RSI ProfileThis indicator shows the RSI profile from historical RSI Value and High / Low RSI Pivots.
It is inspired by the Volume Profile which is a common charting study that indicates activity at specified levels. It plots a histogram on the chart meant to identify dominant/significant levels.
This script is profiling RSI levels into a histogram, which can identify the crucial RSI values in the chart. Along with the pivot options that can help identify the dominant pivot points where RSI values had been rebounding historically.
How to use:
There are three profile types available in the settings. When selecting RSI Values, the indicator will count RSI values from history, and plot the count in a histogram at the end of the chart. If you select RSI Pivots High or RSI Pivots Low, the indicator will count only the RSI Pivot Highs and Lows and plot the count in a histogram. Users can select the Pivot Left/Right length from the settings.
Users can extend the POC line to the left, to study how the values had been reacting to POC
Please note: Since the RSi values range from 0 to 100, the indicator is rounding off the values to absolute numbers. This can cause a situation where multiple POC are identified, to find the unique POC, you can increase the width of the histogram.
The Max/Min RSI settings are for visual purposes only, it can help users shrink down the histogram's top and bottom visibility
在腳本中搜尋"volume profile"
Volume Spikes & Growing Volume Signals With Alerts & ScannerVOLUME SPIKES & GROWING VOLUME SIGNALS WITH ALERTS & SCANNER
This indicator shows arrows when there is a volume spike. It also paints the background when volume is growing. There is also a volume scanner for 8 tickers that will change color in real time when your other favorite tickers see volume growth and spikes.
You can customize the length of DMI, the number of bars to calculate the current volume average from, the number of bars back to get the overall volume average from, the multiple that needs to be hit to give a signal, the position of the scanner table and which tickers are used in the scanner. There are detailed directions as tooltips in the indicator settings you can read to understand exactly what each input does.
All features are customizable as well as which tickers the screener uses.
***HOW TO USE***
Watch for volume to pick up before placing trades as this will help you stay out of the markets when price is choppy. Volume usually brings volatility so watch for the volume signals to show up on the chart. Typically when price has made a big move one direction or is consolidating and you see the volume indicator start giving signals, the market is ready to reverse or continue its current trend but move faster in that direction.
Volume Spikes
When there is a volume spike that is larger than the average of volume over the last 100+ bars(depending on your settings) multiplied by the volume amount multiplier(in your settings) then an arrow will show up on the chart. This arrow will be green if DMI is bullish and red if DMI is bearish.
Volume Growth
A Background color will appear when the average volume over the last 5 bars(depending on your settings) is higher than the average volume over the last 100+ bars(depending on your settings) and is greater than your multiple. It will also paint the background when the volume moving average has increased over the last 3 bars consecutively. The background colors will be red or green depending on buy & sell pressure(DMI). If the background color appears, then you know volume is growing and volatility is near.
Volume Scanner
The scanner can be customized to have all of your favorite tickers by changing the tickers used in the indicator settings at the bottom. When no volume growth or spikes are detected, the ticker will show as light blue. When volume spikes or growth is detected, the ticker will turn orange to notify you.
Alerts
You can set up alerts as well when there is volume growth, bullish volume spikes and bearish volume spikes on any chart or timeframe.
Indicator Settings
Settings will need to be adjusted across different tickers as some have large swings in volume and some stay pretty even, so make sure to set up different chart layouts with settings that work for each ticker and save them individually so you don’t have to reset these values every time you switch charts.
***MARKETS***
This indicator can be used as a signal on all markets, including stocks, crypto, futures and forex as long as Tradingview has volume and DMI data for that ticker.
***TIMEFRAMES***
This volume spike indicator can be used on all timeframes as long as there is enough data for Tradingview to use for calculations.
***TIPS***
Try using numerous indicators of ours on your chart so you can instantly see the bullish or bearish trend of multiple indicators in real time without having to analyze the data. Some of our favorites are our Auto Fibonacci, Volume Profile, Momentum, Auto Support And Resistance and Money Flow Index in combination with this Volume Growth indicator. They all have real time Bullish and Bearish labels as well so you can immediately understand each indicator's trend.
