Dimagi72 Trend Suite (EMA/SMA + 52W + Cross Signals)Dimagi72 Trend Suite is an advanced trend analysis tool designed to give traders a clear picture of market direction, momentum, and major structural turning points.
It combines the most reliable long-term and short-term signals into one clean, easy-to-read indicator.
Features
• EMA9 & EMA21 for short-term momentum
• SMA50, SMA100, SMA200 for medium & long-term trend structure
• 52-Week High & Low levels for institutional support/resistance
• Golden Cross / Death Cross signals (SMA50 vs SMA200)
• Trend Strength Meter, shown directly on the chart
• Clean labels without clutter
• Designed for crypto, stocks, and forex on all timeframes (best on Daily)
How it works
The indicator measures alignment between EMAs and SMAs, tracks long-term institutional levels, and highlights major trend reversals through cross signals.
The Trend Strength Meter calculates a score from -4 to +4, making trend direction instantly visible.
Why use this indicator
This suite brings together the most widely used trend-following tools into one unified system.
It helps traders quickly determine when the market is bullish, bearish, or neutral — and when major reversals may be forming.
Best for:
Swing traders, long-term trend followers, crypto traders, and anyone who wants a clean visual overview of the trend without using multiple separate indicators.
Tags (use these to show up in search)
trend
ema
sma
trend-following
golden cross
death cross
momentum
trend strength
52 week high
crypto
stocks
market structure
Поиск скриптов по запросу "乌德勒支+VS+赫拉克勒斯"
MAHI Indicator v9.5 - Smart Momentum HUD + IntradayMAHI Indicator v9.5 — Smart Momentum HUD (Multi-Framework + Intraday Engine)
A Complete Momentum, Trend, and Setup Framework for Swing, Position & Intraday Traders
MAHI v9.5 is the most advanced version yet — a highly optimized, visual, multi-framework trading system that blends momentum, trend alignment, adaptive setup detection, and now Auto-Intraday Mode for short-term traders.
This indicator acts like a Heads-Up Display (HUD) on your chart: it shows trend strength, squeeze zones, dynamic support/resistance, EMAs, setup validation, and early reversal signals in one clean interface — without clutter.
✔ Core Features
📌 1. Smart Momentum Ribbon
A dynamic EMA-based momentum band that visually shifts as trend strength changes.
Helps identify strong vs. weak momentum zones
Adapts to volatility & trend slope
Works on all timeframes (1m to 1M)
📌 2. EMA 9 → 21 Flip System
A precision trend-switching signal:
EMA 9 → 21 BULL = early bullish momentum
EMA 9 → 21 BEAR = early bearish momentum
More reliable than stand-alone MA crossovers
📌 3. Bullish Setup Engine (Standard + Weak)
Automatically identifies when price is entering a reversal-ready state based on:
Position relative to the ribbon
Candle structure
Momentum compression
Slope + exhaustion conditions
Includes:
Bull Setup (Standard) — Higher probability setup
Bull Setup (Weak) — Early or less developed setup
Setup Invalidated — Confirms that the pattern failed
This prevents false confidence & keeps traders disciplined.
📌 4. Strong Buy / Strong Sell Signals
Only appear when multiple confirmations align:
Ribbon bias
EMA slope
Momentum compression
Trend alignment
Filtered to remove noise — especially in lower timeframes.
📌 5. Multi-Timeframe Trend HUD
Top-right panel summarizing:
Overall Trend (Bullish, Bearish, Neutral)
RSI Condition
Daily vs Weekly Alignment
Trading Mode Suggestions (Buy / Sell / LEAPS / Neutral)
This gives instant context.
📌 6. Auto Intraday Engine (NEW in v9.5)
Automatically switches internal logic when you move into intraday timeframes (1m–30m):
Intraday Enhancements:
Adaptive setup detection
Faster momentum sensitivity
EMAs tuned for scalp/swing precision
Tighter invalidation logic
Reduced false positives
Optional strict filtering
Perfect for scalping, day trading & micro-trends
Works instantly — no settings needed.
Just change the chart timeframe and MAHI adjusts.
📌 7. Dynamic High-Timeframe Support (W & M)
Auto-layers weekly & monthly levels:
Helps identify strong bounce zones
Extremely useful for swing & LEAPS traders
📌 8. Weekly Volume Shelf Projection
Lightweight VWAP-style level based on weekly volume aggregation.
Shows probable bottoming areas during pullbacks.
✔ Who This Indicator Is For
Perfect for:
Day traders
Swing traders
Momentum riders
LEAPS & long-term investors
Beginner traders needing a structured system
MAHI adapts to your timeframe and trading style.
✔ Why MAHI Works
MAHI isn’t a single-signal indicator — it’s a framework.
It combines:
Trend
Momentum
Volatility
Setup pattern detection
Validation & invalidation
Multi-timeframe alignment
Dynamic zones
Intraday optimization
This eliminates guesswork and helps traders avoid the emotional traps that cause most losses.
You don’t just get a signal — you get context.
✔ How to Use It
Follow the ribbon bias
Use EMA 9→21 flips as trend confirmation
Look for Bull Setup tags during pullbacks
Avoid trades when you see Setup Invalidated
Respect weekly/monthly HTF support levels
On intraday charts — rely on auto-optimized mode
For swing entries, combine setups with HTF trend HUD
MAHI gives the map. You choose the path.
✔ Final Notes
This version is heavily optimized for performance, clarity, and high-probability signals.
MAHI does not repaint, and works on all assets including:
Stocks
Crypto
ETFs
Forex
Futures
Abacus Community Williams %R + Bollinger %B📌 Indicator Description (Professional & Clear)
Williams %R + Bollinger %B Momentum Indicator (ThinkOrSwim Style)
This custom indicator combines Williams %R and Bollinger %B into a single, unified panel to provide a powerful momentum-and-positioning view of price action. Modeled after the ThinkOrSwim version used by professional traders, it displays:
✅ Williams %R (10-period) – Yellow Line
This oscillator measures the market's position relative to recent highs and lows.
It plots on a 0% to 100% scale, where:
80–100% → Overbought region
20–0% → Oversold region
50% → Momentum equilibrium
Williams %R helps identify exhaustion, trend strength, and potential reversal zones.
✅ Bollinger %B (20, 2.0) – Turquoise Histogram Bars
%B shows where price is trading relative to the Bollinger Bands:
Above 50% → Price is in the upper half of the band (bullish pressure)
Below 50% → Price is in the lower half (bearish pressure)
Near 100% → Price pushing upper band (possible breakout)
Near 0% → Price testing lower band (possible breakdown)
The histogram visually represents momentum shifts in real time, creating a clean profile of volatility and strength.
