Unified Field: Clean FVG + Session POCCombines FVG with POC. one can combine SMC with Order Flow Strategies for better confluence.
インジケーターとストラテジー
Market Regime Guard PRO Institutional No-Trade ZonesThis dashboard automatically blocks trading on structurally dangerous market days caused by volatility compression, inside-day accumulation, rising VIX liquidation risk, EMA breakdowns, and thin liquidity traps.
Most traders lose not because their entries are bad — but because they trade on structurally dangerous market days.
This dashboard automatically blocks trading on contraction, liquidation-risk, inside-day, and volatility-trap days.
Then list what it detects:
• Inside Days (institutional absorption)
• NR7 contraction traps
• ATR volatility compression
• EMA structure breakdown
• Rising VIX liquidation risk
• News & holiday liquidity traps
Promise:
Only trade when the market structure is favorable.
Use this as your universal go/no-go trading permission system.
If it’s GREEN → Trade.
If it’s RED → Stand Aside or Be careful
Works on:
SPY, QQQ, TQQQ, NVDA, PLTR, TSLA, BTC, ES, NQ, Forex & Crypto.
🧭 How to Use the Market Regime Table
This table is your go / no-go permission system.
Start by checking it on SPY and QQQ — these represent the overall U.S. market and the Nasdaq growth complex.
• If SPY and QQQ are GREEN → market structure is favorable
• If either is RED → stand aside or reduce risk
Once the market is GREEN, you can then apply the same table to individual stocks (NVDA, PLTR, TSLA, AMD, etc.) to confirm that the stock’s structure is also favorable before taking any trades.
Rule of thumb:
Market first. Stock second.
Only trade when both are GREEN.
This one rule alone dramatically improves win rate, drawdown, and consistency.
FULL DESCRIPTION
Most traders don’t lose because their entries are bad —
They lose because they trade on structurally dangerous market days.
On these days:
• Institutions absorb liquidity
• Volatility contracts
• Fake breakouts dominate
• Stop hunts explode
• Real expansion does not occur
This indicator automatically identifies and blocks:
• Inside-day accumulation traps
• NR7 contraction traps
• Falling ATR volatility compression
• EMA structure breakdowns
• Rising VIX liquidation risk
• Thin liquidity / holiday risk
• News-day volatility traps
It gives you a clear desk-style verdict:
Status Meaning
🟢 GREEN Market structure favorable – trade normally
🔴 RED Structural danger – stand aside
This is not an entry system.
This is your permission system.
🛠 HOW TO USE
Add indicator to your chart
Check table in top-right
Trade only on GREEN days
Avoid RED days completely
📈 Personal Note
This regime filter has been instrumental in my own trading journey. After struggling during my first few years in the market, I realized that the biggest losses didn’t come from bad strategies — they came from trading on the wrong days.
Learning to stand aside on structurally dangerous market days and only trade when conditions are favorable dramatically improved my consistency and overall returns.
🧠 Why Market Regime Matters Even More for Day Traders
Most day-trader losses do not come from bad entries.
They come from:
• Choppy inside-day conditions
• Liquidity absorption
• Falling volatility (no follow-through)
• Stop-hunt behavior
• News / thin liquidity traps
Your filter directly blocks every one of these traps.
So for day traders, this tool:
• Prevents revenge trading
• Stops death-by-a-thousand-cuts days
• Filters out random chop days
• Protects capital on slow days
• Preserves psychological capital
📈 Why It Also Improves Swing Trading
For swing traders, this tool:
• Avoids entering during contraction
• Avoids entering before expansions
• Avoids bear-regime traps
• Improves follow-through probability
• Reduces drawdown
• Improves R-multiple expectancy
Which means:
Fewer trades
Higher quality trades
More profit per trade
The Universal Truth
The market does not pay you for activity.
It pays you for selectivity.
This filter improves timing, not tactics.
Your entries can be identical — your results improve simply because you’re trading on the right days.
⚠️ Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial, investment, or trading advice.
Trading stocks, options, futures, forex, and cryptocurrencies involves substantial risk and may result in the loss of some or all of your invested capital. Past performance is not indicative of future results.
This tool does not guarantee profits and should be used as a market structure filter and risk-management aid only. Always perform your own analysis, use proper position sizing, and consult a licensed financial professional before making any trading decisions.
You are solely responsible for all trades taken using this indicator.
EMA Touch Alert Realtime (Once Per Bar)This alert notifies you when the price touches the EMA you set. Once it notifies you, it is designed not to notify you again on that same candlestick.
Nixxo ATR Stop LossATR that prints stop losses for short or long positions with a table that shows the pip values in each case!
ADR% / ATR / LoD dist. Table - V2ADR% / ATR / LoD Distance Table (V2) + ATR Range Lines is a simple “daily volatility dashboard” that helps you quickly judge how extended a stock is during the day and where “normal” daily movement zones sit relative to price.
It’s designed to help you answer:
“Has this stock already made most of its usual daily move?”
“Am I chasing too late?”
“Where are typical +ATR / −ATR stretch and pullback zones?”
What you’ll see
ADR% (Average Daily Range %)
Shows the stock’s typical daily travel (low → high) as a percentage.
Example: ADR% = 4% means the stock often swings ~4% in a normal day.
ATR (Average True Range)
Shows the stock’s typical daily movement in price units ($ / points).
Example: ATR = 2.50 means it often moves about $2.50 per day.
LoD dist. (Low of Day distance)
Shows how far price is from today’s Low of Day, measured relative to ATR (as a %).
Higher % = more extended away from the day’s low.
Optional: ATR Range Lines (added in this version)
You can enable two guide lines that extend to the right:
ATR Up Line = Price + ATR
ATR Down Line = Price − ATR
These act like volatility guardrails to visualize “typical daily stretch” and “typical pullback” zones.
ATR “Live vs Locked” option (important)
Lock ATR to last completed day (no intraday updates):
ON (Locked): Uses the last completed daily ATR (yesterday’s finished value).
✅ ATR stays constant all day while the market is live.
OFF (Live): ATR can update intraday as today’s daily candle expands.
✅ ATR may change during the session.
Either way, ATR is still based on your chosen ATR Length (lookback period). Locking simply prevents the ATR from drifting intraday.
How to use it (Kullamägi-style principle)
Kristjan Kullamägi’s momentum style emphasizes pressing strength when conditions are right, but also respecting extension and risk/reward. This tool helps you quantify that:
If ADR%/ATR suggests the stock already moved near its usual daily range, chasing can be lower reward.
The ATR lines help you visualize when price is in a “normal stretch zone” vs a better risk area.
