ICT Structure Levels (ST/IT/LT) - v7 (by Jonas E)ICT Structure Levels (ST/IT/LT) – Neighbor-Wick Pivots
This indicator is designed for traders following ICT-style market structure analysis. It identifies Short-Term (ST), Intermediary (IT), and Long-Term (LT) swing highs and lows, but with a stricter filter that reduces false signals.
Unlike standard pivot indicators, this script requires not only that a bar makes a structural high/low, but also that the neighboring bars’ extremes are formed by wicks rather than flat-bodied candles. This wick condition helps confirm that the level is a true liquidity sweep and not just random price action.
How it works (conceptual):
Detects pivots based on user-defined left/right bars.
Validates that extremes on both sides of the pivot are wick-driven (high > body for highs, low < body for lows).
Marks valid STH/STL, ITH/ITL, and LTH/LTL directly on the chart with optional price labels.
Uses ATR offset for better label readability.
Alerts can be enabled to notify when a new structural level is confirmed.
How to use it:
Map market structure across multiple layers (ST/IT/LT).
Identify true liquidity grabs and avoid false highs/lows.
Integrate with Break of Structure (BOS) and Change of Character (CHoCH) strategies.
Combine with other ICT concepts (Order Blocks, Fair Value Gaps, Liquidity Pools).
What makes it unique:
Most pivot indicators mark every high/low indiscriminately. This script filters pivots using wick validation, which significantly reduces noise and focuses only on the levels most relevant to liquidity-based trading strategies.
Dönemler
SigmoidCycle Oscillator [LuminoAlgo]Purpose:
The SineCycle Oscillator measures price momentum using sigmoid function mathematics (S-curve transformation) borrowed from neural network theory. It generates an oscillator that fluctuates around 1.0, identifying momentum shifts and potential reversal points.
Mathematical Foundation:
This indicator applies the sigmoid logistic function concept: y = 1/(1+e^-x) , which creates an S-shaped curve. In financial markets context, this transformation:
- Maps price changes to a bounded range (-1 to +1)
- Provides non-linear sensitivity (high near zero, low at extremes)
- Naturally filters outliers without lag penalty
Calculation Process:
1. Statistical Normalization: Price deviations are measured from a moving average baseline and scaled by recent volatility (standard deviation over N periods)
2. Sigmoid Transformation: Normalized values undergo S-curve transformation, which weights small movements linearly but compresses large movements logarithmically
3. Dual Timeframe Analysis:
• Short window: User-defined period (N)
• Long window: Double period (2N)
• Ratio calculation: Short sigmoid average ÷ Long sigmoid average
4. Volatility-Weighted Smoothing: Final values use exponential smoothing where the smoothing factor adjusts based on the coefficient of variation (volatility/mean ratio)
What Makes This Different:
Unlike linear momentum oscillators (RSI, Stochastic) that use fixed mathematical relationships, the sigmoid transformation creates variable sensitivity zones. This mimics how professional traders mentally weight price movements.
Trading Application:
Signal Types:
- Momentum: Green (>1.0) = bullish, Red (<1.0) = bearish
- Reversals: 1.0 line crosses with volume confirmation
- Divergence: Price makes new high/low, oscillator doesn't
- Exhaustion: Extended readings (>1.2 or <0.8) suggest overextension
Optimal Conditions:
- Works best: Trending markets with clear swings
- Avoid: Low volume, ranging markets under 1% daily movement
- Timeframes: 4H and above for reliability
Parameter Guidelines:
- Length 8-10: Day trading (expect more whipsaws)
- Length 14-20: Swing trading (balanced signals)
- Length 25-30: Position trading (fewer, stronger signals)
Limitations:
- Lag increases with higher length settings
- Can give false signals during news-driven spikes
- Requires additional confirmation in choppy markets
Trading Framework:
Based on momentum persistence theory - assumes trends continue until sigmoid curve flattens (indicating momentum exhaustion). The mathematical model captures both mean reversion (extreme readings) and trend following (mid-range readings) characteristics.
Auto-Fit Growth Trendline# **Theoretical Algorithmic Principles of the Auto-Fit Growth Trendline (AFGT)**
## **🎯 What Does This Algorithm Do?**
The Auto-Fit Growth Trendline is an advanced technical analysis system that **automates the identification of long-term growth trends** and **projects future price levels** based on historical cyclical patterns.
### **Primary Functionality:**
- **Automatically detects** the most significant lows in regular periods (monthly, quarterly, semi-annually, annually)
- **Constructs a dynamic trendline** that connects these historical lows
- **Projects the trend into the future** with high mathematical precision
- **Generates Fibonacci bands** that act as dynamic support and resistance levels
- **Automatically adapts** to different timeframes and market conditions
### **Strategic Purpose:**
The algorithm is designed to identify **fundamental value zones** where price has historically found support, enabling traders to:
- Identify optimal entry points for long positions
- Establish realistic price targets based on mathematical projections
- Recognize dynamic support and resistance levels
- Anticipate long-term price movements
---
## **🧮 Core Mathematical Foundations**
### **Adaptive Temporal Segmentation Theory**
The algorithm is based on **dynamic temporal partition theory**, where time is divided into mathematically coherent uniform intervals. It uses modular transformations to create bijective mappings between continuous timestamps and discrete periods, ensuring each temporal point belongs uniquely to a specific period.
