LSMAsThis indicator consists of three lines.
The main line (LSMA-A) is the least squares moving average (LSMA).
The second line (SMMA) is the smoothed moving average of the LSMA-A. When the SMMA crosses the LSMA-A below, it generates a BUY signal, while when it crosses the LSMA-A above, it is considered a SELL signal.
Furthermore, an uptrend is considered if the SMMA line is below, or a downtrend if it is above. Along these trend lines, the third line, LSMA-B (another shorter-period least squares moving average) is used to identify peaks and bottoms. This allows for wave analysis.
For optimization, adjusting the shorter period to market conditions is sufficient.
Análise de Ondas
Guppy MMA [Alpha Extract]A sophisticated trend-following and momentum assessment system that constructs dynamic trader and investor sentiment channels using multiple moving average groups with advanced scoring mechanisms and smoothed CCI-style visualizations for optimal market trend analysis. Utilizing enhanced dual-group methodology with threshold-based trend detection, this indicator delivers institutional-grade GMMA analysis that adapts to varying market conditions while providing high-probability entry and exit signals through crossover and extreme value detection with comprehensive visual mapping and alert integration.
🔶 Advanced Channel Construction
Implements dual-group architecture using short-term and long-term moving averages as foundation points, applying customizable MA types to reduce noise and score-based averaging for sentiment-responsive trend channels. The system creates trader channels from shorter periods and investor channels from longer periods with configurable periods for optimal market reaction zones.
// Core Channel Calculation Framework
maType = input.string("EMA", title="Moving Average Type", options= )
// Short-Term Group Construction
stMA1 = ma(close, st1, maType)
stMA2 = ma(close, st2, maType)
// Long-Term Group Construction
ltMA1 = ma(close, lt1, maType)
ltMA2 = ma(close, lt2, maType)
// Smoothing Application
smoothedavg = ma(overallAvg, 10, maType)
🔶 Volatility-Adaptive Zone Framework
Features dynamic score-based averaging that expands sentiment signals during strong trend periods and contracts during consolidation phases, preventing false signals while maintaining sensitivity to genuine momentum shifts. The dual-group averaging system optimizes zone boundaries for realistic market behavior patterns.
// Dynamic Sentiment Adjustment
shortTermAvg = (stScore1 + stScore2 + ... + stScore11) / 11
longTermAvg = (ltScore1 + ltScore2 + ... + ltScore11) / 11
// Dual-Group Zone Optimization
overallAvg = (shortTermAvg + longTermAvg) / 2
allMAAvg = (shortTermAvg * 11 + longTermAvg * 11) / 22
🔶 Step-Like Boundary Evolution
Creates threshold-based trend boundaries that update on smoothed average changes, providing visual history of evolving bullish and bearish levels with performance-optimized threshold management limited to key zones for clean chart presentation and efficient processing.
🔶 Comprehensive Signal Detection
Generates buy and sell signals through sophisticated crossover analysis, monitoring smoothed average interaction with zero-line and thresholds for high-probability entry and exit identification. The system distinguishes between trend continuation and reversal patterns with precision timing.
🔶 Enhanced Visual Architecture
Provides translucent zone fills with gradient intensity scaling, threshold-based historical boundaries, and dynamic background highlighting that activates upon trend changes. The visual system uses institutional color coding with green bullish zones and red bearish zones for intuitive market structure interpretation.
🔶 Intelligent Zone Management
Implements automatic trend relevance filtering, displaying signals only when smoothed average proximity warrants analysis attention. The system maintains optimal performance through smart averaging management and historical level tracking with configurable MA periods for various market conditions.
🔶 Multi-Dimensional Analysis Framework
Combines trend continuation analysis through threshold crossovers with momentum detection via extreme markers, providing comprehensive market structure assessment suitable for both trending and ranging market conditions with score-normalized accuracy.
🔶 Advanced Alert Integration
Features comprehensive notification system covering buy signals, sell signals, strong bull conditions, and strong bear conditions with customizable alert conditions. The system enables precise position management through real-time notifications of critical sentiment interaction events and zone boundary violations.
🔶 Performance Optimization
Utilizes efficient MA smoothing algorithms with configurable types for noise reduction while maintaining responsiveness to genuine market structure changes. The system includes automatic visual level cleanup and performance-optimized visual rendering for smooth operation across all timeframes.
