אינדיקטורים ואסטרטגיות
Custom Linear Regression Candles with Real-Time PriceHii this is great indicator to build by chatgpt.
How to use------------
1. It is based on the linear regression formula which gives you accurate market conditions.
2. You can do this with a RSI indicator so you can know overbought and oversell label.
3.If you want to get good accuracy then you can use chart type Heikin Ashi.
Input--------------
1. You can take linear regression length on different timeframes, in my backtest it was
5 to 15 min----30 and 1hour to 4hour---20 and Day---10 you can keep it.
2. You can pinpoint the highs and lows of the linear regression line.
--Please use it and give your feedback.
US Net Liquidity + M2 / US Debt (FRED)US Net Liquidity + M2 / US Debt
🧩 What this chart shows
This indicator plots the ratio of US Net Liquidity + M2 Money Supply divided by Total Public Debt.
US Net Liquidity is defined here as the Federal Reserve Balance Sheet (WALCL) minus the Treasury General Account (TGA) and the Overnight Reverse Repo facility (ON RRP).
M2 Money Supply represents the broad pool of liquid money circulating in the economy.
US Debt uses the Federal Government’s total outstanding debt.
By combining net liquidity with M2, then dividing by total debt, this chart provides a structural view of how much monetary “fuel” is in the system relative to the size of the federal debt load.
🧮 Formula
Ratio
=
(
Fed Balance Sheet
−
(
TGA
+
ON RRP
)
)
+
M2
Total Public Debt
Ratio=
Total Public Debt
(Fed Balance Sheet−(TGA+ON RRP))+M2
An optional normalization feature scales the ratio to start at 100 on the first valid bar, making long-term trends easier to compare.
🔎 Why it matters
Liquidity vs. Debt Growth: The numerator (Net Liquidity + M2) captures the monetary resources available to markets, while the denominator (Debt) reflects the expanding obligation of the federal government.
Market Signal: Historically, shifts in net liquidity and money supply relative to debt have coincided with major turning points in risk assets like equities and Bitcoin.
Context: A rising ratio may suggest that liquidity conditions are improving relative to debt expansion, which can be supportive for risk assets. Conversely, a falling ratio may highlight tightening conditions or debt outpacing liquidity growth.
⚙️ How to use it
Overlay this chart against S&P 500, Bitcoin, or gold to analyze correlations with asset performance.
Watch for trend inflections—does the ratio bottom before equities rally, or peak before risk-off periods?
Use normalization for long historical comparisons, or raw values to see the absolute ratio.
📊 Data sources
This indicator pulls from FRED (Federal Reserve Economic Data) tickers available in TradingView:
WALCL: Fed balance sheet
RRPONTSYD: Overnight Reverse Repo
WTREGEN: Treasury General Account
M2SL: M2 money stock
GFDEBTN: Total federal public debt
⚠️ Notes
Some FRED series are updated weekly, others monthly—set your chart timeframe accordingly.
If any ticker is unavailable in your plan, replace it with the equivalent FRED symbol provided in TradingView.
This indicator is intended for macro analysis, not short-term trading signals.
EMRVA//@version=5
indicator("EMRVA", overlay=true)
// === الإعدادات ===
emaLength = input.int(200, "EMA Length")
rsiLength = input.int(14, "RSI Length")
volLength = input.int(20, "Volume MA Length")
adxLength = input.int(14, "ADX Length")
adxFilter = input.int(20, "ADX Minimum Value") // فلتر الاتجاه
// === EMA200 ===
ema200 = ta.ema(close, emaLength)
plot(ema200, color=color.orange, linewidth=2, title="EMA 200")
// === MACD ===
macdLine = ta.ema(close, 12) - ta.ema(close, 26)
signalLine = ta.ema(macdLine, 9)
// === RSI ===
rsi = ta.rsi(close, rsiLength)
// === Volume Confirmation ===
volMA = ta.sma(volume, volLength)
volCond = volume > volMA
// === ADX Manual Calculation ===
upMove = high - high
downMove = low - low
plusDM = na(upMove) ? na : (upMove > downMove and upMove > 0 ? upMove : 0)
minusDM = na(downMove) ? na : (downMove > upMove and downMove > 0 ? downMove : 0)
tr = ta.rma(ta.tr, adxLength)
plusDI = 100 * ta.rma(plusDM, adxLength) / tr
minusDI = 100 * ta.rma(minusDM, adxLength) / tr
dx = 100 * math.abs(plusDI - minusDI) / (plusDI + minusDI)
adx = ta.rma(dx, adxLength)
adxCond = adx > adxFilter
// === شروط الدخول والخروج ===
longCond = close > ema200 and macdLine > signalLine and rsi > 50 and volCond and adxCond
shortCond = close < ema200 and macdLine < signalLine and rsi < 50 and volCond and adxCond
// === منطق الإشارة عند بداية الاتجاه فقط ===
var inLong = false
var inShort = false
buySignal = longCond and not inLong
sellSignal = shortCond and not inShort
if buySignal
inLong := true
inShort := false
if sellSignal
inShort := true
inLong := false
// === إشارات ثابتة ===
plotshape(buySignal, title="Buy Signal", location=location.belowbar,
color=color.green, style=shape.labelup, text="BUY")
plotshape(sellSignal, title="Sell Signal", location=location.abovebar,
color=color.red, style=shape.labeldown, text="SELL")
// === تنبيهات ===
alertcondition(buySignal, title="Buy Alert", message="📈 إشارة شراء مؤكدة مع فلتر ADX")
alertcondition(sellSignal, title="Sell Alert", message="📉 إشارة بيع مؤكدة مع فلتر ADX")
// === رسم ADX للتأكيد ===
plot(adx, title="ADX", color=color.blue)
hline(adxFilter, "ADX Filter", color=color.red)
DrFX Reversal Algo - MACD-RSI System with Dynamic Zone Filtering**DrFX Reversal Algo** is a sophisticated reversal detection system that combines MACD momentum analysis with RSI confirmation and dynamic support/resistance zone filtering. This indicator employs advanced mathematical filtering techniques to identify high-probability reversal points while minimizing false signals through intelligent zone-based filtering.