Locking ATR gives you stable intraday reference levels for cleaner execution.
Tips
Use ADR% to understand whether there’s likely “room” left in today’s move.
Use LoD dist. to quickly gauge if price is already far from the day’s low (extended).
Use ATR Up/Down Lines as a simple volatility framework for entries, add-ons, and risk planning.
Keep Lock ATR ON if you prefer stable levels throughout the session.
Credits
Original indicator concept & script: ArmerSchlucker
ADR% formula credit: MikeC / TheScrutiniser and GlinckEastwoot
Modifications (V2): TradersPod
Added optional ATR Up/Down lines extending to the right
Added “Lock ATR to last completed day” option for stable intraday ATR reference
Kept the original logic and purpose intact
Multi Cycles Predictive System ML - GBM IntegratedMulti-Cycle Predictive System: The Gradient Boosting Machine (GBM) Revolution
Introduction: The Death of Static Analysis
The financial markets are not static; they are a living, breathing, and chaotic system. Yet, for decades, traders have relied on static indicators—using the same RSI settings, the same MACD parameters, and the same Moving Averages regardless of whether the market is trending, chopping, or crashing.
The Multi-Cycle Predictive System (MCPS) represents a paradigm shift. It is not just an indicator; it is an Adaptive Machine Learning Engine running directly on your chart.
By integrating a fully functional Gradient Boosting Machine (GBM), this script does not guess—it learns. It monitors 13 distinct algorithmic models, calculates their real-time accuracy against future price action, and dynamically reallocates influence to the "winning" models using gradient descent.
This is Survival of the Fittest applied to technical analysis.
1. The Core Engine: Gradient Boosting & Adaptive Learning
At the heart of the MCPS is a custom-coded Gradient Boosting Machine. While most "ML" scripts on TradingView simply average a few indicators, this system replicates the architecture of advanced data science models.
How the GBM Works:
Ensemble Prediction: The system aggregates signals from 13 different mathematical models.
Residual Calculation: It compares the ensemble's previous predictions against the actual price movement (Price Return) to calculate the error (Residual).
Gradient Descent: It calculates the gradient of the loss function. We utilize a Huber Loss Gradient, which is robust against outliers (market spikes), ensuring the model doesn't overreact to volatility.
Weight Optimization: Using a configurable learning rate, the system updates the weights of each sub-algorithm. Models that predicted correctly gain weight; models that failed lose influence.
Softmax Normalization: Finally, weights are passed through a Softmax function (with Temperature control) to convert them into probabilities that sum to 1.0.
The "Winner-Takes-All" Philosophy
A common failure in ensemble systems is "Signal Dilution"—where good signals are drowned out by bad ones.
The MCPS solves this with Aggressive Weight Concentration:
Top 3 Logic: The script identifies the top 3 performing algorithms based on historical accuracy.
The 90% Rule: It forces the system to allocate up to 90% of the total decision weight to these top 3 performers.
Result: If Ehlers and Schaff are reading the market correctly, but MACD is failing, MACD is effectively silenced. The system listens only to the winners.
2. The 13 Algorithmic Pillars
The MCPS draws from a diverse library of Digital Signal Processing (DSP), Statistical, and Momentum algorithms. It does not rely on simple moving averages.
Ehlers Bandpass Filter: Isolates the dominant cycle in price data, removing trend and noise.
Zero-Lag EMA (ZLEMA): Reduces lag to near-zero to track momentum shifts instantly.
Coppock Curve: A classic long-term momentum indicator, modified here for adaptive responsiveness.
Detrended Price Oscillator (DPO): Eliminates the trend to identify short-term cycles.
Schaff Trend Cycle (STC): A double-smoothed stochastic of the MACD, excellent for identifying cycle turns.
Fisher Transform: Converts price into a Gaussian normal distribution to pinpoint turning points.
MESA Adaptive: Uses Maximum Entropy Spectral Analysis to detect the current dominant cycle period.
Goertzel Algorithm: A DSP technique used to identify the magnitude of specific frequency components in the price wave.
Hilbert Transform: Extracts the instantaneous amplitude and phase of the price action.
Autocorrelation: Measures the similarity between the price series and a lagged version of itself to detect periodicity.
Singular Spectrum Analysis (SSA): Decomposes the time series into trend, seasonal, and noise components (Simplified).
Wavelet Transform: Analyzes data at different scales (frequencies) simultaneously.
Empirical Mode Decomposition (EMD): Splits data into Intrinsic Mode Functions (IMFs) to isolate pure cycles.
3. The Dashboard: Total Transparency
Black-box algorithms are dangerous. You need to know why a signal is being generated. The MCPS features two detailed dashboards (tables) located at the bottom of your screen.
The Weight & Accuracy Table (Bottom Right)
This is your "Under the Hood" view. It displays:
Algorithm: The name of the model.
Accuracy: The rolling historical accuracy of that specific model over the lookback period (e.g., 58.2%).
Weight: The current influence that model has on the final signal. Watch this change in real-time. You will see the system "giving up" on bad models and "betting heavy" on good ones.
Prob/Sig: The raw probability and directional signal (Up/Down).
The GBM Stats Table (Bottom Left)
Tracks the health of the Machine Learning engine:
Iterations: How many learning cycles have occurred.
Entropy: A measure of market confusion. High entropy means weights are spread out (models disagree). Low entropy means the models are aligned.
Top 3 Weight: Shows how concentrated the decision power is. If this is >80%, the system is highly confident in specific models.
Confidence & Agreement: Statistical measures of the signal strength.
4. How to Trade with MCPS
This system outputs a single, composite Cycle Line (oscillating between -1 and 1) and a background Regime Color.
Strategy A: The Zero-Cross (Trend Reversal)
Bullish: When the Cycle Line crosses above 0. This indicates that the weighted average of the top-performing algorithms has shifted to a net-positive expectation.
Bearish: When the Cycle Line crosses below 0.
Strategy B: Probability Extremes (Mean Reversion)
Strong Buy: When the Cycle Line drops below -0.5 (Oversold) and turns up. This indicates a high-probability cycle bottom.
Strong Sell: When the Cycle Line rises above +0.5 (Overbought) and turns down.
Strategy C: Regime Filtering
The background color changes based on the aggregate consensus:
Green/Lime: Bullish Regime. Look primarily for Long entries. Ignore weak sell signals.
Red/Orange: Bearish Regime. Look primarily for Short entries.
Gray: Neutral/Choppy. Reduce position size or wait.
5. Configuration & GBM Settings
The script is highly customizable for advanced users who want to tune the Machine Learning hyperparameters.
