Supply and Demand Zones [BigBeluga]🔵 OVERVIEW
The Supply and Demand Zones indicator automatically identifies institutional order zones formed by high-volume price movements. It detects aggressive buying or selling events and marks the origin of these moves as demand or supply zones. Untested zones are plotted with thick solid borders, while tested zones become dashed, signaling reduced strength.
🔵 CONCEPTS
Supply Zones: Identified when 3 or more bearish candles form consecutively with above-average volume. The script then searches up to 5 bars back to find the last bullish candle and plots a supply zone from that candle’s low to its low plus ATR.
Demand Zones: Detected when 3 or more bullish candles appear with above-average volume. The script looks up to 5 bars back for a bearish candle and plots a demand zone from its high to its high minus ATR.
Volume Weighting: Each zone displays the cumulative bullish or bearish volume within the move leading to the zone.
Tested Zones: If price re-enters a zone and touches its boundary after being extended for 15 bars, the zone becomes dashed , indicating a potential weakening of that level.
Overlap Logic: Older overlapping zones are removed automatically to keep the chart clean and only show the most relevant supply/demand levels.
Zone Expiry: Zones are also deleted after they’re fully broken by price (i.e., price closes above supply or below demand).
🔵 FEATURES
Auto-detects supply and demand using volume and candle structure.
Extends valid zones to the right side of the chart.
Solid borders for fresh untested zones.
Dashed borders for tested zones (after 15 bars and contact).
Prevents overlapping zones of the same type.
Labels each zone with volume delta collected during zone formation.
Limits to 5 zones of each type for clarity.
Fully customizable supply and demand zone colors.
🔵 HOW TO USE
Use supply zones as potential resistance levels where sell-side pressure could emerge.
Use demand zones as potential support areas where buyers might step in again.
Pay attention to whether a zone is solid (untested) or dashed (tested).
Combine with other confluences like volume spikes, trend direction, or candlestick patterns.
Ideal for swing traders and scalpers identifying key reaction levels.
🔵 CONCLUSION
Supply and Demand Zones is a clean and logic-driven tool that visualizes critical liquidity zones formed by institutional moves. It tracks untested and tested levels, giving traders a visual edge to recognize where price might bounce or reverse due to historical order flow.
Chỉ báo và chiến lược
Pivot Trend [ChartPrime]The Pivot Trend indicator is a tool designed to identify potential trend reversals based on pivot points in the price action. It helps traders spot shifts in market sentiment and anticipate changes in price direction.
◈ User Inputs:
Left Bars: Specifies the number of bars to the left of the current bar to consider when calculating pivot points.
Right Bars: Specifies the number of bars to the right of the current bar to consider when calculating pivot points.
Offset: Adjusts the sensitivity of pivot point detection.
◈ Indicator Calculation:
The indicator calculates pivot points based on the highest and lowest prices within a specified range of bars. It then determines the trend direction based on whether the current price crossed above upper band or crossed below lower band.
Upper and Lower Bands
◈ Visualization:
Trend direction is indicated by the color of the plotted lines, with blue representing an upward trend and red representing a downward trend.
Buy and sell signals are marked on the chart with corresponding symbols (🅑 for buy signals and 🅢 for sell signals).
Buy and sell signals generated by the indicator can be used in conjunction with other technical analysis tools to confirm trading decisions and manage risk.
Overall, the Pivot Trend indicator offers traders a simple yet effective method for identifying potential trend changes and capturing trading opportunities in the market. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
Bollinger Bands Forecast with Signals (Zeiierman)█ Overview
Bollinger Bands Forecast with Signals (Zeiierman) extends classic Bollinger Bands into a forward-looking framework. Instead of only showing where volatility has been, it projects where the basis (midline) and band width are likely to drift next, based on recent trend and volatility behavior.
The projection is built from the measured slopes of the Bollinger basis, the standard deviation (or ATR, depending on the mode), and a volatility “breathing” component. On top of that, the script includes an optional projected price path that can be blended with a deterministic random walk, plus rejection signals to highlight failed band breaks.
█ How It Works
⚪ Bollinger Core
The script first computes standard Bollinger Bands using the selected Source, Length, and Multiplier:
Basis = SMA(Source, Length)
Band width = Multiplier × StDev(Source, Length)
Upper/Lower = Basis ± Width
This remains the “live” (non-forecast) structure on the chart.
⚪ Trend & Volatility Slope Estimation
To project forward, the indicator measures directional drift and volatility drift using linear regression differences:
Basis slope from the Bollinger basis
StDev slope from the Bollinger deviation
ATR slope for ATR-based projection mode
These slopes drive the forecast bands forward, reflecting the market’s recent directional and volatility regime.
⚪ Projection Engine (Forecast Bands)
At the last bar, the indicator draws projected basis, upper, and lower lines out to Forecast Bars. The projected basis can be:
Trend (straight linear projection)
Curved (ease-in/out transition toward projected endpoints)
Smoothed (extra smoothing on projected basis/width)
⚪ Price Path Projection + Optional Random Walk
In addition to projecting the bands, the script can draw a price forecast path made of a small number of zigzag swings.
Each swing targets a point offset from the projected basis by a multiple of the projected half-width (“width units”).
Decay gradually reduces swing size as the forecast deepens.
The Optional Random Walk Blend adds a deterministic drift component to the zigzag path. It’s not true randomness; it’s a stable pseudo-random sequence, so the drawing doesn’t jump around on refresh, while still adding “natural” variation.
⚪ Rejection Signals
Signals are based on failed attempts to break a band:
Bear Signal (Down): price tries to push above the upper band, then falls back inside, while still closing above the basis.
Bull Signal (Up): price tries to push below the lower band, then returns back inside, while still closing below the basis.