**Core Innovation & Originality**
This system uniquely integrates four key analytical components:
1. **Enhanced MACD Engine** - Customizable fast (20), slow (50), and signal (12) lengths with crossover/crossunder detection optimized for reversal identification
2. **RSI Power Classification** - 14-period RSI used to classify signal strength and trend bias, distinguishing between "Strong" and regular signals
3. **Kalman-Filtered Dynamic Zones** - Advanced mathematical smoothing of support/resistance levels using Kalman filter algorithms for noise reduction
4. **Gradient-Based Visual System** - Power-weighted bar coloring that visualizes trend strength using MACD histogram and RSI signal intensity
**System Architecture & Functionality**
**Signal Generation Methodology:**
The core algorithm detects MACD line crossovers above and below the signal line, then applies RSI-based classification. When RSI signal (RSI-50) is positive during bullish MACD crossovers, the system generates "Strong Buy" signals. When RSI signal is negative or neutral, it produces regular "Buy" signals. The inverse logic applies for sell signals.
**Dynamic Zone Calculation:**
Support and resistance zones are calculated using a multi-step process:
1. **Volatility Bands**: ATR-based upper/lower bands using (high+low)/2 ± ATR * multiplier
2. **Precise Zone Definition**: Integration of 20-period highest/lowest calculations with volatility bands
3. **Kalman Filter Smoothing**: Advanced noise reduction using configurable Q (0.01) and R (0.1) parameters
4. **Zone Validation**: Real-time adjustment based on price action and volatility changes
**Kalman Filter Implementation:**
The system employs a custom Kalman filter function for zone smoothing:
```
kf_k = kf_p / (kf_p + kf_r)
kf_x = kf_k * input + (1 - kf_k) * previous_estimate
kf_p = (1 - kf_k) * kf_p + kf_q
```
This mathematical approach reduces zone boundary noise while maintaining responsiveness to genuine support/resistance level changes.
**Unique Visual Features**
**Power-Based Gradient System:**
Bar coloring utilizes a sophisticated gradient calculation based on MACD histogram power (absolute value) and RSI signal strength. The system creates dynamic color transitions:
- **Bullish Gradient**: Green spectrum (0-255 intensity) based on histogram power
- **Bearish Gradient**: Red spectrum (0-255 intensity) based on histogram power
- **Consolidation**: Mixed gradient indicating uncertain market conditions
**Dynamic Zone Visualization:**
- **Support Zones**: Blue-filled areas between smoothed support boundaries
- **Resistance Zones**: Red-filled areas between smoothed resistance boundaries
- **Zone Adaptation**: Real-time boundary adjustment based on volatility and price action
**Signal Classification System**
**Signal Strength Hierarchy:**
1. **Strong Buy**: MACD bullish crossover + RSI signal > 0 (above 50-line)
2. **Regular Buy**: MACD bullish crossover + RSI signal ≤ 0 (below 50-line)
3. **Strong Sell**: MACD bearish crossover + RSI signal < 0 (below 50-line)
4. **Regular Sell**: MACD bearish crossover + RSI signal ≥ 0 (above 50-line)
**Optional Zone Filtering:**
When enabled, the system only displays signals when:
- Buy signals: Price above smoothed support zone end
- Sell signals: Price below smoothed resistance zone start
**Usage Instructions**
**Primary Signal Interpretation:**
- **Large Green Triangles**: Strong buy signals with RSI confirmation above 50
- **Small Green Triangles**: Regular buy signals with RSI below 50
- **Large Red Triangles**: Strong sell signals with RSI confirmation below 50
- **Small Red Triangles**: Regular sell signals with RSI above 50
**Zone Analysis:**
- **Blue Zones**: Dynamic support areas where buying interest may emerge
- **Red Zones**: Dynamic resistance areas where selling pressure may increase
- **Zone Breaks**: Price movement outside zones indicates potential trend continuation
**Bar Color Interpretation:**
- **Bright Green**: Strong bullish momentum (high MACD histogram power + positive RSI)
- **Dark Green**: Moderate bullish momentum
- **Bright Red**: Strong bearish momentum (high MACD histogram power + negative RSI)
- **Dark Red**: Moderate bearish momentum
- **Mixed Colors**: Consolidation or uncertain trend direction
**Optimal Usage Strategies:**
1. **Reversal Trading**: Focus on signals occurring near zone boundaries
2. **Confirmation Trading**: Use zone filter to reduce false signals in trending markets
3. **Momentum Trading**: Prioritize "Strong" signals with bright gradient bar coloring
4. **Multi-Timeframe**: Combine with higher timeframe trend analysis for context
**Parameter Customization**
**MACD Settings:**
- **Fast Length (20)**: Shorter periods increase sensitivity
- **Slow Length (50)**: Longer periods reduce noise
- **Signal Smoothing (12)**: Affects crossover signal timing
**Support/Resistance Settings:**
- **Volatility Period (10)**: ATR calculation period for zone width
- **Multiplier (5.0)**: Zone expansion factor based on volatility
**Visual Settings:**
- **Gradient Range (2000)**: Controls color intensity scaling
- **Zone Filtering**: Enables/disables signal filtering based on zone position
**Advanced Features**
**Alert System:**
Comprehensive alert functionality with detailed messages including symbol, timeframe, current price, and signal type. Separate enable/disable options for long and short alerts.
