6am Candle High/Low Indicator with Highlight6am Candle High/Low Indicator with Highlight
6am Candle High/Low Indicator with Highlight
6am Candle High/Low Indicator with Highlight
6am Candle High/Low Indicator with Highlight 6am Candle High/Low Indicator with Highlight
指標和策略
MESA Adaptive Ehlers Flow | AlphaNattMESA Adaptive Ehlers Flow | AlphaNatt
An advanced adaptive indicator based on John Ehlers' MESA (Maximum Entropy Spectrum Analysis) algorithm that automatically adjusts to market cycles in real-time, providing superior trend identification with minimal lag across all market conditions.
🎯 What Makes This Indicator Revolutionary?
Unlike traditional moving averages with fixed parameters, this indicator uses Hilbert Transform mathematics to detect the dominant market cycle and adapts its responsiveness accordingly:
Automatically detects market cycles using advanced signal processing
MAMA (MESA Adaptive Moving Average) adapts from fast to slow based on cycle phase
FAMA (Following Adaptive Moving Average) provides confirmation signals
Dynamic volatility bands that expand and contract with cycle detection
Zero manual optimization required - the indicator tunes itself
📊 Core Components
1. MESA Adaptive Moving Average (MAMA)
The MAMA is the crown jewel of adaptive indicators. It uses the Hilbert Transform to measure the market's dominant cycle and adjusts its smoothing factor in real-time:
During trending phases: Responds quickly to capture moves
During choppy phases: Smooths heavily to filter noise
Transition is automatic and seamless based on price action
Parameters:
Fast Limit: Maximum responsiveness (default: 0.5) - how fast the indicator can adapt
Slow Limit: Minimum responsiveness (default: 0.05) - maximum smoothing during consolidation
2. Following Adaptive Moving Average (FAMA)
The FAMA is a slower version of MAMA that follows the primary signal. The relationship between MAMA and FAMA provides powerful trend confirmation:
MAMA > FAMA: Bullish trend in progress
MAMA < FAMA: Bearish trend in progress
Crossovers signal potential trend changes
3. Hilbert Transform Cycle Detection
The indicator employs sophisticated DSP (Digital Signal Processing) techniques:
Detects the dominant cycle period (1.5 to 50 bars)
Measures phase relationships in the price data
Calculates adaptive alpha values based on cycle dynamics
Continuously updates as market character changes
⚡ Key Features
Adaptive Alpha Calculation
The indicator's "intelligence" comes from its adaptive alpha:
Alpha dynamically adjusts between Fast Limit and Slow Limit based on the rate of phase change in the market cycle. Rapid phase changes trigger faster adaptation, while stable cycles maintain smoother response.
Dynamic Volatility Bands
Unlike static bands, these adapt to both ATR volatility AND the current cycle state:
Bands widen when the indicator detects fast adaptation (trending)
Bands narrow during slow adaptation (consolidation)
Band Multiplier controls overall width (default: 1.5)
Provides context-aware support and resistance
Intelligent Color Coding
Cyan: Bullish regime (MAMA > FAMA and price > MAMA)
Magenta: Bearish regime (MAMA < FAMA and price < MAMA)
Gray: Neutral/transitional state
📈 Trading Strategies
Trend Following Strategy
The MESA indicator excels at identifying and riding strong trends while automatically reducing sensitivity during choppy periods.
Entry Signals:
Long: MAMA crosses above FAMA with price closing above MAMA
Short: MAMA crosses below FAMA with price closing below MAMA
Exit/Management:
Exit longs when MAMA crosses below FAMA
Exit shorts when MAMA crosses above FAMA
Use dynamic bands as trailing stop references
Mean Reversion Strategy
When price extends beyond the dynamic bands during established trends, look for bounces back toward the MAMA line.
Setup Conditions:
Strong trend confirmed by MAMA/FAMA alignment
Price touches or exceeds outer band
Enter on first sign of reversal toward MAMA
Target: Return to MAMA line or opposite band
Cycle-Based Swing Trading
The indicator's cycle detection makes it ideal for swing trading:
Enter on MAMA/FAMA crossovers
Hold through the detected cycle period
Exit on counter-crossover or band extremes
Works exceptionally well on 4H to Daily timeframes
🔬 Technical Background
The Hilbert Transform
The Hilbert Transform is a mathematical operation used in signal processing to extract instantaneous phase and frequency information from a signal. In trading applications:
Separates trend from cycle components
Identifies the dominant market cycle without curve-fitting
Provides leading indicators of trend changes
MESA Algorithm Components
Smoothing: 4-bar weighted moving average for noise reduction
Detrending: Removes linear price trend to isolate cycles
InPhase & Quadrature: Orthogonal components for phase measurement
Homodyne Discriminator: Calculates instantaneous period
Adaptive Alpha: Converts period to smoothing factor
MAMA/FAMA: Final adaptive moving averages
⚙️ Optimization Guide
Fast Limit (0.1 - 0.9)
Higher values (0.5-0.9): More responsive, better for volatile markets and lower timeframes
Lower values (0.1-0.3): Smoother response, better for stable markets and higher timeframes
Default 0.5: Balanced for most applications
Slow Limit (0.01 - 0.1)
Higher values (0.05-0.1): Less smoothing during consolidation, more signals
Lower values (0.01-0.03): Heavy smoothing during chop, fewer but cleaner signals
Default 0.05: Good noise filtering while maintaining responsiveness
Band Multiplier (0.5 - 3.0)
Adjust based on instrument volatility
Backtest to find optimal value for your specific market
1.5 works well for most forex and equity indices
Consider higher values (2.0-2.5) for cryptocurrencies
🎨 Visual Interpretation
The gradient visualization shows probability zones around the MESA line:
MESA line: The adaptive trend center
Band expansion: Indicates strong cycle detection and trending
Band contraction: Indicates consolidation or ranging market
Color intensity: Shows confidence in trend direction
💡 Best Practices
Let it adapt: Give the indicator 50+ bars to properly calibrate to the market
Combine timeframes: Use higher timeframe MESA for trend bias, lower for entries
Respect the bands: Price rarely stays outside bands for extended periods
Watch for compression: Narrow bands often precede explosive moves
Volume confirmation: Combine with volume for higher probability setups
📊 Optimal Timeframes
15m - 1H: Day trading with Fast Limit 0.6-0.8
4H - Daily: Swing trading with Fast Limit 0.4-0.6 (recommended)
Weekly: Position trading with Fast Limit 0.2-0.4
⚠️ Important Considerations
The indicator needs time to "learn" the market - avoid trading the first 50 bars after applying
Extreme gap events can temporarily disrupt cycle calculations
Works best in markets with detectable cyclical behavior
Less effective during news events or extreme volatility spikes
Consider the detected cycle period for position holding times
🔍 What Makes MESA Superior?
