Multi-Timeframe PivotDescription:
This script provides an advanced tool for multi-timeframe pivot point
analysis. It identifies swing points based on a candle's relationship to
its neighbors. The default strength settings of 1 align with the Inner
Circle Trader (ICT) concept of market structure.
The ICT concept defines a swing point based on a simple 3-candle pattern:
- A swing high is a candle where the candles to the immediate left and right
both have lower highs.
- A swing low is a candle where the candles to the immediate left and right
both have higher lows.
A key feature is its ability to accurately calculate and translate pivot
points from up to five higher timeframes (HTFs) and display them
precisely on a lower timeframe (LTF) chart.
NOTE: This indicator is designed to show HTF data on an LTF chart.
If you select a timeframe in the settings that is lower than your
current chart's timeframe, it will show pivots for the chart's
timeframe instead.
Core Features:
- Up to five independent higher timeframes.
- Per-timeframe customization for pivot strength (left/right bars) and color.
- Optional "Watchlines" that project the price of each pivot forward,
complete with a text label identifying the timeframe.
- An optional "Alignment Model" that colors the background when price is
aligned across all active timeframes (requires at least 2 TFs to be enabled).
Default State:
For a clean initial application, the Watchlines and Alignment Model features
are disabled by default but can be enabled in the settings.
指標和策略
VEP - Volume Explosion Predictor💥 VEP - Volume Explosion Predictor
General Overview
The Volume Explosion Predictor (VEP) is an advanced indicator that analyzes volume peaks to predict when the next volume explosion might occur. Using statistical analysis on historical patterns, it provides accurate probabilities on moments of greater trading activity.
MAIN FEATURES
🎯 Intelligent volume peak detection
Automatically identifies significant volume peaks
Anti-consecutive filter to avoid redundant signals
Customizable threshold for detection sensitivity
📊 Advanced statistical analysis
Calculates the average distance between volume peaks
Monitors the number of sessions without peaks
Tracks the maximum historical range without activity
🔮 Predictive system
Dynamic probability: Calculates the probability of an imminent peak
Visual indicators: Background colors that change based on probability
Time forecasts: Estimates remaining sessions to the next peak
📈 Visual signals
Colored arrows: Green for bullish peaks, red for bearish peaks
Statistics table: Complete real-time overview
ALERT SYSTEM
🚨 Three Alert Levels
New Valid Volume Peak: New peak detected
Approaching Prediction: Increasing probability
High Peak Probability: High probability of explosion
HOW TO USE IT
📋 Recommended setup
Timeframe : Works on all timeframes but daily, weekly or monthly timeframe usage is recommended. In any case, it should always be used consistently with your time horizon
Markets : Stocks, crypto, forex, commodities
Threshold for volume peak realization : It's recommended to start with 2.0x (i.e., twice the volume average) for normal markets, 1.5x for more volatile markets. This parameter can be set in the settings as desired
🎨 Visual interpretation
Green Arrows : Peak during bullish candle
Red Arrows : Peak during bearish candle
Red Background : High probability (>90%) of new peak
Yellow Background : Medium probability (50-70%)
📊 STATISTICS TABLE
The table shows:
Total peaks analyzed
Average distance between peaks
Current sessions without peaks
Forecast remaining sessions
Percentage probability
Volume threshold needed for peak realization
STRATEGIC ADVANTAGES
🎯 For Day Traders
Anticipates moments of greater volatility for analysis, supporting the evaluation of trading setups and providing context on low volume periods
📈 For Swing Traders
Identifies high-probability volume patterns, supporting breakout analysis with volume and improving understanding of market timing
🔍 For Technical Analysts
Understands the stock's volume patterns.
Helps evaluate the historical market interest and supports quantitative research and analysis
OTHER THINGS TO KNOW...
A) Anti-Consecutive Algorithm : allows to avoid multiple and consecutive volume signals and peaks at close range
B) Statistical Validation : Uses standard deviation for accuracy
C) Memory Management : Limits historical data for optimal performance
D) Compatibility : Works with all TradingView chart types
⚠️ IMPORTANT DISCLAIMER
This indicator is exclusively a technical analysis tool for studying volume patterns. It does not provide investment advice, trading signals or entry/exit points. All trading decisions are at the complete discretion and responsibility of the user. Always use in combination with other technical and fundamental analysis and proper risk management.
DESCRIZIONE IN ITALIANO
💥 VEP - Volume Explosion Predictor
Panoramica Generale
Il Volume Explosion Predictor (VEP) è un indicatore avanzato che analizza i picchi di volume per prevedere quando potrebbe verificarsi la prossima esplosione di volume. Utilizzando analisi statistiche sui pattern storici, fornisce probabilità accurate sui momenti di maggiore attività di trading.