**Mathematical Precision:**
The Kalman filter implementation provides superior noise reduction compared to simple moving averages while maintaining responsiveness to genuine market structure changes.
**Important Considerations**
This system works optimally in markets with clear support/resistance levels and moderate volatility. The Kalman filter smoothing may introduce slight lag during rapid market movements. Strong signals generally provide higher probability setups but may be less frequent than regular signals.
The algorithm combines established techniques (MACD, RSI) with advanced filtering and zone detection methodologies. The integration of multiple confirmation methods helps reduce false signals while maintaining sensitivity to genuine reversal opportunities.
**Disclaimer**: This indicator is designed for educational and analytical purposes. Past performance does not guarantee future results. The system's effectiveness varies across different market conditions and timeframes. Always implement proper risk management and consider multiple confirmation methods before making trading decisions.
FSVZO [Alpha Extract]A sophisticated volume-weighted momentum oscillator that combines Fourier smoothing with Volume Zone Oscillator methodology to deliver institutional-grade flow analysis and divergence detection. Utilizing advanced statistical filtering including ADF trend analysis and multi-dimensional volume dynamics, this indicator provides comprehensive market sentiment assessment through volume-price relationships with extreme zone detection and intelligent divergence recognition for high-probability reversal and continuation signals.
🔶 Advanced VZO Calculation Engine
Implements enhanced Volume Zone Oscillator methodology using relative volume analysis combined with smoothed price changes to create momentum-weighted oscillator values. The system applies exponential smoothing to both volume and price components before calculating positive and negative momentum ratios with trend factor integration for market regime awareness.
🔶 Fourier-Based Smoothing Architecture
Features advanced Fourier approximation smoothing using cosine-weighted calculations to reduce noise while preserving signal integrity. The system applies configurable Fourier length parameters with weighted sum normalization for optimal signal clarity across varying market conditions with enhanced responsiveness to genuine trend changes.
// Fourier Smoothing Algorithm
fourier_smooth(src, length) =>
sum = 0
weightSum = 0
for i = 0 to length - 1
weight = cos(2 * π * i / length)
sum += src * weight
weightSum += weight
sum / weightSum
🔶 Intelligent Divergence Detection System
Implements comprehensive divergence analysis using pivot point methodology with configurable lookback periods for both standard and hidden divergence patterns. The system validates divergence conditions through range analysis and provides visual confirmation through plot lines, labels, and color-coded identification for precise timing analysis.
15MIN
4H
12H
🔶 Flow Momentum Analysis Framework
Calculates flow momentum by measuring oscillator deviation from its exponential moving average, providing secondary confirmation of volume flow dynamics. The system creates momentum-based fills and visual indicators that complement the primary oscillator analysis for comprehensive market flow assessment.
🔶 Extreme Zone Detection Engine
Features sophisticated extreme zone identification at ±98 levels with specialized marker system including white X markers for signals occurring in extreme territory and directional triangles for potential reversal points. The system provides clear visual feedback for overbought/oversold conditions with institutional-level threshold accuracy.
🔶 Dynamic Visual Architecture
Provides advanced visualization engine with bullish/bearish color transitions, dynamic fill regions between oscillator and signal lines, and flow momentum overlay with configurable transparency levels. The system includes flip markers aligned to color junction points for precise signal timing with optional bar close confirmation to prevent repainting.
🔶 ADF Trend Filtering Integration
Incorporates Augmented Dickey-Fuller inspired trend filtering using normalized price statistics to enhance signal quality during trending versus ranging market conditions. The system calculates trend factors based on mean deviation and standard deviation analysis for improved oscillator accuracy across market regimes.
🔶 Comprehensive Alert System
Features intelligent multi-tier alert framework covering bullish/bearish flow detection, extreme zone reversals, and divergence confirmations with customizable message templates. The system provides real-time notifications for critical volume flow changes and structural market shifts with exchange and ticker integration.
🔶 Performance Optimization Framework
Utilizes efficient calculation methods with optimized variable management and configurable smoothing parameters to balance signal quality with computational efficiency. The system includes automatic pivot validation and range checking for consistent performance across extended analysis periods with minimal resource usage.
This indicator delivers sophisticated volume-weighted momentum analysis through advanced Fourier smoothing and comprehensive divergence detection capabilities. Unlike traditional volume oscillators that focus solely on volume patterns, the FSVZO integrates volume dynamics with price momentum and statistical trend filtering to provide institutional-grade flow analysis. The system's combination of extreme zone detection, intelligent divergence recognition, and multi-dimensional visual feedback makes it essential for traders seeking systematic approaches to volume-based market analysis across cryptocurrency, forex, and equity markets with clearly defined reversal and continuation signals.
Parametric Multiplier Backtester🧪 An experimental educational tool for visual market analysis and idea testing through the multiplication and interaction of core technical parameters. It allows you to observe in real time how the combination of indicators affects the resulting curve and the potential efficiency of trading strategies.
📖 Detailed Description
1. Philosophy & Purpose of the Tool
This backtester is not created to search for the “Holy Grail,” but for deep learning and analysis. It is intended for:
👶 Beginner traders – to visually understand how basic indicators work and interact with each other.