🎯 Why This Combination Works
Together, Williams %R and Bollinger %B reveal:
Momentum direction
Overbought/oversold conditions
Volatility compression & expansion
Trend continuation vs reversal zones
High-probability inflection points
Williams %R shows oscillation and exhaustion, while %B shows pressure inside volatility bands.
The combination helps identify whether momentum supports the current trend or is weakening.
🔍 Use Cases
Detect early trend reversals
Validate breakouts and breakdowns
Spot momentum failure in price extremes
Confirm pullbacks and continuation setups
Time entries and exits with higher precision
💡 Best For
Swing traders
Momentum traders
Trend-followers
Options traders (for timing premium decay or volatility expansion)
Triple 9 Bias filter Triple 9 Bias – Precision Multi-Timeframe Directional Filter
Technical Overview
The Triple 9 Bias is a precision multi-timeframe directional filter built exclusively for 5-minute (and lower) trading.
It stacks three EMA-9 trend directions (4H + 1H + 15m) as Primary confluence and uses only the 4H RSI-14 as Secondary confirmation.
Integrity Check: Zero repaint · Zero lookahead · Works identically on any chart timeframe.
The Trading Rule (Simple)
Long Trades: Only trade longs when all three EMA-9s are UP + 4H RSI > 50
Short Trades: Only trade shorts when all three EMA-9s are DOWN + 4H RSI < 50
Otherwise — stand aside.
Display Components
A. Plotted Higher-Timeframe EMAs (No Repainting)
All values are pulled from closed higher-timeframe bars.
4H EMA 9 (Red step-line)
1H EMA 9 (Purple step-line)
15m EMA 9 (Orange step-line)
B. Locked Dashboard (Bottom-Right)
Clean table split into Primary and Secondary sections for instant bias reading.
Colour Logic:
🟢 Lime = UP / BUY
🔴 Red = DOWN / SELL
Background Logic:
Full Green: Only when all three EMA-9s are UP
Full Red: Only when all three EMA-9s are DOWN
Gray: Otherwise = no trade
Indicator Breakdown
3.1. Primary Confluence – EMA 9 Slope
4H EMA 9 direction (compared 10 bars back)
1H EMA 9 direction (compared 6 bars back)
15m EMA 9 direction (compared 6 bars back)
3.2. Secondary Confluence
4H RSI-14 vs 50 level (BUY if >50, SELL if <50)
High-Probability Signal: When Primary = all three “UP” and Secondary = “BUY” → highest-probability bullish bias (and vice-versa for bearish).
Distância Preço vs VWAPIt calculates the distance from the price to the VWAP. The idea is to make it easier to observe when the price might return to the VWAP.
XAUUSD Multi-Timeframe Bias Scanner🎯 Purpose & Overview
This is a sophisticated trading indicator that analyzes XAUUSD (Gold) across 5 different timeframes simultaneously to determine market bias and trend direction.
⚙️ Core Components
2. Bias Calculation Engine
The heart of the indicator uses 5 technical factors to score each timeframe:
Technical Factors (Weighted):
Moving Average Alignment (30 points)
Bullish: EMA(9) > EMA(21) > EMA(50)
Bearish: EMA(9) < EMA(21) < EMA(50)
Price vs MA Position (20 points)
Score increases when price above MAs
Score decreases when price below MAs
RSI Momentum (20 points)
Bullish: RSI > 60 or > 50
Bearish: RSI < 40 or < 50
MACD Signals (15 points)
Bullish: MACD line > Signal line AND > 0
Bearish: MACD line < Signal line AND < 0
Volume Confirmation (15 points)
Volume spikes with price movement add confirmation
📊 Timeframe Analysis
Five Timeframes Monitored:
5-minute - Short-term noise (10% weight)
15-minute - Intraday direction (15% weight)
1-hour - Key intraday bias (25% weight)
4-hour - Primary directional bias (30% weight)
1-day - Overall trend context (20% weight)
Bias Scoring System:
0-100 Scale (50 = Neutral)
STRONG BULLISH: ≥70 (Green)
BULLISH: 55-69 (Lime)
NEUTRAL: 46-54 (Gray)
BEARISH: 31-45 (Orange)
STRONG BEARISH: ≤30 (Red)
🎨 Visual Features
1. Comprehensive Table Display
pinescript
var table biasTable = table.new(position.top_right, 3, 7, ...)
Shows a color-coded table with:
Timeframe name
Numerical bias score (0-100)
Strength description with color coding
2. Chart Visual Indicators
Background coloring based on overall bias
Label markers for strong bullish/bearish conditions
Real-time label showing all timeframe scores
3. Alert System
Triggers when overall bias crosses 70 (bullish) or 30 (bearish)
Configurable with sound options
🔄 How It Processes Data
Data Flow:
Requests security data for each timeframe using request.security()
Calculates technical indicators for each TF separately
Scores each TF based on 5 technical factors
Computes weighted overall bias
Updates visual displays and checks alert conditions
💡 Trading Applications
Bullish Scenarios:
Multiple timeframes show bullish alignment
Higher timeframe bias supports lower timeframe direction
Overall score > 70 indicates strong bullish conviction
Bearish Scenarios:
Multiple timeframes show bearish alignment
Higher timeframe bias confirms lower timeframe moves
Overall score < 30 indicates strong bearish conviction
Conflict Detection:
When timeframes show conflicting biases
Caution required - market may be consolidating
Wait for alignment before taking trades
🎚️ Customization Options
Users can modify:
Timeframe weights
Technical indicator parameters
Alert thresholds
Visual display preferences
Scoring sensitivity
📈 XAUUSD Specific Optimizations
The indicator considers Gold's unique characteristics:
High volatility periods
ATR-based volatility adjustments
Volume confirmation for breakouts
Multiple timeframe confirmation for trend reliability
This creates a powerful tool for identifying high-probability trade setups in XAUUSD by ensuring traders have a complete multi-timeframe perspective before entering positions.
Scaling_mastery:Free TrendlinesScaling_mastery Trendlines is a clean, trading-ready smart trendline tool built for the Scaling_mastery community.
It automatically finds swing highs/lows and draws dynamic trendlines or channels that stay locked to price, on any symbol and any timeframe.
🔧 Modes
Trendline type
Wicks – classic trendlines anchored on candle wicks (high/low).
Bodies – trendlines anchored on candle bodies (open/close), great for closing structure.
Channel – 3-line channel:
outer lines form a band around price
middle line runs through the centre of the channel
thickness is adjustable (Small / Medium / Large).
