Price Action and 3 EMAs Momentum plus Sessions FilterThis indicator plots on the chart the parameters and signals of the Price Action and 3 EMAs Momentum plus Sessions Filter Algorithmic Strategy. The strategy trades based on time-series (absolute) and relative momentum of price close, highs, lows and 3 EMAs.
I am still learning PS and therefore I have only been able to write the indicator up to the Signal generation. I plan to expand the indicator to Entry Signals as well as the full Strategy.
The strategy works best on EURUSD in the 15 minutes TF during London and New York sessions with 1 to 1 TP and SL of 30 pips with lots resulting in 3% risk of the account per trade. I have already written the full strategy in another language and platform and back tested it for ten years and it was profitable for 7 of the 10 years with average profit of 15% p.a which can be easily increased by increasing risk per trade. I have been trading it live in that platform for over two years and it is profitable.
Contributions from experienced PS coders in completing the Indicator as well as writing the Strategy and back testing it on Trading View will be appreciated.
STRATEGY AND INDICATOR PARAMETERS
Three periods of 12, 48 and 96 in the 15 min TF which are equivalent to 3, 12 and 24 hours i.e (15 min * period / 60 min) are the foundational inputs for all the parameters of the PA & 3 EMAs Momentum + SF Algo Strategy and its Indicator.
3 EMAs momentum parameters and conditions
• FastEMA = ema of 12 periods
• MedEMA = ema of 48 periods
• SlowEMA = ema of 96 periods
• All the EMAs analyse price close for up to 96 (15 min periods) equivalent to 24 hours
• There’s Upward EMA momentum if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA
• There’s Downward EMA momentum if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA
PA momentum parameters and conditions
• HH = Highest High of 48 periods from 1st closed bar before current bar
• LL = Lowest Low of 48 periods from 1st closed bar from current bar
• Previous HH = Highest High of 84 periods from 12th closed bar before current bar
• Previous LL = Lowest Low of 84 periods from 12th closed bar before current bar
• All the HH & LL and prevHH & prevLL are within the 96 periods from the 1st closed bar before current bar and therefore indicative of momentum during the past 24 hours
• There’s Upward PA momentum if price close > HH and HH > prevHH and LL > prevLL
• There’s Downward PA momentum if price close < LL and LL < prevLL and HH < prevHH
Signal conditions and Status (BuySignal, SellSignal or Neutral)
• The strategy generates Buy or Sell Signals if both 3 EMAs and PA momentum conditions are met for each direction and these occur during the London and New York sessions
• BuySignal if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA and price close > HH and HH > prevHH and LL > prevLL and timeinrange (LDN&NY) else Neutral
• SellSignal if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA and price close < LL and LL < prevLL and HH < prevHH and timeinrange (LDN&NY) else Neutral
Entry conditions and Status (EnterBuy, EnterSell or Neutral)(NOT CODED YET)
• ENTRY IS NOT AT THE SIGNAL BAR but at the current bar tick price retracement to FastEMA after the signal
• EnterBuy if current bar tick price <= FastEMA and current bar tick price > prevHH at the time of the Buy Signal
• EnterSell if current bar tick price >= FastEMA and current bar tick price > prevLL at the time of the Sell Signal
在腳本中搜尋"algo"
NAND PerceptronExperimental NAND Perceptron based upon Python template that aims to predict NAND Gate Outputs. A Perceptron is one of the foundational building blocks of nearly all advanced Neural Network layers and models for Algo trading and Machine Learning.
The goal behind this script was threefold:
To prove and demonstrate that an ACTUAL working neural net can be implemented in Pine, even if incomplete.
To pave the way for other traders and coders to iterate on this script and push the boundaries of Tradingview strategies and indicators.
To see if a self-contained neural network component for parameter optimization within Pinescript was hypothetically possible.
NOTE: This is a highly experimental proof of concept - this is NOT a ready-made template to include or integrate into existing strategies and indicators, yet (emphasis YET - neural networks have a lot of potential utility and potential when utilized and implemented properly).
Hardcoded NAND Gate outputs with Bias column (X0):
// NAND Gate + X0 Bias and Y-true
// X0 // X1 // X2 // Y
// 1 // 0 // 0 // 1
// 1 // 0 // 1 // 1
// 1 // 1 // 0 // 1
// 1 // 1 // 1 // 0
Column X0 is bias feature/input
Column X1 and X2 are the NAND Gate
Column Y is the y-true values for the NAND gate
yhat is the prediction at that timestep
F0,F1,F2,F3 are the Dot products of the Weights (W0,W1,W2) and the input features (X0,X1,X2)
Learning rate and activation function threshold are enabled by default as input parameters
Uncomment sections for more training iterations/epochs:
Loop optimizations would be amazing to have for a selectable length for training iterations/epochs but I'm not sure if it's possible in Pine with how this script is structured.
Error metrics and loss have not been implemented due to difficulty with script length and iterations vs epochs - I haven't been able to configure the input parameters to successfully predict the right values for all four y-true values for the NAND gate (only been able to get 3/4; If you're able to get all four predictions to be correct, let me know, please).
// //---- REFERENCE for final output
// A3 := 1, y0 true
// B3 := 1, y1 true
// C3 := 1, y2 true
// D3 := 0, y3 true
PLEASE READ: Source article/template and main code reference:
towardsdatascience.com
towardsdatascience.com
towardsdatascience.com
Baseline-C [ID: AC-P]The "AC-P" version of jiehonglim's NNFX Baseline script is my personal customized version of the NNFX Baseline concept as part of the NNFX Algorithm stack/structure for 1D Trend Trading for Forex. Everget's JMA implementation is used for the baseline smoothing method, with optional ATR bands at 1.0x and 1.5x from the baseline.
NNFX = No Nonsense Forex
Baseline = Component of the NNFX Algorithm that consists of a single moving average
Baseline ---> Meant to be used in conjunction with ATR/C1/C2/Vol Indicator/Exit Indicator as per NNFX Algorithm setup/structure. C1 is 1st Confirmation Indicator, C2 is 2nd Confirmation Indicator.
JMA (Jurik Moving Average) is used for the baseline and slow baseline.
A slow baseline option is included, but disabled by default.
The faint orange/purple lines are 1.0x/1.5x ATR from the Baseline, and are what I use as potential TP/SL targets or to evaluate when to stay out of a trade (chop/missed entry/exit/other/ATR breach), depending on the trade setup (in conjunction with C1/C2/Vol Indicator/Exit Indicator)
This script is heavily based upon jiehonglim's NNFX Baseline script for signaling, barcoloring, and ATR.
SSL Channel option included but disabled by default (Erwinbeckers SSL component)
POC (Point of Control) from Volume Profile is included/enabled by default for both the current timeframe and 12HR timeframe
03.freeman's InfoPanel Divergence Indicator was used a reference to replace the current/previous ATR information infopanel/info draw from jiehonglim's script. I'm not sure whether I like the previous way ATR info was displayed vs how I have it currently, but it's something that is completely optional:
Specifically: I am tuning this baseline/indicator for 1D trading as part of the NNFX system, for Forex.
DO NOT USE THIS INDICATOR WITHOUT PROPER TUNING/ADJUSTMENT for your timeframe and asset class.
Note about lack of alerts:
Alerts for baseline crosses (and other crosses) have been purposefully omitted for this version upon initial publication. While getting alerts for baseline crosses under certain conditions/filtered conditions that eliminate low-importance signals and crossover whipsaw would be great, it's something I'm still looking into.
SPECIFICALLY: There are entry, exit, take profit, and continuation signal components in relation to the Baseline to the rest of the NNFX Algorithm stack (ATR/C1/C2/Vol Indicator/Exit Indicator), including but limited to the "1 candle rule" and the "7 candle rule" as per NNFX.
Implementing alerts that are significant that also factor in these rules while reducing alert spam/false signals would be ideal, but it's also the HTF/Daily chart - visually, entry/exit/continuation signal alignment is easy to spot when trading 1D - alerts may be redundant/a pursuit in diminishing returns (for now).
//-------------------------------------------------------------------
// Acknowledgements/Reference:
// jiehonglim, NNFX Baseline Script - Moving Averages
//
// Fractured, Many Moving Averages
//
// everget, Jurik Moving Average/JMA
//
// 03.freeman, InfoPanel Divergence Indicator
//
// Ggqmna Volume stops
//
// Libertus RSI Divs
//
// ChrisMoody, CM_Price-Action-Bars-Price Patterns That Work
//
// Erwinbeckers SSL Channel
//
MAMA [DCAUT]█ MAMA (MESA Adaptive Moving Average)
📊 OVERVIEW
The MESA Adaptive Moving Average (MAMA) represents an advanced implementation of John F. Ehlers' adaptive moving average system using the Hilbert Transform Discriminator. This indicator automatically adjusts to market cycles, providing superior responsiveness compared to traditional fixed-period moving averages while maintaining smoothness.
MAMA dynamically calculates two lines: the fast-adapting MAMA line and the following FAMA (Following Adaptive Moving Average) line. The system's core strength lies in its ability to automatically detect and adapt to the dominant market cycle, reducing lag during trending periods while providing stability during consolidation phases.
🎯 CORE CONCEPTS
Signal Interpretation:
• MAMA above FAMA: Indicates bullish trend momentum with the fast line leading upward movement
• MAMA below FAMA: Suggests bearish trend momentum with the fast line leading downward movement
• Golden Cross: MAMA crossing above FAMA signals potential upward momentum shift
• Death Cross: MAMA crossing below FAMA indicates potential downward momentum shift
• Line Convergence: MAMA and FAMA approaching each other suggests trend consolidation or potential reversal
Primary Applications:
• Trend Following: Enhanced responsiveness to trend changes compared to traditional moving averages
• Crossover Signals: MAMA/FAMA crossovers for identifying potential entry and exit points
• Cycle Analysis: Automatic adaptation to market's dominant cycle characteristics
• Reduced Lag: Minimized delay in trend detection while maintaining signal smoothness
📐 MATHEMATICAL FOUNDATION
Hilbert Transform Discriminator Technology:
The MAMA system employs John F. Ehlers' Hilbert Transform Discriminator, a sophisticated signal processing technique borrowed from telecommunications engineering. The Hilbert Transform creates a complex representation of the price series by generating a 90-degree phase-shifted version of the original signal, enabling precise cycle measurement.
The discriminator analyzes the instantaneous phase relationships between the original price series and its Hilbert Transform counterpart. This mathematical relationship reveals the dominant cycle period present in the market data at each point in time, forming the foundation for adaptive smoothing.