CARATTERISTICHE PRINCIPALI
🎯 Rilevamento intelligente dei picchi di volume
- Identifica automaticamente i picchi di volume significativi
- Filtro anti-consecutivo per evitare segnali ridondanti
- Soglia personalizzabile per la sensibilità del rilevamento
📊 Analisi statistica avanzata
Calcola la distanza media tra i picchi di volume
Monitora il numero di sessioni senza picchi
Traccia il range massimo storico senza attività
🔮 Sistema predittivo
Probabilità dinamica: Calcola la probabilità di un imminente picco
Indicatori visivi: Colori di sfondo che cambiano in base alla probabilità
Previsioni temporali: Stima delle sessioni rimanenti al prossimo picco
📈 Segnali visivi
1) Frecce colorate: Verdi per picchi rialzisti, rosse per ribassisti
2) Tabella statistiche: Panoramica completa in tempo reale
SISTEMA DI ALERT
🚨 Tre Livelli di Alert
1) New Valid Volume Peak: Nuovo picco rilevato
2) Approaching Prediction: Probabilità in aumento
3) High Peak Probability: Alta probabilità di esplosione
COME UTILIZZARLO
📋 Setup consigliato
- Timeframe : Funziona su tutti i timeframe ma è consigliabile un utilizzo su timeframe giornaliero, settimanale o mensile. In ogni caso va sempre utilizzato coerentemente con il proprio orizzonte temporale
- Mercati : Azioni, crypto, forex, commodities
- Limite affinché si realizzi il picco di volumi : Si consiglia di iniziare con 2.0x (ovvero due volte la media dei volumi) per mercati normali, 1.5x per mercati più volatili. Questo parametro può essere settato nelle impostazioni a proprio piacimento
🎨 Interpretazione visuale
Frecce Verdi : Picco durante candela rialzista
Frecce Rosse : Picco durante candela ribassista
Sfondo Rosso : Alta probabilità (>90%) di nuovo picco
Sfondo Giallo : Probabilità media (50-70%)
📊 TABELLA STATISTICHE
La tabella mostra:
1. Totale picchi analizzati
2. Distanza media tra picchi
3. Sessioni attuali senza picchi
4. Previsione sessioni rimanenti
5. Probabilità percentuale
6. Soglia volume necessaria affinché si realizzi il picco di volumi
VANTAGGI STRATEGICI
🎯 Per Day Traders
Anticipa i momenti di maggiore volatilità per analisi, supportando la valutazione dei setup di trading e fornendo al contempo un contesto sui periodi di basso volume
📈 Per Swing Traders
1. Identifica pattern di volume ad alta probabilità, supportando l'analisi dei breakout con volume e migliorando la comprensione dei tempi di mercato
🔍 Per Analisti Tecnici
Comprende i pattern di volume del titolo.
Aiuta a fare una valutazione dell'interesse storico del mercato ed è di supporto alla ricerca e analisi quantitativa
ALTRE COSE DA SAPERE...
A) Algoritmo Anti-Consecutivo : permette di evitare segnali e picchi di volume multipli e consecutivi multipli a distanza ravvicinata
B) Validazione Statistica : Utilizza deviazione standard per l'accuratezza
C) Gestione Memoria : Limita i dati storici per performance ottimali
D) Compatibilità : Funziona con tutti i tipi di grafico TradingView
⚠️ DISCLAIMER IMPORTANTE
Questo indicatore è esclusivamente uno strumento di analisi tecnica per lo studio dei pattern di volume. Non fornisce consigli di investimento, segnali di trading o punti di ingresso/uscita. Tutte le decisioni di trading sono a completa discrezione e responsabilità dell'utente. Utilizzare sempre in combinazione con altre analisi tecniche, fondamentali e una adeguata gestione del rischio.