Trend strength
Controls how strong the pivots must be to form a line.
Weak → more lines, reacts faster.
Medium → balanced, good for most pairs.
Strong → only the cleanest swings, higher-probability trendlines.
🎨 Visual controls
Max support / resistance lines – cap how many lines are kept on chart.
Show broken lines – hide broken trendlines or keep them for structure history.
Extend lines – None / Right / Both.
Support / Resistance colors – separate colors for active vs broken.
Channel thickness – Small / Medium / Large (0.5% / 1% / 2% of price).
Channel outer lines – color for channel edges.
Channel middle line – color + style (dotted / dashed / solid).
Broken lines are automatically faded + dotted, so you can instantly see what’s still respected and what’s already been taken out.
🧠 How to use
Add the indicator to any chart.
Start with:
Trendline type: Wicks
Trend strength: Strong
Max lines: 1–2 for both support & resistance
Once you like the behavior, experiment with:
Switching between Wicks / Bodies / Channel
Adjusting Channel thickness and Trend strength
Use the lines as a visual confluence tool with your own strategy:
HTF trend direction
LTF entries / retests
Liquidity grabs around broken lines
This script doesn’t generate entries or risk management – it’s designed to give you clean, reliable structure so you can execute your own edge.
⚠️ Disclaimer
This tool is for educational and visual purposes only and is not financial advice.
Always do your own research and manage risk.
BTC GOD — DEFINITIVE BTC MULTI INDICATORBTC GOD — The Ultimate Bitcoin Cycle Indicator (2025 Edition)
The one indicator every serious BTC holder and trader has been waiting for.
A single script that perfectly combines the 5 most powerful and accurate Bitcoin indicators ever created — all 100 % official versions:
- Official Pi Cycle Top (LookIntoBitcoin) → in 2013, 2017 & 2021 (3/3 hits)
- Official MVRV Z-Score (Glassnode / LookIntoBitcoin) → every major bottom (2015, 2018–19, 2022)
- Dynamic Bull/Bear background (red bear-market when price drops X % from cycle ATH + monthly RSI filter)
- Monthly Golden/Death Cross (50-month EMA vs 200-week EMA) → huge, unmistakable signals
- SuperTrend + 200-week EMA + 50-month EMA
- Cycle ATH/ATL tracking with flashing alert in the table when new highs/lows are made
- Exact days to/from the next halving + optimal accumulation zone (200–750 days post-halving)
- Fully customizable inputs for experienced traders
Zero repainting. Zero errors. Works on every timeframe.
This is the indicator used by people who truly understand Bitcoin’s 4-year cycles.
If you could only keep ONE Bitcoin indicator for the rest of your life… this would be it.
Save it, test it, and you’ll instantly see why it’s called BTC GOD.
Built with love and obsession for Bitcoin cycles.
Last update: November 2025
Average True Range % infoATR% is a modified version of the classic Average True Range indicator that displays price volatility as a percentage of the instrument's value, rather than in absolute values. This allows you to easily compare the volatility of different assets (e.g., Bitcoin vs Tesla stock) regardless of their price.
Main Features
1. ATR% Chart
The red line shows the average volatility from the last N candles (default 14), expressed as a percentage. For example:
ATR% = 2.5% means that the average daily move is approximately 2.5% of the asset's value
Higher values = greater volatility (higher profit potential, but also greater risk)
Lower values = lower volatility (calmer market)
2. Volatility Trend Analysis
The indicator automatically detects whether volatility is rising, falling, or stable:
Up arrow (↑) - volatility is rising (price becomes more "nervous")
Down arrow (↓) - volatility is falling (market is calming down)
Horizontal arrow (⮆) - volatility is stable (within ±3% of the moving average)
3. Information Table
In the upper right corner of the chart you will see Current ATR% value and Trend arrow with color coding:
- Green = rising volatility
- Red = falling volatility
- Gray = stable volatility
Parameters to Configure
Indicator Length (default: 14) - How many candles back to include in calculations:
Lower values (5-10): more sensitive to sudden changes, reacts faster
Higher values (20-30): more smoothed, shows long-term volatility picture
Trend Length (default: 10) - Period to analyze whether volatility is rising/falling:
Lower values: faster trend change signals
Higher values: more reliable, but slower signals
Sample Interpretations
ATR% Volatility Asset Type/Situation
< 1% Very low Stable blue-chip stocks, calm market
1-3% Low-medium Typical stocks, normal conditions
3-5% Medium-high Volatile stocks, cryptocurrencies at rest
5-10% High Cryptocurrencies, penny stocks
> 10% Extremely high Market panic, crash, pump & dump
Đại Ka 3 ATR BandsĐại Ka 3 ATR Bands – The ultimate single-slot indicator that replaces three separate ATR plots.
Designed specifically for ICT/SMC traders in 2025:
• Light red band (±0.5 ATR) → fake moves, Judas Swing, Turtle Soup zone
• Gray band (±1.0 ATR) → normal price action
• Light green band (±2.0 ATR) → real displacement zone → Silver Bullet, SFT, high-probability entries
How to use:
– Price stuck inside red band → expect reversal/fakeout
– Price breaks and closes outside green band + volume spike → enter aggressively in that direction (85%+ win-rate inside Killzones)
Default ATR(14), subtle fills for instant visual filtering of real vs fake moves.
Perfect companion for Order Blocks, FVG, Breaker Blocks and NY/London Killzones.
Free forever – coded with love by Đại Ka & Vietnamese ICT crew.
Static K-means Clustering | InvestorUnknownStatic K-Means Clustering is a machine-learning-driven market regime classifier designed for traders who want a data-driven structure instead of subjective indicators or manually drawn zones.
This script performs offline (static) K-means training on your chosen historical window. Using four engineered features:
RSI (Momentum)
CCI (Price deviation / Mean reversion)
CMF (Money flow / Strength)
MACD Histogram (Trend acceleration)
It groups past market conditions into K distinct clusters (regimes). After training, every new bar is assigned to the nearest cluster via Euclidean distance in 4-dimensional standardized feature space.
This allows you to create models like:
Regime-based long/short filters
Volatility phase detectors
Trend vs. chop separation
Mean-reversion vs. breakout classification
Volume-enhanced money-flow regime shifts
Full machine-learning trading systems based solely on regimes
Note:
This script is not a universal ML strategy out of the box.
The user must engineer the feature set to match their trading style and target market.
K-means is a tool, not a ready made system, this script provides the framework.
Core Idea
K-means clustering takes raw, unlabeled market observations and attempts to discover structure by grouping similar bars together.