Instantaneous Period Calculation:
The algorithm computes the instantaneous period using the arctangent of the ratio between the Hilbert Transform and the original price series. This calculation produces a real-time measurement of the market's dominant cycle, typically ranging from short-term noise cycles to longer-term trend cycles.
The instantaneous period measurement undergoes additional smoothing to prevent erratic behavior from single-bar anomalies. This smoothed period value becomes the basis for calculating the adaptive alpha coefficient that controls the moving average's responsiveness.
Dynamic Alpha Coefficient System:
The adaptive alpha calculation represents the core mathematical innovation of MAMA. The alpha coefficient is derived from the instantaneous period measurement and constrained within the user-defined fast and slow limits.
The mathematical relationship converts the measured cycle period into an appropriate smoothing factor: shorter detected cycles result in higher alpha values (increased responsiveness), while longer cycles produce lower alpha values (increased stability). This creates an automatic adaptation mechanism that responds to changing market conditions.
MAMA/FAMA Calculation Process:
The MAMA line applies the dynamically calculated alpha coefficient to an exponential moving average formula: MAMA = alpha × Price + (1 - alpha) × MAMA . The FAMA line then applies a secondary smoothing operation to the MAMA line, creating a following average that provides confirmation signals.
This dual-line approach ensures that the fast-adapting MAMA line captures trend changes quickly, while the FAMA line offers a smoother confirmation signal, reducing the likelihood of acting on temporary price fluctuations.
Cycle Detection Mechanism:
The underlying cycle detection employs quadrature components derived from the Hilbert Transform to measure both amplitude and phase characteristics of price movements. This allows the system to distinguish between genuine trend changes and temporary price noise, automatically adjusting the smoothing intensity accordingly.
The mathematical framework ensures that during strong trending periods with clear directional movement, the algorithm reduces smoothing to minimize lag. Conversely, during consolidation phases with mixed signals, increased smoothing helps filter out false breakouts and whipsaws.
📋 PARAMETER CONFIGURATION
Source Selection Strategy:
• HL2 (High+Low)/2 (Default): Recommended for cycle analysis as it represents the midpoint of each period's trading range, reducing impact of opening gaps and closing spikes
• Close Price: Traditional choice reflecting final market sentiment, suitable for end-of-day analysis
• HLC3 (High+Low+Close)/3: Balanced approach incorporating range information with closing emphasis
• OHLC4 (Open+High+Low+Close)/4: Most comprehensive price representation for complete market view
Fast Limit Configuration (Default 0.5):
Controls the maximum responsiveness of the adaptive system. Higher values increase sensitivity to recent price changes but may introduce more noise. This parameter sets the upper bound for the dynamic alpha calculation.
Slow Limit Configuration (Default 0.05):
Determines the minimum responsiveness, providing stability during uncertain market conditions. Lower values increase smoothing but may cause delayed signals. This parameter sets the lower bound for the dynamic alpha calculation.
Parameter Relationship Considerations:
The fast and slow limits work together to define the adaptive range. The wider the range between these limits, the more dramatic the adaptation between trending and consolidating market conditions. Different market characteristics may benefit from different parameter configurations, requiring individual testing and validation.
📊 COLOR CODING SYSTEM
Line Visualization:
• Green Line (MAMA): The fast-adapting moving average that responds quickly to price changes
• Red Line (FAMA): The following adaptive moving average that provides confirmation signals
The fixed color scheme provides consistent visual identification of each line, enabling clear differentiation between the fast-adapting MAMA and the following FAMA throughout all market conditions.
💡 CORE VALUE PROPOSITION
Advantages Over Traditional Moving Averages:
• Cycle Adaptation: Automatically adjusts to market's dominant cycle rather than using fixed periods
• Reduced Lag: Faster response to genuine trend changes while filtering market noise
• Mathematical Foundation: Based on advanced signal processing techniques from telecommunications engineering
• Dual-Line System: Provides both fast adaptation (MAMA) and confirmation (FAMA) in one indicator
Comparative Performance Characteristics:
Unlike fixed-period moving averages that apply the same smoothing regardless of market conditions, MAMA adapts its behavior based on current market cycle characteristics. This may help reduce whipsaws during consolidation periods while maintaining responsiveness during trending phases.
Usage Considerations:
This indicator is designed for technical analysis purposes. The adaptive nature means that parameter optimization should consider the specific characteristics of the asset and timeframe being analyzed. Like all technical indicators, MAMA should be used as part of a comprehensive analysis approach rather than as a standalone signal generator.
Alert Functionality:
The indicator includes alert conditions for MAMA/FAMA crossovers, enabling automated notification of potential momentum shifts. These alerts can assist in timing analysis but should be combined with other forms of market analysis for decision-making purposes.
Señales de Compra/Venta - KUSKUS + MACD AlgoAlphaseñales de compra/venta con base en la alineación de dos indicadores
Kalman Ema Crosses - [JTCAPITAL]Kalman EMA Crosses - is a modified way to use Kalman Filters applied on Exponential Moving Averages (EMA Crosses) for Trend-Following.
The Kalman filter is a recursive smoothing algorithm that reduces noise from raw price or indicator data, and in this script it is applied both directly to price and on top of EMA calculations. The goal is to create cleaner, more reliable crossover signals between two EMAs that are less prone to false triggers caused by volatility or market noise.
The indicator works by calculating in the following steps:
Source Selection
The script starts by selecting the price input (default is Close, but can be adjusted). This chosen source is the foundation for all further smoothing and EMA calculations.
Kalman Filtering on Price
Depending on user settings, the selected source is passed through one of two independent Kalman filters. The filter takes into account process noise (representing expected market randomness) and measurement noise (representing uncertainty in the price data). The Kalman filter outputs a smoothed version of price that minimizes noise and preserves underlying trend structure.
EMA Calculation
Two exponential moving averages (EMA 1 and EMA 2) are then computed on the Kalman-smoothed price. The lengths of these EMAs are fully customizable (default 15 and 25).
Kalman Filtering on EMA Values
Instead of directly using raw EMA curves, the script applies a second layer of Kalman filtering to the EMA values themselves. This step significantly reduces whipsaw behavior, creating smoother crossovers that emphasize real momentum shifts rather than temporary volatility spikes.
Trend Detection via EMA Crossovers
-A bullish trend is detected when EMA 1 (fast) crosses above EMA 2 (slow).
-A bearish trend is detected when EMA 1 crosses below EMA 2.
The detected trend state is stored and used to dynamically color the plots.
Visual Representation
Both EMAs are plotted on the chart. Their colors shift to blue during bullish phases and purple during bearish phases. The area between the two EMAs is filled with a shaded region to clearly highlight trending conditions.
Buy and Sell Conditions :
- Buy Condition : When the Kalman-smoothed EMA 1 crosses above the Kalman-smoothed EMA 2, a bullish crossover is confirmed.
- Sell Condition : When EMA 1 crosses below EMA 2, a bearish crossover is confirmed.
Users may enhance the robustness of these signals by adjusting process noise, measurement noise, or EMA lengths. Lower measurement noise values make the filter react faster (but potentially noisier), while higher values make it smoother (but slower).
Features and Parameters :
- Source : Selectable price input (Close, Open, High, Low, etc.).
- EMA 1 Length : Defines the fast EMA period.
- EMA 2 Length : Defines the slow EMA period.
- Process Noise : Controls how much randomness the Kalman filter assumes in price dynamics.
- Measurement Noise : Controls how much uncertainty is assumed in raw input data.
- Kalman Usage : Option to apply Kalman filtering either before EMA calculation (on price) or after (on EMA values).
Specifications :
Kalman Filter
The Kalman filter is an optimal recursive algorithm that estimates the state of a system from noisy measurements. In trading, it is used to smooth prices or indicator values. By balancing process noise (expected volatility) with measurement noise (data uncertainty), it generates a smoothed signal that reacts adaptively to market conditions.
Exponential Moving Average (EMA)
An EMA is a weighted moving average that emphasizes recent data more heavily than older data. This makes it more responsive than a simple moving average (SMA). EMAs are widely used to identify trends and momentum shifts.
EMA Crossovers
The crossing of a fast EMA above a slow EMA suggests bullish momentum, while the opposite suggests bearish momentum. This is a cornerstone technique in trend-following systems.
Dual Kalman Filtering
Applying Kalman both to raw price and to the EMAs themselves reduces whipsaws further. It creates crossover signals that are not only smoothed but also validated across two levels of noise reduction. This significantly enhances signal reliability compared to traditional EMA crossovers.
Process Noise
Represents the filter’s assumption about how much the underlying market can randomly change between steps. Higher values make the filter adapt faster to sudden changes, while lower values make it more stable.
Measurement Noise
Represents uncertainty in price data. A higher measurement noise value means the filter trusts the model more than the observed data, leading to smoother results. A lower value makes the filter more reactive to observed price fluctuations.
Trend Coloring & Fill
The use of dynamic colors and filled regions provides immediate visual recognition of trend states, helping traders act faster and with greater clarity.
Enjoy!
Chimera [theUltimator5]In myth, the chimera is an “impossible” hybrid—lion, goat, and serpent fused into one—striking to look at and formidable in presence. The word has come to mean a beautiful, improbable union of parts that shouldn’t work together, yet do.
Chimera is a dual-mode market context tool that blends a multi-input oscillator with classic ADX/DI trend strength, plus optional multi-timeframe “gap-line” tracking. Use it to visualize regime (trend vs. range), momentum swings around an adaptive midline, and higher timeframe (HTF) reference levels that auto-terminate on touch/cross.
Modes
1) Oscillator view
A smoothed composite of five common inputs—RSI, MACD (oscillator), Bollinger position, Stochastic, and an ATR/DI-weighted bias. Each is normalized to a comparable 0–100 style scale, averaged, and plotted as a candle-style oscillator (short vs. long smoothing, wickless for clarity). A dynamic midline with standard-deviation bands frames neutral → bearish/bullish zones. Colors ramp from neutral to your chosen Oversold/Overbought endpoints; consolidation can override to white.
Here is a description of the (5) signals used to calculate the sentiment oscillator:
RSI (14): Measures recent momentum by comparing average gains vs. losses. High = strength after advances; low = weakness after declines. (Z-score normalized to 0–100.)
MACD oscillator (12/26/9): Uses the difference between MACD and its signal (histogram) to gauge momentum shifts. Positive = bullish tilt; negative = bearish. (Z-score normalized.)