市场参与度宽度 (S&P/Nasdaq)指标功能和解读：
下拉菜单切换： 在指标的设置（点击指标名称旁边的小齿轮图标）中，您可以轻松地从 "S&P 500" 切换到 "Nasdaq 100"，指标会自动更新显示对应的数据。
同框显示： 蓝色的粗线代表50天市场参与度（中期健康度），橙色的细线代表20天市场参与度（短期情绪），两者在同一个副图中，方便您进行对比和观察。
关键水平线：
50%线 (灰色实线): 这是最重要的多空分界线。当指标线持续在50%以上时，表明市场处于强势；反之则处于弱势。
80%线 (红色虚线): 当短期指标（橙色线）进入80%以上时，可能意味着市场情绪过热，进入超买区。
20%线 (绿色虚线): 当短期指标进入20%以下时，可能意味着市场情绪过度悲观，进入超卖区，有时是机会的信号。
背离分析： 您可以观察当主图指数（如SPY）创出新高时，这个指标是否也创出新高。如果指数新高而指标没有，就形成了顶背离，是市场内部力量减弱的警示信号。
Indicator function and interpretation:
Drop-down menu switch: In the indicator settings (click the small gear icon next to the indicator name), you can easily switch from "S&P 500" to "Nasdaq 100", and the indicator will automatically update to display the corresponding data.
Same frame display: The thick blue line represents the 50-day market participation (medium-term health), and the thin orange line represents the 20-day market participation (short-term sentiment). Both are in the same sub-chart for your comparison and observation.
Key horizontal lines:
50% line (solid gray line): This is the most important dividing line between long and short. When the indicator line is continuously above 50%, it indicates that the market is strong; otherwise, it is weak.
80% line (dashed red line): When the short-term indicator (orange line) enters above 80%, it may mean that the market sentiment is overheated and enters the overbought zone.
20% line (dashed green line): When the short-term indicator enters below 20%, it may mean that the market sentiment is overly pessimistic and enters the oversold zone, which is sometimes a signal of opportunity.
Divergence analysis: You can observe whether this indicator also hits a new high when the main chart index (such as SPY) hits a new high. If the index hits a new high but the indicator does not, it forms a top divergence, which is a warning signal of weakening internal market forces.
GER40 Opening Range Breakout (Simple)✅ GER40 Opening Range Breakout Strategy — Trading Plan
🎯 Objective:
Capture early momentum after the Frankfurt open by trading breakouts of the initial 15-minute range.
📌 Rules Summary:
Instrument: GER40 (DAX40)
Timeframe: 5-minute or 15-minute chart
Session Focus: 08:00–10:00 CET
Opening Range: 08:00–08:15 CET
🛠 Entry Conditions:
Long entry: Price breaks above the 08:00–08:15 high with volume confirmation.
Short entry: Price breaks below the 08:00–08:15 low with volume confirmation.
Optional confirmation: RSI > 50 for long, RSI < 50 for short.
Omori Law Recovery PhasesWhat is the Omori Law?
Originally a seismological model, the Omori Law describes how earthquake aftershocks decay over time. It follows a power law relationship: the frequency of aftershocks decreases roughly proportionally to 1/(t+c)^p, where:
t = time since the main shock
c = time offset constant
p = power law exponent (typically around 1.0)
Application to the markets
Financial markets experience "aftershocks" similar to earthquakes:
Market Crashes as Main Shocks: Major market declines (crashes) represent the initial shock event.
Volatility Decay: After a crash, market volatility typically declines following a power law pattern rather than a linear or exponential one.
Behavioral Components: The decay pattern reflects collective market psychology - initial panic gives way to uncertainty, then stabilization, and finally normalization.
The Four Recovery Phases
The Omori decay pattern in markets can be divided into distinct phases:
Acute Phase: Immediately after the crash, characterized by extreme volatility, panic selling, and sharp reversals. Trading is hazardous.
Reaction Phase: Volatility begins decreasing, but markets test previous levels. False rallies and retests of lows are common.
Repair Phase: Structure returns to the market. Volatility approaches normal levels, and traditional technical analysis becomes more reliable.
Recovery Phase: The final stage where market behavior normalizes completely. The impact of the original shock has fully decayed.
Why It Matters for Traders
Understanding where the market stands in this recovery cycle provides valuable context:
Risk Management: Adjust position sizing based on the current phase
Strategy Selection: Different strategies work in different phases
Psychological Preparation: Know what to expect based on the phase
Time Horizon Guidance: Each phase suggests appropriate time frames for trading
EMA + RSI Trend Strength v6✅ Indicator Name:
EMA + RSI Trend Strength v6
📌 Purpose:
This indicator combines trend detection (via EMA) with momentum confirmation (via RSI) to help traders identify high-probability bullish or bearish conditions. It also provides optional visual buy/sell signals and trend shading directly on the chart.
⚙️ Core Components:
1. Inputs:
emaLen: Length of the Exponential Moving Average (default: 50).
rsiLen: RSI period for momentum analysis (default: 14).
rsiOB, rsiOS: RSI levels for context (default: 70/30, but mainly 50 is used for trend strength).
showSignals: Toggle for showing entry signals.