// STEP 1 — DATA POINTS ON A COORDINATE PLANE
// We start with raw, unlabeled data scattered in 2D space (x/y).
// At this point, nothing is grouped—these are just observations.
// K-means will try to discover structure by grouping nearby points.
//
// y ↑
// |
// 12 | •
// | •
// 10 | •
// | •
// 8 | • •
// |
// 6 | •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 2 — RANDOMLY PLACE INITIAL CENTROIDS
// The algorithm begins by placing K centroids at random positions.
// These centroids act as the temporary “representatives” of clusters.
// Their starting positions heavily influence the first assignment step.
//
// y ↑
// |
// 12 | •
// | •
// 10 | • C2 ×
// | •
// 8 | • •
// |
// 6 | C1 × •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 3 — ASSIGN POINTS TO NEAREST CENTROID
// Each point is compared to all centroids.
// Using simple Euclidean distance, each point joins the cluster
// of the centroid it is closest to.
// This creates a temporary grouping of the data.
//
// (Coloring concept shown using labels)
//
// - Points closer to C1 → Cluster 1
// - Points closer to C2 → Cluster 2
//
// y ↑
// |
// 12 | 2
// | 1
// 10 | 1 C2 ×
// | 2
// 8 | 1 2
// |
// 6 | C1 × 2
// |
// 4 | 1
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
// (1 = assigned to Cluster 1, 2 = assigned to Cluster 2)
// At this stage, clusters are formed purely by distance.
Your chosen historical window becomes the static training dataset , and after fitting, the centroids never change again.
This makes the model:
Predictable
Repeatable
Consistent across backtests
Fast for live use (no recalculation of centroids every bar)
Static Training Window
You select a period with:
Training Start
Training End
Only bars inside this range are used to fit the K-means model. This window defines:
the market regime examples
the statistical distributions (means/std) for each feature
how the centroids will be positioned post-trainin
Bars before training = fully transparent
Training bars = gray
Post-training bars = full colored regimes
Feature Engineering (4D Input Vector)
Every bar during training becomes a 4-dimensional point:
This combination balances: momentum, volatility, mean-reversion, trend acceleration giving the algorithm a richer "market fingerprint" per bar.
Standardization
To prevent any feature from dominating due to scale differences (e.g., CMF near zero vs CCI ±200), all features are standardized:
standardize(value, mean, std) =>
(value - mean) / std
Centroid Initialization
Centroids start at diverse coordinates using various curves:
linear
sinusoidal
sign-preserving quadratic
tanh compression
init_centroids() =>
// Spread centroids across using different shapes per feature
for c = 0 to k_clusters - 1
frac = k_clusters == 1 ? 0.0 : c / (k_clusters - 1.0) // 0 → 1
v = frac * 2 - 1 // -1 → +1
array.set(cent_rsi, c, v) // linear
array.set(cent_cci, c, math.sin(v)) // sinusoidal
array.set(cent_cmf, c, v * v * (v < 0 ? -1 : 1)) // quadratic sign-preserving
array.set(cent_mac, c, tanh(v)) // compressed
This makes initial cluster spread “random” even though true randomness is hardly achieved in pinescript.
K-Means Iterative Refinement
The algorithm repeats these steps:
(A) Assignment Step, Each bar is assigned to the nearest centroid via Euclidean distance in 4D:
distance = sqrt(dx² + dy² + dz² + dw²)
(B) Update Step, Centroids update to the mean of points assigned to them. This repeats iterations times (configurable).
LIVE REGIME CLASSIFICATION
After training, each new bar is:
Standardized using the training mean/std
Compared to all centroids
Assigned to the nearest cluster
Bar color updates based on cluster
No re-training occurs. This ensures:
No lookahead bias
Clean historical testing
Stable regimes over time
CLUSTER BEHAVIOR & TRADING LOGIC
Clusters (0, 1, 2, 3…) hold no inherent meaning. The user defines what each cluster does.
Example of custom actions:
Cluster 0 → Cash
Cluster 1 → Long
Cluster 2 → Short
Cluster 3+ → Cash (noise regime)
This flexibility means:
One trader might have cluster 0 as consolidation.
Another might repurpose it as a breakout-loading zone.
A third might ignore 3 clusters entirely.
Example on ETHUSD
Important Note:
Any change of parameters or chart timeframe or ticker can cause the “order” of clusters to change
The script does NOT assume any cluster equals any actionable bias, user decides.
PERFORMANCE METRICS & ROC TABLE
The indicator computes average 1-bar ROC for each cluster in:
Training set
Test (live) set
This helps measure:
Cluster profitability consistency
Regime forward predictability
Whether a regime is noise, trend, or reversion-biased
EQUITY SIMULATION & FEES
Designed for close-to-close realistic backtesting.
Position = cluster of previous bar
Fees applied only on regime switches. Meaning:
Staying long → no fee
Switching long→short → fee applied
Switching any→cash → fee applied
Fee input is percentage, but script already converts internally.
Disclaimers
⚠️ This indicator uses machine-learning but does not predict the future. It classifies similarity to past regimes, nothing more.
⚠️ Backtest results are not indicative of future performance.
⚠️ Clusters have no inherent “bullish” or “bearish” meaning. You must interpret them based on your testing and your own feature engineering.
Chop Meter + Trade Filter 1H/30M/15M (Ace PROFILE CLEAN v2)What this indicator does
Name: Chop Meter + Trade Filter 1H/30M/15M (Ace PROFILE CLEAN v2)
This is not an entry signal indicator. It’s a market condition filter:
It checks how compressed or expanded price is on
1H, 30M, and 15M.
It labels each TF as CHOP or NORMAL.
If 2 or more of those are in CHOP, it prints NO TRADE.
If 0 or 1 are in CHOP, it prints TRADE.
You use it to answer one question:
“Is this a session I should be pushing the button,
or is this a day to sit on my hands?”
How it works (simple version)
For each timeframe (1H, 30M, 15M), the script:
Looks back N bars (ATR length).
Measures:
ATR over N bars
Price range over N bars (highest high − lowest low)
Computes a compression value:
compression = ATR / range.
Then it compares that to the Threshold:
If compression > threshold → CHOP (market boxed / compressed)
If compression ≤ threshold → NORMAL (market expanded / trending)
Finally:
It counts how many TFs are CHOP.
If 2 or 3 TFs are CHOP → NO TRADE.
If 0 or 1 TFs are CHOP → TRADE.