**What does this achieve?** It allows the algorithm to automatically identify natural market cycles (annual, quarterly, etc.) without manual intervention, adapting to the inherent periodicity of each asset.
The temporal mapping function implements a **discrete affine transformation** that normalizes different frequencies (monthly, quarterly, semi-annual, annual) to a space of unique identifiers, enabling consistent cross-temporal comparative analysis.
---
## **📊 Local Extrema Detection Theory**
### **Multi-Point Retrospective Validation Principle**
Local minima detection is founded on **relative extrema theory with sliding window**. Instead of using a simple minimum finder, it implements a cross-validation system that examines the persistence of the extremum across multiple historical periods.
**What problem does this solve?** It eliminates false minima caused by temporal volatility, identifying only those points that represent true historical support levels with statistical significance.
This approach is based on the **statistical confirmation principle**, where a minimum is only considered valid if it maintains its extremum condition during a defined observation period, significantly reducing false positives caused by transitory volatility.
---
## **🔬 Robust Interpolation Theory with Outlier Control**
### **Contextual Adaptive Interpolation Model**
The mathematical core uses **piecewise linear interpolation with adaptive outlier correction**. The key innovation lies in implementing a **contextual anomaly detector** that identifies not only absolute extreme values, but relative deviations to the local context.
**Why is this important?** Financial markets contain extreme events (crashes, bubbles) that can distort projections. This system identifies and appropriately weights them without completely eliminating them, preserving directional information while attenuating distortions.
### **Implicit Bayesian Smoothing Algorithm**
When an outlier is detected (deviation >300% of local average), the system applies a **simplified Kalman filter** that combines the current observation with a local trend estimation, using a weight factor that preserves directional information while attenuating extreme fluctuations.
---
## **📈 Stabilized Extrapolation Theory**
### **Exponential Growth Model with Dampening**
Extrapolation is based on a **modified exponential growth model with progressive dampening**. It uses multiple historical points to calculate local growth ratios, implements statistical filtering to eliminate outliers, and applies a dampening factor that increases with extrapolation distance.
**What advantage does this offer?** Long-term projections in finance tend to be exponentially unrealistic. This system maintains short-to-medium term accuracy while converging toward realistic long-term projections, avoiding the typical "exponential explosions" of other methods.
### **Asymptotic Convergence Principle**
For long-term projections, the algorithm implements **controlled asymptotic convergence**, where growth ratios gradually converge toward pre-established limits, avoiding unrealistic exponential projections while preserving short-to-medium term accuracy.
---
## **🌟 Dynamic Fibonacci Projection Theory**
### **Continuous Proportional Scaling Model**
Fibonacci bands are constructed through **uniform proportional scaling** of the base curve, where each level represents a linear transformation of the main curve by a constant factor derived from the Fibonacci sequence.
**What is its practical utility?** It provides dynamic resistance and support levels that move with the trend, offering price targets and profit-taking points that automatically adapt to market evolution.
### **Topological Preservation Principle**
The system maintains the **topological properties** of the base curve in all Fibonacci projections, ensuring that spatial and temporal relationships are consistently preserved across all resistance/support levels.
---
## **⚡ Adaptive Computational Optimization**
### **Multi-Scale Resolution Theory**
It implements **automatic multi-resolution analysis** where data granularity is dynamically adjusted according to the analysis timeframe. It uses the **adaptive Nyquist principle** to optimize the signal-to-noise ratio according to the temporal observation scale.
**Why is this necessary?** Different timeframes require different levels of detail. A 1-minute chart needs more granularity than a monthly one. This system automatically optimizes resolution for each case.
### **Adaptive Density Algorithm**
Calculation point density is optimized through **adaptive sampling theory**, where calculation frequency is adjusted according to local trend curvature and analysis timeframe, balancing visual precision with computational efficiency.
---
## **🛡️ Robustness and Fault Tolerance**
### **Graceful Degradation Theory**
The system implements **multi-level graceful degradation**, where under error conditions or insufficient data, the algorithm progressively falls back to simpler but reliable methods, maintaining basic functionality under any condition.
**What does this guarantee?** That the indicator functions consistently even with incomplete data, new symbols with limited history, or extreme market conditions.
### **State Consistency Principle**
It uses **mathematical invariants** to guarantee that the algorithm's internal state remains consistent between executions, implementing consistency checks that validate data structure integrity in each iteration.
---
## **🔍 Key Theoretical Innovations**
### **A. Contextual vs. Absolute Outlier Detection**
It revolutionizes traditional outlier detection by considering not only the absolute magnitude of deviations, but their relative significance within the local context of the time series.
**Practical impact:** It distinguishes between legitimate market movements and technical anomalies, preserving important events like breakouts while filtering noise.
### **B. Extrapolation with Weighted Historical Memory**
It implements a memory system that weights different historical periods according to their relevance for current prediction, creating projections more adaptable to market regime changes.
**Competitive advantage:** It automatically adapts to fundamental changes in asset dynamics without requiring manual recalibration.
### **C. Automatic Multi-Timeframe Adaptation**
It develops an automatic temporal resolution selection system that optimizes signal extraction according to the intrinsic characteristics of the analysis timeframe.
**Result:** A single indicator that functions optimally from 1-minute to monthly charts without manual adjustments.
### **D. Intelligent Asymptotic Convergence**
It introduces the concept of controlled asymptotic convergence in financial extrapolations, where long-term projections converge toward realistic limits based on historical fundamentals.