This indicator delivers sophisticated GMMA-based market analysis through score-adaptive averaging calculations and intelligent group construction methodology. By combining dynamic trader and investor sentiment detection with advanced signal generation and comprehensive visual mapping, it provides institutional-grade trend analysis suitable for cryptocurrency, forex, and equity markets. The system's ability to adapt to varying market conditions while maintaining signal accuracy makes it essential for traders seeking systematic approaches to trend trading, momentum reversals, and sentiment continuation analysis with clearly defined risk parameters and comprehensive alert integration.
RSI Divergence + Hidden RSI Divergence + Hidden (TV-like pairing, final)
What it does
This indicator plots RSI and automatically detects both regular and hidden divergences by pairing RSI pivots with price pivots. It supports a TradingView-like loose pairing (within a user-defined bar tolerance) and a strict same-bar pairing. Detected signals are drawn with lines and optional labels on the RSI pane for quick visual verification.
Divergence logic
Regular Bullish (label: Bull)
Price makes a lower low while RSI makes a higher low → potential upward reversal.
Regular Bearish (label: Bear)
Price makes a higher high while RSI makes a lower high → potential downward reversal.
Hidden Bullish (label: H_Bull)
Price makes a higher low while RSI makes a lower low → trend-continuation bias upward.
Hidden Bearish (label: H_Bear)
Price makes a lower high while RSI makes a higher high → trend-continuation bias downward.
All conditions use pivot-to-pivot comparisons with optional equality tolerance for price and RSI to reduce false “equal” mismatches.
Pairing modes
TV-like
Pairs the latest price and RSI pivots if their pivot bars occur within ±tolBars.
A lightweight “pending” buffer allows pairing a newly detected pivot with a recent opposite pivot that arrived a few bars earlier/later (within tolerance).
Same Bar
Price and RSI pivots must occur on the exact same bar to form a pair.
Key inputs
RSI Source & Length: srcRsi, rsiLen (default 14). RSI line and reference levels (70/50/30) can be shown/hidden.
Pivot Window: leftBars, rightBars for both price and RSI pivots.
Pairing: pairMode = TV-like or Same Bar; tolBars for bar tolerance (TV-like only).
Price Pivot Basis: priceMode = High/Low (default) or Close.
Equality Tolerance:
allowEqual (use >=/<=),
priceEpsTks (ticks) for price equality slack,
rsiEps (points) for RSI equality slack.
Visibility: showRSI, showRegular, showHidden, showLabels.
Visuals
Lines (on RSI):
Regular Bearish: red
Regular Bullish: lime
Hidden Bearish: orange
Hidden Bullish: teal
Labels (optional): "Bear", "Bull", "H_Bear", "H_Bull" placed on the RSI series at the second pivot.
Alerts
Four alert conditions are provided and fire when the corresponding divergence is confirmed:
Bear (Regular)
Bull (Regular)
H_Bear (Hidden)
H_Bull (Hidden)
Notes & tips
Divergences are evaluated only when both price and RSI pivots exist and can be paired under the selected mode.
Pivot sensitivity: smaller leftBars/rightBars → earlier but noisier signals; larger values → fewer, more stable pivots.
Tolerance: If you miss valid setups because pivots land a few bars apart, use TV-like with a small tolBars (e.g., 1–2). If you prefer stricter confirmation, use Same Bar.
Equality slack: Use priceEpsTks and rsiEps to avoid rejecting near-equal highs/lows due to tiny differences.
Works on any symbol/timeframe; as with all divergence tools, treat signals as context—combine with trend, structure, and risk management.
