KAMA based on current volatility.
Oscillator Settings:
Set the oscillator’s MA type and its smoothing length.
Fine-tune the oscillator parameters to match your trading style and market conditions.
Common Settings:
Define the ATR length for volatility measurement.
Adjust the volume multiplier and volume SMA period to enable volume spike detection.
Set the low and high pressure thresholds to determine oscillator color changes, reflecting different market pressures.
Multi-Timeframe & Divergence:
Optionally, select a higher timeframe for the oscillator to provide additional confirmation.
Enable divergence detection to highlight potential trend reversals based on price and oscillator pivots.
Signal Interpretation:
Buy Signal: Triggered when the oscillator crosses above zero, accompanied by volume spikes and confirmed by both multi-timeframe analysis and price being above the adaptive MA.
Sell Signal: Triggered under opposite conditions, where the oscillator crosses below zero and the price is below the adaptive MA.
By adjusting these settings, you can tailor Trend Magnet Pro to your specific market and trading strategy, making it an invaluable tool for both trend-following and reversal trading.
Русское Описание
Trend Magnet Pro – Индикатор Адаптивного Тренда и Осциллятора
Обзор:
Trend Magnet Pro – это мощный и полностью настраиваемый индикатор, который объединяет адаптивные скользящие средние с динамическим осциллятором для комплексного анализа рыночных трендов и потенциальных точек разворота. Он интегрирует несколько аналитических слоёв — волатильность, объём, мультитаймфреймовый анализ и детекцию дивергенций — что позволяет принимать обоснованные торговые решения.
Основные преимущества и функциональные возможности:
Адаптивная Скользящая Средняя (MA):
Индикатор рассчитывает адаптивную MA, комбинируя выбранный тип (SMA, EMA, WMA, VWMA, KAMA или LSMA) с Kaufman’s Adaptive Moving Average (KAMA). Такой гибридный подход динамически подстраивается под рыночную волатильность, обеспечивая более плавное определение трендов и снижая уровень шума в нестабильные периоды.
Кастомизированный Расчёт Осциллятора:
Осциллятор вычисляется отдельно на основе разницы между ценой закрытия и специально рассчитанной MA для осциллятора. Эта разница нормализуется с использованием ATR (Average True Range) для оценки волатильности и сглаживается при помощи Hull MA, что позволяет точнее фиксировать значимые сигналы и исключать мелкие колебания.
Интеграция ATR и Объёма:
Применение ATR для измерения волатильности в сочетании с механизмом обнаружения всплесков объёма позволяет отсеивать слабые сигналы. Эти функции гарантируют, что торговые сигналы возникают только при значительных движениях рынка.
Мультитаймфреймовый Анализ:
Встроенный анализ осциллятора на старшем таймфрейме даёт дополнительное подтверждение сигналов. Такой подход повышает надёжность сигналов, помогая выявлять устойчивые тренды.
Детекция Дивергенций:
Индикатор автоматически обнаруживает бычьи и медвежьи дивергенции между движением цены и осциллятором. Эти дивергенции могут служить ранним предупреждением о потенциальном развороте тренда, что добавляет глубины вашему анализу.
Удобство Визуализации и Настройки:
Trend Magnet Pro предлагает:
Отдельную панель осциллятора с цветными гистограммами.
Наложение адаптивной MA на график цены.
Чёткие визуальные сигналы для покупки и продажи.
Настраиваемые параметры для обнаружения пивотов и уровней давления осциллятора.
Как работать с Trend Magnet Pro:
Настройки Основной MA:
Выберите предпочитаемый тип MA и установите период для анализа основного тренда.
Адаптивный алгоритм объединит выбранную MA с KAMA на основе текущей волатильности.
Настройки Осциллятора:
Задайте тип MA для осциллятора и установите период сглаживания.
Подберите параметры осциллятора, чтобы он соответствовал вашему стилю торговли и рыночным условиям.
Общие Настройки:
Определите период ATR для измерения волатильности.
Настройте множитель объёма и период SMA объёма для обнаружения всплесков.
Установите пороги низкого и высокого давления, которые будут влиять на цветовую индикацию осциллятора и отражать рыночное давление.
Мультитаймфреймовый Анализ и Дивергенции:
При необходимости выберите старший таймфрейм для осциллятора, чтобы обеспечить дополнительное подтверждение сигналов.
Включите функцию детекции дивергенций для выявления потенциальных разворотов тренда на основе пивотов цены и осциллятора.
Интерпретация Сигналов:
Сигнал на покупку: Формируется, когда осциллятор пересекает ноль снизу вверх, подтверждаясь всплеском объёма, анализом на старшем таймфрейме и положением цены выше адаптивной MA.
Сигнал на продажу: Формируется при обратных условиях – когда осциллятор пересекает ноль сверху вниз, а цена находится ниже адаптивной MA.
Настройка параметров позволяет адаптировать Trend Magnet Pro под конкретный рынок и торговую стратегию, делая его незаменимым инструментом как для трендового анализа, так и для поиска разворотных сигналов.
Aggregated Spot vs Perp Volume (% Change)Aggregated Spot vs Perp Volume (% Change)
Description
The "Aggregated Spot vs Perp Volume (% Change)" indicator helps crypto traders compare the momentum of spot and perpetual futures (perp) trading volumes across 12 major exchanges. It calculates the percentage change in volume from one bar to the next, highlighting divergences and showing which market—spot or perp—is leading a move. By focusing on relative changes, it eliminates the issue of absolute volume differences, making trends clear.