Prediction Horizon: How many days into the future are we trying to predict? (Default: 3).
Accuracy Lookback: How far back does the model check to calculate "Accuracy"?
GBM Learning Rate: Controls how fast the model adapts.
High (0.2+): Adapts instantly to new market conditions but may be "jumpy."
Low (0.05): Very stable, long-term adaptation.
Temperature: Controls the "Softmax" function. Higher temperatures allow for softer, more distributed weights. Lower temperatures force a "Winner Takes All" outcome.
Max Top 3 Weight: The cap on how much power the top 3 models can hold (Default: 90%).
6. Technical Nuances (For the Geeks)
Huber Gradient: We use Huber loss rather than MSE (Mean Squared Error) for the gradient descent. This is crucial for financial time series because price spikes (outliers) can destroy the learning process of standard ML models. Huber loss transitions from quadratic to linear error, making the model robust.
Regularization: L2 Regularization is applied to prevent overfitting, ensuring the model doesn't just memorize past noise.
Memory Decay: The model has a "fading memory." Recent accuracy is weighted more heavily than accuracy from 200 bars ago, allowing the system to detect Regime Shifts (e.g., transitioning from a trending market to a ranging market).
Disclaimer:
This tool is a sophisticated analytical instrument, not a crystal ball. Machine Learning attempts to optimize probabilities based on historical patterns, but no algorithm can predict black swan events or fundamental news shocks. Always use proper risk management.
The "Warmup Period" is required. The script needs to process 50 bars of history before the GBM engine initializes and produces signals.
Author's Note:
I built the MCPS because I was tired of indicators that stopped working when the market "personality" changed. By integrating GBM, this script adapts to the market's personality in real-time. If the market is cycling, Ehlers and Goertzel take over. If the market is trending, Coppock and ZLEMA take the lead. You don't have to choose—the math chooses for you.
Please leave a boost and a comment if you find this helpful!
Kalman Absorption/Distribution Tracker 3-State EKFQuant-Grade Institutional Flow: 3-State EKF Absorption Tracker
SUMMARY
An advanced, open-source implementation of a 3-State Extended Kalman Filter (EKF) designed to track institutional Order Flow. By analyzing 1-second intrabar microstructure data, this script estimates the true Position, Velocity, and Volatility of the Cumulative Volume Delta (CVD), revealing hidden Absorption and Distribution events in real-time.
INTRODUCTION: THE SIGNAL AMIDST THE NOISE
In the world of technical analysis, noise is the enemy. Traditional indicators rely on Moving Averages (SMA, EMA) to smooth out price and volume data. The problem is the "Lag vs. Noise" paradox: to get a smooth signal, you must accept lag; to get a fast signal, you must accept noise.
This indicator solves that paradox by introducing aerospace-grade mathematics to the TradingView community: The 3-State Extended Kalman Filter (EKF).
Unlike moving averages that blindly average past data, a Kalman Filter is a probabilistic state-space model. It constantly predicts where the order flow "should" be, compares it to the actual measurement, and updates its internal model based on the calculated uncertainty of the market.
This script is not just another volume oscillator. It is a full microstructure analysis engine that digests intrabar data (down to 1-second resolution) to track the true intent of "Smart Money" while filtering out the noise of retail chop.
THE INNOVATION: WHY 3 STATES?
Most Kalman Filters found in public libraries are "1-State" (tracking price only) or occasionally "2-State" (tracking price and velocity). This script introduces a highly advanced 3-State EKF.
The filter tracks three distinct variables simultaneously in a feedback loop:
State 1: Position (The True CVD)
This is the noise-filtered estimate of the Cumulative Volume Delta. It represents the actual inventory accumulation of aggressive buyers versus sellers, stripped of random noise.
State 2: Velocity (The Momentum)
This tracks the rate of change of the order flow. Is buying accelerating? Is selling pressure fading even as price drops? This provides a leading signal before the cumulative value even turns.
State 3: Volatility (The Adaptive Regime)
This is the game-changer. The filter estimates the current volatility of the order flow (Log-Volatility). In high-volatility environments (like news events), the filter automatically widens its uncertainty bands (Covariance) and reacts faster. In low-volatility environments (chop), it tightens up and ignores minor fluctuations.
THE LOGIC: DETECTING ABSORPTION AND DISTRIBUTION
The core philosophy of this indicator is based on Wyckoff Logic: Effort vs. Result.
-- Effort: Represented by the CVD (Buying/Selling pressure).
-- Result: Represented by Price Movement.
When these two diverge, we have an actionable signal. The script uses the EKF Velocity state to detect these moments:
Absorption (Bullish)
This occurs when the EKF detects high negative Velocity (aggressive selling), but Price refuses to drop. The "Smart Money" is absorbing the sell orders via limit buys. The indicator highlights this as a Blue Event in the dashboard.
Distribution (Bearish)
This occurs when the EKF detects high positive Velocity (aggressive buying), but Price refuses to rise. Limit sellers are capping the market. The indicator highlights this as an Orange Event.
TECHNICAL DEEP DIVE: UNDER THE HOOD
For the developers and quants, here is how the Pine Script is architected using the "type" and "method" features of Pine Script v5.
1. Data Ingestion (Microstructure)
The script uses "request.security_lower_tf" to pull intrabar data regardless of your chart timeframe. This allows the script to see "inside" the bar. A 5-minute candle might look green, but the microstructure might reveal that 80% of the volume was selling absorption at the wick. This script sees that.
2. Tick Classification
Standard CVD assumes that if Price Close is greater than Price Open, all volume is buying. This is often flawed. This script offers three modes of tick handling, including a "High-Low Distribution" method that statistically apportions volume based on where the tick closed relative to its high and low.
3. The EKF Mathematics
The script implements the standard Extended Kalman Filter equations manually. It calculates the Jacobian matrix to handle the non-linear relationship between volatility and price. The "Process Noise Matrix" (Q) is dynamically scaled by the Volatility State. This means the mathematics of the indicator literally "breathe" with the market conditions—expanding during expansion and contracting during consolidation.
THE DASHBOARD & VISUALS:
The indicator features a professional-grade HUD (Heads Up Display) located on the chart table.
-- EKF State Vector: Displays the real-time Position, Velocity, and Volatility values derived from the matrix.
-- Ease of Movement (Wyckoff): Calculates how much price moves per 1,000 contracts of CVD. For example, if Price moves +5 points per 1k Buy CVD, but only -2 points per 1k Sell CVD, the "Path of Least Resistance" is clearly UP.