Market Profile with TPOThis is is Market Profile with TPO (the letters) on the current session. Due to pinescript limitations, we are limited to 500 TPOs, since this script uses 1 label per TPO. It is NOT volume profile, this is Time Profile (Time spent at a price).
Multi Time Frame Effective Volume ProfileWHAT DOES THIS INDICATOR DO?
It is a well-known fact that volume often precedes price. As such, if you can spot an increased volume early on, you can take a position before the majority joins the trend. The purpose of this indicator is to show the tactical moves of the insiders and the big players before they become obvious to everyone. Similarly, you should more easily be able to identify trend exhaustion and look to close your position.
This volume indicator is largely inspired by Pascal Willain's concept of Effective Volume described in his book "Value in Time" , which is an improvement over Larry Williams' accumulation/distribution formula. The more robust formula takes into account two very important factors:
1) the gaps that are an inevitable part of almost all securities;
2) the closing price in relation to the spread, which indicates the bull/bear strength;
I have slightly modified Pascal Willain's formula for Effective Volume and introduced a few additional features, which I believe make the indicator easier to use and understand.
HOW DOES THE INDICATOR WORK?
1. Volume Bar Deconstruction
The first significant part of this indicator is that it deconstructs the volume bar of your current trading session into one-minute volume bars, separates the significant volume, and then reconstructs the bar again. As a result, you get a new bar, in which only the significant volume is counted. Not only this, but you also get a more comprehensive view of the relationship between buying and selling that occurred on the smaller time frame.
In the screenshot below you can see that although the bears were stronger, the bulls met them with almost identical force, which resulted in absorbing the supply in 1 and then in 2 the demand drove the price up. In a traditional volume bar chart (which is also plotted), you only see the total traded volume in either red or green depending on the closing of the bar. As you would probably agree, this does not reveal the whole story.
Accumulation/distribution by large players and funds is done with great precision, which is hard to catch intraday and nearly impossible on a daily time frame. However, large orders are hard to conceal on the 1-min chart since any unusual volume sticks out like a sore thumb. The whole idea here is for you to get a comprehensive view of what's going on in the small time frame, reveal any hard to spot transactions, and then make an informed decision on your trading time frame.
To ease your analysis even further, the indicator shows you minor volume as a percent of the major volume . Since your current time frame volume bar is a sum of all buying and selling volume from a smaller time frame, you get to see a more complete picture of the buying and selling that occurred. For example, you have a total volume of 150 BTC in a single 1h volume bar, out of which 100 BTC is in selling volume and 50 BTC is in buying volume. What you will see as parameters are this: 50 (buying volume), 100 (selling volume), 50 (minor volume as a percent of the big volume, since 50/100 = 0.5 = 50%). The higher the percentage, the more even the powers between buying and selling are.
2. Volume Trend
Building upon the first feature of the indicator, you can also choose a cumulative volume trend line. It is constructed by evaluating the type of the significant volume - adding it up if the bar closes positive (green) and subtracting it if the bar closes negative (red). The evaluation is once again done on a 1-min time frame by default, but you can change that along with the count lookback period in settings.
3. Bull / Bear Equilibrium
Based upon the volume bars, Bull/Bear Equilibrium shows you the difference between buying and selling pressure under the form of a smoothed histogram. It is particularly useful not only for spotting trends early in the beginning, but also when those trends start reaching a point of exhaustion. You can then move your Stop Loss accordingly, close part of your position to preserve profits, or even look for a good entry position in the opposite direction.
HOW MUCH DOES THE INDICATOR COST ?
As much as I would like to offer it for free (as some of my other ones), a great deal of work, trading logic, and testing have gone into creating this indicator. More than a few hundred iterations and a few dozen branches were required to reach the end result which is a precise combination of usefulness, simplicity, and practicality. Furthermore, this indicator will continue to be updated and user-requested features that improve its performance will be added.
Disclaimer: The purpose of all indicators is to indicate potential setups, which may lead to profitable results. No indicator is perfect and certainly, no indicator has a 100% success rate. They are subject to flaws, wrongful interpretation, bugs, etc. This indicator makes no exception. It must be used with a sound money management plan that puts the main emphasis on protecting your capital. Please, do not rely solely on any single indicator to take trading decisions instead of you. Indicators are storytellers, not fortune tellers . They help you see the bigger picture, not the future.