The indicator aggregates data from Binance, Bybit, OKX, Coinbase, Bitget, MEXC, Phemex, BingX, WhiteBIT, BitMEX, Kraken, and HTX. Users can toggle exchanges and choose to measure volume in coin units (e.g., BTC) or USD.
How It Works
Volume Aggregation:
Fetches spot and perp volume data for the selected crypto (e.g., BTC) from up to 12 exchanges.
Spot volume is included only if perp volume is available for the same pair, ensuring consistency.
Volume can be measured in coin units or USD (volume × spot price).
Percentage Change:
Calculates the percentage change in spot and perp volumes from the previous bar:
Percentage Change = ((Current Volume − Previous Volume) / Previous Volume) ×100
This focuses on relative momentum, making spot and perp volumes directly comparable.
Visualization:
Spot volume % change is plotted as a blue line, and perp volume % change as a red line, both with a linewidth of 1.
Who Should Use It
Crypto Traders: To understand spot vs. perp market dynamics across exchanges.
Momentum Traders: To spot which market is driving price moves via volume divergences.
Scalpers/Day Traders: For identifying short-term shifts in market activity.
Analysts: To study liquidity and sentiment in crypto markets.
How to Use It
Blue line: Spot volume % change.
Red line: Perp volume % change.
Look for divergences (e.g., a sharp rise in the red line but not the blue line suggests perp markets are leading).
Combine with Price:
Use alongside price charts to confirm trends or spot potential reversals.
Context
Spot markets reflect actual asset trading, while perp markets, with leverage, attract speculative activity and often show higher volumes. This indicator uses percentage change to compare their momentum, helping traders identify market leadership and divergences. For example, a 50% increase in both spot and perp volumes plots at the same level, making it easy to see relative shifts across exchanges.
Stochastic Fusion Elite [trade_lexx]📈 Stochastic Fusion Elite is your reliable trading assistant!
📊 What is Stochastic Fusion Elite ?
Stochastic Fusion Elite is a trading indicator based on a stochastic oscillator. It analyzes the rate of price change and generates buy or sell signals based on various technical analysis methods.
💡 The main components of the indicator
📊 Stochastic oscillator (K and D)
Stochastic shows the position of the current price relative to the price range for a certain period. Values above 80 indicate overbought (an early sale is possible), and values below 20 indicate oversold (an early purchase is possible).
📈 Moving Averages (MA)
The indicator uses 10 different types of moving averages to smooth stochastic lines.:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
- HMA: Moving Average Scale
- KAMA: Kaufman Adaptive Moving Average
- VWMA: Volume-weighted moving average
- ALMA: Arnaud Legoux Moving Average
- TEMA: Triple exponential moving average
- ZLEMA: zero delay exponential moving average
- DEMA: Double exponential moving average
The choice of the type of moving average affects the speed of the indicator's response to market changes.
🎯 Bollinger Bands (BB)
Bands around the moving average that widen and narrow depending on volatility. They help determine when the stochastic is out of the normal range.
🔄 Divergences
Divergences show discrepancies between price and stochastic:
- Bullish divergence: price is falling and stochastic is rising — an upward reversal is possible
- Bearish divergence: the price is rising, and stochastic is falling — a downward reversal is possible
🔍 Indicator signals
1️⃣ KD signals (K and D stochastic lines)
- Buy signal:
- What happens: the %K line crosses the %D line from bottom to top
- What does it look like: a green triangle with the label "KD" under the chart and the label "Buy" below the bar
- What does this mean: the price is gaining an upward momentum, growth is possible
- Sell signal:
- What happens: the %K line crosses the %D line from top to bottom
- What it looks like: a red triangle with the label "KD" above the chart and the label "Sell" above the bar
- What does this mean: the price is losing its upward momentum, possibly falling
2️⃣ Moving Average Signals (MA)
- Buy Signal:
- What happens: stochastic crosses the moving average from bottom to top
- What it looks like: a green triangle with the label "MA" under the chart and the label "Buy" below the bar
- What does this mean: stochastic is starting to accelerate upward, price growth is possible
- Sell signal:
- What happens: stochastic crosses the moving average from top to bottom
- What it looks like: a red triangle with the label "MA" above the chart and the label "Sell" above the bar
- What does this mean: stochastic is starting to accelerate downwards, a price drop is possible
3️⃣ Bollinger Band Signals (BB)
- Buy signal:
- What happens: stochastic crosses the lower Bollinger band from bottom to top
- What it looks like: a green triangle with the label "BB" under the chart and the label "Buy" below the bar
- What does this mean: stochastic was too low and is now starting to recover
- Sell signal:
- What happens: Stochastic crosses the upper Bollinger band from top to bottom
- What it looks like: a red triangle with a "BB" label above the chart and a "Sell" label above the bar
- What does this mean: stochastic was too high and is now starting to decline
4️⃣ Divergence Signals (Div)
- Buy Signal (Bullish Divergence):
- What's happening: the price is falling, and stochastic is forming higher lows
- What it looks like: a green triangle with a "Div" label under the chart and a "Buy" label below the bar
- What does this mean: despite the falling price, the momentum is already changing in an upward direction
- Sell signal (bearish divergence):
- What's going on: the price is rising, and stochastic is forming lower highs