Bollinger Bands position (20, 2): Locates price within the bands (0–100 from lower → upper). Near upper suggests strength/expansion; near lower suggests weakness/contraction. (Then normalized.)
Stochastic (14, 3, 3): Shows where the close sits within the recent high-low range, smoothed via %D. Higher values = closes near highs; lower = near lows. (Scaled 0–100.)
ATR/DI composite (14): Volatility-weighted directional bias: (+DI − −DI) amplified by ATR as a % of price and its relative average. Positive = bullish pressure with volatility; negative = bearish. (Rank/scale normalized.)
All five are normalized and averaged into one composite, then smoothed (short/long) and compared to an adaptive midline with bands.
2) ADX view
Shows ADX, +DI, –DI with user-defined High Threshold. Transparency and color shift with regime. When ADX is strong, a directional “fire/ice” gradient fills the area between ADX and the high threshold, biased toward the dominant DI; when ADX is weak, a soft white fade highlights low-trend conditions.
HTF gap-line tracking (optional; both modes)
Detects “gap-like” reference levels after weak-trend consolidation flips into a sudden DI jump.
Anchors a line at the event bar’s open and auto-terminates upon first touch/cross (tick-size tolerance).
Auto-selects up to three higher timeframes suited to your chart resolution and prints non-overlapping lines with labels like 1H / 4H / 1D. Lower-priority duplicates are suppressed to reduce clutter.
Confirmation / repaint notes
Signals and lines finalize on bar close of the relevant timeframe.
HTF elements update only on the HTF bar close. During a forming bar they may appear transiently.
Line removal finalizes after the bar that produced the touch/cross closes.
Visual cues & effects
Oscillator candles: Open/High = long smoothing; Low/Close = short smoothing (no wicks).
Adaptive bands: Midline ± StdDev Multiplier × stdev of the blended series.
Consolidation tint: Optional white backdrop/candles when the consolidation condition is true (balance + low ADX).
Breakout VFX (optional): With strong DI/ADX and Bollinger breaks, renders a subtle “fire” flare above upper-band thrusts or “ice” shelf below lower-band thrusts.
Inputs (high-level)
Visual Style: Oscillator or ADX.
General (Oscillator): Lookback Period, Short/Long Smoothing, Standard Deviation Multiplier.
Color (Oscillator): Oversold/Overbought colors for gradient endpoints.
Plot (Oscillator): Show Candles, Show Slow MA Line, Show Individual Component (RSI/MACD/BB/Stoch/ATR).
Table (Oscillator): Show Information Table & position (compact dashboard of component values + status).
ADX / Gaps / VFX (both modes): ADX High Threshold, Highlight Backgrounds, Show Gap Labels, Visual Overlay Effects, and color choices for current-TF & HTF lines.
HTF selection: Automatic ladder (3 tiers) based on your chart timeframe.
Alerts (built-in)
Buy Signal – Primary: Oscillator exits oversold.
Sell Signal – Primary: Oscillator exits overbought.
Gap Fill Line Created (Any TF)
Gap Fill Line Terminated (Any TF)
ADX Crossed ABOVE/BELOW Low Threshold
ADX Crossed ABOVE/BELOW High Threshold
Consolidation Started
Alerts evaluate on the close of the relevant timeframe.
How to read it (quick guide)
Pick your lens: Oscillator for blended momentum around an adaptive midline; ADX for trend strength and DI skew.
Watch extremes & mean re-entries (Oscillator): Approaches to the top/bottom band show persistent momentum; returns toward the midline show normalization.
Check regime (ADX): Below Low = low-trend; above High = strong trend, with “fire/ice” bias toward +DI/–DI.
Track gap lines: Fresh labels mark new reference levels; lines auto-remove on first interaction. HTF lines add context but finalize only on HTF close.
The uniqueness from this indicator comes from multiple areas:
1. A unique multi-timeframe algorithm detects gap fill zones and plots them on the chart.
2. Visual effects for both visual modes were hand crafted to provide a visually stunning and intuitive interface.
3. The algorithm to determine sentiment uses a unique blend of weight and sensitivity adjustment to create a plot with elastic upper and lower bounds based off historical volatility and price action.
Information Flow Analysis[b🔄 Information Flow Analysis: Systematic Multi-Component Market Analysis Framework
SYSTEM OVERVIEW AND ANALYTICAL FOUNDATION
The Information Flow Kernel - Hybrid combines established technical analysis methods into a unified analytical framework. This indicator systematically processes three distinct data streams - directional price momentum, volume-weighted pressure dynamics, and intrabar development patterns - integrating them through weighted mathematical fusion to produce statistically normalized market flow measurements.
COMPREHENSIVE MATHEMATICAL FRAMEWORK
Component 1: Directional Flow Analysis
The directional component analyzes price momentum through three mathematical vectors:
Price Vector: p = C - O (intrabar directional bias)
Momentum Vector: m = C_t - C_{t-1} (bar-to-bar velocity)
Acceleration Vector: a = m_t - m_{t-1} (momentum rate of change)
Directional Signal Integration:
S_d = \text{sgn}(p) \cdot |p| + \text{sgn}(m) \cdot |m| \cdot 0.6 + \text{sgn}(a) \cdot |a| \cdot 0.3
The signum function preserves directional information while absolute values provide magnitude weighting. Coefficients create a hierarchy emphasizing intrabar movement (100%), momentum (60%), and acceleration (30%).
Final Directional Output: K_1 = S_d \cdot w_d where w_d is the directional weight parameter.
Component 2: Volume-Weighted Pressure Analysis
Volume Normalization: r_v = \frac{V_t}{\overline{V_n}} where \overline{V_n} represents the n-period simple moving average of volume.
Base Pressure Calculation: P_{base} = \Delta C \cdot r_v \cdot w_v where \Delta C = C_t - C_{t-1} and w_v is the velocity weighting factor.
Volume Confirmation Function:
f(r_v) = \begin{cases}
1.4 & \text{if } r_v > 1.2 \
0.7 & \text{if } r_v < 0.8 \
1.0 & \text{otherwise}
\end{cases}
Final Pressure Output: K_2 = P_{base} \cdot f(r_v)
Component 3: Intrabar Development Analysis
Bar Position Calculation: B = \frac{C - L}{H - L} when H - L > 0 , else B = 0.5
Development Signal Function:
S_{dev} = \begin{cases}
2(B - 0.5) & \text{if } B > 0.6 \text{ or } B < 0.4 \
0 & \text{if } 0.4 \leq B \leq 0.6
\end{cases}
Final Development Output: K_3 = S_{dev} \cdot 0.4
Master Integration and Statistical Normalization
Weighted Component Fusion: F_{raw} = 0.5K_1 + 0.35K_2 + 0.15K_3
Sensitivity Scaling: F_{master} = F_{raw} \cdot s where s is the sensitivity parameter.
Statistical Normalization Process:
Rolling Mean: \mu_F = \frac{1}{n}\sum_{i=0}^{n-1} F_{master,t-i}
Rolling Standard Deviation: \sigma_F = \sqrt{\frac{1}{n}\sum_{i=0}^{n-1} (F_{master,t-i} - \mu_F)^2}
Z-Score Computation: z = \frac{F_{master} - \mu_F}{\sigma_F}
Boundary Enforcement: z_{bounded} = \max(-3, \min(3, z))
Final Normalization: N = \frac{z_{bounded}}{3}
Flow Metrics Calculation:
Intensity: I = |z|
Strength Percentage: S = \min(100, I \times 33.33)
Extreme Detection: \text{Extreme} = I > 2.0
DETAILED INPUT PARAMETER SPECIFICATIONS
Sensitivity (0.1 - 3.0, Default: 1.0)
Global amplification multiplier applied to the master flow calculation. Functions as: F_{master} = F_{raw} \cdot s
Low Settings (0.1 - 0.5): Enhanced precision for subtle market movements. Optimal for low-volatility environments, scalping strategies, and early detection of minor directional shifts. Increases responsiveness but may amplify noise.
Moderate Settings (0.6 - 1.2): Balanced sensitivity for standard market conditions across multiple timeframes.
High Settings (1.3 - 3.0): Reduced sensitivity to minor fluctuations while emphasizing significant flow changes. Ideal for high-volatility assets, trending markets, and longer timeframes.
Directional Weighting (0.1 - 1.0, Default: 0.7)
Controls emphasis on price direction versus volume and positioning factors. Applied as: K_{1,weighted} = K_1 \times w_d
Lower Values (0.1 - 0.4): Reduces directional bias, favoring volume-confirmed moves. Optimal for ranging markets where momentum may generate false signals.
Higher Values (0.7 - 1.0): Amplifies directional signals from price vectors and acceleration. Ideal for trending conditions where directional momentum drives price action.
Velocity Weighting (0.1 - 1.0, Default: 0.6)
Scales volume-confirmed price change impact. Applied in: P_{base} = \Delta C \times r_v \times w_v
Lower Values (0.1 - 0.4): Dampens volume spike influence, focusing on sustained pressure patterns. Suitable for illiquid assets or news-sensitive markets.
Higher Values (0.8 - 1.0): Amplifies high-volume directional moves. Optimal for liquid markets where volume provides reliable confirmation.
Volume Length (3 - 20, Default: 5)
Defines lookback period for volume averaging: \overline{V_n} = \frac{1}{n}\sum_{i=0}^{n-1} V_{t-i}
Short Periods (3 - 7): Responsive to recent volume shifts, excellent for intraday analysis.
Long Periods (13 - 20): Smoother averaging, better for swing trading and higher timeframes.