Dusk Wave🌊 Dusk Wave (시각적 분석 도구)
개요
기반 기술: 8단계 추세 파도 시각화
시간대: 모든 시간대 호환
신호: 신호 없음 (분석 전용)
용도: 추세 방향 및 강도 분석
Wave 테이블 설명
DUSK WAVE | TREND ANALYSIS
├─ Wave Alignment: 8개 파도 정렬 상태
├─ Trend Strength: 추세 강도 (Strong/Medium/Weak)
├─ Wave Direction: 파도 전체 방향 (Up/Down/Sideways)
├─ Fast Waves: 단기 파도 상태 (1-4번)
├─ Slow Waves: 장기 파도 상태 (5-8번)
├─ Convergence: 파도 수렴/발산 상태
└─ Trend Quality: 추세 품질 등급 (A/B/C/D)
Wave 해석 가이드
파란색 그라데이션: 8개 EMA 파도 표시
정렬 상태: 모든 파도가 같은 방향 = 강한 추세
파도 간격: 좁을수록 강한 추세, 넓을수록 약한 추세
색상 변화: 파도별 속도 차이 시각화
🌊 Dusk Wave (Visual Analysis Tool) - English Version
Overview
Core Technology: 8-Stage Trend Wave Visualization
Timeframe: Compatible with all timeframes
Signals: No signals (Analysis only)
Purpose: Trend direction and strength analysis
Wave Table Description
DUSK WAVE | TREND ANALYSIS
├─ Wave Alignment: 8 wave alignment status
├─ Trend Strength: Trend intensity (Strong/Medium/Weak)
├─ Wave Direction: Overall wave direction (Up/Down/Sideways)
├─ Fast Waves: Short-term wave status (Waves 1-4)
├─ Slow Waves: Long-term wave status (Waves 5-8)
├─ Convergence: Wave convergence/divergence state
└─ Trend Quality: Trend quality grade (A/B/C/D)
Wave Interpretation Guide
Blue Gradient: 8 EMA waves display
Alignment Status: All waves same direction = Strong trend
Wave Spacing: Closer = Stronger trend, Wider = Weaker trend
Color Changes: Visualizes speed differences between waves
Bollinger Breakout A3 updateBollinger Breakout A3 update from LuxAlgo signal
You can try it with some another signal.
1H Candlestick vs EMA Crossover# Description — 1H Candlestick vs EMA Crossover (Pine Script)
This indicator is built in **TradingView Pine Script v5** and is designed to track the relationship between the **1‑hour candlestick close** and the **1‑hour Exponential Moving Average (EMA)**. It works on any chart timeframe but always pulls in **1H data** using `request. security`.
### Core Features
* **Customizable EMA length** (default = 200)
* **Plots the 1H EMA** as an orange line on your chart
* Optionally shows the **1H close** as a faint gray line for reference
* Detects and highlights when the **1H candle close crosses above or below the 1H EMA**
* **Arrows**: Green triangles appear below the bar when a bullish crossover happens (1H close > EMA); red triangles appear above the bar when a bearish crossover happens (1H close < EMA)
* **Alerts**: Built‑in `alert condition` statements let you create TradingView alerts whenever a crossover occurs
### How to Use
1. Adjust the EMA length if you want a faster or slower moving average.
2. Enable alerts: Right‑click the chart → Add Alert → choose this indicator and select either “crossed ABOVE EMA” or “crossed BELOW EMA.”
### Trading Applications
* **Trend Confirmation**: Use the 1H EMA as a higher‑timeframe filter while trading on lower timeframes.
* **Entry/Exit Signals**: Crossovers can mark potential entry points for trend continuation or reversals.
* **Scalping/Intraday**: Even on a 5m or 15m chart, you can overlay the 1H EMA to align your trades with the bigger trend.
This makes the indicator a simple yet powerful tool for aligning trades with higher‑timeframe momentum and avoiding false signals from lower‑timeframe noise.
Minute speciale universale (3,11,17,29,41,47,53,59)//@version=5
indicator("Minute speciale universale (3,11,17,29,41,47,53,59)", overlay=true, max_labels_count=500)
// lista de minute speciale
var int specials = array.from(3, 11, 17, 29, 41, 47, 53, 59)
// minutul de start al barei (0..59)
mStart = minute(time)
// durata barei (secunde) -> minute
secInBar = timeframe.in_seconds(timeframe.period)
isIntraday = timeframe.isintraday
minutesInBar = (isIntraday and not na(secInBar)) ? math.max(1, int(math.ceil(secInBar / 60.0))) : 0
// caută dacă vreo valoare din `specials` cade în intervalul barei
bool hit = false
var int first = na
if minutesInBar > 0
for i = 0 to array.size(specials) - 1
s = array.get(specials, i)
delta = (s - mStart + 60) % 60
if delta < minutesInBar
hit := true
if na(first)
first := s
// etichetă (o singură linie ca să evităm parse issues)
if hit
label.new(bar_index, high, str.tostring(first), xloc=xloc.bar_index, yloc=yloc.abovebar, style=label.style_label_up, color=color.black, textcolor=color.white, size=size.tiny)
Draw Trend LinesSometimes the simplest indicators help traders make better decisions. This indicator draws simple trend lines, the same lines you would draw manually.