█ How to Use
⚪ Forward Support/Resistance Corridors
Treat the projected upper/lower bands as a future volatility envelope, not a guarantee:
The upper projection ≈ is likely a resistance level if the regime persists
The lower projection ≈ is likely a support level if the regime persists
Best used for trade planning, targets, and “where price could travel” under similar conditions.
⚪ Regime Read: Trend + Volatility
The projection shape is informative:
Rising basis + expanding width → trend with increasing volatility (needs wider stops / more caution)
Flat basis + compressing width → contraction regime (often precedes expansion)
⚪ Signals for Mean-Reversion / Failed Breakouts
The rejection markers are useful for fade-style setups:
A Down signal near/after upper-band failure can imply rotation back toward the basis.
An Up signal near/after lower-band failure can imply snap-back toward the basis.
With MA filtering enabled, signals are constrained to align with the broader bias, helping reduce chop-driven noise.
█ Related Publications
Donchian Predictive Channel (Zeiierman)
█ Settings
⚪ Bollinger Band
Controls the live Bollinger Bands on the chart.
Source – Price used for calculations.
Length – Lookback period; higher = smoother, lower = more reactive.
Multiplier – Bandwidth; higher = wider bands, lower = tighter bands.
⚪ Forecast
Controls the forward projection of the Bollinger Bands.
Forecast Bars – How far into the future the bands are projected.
Trend Length – Lookback used to estimate trend and volatility slopes.
Forecast Band Mode – Defines projection behavior (linear, curved, breathing, ATR-based, or smoothed).
⚪ Price Forecast
Controls the projected price path inside the bands.
ZigZag Swings – Number of projected oscillations.
Amplitude – Distance from basis, measured in bandwidth units.
Decay – Shrinks swings further into the forecast.
⚪ Random-Walk
Adds controlled randomness to the price path.
Enable – Toggle random-walk influence.
Blend – Strength of randomness vs. zigzag.
Step Size – Size of random steps (band-width units).
Decay – Reduces randomness as the forecast deepens.
Seed – Changes the (stable) random sequence.
⚪ Signals
Controls rejection/mean-reversion signals.
Show Signals – Enable/disable signal markers.
MA Filter (Type/Length) – Filters signals by trend direction.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
ADX Volatility Waves [BOSWaves]ADX Volatility Waves - Trend-Weighted Volatility Mapping with State-Based Wave Transitions
Overview
ADX Volatility Waves is a regime-aware volatility framework designed to map statistically significant price extremes through adaptive wave structures driven by trend strength.
Rather than treating volatility as a static dispersion metric, this indicator conditions all volatility expansion, contraction, and zone placement on ADX-derived trend intensity. Price behavior is interpreted through wave-like transitions between balance, expansion, and exhaustion states rather than isolated band interactions.
The result is a dynamic, gradient-based wave system that visually encodes volatility cycles and regime shifts in real time, allowing traders to contextualize price movement within trend-weighted volatility waves.
Price is evaluated not by static thresholds, but by its position and progression within adaptive volatility waves shaped by directional strength.
Conceptual Framework
ADX Volatility Waves is built on the premise that volatility unfolds in waves, not straight lines.
Traditional volatility tools identify dispersion but fail to account for how volatility behaves differently across trend regimes. By embedding ADX directly into volatility construction, this indicator ensures that volatility waves expand during strong directional phases and compress during weak or transitioning regimes.
Three guiding principles define the framework:
Volatility must be conditioned on trend strength
Extremes occur within zones, not at lines
Signals should emerge from completed wave transitions, not instantaneous touches
This reframes analysis from reactive mean-reversion toward regime-aware wave interpretation.
Theoretical Foundation
The indicator fuses directional movement theory with statistical volatility modeling.
Bollinger-derived dispersion provides the structural base, while ADX normalization controls the amplitude of volatility waves. As ADX increases, volatility waves widen and deepen; as ADX weakens, waves compress and tighten around equilibrium.
From this foundation, extended upper and lower wave zones are constructed and smoothed to represent statistically significant expansion and contraction phases.
At its core are three interacting systems:
ADX-Controlled Volatility Engine : Standard deviation is dynamically scaled using normalized ADX values, producing trend-weighted volatility waves.
Wave Zone Construction : Smoothed volatility boundaries are offset and expanded to form upper and lower wave zones, defining overextension and compression regions.
State-Based Wave Transition Logic : Signals occur only after price completes a full wave cycle: expansion into an extreme wave zone followed by a confirmed return to equilibrium.
This structure ensures that signals reflect completed volatility waves, not transient noise.
How It Works
ADX Volatility Waves processes price action through layered wave mechanics:
Trend-Weighted Volatility Calculation : Volatility boundaries are dynamically adjusted using ADX influence, allowing wave amplitude to scale with trend strength.
Structural Smoothing : Volatility boundaries are smoothed to stabilize wave geometry and reduce short-term distortions.
Wave Offset & Expansion : Upper and lower wave zones are positioned beyond equilibrium and expanded proportionally to volatility range, forming clearly defined expansion waves.
Gradient Wave Depth Mapping : Each wave zone is subdivided into multiple gradient layers, visually encoding increasing extremity as price moves deeper into a wave.
Wave State Tracking & Cooldown Control : The system tracks prior wave occupancy, enforces neutral stabilization periods, and applies cooldowns to prevent overlapping wave signals.
Compression Detection : Volatility width monitoring identifies compression phases, highlighting conditions where new volatility waves are likely to form.
Together, these processes create a continuous, adaptive wave map of volatility behavior.
Interpretation
ADX Volatility Waves reframes market reading around volatility cycles:
Upper Volatility Waves (Red Gradient) : Represent upside expansion phases. Deeper wave penetration indicates increased overextension relative to trend-adjusted volatility.
Lower Volatility Waves (Green Gradient) : Represent downside expansion phases. Sustained presence signals pressure, while exits toward balance suggest wave completion.