To find out more about how to gain access to this indicator, please use the provided information below or just message me. Thank you for your time.
Cumulative Overlapping Volume BarsThis is cheap replacement for volume profile.
Red bars is where accumulated high volume in small range.
if new bar moves out of range all accumulated volume will be lost and color will change.
Delta Volume Columns [LucF]Displays delta volume columns using intrabar volume information. Each volume column is divided into three sections: buying, selling and neutral volume. Volume for each section is determined from the volume and price movement of each intrabar at a user-selected lower resolution.
Features include:
- Choice of color themes for either dark or light chart backgrounds
- Delta volume columns
- Volume Balance displayed as the difference between the MAs of buying and selling volume
- Display of divergences between a bar’s volume balance and the bar’s price movement (example: buying volume > selling volume but close < open). Divergences can be shown in 2 different color schemes (including green/red showing a tentative direction), on volume columns and/or on chart bars
- Display of bar by bar volume balance with highlighting of above average volume
- Display of the usual total volume MA
- Choice of the lower resolution used to retrieve intrabar information
- Alerts configurable on any combination of the markers, with control over long/short direction
- Choice of 3 different markers:
1. Double bumps: two consecutive bars where buying or selling volume is in the same direction and where volume > volume MA
2. Divergence confirmations: direction of the price bar following a price/volume balance divergence
3. Volume balance shifts: zero level crossings of the volume balance MA delta
The chart shows the two main modes of display:
- Top pane : shows the stacked volume columns with divergences in orange and the flattened volume balance MAs delta at the bottom of the volume columns. This volume balance is the same shown in the bottom pane. The top pane also shows the instant volume balance strip above the volume columns. The strip’s colors show which of the buying or selling volume was greater, and colors are brighter if the total volume was above the total volume MA.
- Bottom pane : shows the volume balance MAs delta with markers 1 and 2. Given that this graphic has no price momentum component, I find quite eerie how it often looks like a momentum-based signal.
The default 5 minute intrabar resolution is used in combination with the weekly chart, which is excessive.
This script uses a special characteristic of the security() function’s behavior when it is sent to a resolution lower than the chart’s resolution. Details are given in the script’s comments. This method has the advantage of working under more circumstances than some of the other loop-based methods, but it also has its limits.
IMPORTANT
This is what you need to know:
- The method used does not work on the realtime bar—only on historical bars. Consequently, the volume column shown on the realtime bar is a normal volume column plotted in green or red, following price movement. The column will only show delta volume information after it closes and becomes a historical bar.
- The indicator only works on some chart resolutions: 5, 10, 15 and 30 minutes, 1, 2, 4, 6, and 12 hours, 1 day, 1 week and 1 month. The script’s code can be modified to run on other resolutions, but chart resolutions must be divisible by the lower resolution used for intrabars.
- Intrabar resolutions can be selected from 1, 5, 15, 30, 45 minutes, 1, 2, 3, 4 hours, 1 day, 1 week and 1 month. The intrabar resolution must of course be smaller than the chart’s resolution.
- Contrary to my other indicators where alerts must be configured to trigger “Once Per Bar Close” in order to avoid false triggers (or repainting), all this indicator’s alerts are designed to trigger using previous bar information since the indicator’s calculations in the realtime bar are not exact. Markers are not plotted with a negative offset; they appear at the beginning of the realtime bar following confirmation of the marker’s condition on the previous bar. Alerts for this indicator should thus be configured to trigger “Once Per Bar” so they trigger at the beginning of the realtime bar. Note that the penalty is not that great, as it is simply the instant between the close of the previous realtime bar and the opening of the next. The advantage of using this technique is that the indicator does not repaint; a marker that appears at the beginning of the realtime bar will never disappear.
- The script only plots information that is reliable in the realtime bar, i.e., total volume and markers. All other plots are set to n/a to prevent misleading traders.
- When the difference between the chart’s resolution and the lower resolution is too important, volume columns will not calculate for all bars in the dataset.
On Delta Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by 2 different traders. There is no such thing as “buy only” or “sell only” volume, but trader lingo is riddled with original fabulations.