🧠 Experienced analysts – to search for new ideas and non-obvious relationships between different aspects of the market (trend, volatility, momentum, volume).
The core idea is combining parameters through multiplication.
👉 Why multiplication? Unlike simple addition, multiplication strengthens signals only when several factors align in the same direction. If at least one parameter shows weakness (close to zero in normalized form), it suppresses the overall result, serving as a filter for false signals.
2. How does it work?
Step 1: Parameter Selection
The tool gathers data from 9 popular indicators: 📈 Price, RSI, ADX, Momentum, ROC, ATR, Volume, Acceleration, Slope.
Step 2: Normalization
Since these indicators differ in nature and scale (e.g., RSI from 0–100 vs ATR in points), they are brought to a unified range. Each parameter is normalized within a given period (Normalization Period). This is the key step for proper functioning.
Step 3: Multiplication
The parameters enabled by the user are multiplied, creating a new derived value — Product Line. This line is an aggregated reflection of the selected market model.
Step 4: Smoothing
The resulting line can be noisy. The Smooth Product Line function (via SMA) reduces noise and highlights the main trend.
Step 5: Interpretation
The smoothed Product Line is compared with its own moving average (Mean Line). Crossovers generate trading signals.
3. What conclusions can be drawn from multiplying parameters?
⚡ RSI × Momentum × Volume – Strength of momentum confirmed by volume. High values may indicate strong, volume-backed moves.
📊 ADX × ATR – Strength of trend and its volatility. High values may signal the beginning of a strong trending move with high volatility.
🚀 Price × Slope × Acceleration – Combined speed and acceleration of the trend. Shows not only where price is going, but with what acceleration.
❌ Disabling parameters – By turning parameters on/off (e.g., Volume), you can instantly see how important each factor is for the current market situation.
4. Real-Time Mode & Instant Feedback
The main educational value of this tool is interactivity:
🔄 Turn indicators on/off in real time.
⏱ Change their periods and instantly observe how the Product Line shape and behavior changes.
📉 Immediately see how these changes affect historical trading signals (blue/red arrows) and strategy performance metrics (Profit Factor, Net Profit, etc.).
This process develops “market intuition” and helps understand which settings work better under different conditions (trend vs range).
5. Default Settings & Recommendations
⚙️ Default settings are optimized for demonstration on the 4H timeframe of the SOLUSDT crypto pair.
Parameter Settings: Switch group (Use RSI, Use ADX, etc.).
Normalization Period (20): Lower = more sensitive, Higher = smoother.
Smooth Product Line (true): Enabled by default for clarity.
Smoothing Period (200): Main sensitivity setting.
Trend Filter: Optional 200-SMA filter. Strategy trades only in the main trend direction.
⚠️ Important Warning: This is an experimental & educational tool. The signals it generates are the result of a mathematical model and are not a ready-to-use trading strategy. Always backtest ideas and apply risk management before risking real money.
Buy and Sell Signals (Altius Consulting)Generates Buy and Sell signals based on MACD and RSI.
- Plots MACD, Signal & Histogram (optional pane).
- Buy Label (toggle): Bullish MACD crossover + RSI < threshold (no convergence requirement).
- Sell Label: Bearish MACD crossover (MACD crosses below Signal) prints a SELL tag.
- Alert: Provided for convergence-based buy condition (add your own for simple crossover if desired).
Dextor PivotThis is Simple Indicator which Show previous Month,Week,Day -High, Avg,Low, Along With EMA Crossovers
EMA Crossover Cloud w/Range-Bound FilterA focused 1-minute EMA crossover trading strategy designed to identify high-probability momentum trades while filtering out low-volatility consolidation periods that typically result in whipsaw losses. Features intelligent range-bound detection and progressive market attention alerts to help traders manage focus and avoid overtrading during unfavorable conditions.
Key Features:
EMA Crossover Signals: 10/20 EMA crossovers with volume surge confirmation (1.3x 20-bar average)
Range-Bound Filter: Automatically detects when price is consolidating in tight ranges (0.5% threshold) and blocks trading signals during these periods
Progressive Consolidation Stages: Visual alerts progress through Range Bound (red) → Coiling (yellow) → Loading (orange) → Trending (green) to indicate market compression and potential breakout timing
Market Attention Gauge: Helps manage focus between active trading and other activities with states: Active (watch close), Building (check frequently), Quiet (check occasionally), Dead (handle other business)
Smart RSI Exits: Cloud-based and RSI extreme level exits with conservative stop losses
Dual Mode Operation: Separate settings allow full backtesting performance while providing visual stay-out warnings for manual trading
How to Use:
Entry Signals: Trade aqua up-triangles (long) and orange down-triangles (short) when they appear with volume confirmation
Stay-Out Warnings: Ignore gray "RANGE" triangles - these indicate crossovers during range-bound periods that should be avoided
Monitor Top-Right Display:
Range: Current 60-bar dollar range
Attention: Market activity level for focus management
Status: Consolidation stage (trade green/yellow, avoid red, prepare for orange)
Position Sizing: Default 167 shares per signal, optimized for the crossover frequency
Alerts: Enable consolidation stage alerts and market attention alerts for automated notifications
Recommended Settings:
Timeframe: 1-minute charts
Symbol: Optimized for volatile stocks like TSLA
"Apply Filter to Backtest": Keep OFF for realistic backtesting, ON to see filtered results
Risk Management:
The strategy includes built-in overtrading protection by identifying and blocking trades during low-volatility periods. The progressive consolidation alerts help identify when markets are "loading" for significant moves, allowing traders to position appropriately for higher-probability setups.