- What it looks like: a red triangle with a "Div" label above the chart and a "Sell" label above the bar
- What does this mean: despite the price increase, the momentum is already weakening
🛠️ Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals
- Why it is needed: prevents signals from being too frequent during strong market fluctuations
- How to set it up: Set the number from 0 and above (default: 5)
2️⃣ "Waiting for the opposite signal" mode
- What it does: waits for a signal in the opposite direction before generating a new signal
- Why you need it: it helps you not to miss important trend reversals
- How to set up: just turn the function on or off
3️⃣ Filter by stochastic levels
- What it does: generates signals only when the stochastic is in the specified ranges
- Why it is needed: it helps to catch the moments when the market is oversold or overbought
- How to set up:
- For buy signals: set a range for oversold (for example, 1-20)
- For sell signals: set a range for overbought (for example, 80-100)
4️⃣ MFI filter
- What it does: additionally checks the values of the cash flow index (MFI)
- Why it is needed: confirms stochastic signals with cash flow data
- How to set it up:
- For buy signals: set the range for oversold MFI (for example, 1-25)
- For sell signals: set the range for overbought MFI (for example, 75-100)
5️⃣ The RSI filter
- What it does: additionally checks the RSI values to confirm the signals
- Why it is needed: adds additional confirmation from another popular indicator
- How to set up:
- For buy signals: set the range for oversold MFI (for example, 1-30)
- For sell signals: set the range for overbought MFI (for example, 70-100)
🔄 Signal combination modes
1️⃣ Normal mode
- How it works: all signals (KD, MA, BB, Div) work independently of each other
- When to use it: for general market analysis or when learning how to work with the indicator
2️⃣ "AND" Mode ("AND Mode")
- How it works: the alarm appears only when several conditions are triggered simultaneously
- Combination options:
- KD+MA: signals from the KD and moving average lines
- KD+BB: signals from KD lines and Bollinger bands
- KD+Div: signals from the KD and divergence lines
- KD+MA+BB: three signals simultaneously
- KD+MA+Div: three signals at the same time
- KD+BB+Div: three signals at the same time
- KD+MA+BB+Div: all four signals at the same time
- When to use: for more reliable but rare signals
🔌 Connecting to trading strategies
The indicator can be connected to your trading strategies using 6 different channels.:
1. Connector KD signals: connects only the signals from the intersection of lines K and D
2. Connector MA signals: connects only signals from moving averages
3. Connector BB signal: connects only the signals from the Bollinger bands
4. Connector divergence signals: connects only divergence signals
5. Combined Connector: connects any signals
6. Connector for "And" mode: connects only combined signals
🔔 Setting up alerts
The indicator can send alerts when alarms appear.:
- Alerts for KD: when the %K line crosses the %D line
- Alerts for MA: when stochastic crosses the moving average
- Alerts for BB: when stochastic crosses the Bollinger bands
- Divergence alerts: when a divergence is detected
- Combined alerts: for all types of alarms
- Alerts for "And" mode: for combined signals
🎭 What does the indicator look like on the chart ?
- Main lines K and D: blue and orange lines
- Overbought/oversold levels: horizontal lines at levels 20 and 80
- Middle line: dotted line at level 50
- Stochastic Moving Average: yellow line
- Bollinger bands: green lines around the moving average
- Signals: green and red triangles with corresponding labels
📚 How to start using Stochastic Fusion Elite
1️⃣ Initial setup
- Add an indicator to your chart
- Select the types of signals you want to use (KD, MA, BB, Div)
- Adjust the period and smoothing for the K and D lines
2️⃣ Filter settings
- Set the distance between the signals to get rid of unnecessary noise
- Adjust stochastic, MFI and RSI levels depending on the volatility of your asset
- If you need more reliable signals, turn on the "Waiting for the opposite signal" mode.
3️⃣ Operation mode selection
- First, use the standard mode to see all possible signals.
- When you get comfortable, try the "And" mode for rarer signals.
4️⃣ Setting up Alerts
- Select the types of signals you want to be notified about
- Set up alerts for these types of signals
5️⃣ Verification and adaptation
- Check the operation of the indicator on historical data
- Adjust the parameters for a specific asset
- Adapt the settings to your trading style
🌟 Usage examples
For trend trading
- Use the KD and MA signals in the direction of the main trend
- Set the distance between the signals
- Set stricter levels for filters
For trading in a sideways range
- Use BB signals to detect bounces from the range boundaries
- Use a stochastic level filter to confirm overbought/oversold conditions
- Adjust the Bollinger bands according to the width of the range
To determine the pivot points
- Pay attention to the divergence signals
- Set the distance between the signals
- Check the MFI and RSI filters for additional confirmation
Quantum Motion Oscillator-QMO (TechnoBlooms)Quantum Motion Oscillator (QMO) is a momentum indicator designed for traders who demand precision. Combining multi-timeframe weighted linear regression with EMA crossovers, QMO offers a dynamic view of market momentum, helping traders anticipate trend shifts with greater accuracy.
This oscillator is inspired by quantum mechanics and wave theory, where market movement is seen as a series of probabilistic waves rather than rigid structures.
The histogram is plotted in proportion to the price movement of the candlesticks.
KEY FEATURES
1. Multi-Timeframe Histogram - Integrates 1 to 5 weighted linear regression averages, reducing lag while maintaining accuracy.