Equilibrium Zone : The neutral region between volatility waves. Confirmed re-entry into this zone marks the completion of a wave cycle and forms the basis for BUY and SELL signals.
Regime Context via ADX : Strong ADX regimes widen waves, reducing premature reversal signals. Weak ADX regimes compress waves, increasing sensitivity to reversion.
Wave progression and completion matter more than single-bar interactions.
Signal Logic & Visual Cues
ADX Volatility Waves produces single-entry BUY and SELL labels as its visual cues, plotted only when price first enters a volatility wave zone after the defined cooldown period.
Buy Signal (Bottom Zone Entry) : A BUY label appears when price enters the lower volatility wave (oversold zone). This highlights potential expansion into undervalued extremes, providing visual context for trend assessment rather than a guaranteed execution trigger.
Sell Signal (Top Zone Entry) : A SELL label appears when price enters the upper volatility wave (overbought zone). This marks potential overextension into upper volatility extremes, serving as a contextual indicator of trend stress.
All labels respect cooldown tracking to prevent clustering. Alerts are tied directly to these zone-entry signals, and a separate alert monitors volatility squeezes for awareness of compression periods.
Strategy Integration
ADX Volatility Waves integrates cleanly into volatility-aware trading frameworks:
Wave Context Mapping : Use wave depth to assess expansion and exhaustion risk rather than forcing immediate entries.
Transition-Based Execution : Prioritize BUY and SELL signals formed after confirmed wave completion.
Trend-Regime Filtering : In strong ADX regimes, treat waves as continuation pressure. In weak regimes, favor completed wave reversions.
Volatility Cycle Awareness : Monitor compression phases to anticipate the emergence of new volatility waves.
Multi-Timeframe Alignment : Apply higher-timeframe ADX regimes to contextualize lower-timeframe wave behavior.
Technical Implementation Details
Core Engine : ADX-normalized volatility expansion
Wave System : Smoothed, offset, expanded volatility waves
Visualization : Multi-layer gradient wave zones
Signal Logic : State-based wave transitions with cooldown enforcement
Alerts : Wave entry, wave completion, volatility compression
Performance Profile : Lightweight, real-time optimized overlay
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Short-term volatility waves and intraday transitions
15 - 60 min : Structured intraday wave cycles
4H - Daily : Macro volatility regimes and expansion phases
Suggested Baseline Configuration:
BB Length : 20
BB StdDev : 1.5
ADX Length : 14
ADX Influence : 0.8
Wave Offset : 1.0
Wave Width : 1.0
Neutral Confirmation : 5 bars
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Performance Characteristics
High Effectiveness:
Markets exhibiting rhythmic volatility expansion and contraction
Assets with responsive ADX regime behavior
Reduced Effectiveness:
Erratic, news-driven price action
Illiquid markets with distorted volatility metrics
Integration Guidelines
Confluence : Combine with BOSWaves structure or trend tools
Discipline : Respect wave completion and cooldown logic
Risk Framing : Interpret wave depth probabilistically, not predictively
Regime Awareness : Always contextualize waves within ADX strength
Disclaimer
ADX Volatility Waves is a professional-grade volatility and regime-mapping tool. It does not predict price and does not guarantee profitability. Performance depends on market conditions, parameter calibration, and disciplined execution. BOSWaves recommends using this indicator as part of a comprehensive analytical framework incorporating trend, volatility, and structural context.
RSI Divergence LiquidityRSI Divergence Liquidity is an indicator designed to help you catch high-probability BUY reversals by combining two powerful concepts:
OANDA:XAUUSD
Liquidity Sweep / Swing Low: automatically marks swing-low levels and tracks when price sweeps below them and reacts back.
Bullish RSI Divergence: filters noise by comparing RSI at the swing area versus RSI at the retest, favoring reversals with stronger momentum confirmation.
How it works
The script draws Swing Low lines using Pivot Lows. When a new Swing Low forms, the previous one is cut/frozen .
When price retests a Swing Low and the candle conditions are met (bar n bullish, bar n-1 bearish), the script checks:
Whether RSI at n/n-1 is higher than the RSI at the swing (bullish divergence logic)
Whether min RSI at the swing is below a threshold (default < 36) to focus on oversold swing areas
If all conditions pass, the indicator prints an upward triangle right when bar n closes → a potential BUY signal.
How to use
Enter BUY when an up triangle appears at/near the Swing Low (liquidity sweep zone).
Stop Loss idea: below the most recent swing low / below the sweep wick.
Take Profit idea: nearest supply zone, prior high, or fixed RR such as 1:2 / 1:3 depending on your system.
Recommended settings
Best on: M5–H1 (depending on your style), especially effective when price is trending down and performs a clear sweep.
For stricter filtering: lower Max minRSI at Swing (x) to only take signals from deeper RSI lows.
Smaller Pivot Lookback → more swings/signals; larger values → fewer but cleaner swings.
Note: This tool improves probability, not certainty. Combine it with market structure / key levels and proper risk management for best results.
"Clean Market Structure & Trend Confirmation" Clean Market Structure & Trend Confirmation is a high-probability Market Structure and Trend Confirmation indicator trading system designed specifically for SPY and QQQ.
It combines trend structure, multi-timeframe confirmation, momentum gating, and market-state filtering to deliver clean, disciplined BUY and SELL signals — without noise, chop, or over-trading.
This script is built for traders who want clarity first, execution second.
CT Market Fragility & Systemic Risk Monitor v1.0CT ⊕ Market Fragility & Systemic Risk Monitor v1.0
Systemic Stress & Market Regime Monitor
OVERVIEW
Wall Street-grade structural monitoring now open-source.