2. Logic:
Bullish Condition:
Price is above the EMA
RSI is above 50 (indicating positive momentum)
Bearish Condition:
Price is below the EMA
RSI is below 50
3. Visuals & Outputs:
EMA Line: Orange line on the price chart showing the trend direction.
Buy Signal: Green triangle appears below the candle when bullish condition is met.
Sell Signal: Red triangle appears above the candle when bearish condition is met.
Background Color:
Light green when bullish
Light red when bearish
MACD Histogram v6This script plots the MACD histogram, a popular momentum indicator used to identify bullish/bearish momentum shifts, convergence/divergence between moving averages, and potential entry/exit signals.
Core Components:
Inputs:
fast – Period for the fast EMA (default: 12).
slow – Period for the slow EMA (default: 26).
signal – Period for the signal line EMA (default: 9).
TimezoneFormatIANAUTCLibrary "TimezoneFormatIANAUTC"
Provides either the full IANA timezone identifier or the corresponding UTC offset for TradingView’s built-in variables and functions.
tz(_tzname, _format)
Parameters:
_tzname (string) : "London", "New York", "Istanbul", "+1:00", "-03:00" etc.
_format (string) : "IANA" or "UTC"
Returns: "Europe/London", "America/New York", "UTC+1:00"
Example Code
import ARrowofTime/TimezoneFormatIANAUTC/1 as libtz
sesTZInput = input.string(defval = "Singapore", title = "Timezone")
example1 = libtz.tz("London", "IANA") // Return Europe/London
example2 = libtz.tz("London", "UTC") // Return UTC+1:00
example3 = libtz.tz("UTC+5", "IANA") // Return UTC+5:00
example4 = libtz.tz("UTC+4:30", "UTC") // Return UTC+4:30
example5 = libtz.tz(sesTZInput, "IANA") // Return Asia/Singapore
example6 = libtz.tz(sesTZInput, "UTC") // Return UTC+8:00
sesTime1 = time("","1300-1700", example1) // returns the UNIX time of the current bar in session time or na
sesTime2 = time("","1300-1700", example2) // returns the UNIX time of the current bar in session time or na
sesTime3 = time("","1300-1700", example3) // returns the UNIX time of the current bar in session time or na
sesTime4 = time("","1300-1700", example4) // returns the UNIX time of the current bar in session time or na
sesTime5 = time("","1300-1700", example5) // returns the UNIX time of the current bar in session time or na
sesTime6 = time("","1300-1700", example6) // returns the UNIX time of the current bar in session time or na
Parameter Format Guide
This section explains how to properly format the parameters for the tz(_tzname, _format) function.
_tzname (string) must be either;
A valid timezone name exactly as it appears in the chart’s lower-right corner (e.g. New York, London).
A valid UTC offset in ±H:MM or ±HH:MM format. Hours: 0–14 (zero-padded or not, e.g. +1:30, +01:30, -0:00). Minutes: Must be 00, 15, 30, or 45
examples;
"New York" → ✅ Valid chart label
"London" → ✅ Valid chart label
"Berlin" → ✅ Valid chart label
"America/New York" → ❌ Invalid chart label. (Use "New York" instead)
"+1:30" → ✅ Valid offset with single-digit hour
"+01:30" → ✅ Valid offset with zero-padded hour
"-05:00" → ✅ Valid negative offset
"-0:00" → ✅ Valid zero offset
"+1:1" → ❌ Invalid (minute must be 00, 15, 30, or 45)
"+2:50" → ❌ Invalid (minute must be 00, 15, 30, or 45)
"+15:00" → ❌ Invalid (hour must be 14 or below)
_tztype (string) must be either;
"IANA" → returns full IANA timezone identifier (e.g. "Europe/London"). When a time function call uses an IANA time zone identifier for its timezone argument, its calculations adjust automatically for historical and future changes to the specified region’s observed time, such as daylight saving time (DST) and updates to time zone boundaries, instead of using a fixed offset from UTC.
"UTC" → returns UTC offset string (e.g. "UTC+01:00")
My Strategy: Uptrend Pullback ScreenerUptrend Pullback Screener. this will filter the stock who is in uptrend and ready to pullback from support.
Tsallis Entropy Market RiskTsallis Entropy Market Risk Indicator
What Is It?
The Tsallis Entropy Market Risk Indicator is a market analysis tool that measures the degree of randomness or disorder in price movements. Unlike traditional technical indicators that focus on price patterns or momentum, this indicator takes a statistical physics approach to market analysis.