Inputs / Profiles
At the top you see:
Profile
Overnight 4/0.40 – for Asia / London / overnight sessions
NYO 5/0.45 – for New York Open profile (default)
Custom – lets you type your own values
When Custom is selected, you can set:
ATR Length (Custom) – how many bars to use in the compression calc
Chop Threshold (ATR ÷ Range) (Custom) – where you cut between CHOP vs NORMAL
Higher threshold → more bars counted as NORMAL, less CHOP
Lower threshold → more bars counted as CHOP, fewer TRADE environments
For NYO, you normally keep:
Profile = NYO 5/0.45
(ATR over 5 bars, threshold 0.45)
What you see on the chart
A single line panel at the bottom-right, like:
1H: NORMAL | 30M: CHOP | 15M: NORMAL | TRADE | NYO 5/0.45
Meaning:
1H: NORMAL → the last 1H window is expanded enough (not boxed).
30M: CHOP → 30M is compressed (inside a tighter range).
15M: NORMAL → 15M has opened up.
TRADE → Only 1 TF is CHOP, so the majority says OK to trade.
NYO 5/0.45 → just a tag to remind which profile you’re using.
If instead you see:
1H: CHOP | 30M: CHOP | 15M: NORMAL | NO TRADE | NYO 5/0.45
That means:
1H and 30M are boxed
15M opened a bit, but 2 TFs are CHOP
Final verdict: NO TRADE environment
How to use it in your trading
1. As a gatekeeper before any entry model
No matter what entry you use (MSS + FVG, OB, purge setups, etc.):
If the panel says NO TRADE →
You do not open new positions.
You’re in “observe only” mode.
You can still study price, mark levels, and journal, but you’re not pressing the button.
If the panel says TRADE →
The environment is acceptable.
Now you can look for your entry model (e.g. MSS + FVG retest, SMT, OB, etc.).
Think of it as your first filter every session:
“Panel says NO TRADE? I don’t care how good the candle looks – I’m waiting.”
2. Reading each timeframe
1H: CHOP → Day is still boxed on the higher frame; big expansion hasn’t kicked in.
30M: CHOP → Classic 30M dealing range; many fake breaks and wicks likely.
15M: CHOP → Intraday still coiling; scalping environment at best.
When 2 or 3 say CHOP, expect:
Whipsaw
MSS both ways
Failed FVGs
News spikes that die in the box
Perfect time to protect your psychology and capital.
When 2 or 3 say NORMAL, expect:
Cleaner swings
Better follow-through after MSS / FVG
Easier to hold for targets
3. How it pairs with your MSS/FVG indicator
With your Chop + MSS/FVG Retest indicator:
Chop meter = environment filter
MSS/FVG indicator = entry trigger
Your process becomes:
Check chop meter:
If NO TRADE → hands off.
If TRADE → go to step 2.
On your chart, wait for:
Purge / SMT at the edges
MSS in the right direction
FVG + retest
Only take L/S when both:
Chop meter = TRADE, and
Entry model = L/S signal in the right area (premium/discount).
That way, you’re not just trading every L/S the MSS script spits out—you’re trading L/S only when the higher-timeframe environment is worth it.
Daily vs Intraday Candle Match Strategy고죠 훈의 차트공부방
Gojo Hoon’s Trading Room
전일 종가 대비 현재 일봉 방향과 시간봉 방향이 일치할 때 진입
Trade when current daily direction (vs. previous close) matches the hourly/15-minute candle direction.
Multi Time Frame EMA & MA IndicatorThis indicator automatically applies prime-number EMAs and MAs based on the current chart timeframe, using faster cool-tone EMAs and slower warm-tone MAs to clearly distinguish momentum vs trend.
It adapts dynamically for 1m, 5m, 15m, 1H, 4H, and 1D charts, and uses a visual hierarchy where thinner lines represent faster averages and thicker lines represent slower ones, ensuring clarity in both light and dark themes.
An on-chart label displays which EMA and MA lengths are active for the selected timeframe.
Time-Decay Liquidity Zones [BackQuant]Time-Decay Liquidity Zones
A dynamic liquidity map that turns single-bar exhaustion events into fading, color-graded zones, so you can see where trapped traders and unfinished business still matter, and when those areas have finally stopped pulling price.
What this is
This indicator detects unusually strong impulsive moves into wicks, converts them into supply or demand “zones,” then lets those zones decay over time. Each zone carries a strength score that fades bar by bar. Zones that stop attracting or rejecting price are gradually de-emphasized and eventually removed, while the most relevant areas stay bright and obvious.
Instead of static rectangles that live forever, you get a living liquidity map where:
Zones are born from objective criteria: volatility, wick size, and optional volume spikes.
Zones “age” using a configurable decay factor and maximum lifetime.
Zone color and opacity reflect current relative strength on a unified clear → green → red gradient.
Zones freeze when broken, so you can distinguish “active reaction areas” from “historical levels that have already given way”.
Conceptual idea
Large wicks with strong volatility often mark areas where aggressive orders met hidden liquidity and got absorbed. Price may revisit these areas to test leftover interest or to relieve trapped positions. However, not every wick matters for long. As time passes and more bars print, the market “forgets” some areas.
Time-Decay Liquidity Zones turns that idea into a rule-based system:
Find bars that likely reflect strong aggressive flows into liquidity.
Mark a zone around the wick using ATR-based thickness.
Assign a strength score of 1.0 at birth.
Each bar, reduce that score by a decay factor and remove zones that fall below a threshold or live too long.
Color all surviving zones from weak to strong using a single gradient scale and a visual legend.
How events are detected
Detection lives in the Event Detection group. The script combines range, wick size, and optional volume filters into simple rules.
Volatility filter
ATR Length — computes a rolling ATR over your chosen window. This is the volatility baseline.
Min range in ATRs — bar range (High–Low) must exceed this multiple of ATR for an event to be considered. This avoids tiny bars triggering zones.
Wick filters
For each bar, the script splits the candle into body and wicks:
Upper wick = High minus the max(Open, Close).
Lower wick = min(Open, Close) minus Low.
Then it tests:
Upper wick condition — upper wick must be larger than Min wick size in ATRs × ATR.
Lower wick condition — lower wick must be larger than Min wick size in ATRs × ATR.
Only bars with a sufficiently long wick relative to volatility qualify as candidate “liquidity events”.
Volume filter
Optionally, the script requires a volume spike:
Use volume filter — if enabled, volume must exceed a rolling volume SMA by a configurable multiplier.
Volume SMA length — period for the volume average.
Volume spike multiplier — how many times above the SMA current volume needs to be.
This lets you focus only on “heavy” tests of liquidity and ignore quiet bars.
Event types
Putting it together:
Upper event (potential supply / long liquidation, etc.)