CT ⊕ Market Fragility & Systemic Risk Monitor v1.0 is a real-time systemic risk tool designed to detect fragility before it hits price. Built by former institutional traders, it delivers structural insight typically reserved for desks inside hedge funds and global macro desks.
This isn’t about finding entries or exits, it’s about understanding the environment you're trading in, and recognizing when it's shifting.
WHAT IT DOES
• Monitors six key market domains: Equities, Rates/Credit, FX (USD stress), Commodities, Crypto, and Macro
• Detects volatility stress, cross-domain coupling, and regime synchronization
• Classifies market structure into Normal → Fragile → Critical
• Shows a live dashboard with scores, coupling levels, and structural state
• Plots event markers (T1, T2, T3) for structural transitions
• Implements hysteresis logic to model post-stress 'memory
• Supports both single-domain ("Local Mode") and system-wide monitoring
HOW IT WORKS
This engine does not rely on traditional TA. No moving averages. No MACD. No patterns. No guesswork.
Instead, it measures how markets are behaving beneath price detecting when stress is:
• Building internally
• Spreading across domains
• Synchronizing into systemic fragility
T1 (🟠) — Early instability: acceleration in market coupling
T2 (🔵) — Fragile regime: multiple domains simultaneously stressed
T3 (🔴) — Critical regime: synchronized, system-wide stress
These are not buy/sell signals. They are structural regime alerts, the same kind used by institutions to cut risk before stress cascades.
WHY IT MATTERS
Most retail tools are reactive. They interpret surface-level patterns after the move.
This tool is different. It’s proactive – measuring pressure before it breaks structure.
Institutions have used structural fragility models like this for years. This script helps close that gap, giving everyday traders the same early warnings that pros use to reduce exposure and sidestep systemic blowups.
It’s not about finding the edge.
It’s about not getting crushed when the system breaks.
Whether you trade crypto, stocks, FX, or macro, this engine helps answer:
• Is the system stable right now?
• Are stress levels rising across markets?
• Is it time to tighten risk?
Institutions don’t wait for breakouts. They monitor structure.
Now, you can too.
KEY FEATURES
• Works on any asset class and any timeframe
• Fully customizable domain selection
• Three-tier structural alert system (T1–T3)
• Real-time dashboard: stress scores, states, and coupling levels
• Hysteresis modeling: post-stress “memory” detection
• Supports single-domain (local) or multi-domain (systemic) monitoring
• PineScript alerts built-in
RECOMMENDED USE
Active traders - all asset classes
Use the dashboard and T1–T3 alerts to stay aware of structural risk in real time.
Track multi-timeframe alignment to detect where risk originates and how it spreads across markets.
Crypto trader s
Monitor upstream domains (Equities, FX, Rates, Macro) to detect pressure before it reaches crypto.
Identify reflexive stress before Bitcoin reacts — and stay ahead of contagion events.
Macro & systematic traders
Use T1–T3 transitions as volatility filters, exposure governors, or dynamic risk overlays.
Build regime-aware models that adapt to shifting systemic conditions.
Examples & Visuals
Question: Would it have helped to know that at 9:30 on October 9th and again at 10:00 on October 10th that critical states were detected in the structural behavior of Bitcoin? Take a look:
30 min chart BTC shows two distinct T3 (critical) regime detections October 9th and 10:30 October 10th
5m BTC chart reveals high frequency instability for the same period, identifying instability, fragility, criticality
The 30minute BTC chart at 16:30 Friday October 10th,, a few hours after first detecting critical systemic risk
RISK DISCLAIMER
This is a structural analysis tool, not a predictive signal. It does not provide financial advice, trade entries, or forecasts. Use at your own risk. Full disclaimer embedded in the script.
Complexity Trading - From Wall St to Main St
No patterns. No repainting. No mysticism. Just logic, math, science and market structure - now made accessible to everyone.
Developer of LPPL Critical Pulse (LPPLCP), the Temporal Phase Model (TPM) and other
other advanced structural and attractor based systems inspired by Sornette’s LPPL framework and other differentiated thinkers.
Note on Methodology
This tool is not predictive, and not designed for academic publication.
It is a real-time structural monitoring system inspired by academically established concepts,
including LPPL attractor dynamics, cross-asset coupling, reflexivity, and phase regime transitions, implemented within the real-time constraints of PineScript, and intended for visual, exploratory, and diagnostic use.
SMI Trigger System - Lower - NPR21/ChatGPTSMI Trigger System (Lower) — Buy Low / Hrugu (Modified)
This indicator is a modified version of the original SMI Trigger System created by Buy Low, with later enhancements by Hrugu, published with permission.
The script is a lower-pane Smoothed Stochastic Momentum Index (SMI) designed to deliver clear, visually intuitive momentum signals without unnecessary clutter. This version focuses exclusively on SMI behavior and removes auxiliary indicators to keep signals clean, readable, and consistent across timeframes.
Key Features
Smoothed SMI line with dynamic color changes based on momentum direction
Raw SMI line for additional reference
Zero-line split cloud shading for quick bullish/bearish momentum identification
Upper and lower SMI reference levels for overbought/oversold context
Exact-bar SMI color-flip triangle markers for immediate visual confirmation
Adjustable triangle size and offset so markers do not overlap the SMI line
Fully customizable colors for:
Zero line
Smoothed SMI (up/down)
Raw SMI
Cloud above and below zero
Upper and lower SMI levels
How to Use
This indicator is designed to highlight momentum shifts, not to predict price. It works best when combined with price structure, trend context, or higher-timeframe bias.
1. SMI Line & Color Changes
The smoothed SMI line changes color based on momentum direction:
Up color → momentum strengthening
Down color → momentum weakening
A color change often signals a potential momentum shift.
2. SMI Color-Flip Triangles
Green ▲ triangle below the SMI
Appears when the smoothed SMI turns upward (bearish → bullish momentum).