-- Session State: Tracks cumulative confirmed Bullish vs. Bearish events for Today, Yesterday, and the Day Before (3-Day Profile).
-- Bias Summary: An algorithmic conclusion telling you if the day is "Confirmed Bullish," "Accumulating," or "Neutral."
HOW TO TRADE THIS INDICATOR
Strategy A: The Reversal (Absorption Play)
Look for price making a Lower Low.
Look for the EKF Velocity (Histogram) to be Deep Red (High Selling Pressure).
Watch the Dashboard "Absorption" count increase.
SIGNAL: When EKF Velocity crosses back toward zero and turns grey/green, the absorption is complete. This indicates sellers are exhausted and limit buyers have control.
Strategy B: The Trend Continuation (Ease of Movement)
Check the Dashboard "Ease of Movement" section.
If "Price per +1K CVD" is significantly higher than "Price per -1K CVD", buyers are efficient.
Wait for a pullback where EKF Velocity hits the "Neutral Zone" (Gray).
SIGNAL: Enter Long when Velocity ticks positive again, aligning with the dominant Ease of Movement stats.
CONFIGURATION GUIDE:
Because this is a quant-grade tool, the settings allow for fine-tuning the physics of the filter.
-- Velocity Decay: Controls how fast momentum resets to zero. Set high (0.98) for trending markets, or lower (0.85) for mean-reverting chop.
-- Volatility Persistence: Controls how "sticky" volatility regimes are.
-- Process Noise: Increase this if the filter feels too laggy; decrease it if the filter feels too jittery (noisy).
-- Measurement Noise: Increase this to trust the Mathematical Model more than the Price Data (smoother output).
WHY OPEN SOURCE?
Complex statistical filtering is often sold behind closed doors in expensive "Black Box" algorithms. By releasing this 3-State EKF open source, the goal is to raise the standard of development on TradingView.
I encourage the community to inspect the code, specifically the "ekf_update_3state" function, to understand how matrix operations can be simulated in Pine Script to create adaptive, self-correcting indicators. And also update me for improvements.
DISCLAIMER:
This tool analyzes microstructure volume data. It requires a subscription plan that supports Intrabar inspection (Premium/Pro recommended for best results). Past performance of the Kalman Filter logic does not guarantee future results. Volume analysis is subjective and should be used as part of a comprehensive strategy.
SUGGESTED SETTINGS
-- Timeframe: Works best on 1m, 3m, or 5m charts (Intrabar data is fetched from 1S).
-- Asset Class: Highly effective on Futures (ES, NQ, BTC) and high-volume Forex/Crypto pairs where volume data is reliable.
-- Background: Dark mode recommended for Dashboard visibility.
WHAT IS A KALMAN FILTER?
Imagine driving a car into a tunnel where your GPS signal is lost.
Prediction: Your car knows its last speed (Velocity) and position. It predicts where you are every second inside the tunnel.
Update: When you exit the tunnel, the GPS connects again. The system compares where it thought you were versus where the satellite says you are.
Correction: It corrects your position and updates its estimate of your speed.
Now apply this to trading:
-- The Tunnel: Market Noise, wicks, and Fake-outs.
-- The Car: The True Market Trend.
-- This Indicator: The navigation system that tells you where the market actually is, ignoring the noise of the tunnel.
Enjoy the indicator and trade safe!
Dr. Jay Desai
(Investment Management & Derivatives Area, Gujarat University)
XAUUSD 15m - Clean Signals (Anti-Spam v3)This **XAUUSD 15m – Clean Signals (Anti-Spam v3)** is a trend-aligned signal indicator built around an **EMA basis + ATR channel**. It aims to produce **fewer but cleaner** long/short prompts. A 7-EMA acts as the basis line, ATR forms inner/outer bands, and a 50-EMA provides a trend filter. By default, it uses **ADX strength filtering** plus a **confirmation candle** rule to avoid choppy conditions and weak breakouts. Signals come in three types: **DR (pullback → reversal back above/below the basis)**, **MR (pierce the inner band then reclaim it)**, and **BO (inner-band breakout, off by default due to over-triggering)**. To control frequency, it adds a **cooldown (minimum bars between signals)** and a strict **arming/reset de-duplication**: after a same-direction signal fires, it won’t fire again until price “resets” by touching the inner band or the basis (user-selectable). A “room to outer band” filter helps prevent chasing near extremes. Overall, it’s designed for disciplined 15-minute momentum-pullback entries, especially during liquid sessions like London.
Support and Resistance (High Volume Boxes) [ChartPrime]# 📑 OPERATING MANUAL: Institutional Volume & SR Protocol (v1.0)
## 1. SCOPE AND CORE LOGIC
This trading suite is designed to track **Institutional Order Flow**. By combining statistical volume anomalies (Spikes) with price zones of high participation (Boxes), the system identifies where "Smart Money" is entering the market and which price levels they are likely to defend.
---
## 2. COMPONENT OVERVIEW
### **A. Massive Order Spike Detector**
Identifies momentum and exhaustion through volume standard deviation ($σ$).
* **Green/Red Triangles:** Indicate a volume event exceeding **4x** the historical average.
* **Key Use:** Acts as a **trigger** for entry.
### **B. SR High Volume Boxes**
Maps the areas where high-volume pivots occurred.
* **Teal Boxes:** High-volume Support (Buying zones).
* **Red Boxes:** High-volume Resistance (Selling zones).
* **Diamonds (◆):** Real-time confirmation that a level is "Holding."
* **Dashed Boxes:** Indicate a level has been broken and may now "flip" polarity (Support becomes Resistance).
---
## 3. SIGNAL INTERPRETATION TABLE
| Signal Type | Visual | Market Context | Action |
| :--- | :--- | :--- | :--- |
| **Buy Spike** | 🟢 Triangle | Breakout or Trend Continuation | Confirm with Support Box |
| **Sell Spike** | 🔴 Triangle | Breakdown or Trend Exhaustion | Confirm with Resistance Box |
| **Support Hold**| 🟢 Diamond | Price successfully bounced off a Teal zone | Look for Long entry |
| **Resist. Hold**| 🟠 Diamond | Price successfully rejected from a Red zone | Look for Short entry |
| **SR Break** | 🏷️ Label | A major volume zone has been breached | Wait for Retest of dashed box |
---
## 4. OPERATIONAL WORKFLOW (THE STRATEGY)
### **Step 1: Zone Identification**
Observe the **SR High Volume Boxes** to see where the "battlefields" are.
* *Neutral:* Price is between boxes.
* *Action:* Price enters a Teal (Support) or Red (Resistance) box.