Without access to order book information, traders work with the assumption that when price moves up during a bar, there was more buying pressure than selling pressure. The built-in volume indicator available on TradingView uses this logic to color the volume columns green or red. While this script’s numbers are more precise because it analyses a number of intrabars to calculate its information, it uses the exact same imperfect logic to calculate its buying/selling/neutral sections.
Until Pine scripts can have access to how much volume was transacted at the bid/ask prices, our so-called buying/selling volume information will always be a mere proxy.
Divergences
You may wonder how there can be divergences between buying/selling volume information and price movement. This will sometimes be due to the methodology’s shortcomings we have just discussed, but divergences may also occur in instances where because of order book structure, it takes less volume to increase the price of an asset than it takes to decrease it.
As usual, divergences are points of interest because they reveal imbalances, which may or may not become turning points. I do not share the overwhelming enthusiasm traders have for divergences. To your pattern-hungry brain, the orange bars this indicator shows on chart will—as divergences on other indicators do–appear to often indicate turnarounds. My opinion is that reality is generally quite sobering, as many who have tried building automated rules based on divergences will tell you. I do not have hard numbers on the lack of performance of divergences—only many failed attempts to make them perform, which a few experienced strategy modelers I know share with me. Please don’t try to read too much into them. While they look great on past data, I find they are often difficult to use in realtime to make bets with good odds.
Thanks to:
- A guy called Kuan who commented on a Backtest Rookies presentation of an intrabar delta volume indicator using a for loop. The heart of “my” indicator is code borrowed from Kuan; I just built a hopefully useful wrapper around it.
- @theheirophant, my partner in the exploration of the sometimes weird abysses of security() ’s behavior at lower resolutions.
YBL – Order Flow Bubbles + Alerts (Imbalance, Anchored)**YBL – Order Flow Bubbles + Alerts (Imbalance, Anchored)**
by **YBL / Yuriel**
This tool paints **order flow “bubbles”** directly on the price chart whenever there is a strong **aggressive buy or sell imbalance**, using only OHLCV data (no real bid/ask feed required).
The script estimates delta from **price change × volume**, normalizes it with a **z-score**, and then draws visual bubbles on the candles where the imbalance is strong enough.
---
## 🔍 Core Logic (How It Works)
1. **Delta estimation (no bid/ask feed needed)**
- `delta = (close - open) * volume`
- If price closes above open → delta > 0 (buy aggression).
- If price closes below open → delta < 0 (sell aggression).
2. **Volatility / Z-score filter**
- Moving averages over **lenDelta**:
- `avgVol = SMA(volume)`
- `avgDelta = SMA(delta)`
- `stDelta = stdev(delta)`
- Z-score:
- `deltaZ = (delta - avgDelta) / stDelta`
- Only bars where:
- Volume is above `minVolMul × avgVol`
- |deltaZ| is above `zTrigger`
are considered **strong aggression bubbles**.
3. **Direction detection**
- **Buy bubble** = `delta > 0` with strong z-score and enough volume.
- **Sell bubble** = `delta < 0` with strong z-score and enough volume.
---
## 🎨 Visuals on the Chart
- **Bubbles (labels)**
- Green bubbles for **buy aggression**.
- Red bubbles for **sell aggression**.
- Bubble **size is dynamic** → based on `vol / avgVol`:
- Tiny / Small / Normal / Large / Huge depending on the volume ratio.
- Text inside the bubble (optional):
- Shows `Δ` in **K units** (e.g. `+35.2K`).
- Controlled by `Mostrar Δ (K) dentro de la burbuja`.
- **Anchoring options**
- `Anclaje de burbuja`:
- **“Extremos (Hi/Lo)”** →
- Buy bubbles anchored near **low + ATR offset**.
- Sell bubbles anchored near **high − ATR offset**.
- **“Centro (Mid)”** →
- Bubbles at the **midpoint** of the candle.
- ATR offset is defined by:
- `ATR para offset` (atrLen)
- `Offset = ATR ×` (atrMul)
- **Background shading (heatmap)**
- When a very strong **buy imbalance** appears → chart background tinted **light lime**.
- When a very strong **sell imbalance** appears → background tinted **light red**.
- Helps visually detect clusters of aggressive buying or selling.