To trade with an edge, traders need to interpret the recent price action, whether it's noisy or choppy, or it's trending. Trend Lines will help traders with that interpretation.
The lines drawn are:
1. lower tops
2. higher bottoms
Because trends are defined as higher lows, or lower highs.
When you see "Wedges", formed by prices chopping between top and bottom trend lines, that's noisy environment not to be traded. When you learn to "stop yourself", you already have an edge.
Often when you see a trend, it's still not too late. Trend will continue until it doesn't. But the caveat is a very steep trend is unlikely to continue, because buying volume is extremely unbalanced to cause the steep trend, and that volume will run out of energy. (Same on the sell side of course)
Trends can reverse, and when price action breaks the trend line, Breakout/Breakdown traders can take this as an entry signal.
Enjoy, and good trading!
Ai Golden Support and Resistance Adaptive Support & Resistance (ADR-scaled ABCD + Breakout/Retest Zones)
What it does
This indicator detects actionable support/resistance zones from swing structure and breakout events, then keeps each zone active until it’s invalidated by price. It adapts zone sensitivity using Average Daily Range (ADR) so the same rules scale across symbols and vol regimes.
Core Logic (high level)
Swing & ABCD pattern seed
Detects alternating pivots (high–low–high–low or low–high–low–high) using a user-selected lookback.
Validates basic AB–BC–CD proportions: BC must retrace a portion of AB; CD must extend BC within a set range.
From a valid sequence, sets a candidate level (top for bearish, bottom for bullish).
Breakout confirmation
A level becomes confirmed when price closes beyond it (crossover/crossunder).
On confirmation, the script draws a dotted reference line and records how many bars elapsed from the seed pivot to breakout. That count defines the lookback window used for local extremes.
Zone construction
Supply (bearish): builds a box around the most recent local range near the bearish seed;
Demand (bullish): builds a box around the most recent local range near the bullish seed.
Each zone’s height is derived from nearby extremes and the seed swing, so boxes reflect local structure rather than fixed pip widths.
Volatility normalization (ADR%)
ADR is computed from daily candles.
The Risk Profile input (“High/Medium/Low”) scales required move sizes using ADR%, and adjusts pivot sensitivity (fewer/more bars).
Higher risk → more sensitive (smaller ADR %, tighter pivot lookback).
Lower risk → stricter filters (larger ADR %, wider pivot lookback).
Explosive-move filter (streak logic)
Searches the seeded lookback for consecutive same-color candles (config via the risk profile).
Requires the cumulative % move of that streak to exceed an ADR-scaled threshold.
When found, the zone is tagged as originating from an “explosive” move (potentially higher reaction probability).
Zone persistence & invalidation
Zones persist and auto-extend to the right until invalidated.
Invalidation occurs when price closes through a rule-based threshold derived from the seed structure (stored per zone).
Once invalidated, the zone is marked inactive and stops updating.
Inputs & Controls
Risk Profile: High / Medium / Low (sets pivot lookback, streak length, and ADR% thresholds).
Labels & Visuals: Toggle labels and level lines; set line width.
Colors/Boxes: Supply (red), Demand (green); dotted breakout references.
No broker/session settings are required; the script adapts per symbol via ADR.
On-Chart Elements
Dotted breakout lines at confirmed levels (with measured bars-to-breakout).
Supply/Demand boxes that extend until invalidation.
Optional labels for clarity; minimal clutter by default.
How to Use
Context: Use higher-TF context for bias; apply zones on your trading TF.
Confluence: Combine zones with your own triggers (structure breaks, rejection wicks, momentum shifts).
Invalidation: If price closes beyond a zone’s invalidation threshold, treat that zone as inactive.
Sensitivity: If too many zones appear, switch to Medium/Low Risk (stricter ADR% & pivots); if too few, use High Risk.
Notes & Limitations
Logic is rule-based; there is no machine learning.
Daily ADR is computed from D timeframe, so intraday charts inherit daily volatility context.