### **Step 2: The Trigger (The Spike)**
Wait for the **Massive Order Spike** to appear as the price interacts with a box:
* **The Aggressive Break:** A Spike occurs *as the price breaks through* a box. This validates a strong momentum trade.
* **The Rejection:** A Spike occurs *at the edge of a box* followed by a Diamond (◆). This validates a high-probability reversal.
### **Step 3: Confirmation (The Retest)**
If a box is broken (e.g., "Break Res"), wait for the price to return to the **Dashed Box**. If a "Hold" signal (Diamond) appears on the retest, the setup is high-conviction.
---
## 5. TECHNICAL CONFIGURATION
| Parameter | Recommended Value | Purpose |
| :--- | :--- | :--- |
| **Spike Multiplier** | 4.0 - 5.0 | Filters out noise; captures only major moves. |
| **Lookback Period** | 20 | Balances between minor and major SR levels. |
| **Box Width** | 1.0 - 1.5 | Adjust based on ATR (Volatility) of the asset. |
| **Alert Type** | Once Per Bar Close | Ensures signals are confirmed by the candle close. |
---
## 6. RISK MANAGEMENT & BEST PRACTICES
1. **News Filter:** Avoid trading 5 minutes before/after high-impact news (CPI, FOMC). Spikes are guaranteed but direction is unpredictable.
Guac's MAs, BBs, and ADX (SMA/EMA/BB + ADX/DI + Daily ATR)As someone who browses through numerous TradingView scripts, I find many ideas/functions that I find useful. However, sometimes I find certain features that I don't find useful or that could be added to make something more useful. Because of this I designed this script to collectively encompass functionality of the items/indicators I find useful when looking at an index/equity chart.
This script was desgined/inspired to keep the chart clean while providing signal context for trend, volatility, price action, and regime conditions.
Summary of what this script does:
Plots a compact, customizable set of SMAs + EMAs for structure and trend layering.
Adds Bollinger Bands with expansion/contraction coloring to visualize volatility state.
Optionally overlays ADX/DI regime context, including:
• an ADX-based “regime fill” (temperature-style colors) on the BB fill
• optional DI+ / DI- cross markers for directional shift awareness
• expanded ADX regime labels (Dead Chop → Very Strong/Extended)
• optional “ADX momentum” (smoothed ADX slope) in the status label to show regime acceleration/decay
Provides a small corner “Regime Status Label” that summarizes ADX regime (with numeric ADX) when enabled.
Optionally appends Daily ATR (value + momentum) to the same label for range/volatility context that is consistent across intraday timeframes.
I always find it frustrating when I am testing or playing with someones indicator and they don't have tooltips implemented so that I can understand the purpose of their parameters and the inputs. I have specifically tried to implement tooltip info bubbles next to every parameter input to give a short explanation of the parameter and it's purpose
Canales Pivot H y P - EXTREMOSBollinger Extremes measures the average estimated volatility during the day, compared to the closing price.
Timeframe-Independent Anchored VWAPAn anchored VWAP (Volume Weighted Average Price) that produces identical values (down to the tick!) across different timeframes (unlike, for example, TradingView's built-in Anchored VWAP).
Advantages
This indicator calculates identical values whether you view it on 1m, 5m, 15m, or any other timeframe within reasonable ranges. Even challenging non-integer timeframe ratios like calculating on 2m while viewing on 3m are handled perfectly. In High or Low mode, VWAP will anchor precisely at the selected candle's high/low. As usual for AVWAP, up to 3 standard deviation bands are supported.
How to Use
Setting the Anchor: When the indicator is added, select your anchor time. This is typically placed at a significant swing high/low or session open.
Source Selection: Choose whether to anchor from High, Low, or Close price.
Calculation Timeframe: Select the timeframe used for VWAP calculation.
For intraday trading (1m-1H charts): Just keep the default setting (1m)
For swing trading (4H-D charts): Use 5m or 15m calculation timeframe
For position trading (D-W charts): Use 1H calculation timeframe
Important: Lower calculation timeframes provide more precise data but may hit Pine Script's bar limit on very long timeframes
Standard Deviation Bands: Enable additional band sets as needed for your trading style.
Technical Implementation
The indicator achieves timeframe independence through the following algorithm:
Lower Timeframe Sampling: Uses Pine Script's request.security_lower_tf() to retrieve bar data at the specified calculation timeframe, regardless of the viewing timeframe. This provides consistent data resolution across all chart timeframes.
Anchor Detection: Scans the lower timeframe data to identify the exact bar containing the selected anchor price. The algorithm handles both simple cases (where anchor falls on a complete bar) and complex cases (where anchor falls within a split bar in non-integer timeframe ratios like calculating on 2m while viewing on 3m).
FIFO Buffer Management: Maintains a First-In-First-Out buffer of lower timeframe bars. On each chart bar:
Adds new lower timeframe bars to the buffer
Processes exactly one period worth of bars (matching the viewing timeframe)
Removes processed bars from the buffer
This approach ensures consistent calculation regardless of viewing timeframe.
First Bar Initialization: On the anchor bar, processes only the single anchor bar to ensure the VWAP starts exactly at the anchor price. Subsequent bars process the full period, maintaining mathematical accuracy.
VWAP Calculation: Applies the standard volume-weighted average price formula:
VWAP = Σ(Price × Volume) / Σ(Volume)
StdDev = √(Σ(Price² × Volume) / Σ(Volume) - VWAP²)
All calculations accumulate from the anchor point forward.
Visual Continuity: For edge cases where the anchor falls in an incomplete bar (e.g., calculating on 2m while viewing on 3m), displays the anchor price as a visual placeholder until the actual calculation begins on the next bar. This ensures the line always starts visually at the anchor point.
Multi Asset & Multi Timeframe Trend DashboardOverview
The Multi-Asset & Multi-Timeframe Trend Dashboard is a comprehensive visual data terminal designed to provide a bird's-eye view of market sentiment across five different assets and seven distinct timeframes simultaneously. By consolidating 10 core technical indicators into a single table, it eliminates the need for "chart hopping" and helps traders identify high-probability trend alignment.
How It Works
The dashboard evaluates each asset based on a Scoring System ($-10$ to $+10$). For every timeframe, the script analyzes the following 10 conditions:
Trend: EMA 20 > EMA 50Macro
Trend: EMA 50 > EMA 200
Position: Price > EMA 200
MACD: MACD Line > Signal Line
MACD Momentum: MACD Histogram > 0
RSI Momentum: RSI(14) > RSI SMA(14)
RSI Level: RSI(14) > 50
Stochastics: Stoch K > D
CCI: Commodity Channel Index > 0
Awesome Oscillator: AO > 0
Visual Logic & Features
Indicator Dots (■): Represent the 10 individual technical conditions. Green indicates a bullish state; Red indicates a bearish state.