DASHBOARD SYSTEM
Primary Flow Gauge
Bilaterally symmetric visualization displaying normalized flow direction and intensity:
Segment Calculation: n_{active} = \lfloor |N| \times 15 \rfloor
Left Fill: Bearish flow when N < -0.01
Right Fill: Bullish flow when N > 0.01
Neutral Display: Empty segments when |N| \leq 0.01
Visual Style Options:
Matrix: Digital blocks (▰/▱) for quantitative precision
Wave: Progressive patterns (▁▂▃▄▅▆▇█) showing flow buildup
Dots: LED-style indicators (●/○) with intensity scaling
Blocks: Modern squares (■/□) for professional appearance
Pulse: Progressive markers (⎯ to █) emphasizing intensity buildup
Flow Intensity Visualization
30-segment horizontal bar graph with mathematical fill logic:
Segment Fill: For i \in : filled if \frac{i}{29} \leq \frac{S}{100}
Color Coding System:
Orange (S > 66%): High intensity, strong directional conviction
Cyan (33% ≤ S ≤ 66%): Moderate intensity, developing bias
White (S < 33%): Low intensity, neutral conditions
Extreme Detection Indicators
Circular markers flanking the gauge with state-dependent illumination:
Activation: I > 2.0 \land |N| > 0.3
Bright Yellow: Active extreme conditions
Dim Yellow: Normal conditions
Metrics Display
Balance Value: Raw master flow output ( F_{master} ) showing absolute directional pressure
Z-Score Value: Statistical deviation ( z_{bounded} ) indicating historical context
Dynamic Narrative System
Context-sensitive interpretation based on mathematical thresholds:
Extreme Flow: I > 2.0 \land |N| > 0.6
Moderate Flow: 0.3 < |N| \leq 0.6
High Volatility: S > 50 \land |N| \leq 0.3
Neutral State: S \leq 50 \land |N| \leq 0.3
ALERT SYSTEM SPECIFICATIONS
Mathematical Trigger Conditions:
Extreme Bullish: I > 2.0 \land N > 0.6
Extreme Bearish: I > 2.0 \land N < -0.6
High Intensity: S > 80
Bullish Shift: N_t > 0.3 \land N_{t-1} \leq 0.3
Bearish Shift: N_t < -0.3 \land N_{t-1} \geq -0.3
TECHNICAL IMPLEMENTATION AND PERFORMANCE
Computational Architecture
The system employs efficient calculation methods minimizing processing overhead:
Single-pass mathematical operations for all components
Conditional visual rendering (executed only on final bar)
Optimized array operations using direct calculations
Real-Time Processing
The indicator updates continuously during bar formation, providing immediate feedback on changing market conditions. Statistical normalization ensures consistent interpretation across varying market regimes.
Market Applicability
Optimal performance in liquid markets with consistent volume patterns. May require parameter adjustment for:
Low-volume or after-hours sessions
News-driven market conditions
Highly volatile cryptocurrency markets
Ranging versus trending market environments
PRACTICAL APPLICATION FRAMEWORK
Market State Classification
This indicator functions as a comprehensive market condition assessment tool providing:
Trend Analysis: High intensity readings ( S > 66% ) with sustained directional bias indicate strong trending conditions suitable for momentum strategies.
Reversal Detection: Extreme readings ( I > 2.0 ) at key technical levels may signal potential trend exhaustion or reversal points.
Range Identification: Low intensity with neutral flow ( S < 33%, |N| < 0.3 ) suggests ranging market conditions suitable for mean reversion strategies.
Volatility Assessment: High intensity without clear directional bias indicates elevated volatility with conflicting pressures.
Integration with Trading Systems
The normalized output range facilitates integration with automated trading systems and position sizing algorithms. The statistical basis provides consistent interpretation across different market conditions and asset classes.
LIMITATIONS AND CONSIDERATIONS
This indicator combines established technical analysis methods and processes historical data without predicting future price movements. The system performs optimally in liquid markets with consistent volume patterns and may produce false signals in thin trading conditions or during news-driven market events. This indicator is provided for educational and analytical purposes only and does not constitute financial advice. Users should combine this analysis with proper risk management, position sizing, and additional confirmation methods before making any trading decisions. Past performance does not guarantee future results.
Note: The term "kernel" in this context refers to modular calculation components rather than mathematical kernel functions in the formal computational sense.
As quantitative analyst Ralph Vince noted: "The essence of successful trading lies not in predicting market direction, but in the systematic processing of market information and the disciplined management of probability distributions."
— Dskyz, Trade with insight. Trade with anticipation.
Machine Learning-Inspired Supply & Demand Zones [AlgoPoint]This indicator is a Smart Supply & Demand Zone tool, developed with principles inspired by Machine Learning (ML). It intelligently filters out market noise, allowing you to focus only on the most significant zones where institutional order flow is likely present.
💡 How It Works: Why Is This Indicator "Smart"?
Unlike traditional indicators that only measure simple price movements, this script uses an algorithm that asks the same critical questions an experienced market analyst would to qualify a zone:
- 1. Price Imbalance: How fast and aggressively did the price leave the zone? Our algorithm measures the body size of the "departure candle" relative to the current market volatility (ATR). A zone is only considered if it was formed by an explosive move that is statistically significant, indicating a major imbalance between buyers and sellers.
- 2. Volume Confirmation: Did the "smart money" participate in this move? The script checks if the volume on the departure candle was significantly higher than the recent average volume. A spike in volume confirms that the move was backed by institutional interest, adding strength and validity to the zone.
- 3. Valid Pivot Structure: Did the zone originate from a meaningful swing high or low? The algorithm first identifies a valid pivot structure, ensuring that zones are not drawn from insignificant or random price fluctuations.
Only when a potential zone passes these three critical tests—our "quality filter"—is it drawn on your chart.
🚀 Features & How to Use
Using the indicator is straightforward. You will see two primary types of boxes on your chart:
* 🟥 Red Box (Supply Zone): An area of potential resistance where selling pressure is likely to be strong. Look for potential shorting opportunities as the price approaches this zone.
* 🟩 Green Box (Demand Zone): An area of potential support where buying pressure is likely to be strong. Look for potential long opportunities as the price pulls back into this zone.
Dynamic Zone Management
This indicator is not static; it lives and breathes with the market:
- Fresh Zone: A newly formed zone appears in its full, vibrant color. These are the highest-probability zones as they have not yet been re-tested.
- Broken / Flipped Zone: You have full control over what happens when a zone is broken! In the settings, you can choose:
- Delete Zone: The zone will be removed completely when the price closes through it.
- Show as Broken (Flip): When broken, the zone will turn gray, stop extending, and remain on your chart. This is extremely useful for identifying Support/Resistance Flips, where a broken demand zone becomes new resistance, or a broken supply zone becomes new support.
⚙️ Settings & Customization
Fine-tune the indicator to match your personal trading style via the settings menu:
- Breakout Behavior: The most powerful feature. Choose between Delete Zone and Show as Broken (Flip) to customize your chart.
- Zone Finding Logic: Control the indicator's sensitivity.
- Selective: Requires both strong imbalance and high volume. Finds fewer, but higher-quality, zones.
- Moderate: Requires either strong imbalance or high volume. Finds more potential zones.
- Sensitivity Settings: Adjust the ATR Multiplier and Volume Multiplier to make the criteria for a "strong" zone stricter or looser.
Swing Z | Zillennial Technologies Inc.Swing Z by Zillennial Technologies Inc. is an advanced algorithmic framework built specifically for cryptocurrency markets. It integrates multiple layers of technical analysis into a single decision-support tool, generating buy and sell signals only when several independent confirmations align.
Core Concept
Swing Z fuses trend structure, momentum oscillators, volatility signals, and price action tools to capture high-probability trading opportunities in volatile crypto environments.
Trend Structure (EMA 9, 21, 50, 200)
Short-term EMAs (9 & 21) detect immediate momentum shifts.
Longer-term EMAs (50 & 200) define the broader trend and dynamic support/resistance.
Momentum & Confirmation Layer
RSI measures relative strength and market conditions.
MACD crossovers confirm momentum shifts and trend continuations.
Volatility & Market Pressure
TTM Squeeze highlights compression zones likely to precede breakouts.
Volume analysis confirms conviction behind directional moves.
VWAP (Volume Weighted Average Price) establishes intraday value zones and institutional benchmarks.
Price Action Filters
Fibonacci retracements are integrated to identify key reversal and continuation levels.
Signals are produced only when multiple conditions agree, reducing noise and improving reliability in fast-moving crypto markets.
Features
Tailored for cryptocurrency trading across major pairs (BTC, ETH, and altcoins).
Works effectively on swing and trend-based timeframes (1H–1D).
Combines trend, momentum, volatility, and price action into a single framework.
Generates clear Buy/Sell markers and integrates with TradingView alerts.
How to Use
Apply to a clean chart for the clearest visualization.
Use Swing Z as a swing trading tool, aligning entries with both trend structure and momentum confirmation.
Combine with your own stop-loss, take-profit, and position sizing rules.
Avoid application on non-standard chart types such as Renko, Heikin Ashi, or Point & Figure, which may distort results.
Disclaimer
Swing Z is designed as a decision-support tool, not financial advice.
All backtesting should use realistic risk, commission, and slippage assumptions.
Past results do not guarantee future performance.
Signals do not repaint but may adjust as new data develops in real-time.
Why Swing Z is original & useful:
Swing Z unifies EMA trend structure, RSI, MACD, TTM Squeeze, VWAP, Fibonacci retracements, and volume analysis into a single algorithmic framework. This multi-confirmation approach improves accuracy by requiring consensus across trend, momentum, volatility, and price action — a design made specifically for the challenges and volatility of cryptocurrency markets.
Alexmoku Genesis v0.2.6 — Runtime BulletproofAlexmoku Genesis v0.2.6 – Reinventing Ichimoku with Precision and Intelligence
Built by Alex • Engineered for traders who demand more than lagging clouds
🔬 Overview
Alexmoku Genesis is a ground-up reimagining of the traditional Ichimoku system — retaining its philosophical foundations of harmony, balance, and structure, while infusing it with modern logic, advanced volatility modeling, and AI-aligned signal classification.
This is not your grandfather’s Ichimoku. Genesis transforms it into a forward-sensing, volatility-aware system that adapts in real time and guides discretionary and algorithmic traders alike with smarter signals, predictive structure, and built-in trade intelligence.
⚙️ Core Enhancements
📐 Volatility-Responsive Smoothing
Tenkan-sen and Kijun-sen lengths are dynamically adjusted based on recent price volatility (ATR-based).
Prevents overreaction in choppy markets and improves responsiveness during strong trends.
🌀 Adaptive Cloud Projection
Span A and Span B are still projected 52 periods forward — but cloud width adapts to market rhythm, not just static values.
🕵️ Enhanced Chikou Span (CKS+)
Chikou logic is upgraded to emphasize structure interaction, not just simple price overlay.
Useful for identifying support/resistance echoes and divergence validation.
🌐 Multi-Timeframe Cloud Awareness (Genesis Core)
Internal alignment checks between higher and lower timeframe Kumo positioning.
Future module support for overlaying MTF clouds.
🔖 Signal Classifier Engine (Experimental)
Each major structure event is tagged with signal intent:
📦 prep
🚀 launch
🔁 reversion
🪤 trap
Enables faster discretionary reads or future automation.
🧠 Trust Score Logic (Coming soon)
Future versions will assign numerical trust scores (1–10) to trade setups based on confluence.