Scientific Foundation
The indicator is based on Tsallis entropy, a generalization of traditional Shannon entropy developed by physicist Constantino Tsallis. The Tsallis entropy is particularly effective at analyzing complex systems with long-range correlations and memory effects—precisely the characteristics found in crypto and stock markets.
The indicator also borrows from Log-Periodic Power Law (LPPL).
Core Concepts
1. Entropy Deficit
The primary measurement is the "entropy deficit," which represents how far the market is from a state of maximum randomness:
Low Entropy Deficit (0-0.3): The market exhibits random, uncorrelated price movements typical of efficient markets
Medium Entropy Deficit (0.3-0.5): Some patterns emerging, moderate deviation from randomness
High Entropy Deficit (0.5-0.7): Strong correlation patterns, potentially indicating herding behavior
Extreme Entropy Deficit (0.7-1.0): Highly ordered price movements, often seen before significant market events
2. Multi-Scale Analysis
The indicator calculates entropy across different timeframes:
Short-term Entropy (blue line): Captures recent market behavior (20-day window)
Long-term Entropy (green line): Captures structural market behavior (120-day window)
Main Entropy (purple line): Primary measurement (60-day window)
3. Scale Ratio
This measures the relationship between long-term and short-term entropy. A healthy market typically has a scale ratio above 0.85. When this ratio drops below 0.85, it suggests abnormal relationships between timeframes that often precede market dislocations.
How It Works
Data Collection: The indicator samples price returns over specific lookback periods
Probability Distribution Estimation: It creates a histogram of these returns to estimate their probability distribution
Entropy Calculation: Using the Tsallis q-parameter (typically 1.5), it calculates how far this distribution is from maximum entropy
Normalization: Results are normalized against theoretical maximum entropy to create the entropy deficit measure
Risk Assessment: Multiple factors are combined to generate a composite risk score and classification
Market Interpretation
Low Risk Environments (Risk Score < 25)
Market is functioning efficiently with reasonable randomness
Price discovery is likely effective
Normal trading and investment approaches appropriate
Medium Risk Environments (Risk Score 25-50)
Increasing correlation in price movements
Beginning of trend formation or momentum
Time to monitor positions more closely
High Risk Environments (Risk Score 50-75)
Strong herding behavior present
Market potentially becoming one-sided
Consider reducing position sizes or implementing hedges
Extreme Risk Environments (Risk Score > 75)
Highly ordered market behavior
Significant imbalance between buyers and sellers
Heightened probability of sharp reversals or corrections
Practical Application Examples
Market Tops: Often characterized by gradually increasing entropy deficit as momentum builds, followed by extreme readings near the actual top
Market Bottoms: Can show high entropy deficit during capitulation, followed by normalization
Range-Bound Markets: Typically display low and stable entropy deficit measurements
Trending Markets: Often show moderate entropy deficit that remains relatively consistent
Advantages Over Traditional Indicators
Forward-Looking: Identifies changing market structure before price action confirms it
Statistical Foundation: Based on robust mathematical principles rather than empirical patterns
Adaptability: Functions across different market regimes and asset classes
Noise Filtering: Focuses on meaningful structural changes rather than price fluctuations
Limitations
Not a Timing Tool: Signals market risk conditions, not precise entry/exit points
Parameter Sensitivity: Results can vary based on the chosen parameters
Historical Context: Requires some historical perspective to interpret effectively
Complementary Tool: Works best alongside other analysis methods
Enjoy :)
Avg High/Low Lines with TP & SL아래 코드는 TradingView Pine Script v6으로 작성된 스크립트로, 주어진 캔들 수 동안의 평균 고가와 저가를 계산해서 그 위에 수평선을 그리며, 해당 수평선 돌파 시 진입 가격을 기록하고, 손절가(SL)와 목표가(TP)를 자동으로 계산하여 표시하는 전략입니다. 알림(alert) 기능도 포함되어 있습니다.
코드 주요 기능 요약
length 기간 동안 평균 고가, 저가를 단순 이동평균(SMA)으로 계산
평균 고가선, 저가선 수평선을 일정 바 개수만큼 좌우 연장하여 차트에 표시
평균 고가 돌파 시 매수 진입, 평균 저가 돌파 시 매도 진입 처리
진입 가격 저장 및 상태 관리 (inLong, inShort 플래그)
손절가(SL): 롱이면 평균 저가, 숏이면 평균 고가
목표가(TP): 진입가에서 손절 거리의 1.5배만큼 설정
진입가 기준으로 TP, SL 라인과 라벨 표시
상단 돌파 후 종가 마감 시 매수 알림, 하단 돌파 후 종가 마감 시 매도 알림
Sure! Here’s the English explanation of your TradingView Pine Script v6 code:
Summary of Key Features
Calculates the simple moving average (SMA) of the high and low prices over a user-defined number of candles (length).