Trend Arrows (▲/▼): Displays the aggregate directional bias of a timeframe based on the sum of the 10 dots.
Neutral State (✖): If indicators are split 50/50 (Score of 0), a grey cross is displayed to indicate total market indecision.
"ALL" Column: A macro-summary that aggregates scores across all four primary timeframes.
Volatility Marker (•): A dot appearing next to the symbol name indicates that current ATR is higher than the historical average (user-defined threshold).
Market Status Color: The symbol name background turns Green if the market is currently open and active, and Red if it is closed or stagnant.
Technical Implementation
This script utilizes request.security calls to fetch data across timeframes. To ensure performance and prevent repainting issues, all security calls are handled using the barstate.islast flag to only render the dashboard on the most recent bar.
How to Use
Alignment Trading: Look for "Full House" scenarios where all arrows (15m through Daily) are the same color.
Scalping Bias: Use the "Mini Timeframes" (1m, 3m, 5m) to find entries that align with the higher timeframe trend shown in the main table.
Volatility Filter: Only take trades when the volatility marker (•) is active to ensure there is enough "power" in the move.
KCP Ultimate Supply & Demand Zones [Dr. K.C. Prakash]📊 KCP Ultimate Supply & Demand Zones — Indicator Description
KCP Ultimate Supply & Demand Zones is a professional, non-repainting Smart Money–based indicator designed to identify high-probability institutional Supply and Demand zones with trend confirmation.
It combines price structure, volume expansion, ATR volatility, EMA 200 trend direction, and VWAP alignment to filter only the most reliable zones for intraday and positional trading.
🔑 Core Concept
Markets move due to institutional order flow, not indicators.
This tool detects where institutions likely entered the market and allows traders to trade reactions, breakouts, and retests from those zones — only in the direction of the dominant trend.
⚙️ Key Features
🔴 Supply Zones (Red)
Formed after multiple strong bearish HTF candles
Confirmed with above-average volume
Valid only when price is below EMA 200 & VWAP
Acts as sell / short / resistance zones
🟢 Demand Zones (Green)
Formed after multiple strong bullish HTF candles
Confirmed with volume expansion
Valid only when price is above EMA 200 & VWAP
Acts as buy / long / support zones
Multi Cycles Slope-Fit System MLMulti Cycles Predictive System : A Slope-Adaptive Ensemble
Executive Summary:
The MCPS-Slope (Multi Cycles Slope-Fit System) represents a paradigm shift from static technical analysis to adaptive, probabilistic market modeling. Unlike traditional indicators that rely on a single algorithm with fixed settings, this system deploys a "Mixture of Experts" (MoE) ensemble comprising 13 distinct cycle and trend algorithms.
Using a Gradient-Based Memory (GBM) learning engine, the system dynamically solves the "Cycle Mode" problem by real-time weighting. It aggressively curve-fits the Slope of component cycles to the Slope of the price action, rewarding algorithms that successfully predict direction while suppressing those that fail.
This is a non-repainting, adaptive oscillator designed to identify market regimes, pinpoint high-probability reversals via OB/OS logic, and visualize the aggregate consensus of advanced signal processing mathematics.
1. The Core Philosophy: Why "Slope" Matters:
In technical analysis, most traders focus on Levels (Price is above X) or Values (RSI is at 70). However, the primary driver of price action is Momentum, which is mathematically defined as the Rate of Change, or the Slope.
This script introduces a novel approach: Slope Fitting.
Instead of asking "Is the cycle high or low?", this system asks: "Is the trajectory (Slope) of this cycle matching the trajectory of the price?"
The Dual-Functionality of the Normalized Oscillator
The final output is a normalized oscillator bounded between -1.0 and +1.0. This structure serves two critical functions simultaneously:
Directional Bias (The Slope):
When the Combined Cycle line is rising (Positive Slope), the aggregate consensus of the 13 algorithms suggests bullish momentum. When falling (Negative Slope), it suggests bearish momentum. The script measures how well these slopes correlate with price action over a rolling lookback window to assign confidence weights.
Overbought / Oversold (OB/OS) Identification:
Because the output is mathematically clipped and normalized:
Approaching +1.0 (Overbought): Indicates that the top-weighted algorithms have reached their theoretical maximum amplitude. This is a statistical extreme, often preceding a mean reversion or trend exhaustion.
Approaching -1.0 (Oversold): Indicates the aggregate cycle has reached maximum bearish extension, signaling a potential accumulation zone.
Zero Line (0.0): The equilibrium point. A cross of the Zero Line is the most traditional signal of a trend shift.
2. The "Mixture of Experts" (MoE) Architecture:
Markets are dynamic. Sometimes they trend (Trend Following works), sometimes they chop (Mean Reversion works), and sometimes they cycle cleanly (Signal Processing works). No single indicator works in all regimes.
This system solves that problem by running 13 Algorithms simultaneously and voting on the outcome.
The 13 "Experts" Inside the Code:
All algorithms have been engineered to be Non-Repainting.
Ehlers Bandpass Filter: Extracts cycle components within a specific frequency bandwidth.
Schaff Trend Cycle: A double-smoothed stochastic of the MACD, excellent for cycle turning points.
Fisher Transform: Normalizes prices into a Gaussian distribution to pinpoint turning points.
Zero-Lag EMA (ZLEMA): Reduces lag to track price changes faster than standard MAs.
Coppock Curve: A momentum indicator originally designed for long-term market bottoms.
Detrended Price Oscillator (DPO): Removes trend to isolate short-term cycles.
MESA Adaptive (Sine Wave): Uses Phase accumulation to detect cycle turns.
Goertzel Algorithm: Uses Digital Signal Processing (DSP) to detect the magnitude of specific frequencies.
Hilbert Transform: Measures the instantaneous position of the cycle.
Autocorrelation: measures the correlation of the current price series with a lagged version of itself.
SSA (Simplified): Singular Spectrum Analysis approximation (Lag-compensated, non-repainting).
Wavelet (Simplified): Decomposes price into approximation and detail coefficients.
EMD (Simplified): Empirical Mode Decomposition approximation using envelope theory.
3. The Adaptive "GBM" Learning Engine
This is the "Machine Learning" component of the script. It does not use pre-trained weights; it learns live on your chart.
How it works:
Fitting Window: On every bar, the system looks back 20 days (configurable).