🧰 Settings
🔧 Volatility Scaling Factor – Adjusts how reactive the indicator is to volatility. Default: 300.
🌫 Displacement (Kumo) – Cloud projection forward. Default (and required): 52.
⛅ Cloud Display Toggle – Show/hide Kumo visuals without affecting logic.
⚡️ Future expansion modules already scaffolded (MTF overlays, color-coded signal classifiers, Trust Score engine, etc.)
🧘 Philosophy Behind the System
"This isn’t just about catching runners — it’s about becoming the kind of person who can trade with clarity, peace, and precision."
Alexmoku Genesis reflects the W.E.A.L.T.H. System's holistic philosophy:
Wealth
Engineered
Algorithmic
Leveraged
Trading
Holistically
Trading isn't just a strategy. It's a mirror. Genesis is designed to train both your execution and your awareness.
⚠️ Disclaimer
This tool is designed for experienced technical traders and is still in active development. Use judgment and proper risk management. This is not financial advice.
ICT Macro Time Window NYThis script highlights the typical ICT “macro” algorithm activity windows on your chart. It marks 10 minutes before to 10 minutes after each full hour, based on New York time (NY). The display is restricted to the 00:00 – 16:00 NY time range.
Overlay on chart with semi-transparent background
Automatically adjusts to the chart timeframe
Customizable: window start/end minutes, hours, and background color
Ideal for traders following ICT concepts to visually identify high-probability algorithm activity periods.
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
QFisher-R™ [ParadoxAlgo]QFISHER-R™ (Regime-Aware Fisher Transform)
A research/education tool that helps visualize potential momentum exhaustion and probable inflection zones using a quantitative, non-repainting Fisher framework with regime filters and multi-timeframe (MTF) confirmation.
What it does
Converts normalized price movement into a stabilized Fisher domain to highlight potential turning points.
Uses adaptive smoothing, robust (MAD/quantile) thresholds, and optional MTF alignment to contextualize extremes.
Provides a Reversal Probability Score (0–100) to summarize signal confluence (extreme, slope, cross, divergence, regime, and MTF checks).
Key features
Non-repainting logic (bar-close confirmation; security() with no lookahead).
Dynamic exhaustion bands (data-driven thresholds vs fixed ±2).
Adaptive smoothing (efficiency-ratio based).
Optional divergence tags on structurally valid pivots.
MTF confirmation (same logic computed on a higher timeframe).
Compact visuals with subtle plotting to reduce chart clutter.
Inputs (high level)
Source (e.g., HLC3 / Close / HA).
Core lookback, fast/slow range blend, and ER length.
Band sensitivity (robust thresholding).
MTF timeframe(s) and agreement requirement.
Toggle divergence & intrabar previews (default off).
Signals & Alerts
Turn Candidate (Up/Down) when multiple conditions align.
Trade-Grade Turn when score ≥ threshold and MTF agrees.
Divergence Confirmed when structural criteria are met.
Alerts are generated on confirmed bar close by default. Optional “preview” mode is available for experimentation.
How to use
Start on your preferred timeframe; optionally enable an HTF (e.g., 4×) for confirmation.
Look for RPS clusters near the exhaustion bands, slope inflections, and (optionally) divergences.
Combine with your own risk management, liquidity, and trend context.
Paper test first and calibrate thresholds to your instrument and timeframe.
Notes & limitations
This is not a buy/sell signal generator and does not predict future returns.
Readings can remain extreme during strong trends; use HTF context and your own filters.
Parameters are intentionally conservative by default; adjust carefully.
Compliance / Disclaimer
Educational & research tool only. Not financial advice. No recommendation to buy/sell any security or derivative.
Past performance, backtests, or examples (if any) are not indicative of future results.
Trading involves risk; you are responsible for your own decisions and risk management.
Built upon the Fisher Transform concept (Ehlers); all modifications, smoothing, regime logic, scoring, and visualization are original work by Paradox Algo.
AI BUY AND SELL BGThe Gk fundamental is a next gen level ai powered BUY and SELL system engineered for big market moves, it runs an embedded algorithm within a algorithm to detect breakout points before they happen giving traders insane results
works best and only 2h and 4h
Time Window Optimizer [theUltimator5]The Time Window Optimizer is designed to identify the most profitable 30-minute trading windows during regular market hours (9:30 AM - 4:00 PM EST). This tool helps traders optimize their intraday strategies by automatically discovering time periods with the highest historical performance or allowing manual selection for custom analysis. It also allows you to select manual timeframes for custom time period analysis.
🏆 Automatic Window Discovery
The core feature of this indicator is its intelligent Auto-Find Best 30min Window system that analyzes all 13 possible 30-minute time slots during market hours.
How the Algorithm Works:
Concurrent Analysis: The indicator simultaneously tracks performance across all 13 time windows (9:30-10:00, 10:00-10:30, 10:30-11:00... through 15:30-16:00)
Daily Performance Tracking: For each window, it captures the percentage change from window open to window close on every trading day
Cumulative Compounding: Daily returns are compounded over time to show the true long-term performance of each window, starting from a normalized value of 1.0
Dynamic Optimization: The system continuously identifies the window with the highest cumulative return and highlights it as the optimal choice
Statistical Validation: Performance is validated through multiple metrics including average daily returns, win rates, and total sample size
Visual Representation:
Best Window Line: The top-performing window is displayed as a thick colored line for easy identification
All 13 Lines (optional): Users can view performance lines for all time windows simultaneously to compare relative performance
Smart Coloring: Lines are color-coded (green for gains, red for losses) with the best performer highlighted in a user-selected color
📊 Comprehensive Performance Analysis
The indicator provides detailed statistics in an information table:
Average Daily Return: Mean percentage change per trading session
Cumulative Return: Total compounded performance over the analysis period
Win Rate: Percentage of profitable days (colored green if ≥50%, red if <50%)
Buy & Hold Comparison: Shows outperformance vs. simple buy-and-hold strategy
Sample Size: Number of trading days analyzed for statistical significance
🛠️ User Settings
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Auto-Optimization Controls:
Auto-Find Best Window: Toggle to enable/disable automatic optimization
Show All 13 Lines: Display all time window performance lines simultaneously
Best Window Line Color: Customize the color of the top-performing window
Manual Mode:
imgur.com
Custom Time Window: Set any desired time range using session format (HHMM-HHMM)
Crypto Support: Built-in timezone offset adjustment for cryptocurrency markets
Chart Type Options: Switch between candlestick and line chart visualization
Visual Customization:
imgur.com
Background Highlighting: Optional background color during active time windows
Candle Coloring: Custom colors for bullish/bearish candles within the time window
Table Positioning: Flexible placement of the statistics table anywhere on the chart
🔧 Technical Features
Market Compatibility:
Stock Markets: Optimized for traditional market hours (9:30 AM - 4:00 PM EST)
Cryptocurrency: Includes timezone offset adjustment for 24/7 crypto markets
Exchange Detection: Automatically detects crypto exchanges and applies appropriate settings
Performance Optimization:
Efficient Calculation: Uses separate arrays for each time block to minimize computational overhead
Real-time Updates: Dynamically updates the best-performing window as new data becomes available
Memory Management: Optimized data structures to handle large datasets efficiently
💡 Use Cases
Strategy Development: Identify the most profitable trading hours for your specific instruments
Risk Management: Focus trading activity during historically successful time periods
Performance Comparison: Evaluate whether time-specific strategies outperform buy-and-hold
Market Analysis: Understand intraday patterns and market behavior across different time windows
📈 Key Benefits
Data-Driven Decisions: Base trading schedules on historical performance data
Automated Analysis: No manual calculation required - the algorithm does the work
Flexible Implementation: Works in both automated discovery and manual selection modes
Comprehensive Metrics: Multiple performance indicators for thorough analysis
Visual Clarity: Clear, color-coded visualization makes interpretation intuitive
This indicator transforms complex intraday analysis into actionable insights, helping traders optimize their time allocation and improve overall trading performance through systematic, data-driven approach to market timing.
Bollinger Heatmap [Quantitative]Overview
The Bollinger Heatmap is a composite indicator that synthesizes data derived from 30 Bollinger bands distributed over multiple time horizons, offering a high-dimensional characterization of the underlying asset.
Algorithm
The algorithm quantifies the current price’s relative position within each Bollinger band ensemble, generating a normalized position ratio. This ratio is subsequently transformed into a scalar heat value, which is then rendered on a continuous color gradient from red to blue. Red hues correspond to price proximity to or extension below the lower band, while blue hues denote price proximity to or extension above the upper band.
Using default parameters, the indicator maps bands over timeframes increasing in a pattern approximating exponential growth, constrained to multiples of seven days. The lower region encodes relationships with shorter-term bands spanning between 1 and 14 weeks, whereas the upper region portrays interactions with longer-term bands ranging from 15 to 52 weeks.
Conclusion
By integrating Bollinger bands across a diverse array of time horizons, the heatmap indicator aims to mitigate the model risk inherent in selecting a single band length, capturing exposure across a richer parameter space.
MTF Dashboard 9 Timeframes + Signals# MTF Dashboard Pro - Multi-Timeframe Confluence Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive dashboard that simultaneously analyzes market conditions across 9 different timeframes (1m, 5m, 15m, 30m, 1H, 4H, Daily, Weekly, Monthly) using a proprietary confluence scoring methodology. Unlike simple multi-timeframe displays that show individual indicators separately, this script combines trend analysis, momentum, volatility signals, and volume analysis into unified confluence scores for each timeframe.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Most traders manually check multiple timeframes and struggle to quickly assess overall market bias when different timeframes show conflicting signals. Existing MTF scripts typically display individual indicators without synthesizing them into actionable intelligence.