2. EMA Crossover Signal - Uses a Short and Long EMA to confirm trend shifts with minimal noise.
3. Adaptive Trend Analysis - Self-adjusting mechanics make QMO effective in both ranging and trending markets.
4. Scalable for Different Trading Styles - Works seamlessly for scalping, intraday, swing and position trading.
ADVANCED PROFESSIONAL INSIGHTS
1. Wave Dynamics and Market Flow - Inspired by wave mechanics, QMO reflects the energy accumulation and dissipation in price movements.
Expanding histogram waves = Strong momentum surge
Contracting waves = Momentum weakening, potential reversal zone.
2. Liquidity and Order Flow Applications - QMO works well alongside liquidity concepts and smart money techniques:
Combine with Fair Value Gaps & Order Blocks -> Enter when QMO signals align with liquidity zones.
Avoid False Moves - If price sweeps liquidity, but QMO momentum diverges, it is a sign of potential smart money manipulation.
BBTrend ModularBBTrend Modular Indicator
The BBTrend Modular Indicator is designed to provide multiple perspectives on market dynamics by leveraging Bollinger Bands. It consists of several independent modules, each analyzing a specific aspect of price action and volatility. By default, all modules are enabled except the Adaptive BBTrend module, which remains off unless activated.
Modules Overview
1. BBTrend (Basic Module)
- Purpose: Calculates the difference between the absolute differences of the upper and lower Bollinger Bands for short and long periods.
- Working Principle: By comparing the divergence between the bands of two different timeframes, this module gives an indication of trend strength. A positive value may indicate bullish conditions, while a negative value suggests bearish conditions.
2. BB Expansion (Volatility Analysis)
- Purpose: Measures market volatility by comparing the widths of the Bollinger Bands for short and long periods.
- Working Principle: An increased width in the short-period bands relative to the long-period bands signals rising volatility and trend expansion. Dynamic color coding further helps in interpreting volatility changes.
3. BB Momentum Trend (Slope Analysis)
- Purpose: Assesses market momentum by analyzing the slope (or the rate of change) of the short-period Bollinger Band’s middle line.
- Working Principle: A positive slope indicates upward (bullish) momentum, whereas a negative slope points to downward (bearish) momentum. This helps traders gauge the speed at which the trend is evolving.
4. Adaptive BBTrend (Adaptive Calculation)
- Purpose: Adjusts the Bollinger Bands’ lengths dynamically using the Average True Range (ATR) to better respond to changing market volatility.
- Working Principle: An adaptive factor is computed based on the ATR relative to the closing price. This factor recalculates the short and long periods, making the indicator more responsive in volatile markets. Note: This module is disabled by default.
5. Volume-Weighted BBTrend (Volume Adjustment)
- Purpose: Integrates trading volume into the BBTrend calculation to refine the trend signal.
- Working Principle: By applying a volume weighting factor, the module gives more significance to high-volume bars. This results in a nuanced view of market sentiment, where high trading activity can strengthen the trend signal.
Русское описание
Индикатор BBTrend Modular
Индикатор BBTrend Modular создан для предоставления различных взглядов на динамику рынка с использованием полос Боллинджера. Он состоит из нескольких независимых модулей, каждый из которых анализирует определенный аспект ценового действия и волатильности. По умолчанию все модули включены, за исключением модуля Adaptive BBTrend, который остается выключенным, если его специально не активировать.
Обзор модулей
1. BBTrend (Базовый модуль)
- Назначение: Рассчитывает разницу между абсолютными разностями верхней и нижней линий полос Боллинджера для короткого и длинного периодов.
- Принцип работы: Сравнивая дивергенцию полос для двух разных временных периодов, модуль предоставляет информацию о силе тренда. Положительное значение может свидетельствовать о бычьем тренде, а отрицательное — о медвежьем.
2. BB Expansion (Анализ волатильности)
- Назначение: Оценивает волатильность рынка путем сравнения ширины полос Боллинджера для короткого и длинного периодов.
- Принцип работы: Увеличение ширины короткого периода по сравнению с длинным сигнализирует об увеличении волатильности и расширении тренда. Динамическая раскраска помогает визуально интерпретировать изменения волатильности.
3. BB Momentum Trend (Анализ наклона)
- Назначение: Анализирует моментум рынка путем оценки наклона (темпа изменения) средней линии полос Боллинджера для короткого периода.
- Принцип работы: Положительный наклон указывает на бычий моментум, а отрицательный — на медвежий, что помогает оценить скорость изменения тренда.
4. Adaptive BBTrend (Адаптивный расчет)
- Назначение: Динамически корректирует периоды расчета полос Боллинджера с использованием Average True Range (ATR) для лучшей адаптации к изменяющейся волатильности рынка.
- Принцип работы: Вычисляется адаптивный коэффициент на основе ATR относительно цены закрытия, после чего пересчитываются короткий и длинный периоды. Такой подход позволяет индикатору быть более чувствительным в условиях высокой волатильности. Примечание: Модуль по умолчанию выключен.
5. Volume-Weighted BBTrend (Объёмно-взвешенный расчет)
- Назначение: Включает объем торгов в расчет BBTrend для уточнения сигнала тренда.
- Принцип работы: Модуль применяет объемное взвешивание, придавая больший вес барам с высоким объемом. Это позволяет получить более точное представление о настроениях рынка, когда высокий объем торговли усиливает сигнал тренда.