**Added value:** Mathematically sound long-term projections that avoid the unrealistic extremes typical of other extrapolation methods.
---
## **📊 Complexity and Scalability Theory**
### **Optimized Linear Complexity Model**
The algorithm maintains **linear computational complexity** O(n) in the number of historical data points, guaranteeing scalability for extensive time series analysis without performance degradation.
### **Temporal Locality Principle**
It implements **temporal locality**, where the most expensive operations are concentrated in the most relevant temporal regions (recent periods and near projections), optimizing computational resource usage.
---
## **🎯 Convergence and Stability**
### **Probabilistic Convergence Theory**
The system guarantees **probabilistic convergence** toward the real underlying trend, where projection accuracy increases with the amount of available historical data, following **law of large numbers** principles.
**Practical implication:** The more history an asset has, the more accurate the algorithm's projections will be.
### **Guaranteed Numerical Stability**
It implements **intrinsic numerical stability** through the use of robust floating-point arithmetic and validations that prevent overflow, underflow, and numerical error propagation.
**Result:** Reliable operation even with extreme-priced assets (from satoshis to thousand-dollar stocks).
---
## **💼 Comprehensive Practical Application**
**The algorithm functions as a "financial GPS"** that:
1. **Identifies where we've been** (significant historical lows)
2. **Determines where we are** (current position relative to the trend)
3. **Projects where we're going** (future trend with specific price levels)
4. **Provides alternative routes** (Fibonacci bands as alternative targets)
This theoretical framework represents an innovative synthesis of time series analysis, approximation theory, and computational optimization, specifically designed for long-term financial trend analysis with robust and mathematically grounded projections.
MMA, Mid-Price Moving Averages (Open + Close Based MAs)📝 Script Description
This script introduces a custom set of moving averages based on the mid-price, calculated as the average of the open and close prices:
Mid Price = (Open + Close) / 2
Instead of traditional close-based MAs, this approach reflects the average sentiment throughout the trading session, offering a smoother and more realistic view of price action.
🔍 Key Features:
✅ Gap-aware smoothing
Captures opening gaps, offering a better representation of intraday shifts.
✅ Reduced noise
Less vulnerable to sharp closing moves or one-off spikes, making it easier to identify true trend breaks or supports.
✅ Closer to actual flow
Reflects a more natural midline of price movement, ideal for traders who prioritize clean, sustained trends.
✅ Better support/resistance alignment
Especially useful for identifying stable uptrends and minimizing false breakout signals.
📐 Included Moving Averages:
MA 5
MA 10
MA 20
MA 60
MA 120
MA 200
(All based on mid-price, not close)
🎯 Recommended For:
Traders seeking smoother and more reliable trendlines
Those who want a more realistic depiction of support and resistance
Ideal for filtering out noisy movements while focusing on clean, straight-moving charts
Daily Seasonality Strength + Prediction TableDaily Seasonality Strength + Prediction Table
Return Estimates:
This indicator uses historical price data to calculate average returns for each day (of the week or month) and uses these to predict the next day’s return.
Seasonality Strength:
It measures seasonality strength by comparing predicted returns with actual returns, using the inverse of MSE (higher values mean stronger seasonality).
supports up to 10 assets
This script is for informational and educational purposes only. It does not constitute financial, investment, or trading advice. I am not a financial advisor. Any decisions you make based on this indicator are your own responsibility. Always do your own research and consult with a qualified financial professional before making any investment decisions.
Past performance is no guarantee of future results. The value of the instruments may fluctuate and is not guaranteed
CITY REVERS+TREND+ICT+SMC+PriceAction V.5THiS INDiCATOR CREAT BY CITY TRADERs PRO.
for support city all in-pc desktop ea
Possible Deviations | Session Fibs📌 Session Fibs with Confluence Detection
This script automatically plots custom Fibonacci extensions from key market sessions and candles, giving you a structured view of intraday levels that matter:
Asia Session (20:00–00:00 NY time)
→ Marks the session high/low, draws fib projections, and shades the range.
London 4:00 AM (1H) Candle
→ Captures the 1-hour “last leg” move into London and projects fib levels.
New York Open Key Candles
→ 8:30 AM and 9:30 AM (5-minute) candles with fib projections.
⚡ Features
Custom fib set (0, 0.5, ±0.618, ±2.0, ±2.25, ±2.5, ±3.0, ±3.25, ±3.5, ±4.0, ±4.25, ±4.5, 4.618).
Adjustable line extension mode (none, right N bars, infinite right).
Toggleable labels & text color, with placement options (on line / left of line).
Asia session box highlight for visual clarity.
Confluence detection: automatically checks for overlapping fib levels between
Asia ↔ London (same day)
Today ↔ Previous day (optional)
→ Highlights overlaps with dashed lines + labels (e.g., LON -3.25 ≈ ASIA -2.25).
🎯 Use Case
Designed for traders who track session ranges and liquidity sweeps, this tool makes it easy to spot:
Intraday fib alignment between Asia and London.
Key NYO candles in relation to overnight ranges.
High-probability confluence zones for entries/exits.