**The Solution:** This script implements a mathematical confluence algorithm that:
- Weights each indicator's signal strength (trend direction, RSI momentum, MACD volatility, volume analysis)
- Calculates normalized scores across all active timeframes
- Determines overall market bias with statistical confidence levels
- Provides instant visual feedback through color-coded symbols and star ratings
**Unique Features:**
1. **Confluence Scoring Algorithm**: Mathematically combines multiple indicator signals into a single confidence rating per timeframe
2. **Market Bias Engine**: Automatically calculates overall directional bias with percentage strength across all selected timeframes
3. **Dynamic Display System**: Real-time updates with customizable layouts, color schemes, and selective timeframe activation
4. **Statistical Analysis**: Provides bullish/bearish vote counts and overall confluence percentages
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Calculation Methodology:
**1. Trend Analysis (EMA-based):**
- Fast EMA (default: 9) vs Slow EMA (default: 21) crossover analysis
- Returns values: +1 (bullish), -1 (bearish), 0 (neutral)
**2. Momentum Analysis (RSI-based):**
- RSI levels: >70 (strong bullish +2), >50 (bullish +1), <30 (strong bearish -2), <50 (bearish -1)
- Provides overbought/oversold context for trend confirmation
**3. Volatility Analysis (MACD-based):**
- MACD line vs Signal line positioning
- Histogram strength comparison with previous bar
- Combined score considering both direction and momentum strength
**4. Volume Analysis:**
- Current volume vs 20-period moving average
- Thresholds: >150% MA (strong +2), >100% MA (bullish +1), <50% MA (weak -2)
**5. Confluence Calculation:**
```
Confluence Score = (Trend + RSI + MACD + Volume) / 4.0
```
**6. Market Bias Determination:**
- Counts bullish vs bearish signals across all active timeframes
- Calculates bias strength percentage: |Bullish Count - Bearish Count| / Total Active TFs * 100
- Determines overall market direction: BULLISH, BEARISH, or NEUTRAL
### Multi-Timeframe Implementation:
Uses `request.security()` calls to fetch data from each timeframe, ensuring all calculations are performed on the respective timeframe's data rather than current chart timeframe, providing accurate multi-timeframe analysis.
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Timeframe Selection**: Enable/disable specific timeframes in "Timeframe Selection" group based on your trading style
2. **Indicator Configuration**: Adjust EMA periods (Fast: 9, Slow: 21), RSI length (14), and MACD settings (12/26/9) to match your analysis preferences
3. **Display Options**: Choose table position, text size, and color scheme for optimal visibility
### Reading the Dashboard:
**Symbol Interpretation:**
- ⬆⬆ = Strong bullish signal (score ≥ 2)
- ⬆ = Bullish signal (score > 0)
- ➡ = Neutral signal (score = 0)
- ⬇ = Bearish signal (score < 0)
- ⬇⬇ = Strong bearish signal (score ≤ -2)
**Confluence Stars:**
- ★★★★★ = Very high confidence (score > 0.75)
- ★★★★☆ = High confidence (score > 0.5)
- ★★★☆☆ = Medium confidence (score > 0.25)
- ★★☆☆☆ = Low confidence (score > 0)
- ★☆☆☆☆ = Very low confidence (score > -0.25)
**Market Bias Section:**
- Shows overall market direction across all active timeframes
- Strength percentage indicates conviction level
- Overall confluence score represents average agreement across timeframes
### Trading Applications:
**Entry Signals:**
- Look for high confluence (4-5 stars) across multiple timeframes in same direction
- Higher timeframe alignment provides stronger signal validation
- Use confluence percentage >75% for high-probability setups
**Risk Management:**
- Lower timeframe conflicts may indicate choppy conditions
- Neutral bias suggests ranging market - adjust position sizing
- Strong bias with high confluence supports larger position sizes
**Timeframe Harmony:**
- Short-term trades: Focus on 1m-1H alignment
- Swing trades: Emphasize 1H-Daily alignment
- Position trades: Prioritize Daily-Monthly confluence
## SCRIPT SETTINGS EXPLANATION
### Dashboard Settings:
- **Table Position**: Choose optimal location (Top Right recommended for most layouts)
- **Text Size**: Adjust based on screen resolution and preferences
- **Color Scheme**: Professional (default), Classic, Vibrant, or Dark themes
- **Background Color/Transparency**: Customize table appearance
### Timeframe Selection:
All timeframes optional - activate based on trading timeframe preference:
- **Lower Timeframes (1m-30m)**: Scalping and day trading
- **Medium Timeframes (1H-4H)**: Swing trading
- **Higher Timeframes (D-M)**: Position trading and long-term bias
### Indicator Parameters:
- **Fast EMA (Default: 9)**: Shorter period for trend sensitivity
- **Slow EMA (Default: 21)**: Longer period for trend confirmation
- **RSI Length (Default: 14)**: Standard momentum calculation period
- **MACD Settings (12/26/9)**: Standard MACD configuration for volatility analysis
### Alert Configuration:
- **Strong Signals**: Alerts when confluence >75% with clear directional bias
- **High Confluence**: Alerts when multiple timeframes strongly agree
- All alerts use `alert.freq_once_per_bar` to prevent spam
## VISUAL FEATURES
### Chart Elements:
- **Background Coloring**: Subtle background tint reflects overall market bias
- **Signal Labels**: Strong buy/sell labels appear on chart during high-confluence signals
- **Clean Presentation**: Dashboard overlays chart without interfering with price action
### Color Coding:
- **Green/Bullish**: Various green shades for positive signals
- **Red/Bearish**: Various red shades for negative signals
- **Gray/Neutral**: Neutral color for conflicting or weak signals
- **Transparency**: Configurable transparency maintains chart readability
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- This tool provides analysis framework, not trading signals
- Always combine with proper risk management
- Past performance does not guarantee future results
- Market conditions can change rapidly - use appropriate position sizing
**Best Practices:**
- Verify signals with additional analysis methods
- Consider fundamental factors affecting the instrument
- Use appropriate timeframes for your trading style
- Regular parameter optimization may be beneficial for different market conditions
**Limitations:**
- Effectiveness may vary across different instruments and market conditions
- Confluence scoring is mathematical model - not predictive guarantee
- Requires understanding of underlying indicators for optimal use
This script serves as a comprehensive analysis tool for traders who need quick, organized access to multi-timeframe market information with statistical confidence levels.
Volume Footprint Anomaly Scanner [PhenLabs]📊 PhenLabs - Volume Footprint Anomaly Scanner (VFAS)
Version: PineScript™ v6
📌 Description
The PhenLabs Volume Footprint Anomaly Scanner (VFAS) is an advanced Pine Script indicator designed to detect and highlight significant imbalances in buying and selling pressure within individual price bars. By analyzing a calculated "Delta" – the net difference between estimated buy and sell volume – and employing statistical Z-score analysis, VFAS pinpoints moments when buying or selling activity becomes unusually dominant. This script was created not in hopes of creating a "Buy and Sell" indicator but rather providing the user with a more in-depth insight into the intrabar volume delta and how it can fluctuate in unusual ways, leading to anomalies that can be capitalized on.
This indicator helps traders identify high-conviction points where strong market participants are active, signaling potential shifts in momentum or continuation of a trend. It aims to provide a clearer understanding of underlying market dynamics, allowing for more informed decision-making in various trading strategies, from identifying entry points to confirming trend strength.
🚀 Points of Innovation
● Z-Score for Delta Analysis : Utilizes statistical Z-scores to objectively identify statistically significant anomalies in buying/selling pressure, moving beyond simple, arbitrary thresholds.
● Dynamic Confidence Scoring : Assigns a multi-star confidence rating (1-4 stars) to each signal, factoring in high volume, trend alignment, and specific confirmation criteria, providing a nuanced view of signal strength.
● Integrated Trend Filtering : Offers an optional Exponential Moving Average (EMA)-based trend filter to ensure signals align with the broader market direction, reducing false positives in ranging markets.
● Strict Confirmation Logic : Implements specific confirmation criteria for higher-confidence signals, including price action and a time-based gap from previous signals, enhancing reliability.
● Intuitive Info Dashboard : Provides a real-time summary of market trend and the latest signal's direction and confidence directly on the chart, streamlining information access.
🔧 Core Components
● Core Delta Engine : Estimates the net buying/selling pressure (bar Delta) by analyzing price movement within each bar relative to volume. It also calculates average volume to identify bars with unusually high activity.
● Anomaly Detection (Z-Score) : Computes the Z-score for the current bar's Delta, indicating how many standard deviations it is from its recent average. This statistical measure is central to identifying significant anomalies.
● Trend Filter : Utilizes a dual Exponential Moving Average (EMA) cross-over system to define the prevailing market trend (uptrend, downtrend, or range), providing contextual awareness.
● Signal Processing & Confidence Algorithm : Evaluates anomaly conditions against trend filters and confirmation rules, then calculates a dynamic confidence score to produce actionable, contextualized signal information.
🔥 Key Features
● Advanced Delta Anomaly Detection : Pinpoints bars with exceptionally high buying or selling pressure, indicating potential institutional activity or strong market conviction.
● Multi-Factor Confidence Scoring : Each signal comes with a 1-4 star rating, clearly communicating its reliability based on high volume, trend alignment, and specific confirmation criteria.
● Optional Trend Alignment : Users can choose to filter signals, so only those aligned with the prevailing EMA-defined trend are displayed, enhancing signal quality.
● Interactive Signal Labels : Displays compact labels on the chart at anomaly points, offering detailed tooltips upon hover, including signal type, direction, confidence, and contextual information.
● Customizable Bar Colors : Visually highlights bars with Delta anomalies, providing an immediate visual cue for strong buying or selling activity.
● Real-time Info Dashboard : A clean, customizable dashboard shows the current market trend and details of the latest detected signal, keeping key information accessible at a glance.
● Configurable Alerts : Set up alerts for bullish or bearish Delta anomalies to receive real-time notifications when significant market pressure shifts occur.
🎨 Visualization
Signal Labels :
* Placed at the top/bottom of anomaly bars, showing a "📈" (bullish) or "📉" (bearish) icon.
* Tooltip: Hovering over a label reveals detailed information: Signal Type (e.g., "Delta Anomaly"), Direction, Confidence (e.g., "★★★☆"), and a descriptive explanation of the anomaly.
* Interpretation: Clearly marks actionable signals and provides deep insights without cluttering the chart, enabling quick assessment of signal strength and context.
● Info Dashboard :
* Located at the top-right of the chart, providing a clean summary.
* Displays: "PhenLabs - VFAS" header, "Market Trend" (Uptrend/Downtrend/Range with color-coded status), and "Direction | Conf." (showing the last signal's direction and star confidence).
* Optional "💡 Hover over signals for details" reminder.
* Interpretation: A concise, real-time summary of the market's pulse and the most recent high-conviction event, helping traders stay informed at a glance.
📖 Usage Guidelines
Setting Categories
⚙️ Core Delta & Volume Engine
● Minimum Volume Lookback (Bars)
○ Default: 9
○ Range: Integer (e.g., 5-50)
○ Description: Defines the number of preceding bars used to calculate the average volume and delta. Bars with volume below this average won't be considered for high-volume signals. A shorter lookback is more reactive to recent changes, while a longer one provides a smoother average.