Slope Correlation: It calculates the correlation between the Slope of each of the 13 algorithms and the Slope of the Price.
Directional Bonus: It checks if the algorithm is pointing in the same direction as the price.
Weight Optimization:
Algorithms that match the price direction and correlation receive a higher "Fit Score."
Algorithms that diverge from price action are penalized.
A "Softmax" style temperature function and memory decay allow the weights to shift smoothly but aggressively.
The Result: If the market enters a clean sine-wave cycle, the Ehlers and Goertzel weights will spike. If the market explodes into a linear trend, ZLEMA and Schaff will take over, suppressing the cycle indicators that would otherwise call for a premature top.
4. How to Read the Interface:
The visual interface is designed for maximum information density without clutter.
The Dashboard (Bottom Left - GBM Stats)
Combined Fit: A percentage score (0-100%). High values (>70%) mean the system is "Locked In" and tracking price accurately. Low values suggest market chaos/noise.
Entropy: A measure of disorder. High entropy means the algorithms disagree (Neutral/Chop). Low entropy means the algorithms are unanimous (Strong Trend).
Top 1 / Top 3 Weight: Shows how concentrated the decision is. If Top 1 Weight is 50%, one algorithm is dominating the decision.
The Matrix (Bottom Right - Weight Table)
This table lifts the hood on the engine.
Fit Score: How well this specific algo is performing right now.
Corr/Dir: Raw correlation and Direction Match stats.
Weight: The actual percentage influence this algorithm has on the final line.
Cycle: The current value of that specific algorithm.
Regime: Identifies if the consensus is Bullish, Bearish, or Neutral.
The Chart Overlay
The Line: The Gradient-Colored line is the Weighted Ensemble Prediction.
Green: Bullish Slope.
Red: Bearish Slope.
Triangles: Zero-Cross signals (Bullish/Bearish).
"STRONG" Labels: Appears when the cycle sustains a value above +0.5 or below -0.5, indicating strong momentum.
Background Color: Changes subtly to reflect the aggregate Regime (Strong Up, Bullish, Neutral, Bearish, Strong Down).
5. Trading Strategies:
A. The Slope Reversal (OB/OS Fade)
Concept: Catching tops and bottoms using the -1/+1 normalization.
Signal: Wait for the Combined Cycle to reach extreme values (>0.8 or <-0.8).
Trigger: The entry is taken not when it hits the level, but when the Slope flips.
Short: Cycle hits +0.9, color turns from Green to Red (Slope becomes negative).
Long: Cycle hits -0.9, color turns from Red to Green (Slope becomes positive).
B. The Zero-Line Trend Join
Concept: Joining an established trend after a correction.
Signal: Price is trending, but the Cycle pulls back to the Zero line.
Trigger: A "Triangle" signal appears as the cycle crosses Zero in the direction of the higher timeframe trend.
C. Divergence Analysis
Concept: Using the "Fit Score" to identify weak moves.
Signal: Price makes a Higher High, but the Combined Cycle makes a Lower High.
Confirmation: Check the GBM Stats table. If "Combined Fit" is dropping while price is rising, the trend is decoupling from the cycle logic. This is a high-probability reversal warning.
6. Technical Configuration:
Fitting Window (Default: 20): The number of bars the ML engine looks back to judge algorithm performance. Lower (10-15) for scalping/quick adaptation. Higher (30-50) for swing trading and stability.
GBM Learning Rate (Default: 0.25): Controls how fast weights change.
High (>0.3): The system reacts instantly to new behaviors but may be "jumpy."
Low (<0.15): The system is very smooth but may lag in regime changes.
Max Single Weight (Default: 0.55): Prevents one single algorithm from completely hijacking the system, ensuring an ensemble effect remains.
Slope Lookback: The period over which the slope (velocity) is calculated.
7. Disclaimer & Notes:
Repainting: This indicator utilizes closed bar data for calculations and employs non-repainting approximations of SSA, EMD, and Wavelets. It does not repaint historical signals.
Calculations: The "ML" label refers to the adaptive weighting algorithm (Gradient-based optimization), not a neural network black box.
Risk: No indicator guarantees future performance. The "Fit Score" is a backward-looking metric of recent performance; market regimes can shift instantly. Always use proper risk management.
Author's Note
The MCPS-Slope was built to solve the frustration of "indicator shopping." Instead of switching between an RSI, a MACD, and a Stochastic depending on the day, this system mathematically determines which one is working best right now and presents you with a single, synthesized data stream.
If you find this tool useful, please leave a Boost and a Comment below!
Levels by EVThis indicator plots a clean set of commonly used reference levels on the chart, including the prior day high and low (PDH/PDL), the current day open (DO), prior week high and low (PWH/PWL), prior month high and low (PMH/PML).
Daily, weekly, and monthly levels are sourced from their respective higher timeframes to keep the values stable and consistent across intraday charts. Session ranges are calculated using a selectable timezone and are updated in a controlled way to avoid unnecessary object creation and chart clutter. An optional setting allows developing session highs and lows to update while the session is active, or you can keep session levels fixed once the session ends.
Use these levels as context for liquidity, support/resistance, and session structure. Labels can be enabled or disabled, and can optionally be kept on the right edge so the chart remains readable on any zoom level.
Pivots Universales 1H - H y PIt aims to measure the projected average volatility of the current day versus that of the previous day using Bollinger.
MA Zone Candle Color 8.0This indicator plots a selected moving average (any type: EMA, VWAP, HMA, ALMA, custom composites, RVWAP, etc.) and creates a symmetrical grid of horizontal levels/bands spaced at precise, predefined increments around it. The spacing between levels can be set in two modes:
Percent (%) of the current MA value
Points (fixed price units)
The available increment sizes follow a specific geometric-like sequence (very similar to Gann square-of-9 derived steps), giving you clean, repeatable distance choices such as 0.61, 1.22, 2.44, 4.88, 9.77 points (or their percentage equivalents).
Core purpose
It visually marks exactly how far price has moved away from your chosen moving average — in multiples of the increment you selected.
Main practical use cases -
1. Measuring distance from key reference level
VWAP or EMA(20–89), Points mode, 1.22–4.88 incr.