Results vary by symbol and timeframe; validate settings per market.
This is an indicator (no orders or P/L).
My_EMA_CloudsThis script is a comprehensive technical indicator for trading, which includes several functional blocks:
Consolidation zones
Detects and displays price consolidation areas
Draws horizontal support/resistance lines
Generates breakout alerts (up/down)
Allows customization of analysis period and minimum consolidation length
EMA Clouds (Exponential Moving Averages)
Contains 5 sets of EMA clouds with customizable periods
Each cloud consists of short and long EMAs
Cloud colors change depending on trend direction
Offers offset and display settings customization
Support and Resistance Levels
Automatically detects key levels
Uses ATR (Average True Range) for calculation
Displays extended levels
Allows visual style customization
Side Volume Indicator
Shows volume distribution across price levels
Visualizes buy and sell volumes
Displays Point of Control (PoC)
Customizable number of histograms
Liquidation Zones
Identifies potential areas of mass position liquidations
Displays levels with different multipliers (10x, 25x, 50x, 100x)
Shows position volume
Includes heatmap functionality
The script provides traders with a comprehensive set of tools for market analysis, including trend indicators, support/resistance levels, volume metrics, and potential price movement zones. All components can be customized to fit individual trading strategies.
Best usage with Likelihood of Winning - Probability Density Function
Данный скрипт представляет собой комплексный технический индикатор для трейдинга, который включает в себя несколько функциональных блоков:
Зоны консолидации
Определяет и отображает области консолидации цены
Рисует горизонтальные линии поддержки/сопротивления
Генерирует оповещения о прорывах вверх/вниз
Позволяет настраивать период анализа и минимальную длину консолидации
Облака EMA (Exponential Moving Averages)
Содержит 5 наборов EMA-облаков с настраиваемыми периодами
Каждое облако состоит из короткой и длинной EMA
Цвета облаков меняются в зависимости от направления тренда
Есть возможность настройки смещения и отображения
Уровни поддержки и сопротивления
Автоматически определяет ключевые уровни
Использует ATR (средний истинный диапазон) для расчета
Отображает расширенные уровни
Позволяет настраивать визуальный стиль
Индикатор бокового объема
Показывает распределение объема по ценовым уровням
Визуализирует объемы покупок и продаж
Отображает точку контроля (PoC)
Настраиваемое количество гистограмм
Зоны ликвидаций
Определяет потенциальные зоны массовых ликвидаций позиций
Отображает уровни с разными множителями (10x, 25x, 50x, 100x)
Показывает объем позиций
Включает функцию тепловой карты
Скрипт предоставляет трейдерам комплексный набор инструментов для анализа рынка, включая трендовые индикаторы, уровни поддержки/сопротивления, объемные показатели и зоны потенциальных движений цены. Все компоненты можно настраивать под индивидуальные торговые стратегии.
Optimized Trend-Momentum SignalsThis indicator combines trend, momentum, and volume-strength factors into a single buy/sell signal system. It integrates:
SMA 200 → Identifies the long-term trend (price above = bullish bias, below = bearish bias).
MACD (12,26,9) → Confirms momentum direction with line crossovers.
RSI (7) → Filters strength (above 50 = bullish, below 50 = bearish).
ROC (45) → Validates positive or negative rate of change.
Signal Logic:
Buy Signal → Price above SMA 200, MACD bullish, RSI > 50, and ROC > 0.
Sell Signal → Price below SMA 200, MACD bearish, RSI < 50, and ROC < 0.
Features:
Clear arrows for BUY and SELL signals.
Long-term SMA plotted for trend visualization.
Alerts built-in for real-time notifications.
This tool helps traders filter out noise and act only when all major confirmation factors align, reducing false signals and improving decision-making.
Elliott Wave [BigBeluga]🔵 OVERVIEW
Elliott Wave automatically finds and draws an Elliott-style 5-wave impulse and a dashed projection for a potential -(a)→(b)→(c) correction. It detects six sequential reversal points from rolling highs/lows — 1, 2, 3, 4, 5, (a) — validates their relative placement, and then renders the wave with labels and horizontal reference lines. If price invalidates the structure by closing back through the Wave-5 level inside a 100-bar window, the pattern is cleared (optionally kept as “broken”) while key dotted levels remain for context.