SMC - OB/Breaker Block/Bos/ChoCh (DeadCat) Based on analyzing your Pine Script code, here are comprehensive descriptions that should comply with TradingView's house rules:
Script 1: "PO3 Liquidity w/ CISD (DeadCat)"
Description:
This indicator implements the Power of Three (PO3) liquidity concept combined with Change in State of Delivery (CISD) pattern recognition for Smart Money Concepts (SMC) trading. The script operates on multi-timeframe analysis using automated timeframe selection.
Core Methodology: The indicator identifies C2 liquidity sweeps by detecting when price breaks previous period highs/lows and then reverses back above/below those levels. It specifically looks for:
C2 Buy Setup: When current low breaks previous period low but closes back above it
C2 Sell Setup: When current high breaks previous period high but closes back below it
CISD Pattern Detection: The script implements sophisticated CISD (Change in State of Delivery) pattern recognition by:
Tracking the first break of previous HTF high/low levels
Identifying imbalance candles (gaps between consecutive candles)
Confirming CISD when price reclaims the imbalance level within 2 HTF periods
Validating setups only when both liquidity sweep AND CISD confirmation occur
Visual Components:
HTF Candles: Displays higher timeframe candle structure on current chart
Trading Zones: Shows zones between HTF open and equilibrium levels
CISD Lines: Marks confirmed change in state of delivery levels
C2/C4 Labels: Identifies liquidity sweep entry points and potential continuation setups
Market Structure: Optional HH/HL/LH/LL pivot markers
Unique Features:
Automatic timeframe calculation (15m→4H, 1H→1D, etc.)
Real-time HTF period countdown
Setup invalidation tracking when stops are hit
Progressive setup confirmation (C2→C4 evolution)
Bias filter for directional trading preferences
Usage: C2 setups provide initial entry opportunities after confirmed liquidity sweeps with CISD confirmation. C4 setups offer additional entries when HTF equilibrium conditions align favorably. The indicator helps traders identify institutional liquidity grabs followed by genuine directional moves.
Script 2: "SMC Toolkit (DeadCat)"
Description:
This comprehensive Smart Money Concepts toolkit provides institutional-level market structure analysis with automated Order Block (OB) and Breaker Block (BB) zone identification, plus Break of Structure (BOS) and Change of Character (ChoCh) detection.
Market Structure Algorithm: The indicator uses a sophisticated pivot-based algorithm to identify and track market structure progression:
Uptrend: HH→HL→HH sequence tracking
Downtrend: LL→LH→LL sequence tracking
Trend Changes: Automatic ChoCh detection when structure breaks occur
Order Block Logic:
Bullish OB Zones: Created at Higher Lows (HL) and Lower Lows (LL) during uptrends
Bearish OB Zones: Created at Lower Highs (LH) and Higher Highs (HH) during downtrends
Uses last bearish candle before bullish moves (and vice versa) to define precise zone boundaries
Breaker Block Logic:
Bullish BB Zones: Former resistance that becomes support after HH/LH breaks
Bearish BB Zones: Former support that becomes resistance after LL/HL breaks
Automatically transitions when structure points are breached
Zone Management: The script employs intelligent zone lifecycle management:
Creates new zones only at confirmed structure points
Makes previous zones transparent when new structure is confirmed
Maintains zone relevance through dynamic extension
Limits total zones to prevent chart clutter
BOS vs ChoCh Detection:
BOS (Break of Structure): Continuation patterns when trend highs/lows are exceeded
ChoCh (Change of Character): Reversal patterns when pullback levels are broken against trend
Requires 2-candle confirmation before finalizing structure changes
Visual Enhancements:
Color-coded zones with transparency controls
Directional arrows (▲/▼) in zone labels
Customizable line styles and text sizing
Clean market structure progression tracking
Originality: This toolkit combines traditional SMC concepts with enhanced zone boundary calculation using multi-candle analysis and intelligent zone lifecycle management, providing more precise entry/exit levels than standard implementations.
BTC Cycle Crystal Ball (MMI)
The BTC Cycle Crystal Ball (Market Mood Index)
Visualize Bitcoin’s market cycles at a glance! This dashboard combines three core metrics—MVRV-Z proxy, 200-week MA ratio, and price vs realized price—into a single 0–1 Market Mood Index .
Color-coded from deep blue (strong buying) to red (potential selling), it highlights accumulation and distribution zones. Fully adjustable thresholds let you define your own buying/selling zones. Quickly see BTC’s market “mood” and identify key cycle points—no clutter, just clarity.
Disclaimer
This indicator is for informational and educational purposes only . It is not financial advice. Users should perform their own analysis before making trading or investment decisions.
QST RSI - Directional Entry Strict📌 Quantum Swing Trading – RSI
The RSI Zones – Directional Entry Strict indicator is designed to highlight high-probability buy and sell opportunities by focusing on strict RSI entry conditions within predefined trading zones.
🔎 How it works:
Calculates the Relative Strength Index (RSI) over a customizable period (default: 14).
Defines Buy Zone between RSI 35–40 and Sell Zone between RSI 60–65 (user adjustable).
Plots shaded green boxes whenever RSI enters the Buy Zone from above, signaling a potential oversold bounce.
Plots shaded red boxes whenever RSI enters the Sell Zone from below, signaling a potential overbought rejection.
Each box dynamically extends as long as RSI stays within the respective zone, giving a clear visual region of opportunity.
A neutral midline (50) is plotted to help confirm momentum bias.