- **Tooltips**
- Each bubble includes a tooltip with:
- `Δ` (raw delta)
- `z` (z-score of delta)
- % of volume vs average (Vol%)
---
## ⚙️ Inputs (Settings Overview)
### Group “Cálculo”
- **Longitud media/volatilidad (z-score)** (`lenDelta`)
Lookback for average volume, delta and standard deviation.
- **Umbral z-score desequilibrio fuerte** (`zTrigger`)
Higher = fewer but stronger signals.
- **Volumen mínimo (× promedio)** (`minVolMul`)
Minimum volume relative to average volume.
### Group “Dibujo”
- **Transparencia burbujas (0=opaco)**
Controls how strong the color of the bubbles is.
- **Mostrar Δ (K) dentro de la burbuja**
Toggle on/off the text inside the bubbles.
- **Tamaño del TEXTO**
tiny / small / normal / large / huge.
- **Anclaje de burbuja**
- “Extremos (Hi/Lo)” → buy near low, sell near high.
- “Centro (Mid)” → bubble in the middle of the bar.
- **ATR para offset** / **Offset = ATR ×**
Fine-tune vertical offset relative to high/low.
---
## 📢 Alerts
The script includes ready-to-use **alerts**:
1. **BUY Aggression Bubble**
- Triggered when a strong **buy imbalance** appears (green bubble).
- Message includes ticker, timeframe and close.
2. **SELL Aggression Bubble**
- Triggered when a strong **sell imbalance** appears (red bubble).
- Message includes ticker, timeframe and close.
Use these alerts to catch:
- Sudden bursts of **aggressive buying** at lows or pullbacks.
- Sudden bursts of **aggressive selling** at highs or after rallies.
- Potential **reversal** or **continuation** points based on flow.
---
## 🧠 How to Use (Practical Ideas)
- Combine this script with:
- **VWAP**, volume profile, liquidity pools or CVD.
- Your own session filters (e.g. NY open, London open).
- Look for:
- **Clusters of green bubbles** at support / VWAP → potential accumulation.
- **Clusters of red bubbles** at resistance / previous highs → possible distribution.
- Breakouts where the candle is supported by **large same-direction bubbles**.
It works especially well on:
- **1m / 5m** charts for scalping and intraday.
- Futures, indices, FX and crypto where volume is reliable.
---
## ⚠️ Disclaimer
This script is for **educational purposes only** and does **not** constitute financial advice.
Always backtest and use proper risk management before trading live.
---
© YBL / Yuriel – “YBL – Order Flow Bubbles + Alerts (Imbalance, Anchored)”
If you find this useful, please **leave a like ⭐ and add it to your favorites.**
YM Ultimate SNIPER v5# YM Ultimate SNIPER v5 - Documentation & Trading Guide
## 🎯 Unified GRA + DeepFlow | YM/MYM Optimized
**TARGET: 3-7 High-Confluence Trades per Day**
---
## ⚡ QUICK START
```
┌─────────────────────────────────────────────────────────────────┐
│ YM ULTIMATE SNIPER v5 │
├─────────────────────────────────────────────────────────────────┤
│ │
│ SIGNALS: │
│ S🎯 = S-Tier (50+ pts) → HOLD position │
│ A🎯 = A-Tier (25-49 pts) → SWING trade │
│ B🎯 = B-Tier (12-24 pts) → SCALP quick │
│ Z = Zone entry (price at FVG zone) │
│ │
│ SESSIONS (ET): │
│ LDN = 3:00-5:00 AM (London) │
│ NY = 9:30-11:30 AM (New York Open) │
│ PWR = 3:00-4:00 PM (Power Hour) │
│ │
│ COLORS: │
│ 🟩 Green zones = Bullish FVG (buy zone) │
│ 🟥 Red zones = Bearish FVG (sell zone) │
│ 🟣 Purple lines = Single prints (S/R levels) │
│ │
│ TABLE (Top Right): │
│ Pts = Candle point range │
│ Tier = S/A/B/X classification │
│ Vol = Volume ratio (green = good) │
│ Delta = Buy/Sell dominance │
│ Sess = Current session │
│ Zone = In FVG zone status │
│ Score = Confluence score /10 │
│ CVD = Cumulative delta direction │
│ R:R = Risk:Reward ratio │
│ │