Moving Average SlopeA simple tool that allows you to choose from multiple types of moving averages (e.g. WMA, EMA, SMA, HMA) and define the MA period, and lookback period for slope calculation.
Anrazzi - EMAs/ATR - 1.0.2The Anrazzi – EMAs/ATR indicator is a multi-purpose overlay designed to help traders track trend direction and market volatility in a single clean tool.
It plots up to six customizable moving averages (MAs) and an Average True Range (ATR) value directly on your chart, allowing you to quickly identify market bias, dynamic support/resistance, and volatility levels without switching indicators.
This script is ideal for traders who want a simple, configurable, and efficient way to combine trend-following signals with volatility-based position sizing.
📌 Key Features
Six Moving Averages (MA1 → MA6)
Toggle each MA on/off individually
Choose between EMA or SMA for each
Customize length and color
Perfect for spotting trend direction and pullback zones
ATR Display
Uses Wilder’s ATR formula (ta.rma(ta.tr(true), 14))
Can be calculated on current or higher timeframe
Adjustable multiplier for position sizing (e.g., 1.5× ATR stops)
Displays cleanly in the bottom-right corner
Custom Watermark
Displays symbol + timeframe in top-right
Adjustable color and size for streamers, screenshots, or clear charting
Compact UI
Organized with group and inline inputs for quick configuration
Lightweight and optimized for real-time performance
⚙️ How It Works
MAs: The script uses either ta.ema() or ta.sma() to compute each moving average based on the user-selected type and length.
ATR: The ATR is calculated using ta.rma(ta.tr(true), 14) (Wilder’s smoothing), and optionally scaled by a multiplier for easier use in risk management.
Tables: ATR value and watermark are displayed using table.new() so they stay anchored to the screen regardless of zoom level.
📈 How to Use
Enable the MAs you want to track and adjust their lengths, type, and colors.
Enable ATR if you want to see volatility — optionally select a higher timeframe for broader context.
Use MAs to:
Identify overall trend direction (e.g. price above MA20 = bullish)
Spot pullback zones for entries
See when multiple MAs cluster together as support/resistance zones
Use ATR value to:
Size your stop-loss dynamically (e.g. stop = entry − 1.5×ATR)
Detect volatility breakouts (ATR spikes = market expansion)
🎯 Recommended For
Day traders & swing traders
Trend-following & momentum strategies
Volatility-based risk management
Traders who want a clean, all-in-one dashboard
Cycle Low (RSI + StochRSI) – v5 John.KCycle Low (RSI + StochRSI) – v5 John.K
This tool is designed to detect potential cycle lows by combining RSI and Stochastic RSI oversold signals.
RSI Oversold + Cross → confirms momentum exhaustion
StochRSI Cross from Oversold → confirms short-term cycle turn
Score System (0–4) → evaluates confluence strength
Strict Mode → requires both RSI and StochRSI to be oversold for A+ signals
One-Bar Tolerance → allows RSI & StochRSI to cross within 1 bar
Anchor Option → optional reference level for cycle projection
Signals are plotted directly on the candles as green triangles (CL) when conditions are met.
Adjust thresholds (RSI, Stoch, Score) to control signal frequency.
FU + SMI Validator (Proper FU, 30m)Overview
The FU + SMI Validator is a sophisticated technical analysis indicator designed to detect Proper FU (Fakeouts or Liquidity Sweeps) on the 30-minute timeframe. This tool aims to help traders identify high-probability reversal setups that occur when price briefly breaks key levels (sweeping liquidity), then reverses with momentum confirmation.
Fakeouts are common market events where price action “hunts stops” before reversing direction. Correctly identifying these events can offer excellent entry points with defined risk. This indicator combines price action logic with momentum and volatility filters to provide reliable signals.
Core Concepts
Proper FU (Fakeout) Detection
At its core, the script identifies proper fakeouts by checking if the current bar’s price:
For bullish fakeouts: dips below the previous bar’s low (sweeping stops) and then closes above the previous bar’s high
For bearish fakeouts: spikes above the previous bar’s high and then closes below the previous bar’s low
This ensures that the breakout is a true sweep rather than just a one-sided close.
Optionally, the script can require one additional confirmation bar after the FU, ensuring that the momentum is sustained and reducing false signals.
SMI-style Momentum Validation
To improve the quality of signals, the indicator uses a proxy for the Stochastic Momentum Index (SMI) by calculating the difference between current and past linear regression slopes of price. This momentum check helps ensure that fakeouts occur alongside actual directional strength.
Key points:
Momentum must be increasing in the direction of the FU signal.
Momentum filters can be enabled or disabled based on user preference.
Squeeze Condition to Avoid Low-Volatility Traps
The script includes a volatility filter based on a squeeze-like condition:
It compares Bollinger Bands (BB) and Keltner Channels (KC).
When BB bands contract inside KC bands, the market is in a squeeze state, signaling low volatility.
Fakeouts during squeeze conditions are often unreliable; the script can filter these out to reduce false alarms.
Killzone Session Timing Filter
Recognizing that liquidity and volatility vary by session, this tool supports optional filtering for:
London Killzone: 09:00 to 10:30 (UK time)
New York Killzone: 13:00 to 14:30 (UK time)
Signals only trigger during these high-activity windows if enabled, helping traders focus on periods with the best liquidity and market participation.
Note: For Killzone filtering to work accurately, your TradingView chart must be set to the UK timezone.
Features & Benefits
Robust FU detection ensures the breakout price action is meaningful, reducing noise.
Momentum filter via linear regression slope captures trend strength in a smooth, mathematically sound way.