Compared to traditional indicators:
vs. Fixed MAs: Automatically adjusts to market conditions instead of using one-size-fits-all parameters
vs. Other Adaptive MAs: Uses true DSP mathematics rather than simple volatility adjustments
vs. Manual Optimization: Continuously re-optimizes itself in real-time
vs. Lagging Indicators: Hilbert Transform provides earlier trend change detection
🎓 Understanding Adaptation
The magic of MESA is that it solves the eternal dilemma of technical analysis: be fast and get whipsawed in chop, or be smooth and miss the early move. MESA does both by detecting when to be fast and when to be smooth.
Adaptation in Action:
Strong trend starts → MESA quickly detects phase change → Fast Limit kicks in → Early entry
Trend continues → Phase stabilizes → MESA maintains moderate speed → Smooth ride
Consolidation begins → Phase changes slow → Slow Limit engages → Whipsaw avoidance
🚀 Advanced Applications
Multi-timeframe confluence: Use MESA on 3 timeframes for high-probability setups
Divergence detection: Watch for MAMA/price divergences at band extremes
Cycle period analysis: The internal period calculation can guide position duration
Band squeeze trading: Narrow bands + MAMA/FAMA cross = high-probability breakout
Created by AlphaNatt - Based on John Ehlers' MESA research. For educational purposes. Always practice proper risk management. Not financial advice. Always DYOR.
Alerts Killzones + PD/WL/ML Levels (No Labels)This indicator automatically highlights the London and New York killzones and triggers alerts at key price levels — without adding any labels or text clutter to the chart.
Features:
Highlights London (10:00–13:00) and New York (15:00–17:00) sessions (GMT+3, Romania).
Draws and updates key levels automatically:
PDH / PDL – Previous Day High & Low
WH / WL – Previous Week High & Low
MH / ML – Previous Month High & Low
Alerts when price touches any of these levels.
Alerts at session opens and closes for both London and New York.
Clean interface – no labels or extra markers on chart.
Ideal for:
Traders who follow ICT concepts, session-based setups, or liquidity sweeps and want precise alerts without chart noise.
Arnaud Legoux Gaussian Flow | AlphaNattArnaud Legoux Gaussian Flow | AlphaNatt
A sophisticated trend-following and mean-reversion indicator that combines the power of the Arnaud Legoux Moving Average (ALMA) with advanced Gaussian distribution analysis to identify high-probability trading opportunities.
🎯 What Makes This Indicator Unique?
This indicator goes beyond traditional moving averages by incorporating Gaussian mathematics at multiple levels:
ALMA uses Gaussian distribution for superior price smoothing with minimal lag
Dynamic envelopes based on Gaussian probability zones
Multi-layer gradient visualization showing probability density
Adaptive envelope modes that respond to market conditions
📊 Core Components
1. Arnaud Legoux Moving Average (ALMA)
The ALMA is a highly responsive moving average that uses Gaussian distribution to weight price data. Unlike simple moving averages, ALMA can be fine-tuned to balance responsiveness and smoothness through three key parameters:
ALMA Period: Controls the lookback window (default: 21)
Gaussian Offset: Shifts the Gaussian curve to adjust lag vs. responsiveness (default: 0.85)
Gaussian Sigma: Controls the width of the Gaussian distribution (default: 6.0)
2. Gaussian Envelope System
The indicator features three envelope calculation modes:
Fixed Mode: Uses ATR-based fixed width for consistent envelope sizing
Adaptive Mode: Dynamically adjusts based on price acceleration and volatility
Hybrid Mode: Combines ATR and standard deviation for balanced adaptation
The envelopes represent statistical probability zones. Price moving beyond these zones suggests potential mean reversion opportunities.
3. Momentum-Adjusted Envelopes
The envelope width automatically expands during strong trends and contracts during consolidation, providing context-aware support and resistance levels.
⚡ Key Features
Multi-Layer Gradient Visualization
The indicator displays 10 gradient layers between the ALMA and envelope boundaries, creating a visual "heat map" of probability density. This helps traders quickly assess:
Distance from the mean
Potential support/resistance strength
Overbought/oversold conditions in context
Dynamic Color Coding
Cyan gradient: Price below ALMA (bullish zone)
Magenta gradient: Price above ALMA (bearish zone)
The ALMA line itself changes color based on price position
Trend Regime Detection
The indicator automatically identifies market regimes:
Strong Uptrend: Trend strength > 0.5% with price above ALMA
Strong Downtrend: Trend strength < -0.5% with price below ALMA
Weak trends and ranging conditions
📈 Trading Strategies
Mean Reversion Strategy
Look for price entering the extreme Gaussian zones (beyond 95% of envelope width) when trend strength is moderate. These represent statistical extremes where mean reversion is probable.
Signals:
Long: Price in lower Gaussian zone with trend strength > -0.5%
Short: Price in upper Gaussian zone with trend strength < 0.5%
Trend Continuation Strategy
Enter when price crosses the ALMA during confirmed strong trend conditions, riding momentum while using the envelope as a trailing stop reference.