└─────────────────────────────────────────────────────────────────┘
```
---
## 📋 VERSION 5 CHANGES
### What's New
- **Removed all imbalance code** - caused compilation errors
- **Simplified delta analysis** - uses candle structure instead of intrabar data
- **Cleaner confluence scoring** - 5 clear factors, max 10 points
- **Reliable table** - updates on last bar only, no flickering
- **Works on YM and MYM** - same logic applies to micro contracts
### Removed Features
- Candle-anchored imbalance markers
- Imbalance S/R zones
- Intrabar volume profile analysis
- POC visualization
### Kept & Improved
- Tier classification (S/A/B)
- FVG zone detection & visualization
- Single print detection
- Session windows with backgrounds
- Confluence scoring
- Stop/Target auto-calculation
- All alerts
---
## 🎯 SIGNAL TYPES
### Tier Signals (S🎯, A🎯, B🎯)
These are high-confluence signals that pass all filters:
| Tier | Points | Value/Contract | Action | Hold Time |
|------|--------|----------------|--------|-----------|
| **S** | 50+ | $250+ | HOLD | 2-5 min |
| **A** | 25-49 | $125-245 | SWING | 1-3 min |
| **B** | 12-24 | $60-120 | SCALP | 30-90 sec |
**Filters Required:**
1. Tier threshold met (points)
2. Volume ≥ 1.8x average
3. Delta dominance ≥ 62%
4. Body ratio ≥ 70%
5. Range ≥ 1.3x average
6. Proper wicks (no reversal wicks)
7. CVD confirmation (optional)
8. In trading session
### Zone Signals (Z)
Zone entries trigger when:
- Price is inside an FVG zone
- Delta shows dominance in zone direction
- Volume is above average
- In active session
- No tier signal already present
---
## 📊 CONFLUENCE SCORING
**Maximum Score: 10 points**
| Factor | Points | Condition |
|--------|--------|-----------|
| Tier | 1-3 | B=1, A=2, S=3 |
| In Zone | +2 | Price inside FVG zone |
| Strong Volume | +2 | Volume ≥ 2x average |
| Strong Delta | +2 | Delta ≥ 70% |
| CVD Momentum | +1 | CVD trending with signal |
**Score Interpretation:**
- **7-10**: Elite setup - full size
- **5-6**: Good setup - standard size
- **4**: Minimum threshold - reduced size
- **< 4**: No signal shown
---
## ⏰ SESSION WINDOWS
### London (3:00-5:00 AM ET)
- European institutional flow
- Character: Slow build-up, clean trends
- Expected trades: 1-2
- Best for: Zone entries, A/B tier
### NY Open (9:30-11:30 AM ET)
- Highest volume, most institutional activity
- Character: Initial balance, breakouts
- Expected trades: 2-3
- Best for: S/A tier, zone confluence
### Power Hour (3:00-4:00 PM ET)
- End-of-day rebalancing, MOC orders
- Character: Mean reversion or trend acceleration
- Expected trades: 1-2
- Best for: Zone entries, B tier scalps
---
## 🟩 FVG ZONES
### What Are FVG Zones?
Fair Value Gaps (FVGs) are price gaps between candles where price moved so fast that a gap was left. These gaps often act as support/resistance.
### Zone Requirements
- Gap size ≥ 25% of ATR
- Impulse candle has strong body (≥ 70%)
- Impulse candle is 1.5x average range
- Volume above average on impulse
- Created during active session
### Zone States
1. **Fresh** (bright color) - Just created, untested
2. **Tested** (gray) - Price touched zone midpoint
3. **Broken** (removed) - Price closed through zone
### Trading FVG Zones
| Zone | Approach From | Expected |
|------|--------------|----------|
| 🟩 Bull | Above (falling) | Support - look for bounce |
| 🟥 Bear | Below (rising) | Resistance - look for rejection |
---
## 🟣 SINGLE PRINTS
Single prints mark candles with:
- Range > 1.3x average
- Body > 70% of range
- Volume > 1.8x average
- Clear delta dominance
These become horizontal support/resistance lines extending into the future.