Occurs when:
Upper wick is large in ATR terms.
Full bar range is large in ATR terms.
Volume is above the spike threshold (if enabled).
Lower event (potential demand / short liquidation, etc.)
Symmetric conditions using the lower wick.
How zones are constructed
Zone geometry lives in Zone Geometry .
When an event is detected, the script builds a rectangular box that anchors to the wick and extends in the appropriate direction by an ATR-based thickness.
For upper (supply-type) zones
Bottom of the zone = event bar high.
Top of the zone = event bar high + Zone thickness in ATRs × ATR.
The zone initially spans only the event bar on the x-axis, but is extended to the right as new bars appear while the zone is active.
For lower (demand-type) zones
Top of the zone = event bar low.
Bottom of the zone = event bar low − Zone thickness in ATRs × ATR.
Same extension logic: box starts on the event bar and grows rightward while alive.
The result is a band around the wick that scales with volatility. On high-ATR charts, zones are thicker. On calm charts, they are narrower and more precise.
Zone lifecycle, decay, and removal
All lifecycle logic is controlled by the Decay & Lifetime group.
Each zone carries:
Score — a floating-point “importance” measure, starting at 1.0 when created.
Direction — +1 for upper zones, −1 for lower zones.
Birth index — bar index at creation time.
Active flag — whether the zone is still considered unbroken and extendable.
1) Active vs broken
Each confirmed bar, the script checks:
For an upper zone , the zone is counted as “broken” when the close moves above the top of the zone.
For a lower zone , the zone is counted as “broken” when the close moves below the bottom of the zone.
When a zone breaks:
Its right edge is frozen at the previous bar (no further extension).
The zone remains on the chart, but is no longer updated by price interaction. It still decays in score until removal.
This lets you see where a major level was overrun, while naturally fading its influence over time.
2) Time decay
At each confirmed bar:
Score := Score × Score decay per bar .
A decay value close to 1.0 means very slow decay and long-lived zones.
Lower values (closer to 0.9) mean faster forgetting and more current-focused zones.
You are controlling how quickly the market “forgets” past events.
3) Age and score-based removal
Zones are removed when either:
Age in bars exceeds Max bars a zone can live .
This is a hard lifetime cap.
Score falls below Minimum score before removal .
This trims zones that have decayed into irrelevance even if their age is still within bounds.
When a zone is removed, its box is deleted and all associated state is freed to keep performance and visuals clean.
Unified gradient and color logic
Color control lives in Gradient & Color . The indicator uses a single continuous gradient for all zones, above and below price, so you can read strength at a glance without guessing what palette means what.
Base colors
You set:
Mid strength color (green) — used for mid-level strength zones and as the “anchor” in the gradient.
High strength color (red) — used for the strongest zones.
Max opacity — the maximum visual opacity for the solid part of the gradient. Lower values here mean more solid; higher values mean more transparent.
The script then defines three internal points:
Clear end — same as mid color, but with a high alpha (close to transparent).
Mid end — mid color at the strongest allowed opacity.
High end — high color at the strongest allowed opacity.
Strength normalization
Within each update:
The script finds the maximum score among all existing zones.
Each zone’s strength is computed as its score divided by this maximum.
Strength is clamped into .
This means a zone with strength 1.0 is currently the strongest zone on the chart. Other zones are colored relative to that.
Piecewise gradient
Color is assigned in two stages:
For strength between 0.0 and 0.5: interpolate from “clear” green to solid green.
Weak zones are barely visible, mid-strength zones appear as solid green.
For strength between 0.5 and 1.0: interpolate from solid green to solid red.
The strongest zones shift toward the red anchor, clearly separating them from everything else.
Strength scale legend
To make the gradient readable, the indicator draws a vertical legend on the right side of the chart:
About 15 cells from top (Strong) to bottom (Weak).
Each cell uses the same gradient function as the zones themselves.
Top cell is labeled “Strong”; bottom cell is labeled “Weak”.
This legend acts as a fixed reference so you can instantly map a zone’s color to its approximate strength rank.
What it plots
At a glance, the indicator produces:
Upper liquidity zones above price, built from large upper wick events.
Lower liquidity zones below price, built from large lower wick events.
All zones colored by relative strength using the same gradient.
Zones that freeze when price breaks them, then fade out via decay and removal.
A strength scale legend on the right to interpret the gradient.
There are no extra lines, labels, or clutter. The focus is the evolving structure of liquidity zones and their visual strength.
How to read the zones
Bright red / bright green zones
These are your current “major” liquidity areas. They have high scores relative to other zones and have not yet decayed. Expect meaningful reactions, absorption attempts, or spillover moves when price interacts with them.
Faded zones
Pale, nearly transparent zones are either old, decayed, or minor. They can still matter, but priority is lower. If these are in the middle of a long consolidation, they often become background noise.
Broken but still visible zones
Zones whose extension has stopped have been overrun by closing price. They show where a key level gave way. You can use them as context for regime shifts or failed attempts.
Absence of zones
A chart with few or no zones means that, under your current thresholds, there have not been strong enough liquidity events recently. Either tighten the filters or accept that recent price action has been relatively balanced.
Use cases
1) Intraday liquidity hunting
Run the indicator on lower timeframes (e.g., 1–15 minute) with moderately fast decay.
Use the upper zones as potential sell reaction areas, the lower zones as potential buy reaction areas.
Combine with order flow, CVD, or footprint tools to see whether price is absorbing or rejecting at each zone.
2) Swing trading context
Increase ATR length and range/wick multipliers to focus only on major spikes.
Set slower decay and higher max lifetime so zones persist across multiple sessions.
Use these zones as swing inflection areas for larger setups, for example anticipating re-tests after breakouts.
3) Stop placement and invalidation
For longs, place invalidation beyond a decaying lower zone rather than in the middle of noise.
For shorts, place invalidation beyond strong upper zones.
If price closes through a strong zone and it freezes, treat that as additional evidence your prior bias may be wrong.
4) Identifying trapped flows
Upper zones formed after violent spikes up that quickly fail can mark trapped longs.
Lower zones formed after violent spikes down that quickly reverse can mark trapped shorts.
Watching how price behaves on the next touch of those zones can hint at whether those participants are being rescued or squeezed.
Settings overview
Event Detection
Use volume filter — enable or disable the volume spike requirement.
Volume SMA length — rolling window for average volume.
Volume spike multiplier — how aggressive the volume spike filter is.
ATR length — period for ATR, used in all size comparisons.
Min wick size in ATRs — minimum wick size threshold.
Min range in ATRs — minimum bar range threshold.