✅ Key Features:
Clear visual zones for directional entries.
Strict entry condition avoids false signals (RSI must enter from the opposite side).
Adjustable thresholds to adapt to different markets or strategies.
Works across Forex, Stocks, Crypto, and Indices.
⚡ How traders use it:
Buy setups when price enters the green RSI zone and aligns with bullish structure/support.
Sell setups when price enters the red RSI zone and aligns with bearish structure/resistance.
Combine with trend filters (EMA, VWAP, Market Structure) for higher accuracy.
🔒 Exclusive Access: This indicator is not free and is available only to members who value premium tools. If you’re ready to level up your trading with institutional precision, this is your edge.
Send me a direct message here on TradingView or via our Discord community: discord.gg
obm4xuthis will highlight 4 gold high volume maro times ..
For xauusd , i have noted some imporatnt time macros
so this indicator will just highlight the time widnows and alos alerts
the user when this macros started .
Perfect Buy Entry Point Checklist (M15) V4 Of course. Here is a detailed script description you can use to publish your indicator on TradingView. You can copy and paste this directly into the "Describe your script..." box.
The description is formatted to be clear, professional, and easy for other traders to understand.
Script Title
Perfect Buy Entry Point Checklist (M15)
Script Description
(You can copy everything below this line)
Overview
This indicator is a comprehensive toolkit designed to identify high-probability buy setups based on Smart Money Concepts (SMC). It was specifically built for lower timeframes like the 15-minute (M15) chart to help traders align their entries with institutional order flow.
The core of this script is a real-time, on-chart checklist that validates five key criteria before signaling a potential entry. The goal is to move beyond single-indicator signals and provide a more confluent, rules-based approach to trading.
Key Features
Real-Time Checklist Dashboard: An intuitive panel in the corner of your chart shows the status (✅ / ❌) of each rule, so you can see a setup forming in real-time.
Automatic Zone Detection: The indicator automatically identifies and plots Bullish Order Blocks (OB) and Fair Value Gaps (FVG), highlighting key areas of interest.
Clear "BUY" Signals: A clear "BUY" label appears below the price bar only when all five checklist conditions are met simultaneously.
Integrated Risk/Reward Planner: When a valid signal appears, the script automatically plots a hypothetical Entry Line, Stop Loss, and Take Profit based on your customizable R/R ratio (defaulting to 1:2.5).
Higher Timeframe Trend Filter: Includes an optional "Daily Focus" filter that uses a Daily EMA to ensure your M15 entries are aligned with the broader market trend.
How It Works: The 5-Point Checklist
The script will only generate a "BUY" signal if all of the following conditions are true:
1. 🔹 Liquidity Was Swept
The script first checks if the price has recently dipped below a key swing low or equal lows, only to quickly reverse. This is often a sign that institutional players have "swept" retail stop losses before pushing the price higher.
2. 🔹 Price Tapped a Strong Bullish Zone
After the sweep, the price must react from a significant smart money zone. The script confirms if the price has touched a pre-identified Bullish Order Block or filled a nearby Fair Value Gap (FVG).
3. 🔹 Momentum Confirmed the Reversal
A price reversal needs momentum behind it. This condition is met if there is a bullish confirmation from one of the following:
MACD bullish crossover or histogram turning positive.
RSI bouncing up from the 30-40 oversold area.
A strong bullish candle pattern, such as a Bullish Engulfing.
4. 🔹 Price Broke Market Structure (BoS/ChoCh)
To confirm that buyers are in control, the script looks for a Break of Structure (BoS) or a Change of Character (ChoCh). This occurs when the price breaks above a recent minor swing high, signaling a shift from bearish to bullish momentum.
5. 🔹 Risk/Reward is Favorable (Visual Tool)
While not a condition for the signal, this is a crucial part of the tool. Once a signal is confirmed, the script places a Stop Loss just below the liquidity sweep low and projects a Take Profit target based on your desired Risk/Reward ratio.
How to Use
Apply to an M15 Chart: This script is optimized for the 15-minute timeframe but can be tested on others.
Monitor the Dashboard: Watch the checklist panel in the top-right corner. A potential setup is forming as more conditions turn green (✅).
Wait for the Signal: Do not enter a trade until the official "BUY" label appears below a candle. This confirms all rules have been met.
Manage Your Trade: Use the automatically plotted R/R lines as a guide for setting your Stop Loss and Take Profit levels. Always adjust based on your own analysis and risk management rules.
AI Gold Liquidity Breakout CatcherTitle: Gold AI Liquidity Breakout Catcher
Description:
Indicator Philosophy and Originality:
This indicator is not merely a collection of separate tools, but an integrated trading framework designed to improve decision-making by ensuring signal confluence. The core philosophy is that high-probability trading signals occur when multiple, distinct analysis methodologies align.
The originality of this script lies in how it systematically combines a leading signal (the Liquidity Breakout) with multiple, independent lagging confirmation tools (the Classic Filters, the Hull MA, and the Range Filter). A user can see a primary breakout signal and immediately validate its strength against the broader trend defined by the Hull MA, the intermediate trend from the Range Filter, and the specific conditions of the classic filters.
This synergy, where different components work together to validate a single event, is the primary value and reason for this mashup. It provides a structured, multi-layered confirmation process within a single tool, which is not achievable by adding these indicators separately to the chart.