Red ▼ triangle above the SMI
Appears when the smoothed SMI turns downward (bullish → bearish momentum).
Triangles are plotted on the same bar the SMI changes color and are offset so they do not overlap the SMI line.
These markers are intended as visual confirmations, not standalone trade signals.
3. Zero Line & Cloud
The zero line separates bullish and bearish momentum regimes.
Cloud above zero → bullish momentum bias
Cloud below zero → bearish momentum bias
Stronger signals often occur when SMI flips in the direction of the cloud.
4. Upper & Lower SMI Levels
Upper and lower reference levels help identify extended momentum.
Momentum flips near or beyond these levels may indicate:
Exhaustion
Potential pullbacks
Trend continuation setups when aligned with higher-timeframe direction
5. Best Practices
Use this indicator as a confirmation tool, not a prediction tool.
Combine with:
Market structure
Support and resistance
Trend direction
Volume or price action
Works well on tick charts, intraday timeframes, and higher-timeframe analysis.
Additional Notes
Triangles do not repaint
All visual elements are user-configurable
No ADX or Awesome Oscillator components
Designed for clarity, speed, and ease of interpretation
This script is intended for analytical and educational purposes only and does not constitute trading advice.
Probability-Based Adaptive Detection🙏🏻 PBAD (Probability-Based Adaptive Detection) : adaptive control tool for outliers || novelty detection, made for worst case data & processes, for the highest time complexity O(n^2) compared with the alternatives (would be explained in a sec). Thresholds are completely data driven and axiomatic, no need in provided hyperparameters, are not learned or optimized. The method accepts multiple weights, e.g. both temporal and volatility weights.
Method briefly explained (I can go deeper if any1 asks explicitly):
Performs weighted KDE on initial input data, finds KDE global maximum (mode), creates new “residuals” dataset by centering initial data around this value;
Performs weighted KDE on residuals, uses sigmoid based probability mass targets with increasing probability coverage to construct a set of non-disjoint High Density Intervals (also called HDR, HPD in Bayesian terms);
Uses these intervals to calculate analogs of centralized & standardized moments;
Uses these ^^ moments to construct a set of control thresholds. The scheme used in PBAD is not only based on a central threshold, or on neighboring ones, it utilizes all previous thresholds, gaining more information.
...
The most important part is to understand whether you really need PBAD. Because even tho it seems to be the best one given highest algocomplexity, irl it would work worse in cases when it’s not required by your data.
Here’s the menu (aka taxonomy omg) of methods you can use that would let you make the right choice:
Moment-Based Adaptive Detection (MBAD) :
Norm: L2
Time complexity: original O(n), successfully reduced to O(1) in online version
Use case: default, general purpose
Based on: method of moments (powers of residuals from mean)
Thresholds architecture: centralized
Quantile-Based Adaptive Detection (QBAD):
Norm: L1
Time complexity: O(nlogn)
Use case: either bad data Or process instability
Based on: quantile moments (dyadic percentiles of residuals from median)
Thresholds architecture: chained/recursive/sequential
Probability-Based Adaptive Detection (PBAD):
Norm: L0
Time complexity: O(n^2)
Use case: both bad data And process instability
Based on: probability moments (target probability masses of residuals from KDE mode)
Thresholds architecture: decentralized (for lack of a better name xd, the idea is that these thresholds gain information from the all other threshold and are Not exclusively based on the central or neighboring thresholds)
...
Examples of true use cases:
^^ an appropriate financial instrument to use PBAD
^^ and another one
...
Additional details about how to use it:
Keep the student5 kernel, it’s the best you can do. I added others mostly for comparisons and if you want to use the tool Not for its primary purpose (on a fine data)
“Calculate for N bars” and “Starting at bar N” options allow to reduce calculation period only on the N number of last bars or next bars from a chosen one. It's vital, because calculations here are heavy
Keep plotting offset at 1 (allows to visually compare current bar with the previous threshold values). This is the way it should be done on price data.
HLC3 is the optimal source input, unless you want to use your own better one point estimate of each datapoint (in the best case done by using PBAD itself on OHLC+ values).
In essence it should be used just like MBAD or QBAD, fade/push extensions and limit, fade/push/skip deviations & basis, or other strategies of your. Again, the only reason for 3 methods to exist is to be chosen for according data characteristics.
Btw:
This is the initial version, I don’t consider it perfected tbh, even tho it works as expected, however this method is very situational anyways.
In this script KDE function is modified to ensure the outcoming probabilities Do sum up to 1. I didn’t do this normalization in Weighted KDE Mode script , but there it’s not required since we just need a KDE global max.
see ya
∞
Liquidity Levels Pro Tool - thewallranka
Liquidity Levels Pro Tool is a market-structure and liquidity-mapping indicator designed to help discretionary futures and index traders identify statistically relevant price levels where reactions, continuations, or liquidity sweeps are more likely to occur.
This script is a decision-support tool, not a signal generator. It does not issue buy/sell alerts or predict future price movement. Instead, it organizes and scores liquidity information so traders can make their own contextual decisions.
What this indicator does
The script continuously detects and maintains liquidity zones derived from price pivots, then evaluates those zones using multiple structural and contextual factors:
Repeated price interaction (touches)
Freshness (time since last interaction)
Confluence with key reference levels
Reaction behavior after contact
Session relevance (RTH vs overnight)
Market regime (trend vs mean reversion)
Time-of-day effects (open, midday, power hour)
Only the most relevant zones—based on a dynamic scoring system—are displayed to reduce chart clutter and focus attention on levels that have historically mattered.
Core components
1. Liquidity Zones
Zones are built from pivot highs and lows and expanded into areas using a configurable tick-based padding. Nearby zones are merged to avoid redundancy.
Each zone is continuously evaluated and assigned a score (0–100) reflecting its relative importance.