Low-volatility squeeze avoidance helps reduce false signals in choppy or range-bound markets.
Killzone timing filter focuses your attention on the most liquid and active market hours.
Optional confirmation bar increases signal reliability.
Raw FU markers allow visualization of all detected fakeouts for pattern recognition and manual analysis.
Alerts built-in for both valid buy and sell FU setups, enabling real-time notification and quicker decision-making.
Customization Options
Killzone usage: Enable or disable the session timing filter.
Sessions: Configure London and New York killzone time ranges.
Momentum alignment: Enable or disable momentum filter based on SMI proxy.
Volatility filter: Avoid signals during squeeze or low-volatility conditions.
FU confirmation: Option to require one additional confirming candle after the initial FU.
Squeeze and momentum parameters: Adjust Bollinger Bands length and multiplier, Keltner Channel length and ATR multiplier.
Raw FU markers: Show or hide all detected fakeouts regardless of filters.
How to Use This Indicator
Apply to 30-minute charts for forex pairs, indices, cryptocurrencies, or other instruments.
Set your chart timezone to UK time if using Killzone filters.
Adjust input parameters based on your preferred sessions and risk tolerance.
Look for green “VALID BUY FU” labels below bars for bullish fakeout entries.
Look for red “VALID SELL FU” labels above bars for bearish fakeout entries.
Use the alert system to receive notifications on setups.
Combine with your existing analysis or risk management strategy for entries, stops, and profit targets.
Why Use FU + SMI Validator?
Fakeouts are some of the most lucrative but tricky setups for many traders. Without proper filters, they can lead to false entries and losses. This script integrates price action, momentum, volatility, and session timing into one package, providing a robust tool to spot high-quality fakeout opportunities and improve trading confidence.
Limitations
Requires chart to be set to UK timezone for session filters.
Designed specifically for 30-minute timeframe — performance on other timeframes may vary.
Momentum is a proxy, not a direct SMI calculation.
Like all indicators, best used in conjunction with sound risk management and other analysis tools.
Potential Enhancements
Conversion into a full strategy script for backtesting entries and exits.
Addition of other momentum indicators (RSI, MACD) or volume filters.
Customizable time zones or auto time zone detection.
Multi-timeframe analysis capabilities.
Visual dashboard for summary of signal stats.
EMRV101//@version=5
indicator("EMA200 + MACD + RSI + Volume Confirmation + Alerts", overlay=true)
// === الإعدادات ===
emaLength = input.int(200, "EMA Length")
rsiLength = input.int(14, "RSI Length")
volLength = input.int(20, "Volume MA Length")
// === EMA200 ===
ema200 = ta.ema(close, emaLength)
plot(ema200, color=color.orange, linewidth=2, title="EMA 200")
// === MACD ===
macdLine = ta.ema(close, 12) - ta.ema(close, 26)
signalLine = ta.ema(macdLine, 9)
// === RSI ===
rsi = ta.rsi(close, rsiLength)
// === Volume Confirmation ===
volMA = ta.sma(volume, volLength)
volCond = volume > volMA
// === شروط الدخول والخروج ===
longCond = close > ema200 and macdLine > signalLine and rsi > 50 and volCond
shortCond = close < ema200 and macdLine < signalLine and rsi < 50 and volCond
// === منطق الإشارة عند بداية الاتجاه فقط ===
var inLong = false
var inShort = false
buySignal = longCond and not inLong
sellSignal = shortCond and not inShort
if buySignal
inLong := true
inShort := false
if sellSignal
inShort := true
inLong := false
// === إشارات ثابتة ===
plotshape(buySignal, title="Buy Signal", location=location.belowbar,
color=color.green, style=shape.labelup, text="BUY")
plotshape(sellSignal, title="Sell Signal", location=location.abovebar,
color=color.red, style=shape.labeldown, text="SELL")
// === تنبيهات ===
alertcondition(buySignal, title="Buy Alert", message="📈 إشارة شراء مؤكدة")
alertcondition(sellSignal, title="Sell Alert", message="📉 إشارة بيع مؤكدة")
Panchak Indicator 2025 - High/Low with OptionsPanchak high low line, plote high low of panchak dates candels
Bollinger Bands (with Width/GaUGE)This overlay plots standard Bollinger Bands and makes volatility obvious. The fill between bands is color-coded by band width (tight = red “squeeze”, wide = teal “expansion”, mid = yellow). A compact table (top-right) shows live BB Gap ($) and BB Width (%), and the width also appears in the status line. Thresholds for squeeze/expansion are user-set. Use it to avoid low-volatility chop and time breakouts when width expands.
✅ Multi-TF RSI Buy/Sell Signal + Debug Panel
Multi-TF RSI Buy/Sell Signal + Debug Panel
This script provides RSI-based Buy and Sell signals confirmed across multiple timeframes, designed to help identify high-confluence market entries. Includes an optional debug panel for real-time monitoring and diagnostics.
How It Works
RSI Thresholds:
Oversold (OS): RSI < Oversold value → potential Buy
Overbought (OB): RSI > Overbought value → potential Sell
Timeframe Inputs:
You can monitor RSI across up to 4 different timeframes (customizable).
You can enable/disable each individually.
Signal Confirmation:
You define how many of the selected timeframes need to agree (via Min Confirmations).
If Auto Confirm is enabled, it automatically matches the number of confirmations to how many timeframes are enabled.
Signal Logic:
If enough RSI values are oversold, a Buy arrow is shown below the bar.
If enough RSI values are overbought, a Sell arrow appears above the bar.
Alerts are also triggered accordingly.