Signals:
Long: Price crosses above ALMA during strong uptrend
Short: Price crosses below ALMA during strong downtrend
🎨 Visualization Guide
The gradient layers create a "probability cloud" around the ALMA:
Darker shades (near ALMA): High probability zone - price tends to stay here
Lighter shades (near envelope edges): Lower probability - potential reversal zones
Price at envelope extremes: Statistical outliers - strongest mean reversion setups
⚙️ Customization Options
ALMA Parameters
Adjust period for different timeframes (lower for day trading, higher for swing trading)
Modify offset to tune responsiveness vs. smoothness
Change sigma to control distribution width
Envelope Configuration
Choose envelope mode based on market characteristics
Adjust multiplier to match instrument volatility
Modify gradient depth for visual preference (5-15 layers)
Signal Enhancement
Momentum Length: Lookback for trend strength calculation
Signal Smoothing: Additional EMA smoothing to reduce noise
🔔 Built-in Alerts
The indicator includes six pre-configured alert conditions:
ALMA Trend Long - Price crosses above ALMA in strong uptrend
ALMA Trend Short - Price crosses below ALMA in strong downtrend
Mean Reversion Long - Price enters lower Gaussian zone
Mean Reversion Short - Price enters upper Gaussian zone
Strong Uptrend Detected - Momentum confirms strong bullish regime
Strong Downtrend Detected - Momentum confirms strong bearish regime
💡 Best Practices
Use on clean, liquid markets with consistent volatility
Combine with volume analysis for confirmation
Adjust envelope multiplier based on backtesting for your specific instrument
Higher timeframes (4H+) generally provide more reliable signals
Use adaptive mode for trending markets, hybrid for mixed conditions
⚠️ Important Notes
This indicator works best in markets with normal price distribution
Extreme news events can invalidate Gaussian assumptions temporarily
Always use proper risk management - no indicator is perfect
Backtest parameters on your specific instrument and timeframe
🔬 Technical Background
The Arnaud Legoux Moving Average was developed to solve the classic dilemma of moving averages: the trade-off between lag and noise. By applying Gaussian distribution weighting, ALMA achieves superior smoothing while maintaining responsiveness to price changes.
The envelope system extends this concept by creating probability zones based on volatility and momentum, effectively mapping where price is "likely" vs "unlikely" to be found based on statistical principles.
Created by AlphaNatt - For educational purposes. Always practice proper risk management. Not financial advice. Always DYOR.
Hello Crypto! Modern Combo Snapshot
Unified long/short analyzer blending EMA structure, SuperTrend, WaveTrend, QQE, and volume pressure.
Background shading flags “watch” and “ready” states; optional long/short modules let you focus on one side.
Alerts fire when every checklist item aligns, while the side-panel table summarizes trend, momentum, liquidity, and overall score in real time.
Indicator → Trend Analysis
Indicator → Momentum Oscillators
Indicator → Volume Indicators
Tags:
cryptocurrency, bitcoin, altcoins, trend-following, momentum, volume, ema, supertrend, intraday, swing-trading, alerts, checklist, trading-strategy, risk-management
Asia & London Session High/Low – EOD Segments (v4.5)What it does
Plots the Asia and London session high & low each day.
When a session ends, its high/low are locked (non-repainting) and drawn as horizontal segments that auto-extend to the end of that same day (no infinite rays).
Optional labels show the exact level at session close.
Toggle whether to keep prior days on the chart or auto-clear them on the first bar of a new day.
Why traders use it
Quickly see overnight liquidity levels that often act as magnets or barriers during the U.S. session.
Map session range extremes for breakout/reversal planning, partials, and invalidation.
Works great alongside VWAP, 8/20/200 MAs, or your NY session tools to build confluence.
How it works
You define the session windows (defaults: Asia 00:00–06:00, London 07:00–11:00).
While a session is active, the script tracks running high/low.
On the bar after the session ends, the level is finalized and drawn; the segment’s right edge updates each bar until EOD, then stops automatically.
Inputs
Session Timezone: “Exchange”, UTC, or a specific region (set this to match your venue).
Asia / London Session: editable HHMM-HHMM windows.
Show Asia / Show London: enable either/both sessions.
Keep history: keep or auto-delete previous days.
Show labels: price labels at session close.
Colors & width: customize high/low colors and line width.
Best practices
Use on intraday timeframes (1–60m).
For equities/futures, set timezone to your exchange (e.g., America/New_York). For FX/crypto, pick what matches your workflow.
Common tweak: London 08:00–12:00 local; Asia 00:00–05:00 or your broker’s definition.
Notes
Non-repainting: levels only print once the session is complete.
Designed to be light and reliable—no boxes, just clean lines and labels.
If you want NY session levels, midlines (50%), anchored stop-time, or alerts on touches, this script can be extended.
For educational use only. Not financial advice.
RVI Divergence Detector with Custom SMA Filter (v6)This script enhances the classic Relative Vigor Index (RVI) by integrating divergence detection with a user-configurable SMA filter applied directly to the RVI oscillator. The goal is to help traders identify high-probability reversal and continuation signals by combining momentum analysis with dynamic baseline filtering.
How it works:
- The RVI measures the conviction behind price moves by comparing closing vs. opening prices relative to the high-low range over a 10-period window.
- Divergences are detected when price makes a new high/low but the RVI does not:
- Regular Bullish: Price makes a lower low, RVI makes a higher low → potential reversal up.
- Hidden Bullish: Price makes a higher low, RVI makes a lower low → trend continuation.
- Inverse logic applies for bearish cases.
- A customizable SMA (default: 14 periods) is plotted on the RVI line. This acts as a dynamic reference to assess whether divergences occur in strong momentum zones (far from SMA) or neutral zones (near SMA), helping filter out weaker signals.
- Users can adjust:
- Pivot lookback range (min/max bars)
- SMA period (1–200)
- Visibility of bullish/bearish and hidden/regular divergences
Why this version adds value:
Unlike basic RVI scripts, this adaptation introduces a configurable trend filter (SMA) and clear visual labeling ("D" for regular, "H" for hidden) with colored lines (green/red) connecting oscillator and price pivots—making divergences instantly recognizable. The logic is optimized for both scalping (short SMA) and swing trading (longer SMA).