2. Zone Scoring (No Lookahead)
Zone scores are based on:
Number of confirmed interactions
Recency of the last touch
Confluence with prior day/week levels, VWAP, and Opening Range
Reaction quality after touches (speed and follow-through)
Session alignment (zones that “work” in the current session are favored)
Penalties after liquidity sweeps
Zones are not forward-looking and do not rely on future data.
3. Context Engine
The script classifies the current environment using VWAP slope and distance:
Trend (up or down)
Mean reversion
Mixed/transition
Time-of-day context (Open, Midday, Power Hour) is also tracked internally and influences zone scoring.
This context is displayed in the HUD to support situational awareness, not automated decisions.
4. Liquidity Sweeps
Optional sweep detection highlights situations where price trades beyond a zone and closes back inside, indicating potential stop runs or failed breakouts.
Sweeps are rate-limited and applied conservatively to avoid visual noise.
5. Trade Planning Levels (Optional)
When enabled, the script highlights the nearest high-quality liquidity level above and below price based on score thresholds.
These are intended as reference targets, not trade entries or exits.
HUD (Heads-Up Display)
The on-chart HUD summarizes:
Key reference levels (prior day/week, Opening Range)
Nearest strong liquidity above/below price
Market regime and time-of-day context
Distance to levels (ticks or points)
The HUD is fully optional, positionable, and includes resizable modes (Small / Medium / Large) to fit different chart layouts.
How to use this tool
This indicator is best used as part of a discretionary trading process, for example:
Identifying areas where price is more likely to react or pause
Framing trades around higher-quality structure instead of arbitrary levels
Filtering setups based on session and regime context
Managing expectations near known liquidity rather than chasing price
It is intentionally designed not to provide trade signals.
Limitations and important notes
This script does not predict outcomes or guarantee reactions
High-scoring zones can still fail
Liquidity behavior is context-dependent and probabilistic
No performance claims or backtested results are provided
The indicator should not be used in isolation
Past behavior does not imply future results.
Chart and usage notes
The script is intended for standard time-based charts
Recommended for liquid futures and index products
Use a clean chart for clarity when publishing or sharing
No external indicators are required
Final note
Liquidity Levels Pro (Tool) — v6 is designed to organize complex market structure into a clear, readable framework, allowing traders to focus on execution and risk management rather than raw level detection.
This script reflects an analytical approach to intraday liquidity and structure, not an automated trading system.
rj_temu_pair_tradea simple "temu" implementation of a pair trade
see robotjames.substack.com for details.
Options Pivot Smile## Options Pivot Smile
**Options Pivot Smile** is a visual market-structure indicator that transforms classic daily pivot levels into a smooth, bell-shaped “smile curve.” It is designed to help traders understand price equilibrium, directional bias, and volatility expansion using historically anchored support and resistance zones.
The script is optimized for discretionary analysis, options structure mapping, and futures market context.
---
### Core Concept
This indicator calculates **previous-day Pivot, S1, S2, R1, and R2** levels and projects them backward across configurable historical widths. These anchor points are then connected using a **Catmull–Rom spline**, producing a smooth bell-shaped curve that represents market balance and skew.
The result is a **visual distribution of price pressure**, rather than static horizontal levels.
---
### Key Features
#### 1. Daily Pivot-Based Levels
* Uses **previous daily High, Low, Close**
* Calculates:
* Pivot (P)
* Support: S1, S2
* Resistance: R1, R2
* Optional **pivot shift** for futures or synthetic instruments
* Optional **spread rounding** for options strike alignment
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#### 2. Historical Anchor Projection
Each level is placed at a different historical distance:
* **R2 / S2** → farthest back
* **R1 / S1** → medium range
* **Pivot** → nearest anchor
This spacing creates the structural foundation for the bell curve.
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#### 3. Smile / Bell Curve Visualization
* Smooth curve generated using **Catmull–Rom spline interpolation**
* Adjustable smoothness (number of curve segments)
* Customizable color and line width
* Represents equilibrium, skew, and volatility structure
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#### 4. Structural Aids
Optional visual components include:
* Horizontal projection lines to the current bar
* Dotted straight connecting lines between anchor points
* Anchor dots at each pivot level
* Adaptive-width level boxes scaled by ATR
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#### 5. Professional Styling Controls
* Line style: Solid / Dotted / Dashed
* Adjustable strike line width
* Independent colors for:
* S2, S1
* Pivot
* R1, R2
* Box opacity, borders, and label text colors
---
### Use Cases
* Market balance and mean-reversion analysis
* Options strike clustering and distribution framing
* Futures pivot bias visualization
* Contextual support/resistance mapping
* Intraday and swing structure reference
---
### Notes & Limitations
* This is a **visual analytical tool**, not a trading strategy
* Does not generate buy/sell signals
* Best used in conjunction with price action, volume, or volatility tools
* Requires sufficient historical bars to render the full structure
---
### Recommended Timeframes
* Intraday (5m–30m) for structure context
* H1–H4 for swing equilibrium
* Works on all symbols with daily data availability
---
**Options Pivot Smile** converts traditional pivot math into an intuitive visual distribution, helping traders see market structure as a curve rather than isolated lines.
SCOTTGO - RVOL Bull/Bear Painter (Real-Time) SCOTTGO - RVOL Bull/Bear Painter (Real-Time Momentum Detection)
📌Overview
The RVOL Bull/Bear Painter is a Pine Script indicator designed to instantly highlight high-momentum candles driven by significant Relative Volume (RVOL).
It provides a clear visual signal (bar color, shape, and label) when a candle's volume exceeds its average by a user-defined threshold, confirming strong bullish or bearish interest in real-time. This helps traders quickly identify potential institutional accumulation/distribution or breakout/breakdown attempts.