"Price is currently 3.5 increments above VWAP" → quick context for context
2. Identifying structured price levels
Points mode + 2.44 or 4.88 increment
Treat every band as potential support/resistance or target zone
3. Comparing extension size across instruments
Percent mode, same increment value across symbols
Makes extensions visually comparable (BTC vs ETH vs SPX vs NQ)
4. Session / intraday structure mapping
RVWAP or session VWAP + Points mode
See how many "steps" price has made since session open / reset
5. Setting objective take-profit / scale-out levels
Any MA + medium increment (4.88–19.53 points)
"I'll take partials at +2×, +4×, +6× increment" — very mechanical
6. Volatility-adjusted grid (crypto/forex)
Points mode with larger increments
Prevents bands from becoming too wide/narrow during huge volatility swings
Most common combo
MA: VWAP or RVWAP (session/day reset)
Mode: Points
Increment: 1.220704 or 2.441408 or 4.8828125
Bands per side: 30–60
→ Creates a clean, evenly-spaced ladder of levels around the daily/intraday average that traders can use purely for distance measurement and objective level marking.
In short:
It's a very precise, repeatable distance ruler built around any moving average you choose — nothing more, nothing less.
SA_ORB_ONR_CLOUD_vwapBandsSIGNAL ARCHITECT™ — ORB / ONR Cloud with VWAP Bands
Optimized for the 15-Minute Timeframe
Overview
The Signal Architect™ ORB / ONR Cloud is a session-structure and probability framework designed to help traders understand where price is statistically compressed, transitioning, or escaping value during the regular trading session.
On the 15-minute chart, this study excels at identifying:
High-probability consolidation zones
Early session directional intent
Fade vs continuation environments
Context for VWAP-based mean reversion or trend extension
Rather than predicting price, the indicator classifies market behavior using time-anchored ranges and volume-weighted statistics.
Core Components (15-Minute Context)
1️⃣ Overnight Range (ONR)
The Overnight Range captures price extremes formed before the regular session opens.
On the 15-minute timeframe, ONR acts as:
A higher-timeframe reference level
A source of institutional liquidity memory
A boundary where early session reactions often occur
2️⃣ Opening Range (ORB)
The Opening Range is defined as the first X minutes after the session open (default: 15 minutes).
On a 15-minute chart:
The ORB often forms entirely within a single candle
It represents initial institutional positioning
It helps differentiate initiative vs responsive behavior
3️⃣ ORB–ONR Cloud (Key Feature)
The Cloud is the overlapping area between the Overnight Range and the Opening Range.
This zone is critical on the 15-minute timeframe because it often represents:
Compressed auction
Balance / indecision
Liquidity absorption
Interpretation:
Price inside the cloud → Higher probability of consolidation, fade, or contraction
Price exiting the cloud → Transition toward expansion or trend resolution
The cloud is not a signal — it is a probability environment.
4️⃣ VWAP with Session-Weighted σ Bands
The study plots VWAP starting from the regular session open, along with true volume-weighted standard deviation bands (±1σ, ±2σ).
On the 15-minute timeframe:
VWAP defines fair value
σ bands help distinguish normal rotation vs statistical extension
Interaction with VWAP while inside the cloud often suggests mean-reverting conditions
Interaction with VWAP after leaving the cloud often confirms trend continuation
5️⃣ Breakout Classification (BRK)
A BRK event occurs when price closes outside BOTH:
The Overnight Range
The Opening Range
On the 15-minute chart:
BRK events often mark session regime changes
They are contextual markers, not entries
Arrows are color-matched to the candle (green candle → green arrow, red candle → red arrow)
To avoid clutter, breakouts can be limited to first-occurrence only.
Probability Layer (15-Minute Edge)
The indicator includes rolling probability calculations to quantify market behavior:
📊 Inside-Cloud Probability
Shows how often price remains inside the ORB–ONR cloud over the selected lookback.
Higher values → balance / compression dominant
Lower values → trend / expansion dominant
📉 Fade / Contraction Probability (Inside Cloud)
When price is inside the cloud, the study measures volatility contraction using ATR behavior.
Higher contraction % → Greater likelihood of rotation or fade
Lower contraction % → Cloud acting as launchpad rather than balance
📈 State Occupancy (5-State Model)
Tracks how price distributes its time across:
Above both ranges
Below both ranges
Inside ORB only
Inside ONR only
Inside the Cloud
This helps traders understand where the market statistically prefers to trade on the 15-minute structure.
Best Use Cases (15-Minute Chart)
✔ Contextual bias for intraday swing trades
✔ Identifying fade vs trend conditions
✔ VWAP-based execution alignment
✔ Avoiding low-probability entries inside compression
✔ Session structure awareness without lower-timeframe noise
What This Indicator Is NOT
❌ Not a buy/sell system
❌ Not predictive
❌ Not a guarantee of outcomes
It is a market structure and probability framework — designed to improve decision quality, not replace risk management.
Recommended Settings (15-Minute)
ORB Length: 15 minutes
VWAP Bands: ±1σ / ±2σ
Probability Lookback: 100–200 bars
Breakout Mode: First-occurrence only
Cloud Enabled: Yes
Risk & Compliance Notice
This tool is provided for educational and informational purposes only.
It does not constitute financial advice, investment recommendations, or trade instructions.
All trading involves risk, including the possible loss of capital.
Standalone Signal - trianchor.gumroad.com
chatgpt.com
chatgpt.com
chatgpt.com
Precision Trend Signal V5Strategy Logic OverviewThis indicator is a "Triple-Confirmation" trend-following system. It combines volume-weighted smoothing, immediate price action, and momentum filtering.1. Core ComponentsEMA 1 (The Trigger): Since the period is set to 1, this represents the raw price action. It acts as the fastest possible trigger to capture entries at the exact moment a trend shifts.SALMA (The Baseline): This is a double-smoothed moving average. It provides a stabilized support/resistance line that filters out market noise better than a standard SMA.Tillson T3 (The Trend Filter): Known for its low lag and extreme smoothness. We use this as a "Guardrail." We only take BUY signals when price is above the T3 and SELL signals when price is below it.RSI (The Momentum Filter): Ensures that we only enter a trade when there is sufficient strength ($> 50$ for Long, $< 50$ for Short).2. Signal Rules🚀 BUY SignalA green BUY label appears when:Crossover: EMA 1 crosses above the SALMA line.Trend: The current price is trading above the Tillson T3 line.Momentum: RSI is greater than 50.🔻 SELL SignalA red SELL label appears when:Crossunder: EMA 1 crosses below the SALMA line.Trend: The current price is trading below the Tillson T3 line.Momentum: RSI is less than 50.3. Execution & ManagementTake Profit (TP): Based on your preference, the suggested target is 2%.Alerts: The script includes alertcondition functions. You can set up TradingView alerts to send Webhooks to your quant infrastructure or bot, solving the "manual execution" problem you mentioned.
Price Levels [TickDaddy] just some fixes on the info box, fixed the dollar calculation between levels on agriculture products.