This indicator is a comprehensive technical analysis tool designed to identify potential trading opportunities and provide supplemental trend analysis. It features a primary signal engine based on pivot trendline breakouts, a sophisticated confirmation layer using classic technical indicators, and three separate modules for discretionary analysis: an ICT-based structure plotter, a highly customizable Hull Moving Average (HMA), and a volatility-adaptive Range Filter. This document provides a detailed, transparent explanation of all underlying logic.
1. Core Engine: Pivot-Based Liquidity Trendline Signals
The indicator's foundational signal is generated from a custom method we call "Liquidity Trendlines," which aims to identify potential shifts in momentum.
How It Works:
The script first identifies significant swing points in the price using ta.pivothigh() and ta.pivotlow().
It then draws a trendline connecting consecutive pivot points.
A "Liquidity Breakout" signal (liquidity_plup for buy, liquidity_pldn for sell) is generated when the price closes decisively across this trendline, forming the basis for a potential trade.
2. The Signal Confirmation Process: Multi-Layered Filtering System
A raw Liquidity Breakout signal is only a starting point. To enhance reliability, the signal must pass through a series of user-enabled filters. A final Buy or Sell signal is only plotted if all active filter conditions are met simultaneously.
General & Smart Trend Filters: Use a combination of EMAs, DMI (ADX), and market structure to define the trend.
RSI & MACD Filters: Used for momentum confirmation.
Directional Body Strength Filter: A custom filter that validates the signal based on the strength and direction of the signal candle's body (bodyUpOK / bodyDownOK).
Support & Resistance (S&R) Filter: Blocks signals forming too close to key S&R zones.
Higher Timeframe (HTF) Filter: Provides confluence by checking the trend on higher timeframes.
3. Visual Aid 1: ICT-Based Structure & Premium/Discount Zones
This module is for visual and discretionary analysis only and does not directly influence the automated Buy/Sell signals.
ICT Market Structure: Plots labels for CHoCH, SMS, and BMS based on a Donchian-channel-like logic.
ICT Premium & Discount Zones: When enabled, it draws colored zones corresponding to Premium, Discount, and Equilibrium levels.
4. Visual Aid 2: Hull Moving Average (HMA) Integration
This is another independent tool for trend analysis. It does not affect the primary signals but has its own alerts and serves as a powerful visual confirmation layer.
Functionality: Includes multiple Hull variations (HMA, THMA, EHMA), customizable colors based on trend, and the ability to pull data from a higher timeframe.
5. Visual Aid 3: Range Filter Integration
This module is a volatility-adaptive trend filter that provides its own set of signals and visuals. It is designed to be a standalone trend analysis tool integrated within the indicator for additional confluence.
How It Works: The Range Filter calculates a dynamic volatility threshold based on the average range of the price. A central filter line moves up or down only when the price exceeds this threshold, effectively filtering out market noise.
Visuals: It plots the central filter line and upper/lower bands that create a volatility channel. It can also color the price bars based on the trend.
Signals & Alerts: The Range Filter generates its own "Manual Buy" and "Manual Sell" signals when the price crosses the filter line after a change in trend direction. These signals have their own dedicated alerts.
6. Risk Management & Additional Features
TP/SL Calculations: Automatically calculates Take Profit and Stop Loss levels for the primary signals based on the ATR.
Multi-Timeframe (MTF) Scanner: A dashboard that monitors the final Buy/Sell signal status across multiple timeframes.
Session Filter & Alerts: Allows for restricting trades to specific market sessions and configuring alerts for any valid signal.
By combining breakout detection with a rigorous confirmation process and multiple supplemental analysis tools, this indicator provides a structured and transparent approach to trading.
Transfer Function Filter [theUltimator5]The Transfer Function Filter is an engineering style approach to transform the price action on a chart into a frequency, then filter out unwanted signals using Butterworth-style filter approach.
This indicator allows you to analyze market structure by isolating or removing different frequency components of price movement—similar to how engineers filter signals in control systems and electrical circuits.
🔎 Features
Four Filter Types
1) Low Pass Filter – Smooths price data, highlighting long-term trends while filtering out short-term noise. This filter acts similar to an EMA, removing noisy signals, resulting in a smooth curve that follows the price of the stock relative to the filter cutoff settings.
Real world application for low pass filter - Used in power supplies to provide a clean, stable power level.
2) High Pass Filter – Removes slow-moving trends to emphasize short-term volatility and rapid fluctuations. The high pass filter removes the "DC" level of the chart, removing the average price moves and only outputting volatility.
Real world application for high pass filter - Used in audio equalizers to remove low-frequency noise (like rumble) while allowing higher frequencies to pass through, improving sound clarity.
3) Band Pass Filter – Allows signals to plot only within a band of bar ranges. This filter removes the low pass "DC" level and the high pass "high frequency noise spikes" and shows a signal that is effectively a smoothed volatility curve. This acts like a moving average for volatility.
Real world application for band pass filter - Radio stations only allow certain frequency bands so you can change your radio channel by switching which frequency band your filter is set to.
4) Band Stop Filter – Suppresses specific frequency bands (cycles between two cutoffs). This filter allows through the base price moving average, but keeps the high frequency volatility spikes. It allows you to filter out specific time interval price action.