✨ Key Features
Relative Volume (RVOL) Calculation: Automatically calculates the ratio of the current bar's volume to its moving average (SMA or EMA) over a customizable lookback period.
Momentum Confirmation: Paints the candle green (bullish) or red (bearish) only when both price direction and high RVOL criteria are met.
Real-Time Detection: Uses a plotshape method to display the signal triangle as soon as the RVOL and direction conditions are met on the currently forming candle, aiming for faster alerts than bar-close coloring.
Customizable Threshold: Easily adjust the RVOL multiplier (e.g., 1.5x, 2.0x, 3.0x) to filter out noise and only focus on truly significant volume events.
Labels and Alerts: Displays a volume multiplier label (e.g., BULL 2.55x) and includes pre-configured alert conditions for automated notifications.
🛠️ How to Use It
1. Identify High-Conviction Moves
Look for the painted candles and the corresponding labels. A candle painted green with a BULL label (e.g., BULL 2.5x) indicates that buyers stepped in with 2.5 times the typical volume to drive the price higher.
2. Configure Your Sensitivity
The power of the script lies in customizing the inputs:
RVOL Lookback Period: Determines the length of the volume moving average.
Shorter periods (e.g., 9-20) make the indicator more reactive to recent volume changes.
Longer periods (e.g., 50-200) require a much larger volume spike to trigger a signal.
RVOL Threshold: This is the multiplier.
Lower values (e.g., 1.5) will generate more signals.
Higher values (e.g., 3.0) will generate fewer, but generally higher-conviction, signals.
3. Set Up Alerts
Use the pre-configured alert conditions (Bullish RVOL Signal and Bearish RVOL Signal) in TradingView's alert menu. Crucially, set the alert frequency to "Once per bar" or "Once per minute" to receive notifications as soon as the high RVOL event occurs, without waiting for the bar to close.
VR Volume Ratio + Divergence (Pro)成交量比率 (Volume Ratio, VR) 是一項通過分析股價上漲與下跌日的成交量，來研判市場資金氣氛的技術指標。本腳本基於傳統 VR 公式進行了優化，增加了**「趨勢變色」與「自動背離偵測」**功能，幫助交易者更精準地捕捉量價轉折點。
Introduction
Volume Ratio (VR) is a technical indicator that measures the strength of a trend by comparing the volume on up-days versus down-days. This script enhances the classic VR formula with "Trend Color Coding" and "Auto-Divergence Detection", helping traders identify volume-price reversals more accurately.
核心功能與參數
公式原理： VR = (Qu + Qf/2) / (Qd + Qf/2) * 100
Qu: 上漲日成交量 (Up volume)
Qd: 下跌日成交量 (Down volume)
Qf: 平盤日成交量 (Flat volume)
參數 (Length)：預設為 26 日，這是市場公認最有效的短中線參數。
關鍵水位線 (Key Levels)：
< 40% (底部區)：量縮極致，市場情緒冰點，常對應股價底部，適合尋找買點。
100% (中軸)：多空分界線。
> 260% (多頭警戒)：進入強勢多頭行情，但需注意過熱。
> 450% (頭部區)：成交量過大，市場情緒亢奮，通常為頭部訊號。
視覺優化 (Visuals)：
紅漲綠跌：當 VR 數值大於前一日顯示為紅色（動能增強）；小於前一日顯示為綠色（動能退潮）。
背離訊號 (Divergence)：自動標記量價背離。
▲ 底背離 (Bullish)：股價創新低，但 VR 指標墊高（主力吸籌）。
▼ 頂背離 (Bearish)：股價創新高，但 VR 指標走弱（買氣衰竭）。
Features & Settings
Formula Logic: Calculated as VR = (Qu + Qf/2) / (Qd + Qf/2) * 100.
Default Length: 26, widely regarded as the optimal setting for short-to-medium term analysis.
Key Zones:
< 40% (Oversold/Bottom): Extreme low volume, often indicating a market bottom and potential buying opportunity.
100% (Neutral): The balance point between bulls and bears.
> 260% (Bullish Zone): Strong uptrend, volume is expanding.
> 450% (Overbought/Top): Extreme high volume, often indicating a market top and potential reversal.
Visual Enhancements:
Color Coding: Line turns Red when VR rises (Momentum Up) and Green when VR falls (Momentum Down).
Divergence Signals: Automatically marks divergence points on the chart.
▲ Bullish Divergence: Price makes a lower low, but VR makes a higher low (Accumulation).
▼ Bearish Divergence: Price makes a higher high, but VR makes a lower high (Distribution).
應用策略建議
抄底策略：當 VR 跌破 40% 後，指標線由綠翻紅，或出現「▲底背離」訊號時，為極佳的波段進場點。
逃頂策略：當 VR 衝過 450% 進入高檔區，一旦指標線由紅翻綠，或出現「▼頂背離」訊號時，建議分批獲利了結。
Strategy Guide
Bottom Fishing: Look for entries when VR drops below 40% and turns red, or when a "▲ Bullish Divergence" label appears.
Taking Profit: Consider selling when VR exceeds 450% and turns green, or when a "▼ Bearish Divergence" label appears.
Disclaimer: This tool is for informational purposes only and does not constitute financial advice. / 本腳本僅供參考，不構成投資建議。
Raeinex Momentum Liquidity IndexEntry arrow signals with volumetric momentum (buying and selling pressure) and the possibility to use all entry signals as liquidity area for price retest.
Stochastic RSI + RSI/ADX Stochastic RSI with RSI/ADX Display
DESCRIPTION:
Advanced momentum oscillator combining Stochastic RSI with Ehlers SuperSmoother filter for reduced noise and cleaner signals. Includes real-time RSI and ADX value displays for complete market analysis.