How to Use
Choose the 4 timeframes you want to monitor.
Toggle which ones to enable (checkboxes).
Select RSI thresholds for oversold/overbought conditions.
Enable Auto Confirmations or manually set how many confirmations are required to trigger a signal.
Use the Style tab to customize the signal visuals.
Turn on alerts with Buy Alert or Sell Alert
Debug Panel
Toggle it on/off via Show Debug Panel.
Move its position to any chart corner.
Updates every 5 bars.
Displays:
Each TF label
RSI value
If it's currently oversold/overbought
If that TF is currently enabled
Tips:
Try to match chart timeframe with one of your selected TFs for better signal visibility.
Use in confluence with other indicators for best results.
RSI alone is not a guaranteed signal – treat it as a filter or alert, not a full strategy.
Notes
This is not financial advice. Always combine with your own analysis.
RSI-based systems work best in ranging or balanced conditions.
Confirmation logic helps reduce noise, but no indicator is infallible.
MACD Scaled Overlay█ OVERVIEW
The "MACD Scaled Overlay" indicator is an advanced version of the classic MACD (Moving Average Convergence Divergence) oscillator that displays signals directly on the price chart. Instead of a traditional separate panel, the MACD line, signal line, and histogram are scaled and overlaid on the price chart, making it easier to identify key price levels and potential reversal points. The indicator also supports the detection of divergences (regular and hidden) and offers extensive customization options, such as adjusting colors, line thickness, and enabling/disabling visual elements.
█ CONCEPTS
The "MACD Scaled Overlay" indicator is designed to simplify trend and reversal analysis by integrating MACD signals with the price chart. The MACD Scaled Overlay is scaled relative to the average candle range, allowing the lines and histogram to dynamically adjust to market volatility. Additionally, the indicator enables the detection of divergences (bullish and bearish, both regular and hidden) based on the traditional MACD histogram (before scaling), ensuring consistency with classic divergence analysis. The indicator is most effective when combined with other technical analysis tools, such as Fibonacci levels, pivot points, or trend lines.
█ MACD Calculations and Scaling
The indicator is based on the classic MACD formula, which includes:
-MACD Line: The difference between the fast EMA (default: 12) and the slow EMA (default: 26).
-Signal Line: The EMA of the MACD line (default: 9).
-Histogram: The difference between the MACD line and the signal line.
Scaling is achieved by normalizing the MACD values relative to the standard deviation and the average candle range. This makes the lines and histogram dynamically adjust to market volatility, improving their readability and utility on the price chart. The scaling formulas are:
-MACD Scaled: macdNorm * avgRangeLines * scaleFactor
-Signal Scaled: signalNorm * avgRangeLines * scaleFactor
-Histogram Scaled: histNorm * avgRangeHist * scaleFactor
Where:
-macdNorm and signalNorm are the normalized MACD and signal line values.
-avgRangeLines and avgRangeHist are the average candle ranges.
-scaleFactor is the scaling multiplier (default: 2).
The positioning of the lines and histogram is relative to the candle midpoint (candleMid = (high + low) / 2), ensuring proper display on the price chart. Divergences are calculated based on the traditional MACD histogram (before scaling), maintaining consistency with standard divergence detection methodology.
█INDICATOR FEATURES
-Dynamic MACD and Signal Lines: Scaled and overlaid on the price chart, facilitating the identification of reversal points.
-Histogram: Displays the difference between the MACD and signal lines, dynamically adjusted to market volatility.
-Divergence Detection: Ability to detect regular and hidden divergences (bullish and bearish) based on the traditional MACD histogram, with options to enable/disable their display.
-Visual Customization: Options to adjust colors, line thickness, transparency, and enable/disable elements such as the zero line, MACD line, signal line, or histogram.
-Smoothing: Smoothing length for lines (default: 1) and histogram (default: 3). Smoothing may delay crossover signals, which should be considered during analysis.
-Alerts: Alert conditions for MACD and signal line crossovers, enabling notifications for potential buy/sell signals.
█ HOW TO SET UP THE INDICATOR
-Add the "MACD Scaled Overlay" indicator to your TradingView chart.
-Configure parameters in the settings, such as EMA lengths, scaling multiplier, or smoothing periods, to match your trading style.
-Enable or disable the display of the zero line, MACD line, signal line, or histogram based on your needs.
-Adjust colors and line thickness in the "Style" section and transparency settings in the input section to optimize visualization.
█ HOW TO USE
Add the indicator to your chart, configure the parameters, and observe the interactions of the price with the MACD line, signal line, and histogram to identify potential entry and exit points. Key signals include:
-MACD and Signal Line Crossovers: A crossover of the MACD line above the signal line may indicate a buy signal (bullish cross), while a crossover below the signal line may indicate a sell signal (bearish cross).
-Crossings Through the Price Line (Zero): The MACD line or histogram crossing the price line (candle midpoint) may indicate a change in momentum. For example, the histogram moving from negative to positive values near the price line may signal increasing bullish trend strength.
-Divergences: Detection of regular and hidden divergences (bullish and bearish) based on the traditional MACD histogram can help predict trend reversals. Divergences are not standalone signals, as they are delayed by the specified pivot length (default: 3). However, they help strengthen the significance of other signals, such as crossovers or support/resistance levels.
The indicator is most effective when combined with other tools, such as Fibonacci levels, pivot points, or support/resistance lines, to confirm signals.
Full Numeric Panel For Scalping – By Ali B.AI Full Numeric Panel – Final (Scalping Edition)
This script provides a numeric dashboard overlay that summarizes the most important technical indicators directly on the price chart. Instead of switching between multiple panels, traders can monitor all key values in a single glance – ideal for scalpers and short-term traders.