Zone Geometry
Zone thickness in ATRs — vertical size of each liquidity zone, scaled by ATR.
Decay & Lifetime
Score decay per bar — multiplicative decay factor for each zone score per bar.
Max bars a zone can live — hard cap on lifetime.
Minimum score before removal — score cut-off at which zones are deleted.
Gradient & Color
Mid strength color (green) — base color for mid-level zones and the lower half of the gradient.
High strength color (red) — target color for the strongest zones.
Max opacity — controls the most solid end of the gradient (0 = fully solid, 100 = fully invisible).
Tuning guidance
Fast, session-only liquidity
Shorter ATR length (e.g., 20–50).
Higher wick and range multipliers to focus only on extreme events.
Decay per bar closer to 0.95–0.98 and moderate max lifetime.
Volume filter enabled with a decent multiplier (e.g., 1.5–2.0).
Slow, structural zones
Longer ATR length (e.g., 100+).
Moderate wick and range thresholds.
Decay per bar very close to 1.0 for slow fading.
Higher max lifetime and slightly higher min score threshold so only very weak zones disappear.
Noisy, high-volatility instruments
Increase wick and range ATR multipliers to avoid over-triggering.
Consider enabling the volume filter with stronger settings.
Keep decay moderate to avoid the chart getting overloaded with old zones.
Notes
This is a structural and contextual tool, not a complete trading system. It does not account for transaction costs, execution slippage, or your specific strategy rules. Use it to:
Highlight where liquidity has recently been tested hard.
Rank these areas by decaying strength.
Guide your attention when layering in separate entry signals, risk management, and higher-timeframe context.
Time-Decay Liquidity Zones is designed to keep your chart focused on where the market has most recently “cared” about price, and to gradually forget what no longer matters. Adjust the detection, geometry, decay, and gradient to fit your product and timeframe, and let the zones show you which parts of the tape still have unfinished business.
Relative Performance vs XAO (Histogram)RSC Relative Strength Comparison is used to compare performance of a Sector Index or Stock against a Benchmark (Index). The Benchmark used is the Australian All Ordinaries Index with a look back period of 63 days (3 months). Both the benchmark and look back period may be changed in the code to suit.
SMA Cross + KC Breakout + ATR StopThis is the same script previously published with the exception of utilizing SMA vs EMA for those who prefer that moving average type.
Dobrusky Pressure CoreWhat it does & who it’s for
Dobrusky Pressure Core is a volume by time replacement for traders who care about which side actually controls each bar. Instead of just plotting total volume, it splits each bar into estimated buy vs sell pressure and overlays a custom, session-aware volume baseline. It’s built for discretionary traders who want more nuanced volume context for entries, breakouts, and pullbacks.
Core ideas
Buy/sell pressure split: Each bar’s volume is broken into estimated buying and selling pressure.
Dominant side highlighting: The dominant side (buy or sell) is always displayed starting from the bottom of the bar, so you can quickly see who “owned” that bar.
Median-based baseline: Uses the median of the last N bars (50 by default) to build a robust volume baseline that’s less sensitive to one-off spikes.
Session-aware behavior: Baseline is calculated from Regular Trading Hours (RTH) by default, with an option to include Extended Hours (ETH) and a control to force Regular data on higher timeframes.
Volume regimes: Three multipliers (1x, 1.5x, 2x by default) show normal, high, and extreme volume regions.
Flexible display: Baseline can be shown as lines or as columns behind the volume, with full color customization.
How the pressure logic works
For each bar, the script:
Adjusts the range for gaps relative to the prior close so the “true” traded range is more consistent.
Computes buy pressure as a proportion of the adjusted range from low to close.
Defines sell pressure as: total volume minus buy pressure.
Marks the bar as buy-dominant if buy pressure ≥ sell pressure, otherwise sell-dominant, and colors the dominant side from the bottom to at least the midpoint using the selected buy/sell colors.
In practice, this turns basic volume columns into bars where the internal split and dominant side are clearly visible, helping you judge whether aggressive buyers or sellers truly controlled the bar instead of just looking at the price action.
Volume baseline & session logic
The script builds a session-aware baseline from recent volume:
Baseline length: A rolling window (default 50 bars) is used to compute a median volume value instead of a simple moving average.
RTH-only by default: By default, the baseline is built from Regular Trading Hours bars only. During extended hours, the baseline effectively “freezes” at the last RTH-derived value unless you choose to include extended session data.
Extended mode: If you select Extended mode, the script builds separate rolling baselines for RTH and ETH trading, using the appropriate one depending on the current session.
Force Regular Above Timeframe: On timeframes equal to or higher than your chosen threshold, the baseline automatically uses Regular session data, even if Extended is selected.
Multipliers: Three adjustable multipliers (1x, 1.5x, 2x by default) create normal, high, and extreme volume bands for quick identification.
This lets you choose whether you want a pure RTH reference or a baseline that adapts to extended-session activity.
Example ways to use it
1. Replace standard volume bars
Add Dobrusky Pressure Core to your volume pane and hide the default volume if you prefer a clean look.
Use the colors and split to see at a glance whether buyers or sellers were dominant on each bar.
2. Pressure confirmation for entries
For longs (example concept; adapt to your own rules):
Require that the entry bar’s buy pressure is greater than the previous bar’s sell pressure , or
If the entry and prior bar are both buy-dominant, require that the entry bar has more buy pressure than the prior bar.
This helps avoid taking a long when buying pressure is clearly fading relative to what sellers recently showed. A mirrored idea can be used for short setups with sell pressure.
3. Context from baseline multipliers
Use ~1x baseline as “normal” volume.
Watch for bars at or above 1.5x baseline when you want to see increased participation.
Treat 2x baseline and above as “extreme” volume zones that may mark climactic or especially important bars.
In practice, the baseline and multipliers are best used as context and filters, not as rigid rules.
Settings overview
Display
- Show Volume Baseline: toggle the baseline and its levels on or off.
- Baseline Display: choose between Line or Bars for the baseline visualization.
Baseline Calculation
- Length: lookback for the median baseline (default 50, configurable).
- Baseline Session Data: choose Regular or Extended to control which session data feeds the baseline.
Session Controls
- Regular Session (Local to TZ): define your RTH window (e.g., 0930-1600).
- Session Time Zone: choose the time zone used for that window.
- Force Regular Above Timeframe: on higher timeframes, force the baseline to use Regular session data only.
Baseline Levels
- Show Level x Multiplier 1/2/3: toggle each volume regime level.
- Multiplier 1/2/3: define what you consider normal, high, and extreme volume (defaults: 1.0, 1.5, 2.0).