Draws horizontal lines for the average high and average low, extending them a specified number of bars to the left and right on the chart.
Detects breakouts above the average high to trigger a long entry, and breakouts below the average low to trigger a short entry.
Records the entry price and manages trade states using flags (inLong, inShort).
Sets the stop loss (SL) at the average low for long positions, and at the average high for short positions.
Calculates the take profit (TP) level based on the entry price plus 1.5 times the stop loss distance.
Draws lines and labels for the TP and SL levels starting from the entry bar, extended to the right.
Sends alerts when the price closes above the average high after a breakout (long signal), or closes below the average low after a breakout (short signal).
-onestar-
Khalid's Custom ForecastThe indicator printed on the chart is as expected beads on the information for last 5 years , this indicator could be linked to others to give future price actions
ATR Stop-Loss with Fibonacci Take-Profit [jpkxyz]ATR Stop-Loss with Fibonacci Take-Profit Indicator
This comprehensive indicator combines Average True Range (ATR) volatility analysis with Fibonacci extensions to create dynamic stop-loss and take-profit levels. It's designed to help traders set precise risk management levels and profit targets based on market volatility and mathematical ratios.
Two Operating Modes
Default Mode (Rolling Levels)
In default mode, the indicator continuously plots evolving stop-loss and take-profit levels based on real-time price action. These levels update dynamically as new bars form, creating rolling horizontal lines across the chart. I use this mode primarily to plot the rolling ATR-Level which I use to trail my Stop-Loss into profit.
Characteristics:
Levels recalculate with each new bar
All selected Fibonacci levels display simultaneously
Uses plot() functions with trackprice=true for price tracking
Custom Anchor Mode (Fixed Levels)
This is the primary mode for precision trading. You select a specific timestamp (typically your entry bar), and the indicator locks all calculations to that exact moment, creating fixed horizontal lines that represent your actual trade levels.
Characteristics:
Entry line (blue) marks your anchor point
Stop-loss calculated using ATR from the anchor bar
Fibonacci levels projected from entry-to-stop distance
Lines terminate when price breaks through them
Includes comprehensive alert system
Core Calculation Logic
ATR Stop-Loss Calculation:
Stop Loss = Entry Price ± (ATR × Multiplier)
Long positions: SL = Entry - (ATR × Multiplier)
Short positions: SL = Entry + (ATR × Multiplier)
ATR uses your chosen smoothing method (RMA, SMA, EMA, or WMA)
Default multiplier is 1.5, adjustable to your risk tolerance
Fibonacci Take-Profit Projection:
The distance from entry to stop-loss becomes the base unit (1.0) for Fibonacci extensions:
TP Level = Entry + (Entry-to-SL Distance × Fibonacci Ratio)
Available Fibonacci Levels:
Conservative: 0.618, 1.0, 1.618
Extended: 2.618, 3.618, 4.618
Complete range: 0.0 to 4.764 (23 levels total)
Multi-Timeframe Functionality
One of the indicator's most powerful features is timeframe flexibility. You can analyze on one timeframe while using stop-loss and take-profit calculations from another.
Best Practices:
Identify your entry point on execution timeframe
Enable "Custom Anchor" mode
Set anchor timestamp to your entry bar
Select appropriate analysis timeframe
Choose relevant Fibonacci levels
Enable alerts for automated notifications
Example Scenario:
Analyse trend on 4-hour chart
Execute entry on 5-minute chart for precision
Set custom anchor to your 5-minute entry bar
Configure timeframe setting to "4h" for swing-level targets
Select appropriate Fibonacci Extension levels
Result: Precise entry with larger timeframe risk management
Visual Intelligence System
Line Behaviour in Custom Anchor Mode:
Active levels: Lines extend to the right edge
Hit levels: Lines terminate at the breaking bar
Entry line: Always visible in blue
Stop-loss: Red line, terminates when hit
Take-profits: Green lines (1.618 level in gold for emphasis)
Customisation Options:
Line width (1-4 pixels)
Show/hide individual Fibonacci levels
ATR length and smoothing method
ATR multiplier for stop-loss distance
RSP / VOO 比值指標The RSP/VOO ratio compares the performance of the S&P 500 Equal Weight ETF (RSP) to the S&P 500 Market Cap Weighted ETF (VOO). When the ratio is falling, it indicates that large-cap stocks—especially mega-cap tech names—are outperforming the broader market. In contrast, a rising ratio suggests that smaller and mid-sized companies are catching up or leading, which may signal a healthy broadening of market participation. Investors often use this ratio to identify shifts in market leadership and assess the strength or fragility of a rally.