Credits:
Based on the original RVI divergence concept by madoqa. This is an open-source adaptation under the Mozilla Public License 2.0. No financial advice. Use at your own risk.
The Vishnu Zone Ver 2 by Dr. Sudhir Khollam## 📜 **The Vishnu Zone — Trade When the Brahma Zone Ends**
**Author:** Dr. Sudhir Khollam (SALSA© Method of Astrology & Market Psychology)
**Category:** Volatility Phase Detection / Bollinger Band Expansion Analysis
---
### 🔶 **Concept Overview**
In the **SALSA© Market Philosophy**, every market phase follows a cosmic rhythm —
* **Brahma Phase** represents *creation and expansion* (high volatility and strong directional movement).
* **Vishnu Phase** represents *maintenance and stability* (where expansion cools down and balanced opportunities appear).
**“The Vishnu Zone”** indicator identifies the exact moments when the **Brahma Phase ends** — signaling that the expansion has completed and the market is likely to enter a more stable, tradable state.
This is a **precision-timing indicator** that helps traders avoid entering at the end of impulsive phases and instead prepare for equilibrium-based trades (mean reversion, range setups, or steady trends).
---
### ⚙️ **How It Works**
The indicator measures **Bollinger Band Width (BBW)** to quantify expansion and contraction in volatility.
1. It calculates the **adaptive expansion threshold** using the average BBW over a rolling lookback period.
2. When the current BBW **drops below** this adaptive threshold **after being above it**, the script marks it as the **end of the Brahma Phase**.
3. This moment is shown visually as:
* 🕉 **“Vishnu” label** above the candle
* A **horizontal dotted line** extending for several bars
Together, these mark a **Vishnu Zone**, where the market transitions from expansion to consolidation — an ideal time for stabilization or entry planning.
---
### 📊 **Inputs & Settings**
| Parameter | Description |
| ---------------------------------- | ------------------------------------------------------------------------------ |
| **Bollinger Band Length** | The number of bars used for SMA and standard deviation (default 20). |
| **Bollinger Multiplier** | Determines the width of Bollinger Bands (default 2.0). |
| **Adaptive Lookback Period** | Rolling window to calculate the mean BBW for dynamic adjustment (default 150). |
| **Expansion Multiplier** | Multiplies the mean BBW to define the expansion threshold (default 1.35). |
| **Horizontal Line Extension Bars** | Number of bars to extend the Vishnu Zone line into the future (default 40). |
| **Show End-of-Brahma Labels?** | Toggle 🕉 labels on/off. |
| **Show Horizontal Lines?** | Toggle Vishnu Zone lines on/off. |
---
### 🔔 **Alerts**
When the **Brahma Phase ends**, the indicator triggers an alert:
> *“Brahma Phase Ends, Vishnu has taken over.”*
This helps traders receive real-time notification of volatility contraction and possible entry zones.
---
### 🧠 **Best Practices**
* Works effectively on **5-minute to 1-hour timeframes** for intraday trading.
* Best paired with **momentum or volume filters** to confirm trend exhaustion.
* Avoid entering during rapid expansion (Brahma phase). Wait for a Vishnu signal to ensure market stabilization.
---
### 🌌 **Philosophical Interpretation (SALSA© Principle)**
Just as Vishnu sustains the universe after Brahma’s creation, the market too enters a **maintenance phase** after every burst of expansion.
Recognizing this shift allows traders to align with **cosmic rhythm and price psychology**, not just technical metrics.
---
### 🧩 **Summary**
✅ Detects when expansion volatility ends
✅ Marks transition zones between impulsive and stable phases
✅ Sends real-time alerts
✅ Adaptive and self-adjusting across markets and assets
✅ Simple, clean visualization — ideal for disciplined trading
---
### ⚡ **Use Case**
Perfect for traders who:
* Prefer **low-risk entries** after volatility spikes
* Trade **mean reversion**, **range breakouts**, or **volatility collapses**
* Believe in the **cyclic nature of market energy**
---
Modern Combo Crypto SuiteBlends long and short playbooks in one overlay with quick toggles.
Tracks EMA stacks, SuperTrend, WaveTrend, QQE, and volume to score bias.
Colors the chart background when watch/ready conditions align.
Fires alerts for imminent or fully aligned long/short setups.
Displays a live checklist table summarizing trend, momentum, and volume confidence.
ADR + MOVE BoxADR + Move 20 day average Box for any ticker. Calculates the average daily range as well as the absolute delta from open to close. For Full day as well as NY session only
Previous day high lowThis script Identifies and draw Previous day High low on 15 min Intra day chart
RSI Divergence Strategy v6 What this does
Detects regular and hidden divergences between price and RSI using confirmed RSI pivots. Adds RSI@pivot entry gates, a normalized strength + volume filter, optional volume gate, delayed entries, and transparent risk management with rigid SL and activatable trailing. Visuals are throttled for clarity and include a gap-free horizontal RSI gradient.
How it works (simple)
🧮 RSI is calculated on your selected source/period.
📌 RSI pivots are confirmed with left/right lookbacks (lbL/lbR). A pivot becomes final only after lbR bars; before that, it can move (expected).
🔎 The latest confirmed pivot is compared against the previous confirmed pivot within your bar window:
• Regular Bullish = price lower low + RSI higher low
• Hidden Bullish = price higher low + RSI lower low
• Regular Bearish = price higher high + RSI lower high
• Hidden Bearish = price lower high + RSI higher high
💪 Each divergence gets a strength score that multiplies price % change, RSI change, and a volume ratio (Volume SMA / Baseline Volume SMA).
• Set Min divergence strength to filter tiny/noisy signals.
• Turn on the volume gate to require volume ratio ≥ your threshold (e.g., 1.0).
🎯 RSI@pivot gating:
• Longs only if RSI at the bullish pivot ≤ 30 (default).