RSI-Colored Price Candles with BackgroundThis Pine Script indicator visually enhances price candles based on **RSI (Relative Strength Index)** behavior, helping traders quickly assess momentum directly on the price chart.
**RSI Calculation:**
The RSI is computed using a traditional 14-period lookback. It uses `ta.rma()` to smooth average gains and losses, and then transforms the result into an RSI value between 0 and 100. This value is used to determine both **candle color** and optional **background shading**.
**Candle Coloring:**
Each price candle is recolored based on the current RSI value:
- If RSI is **greater than or equal to 50**, the candle is **bright green**, indicating bullish momentum.
- If RSI is **less than 50**, the candle is **bright red**, indicating bearish momentum.
The actual OHLC values of the candles remain unchanged. Only their color is modified to reflect RSI strength.
**Optional Background Highlighting:**
A user setting called `Show Overbought/Oversold Background` lets traders toggle background shading on or off. When enabled:
- If RSI is **above 70**, a soft **green** background appears, signaling overbought conditions.
- If RSI is **below 30**, a soft **red** background appears, signaling oversold conditions.
This provides an intuitive visual cue that highlights potential reversal or exhaustion zones based on RSI extremes.
**Custom Settings:**
- The RSI length and source are customizable.
- Background highlighting is turned **off by default**, giving users a clean chart unless they choose to enable it.
**Purpose and Use:**
This script is designed for traders who want to visually integrate RSI momentum directly into their chart candles, reducing the need to look away from price action. It's clean, responsive, and adjustable — perfect for intraday or swing traders who value simplicity backed by momentum data.
Melody Markets RSI UT+🎵 Melody Markets RSI UT+ – The Reinvented RSI Indicator 🎵
📌 Indicator Description
The Melody Markets RSI UT+ takes the Relative Strength Index (RSI) to the next level by incorporating acceleration zones and the ability to display RSI levels from higher timeframes directly on the price chart.
Unlike traditional RSI indicators that appear in a separate window, Melody Markets RSI UT+ transforms RSI bands into dynamic levels around the price, making market analysis more intuitive and responsive.
🔍 Key Features
✅ RSI integrated into the main chart → No need for a separate window, the RSI is displayed as bands around the price.
✅ RSI Acceleration Zones → Detects bullish and bearish acceleration movements, highlighting price momentum.
✅ Multi-TF RSI Display → View RSI levels from higher timeframes (5min, 15min, 1H, 4H, D...) without switching charts.
✅ Automatic RSI Breakout Detection → Highlights reintegrations and breakouts of RSI boundaries to anticipate reversals.
✅ Fully Customizable → Enable/disable RSI levels, adjust colors and styles of RSI zones, and fine-tune indicator sensitivity.
✅ Built-in Alerts → Get notified when the price crosses a key RSI level or reintegrates an acceleration zone.
📖 How to Use Melody Markets RSI UT+?
1️⃣ Enable RSI Zones → Display RSI bands directly around the price to spot strength or weakness areas.
2️⃣ Identify RSI Accelerations → Colored zones highlight explosive bullish or bearish movements.
3️⃣ Track Higher TF RSI Levels → Enable RSI levels from higher timeframes (H1, H4, D...) to identify key support and resistance zones.
4️⃣ Use RSI Alerts → Get instant notifications when a breakout or reintegration of an RSI level occurs.
5️⃣ Refine Your Entries & Exits → Combine this indicator with other technical tools to confirm your trading decisions.
🎯 Who Is This Indicator For?
🔹 Scalpers & Day Traders → Huge time-saver with an RSI directly integrated into the main chart.
🔹 Swing Traders → Easily track key RSI levels without constantly switching timeframes.
🔹 Beginners & Advanced Traders → A more intuitive and fluid RSI reading, perfect for anticipating market moves.
🔥 Conclusion
Melody Markets RSI UT+ is a game-changing indicator that redefines how RSI is used in trading. Its seamless integration into the main chart, combined with higher TF visualization and acceleration zones, allows traders to make sharper decisions with unmatched clarity.
📌 Add it to your chart now and unlock a new way to trade RSI! 🚀
Touch HMA + ATR Band Bands Alert (NTY88)🔔 Precision Alerts | No Repainting | ATR-Based Touch Detection | HMA Trend Coloring
This script is a clean and powerful tool designed to help you catch precise market reversals using ATR Band touches combined with trend-following logic.
📌 How It Works
A custom Hull Moving Average (HMA) is used to track the trend.
Two dynamic ATR-based bands are drawn above and below the HMA.
A signal is generated when the closing price touches the upper or lower ATR band within a small tolerance zone.
✅ Key Features
🔁 Alternating Signals: Only one Buy → then one Sell → then Buy again. No signal spam.
🟢🔴 Color-Changing HMA Line: Green = HMA rising | Red = HMA falling
📏 Price Tolerance Input: Define how close the candle must be to the ATR band to trigger a signal.
🔔 Real-Time Alerts: Easily set alerts for Buy and Sell signals — works in live markets.
🚫 No Repainting: All signals are confirmed at candle close and will not change afterward.
🎯 When to Use
Great for trend reversals, scalping zones, or identifying potential exhaustion points.
Works well on any timeframe or market (crypto, stocks, forex).
💬 Pro Tip:
Combine this with RSI, Volume, or ADX filters to build a complete confluence system.
📈 Built for traders who love clean logic, precision entries, and visual clarity.