🔵 CONCEPTS
Reversal harvesting from extremes : The script scans highest/lowest values over a user-set Length and stores swing points with their bar indices.
Six-point validation : A pattern requires six pivots (1…5 and (a)). Their vertical/temporal order must satisfy Elliott-style constraints before drawing.
Impulse + projection : After confirming 1→5, the tool plots a curved polyline through the pivots and a dashed forward path from (a) toward (b) (midpoint of 5 and (a)) and back to (c).
Risk line (invalidator) : The Wave-5 price is tracked; a close back through it within 100 bars marks the structure as broken.
Minimal persistence : When broken, the wave drawing is removed to avoid noise, while dotted horizontals for waves 5 and 4 remain as reference.
🔵 FEATURES
Automatic pivot collection from rolling highs/lows (user-controlled Length ).
Wave labeling : Points 1–5 are printed; the last collected swing is marked b
. Projected i
& i
are shown with a dashed polyline.
Breaker line & cleanup : If price closes above Wave-5 (opposite for bears) within 100 bars, the pattern is removed; only dotted levels of 5 and 4 stay.
Styling controls :
Length (pivot sensitivity)
Text Size for labels (tiny/small/normal/large)
Wave color input
Show Broken toggle to keep invalidated patterns visible
Lightweight memory : Keeps a compact buffer of recent pivots/draws to stay responsive.
🔵 HOW TO USE
Set sensitivity : Increase Length on noisy charts for cleaner pivots; decrease to catch earlier/shorter structures.
Wait for confirmation : Once 1→5 is printed and (a) appears, use the Wave-5 line as your invalidation. A close back through it within ~100 bars removes the active wave (unless Show Broken is on).
Plan with the dashed path : The (a)→(b)→(c) projection offers a scenario for potential corrective movement and risk placement.
Work MTF : Identify cleaner waves on higher TFs; refine execution on lower TFs near the breaker or during the move toward (b).
Seek confluence : Align with structure (S/R), volume/Delta, or your trend filter to avoid counter-context trades.
🔵 CONCLUSION
Elliott Wave systematizes discretionary wave analysis: it detects and labels the 5-wave impulse, projects a plausible (a)-(b)-(c) path, and self-cleans on invalidation. With clear labels, dotted reference levels, and a practical breaker rule, it gives traders an objective framework for scenario planning, invalidation, and timing.
Sorry Cryptoface Market Cypher B//@version=5
indicator("Sorry Cryptoface Market Cypher B", shorttitle="SorryCF B", overlay=false)
// 🙏 Respect to Cryptoface
// Market Cipher is the brainchild of Cryptoface, who popularized the
// combination of WaveTrend, Money Flow, RSI, and divergence signals into a
// single package that has helped thousands of traders visualize momentum.
// This script is *not* affiliated with or endorsed by him — it’s just an
// open-source educational re-implementation inspired by his ideas.
// Whether you love him or not, Cryptoface deserves credit for taking complex
// oscillator theory and making it accessible to everyday traders.
// -----------------------------------------------------------------------------
// Sorry Cryptoface Market Cypher B
//
// ✦ What it is
// A de-cluttered, optimized rework of the popular Market Cipher B concept.
// This fork strips out repaint-prone code and redundant signals, adds
// higher-timeframe and trend filters, and introduces volatility &
// money-flow gating to cut down on the "confetti signals" problem.
//
// ✦ Key Changes vs. Original MC-B
// - Non-repainting security(): switched to request.security(..., lookahead_off)
// - Inputs updated to Pine v5 (input.int, input.float, etc.)
// - Trend filter: EMA or HTF WaveTrend required for alignment
// - Volatility filter: minimum ADX & ATR % threshold to avoid chop
// - Money Flow filter: signals require minimum |MFI| magnitude
// - WaveTrend slope check: reject flat or contra-slope crosses
// - Cooldown filter: prevents multiple signals within N bars
// - Bar close confirmation: dots/alerts only fire once a candle is closed
// - Hidden divergences + “second range” divergences disabled by default
// (to reduce noise) but can be toggled on
//
// ✦ Components
// - WaveTrend oscillator (2-line system + VWAP line)
// - Money Flow Index + RSI overlay
// - Stochastic RSI
// - Divergence detection (WT, RSI, Stoch)
// - Optional Schaff Trend Cycle
// - Optional Sommi flags/diamonds (HTF confluence markers)
//
// ✦ Benefits
// - Fewer false positives in sideways markets
// - Signals aligned with trend & volatility regimes
// - Removes repaint artifacts from higher-timeframe sources
// - Cleaner chart (reduced “dot spam”)
// - Still flexible: all original toggles/visuals retained
//
// ✦ Notes
// - This is NOT the official Market Cipher.