📈 Anomaly Detection Settings
Delta Z-Score Anomaly Threshold
○ Default: 2.5
○ Range: Float (e.g., 1.0-5.0+)
○ Description: The number of standard deviations from the mean that a bar's delta must exceed to be considered a significant anomaly. A higher threshold means fewer, but potentially stronger, signals. A lower threshold will generate more signals, which might include less significant events. Experiment to find the optimal balance for your trading style.
🔬 Context Filters
Enable Trend Filter
○ Default: False
○ Range: Boolean (True/False)
○ Description: When enabled, signals will only be generated if they align with the current market trend as determined by the EMAs (e.g., only bullish signals in an uptrend, bearish in a downtrend). This helps to filter out counter-trend noise.
● Trend EMA Fast
○ Default: 50
○ Range: Integer (e.g., 10-100)
○ Description: The period for the faster Exponential Moving Average used in the trend filter. In combination with the slow EMA, it defines the trend direction.
● Trend EMA Slow
○ Default: 200
○ Range: Integer (e.g., 100-400)
○ Description: The period for the slower Exponential Moving Average used in the trend filter. The relationship between the fast and slow EMA determines if the market is in an uptrend (fast > slow) or downtrend (fast < slow).
🎨 Visual & UI Settings
● Show Info Dashboard
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles the visibility of the dashboard on the chart, which provides a summary of market trend and the last detected signal.
● Show Dashboard Tooltip
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles a reminder message in the dashboard to hover over signal labels for more detailed information.
● Show Delta Anomaly Bar Colors
○ Default: True
○ Range: Boolean (True/False)
○ Description: Enables or disables the coloring of bars based on their delta direction and whether they represent a significant anomaly.
● Show Signal Labels
○ Default: True
○ Range: Boolean (True/False)
○ Description: Controls the visibility of the “📈” or “📉” labels that appear on the chart when a delta anomaly signal is generated.
🔔 Alert Settings
Alert on Delta Anomaly
○ Default: True
○ Range: Boolean (True/False)
○ Description: When enabled, this setting allows you to set up alerts in TradingView that will trigger whenever a new bullish or bearish delta anomaly is detected.
✅ Best Use Cases
Early Trend Reversal / Continuation Detection: Identify strong surges of buying/selling pressure at key support/resistance levels that could indicate a reversal or the continuation of a strong move.
● Confirmation of Breakouts: Use high-confidence delta anomalies to confirm the validity of price breakouts, indicating strong conviction behind the move.
● Entry and Exit Points: Pinpoint precise entry opportunities when anomalies align with your trading strategy, or identify potential exhaustion signals for exiting trades.
● Scalping and Day Trading: The indicator’s sensitivity to intraday buying/selling imbalances makes it highly effective for short-term trading strategies.
● Market Sentiment Analysis: Gain a real-time understanding of underlying market sentiment by observing the prevalence and strength of bullish vs. bearish anomalies.
⚠️ Limitations
Estimated Delta: The script uses a simplified method to estimate delta based on bar close relative to its range, not actual order book or footprint data. While effective, it’s an approximation.
● Sensitivity to Z-Score Threshold: The effectiveness heavily relies on the `Delta Z-Score Anomaly Threshold`. Too low, and you’ll get many false positives; too high, and you might miss valid signals.
● Confirmation Criteria: The 4-star confidence level’s “confirmation” relies on specific subsequent bar conditions and previous confirmed signals, which might be too strict or specific for all contexts.
● Requires Context: While powerful, VFAS is best used in conjunction with other technical analysis tools and price action to form a comprehensive trading strategy. It is not a standalone “buy/sell” signal.
💡 What Makes This Unique
Statistical Rigor: The application of Z-score analysis to bar delta provides an objective, statistically-driven way to identify true anomalies, moving beyond arbitrary thresholds.
● Multi-Factor Confidence Scoring: The unique 1-4 star confidence system integrates multiple market dynamics (volume, trend alignment, specific follow-through) into a single, easy-to-interpret rating.
● User-Friendly Design: From the intuitive dashboard to the detailed signal tooltips, the indicator prioritizes clear and accessible information for traders of all experience levels.
🔬 How It Works
1. Bar Delta Calculation:
● The script first estimates the “buy volume” and “sell volume” for each bar. This is done by assuming that volume proportional to the distance from the low to the close represents buying, and volume proportional to the distance from the high to the close represents selling.
● How this contributes: This provides a proxy for the net buying or selling pressure (delta) within that specific price bar, even without access to actual footprint data.
2. Volume & Delta Z-Score Analysis:
● The average volume over a user-defined lookback period is calculated. Bars with volume less than twice this average are generally considered of lower interest.
● The Z-score for the calculated bar delta is computed. The Z-score measures how many standard deviations the current bar’s delta is from its average delta over the `Minimum Volume Lookback` period.
● How this contributes: A high positive Z-score indicates a bullish delta anomaly (significantly more buying than usual), while a high negative Z-score indicates a bearish delta anomaly (significantly more selling than usual). This identifies statistically unusual levels of pressure.
3. Trend Filtering (Optional):
● Two Exponential Moving Averages (Fast and Slow EMA) are used to determine the prevailing market trend. An uptrend is identified when the Fast EMA is above the Slow EMA, and a downtrend when the Fast EMA is below the Slow EMA.
● How this contributes: If enabled, the indicator will only display bullish delta anomalies during an uptrend and bearish delta anomalies during a downtrend, helping to confirm signals within the broader market context and avoid counter-trend signals.
4. Signal Generation & Confidence Scoring:
● When a delta Z-score exceeds the user-defined anomaly threshold, a signal is generated.
● This signal is then passed through a multi-factor confidence algorithm (`f_calculateConfidence`). It awards stars based on: high volume presence, alignment with the overall trend (if enabled), and a fourth star for very strong Z-scores (above 3.0) combined with specific follow-through candle patterns after a cooling-off period from a previous confirmed signal.
● How this contributes: Provides a qualitative rating (1-4 stars) for each anomaly, allowing traders to quickly assess the potential significance and reliability of the signal.
💡 Note:
The PhenLabs Volume Footprint Anomaly Scanner is a powerful analytical tool, but it’s crucial to understand that no indicator guarantees profit. Always backtest and forward-test the indicator settings on your chosen assets and timeframes. Consider integrating VFAS with your existing trading strategy, using its signals as confirmation for entries, exits, or trend bias. The Z-score threshold is highly customizable; lower values will yield more signals (including potential noise), while higher values will provide fewer but potentially higher-conviction signals. Adjust this parameter based on market volatility and your risk tolerance. Remember to combine statistical insights from VFAS with price action, support/resistance levels, and your overall market outlook for optimal results.
Setup: Smooth Gaussian + Adaptive Supertrend (Manual Vol)Overview
This strategy combines two powerful trend-based tools originally developed by Algo Alpha: the Smooth Gaussian Trend (simulated) and the Adaptive Supertrend. The objective is to capture sustained bullish movements in periods of controlled volatility by filtering for high-probability entries.
Entry Logic
Long Entry Conditions:
The closing price is above the Smooth Gaussian Trend line (with length = 75), and
The volatility setting from the Adaptive Supertrend is manually defined as either 2 or 3
Exit Condition:
The closing price falls below the Smooth Gaussian Trend line
This script uses a simulated version of the Gaussian Trend line via double-smoothed SMA, as the original Algo Alpha indicator is protected and cannot be accessed directly in code.
Features
Plots entry and exit signals directly on the chart
Manual toggle to enable or disable the volatility filter
Lightweight design to allow flexible backtesting even without access to proprietary indicators
Important Note
This strategy does not connect to the actual Adaptive Supertrend from Algo Alpha. Users must manually input the volatility level based on what they observe on the chart when the original indicator is also applied. The Smooth Gaussian Trend is approximated and may differ slightly from the original.
Suggested Use
Recommended timeframes: 1H, 4H, or Daily
Best used alongside the original indicators displayed on the chart
Consider incorporating additional structure, momentum, or volume filters to enhance performance
If you have suggestions or would like to contribute improvements, feel free to reach out or fork the script.
Step-OMA with SignalsThe Step-OMA with Signals is a sophisticated trend-following indicator that combines Loxx's Optimized Moving Average (OMA) algorithm with an advanced step function to create a highly responsive yet smooth trend detection system. This indicator excels at identifying trend changes early while minimizing false signals through its adaptive filtering mechanism.
Core Algorithm Components
1. Optimized Moving Average (OMA) Foundation
Based on Loxx's advanced OMA implementation
Uses a 6-stage exponential smoothing process
Incorporates adaptive period calculation based on market noise
Employs Jurik-style smoothing techniques for superior signal quality
2. Step Function Integration
Implements a step-based trend detection mechanism
Uses ATR-based dynamic threshold calculation
Maintains trend consistency through threshold memory
Provides clear trend change identification
3. Adaptive Noise Filtering
Automatically adjusts to market volatility
Calculates optimal averaging periods based on price noise
Reduces false signals in choppy market conditions
Speed (Default: 3.0, Range: -1.5 to unlimited)
This is the most critical parameter affecting indicator behavior:
Positive Speed Values (0 to 10.0+):
Creates faster, more responsive signals
Higher values increase sensitivity to recent price action
Negative Speed Values (-1.5 to -0.1):
Produces smoother, more conservative signals
Reduces noise and false breakouts
Creates delayed but more reliable trend confirmations
Adaptive (Default: True)
When enabled: Automatically adjusts averaging period based on market noise
When disabled: Uses fixed length parameter
Recommendation: Keep enabled for most market conditions
Sensitivity Factor (Default: 3.0)
Controls the threshold distance for trend change detection
Lower values: More frequent signals, higher sensitivity
Higher values: Fewer but more reliable signals
Optimal range: 2.0-5.0 depending on market volatility
Step Size Period (Default: 50)
Determines the ATR calculation period for dynamic thresholds
Affects the indicator's adaptation to volatility changes
Lower values: More reactive to recent volatility
Higher values: More stable threshold calculation
For a trading application, Step-OMA is a suitable base filter to complement other types of signaling indicators (oscillators, momentum indicators).
Disclaimer: This indicator is a technical analysis tool and should be used in conjunction with proper risk management and comprehensive market analysis. Past performance does not guarantee future results.
Pattern Detector [theUltimator5]🎯 Overview
The Pattern Detector is a comprehensive technical analysis indicator that automatically identifies and visualizes multiple pattern types on your charts. Built with advanced ZigZag technology and sophisticated pattern recognition algorithms, this tool helps traders spot high-probability trading opportunities across all timeframes and markets.