Highest High Line with Multi-Timeframe Supertrend and RSIOverview:
This powerful indicator combines three essential elements for traders:
Highest High Line – Tracks the highest price over a customizable lookback period across different timeframes.
Multi-Timeframe Supertrend – Displays Supertrend values and trend directions for multiple timeframes simultaneously.
Relative Strength Index (RSI) – Shows RSI values across different timeframes for momentum analysis.
Features:
✅ Customizable Highest High Line:
Selectable timeframes: Daily, Weekly, Monthly, Quarterly, Yearly
Adjustable lookback period
✅ Multi-Timeframe Supertrend:
Supports 1min, 5min, 10min, 15min, 30min, 1H, Daily, Weekly, Monthly, Quarterly, Yearly
ATR-based calculation with configurable ATR period and multiplier
Identifies bullish (green) & bearish (red) trends
✅ Multi-Timeframe RSI:
Calculates RSI for the same timeframes as Supertrend
Overbought (≥70) and Oversold (≤30) signals with color coding
✅ Comprehensive Table Display:
A clean, structured table in the bottom-right corner
Displays Supertrend direction, value, and RSI for all timeframes
Helps traders quickly assess trend and momentum alignment
How to Use:
Use the Highest High Line to identify key resistance zones.
Confirm trend direction with Multi-Timeframe Supertrend.
Check RSI values to avoid overbought/oversold conditions before entering trades.
Align multiple timeframes for stronger confirmation of trend shifts.
Ideal For:
✅ Scalpers (lower timeframes: 1m–30m)
✅ Swing Traders (higher timeframes: 1H–D)
✅ Position Traders (Weekly, Monthly, Quarterly)
💡 Tip: Look for Supertrend & RSI confluence across multiple timeframes for higher probability setups.
Stochastic and MACD HistogramStochastic-MACD Fusion Histogram (concept)
How It Works:
This indicator combines Stochastic Oscillator and MACD Histogram to create a unique momentum-tracking histogram. It blends stochastic-based overbought/oversold levels with MACD-based trend strength, helping traders identify potential reversals and trend momentum more effectively.
Stochastic Component: Measures where the price is relative to its recent range, highlighting overbought/oversold conditions.
MACD Component: Captures momentum shifts by calculating the difference between two EMAs and a signal line.
Fusion Algorithm: The MACD histogram is normalized and combined with the Stochastic %K using a weighted formula (60% Stoch, 40% MACD) to smooth fluctuations and improve signal clarity.
Usage:
Histogram Colors:
Blue / SkyBlue: Positive momentum increasing.
Red / LightRed: Negative momentum increasing.
Levels:
Overbought (>30): Potential selling pressure.
Oversold (<-30): Potential buying pressure.
Zero Line: Momentum shift zone.
Notes:
Best to combine it with others indicators for trend confirmation, like Moving Average, MACD, etc.
This indicator is good for quick entry/exit in futures market, from few seconds up to minutes.
It works well on 5 minutes candle. Regular Hours works better.
To sell wait for histogram to go OVER overbought level, once the first candle reach BELOW the overbought level hit sell. Same strategy for buy when it hits oversold level. Make sure you won't use the indicator alone.
ADR Checker - Breakouts📈 ADR Checker – Breakouts
Gain the edge by knowing when a stock has already made its move.
🚀 What It Does:
The ADR Checker - Breakouts is a powerful yet simple visual tool that helps traders instantly assess whether a stock has already exceeded its Average Daily Range (ADR) for the day — a critical piece of information for momentum traders, swing traders, and especially those following breakout, VCP, or CANSLIM strategies.
Using a customizable on-screen table that always stays in view (regardless of zoom or chart scaling), this script shows:
✅ Average ADR% – 20-day average range, calculated in %.
📊 Today’s Move – how much the stock has moved today.
🔥 % of Avg ADR – today's move relative to its historical average, with live color feedback:
🟥 Over 100% (Overextended – danger!)
🟧 70-100% (Caution zone)
🟩 Below 70% (Room to move)
💡 Why It Matters:
One of the most overlooked mistakes by breakout traders is entering a trade after the move has already happened. If a stock has already moved more than its typical daily range, the odds of further continuation sharply decrease, while the risk of pullback or chop increases.
With this tool, you can:
🚫 Avoid chasing extended breakouts
🎯 Time entries before the real move
⚠️ Quickly assess risk/reward potential intraday
🧠 Example Use Case:
Imagine you're watching a classic VCP setup or flat base breakout. The stock breaks out on volume—but when you check this indicator, you see:
Today’s Move: 7.2%
Avg ADR: 5.3%
% of ADR: 135% 🟥
This tells you the stock is already well beyond its average daily range. While it may continue higher, odds now favor a consolidation, shakeout, or pullback. This is your cue to wait for a better entry or pass entirely.
On the flip side, if the breakout just started and the % of ADR is still under 50%, you have confirmation that there’s room to run — giving you more confidence to enter early.
⚙️ Fully Customizable:
Choose position on screen (top/bottom left/right)
Customize text color, background, and size
🔧 Install This Tool and:
✅ Stop chasing extended moves
✅ Add discipline to your entries
✅ Improve your breakout win rate
Perfect for VCP, CANSLIM, and BREAKOUT traders who want a clean, edge-enhancing visual guide.