Real world application for band stop filter - If there is prominent frequency signal in the area which can cause unnecessary noise in your system, a band stop filter can cancel out just that frequency so you get everything else
Configurable Parameters
• Cutoff Periods – Define the cycle lengths (in bars) to filter. This is a bit counter-intuitive with the numbering since the higher the bar count on the low-pass filter, the lower the frequency cutoff is. The opposite holds true for the high pass filter.
• Filter Order – Adjust steepness and responsiveness (higher order = sharper filtering, but with more delay).
• Overlay Option – Display Low Pass & Band Stop outputs directly on the price chart, or in a separate pane. This is enabled by default, plotting the filters that mimic moving averages directly onto the chart.
• Source Selection – Apply filters to close, open, high, low, or custom sources.
Histograms for Comparison
• BS–LP Histogram – Shows distance between Band Stop and Low Pass filters.
• BP–HP Histogram – Highlights differences between Band Pass and High Pass filters.
Histograms give the visualization of a pseudo-MACD style indicator
Visual & Informational Aids
• Customizable colors for each filter line.
• Optional zero-line for histogram reference.
• On-chart info table summarizing active filters, cutoff settings, histograms, and filter order.
📊 Use Cases
Trend Detection – Use the Low Pass filter to smooth noise and follow underlying market direction.
Volatility & Cycle Analysis – Apply High Pass or Band Pass to capture shorter-term patterns.
Noise Suppression – Deploy Band Stop to remove specific choppy frequencies.
Momentum Insight – Watch the histograms to spot divergences and relative filter strength.
Elliott Wave Detector with FibonacciDetermines what timeframe (if any) the underlying asset displays congruence with Elliot Waves, validated by examining the congruence of the waves with fibonacci patterns. Like all backwards-looking indicators, any actual match will be a very pretty coincidence rather than any kind of indicator of potential future behaviour,
Nasdaq Sentiment DashboardBuilds a composite sentiment state — RISK-ON / NEUTRAL / RISK-OFF — using three legs:
Volatility: CBOE VXN vs its moving average and absolute thresholds (risk-on when low & below MA; risk-off when high & above MA).
Breadth (quality of participation): QQEW/QQQ ratio vs its MA (equal-weight beating cap-weight = healthier breadth).
Advance/Decline (intraday breadth): advdec.nq vs its MA, with a magnitude filter (ignores tiny A/D days).
How it works
Pulls each series on your chosen signal timeframe (default Daily).
Creates binary signals per leg:
Vol: volOn if VXN < MA and < vxnLower; volOff if VXN > MA and > vxnUpper.
Breadth: brOn if QQEW/QQQ is above its MA by a deadband; brOff if below.
A/D: adOn if A/D > MA and above adMin; adOff if below MA and < -adMin.
Scores each leg (+1 on, −1 off, 0 neutral) → sums to −3…+3.
State rule (default): RISK-ON if score ≥ +2, RISK-OFF if ≤ −2, else NEUTRAL (i.e., need 2 of 3 to agree).
Detects flips (changes in state) and provides alert conditions that fire only on the flip bar.
What you see
Lines for VXN & MA, QQEW/QQQ & MA, A/D & MA.
Background color shows current composite state.
Triangle markers on the flip bar (up for ON, down for OFF).
A top-right table summarizing state, each leg vs its MA, and the composite score.
How to tune
Vol thresholds: vxnLower / vxnUpper.
Breadth whipsaw control: deadbandBps around the ratio’s MA.
A/D sensitivity: adMin and adMaLen.
Stricter regime: require all 3 to agree by changing the state line to score == 3 / -3.
BTC Power Law Valuation BandsBTC Power Law Rainbow
A long-term valuation framework for Bitcoin based on Power Law growth — designed to help identify macro accumulation and distribution zones, aligned with long-term investor behavior.
🔍 What Is a Power Law?
A Power Law is a mathematical relationship where one quantity varies as a power of another. In this model:
Price ≈ a × (Time)^b
It captures the non-linear, exponentially slowing growth of Bitcoin over time. Rather than using linear or cyclical models, this approach aligns with how complex systems, such as networks or monetary adoption curves, often grow — rapidly at first, and then more slowly, but persistently.
🧠 Why Power Law for BTC?
Bitcoin:
Has finite supply and increasing adoption.
Operates as a monetary network , where Metcalfe’s Law and power laws naturally emerge.
Exhibits exponential growth over logarithmic time when viewed on a log-log chart .
This makes it uniquely well-suited for power law modeling.
🌈 How to Use the Valuation Bands
The central white line represents the modeled fair value according to the power law.
Colored bands represent deviations from the model in logarithmic space, acting as macro zones:
🔵 Lower Bands: Deep value / Accumulation zones.
🟡 Mid Bands: Fair value.
🔴 Upper Bands: Euphoria / Risk of macro tops.
📐 Smart Money Concepts (SMC) Alignment
Accumulation: Occurs when price consolidates near lower bands — often aligning with institutional positioning.
Markup: As price re-enters or ascends the bands, we often see breakout behavior and trend expansion.
Distribution: When price extends above upper bands, potential for exit liquidity creation and distribution events.
Reversion: Historically, price mean-reverts toward the model — rarely staying outside the bands for long.
This makes the model useful for:
Cycle timing
Long-term DCA strategy zones
Identifying value dislocations
Filtering short-term noise
⚠️ Disclaimer
This tool is for educational and informational purposes only . It is not financial advice. The power law model is a non-predictive, mathematical framework and does not guarantee future price movements .