• Shorts only if RSI at the bearish pivot ≥ 70 (default).
⏱ Entry timing:
• Immediate: on divergence confirm (delay = 0).
• Delayed: after N bars if RSI is still valid.
• RSI-only mode: ignore divergences; use RSI thresholds only.
🛡 Risk:
• Rigid SL is placed from average entry.
• Trailing activates only after unrealized gain ≥ threshold; it re-anchors on new highs (long) or new lows (short).
What’s NEW here (vs. the reference) — and why you may care
• Improved pivots + bar window → fewer early/misaligned signals; cleaner drawings.
• RSI@pivot gates → entries aligned with true oversold/overbought at the exact decision bar.
• Normalized strength + volume gate → ignore weak or low-volume divergences.
• Delayed entries → require the signal to persist N bars if you want more confirmation.
• Rigid SL + activatable trailing → trailing engages only after a cushion, so it’s less noisy.
• Clutter control + gradient → readable chart with a smooth RSI band look.
Suggested starting values (clear ranges)
• RSI@pivot thresholds: LONG ≤ 30 (oversold), SHORT ≥ 70 (overbought).
• Min divergence strength:
0.0 = off
3–6 = moderate filter
7–12 = strict filter for noisy LTFs
• Volume gate (ratio):
1.0 = at least baseline volume
1.2–1.5 = strong-volume only (fewer but cleaner signals)
• Pivot lookbacks:
lbL 1–2, lbR 3–4 (raise lbR to confirm later and reduce noise)
• Bar window (between pivots):
Min 5–10, Max 30–60 (increase Min if you see micro-pivots; increase Max for wider structures)
• Risk:
Rigid SL 2–5% on liquid majors; 5–10% on higher-volatility symbols
Trailing activation 1–3%, trailing 0.5–1.5% are common intraday starts
Plain-text examples
• BTCUSDT 1h → RSI 9, lbL 1, lbR 3, Min strength 5.0, Volume gate 1.0, SL 4.5%, Trail on 2.0%, Trail 1.0%.
• SPY 15m → RSI 8, lbL 1, lbR 3, Min strength 7.0, Volume gate 1.2, SL 3.0%, Trail on 1.5%, Trail 0.8%.
• EURUSD 4h → RSI 14, lbL 2, lbR 4, Min strength 4.0, Volume gate 1.0, SL 2.5%, Trail on 1.0%, Trail 0.5%.
Notes & limitations
• Pivot confirmation means the newest candidate pivot can move until lbR confirms it (expected).
• Results vary by timeframe/symbol/settings; always forward-test.
• Educational tool — no performance or profit claims.
Credits
• RSI by J. Welles Wilder Jr. (1978).
• Reference divergence script by eemani123:
• This version by tagstrading 2025 adds: improved pivot engine, RSI@pivot gating, normalized strength + optional volume gate, delayed entries, rigid SL and activatable trailing, and a gap-free RSI gradient.
Multi-Timeframe Support & ResistanceThis indicator automatically plots dynamic support and resistance levels across multiple timeframes — including 1H, 4H, 1D, 1W, 1M, and the current chart timeframe. Each level is color-coded for clarity and extends across the chart to highlight key price zones.
**Key Features:**
- ⏱ Multi-timeframe analysis: 6 configurable timeframes
- 🎨 Custom color and style settings for each timeframe
- 📏 Adjustable number of levels per timeframe
- 🧼 Clean chart layout with no duplicate lines
- 🔄 Auto-refresh every 10 bars for up-to-date levels
Support and resistance levels are calculated using historical high/low ranges and evenly distributed across the selected lookback period. This helps traders identify confluence zones, breakout targets, and reversal areas with precision.
Earnings Day - Price Predictor [DunesIsland]It's designed to analyze and visualize historical stock price movements on earnings report days, focusing on percentage changes.
Here's a breakdown of what it does, step by step:
Key Inputs and Setup
User Input: There's a single input for "Lookback Years" (default: 10), which determines how far back in time (approximately) the indicator analyzes earnings data. It uses a rough calculation of milliseconds in that period to filter historical data.
Data Fetching: It uses TradingView's request.earnings function to pull actual earnings per share (EPS) data for the current ticker. Earnings days are identified where EPS data exists on a bar but not on the previous one (to avoid duplicates).
Price Change Calculation: For each detected earnings day, it computes the percentage price movement as (close - close ) / close * 100, representing the change from the previous close to the current close on that day.
Processing and Calculations (on the Last Bar)
Lookback Filter: It calculates a cutoff timestamp for the lookback period and processes only earnings events within that window.
Overall Averages:
Separates positive (≥0%) and negative (<0%) percentage changes.
Seasonality (Next Quarter Prediction):
Identifies the most recent earnings quarter (latest_q).
Predicts the "next" quarter (e.g., if latest is Q4, next is Q1;
Again, separates positive and negative changes, computing their respective averages.
Visual Outputs
Lookback: How far to fetch the data in years.
Average Change (Green): Showing the average of all positive changes.
Average Change (Red): Showing the average of all negative changes.
Seasonality Change (Green): Showing the average of positive changes for the predicted next quarter.
Seasonality Change (Red): Showing the average of negative changes for the predicted next quarter.
Purpose and Usage
This indicator helps traders assess a stock's historical reaction to earnings announcements. The overall averages give a broad sense of typical gains/losses, while the seasonality focuses on quarter-specific trends to "predict" potential movement for the upcoming earnings (based on past same-quarter performance). It's best used on daily charts for stocks with reliable earnings data. Note that quarter inference is calendar-based and may not perfectly match fiscal calendars for all companies—it's an approximation.
RSI to Price Projection PanelThis indicator calculates the current RSI based on the closing price and projects estimated prices for user-defined RSI target levels. Results are displayed in a table at the top-right corner of the chart.