KEY FEATURES:
- Stochastic RSI applied to logarithmic price for normalized movements
- Ehlers SuperSmoother filter reduces lag while eliminating false signals
- Second derivative (curvature) analysis filters out low-probability setups
- Real-time RSI and ADX boxes with color-coded thresholds
- Buy/Sell signals only trigger with confirmed momentum and curvature alignment
COMPONENTS:
1. K Line (Blue): Smoothed Stochastic RSI
2. D Line (Orange): Signal line (SMA of K)
3. RSI Box: Green above 50, Red below 50
4. ADX Box: Green above 25 (trending), Red below 25 (ranging)
SIGNAL LOGIC:
BUY: K crosses above D + positive curvature + below midpoint (50)
SELL: K crosses below D + negative curvature + above midpoint (50)
PARAMETERS:
- K Smoothing: 10 (Ehlers filter period)
- D Smoothing: 3 (Signal line)
- RSI
CPR + Elliott Wave 3 Combo (Ultra Safe)This will help you to identify the stage of a script. In Elliot wave patter, 3rd wave is the longest length. This will identify the 3rd wave
SMI Trigger System The SMI Trigger System is a lower-pane momentum indicator based on a Hull-smoothed Stochastic Momentum Index (SMI). It is designed to assist in identifying potential momentum shifts by highlighting signal alignment and level interactions.
This indicator is intended to be used as part of a broader analysis framework. Confluence between trend, structure, and higher-timeframe context defines the setup, while SMI signal behavior may be used for confirmation.
The script can be applied across multiple timeframes and markets. It does not generate trade signals on its own and should be used alongside additional analysis and risk management techniques.
For educational purposes only. Not financial advice.
EMA Trend & Stochastic Signal IndicatorThis indicator displays trend-aligned Stochastic crossover signals using EMA structure and swing-based directional filtering for market analysis.
X-trend Volume Anomaly 📊 X-TREND Volume Anomaly: Advanced VSA Analysis
Effective market analysis requires understanding the relationship between Price Action and Volume. X-Trend Volume Anomaly is a technical instrument that simplifies Volume Spread Analysis (VSA) into a clear, visual system. It allows traders to instantly decode the footprint of "Smart Money" by analyzing the correlation between Relative Volume (RVOL) and Candle Range.
The algorithm automatically classifies market behavior into three distinct states:
1. 🟢🔴 Impulse (Trend Validation)
Logic: High Relative Volume + High Price Range.
Interpretation: Represents genuine market intent. Institutional aggregators are aggressively pushing price. This confirms the validity of a breakout or trend continuation.
2. 🟠 Absorption / Churn (Reversal Warning)
Logic: Ultra-High Relative Volume + Low Price Range (Doji, Pin-bar).
Interpretation: The critical signal. This indicates a major divergence between Effort (Volume) and Result (Price Movement). Large players are absorbing liquidity via limit orders, halting the trend. This is often a precursor to an immediate reversal. (See the Orange candle in the chart examples).
3. 👻 Ghost Mode (Noise Reduction)
Logic: Candles with low/insignificant volume are rendered in a transparent gray scale.
Utility: Eliminates visual noise, allowing the trader to focus exclusively on significant liquidity events and institutional activity.
⚙️ SYSTEM SYNERGY
While this indicator provides robust standalone volume analysis, it is engineered to function as the Volume Confirmation Layer within the X-Trend Ecosystem. For a complete institutional trading setup, we recommend pairing this tool with:
X-Trend Reversal (PRO): For precise, non-repainting entry signals.
X-Trend Liquidation Heatmap: For identifying high-probability price targets.
Displacement## Displacement Indicator (Institutional Momentum Filter)
This indicator highlights **true price displacement** — candles where price moves with **abnormal force relative to recent volatility**.
It is designed to help traders distinguish **real momentum** from normal market noise.
Displacement often precedes:
- Breaks of structure
- Fair Value Gaps (FVGs)
- Strong continuation or meaningful pullbacks
This tool focuses on **confirmation**, not prediction.
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### 🔍 How Displacement Is Defined
A candle is marked as *displacement* only when **all conditions are met**:
• Candle body is larger than a multiple of ATR (volatility-adjusted)
• Candle body makes up a high percentage of the full candle (strong close)
• Directional conviction (bullish or bearish close)
This filters out:
- Small or average candles
- Wick-heavy indecision
- Low-quality breakouts
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### 🎯 What This Indicator Is Best Used For
✔ Confirming impulsive moves
✔ Validating structure breaks
✔ Anchoring Fair Value Gaps
✔ Filtering low-probability setups
✔ Identifying institutional participation
Works best on **M5, M15, and H1**, especially during **London and NY sessions**.
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### ⚠️ Important Notes
• This is **not** a buy/sell signal by itself
• Best used with trend, structure, or liquidity context
• Not designed for ranging or low-volatility markets
Think of this indicator as a **momentum truth filter** —
if displacement is missing, conviction is likely missing too.
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### ⚙️ Inputs Explained
• ATR Length – defines normal volatility
• ATR Multiplier – how aggressive displacement must be
• Minimum Body % – ensures strong candle closes
All inputs are adjustable to fit different markets and styles.
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### 🧠 Philosophy
Displacement reflects **commitment**, not anticipation.
This tool helps you wait for **proof**, not hope.
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If you want, I can:
- Tighten this for **ICT-style language**
- Rewrite for **beginner clarity**
- Add a **“How I personally use it”** section
- Optimize it for **TradingView algorithm visibility**
**Tell me which you want changed.**
Buy the dips StrategyThis strategy getting in long position only after the price drop- Buy the dips
The % of the drop is Determined by SMA for the first trade
The inputs of SMA and % of the drop can be adjust from the User
After that Strategy start taking safe trades if not take profit from the first trade
The safe trades are Determined by step down deviation % and by quantity
There is no Stop loss is not for one with small tolerance to getting under
if any question ask