MACD + MA 2-Min Binary Options Strategy (Strategy Mode)📈 "MACD + MA Crossover Momentum Strategy" (2-Minute Expiry)
✅ Objective:
Catch short-term momentum in the direction of the trend confirmed by MACD crossover and MA alignment.
🧰 Strategy Setup
🕒 Chart Timeframe:
15-second or 30-second candles
(2-minute expiry = 4–8 candles ahead)
📊 Indicators:
EMA 5 (fast)
EMA 13 (slow)
MACD (12, 26, 9) – Standard settings
(Optional): Support/Resistance zones (manual or indicator)
🟩 Call (Buy) Conditions:
EMA 5 crosses above EMA 13
MACD Line crosses above the Signal Line (MACD crossover happens after or at the same time as EMA cross)
MACD histogram is increasing (momentum rising)
Price is above both EMAs, confirming trend strength
No major resistance or news in the next 2 minutes
🟨 Enter on the close of the confirmation candle. Set expiry: 2 minutes from entry.
🟥 Put (Sell) Conditions:
EMA 5 crosses below EMA 13
MACD Line crosses below Signal Line
MACD histogram is decreasing
Price is below both EMAs
No support zone or news in next 2 minutes
✅ Additional Entry Filters
Only trade in the direction of the higher timeframe trend (check 5-minute chart to confirm)
Avoid trading during low volume (e.g., lunch hours, between sessions)
Avoid entry right after a MACD crossover has been running for several candles (too late)
Use price action candles to confirm (e.g., engulfing, strong momentum bars)
🧠 Example Workflow (Call Trade):
You're watching GBP/USD on 30-sec candles.
EMA 5 just crosses above EMA 13.
MACD line crosses above signal, histogram increases.
Price is above both EMAs, showing strength.
Candle closes strong bullish.
➡️ Enter CALL with 2-minute expiry.
Rolling Log Returns [BackQuant]Rolling Log Returns
The Rolling Log Returns indicator is a versatile tool designed to help traders, quants, and data-driven analysts evaluate the dynamics of price changes using logarithmic return analysis. Widely adopted in quantitative finance, log returns offer several mathematical and statistical advantages over simple returns, making them ideal for backtesting, portfolio optimization, volatility modeling, and risk management.
What Are Log Returns?
In quantitative finance, logarithmic returns are defined as:
ln(Pₜ / Pₜ₋₁)
or for rolling periods:
ln(Pₜ / Pₜ₋ₙ)
where P represents price and n is the rolling lookback window.
Log returns are preferred because:
They are time additive : returns over multiple periods can be summed.
They allow for easier statistical modeling , especially when assuming normally distributed returns.
They behave symmetrically for gains and losses, unlike arithmetic returns.
They normalize percentage changes, making cross-asset or cross-timeframe comparisons more consistent.
Indicator Overview
The Rolling Log Returns indicator computes log returns either on a standard (1-period) basis or using a rolling lookback period , allowing users to adapt it to short-term trading or long-term trend analysis.
It also supports a comparison series , enabling traders to compare the return structure of the main charted asset to another instrument (e.g., SPY, BTC, etc.).
Core Features
✅ Return Modes :
Normal Log Returns : Measures ln(price / price ), ideal for day-to-day return analysis.
Rolling Log Returns : Measures ln(price / price ), highlighting price drift over longer horizons.
✅ Comparison Support :
Compare log returns of the primary instrument to another symbol (like an index or ETF).
Useful for relative performance and market regime analysis .
✅ Moving Averages of Returns :
Smooth noisy return series with customizable MA types: SMA, EMA, WMA, RMA, and Linear Regression.
Applicable to both primary and comparison series.
✅ Conditional Coloring :
Returns > 0 are colored green ; returns < 0 are red .
Comparison series gets its own unique color scheme.
✅ Extreme Return Detection :
Highlight unusually large price moves using upper/lower thresholds.
Visually flags abnormal volatility events such as earnings surprises or macroeconomic shocks.
Quantitative Use Cases
🔍 Return Distribution Analysis :
Gain insight into the statistical properties of asset returns (e.g., skewness, kurtosis, tail behavior).
📉 Risk Management :
Use historical return outliers to define drawdown expectations, stress tests, or VaR simulations.
🔁 Strategy Backtesting :
Apply rolling log returns to momentum or mean-reversion models where compounding and consistent scaling matter.