Advanced HMM - 3 States CompleteHidden Markov Model
Aconsistent challenge for quantitative traders is the frequent behaviour modification of financial
markets, often abruptly, due to changing periods of government policy, regulatory environment
and other macroeconomic effects. Such periods are known as market regimes. Detecting such
changes is a common, albeit difficult, process undertaken by quantitative market participants.
These various regimes lead to adjustments of asset returns via shifts in their means, variances,
autocorrelation and covariances. This impacts the effectiveness of time series methods that rely
on stationarity. In particular it can lead to dynamically-varying correlation, excess kurtosis ("fat
tails"), heteroskedasticity (volatility clustering) and skewed returns.
There is a clear need to effectively detect these regimes. This aids optimal deployment of
quantitative trading strategies and tuning the parameters within them. The modeling task then
becomes an attempt to identify when a new regime has occurred adjusting strategy deployment,
risk management and position sizing criteria accordingly.
A principal method for carrying out regime detection is to use a statistical time series tech
nique known as a Hidden Markov Model . These models are well-suited to the task since they
involve inference on "hidden" generative processes via "noisy" indirect observations correlated
to these processes. In this instance the hidden, or latent, process is the underlying regime state,
while the asset returns are the indirect noisy observations that are influenced by these states.
MAIN FEATURES OF THE INDICATOR
The "Advanced HMM - 3 States Complete" indicator is an advanced technical analysis tool that uses Hidden Markov Model (HMM) to identify three main market regimes: BULL, BEAR, and SIDEWAYS.
🎯 KEY FEATURES:
1. HMM-based Trend Detection
3 market states: Bull (0), Bear (1), Sideways (2)
Dynamic probabilities: Calculates probability for each state based on price data
Transition matrix: Models state transitions between regimes
2. Analytical Features
Price volatility: Log returns and standard deviation
Momentum: Rate of Change (ROC)
Volume: Volume ratio vs moving average
Data normalization: Standardizes features to common scale
3. Visual Trading Signals
text
📍 BUY Signals:
- Green upward triangle below bars
- "LONG" label in green
📍 SELL Signals:
- Red downward triangle above bars
- "SHORT" label in red
📍 EXIT Signals:
- Orange X marks when transitioning to sideways
4. Information Display
Probability table (top-right): Shows percentage for each state
State label: Current regime with probability percentages
Chart background color: Reflects dominant market state
5. Automated Alerts
Alerts when new Bull/Bear market detected
Alerts when market transitions to sideways
Configurable TradingView notifications
6. Customizable Parameters
pinescript
length: 100 // Lookback period
smoothing_period: 20 // Probability smoothing
volatility_threshold: 0.5 // Volatility threshold
💡 PRACTICAL APPLICATIONS:
Identify primary trends with quantified probabilities
Entry/exit signals based on state transitions
Risk management during sideways markets
Trend confirmation when combined with other indicators
This indicator is particularly useful for market regime analysis and identifying trend transition points using advanced statistical probability methods.
🔧 TECHNICAL IMPLEMENTATION:
Composite observation: Weighted combination of returns (40%), momentum (30%), and volatility (30%)
Gaussian emission probabilities: Different distributions for each state
Manual HMM updates: Avoids matrix computation limitations in Pine Script
Real-time smoothing: EMA applied to state probabilities
The indicator provides institutional-grade regime detection in a visually intuitive package suitable for both discretionary and systematic traders.
LANZ Origins🔷 LANZ Origins – Multi-Framework Liquidity, Structure & Risk Management Overlay
LANZ Origins is an advanced multi-framework visualization toolkit that unifies key institutional concepts into one efficient interface. Designed for professional traders, it merges session mapping, liquidity analysis, imbalance detection, multi-account risk control, and higher-timeframe candle tracing — all in a single overlay.
🧩 Core Components
🈵 Asian Range Liquidity
Automatically detects and projects the Asian session range (19:00–02:00 NY) with an optional mid-price line (50 %). This provides visual context for intraday liquidity and manipulation zones commonly referenced in ICT-style analysis.
📊 Imbalance Detector
Highlights Fair Value Gaps (FVG), Opening Gaps (OG), and Volume Imbalances (VI) directly on-chart, using separate color schemes for bullish and bearish inefficiencies. Each element can be customized by width, ATR filter, and extension length.
🕯️ Higher-Timeframe Candles (ICT Style)
Displays multi-timeframe candles (HTF1–HTF6) simultaneously — e.g., 5 m, 30 m, 1 h, 4 h, 1 D, 1 W — each rendered with independent wick, border, and fill settings. Includes remaining-time counters, timeframe labels, and optional imbalance shading between bodies.
📈 Market Structure (ZigZag 30 m)
Replicates 30-minute swing structure to all active timeframes, producing dynamic pivots with live extension. Ideal for contextualizing BOS/CHoCH events across multiple scales.
💸 Multi-Account Lot Size Panel
Calculates position size for up to five accounts simultaneously, using your defined capital, risk %, and fixed SL distance (in pips). Results appear in a clean table at the bottom-right corner of the chart.
🎨 Session Visualization
Colored backgrounds mark key trading phases:
🟢 Day division
🔴 No-action zone
🔵 Kill-zone
🟡 Hold session
⚙️ Customization & Performance
Every module can be toggled individually, with full color, opacity, and style control. The script is optimized for overlay use and supports up to 500 boxes, lines, and labels with efficient resource handling.
🧠 Best Use Case
LANZ Origins is ideal for traders who follow:
Smart Money Concepts / ICT methodology
Liquidity & Imbalance-based trading
Multi-timeframe confluence setups
Risk-based position sizing workflows
Use it to observe how price interacts with liquidity pools, higher-timeframe candles, and imbalances within key sessions — while monitoring lot size risk in real time.
📌 Recommended Setup
Timeframes: 30m - 5m – 3m
Pairs: FX
Session Timezone: New York (EST/EDT)
Combine with: LANZ Strategy series for execution and journaling
💬 Note
This indicator does not generate buy/sell signals. It’s a visual and analytical tool built to support your own decision-making process.