// - Educational / experimental use only. Do your own testing.
// - Best tested on 2H–4H timeframes; short TFs may still look choppy
//
// ✦ Credits
// Original open-source inspirations by LazyBear, RicardoSantos, LucemAnb,
// falconCoin, dynausmaux, andreholanda73, TradingView community.
// This fork modified by Lumina+Thomas (2025).
// -----------------------------------------------------------------------------
EMA Range OscillatorEMA Range Oscillator (ERO) - User Guide
Overview
The EMA Range Oscillator (ERO) is a technical indicator that measures the distance between two Exponential Moving Averages (EMAs) and the distance between price and EMA. It normalizes these distances into a 0-100 range, helping traders identify trend strength, market momentum, and potential reversal points.
Components
Main Line
Green Line: EMA20 > EMA50 (Uptrend)
Red Line: EMA20 < EMA50 (Downtrend)
Histogram
White Histogram: Price distance from EMA20
Key Levels
Upper Level (80): High divergence zone
Middle Level (50): Neutral zone
Lower Level (20): Low divergence zone
Parameters
ParameterDefaultDescriptionFast EMA20Short-term EMA periodSlow EMA50Long-term EMA periodNormalization Period100Lookback period for scalingUpper80Upper threshold levelLower20Lower threshold level
How to Read the Indicator
High Values (Above 80)
Strong trend in progress
EMAs are widely separated
High momentum
Potential overbought/oversold conditions
Watch for possible trend exhaustion
Low Values (Below 20)
Consolidation phase
EMAs are close together
Low volatility
Potential breakout setup
Range-bound market conditions
Middle Zone (20-80)
Normal market conditions
Moderate trend strength
Balanced momentum
Look for directional clues from color changes
Relative Weighted Rate of Change (WROC) vs Nifty 50Relative Weighted Rate of Change (WROC) vs Nifty 50
Trend Display Table (with Change Alerts)📌 Indicator: Trend Display Table (with Change Alerts)
This indicator helps identify trend direction based on a 15-minute 20 SMA compared against a 10 EMA applied to that SMA.
Trend Logic:
Bullish → 20 SMA crosses above 10 EMA (on SMA values)
Bearish → 20 SMA crosses below 10 EMA (on SMA values)
Neutral → No crossover (trend continues from previous state)
Display:
A compact trend table appears on the chart (top-right), showing the current trend with customizable colors, font size, and background.
Alerts:
Alerts are triggered only when the trend changes (from Bullish → Bearish or Bearish → Bullish).
This prevents repeated alerts on every bar.
✅ Useful for:
Confirming higher timeframe trend bias
Filtering trades in choppy markets
Getting notified instantly when the trend flips
Sinusoidal Cycles OscillatorTitle: Sinusoidal Cycles Oscillator – Multi-Cycle Market Indicator
Description:
Discover market rhythm with the Sinusoidal Cycles Oscillator, a powerful tool for technical analysis and cyclical trading.
Three customizable cycles track short, medium, and long-term market oscillations.
Cycle 1 serves as the main reference wave with an optional mirror envelope.
Cycles 2 & 3 provide supporting harmonics for deeper insight.
Composite wave averages all cycles to reveal overall market phase.
Features:
Fully adjustable periods and amplitude.
Visualize tops, bottoms, and turning points at a glance.
Oscillator ranges from -1 to +1 with clear threshold guides.
Ideal for traders using cycle analysis, harmonic trading, or market timing.
Easy-to-read visual overlay and separate panel option.
Use it to:
Identify potential price reversals.
Compare market cycles across multiple timeframes.
Enhance timing and entry/exit decisions.
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.
Zero Tolerance - NeilsonVWAP Wave system. Perfect for every!!
Helps predict reversals.
Entry point
Exit points
Everything else
ICT Midnight PDH PDLPara marcar rango Midnight to Midnight (NYMO).