🔧 What it does
Displays live values for:
Price
EMA9 / EMA21 / EMA200
Bollinger Bands (20,2)
VWAP (Session)
RSI (configurable length)
Stochastic RSI (RSI base, Stoch length, K & D smoothing configurable)
MACD (Fast/Slow/Signal configurable) → Line, Signal, and Histogram shown separately
ATR (configurable length)
Adds Dist% column: shows how far the current price is from each reference (EMA, BB, VWAP etc.), with green/red coloring for positive/negative values.
Optional Rel column: shows context such as RSI zone, Stoch RSI cross signals, MACD cross signals.
🔑 Why it is original
Unlike simply overlaying indicators, this panel:
Collects multiple calculations into one unified table, saving chart space.
Provides numeric precision (configurable decimals for MACD, RSI, etc.), so scalpers can see exact values.
Highlights signal conditions (crossovers, overbought/oversold, zero-line crosses) with clear text or symbols.
Fully customizable (toggle indicators on/off, position of the panel, text size, colors).
📈 How to use it
Add the script to your chart.
In the input menu, enable/disable the metrics you want (RSI, Stoch RSI, MACD, ATR).
Match the panel parameters with your sub-indicators (for example: set Stoch RSI = 3/3/9/3 or MACD = 6/13/9) to ensure values are identical.
Use the numeric panel as a quick decision tool:
See if RSI is near 30/70 zones.
Spot Stoch RSI crossovers or extreme zones (>80 / <20).
Confirm MACD line/signal cross and histogram direction.
Monitor volatility with ATR.
This makes scalping decisions faster without losing precision. The panel is not a signal generator but a numeric assistant that summarizes market context in real time.
⚡ This version fixes earlier limitations (no more vague mashup, clear explanation of originality, clean chart requirement). TradingView moderators should accept it since it now explains:
What the script is
How it is different
How to use it practically
Dynamic Levels This indicator plots key price levels (Open, High, Low, Mid, Close) from multiple higher timeframes (Monday, Daily, Weekly, Monthly, Yearly).
It allows you to track how price interacts with important reference levels without switching timeframes.
🔑 Features
✅ Monday levels (MO, MH, MM)
By default: shows the last completed Monday (fixed values).
Option: “live mode” to update Monday High/Low/Mid while Monday’s candle is forming.
✅ Daily levels (DO, DH, DL, DM, DC)
Live: Daily High/Low/Mid update dynamically while today’s candle is forming.
Previous Daily Close (DC) is always fixed.
✅ Weekly levels (WO, WH, WL, WM)
Live: Weekly High/Low/Mid update dynamically while this week’s candle is forming.
Weekly Open is fixed.
✅ Monthly levels (MO(n), MH(n-1), ML(n-1), MM(n-1), MC(n-1))
Shows last completed month’s values (constant, never changing).
Current Monthly Open is also shown (naturally fixed).
✅ Yearly levels (YO(n), YH(n-1), YL(n-1), YM(n-1), YC(n-1))
Shows last completed year’s values (constant, never changing).
Current Yearly Open is also shown (naturally fixed).
🎨 Customization
Toggle each level (on/off) in indicator settings.
Individual color settings for Monday, Daily, Weekly, Monthly, and Yearly.
Adjustable line width and transparency.
Optional short labels (MO, DO, WM, etc.) displayed on the right side of the chart.
🔄 Dynamic Logic
Daily and Weekly → update dynamically while their candle is forming.
Monday, Monthly, and Yearly → use fixed values from the last completed bar (do not “breathe”).
📌 Use cases
Quickly see where price stands relative to previous close, current open, or mid-levels.
Use Monday Open/High/Mid as strong intraday references.
Use Monthly/Yearly levels as long-term support/resistance zones.
Estrategia Cava - IndicadorSimplified Criteria of the Cava Strategy
Below is the logic behind the Cava strategy, broken down into conditions for a buy operation:
Variables and Necessary Data
EMA 55: 55-period Exponential Moving Average.
MACD: Two lines (MACD Line and Signal Line) and the histogram.
RSI: Relative Strength Index.
Stochastic: Two lines (%K and %D).
Closing Price: The closing price of the current period.
Previous Closing Price: The closing price of the previous period.
Entry Logic (Buy Operation)
Trend Condition (EMA 55):
The price must be above the EMA 55.
The EMA 55 must have a positive slope (or at least not a negative one). This can be checked if the current EMA 55 is greater than the previous period's EMA 55.
Momentum Conditions (Oscillators):
MACD: The MACD line must have crossed above the signal line. For a strong signal, this cross should occur near or above the zero line.
RSI: The RSI must have exited the "oversold" zone (generally below 30) and be rising.
Stochastic: The Stochastic must have crossed upwards from the "oversold" zone (generally below 20).
Confirmation Condition (Price):
The current closing price must be higher than the previous closing price. This confirms the strength of the signal.
Position Management (Exit)
Take Profit: An exit can be programmed at a predetermined price target (e.g., the next resistance level) or when the momentum of the move begins to decrease.
Stop Loss: A stop loss should be placed below a significant support level or the entry point to limit losses in case the trade does not evolve as expected. The Cava strategy focuses on dynamic stop-loss management, moving it in the trader's favor as the price moves.
In summary, the strategy is a filtering system. If all conditions are met, the trade is considered high probability. If only some are met, the signal is discarded, and you wait for the next one. It's crucial to understand that discipline and risk management are just as important as the indicators themselves.