Metallic Retracement ToolI made a version of the Metallic Retracement script where instead of using automatic zig-zag detection, you get to place the points manually. When you add it to the chart, it prompts you to click on two points. These two points become your swing range, and the indicator calculates all the metallic retracement levels from there and plots them on your chart. You can drag the points around afterwards to adjust the range, or just add the indicator to the chart again to place a completely new set of points.
The mathematical foundation is identical to the original Metallic Retracement indicator. You're still working with metallic means, which are the sequence of constants that generalize the golden ratio through the equation x² = kx + 1. When k equals 1, you get the golden ratio. When k equals 2, you get silver. Bronze is 3, and so on forever. Each metallic number generates its own set of retracement ratios by raising alpha to various negative powers, where alpha equals (k + sqrt(k² + 4)) / 2. The script algorithmically calculates these levels instead of hardcoding them, which means you can pick any metallic number you want and instantly get its complete retracement sequence.
What's different here is the control. Automatic zig-zag detection is useful when you want the indicator to find swings for you, but sometimes you have a specific price range in mind that doesn't line up with what the zig-zag algorithm considers significant. Maybe you're analyzing a move that's still developing and hasn't triggered the zig-zag's reversal thresholds yet. Maybe you want to measure retracements from an arbitrary high to an arbitrary low that happened weeks apart with tons of noise in between. Manual placement lets you define exactly which two points matter for your analysis without fighting with sensitivity settings or waiting for confirmation.
The interactive placement system uses TradingView's built-in drawing tools, so clicking the two points feels natural and works the same way as drawing a trendline or fibonacci retracement. First click sets your starting point, second click sets your ending point, and the indicator immediately calculates the range and draws all the metallic levels extending from whichever point you chose as the origin. If you picked a swing low and then a swing high, you get retracement levels projecting upward. If you went from high to low, they project downward.
Moving the points after placement is as simple as grabbing one of them and dragging it to a new location. The retracement levels recalculate in real-time as you move the anchor points, which makes it easy to experiment with different range definitions and see how the levels shift. This is particularly useful when you're trying to figure out which swing points produce retracement levels that line up with other technical features like previous support or resistance zones. You can slide the points around until you find a configuration that makes sense for your analysis.
Adding the indicator to the chart multiple times lets you compare different metallic means on the same price range, or analyze multiple ranges simultaneously with different metallic numbers. You could have golden ratio retracements on one major swing and silver ratio retracements on a smaller correction within that swing. Since each instance of the indicator is independent, you can mix and match metallic numbers and ranges however you want without one interfering with the other.
The settings work the same way as the original script. You select which metallic number to use, control how many power ratios to display above and below the 1.0 level, and adjust how many complete retracement cycles you want drawn. The levels extend from your manually placed swing points just like they would from automatically detected pivots, showing you where price might react based on whichever metallic mean you've selected.
What this version emphasizes is that retracement analysis is subjective in terms of which swing points you consider significant. Automatic detection algorithms make assumptions about what constitutes a meaningful reversal, but those assumptions don't always match your interpretation of the price action. By giving you manual control over point placement, this tool lets you apply metallic retracement concepts to exactly the price ranges you care about, without requiring those ranges to fit someone else's definition of a valid swing. You define the context, the indicator provides the mathematical framework.
DCA Percent SignalOverview
The DCA Percent Signal Indicator generates buy and sell signals based on percentage drops from all-time highs and percentage gains from lowest lows since ATH. This indicator is designed for pyramiding strategies where each signal represents a configurable percentage of equity allocation.
Definitions
DCA (Dollar-Cost Averaging): An investment strategy where you invest a fixed amount at regular intervals, regardless of price fluctuations. This indicator generates signals for a DCA-style pyramiding approach.
Gann Bar Types: Classification system for price bars based on their relationship to the previous bar:
Up Bar: High > previous high AND low ≥ previous low
Down Bar: High ≤ previous high AND low < previous low
Inside Bar: High ≤ previous high AND low ≥ previous low
Outside Bar: High > previous high AND low < previous low
ATH (All-Time High): The highest price level reached during the entire chart period
ATL (All-Time Low): The lowest price level reached since the most recent ATH
Pyramiding: A trading strategy that adds to positions on favorable price movements
Look-Ahead Bias: Using future information that wouldn't be available in real-time trading
Default Properties
Signal Thresholds:
Buy Threshold: 10% (triggers every 10% drop from ATH)
Sell Threshold: 30% (triggers every 30% gain from lowest low since ATH)
Price Sources:
ATH Tracking: High (ATH detection)
ATL Tracking: Low (low detection)
Buy Signal Source: Low (buy signals)
Sell Signal Source: High (sell signals)
Filter Options:
Apply Gann Filter: False (disabled by default)
Buy Sets ATL: False (disabled by default)
Display Options:
Show Buy/Sell Signals: True
Show Reference Lines: True
Show Info Table: False
Show Bar Type: False
How It Works
Buy Signals: Trigger every 10% drop from the all-time highest price reached
Sell Signals: Trigger every 30% increase from the lowest low since the most recent all-time high
Smart Tracking: Uses configurable price sources for signal generation
Key Features
Configurable Thresholds: Adjustable buy/sell percentage thresholds (default: 10%/30%)
Separate Price Sources: Independent sources for ATH tracking, ATL tracking, and signal triggers
Configurable Signals: Uses low for buy signals and high for sell signals by default
Optional Gann Filter: Apply Gann bar analysis for additional signal filtering
Optional Buy Sets ATL: Option to set ATL reference point when buy signals occur
Visual Debug: Detailed labels showing signal parameters and values
Usage Instructions
Apply to Chart: Use on any timeframe (recommended: 1D or higher for better signal quality)
Risk Management: Adjust thresholds based on your risk tolerance and market volatility
Signal Analysis: Monitor debug labels for detailed signal information and validation
Signal Logic
Buy signals are blocked when ATH increases to prevent buying at peaks
Sell signals are blocked when ATL decreases to prevent selling at lows
This ensures signals only trigger on subsequent bars, not the same bar that establishes new reference points
Buy Signals:
Calculate drop percentage from ATH to buy signal source
Trigger when drop reaches threshold increments (10%, 20%, 30%, etc.)