También para marcar rangos horarios que tu quieras.
Capiba Directional Momentum Oscillator (ADX-based)
🇬🇧 English
Summary
The Capiba ADX is a momentum oscillator that transforms the classic ADX (Average Directional Index) into a much more intuitive visual tool. Instead of analyzing three separate lines (ADX, DI+, DI-), this indicator consolidates the strength and direction of the trend into a single histogram that oscillates around the zero line.
The result is a clear and immediate reading of market sentiment, allowing traders to quickly identify who is in control—buyers or sellers—and with what intensity.
How to Interpret and Use the Indicator
The operation of the Capiba ADX is straightforward:
Green Histogram (Above Zero): Indicates that buying pressure (DI+) is in control. The height of the bar represents the magnitude of the bullish momentum. Taller green bars suggest a stronger uptrend.
Red Histogram (Below Zero): Indicates that selling pressure (DI-) is in control. The "depth" of the bar represents the magnitude of the bearish momentum. Lower (more negative) red bars suggest a stronger downtrend.
Zero Line (White): This is the equilibrium point. Crossovers through the zero line signal a potential shift in trend control.
Crossover Above: Buyers are taking control.
Crossover Below: Sellers are taking control.
Reference Levels (Momentum Strength)
The indicator plots three fixed reference levels to help gauge the intensity of the move:
0 Line: Equilibrium.
100 Line: Signals significant directional momentum. When the histogram surpasses this level, the trend (whether bullish or bearish) is gaining considerable strength.
200 Line: Signals very strong directional momentum, or even potential exhaustion conditions. Moves that reach this level are powerful but may also precede a consolidation or reversal.
Usage Strategy
Trend Confirmation: Use the indicator to confirm the direction of your analysis. If you are looking for long positions, the Capiba ADX should ideally be green and, preferably, rising.
Strength Identification: Watch for the histogram to cross the 100 and 200 levels to validate the strength of a breakout or an established trend.
Entry/Exit Signals: A zero-line crossover can be used as a primary entry or exit signal, especially when confirmed by other technical analysis tools.
Acknowledgements
This indicator is the result of adapting knowledge and open-source codes shared by the vibrant TradingView community.
KhoiHV - Bollinger Bands Buy/Sell Area ProBollinger Bands Buy/Sell Area Pro is a professional-grade indicator designed to identify potential trading opportunities based on Bollinger Bands. It highlights dynamic buy and sell areas by combining price action with volatility, helping traders quickly visualize market conditions.
✨ Key Features
Automatically plots upper, middle, and lower Bollinger Bands.
Marks Buy Areas when price enters oversold zones near the lower band.
Marks Sell Areas when price enters overbought zones near the upper band.
Configurable inputs for length, source, and multiplier to fit any trading style.
Easy-to-read chart visuals with colored zones for instant recognition.
💡 How to Use
Look for Buy Areas near the lower band in trending markets to catch potential rebounds.
Watch for Sell Areas near the upper band to anticipate possible pullbacks.
Combine with volume, momentum, or trend indicators for stronger confirmation.
This tool is especially useful for traders who want a clear, visual edge in spotting volatility-based entries and exits without constantly recalculating signals.
Trading bot gridsGuide: Price Lines – Arithmetic vs. Geometric
This script draws horizontal price lines (grids) between a start price and an end price.
You can choose whether the lines are distributed evenly (arithmetic) or by percentage (geometric).
🔧 Inputs
Start Price → Lower or upper boundary of the price range.
End Price → Opposite boundary of the price range.
Number of Lines → Total number of lines to be drawn between the start and end prices.
Distribution →
Arithmetic: Fixed USDT distance between each line.
Geometric: Fixed percentage distance between each line.
Grid Color → Color of the drawn lines.
📈 How it Works
The script calculates the lower (lo) and upper (hi) boundaries, regardless of which is entered first.
Arithmetic distribution: Each line is spaced by a fixed amount in USDT.
Geometric distribution: Each line is spaced by the same percentage difference from the previous one.
Lines are created only once at the first bar and remain on the chart.
All lines are extended across the entire visible chart.
💡 Tips
Useful for Grid Bot backtesting or visualizing price zones.
Works for both long and short price ranges.
In geometric mode, lines appear closer together near the lower price range and farther apart toward the upper range.