TMO (True Momentum Oscillator)TMO ((T)rue (M)omentum (O)scilator)
Created by Mobius V01.05.2018 TOS Convert to TV using Claude 3.7 and ChatGPT 03 Mini :
TMO calculates momentum using the delta of price. Giving a much better picture of trend, tend reversals and divergence than momentum oscillators using price.
True Momentum Oscillator (TMO)
The True Momentum Oscillator (TMO) is a momentum-based technical indicator designed to identify trend direction, trend strength, and potential reversal points in the market. It's particularly useful for spotting overbought and oversold conditions, aiding traders in timing their entries and exits.
How it Works:
The TMO calculates market momentum by analyzing recent price action:
Momentum Calculation:
For a user-defined length (e.g., 14 bars), TMO compares the current closing price to past open prices. It assigns:
+1 if the current close is greater than the open price of the past bar (indicating bullish momentum).
-1 if it's less (indicating bearish momentum).
0 if there's no change.
The sum of these scores gives a raw momentum measure.
EMA Smoothing:
To reduce noise and false signals, this raw momentum is smoothed using Exponential Moving Averages (EMAs):
First, the raw data is smoothed by an EMA over a short calculation period (default: 5).
Then, it undergoes additional smoothing through another EMA (default: 3 bars), creating the primary "Main" line of the indicator.
Lastly, a "Signal" line is derived by applying another EMA (also default: 3 bars) to the main line, adding further refinement.
Trend Identification:
The indicator plots two lines:
Main Line: Indicates current momentum strength and direction.
Signal Line: Acts as a reference line, similar to a moving average crossover system.
When the Main line crosses above the Signal line, it suggests strengthening bullish momentum. Conversely, when the Main line crosses below the Signal line, it indicates increasing bearish momentum.
Overbought/Oversold Levels:
The indicator identifies key levels based on the chosen length parameter:
Overbought zone (positive threshold): Suggests the market might be overheated, and a potential bearish reversal or pullback could occur.
Oversold zone (negative threshold): Suggests the market might be excessively bearish, signaling a potential bullish reversal.
Clouds visually mark these overbought/oversold areas, making it easy to see potential reversal zones.
Trading Applications:
Trend-following: Traders can enter positions based on crossovers of the Main and Signal lines.
Reversals: The overbought and oversold areas highlight high-probability reversal points.
Momentum confirmation: Use TMO to confirm price action or other technical signals, improving trade accuracy and timing.
The True Momentum Oscillator provides clarity in identifying momentum shifts, making it a valuable addition to various trading strategies.
Choppiness IndicatorE.W. Dreiss, an Australian commodity trader, developed the Choppiness Index in 1993, drawing upon chaos theory to analyze financial markets. This technical indicator helps traders determine whether a market is trending or experiencing sideways (choppy) price action.
#Hint: The Market is considered TRENDING when the index is below 38.2 The Market is considered CHOPPY when the index is above 61.8. A move above the 38.2 Level indicates a possible end to a trend, and a move below 61.8 indicates a possible breakout from a period of consolidation.
Mobius constructed this in Thinkscript V001.03.2012, and Claude 3.7 Sonnet converted it to Pinescript V002. 03.2025
The Market is considered TRENDING when the index is below 38.2 The Market is considered CHOPPY when the index is above 61.8. A move above the 38.2 Level indicates a possible end to a trend, and a move below 61.8 indicates a potential breakout from a period of consolidation.
Integrated Reversal & Divergence DetectionThe Integrated Reversal & Divergence Detection indicator (IntgRevDiv) combines two powerful technical analysis systems into one comprehensive tool:
Advanced Reversal Detection System: Identifies potential market reversals using volume analysis, RSI divergence, and smart money techniques.
Divergence Indicator System: Detects regular and hidden divergences using multiple technical indicators and fractal patterns.
This integration provides confirmation from multiple analysis methods, resulting in higher quality trading signals.
Divergence Lines
When System B detects divergences, it draws lines connecting the relevant price pivots:
Green Lines: Connect bullish divergence pivot points.
Red Lines: Connect bearish divergence pivot points.
Information Tables
The indicator displays two information tables:
System A Table (Bottom Right):
Current signal status (BUY/SELL/NEUTRAL)
Volume, RSI, and SMT divergence status.
Composite signal information.
Divergence Table (Top Right):
Divergence existence indicators (+/-).
Consecutive divergence count.
Divergence quality rating.
Phase change indicators.
This system analyzes multiple factors to detect potential market reversals:
Volume Delta Analysis:
Calculates the difference between buying and selling volume.
Detects divergence between price action and volume.
When price increases but volume decreases, it may signal weakness.
RSI Divergence Detection:
Regular Divergence: Price makes a higher high but RSI makes a lower high (bearish) or price makes a lower low but RSI makes a higher low (bullish).
Hidden Divergence: Price makes a lower high but RSI makes a higher high (bearish) or price makes a higher low but RSI makes a lower low (bullish).
Smart Money Technique (SMT):
Analyzes correlation between the current instrument and a reference symbol.
Detects divergence in the correlation that may signal institutional activity.
Balance Range & Momentum Detection:
Identifies periods of price balance before breakouts.
Detects rapid price movements that may indicate reversals.
This system also focuses exclusively on detecting divergences using:
Multiple Technical Indicators:
MACD: Momentum and trend-following indicator.
Awesome Oscillator (AO): Momentum indicator.
RSI: Oscillator showing overbought/oversold conditions.
Fractal Pattern Detection:
Identifies swing highs and lows using fractals.