Always blocked on ATH bars to prevent buying at peaks
Optional: Also blocked on up/outside bars when Gann filter enabled
Sell Signals:
Calculate gain percentage from lowest low to sell signal source
Trigger when gain reaches threshold increments (30%, 60%, 90%, etc.)
Always blocked when ATL decreases to prevent selling at lows
Optional: Also blocked on down bars when Gann filter enabled
Limitations
Designed for trending markets; may generate many signals in sideways/ranging markets
Requires sufficient price movement to be effective
Not suitable for scalping or very short timeframes
Implementation Notes
Signals use optimistic price sources (low for buys, high for sells), these can be configured to be more conservative
Gann filter provides additional signal filtering based on bar types
Debug information available in data window for real-time analysis
Detailed labels on each signal show ATH, lowest low, buy level, sell level, and drop/gain percentages
Scalp BTC/ETH — Reversal & Continuation (v1, Pine v6)Scalp BTC/ETH — Reversal & Continuation (1m à 10m)
Cet indicateur détecte des opportunités de micro-scalping sur futures (BTC/ETH) basées sur deux mécaniques courtes validées par structure de prix :
A) Reversal de pression (contre-mouvement contrôlé)
Détection d’une sur-extension brutale suivie d’une absorption sur la bougie suivante.
Objectif : capturer la première respiration après un excès de prix (rejet court).
B) Continuation courte (momentum + reprise)
Détection de 3 bougies directionnelles consécutives suivies d’un pullback léger, puis signal sur la reprise du mouvement initial.
Gestion intégrée (scénario standard TP dynamique)
TP1 → 50% de la position à un gain fixe (% adaptable au timeframe)
Stop déplacé au Break-Even sur le restant
Sortie finale sur bougie inverse significative
(correction ≥ X% du corps précédent) ou timeout (max bars en trade)
Scalp BTC/ETH — Reversal & Continuation (1m to 10m)
This indicator detects short-term futures scalping setups on BTC & ETH using two mechanical price-action models designed for fast execution:
A) Reversal Compression (counter-move entry)
Identifies a sharp impulse (overextension) followed by absorption / failure to extend on the next candle.
Objective: capture the first corrective pullback after exhaustion.
B) Controlled Continuation (momentum follow-through)
Identifies 3 consecutive trend candles, then a shallow pullback, and triggers an entry on the resumption of the main leg.
Built-in trade logic (dynamic TP structure)
TP1 → scale out 50% of the position at a fixed percentage (auto-scaled per timeframe)
Stop moved to Break-Even after TP1
Final exit on either:
• a meaningful opposite candle (≥ X% correction of prior body), or
• a timeout (max bars in trade)
Technical characteristics
Designed for 1m / 3m / 5m / 7m / 10m
No repainting (bar-close confirmed logic)
Works for both LONG & SHORT
Built-in alert events:
ENTRY_LONG / ENTRY_SHORT / TP1 / EXIT_STOP / EXIT_INVERSE / EXIT_TIMEOUT
Suitable for manual execution, semi-automation (alerts) or full bot integration (webhook JSON)
Purpose
Provide a repeatable, rule-based, non-subjective framework to harvest micro-moves with controlled risk, without relying on lagging indicators or long-term prediction.
(A Strategy / backtesting version is planned as a next iteration.)
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy
Summary
Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts.
Scope and intent
• Markets: large cap equities and ETFs, index futures, major FX, liquid crypto
• Timeframes: one minute to daily
• Default demo: BTC on 60 minute
• Purpose: faster yet calmer PSAR that resists chop and improves short discipline
• Limits: this is a strategy that places simulated orders on standard candles
Originality and usefulness
• Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias
• Addresses false flips in low volatility and weak downtrends
• All controls are exposed in Inputs for testability
• Yardstick: ATR normalizes drift so settings port across symbols
• Open source. No links. No solicitation
Method overview
Components
• Adaptive AF: base step plus boost factor times logistic strength
• Trail inertia: one sided blend that keeps the SAR monotone
• Flip hysteresis: price must clear SAR by a buffer times ATR
• Volatility gate: ATR over its mean must exceed a ratio
• Bear bias for shorts: price below EMA of length 91 with negative slope window 54
• Cooldown bars optional after any entry
• Visual SAR smoothing is cosmetic and does not drive orders
Fusion rule
Entry requires the internal flip plus all enabled gates. No weighted scores.
Signal rule
• Long when trend flips up and close is above SAR plus buffer times ATR and gates pass
• Short when trend flips down and close is below SAR minus buffer times ATR and gates pass
• Exit uses SAR as stop and optional ATR take profit per side
Inputs with guidance
Reactor Engine
• Start AF 0.02. Lower slows new trends. Higher reacts quicker
• Max AF 1. Typical 0.2 to 1. Caps acceleration
• Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends
• Strength window 18. Typical 10 to 40. Drift estimation window
• ATR length 16. Typical 10 to 30. Volatility unit
• Strength gain 4.5. Typical 2 to 6. Steepness of logistic
• Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic
• Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises
• AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth
• Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail
• Allow Long, Allow Short toggles
Trade Filters
• Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips
• Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars
• Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes
• Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness
Risk
• TP long ATR 1.0. Set to zero to disable
• TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts
Usage recipes
Intraday trend focus
Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime.
Intraday mean reversion focus
Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated.
Swing continuation
Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts.
Properties visible in this publication
Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles.
Honest limitations and failure modes
High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips.
Open source reuse and credits
Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors.
Strategy notice
Orders are simulated on standard candles. No lookahead.
Entries and exits
Long: flip up plus ATR buffer and all gates true
Short: flip down plus ATR buffer and gates true with bear bias when enabled
Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry
Tie handling: stop first if both stop and target could fill in one bar