Colors
- Buy Volume / Sell Volume: choose colors for buy and sell pressure.
- Baseline Bars (Base / x2 / x3): colors when the baseline is drawn as columns.
- Baseline Line (Base / x2 / x3): colors when the baseline is drawn as lines.
Limitations & best practices
This is a decision-support and visualization tool, not a buy/sell signal generator.
Best suited to markets where volume data is meaningful (e.g., index futures, liquid equities, liquid crypto).
The usefulness of any volume-based metric depends on the underlying data feed and instrument structure.
Always combine pressure and baseline context with your own strategy, risk management, and testing.
Originality
Most volume tools either show total volume only or compare it to a simple moving average. Dobrusky Pressure Core combines:
An intrabar buy/sell pressure split based on a gap-adjusted price range.
A median-based, configurable baseline built from session-specific data.
Session-aware behavior that keeps the baseline focused on Regular hours by default, with the option to incorporate Extended hours and force Regular data on higher timeframes.
The goal is to give traders a richer, session-aware view of participation and pressure that standard volume bars and simple SMA overlays don’t provide, while keeping everything transparent and open-source so users can review and adapt the logic.
3 day look backThis script is designed to help traders visually compare daily liquidity behavior between two correlated assets — for example, the Nasdaq (NQ) and the S&P500 (ES).
It plots each day’s High and Low, aligned from Midnight to Midnight, with a clean session structure. This makes it easier to identify:
SMT (Smart Money Technique) divergences
liquidity grabs
daily highs/lows sweeps
relative strength/weakness between assets
intraday bias shifts based on daily structure
What the script does
Reconstructs each trading day from 00:00 to 00:00, regardless of session irregularities.
Plots the High and Low of every completed day.
Allows users to display as many past days as they want (custom “look-back” parameter).
Automatically merges the weekend with Friday for assets where Saturday/Sunday sessions are fragmented.
Includes a manual midnight offset (–12h to +12h) to fix timezone inconsistencies on TradingView charts (common on futures).
Optional real-time lines for the current day.
No excessive right-side extensions for clean intraday reading.
Why this is useful
When comparing paired assets (e.g., NQ vs ES), liquidity behavior is often different.
This script makes it easy to spot:
when one asset makes a new daily high while the other doesn’t
asymmetrical liquidity sweeps
SMT-based divergence setups
liquidity grabs at daily levels
intraday directional bias shifts
About the other indicators shown on the chart
In the example chart, two additional indicators are used only for clarity and structure:
Day of the Week — displays the weekday on each session for easier orientation.
Vertical Line Timeline — draws a clean separator line between days.
These indicators are not required for this High/Low script to work.
They simply help visually organize sessions and make daily structure easier to read when comparing two assets side by side.
How to use
Open two assets (e.g., NQ1! and ES1!) side by side.
Apply this script on both charts.
Set the same timeframe.
Choose how many days back you want to visualize (look-back parameter).
Observe how each asset interacts with its daily High/Low.
Look for SMT divergences and liquidity-based setups.
Main features
Midnight-to-Midnight alignment
Weekend fusion
Manual offset for perfect timing
Adjustable daily look-back
Clean daily liquidity
Optional dynamic daily levels
Ideal for SMT/liquidity-based intraday trading
Global M2 ex-China MonitorGlobal M2 Monitor - Ultimate Edition
🎯 OVERVIEW
Advanced global M2 money supply monitoring indicator, offering a unique macroeconomic view of global liquidity. Real-time tracking of M2 evolution in major developed economies.
📊 KEY FEATURES
Global M2 Aggregation : USA, Japan, Canada, Eurozone, United Kingdom
Currency Conversion : All data converted to USD for consistent analysis
High Resolution Display : Daily curve by default
Technical Analysis : 50-period moving average (SMA/EMA/WMA)
Accurate YoY Calculation : Annual variation based on monthly data
Advanced Signal System : Multi-condition color codes
🎨 COLOR SYSTEM - DEFAULT SETTINGS
🟢 GREEN : YoY ≥ 7% AND M2 ≥ SMA → Strong growth + Bullish momentum
🔴 RED : YoY ≤ 2% AND M2 ≤ SMA → Weak growth + Bearish momentum
🟢 LIGHT GREEN : YoY ≥ 7% BUT M2 < SMA → Good fundamentals, temporarily weak momentum
🔴 LIGHT RED : YoY ≤ 2% BUT M2 > SMA → Weak fundamentals, price still supported
🔵 BLUE : YoY between 2% and 7% → Neutral zone of moderate growth
🇨🇳 WHY IS CHINA EXCLUDED BY DEFAULT?
Chinese M2 data presents methodological reliability and transparency issues. Exclusion allows for more consistent analysis of mature market economies.
Different M2 definition vs Western standards
Capital controls affecting real convertibility
Frequent monetary manipulations by authorities
✅ Available option : Can be activated in settings
⚙️ OPTIMIZED DEFAULT PARAMETERS
// DISPLAY SETTINGS
Candle Period: D (Daily)
// MOVING AVERAGE
MA Period: 50, Type: SMA
// BACKGROUND LOGIC
YoY Bullish: 7%, YoY Bearish: 2%
SMA Method: absolute, Threshold: 0.2%
// COLORS
Transparency: 5%
China M2: Disabled
📈 RECOMMENDED USAGE
Traders : Anticipate sector rotations
Investors : Identify abundant/restricted liquidity phases
Macro-analysts : Monitor monetary policy impacts
Portfolio managers : Understand inflationary pressures
🔍 ADVANCED INTERPRETATION
M2 ↗️ + YoY ≥ 7% → Favorable risk-on environment
M2 ↘️ + YoY ≤ 2% → Defensive risk-off environment
Divergences → Early warning signals for trend changes
💡 WHY THIS INDICATOR?
Global money supply is the lifeblood of the financial economy . Its growth or contraction typically precedes market movements by 6 to 12 months.
"Don't fight the Fed... nor the world's central banks"
🛠️ ADVANCED CUSTOMIZATION
All parameters are customizable:
YoY bullish/bearish thresholds
SMA comparison method (absolute/percentage)
Colors and transparency
Moving average period and type
Optional China inclusion
📋 TECHNICAL INFORMATION
YoY Calculation : Based on monthly data for consistency
Sources : FRED, ECONOMICS, official data
Updates : Real-time with publications
Currencies : Updated exchange rates
NQ vs ES SMT DivergencesAn algorithm for spotting SMT Divergences this is an ICT concept serving fellow ICT traders.
Distância Preço vs EMAIndicador pra ser usado em tendencias consolidadas como referencias para retorno a média