✨ Key Features
🔍 Multi-Pattern Detection System
Harmonic Patterns: Butterfly, Gartley, Bat, and Crab patterns with precise Fibonacci ratios
Classic Reversal Patterns: Head & Shoulders and Inverse Head & Shoulders
Double Patterns: Double Tops and Double Bottoms with extreme validation
Wedge Patterns: Rising and Falling Wedges with volume confirmation
📊 Advanced ZigZag Engine
Customizable sensitivity (5-50 levels)
Depth multiplier for multi-timeframe analysis
Real-time pivot detection with noise filtering
Option to display ZigZag lines only for pure price action analysis
🎨 Visualization
Clean pattern lines with distinct color coding
Point labeling system (X, A, B, C, D for harmonics / LS, H, RS for H&S)
Pattern name displays with bullish/bearish direction
Price target projections with arrow indicators
Subtle pattern fills for enhanced visibility
🛠️ Settings & Configuration
Core ZigZag Settings
ZigZag Sensitivity (5-50): Controls pattern detection sensitivity. Lower values detect more patterns but may include noise. Higher values focus on major swings only.
ZigZag Depth Multiplier (1-5): Multiplies sensitivity for deeper analysis. Level 1 = most responsive, Level 5 = major swings only.
Pattern Detection Toggles
Show ZigZag Lines Only: Displays pure ZigZag without pattern detection for price structure analysis
Detect Harmonic Patterns: Enable/disable Fibonacci-based harmonic pattern detection
Detect Head & Shoulders: Toggle classic reversal pattern identification
Detect Double Tops/Bottoms: Enable double pattern detection with extreme validation
Detect Wedge Patterns: Toggle wedge pattern detection with volume confirmation
Display Options
Show Pattern Names: Display pattern names directly on chart (e.g., "Butterfly (Bullish)")
Show Point Labels: Add lettered labels at key pattern points for structure identification
Project Harmonic Targets: Show projected completion points for incomplete harmonic patterns
📈 Pattern Types Explained
Harmonic Patterns 🦋
Advanced Fibonacci-based patterns that provide high-probability reversal signals:
Butterfly: AB=0.786 XA, BC=0.382-0.886 AB, CD=1.618-2.24 BC
Gartley: AB=0.618 XA, BC=0.382-0.886 AB, CD=1.272-1.618 BC
Bat: AB=0.382-0.50 XA, BC=0.382-0.886 AB, CD=1.618-2.24 BC
Crab: AB=0.382-0.618 XA, BC=0.382-0.886 AB, CD=2.24-3.618 BC
Head & Shoulders 👤
Classic three-peak reversal pattern indicating trend exhaustion:
Standard H&S: Bearish reversal at tops
Inverse H&S: Bullish reversal at bottoms
Automatic neckline validation and price target calculation
Double Patterns 📊
Powerful reversal patterns with extreme validation:
Double Top: Two similar highs with valley between (bearish)
Double Bottom: Two similar lows with peak between (bullish)
Includes lookback period validation to ensure patterns are significant extremes
Wedge Patterns 📐
Continuation/reversal patterns with converging trend lines:
Rising Wedge: Converging upward slopes (typically bearish)
Falling Wedge: Converging downward slopes (typically bullish)
Volume confirmation required for increased accuracy
🎯 Trading Applications
Entry Signals
Harmonic Patterns: Enter at point D completion with targets at point A
H&S Patterns: Enter on neckline break with calculated targets
Double Patterns: Enter on support/resistance break with measured moves
Wedge Patterns: Enter on breakout direction with volume confirmation
Risk Management
Use pattern structure for logical stop placement
Pattern invalidation levels provide clear exit rules
Multiple pattern confirmation increases probability
Multi-Timeframe Analysis
Higher ZigZag depth for longer-term patterns
Lower sensitivity for short-term trading patterns
Combine with other timeframes for confluence
⚙️ Optimal Settings
For Day Trading (1m-15m charts)
ZigZag Sensitivity: 5-9
Depth Multiplier: 1-2
Enable all pattern types for maximum opportunities
For Swing Trading (1H-4H charts)
ZigZag Sensitivity: 9-15
Depth Multiplier: 2-3
Focus on harmonic and H&S patterns
For Position Trading (Daily+ charts)
ZigZag Sensitivity: 15-25
Depth Multiplier: 3-5
Emphasize major harmonic and double patterns
🔧 Technical Specifications
Maximum Lookback: 5000 bars for comprehensive analysis
Pattern Overlap Prevention: Intelligent filtering prevents duplicate patterns
Performance Optimized: Efficient algorithms for real-time detection
Volume Integration: Advanced volume analysis for wedge confirmation
Fibonacci Precision: 10% tolerance for harmonic ratio validation
📚 How to Use
Add to Chart: Apply indicator to any timeframe/market
Configure Settings: Adjust sensitivity based on trading style
Enable Patterns: Toggle desired pattern types
Analyze Results: Look for completed patterns with clear structure
Plan Trades: Use price targets and pattern invalidation for trade management
Perfect for both novice and experienced traders seeking systematic pattern recognition with visualization and entry/exit signals.
Contrarian Market Structure BreakMarket Structure Break application was inspired and adapted from Market Structure Oscillator indicator developed by Lux Algo. So much credit to their work.
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Indicator Description: Contrarian Market Structure BreakOverview
The "Contrarian Market Structure Break" indicator is a versatile tool tailored for traders seeking to identify potential reversal opportunities by analyzing market structure across multiple timeframes. Built on Institutional Concepts of Structure (ICT), this indicator detects Break of Structure (BOS) and Change of Character (CHoCH) patterns across short-term, intermediate-term, and long-term swings, plotting them with customizable lines and labels. It generates contrarian buy and sell signals when price breaks key swing levels, with a unique "Blue Dot Tracker" to monitor consecutive buy signals for trend confirmation. Optimized for the daily timeframe, this indicator is adaptable to other timeframes with proper testing, making it ideal for traders of forex, stocks, or cryptocurrencies.
How It Works
The indicator combines three key components to provide a comprehensive view of market dynamics: Multi-Timeframe Market Structure Analysis: It identifies swing highs and lows across short-term, intermediate-term, and long-term periods, plotting BOS (continuation) and CHoCH (reversal) events with customizable line styles and labels.
Contrarian Signal Generation: Buy and sell signals are triggered when the price crosses below swing lows (buy) or above swing highs (sell), indicating potential reversals in overextended markets.
Blue Dot Tracker: A unique feature that counts consecutive buy signals ("blue dots") and highlights a "Hold Investment" state with a yellow background when three or more buy signals occur, suggesting a potential trend continuation.
Signals are visualized as small circles below (buy) or above (sell) price bars, and a table in the bottom-right corner displays the blue dot count and recommended action (Hold or Flip Investment), enhancing decision-making clarity.
Mathematical Concepts Swing Detection: The indicator identifies swing highs and lows by comparing price patterns over three bars, ensuring robust detection of pivot points. A swing high occurs when the middle bar’s high is higher than the surrounding bars, and a swing low occurs when the middle bar’s low is lower.
Market Structure Logic: BOS is detected when the price breaks a prior swing high (bullish) or low (bearish) in the direction of the current trend, while CHoCH signals a potential reversal when the price breaks a swing level against the trend. These are calculated across three timeframes for a multi-dimensional perspective.
Blue Dot Tracker: This feature counts consecutive buy signals and tracks the entry price. If three or more buy signals occur without a sell signal, the indicator enters a "Hold Investment" state, marked by a yellow background, until the price exceeds the entry price or a sell signal occurs.
Entry and Exit Rules Buy Signal (Blue Dot Below Bar): Triggered when the closing price crosses below a swing low on either the intermediate-term or long-term timeframe, suggesting an oversold condition and potential reversal upward. Short-term signals can be enabled but are disabled by default to reduce noise.
Sell Signal (White Dot Above Bar): Triggered when the closing price crosses above a swing high on either the intermediate-term or long-term timeframe, indicating an overbought condition and potential reversal downward.
Blue Dot Tracker Logic: After a buy signal, the indicator increments a blue dot counter and records the entry price. If three or more consecutive buy signals occur (blueDotCount ≥ 3), the indicator enters a "Hold Investment" state, highlighted with a yellow background, suggesting a potential trend continuation. The "Hold Investment" state ends when the price exceeds the entry price or a sell signal occurs, resetting the counter.
Exit Rules: Traders can exit buy positions when a sell signal appears, the price exceeds the entry price during a "Hold Investment" state, or based on additional confirmation from BOS/CHoCH patterns or other technical analysis tools. Always use proper risk management.
Recommended Usage
The indicator is optimized for the daily timeframe, where it effectively captures significant reversal and continuation patterns in trending or ranging markets. It can be adapted to other timeframes (e.g., 1H, 4H, 15M) with careful testing of settings, particularly enabling/disabling short-term structure analysis to suit market conditions. Backtesting is recommended to optimize performance for your chosen asset and timeframe.
Customization Options Market Structure Display: Toggle short-term, intermediate-term, and long-term structures on or off, with customizable line styles (solid, dashed, dotted) and colors for bullish and bearish breaks.
Labels: Enable or disable BOS/CHoCH labels for each timeframe to reduce chart clutter.
Signal Visibility: Hide buy/sell signals if desired for a cleaner chart.
Blue Dot Tracker: Monitor the blue dot count and action (Hold or Flip Investment) via the table display, which is fully customizable in terms of position and appearance.
Why Use This Indicator?
The "Contrarian Market Structure Break" indicator offers a robust framework for identifying high-probability reversal and continuation setups using ICT principles. Its multi-timeframe analysis, clear signal visualization, and innovative Blue Dot Tracker provide traders with actionable insights into market dynamics. Whether you're a swing trader or a day trader, this indicator’s flexibility and intuitive design make it a valuable addition to your trading arsenal.
Note for TradingView Moderators
This script complies with TradingView's House Rules by providing an educational and transparent description without performance claims or guarantees. It is designed to assist traders in technical analysis and should be used alongside proper risk management and personal research. The code is original, well-documented, and includes customizable inputs and clear visual outputs to enhance the user experience.
Tips for Users:
Backtest thoroughly on your chosen asset and timeframe to validate signal reliability. Combine with other indicators or price action analysis for confirmation of entries and exits. Adjust timeframe settings and enable/disable short-term structures to match market volatility and your trading style.
Hope the "Contrarian Market Structure Break" indicator enhances your trading strategy and helps you navigate the markets with confidence! Happy trading!