Always use additional tools, risk management, and your own judgment before making trading or investment decisions.
Lanzadera)The Lanzadera Indicator is designed to identify market momentum and potential breakout opportunities. It works as a dynamic tool that helps traders detect price acceleration zones, providing clear signals for possible entries and exits. With customizable settings and a user-friendly design, this indicator is suitable for both beginners and experienced traders.
Use it to:
Spot momentum shifts before major price movements.
Enhance your breakout trading strategies.
Gain a clearer view of market dynamics with visual alerts.
This indicator is built for traders who want precision, discipline, and a professional edge in their decision-making process.
True Opens - (SpeculatorBryan)Overview
This indicator provides a complete framework of key institutional levels by plotting the "True Open" price for the Month, Week, Day, and Intraday Sessions. Instead of using standard chart opens, it uses specific, globally significant times (based in the NY timezone) to identify levels that price action traders watch closely for support, resistance, and market direction.
What It Does
True Monthly Open (TMO): The key macro level, marking the start of the month's trading.
True Weekly Open (TWO): Arguably the most important level, defining the weekly bias. Based on the Sunday evening start of the forex trading week.
True Daily Open (TDO): The New York midnight open, marking the true start of the institutional 24-hour cycle.
True Session Opens (TSO): Key intraday opens (e.g., London, NY) for finding entries and exits on lower timeframes.
Key Features
Clean Forward Projection: All lines and labels project into the future, so you always see the levels in your current price action.
Full Styling Control: Customize the color, style (solid, dashed, dotted), and text for every level to match your chart theme.
Intelligent Display: Levels automatically show on appropriate timeframes to keep your chart clutter-free. Use the "Stacked Opens" feature to override this.
Lightweight & Efficient: Optimized to run smoothly without lagging your chart.
How to Use It
Look for price to react at these levels. A bounce can signal a continuation, while a clean break and retest can signal a change in market structure. Use the higher-timeframe opens (TMO, TWO) as major anchors for your overall bias and the lower-timeframe opens (TDO, TSO) for fine-tuning your entries and exits.
GEXStrik BarS EUR USDGEX strike bars on the left side measure the prevailing amount of positive or negative gamma. On the right side, the volume of calls and puts traded in the region.
Multi-Minute Interval MarkerTesting
Apply this to a 15-second chart (e.g., SOL/USDT).
Verify that thin vertical lines with "1" (grey) and "5" (yellow) appear above the candles at 4-candle (1-minute) and 20-candle (5-minute) intervals, respectively.
The numbers should be positioned above the lines, and you can toggle the markers with show1Min and show5Min.
Macro Times by OutOfOptionsThis indicator highlights macro times on the chart and provides visual and system alerts before a macro begins.
Unlike other macro indicators, this one supports unlimited macro configurations using the format 'HH:mm-HH:mm : Description' . By default, it includes a mix of ICT and Hydra macro times. Incorrect formatting in settings triggers an error, and clicking the "!" error message identifies the problematic configuration line.
You can customize all visual elements, including whether to display Top, Bottom, or 50% lines, highlight the macro zone, or label the macro.
To reduce chart clutter, you can also limit the number of past macros displayed.
For alerts, you can set the advance warning time in minutes and customize the visual alert style (e.g., a vertical line) if enabled.
The indicator is compatible with timeframes of 5 minutes or less; higher timeframes will generate an error.
STOCK EXCHANGE + SILVER BULLET FRAMESThis script is an updated version of the " NY/LDN/TOK Stock Exchange Opening Hours " script.
Objective
Displays global stock exchange sessions (New York, London, Tokyo) with session frames, highs/lows, and opening lines. Includes ICT Silver Bullet windows (NY, London, Tokyo) with configurable shading. Past sessions are frozen at close, ongoing sessions update dynamically until closure, and upcoming sessions are pre-drawn. Fully customizable with options for weekends, labels, padding, opacity, and individual session toggles.
It is designed to help traders quickly interpret market context, liquidity zones, and session-based price behavior.
Main Features
Past sessions (historical data)
• Session Frames:
• Each box is frozen at the session’s close.
• The left edge aligns with the opening time, while the right edge is fixed at the closing time.
• The top and bottom reflect the highest and lowest prices during the session.
• Session Labels:
• Names (NY, LDN, TOK) displayed above the frame, aligned left, in the same color as the frame.
• Opening Lines:
• Vertical dotted lines mark the start of each session.
Ongoing and upcoming sessions (live market)
• Dynamic Session Frames:
• The right edge is locked at the future close time.
• The top and bottom update in real time as new highs and lows form.
• Labels and Lines:
• The session label is visible above the active frame.
• Opening lines are drawn as soon as the session begins.
Silver Bullet Time Windows (ICT concept)
• Highlights key liquidity windows within sessions:
• New York: 10:00–11:00 and 14:00–15:00
• London: 08:00–09:00
• Tokyo: 09:00–10:00
• Silver Bullet zones are shaded with configurable opacity (default 5%).
Customization and Options
• Enable or disable individual sessions (NY, London, Tokyo).
• Toggle weekend display (frames and Silver Bullets).
• Adjust label size, padding, and text visibility.
• Control frame opacity (default 0%).
• Optimized memory management with automatic pruning of old graphical objects.