📊 Market Regime Detection :
Identify periods of consistent overperformance/underperformance relative to a benchmark asset.
📈 Signal Engineering :
Incorporate return deltas, moving average crossover of returns, or threshold-based triggers into machine learning pipelines or rule-based systems.
Recommended Settings
Use Normal mode for high-frequency trading signals.
Use Rolling mode for swing or trend-following strategies.
Compare vs. a broad market index (e.g., SPY or QQQ ) to extract relative strength insights.
Set upper and lower thresholds around ±5% for spotting major volatility days.
Conclusion
The Rolling Log Returns indicator transforms raw price action into a statistically sound return series—equipping traders with a professional-grade lens into market behavior. Whether you're conducting exploratory data analysis, building factor models, or visually scanning for outliers, this indicator integrates seamlessly into a modern quant's toolbox.
Evening Sessions HighlighterHighlights the evening hours ranging from opening hours to any other hours specified.
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
Simple Volume Profile with POC, VAH, VAL + nPOCVRVP by Kolesnik
This indicator halp you with analitick
Market Maker Trap Reversal V1Market Maker Trap Reversal V1 is a lightweight, precision-focused tool designed to detect the same liquidity manipulation tactics used by institutional players and market makers.
This script identifies key liquidity sweeps of prior swing highs/lows and confirms trap reversals when price closes back inside the swept range — a signature move of smart money designed to trap retail breakout traders.
Built for disciplined execution, this tool includes:
✅ Sweep detection using custom swing lookbacks
✅ Convincing trap confirmation (strong candle body)
✅ Optional NY session filter for optimal timing
✅ Clean long/short alerts for seamless automation
✅ No indicators — just raw price action and intent
Use this strategy to mirror market maker logic, avoid false breakouts, and trade with real conviction around liquidity events.
**Coded with the help of Zero"
ZF RSI PLOT1. How RSI Is Calculated
RSI is typically computed over 14 periods (days, hours, etc.) using the formula:
RSI=100−1001+RS
RSI=100−1+RS100
where
RS=Average Gain over N periodsAverage Loss over N periods
RS=Average Loss over N periodsAverage Gain over N periods
2. Overbought (> 70)
Definition: An RSI reading above 70 suggests that the instrument has experienced relatively large gains and may be “overbought.”
Interpretation:
Potential Reversal: Prices may have risen too far, too fast, and could be due for a pullback or consolidation.
Exit/Take Profits: Traders often trim long positions or tighten stops as RSI climbs above 70.
Confirmation Needed:
Bearish “RSI divergence” (price makes a higher high while RSI makes a lower high).
Price action signals (e.g., bearish candlestick patterns).
Volume drying up on advances.
3. Oversold (< 30)
Definition: An RSI reading below 30 suggests that the instrument has experienced relatively large losses and may be “oversold.”
Interpretation:
Potential Bounce: Prices may have fallen too far, too fast, and could be due for a rebound or consolidation.
Buying Opportunity: Traders often look to initiate or add to long positions as RSI drops below 30.
Confirmation Needed:
Bullish “RSI divergence” (price makes a lower low while RSI makes a higher low).
Price action signals (e.g., hammer candlesticks, support levels).
Volume picking up on declines.
4. Divergences
Bullish Divergence: Price ↓ makes a lower low, RSI ↑ makes a higher low ⇒ possible trend change to the upside.
Bearish Divergence: Price ↑ makes a higher high, RSI ↓ makes a lower high ⇒ possible trend change to the downside.
5. Adjustments & Variations
Stronger Trends: Use 80/20 thresholds to avoid early signals in very strong up- or down-trends.
Shorter/Longer Periods: Adjust the look-back period (e.g., 9 for more sensitivity, 21 for smoother signals) depending on your time frame.
6. Limitations & Best Practices
Can Stay Extreme: In strong trends, RSI may remain overbought/oversold for extended periods—don’t trade it in isolation.
Combine with Other Tools: Use trend filters (moving averages, ADX), support/resistance, and volume to confirm entries.
Risk Management: Always set stops and manage position size; RSI signals can fail.
7. Putting It All Together
Identify Trend: Is the market in an uptrend, downtrend, or range?
Watch RSI Extremes: Note when RSI crosses above 70 or below 30.
Seek Confirmation: Look for divergences, candlestick/pricing signals, and supporting volume.
Execute & Manage: Enter with clear stop-loss levels, consider scaling, and lock in profits appropriately.
By understanding both the raw threshold signals and the nuances—like divergences and trend-context—you can harness RSI’s simplicity while mitigating its pitfalls.