Uses these pivot points to detect divergences.
Phase Change Monitoring:
Detects when the histogram switches from positive to negative or vice versa.
Provides additional confirmation of trend changes.
Consecutive Divergence Tracking:
Counts consecutive bullish/bearish divergences.
Assigns quality ratings based on the count:
1 divergence: "Normal Dive".
2 divergences: "Good Dive".
3+ divergences: "Strong Dive".
Multi-Timeframe Analysis:
Apply the indicator to multiple timeframes.
Look for alignment of signals across timeframes.
Use longer timeframes for trend direction, shorter for entry timing.
Signal Filtering Based on Quality:
For higher probability trades, only take signals when:
Divergence quality shows "Good" or "Strong".
Phase change indicators show "+" in the direction of your trade.
Multiple divergence types (Volume, RSI, SMT) show agreement.
Combining with Support/Resistance:
Use the indicator's signals near key support/resistance levels.
Buy signals near support areas have higher probability.
Sell signals near resistance areas have higher probability.
Market Regime Adaptation:
I n trending markets: Focus on hidden divergences and SMT.
In ranging markets: Focus on regular divergences and RSI.
In high volatility: Increase the Volume Delta Threshold.
In low volatility: Decrease the Fractal Periods.
Signal Combination Logic Selection:
For fewer but higher quality signals: Use "Consensus" mode.
For more trading opportunities: Use "Enhanced" mode.
To emphasize price action reversals: Use "System A Priority".
To emphasize technical divergences: Use "System B Priority".
Market-Specific Adjustments:
Stocks/Indices: Focus on Volume Delta and RSI divergence.
Forex: Emphasize SMT and RSI divergence.
Crypto: Balance all three with slightly higher weight on Volume.
Commodities: Focus on MACD for divergence detection.
This indicator provides multiple layers of market analysis through its integrated approach. By understanding each component's function and how they work together, you can develop a nuanced trading strategy that takes advantage of high-probability reversal and divergence setups across various market conditions.
Multi-Indicator Trading DashboardMulti-Indicator Trading Dashboard: Comprehensive Analysis and Actionable Signals
This Pine Script indicator, "Multi-Indicator Trading Dashboard," provides a comprehensive overview of key market indicators and generates actionable trading signals, all presented in a clear, easy-to-read table format on your TradingView chart.
Key Features:
Real-time Indicator Analysis: The dashboard displays real-time values and signals for:
RSI (Relative Strength Index): Tracks overbought and oversold conditions.
MACD (Moving Average Convergence Divergence): Identifies trend changes and momentum.
ADX (Average Directional Index): Measures trend strength.
Volatility (ATR-based): Estimates volatility as a percentage, acting as a VIX proxy for single-symbol charts.
Trend Determination: Analyzes 20, 50, and 200-period EMAs to provide a clear trend assessment (Strong Bullish, Cautious Bullish, Cautious Bearish, Strong Bearish).
Combined Trading Signals: Integrates signals from RSI, MACD, ADX, and trend analysis to generate a combined "Buy," "Sell," or "Neutral" action signal.
User-Friendly Table Display: Presents all information in a neatly organized table, positioned at the top-right of your chart.
Visual Chart Overlays: Plots 20, 50, and 200-period EMAs directly on the chart for visual trend confirmation.
Background Color Alerts: Colors the chart's background based on the "Buy" or "Sell" action signal for quick visual cues.
Customizable Inputs: Allows you to adjust key parameters like RSI lengths, MACD settings, ADX thresholds, and EMA periods.
How It Works:
Indicator Calculations: The script calculates RSI, MACD, ADX, and a volatility proxy (ATR) using standard Pine Script functions.
Trend Analysis: It compares 20, 50, and 200-period EMAs to determine the overall trend direction.
Individual Signal Generation: It generates individual "Buy," "Sell," or "Neutral" signals based on RSI, MACD, and ADX values.
Combined Signal Logic: It combines the individual signals and trend analysis, assigning a "Buy" or "Sell" action only when at least two indicators align.
Table Display: It creates a table and populates it with the calculated values, signals, and trend information.
Chart Overlays: It plots the EMAs on the chart and colors the background based on the combined action signal.
Use Cases:
Quick Market Overview: Get a snapshot of key market indicators and trend direction at a glance.
Confirmation Tool: Use the combined signals to confirm your existing trading strategies.
Educational Purpose: Learn how different indicators interact and influence trading decisions.
Automated Alerting: Set up alerts based on the "Buy" or "Sell" action signals.
Customization:
Adjust the input parameters to fine-tune the indicator's sensitivity to your trading style and the specific market you're analyzing.
Disclaimer:
This indicator is for informational and educational purposes only and should not be considered financial advice. Always conduct thorough research and consult with 1 a qualified professional before making any 2 trading decisions.
SMIIOLThis indicator generates long signals.
The operation of the indicator is as follows;
First, true strength index is calculated with closing prices. We call this the "ergodic" curve.
Then the average of the ergodic (ema) is calculated to obtain the "signal" curve.
To calculate the "oscillator", the signal is subtracted from ergodic (oscillator = ergodic - signal).
The last variable to be used in the calculation is the average volume, calculated with sma.
Calculation for long signal;
- If the ergodic curve cross up the lower band and,
- If the hma slope is positive,
If all the above conditions are fullfilled, the long input signal is issued with "Buy" label.