---
## 📊 TABLE REFERENCE
| Row | Label | Meaning |
|-----|-------|---------|
| 1 | Pts | Current candle point range |
| 2 | Tier | S/A/B/X classification |
| 3 | Vol | Volume ratio vs 20-bar average |
| 4 | Delta | Buy/Sell percentage dominance |
| 5 | Sess | Current session (LDN/NY/PWR/OFF) |
| 6 | Zone | In FVG zone (BULL/BEAR/---) |
| 7 | Score | Confluence score out of 10 |
| 8 | CVD | Delta momentum direction |
| 9 | R:R | Risk:Reward if signal active |
### Color Coding
- **Green/Lime**: Good, meets threshold
- **Yellow**: Caution, borderline
- **Red**: Bad, below threshold
- **Gray**: Inactive/neutral
---
## 🔧 SETTINGS GUIDE
### Tier Thresholds
| Setting | Default | Notes |
|---------|---------|-------|
| S-Tier | 50 pts | ~$250/contract |
| A-Tier | 25 pts | ~$125/contract |
| B-Tier | 12 pts | ~$60/contract |
### Sniper Filters
| Setting | Default | Notes |
|---------|---------|-------|
| Min Volume Ratio | 1.8x | Lower = more signals |
| Delta Dominance | 62% | Lower = more signals |
| Body Ratio | 70% | Higher = fewer, cleaner |
| Range Multiplier | 1.3x | Higher = fewer, bigger moves |
| CVD Confirm | On | Off = more signals |
### Recommended Configurations
**Conservative (3-4 trades/day):**
```
Min Confluence: 6
Volume Ratio: 2.0
Delta Threshold: 65%
Body Ratio: 75%
```
**Standard (5-7 trades/day):**
```
Min Confluence: 4
Volume Ratio: 1.8
Delta Threshold: 62%
Body Ratio: 70%
```
**Aggressive (7-10 trades/day):**
```
Min Confluence: 3
Volume Ratio: 1.5
Delta Threshold: 60%
Body Ratio: 65%
```
---
## ✓ ENTRY CHECKLIST
Before entering any trade:
1. ☐ Signal present (S🎯, A🎯, B🎯, or Z)
2. ☐ Session active (LDN, NY, or PWR)
3. ☐ Score ≥ 4 (preferably 6+)
4. ☐ Vol shows GREEN
5. ☐ Delta colored (not gray)
6. ☐ CVD arrow matches direction
7. ☐ Note stop/target lines
8. ☐ Execute at signal candle close
---
## ⛔ DO NOT TRADE
- Session shows "OFF"
- Score < 4
- Vol shows RED
- Delta gray (no dominance)
- Multiple conflicting signals
- Major news imminent (FOMC, NFP, CPI)
- Overnight session (11:30 PM - 3:00 AM ET)
---
## 🎯 POSITION SIZING
| Tier | Score | Size | Stop |
|------|-------|------|------|
| S (50+ pts) | 7+ | 100% | Below/above candle |
| A (25-49 pts) | 5-6 | 75% | Below/above candle |
| B (12-24 pts) | 4 | 50% | Below/above candle |
| Zone | Any | 50% | Beyond zone |
---
## 🚨 ALERTS
### Priority Alerts (Set These)
| Alert | Action |
|-------|--------|
| 🎯 S-TIER | Drop everything, check immediately |
| 🎯 A-TIER | Evaluate within 15 seconds |
| 🎯 B-TIER | Check if available |
| 🎯 ZONE | Good context entry |
### Info Alerts (Optional)
| Alert | Purpose |
|-------|---------|
| NEW BULL/BEAR FVG | Mark zones on mental map |
| SINGLE PRINT | Note for future S/R |
| SESSION OPEN | Prepare to trade |
---
## 📈 TRADE JOURNAL
```
DATE: ___________
SESSION: ☐ LDN ☐ NY ☐ PWR
TRADE:
├── Time: _______
├── Signal: S🎯 / A🎯 / B🎯 / Z
├── Direction: LONG / SHORT
├── Score: ___/10
├── Entry: _______
├── Stop: _______
├── Target: _______
├── In Zone: ☐ Yes ☐ No
├── Result: +/- ___ pts ($_____)
└── Notes: _______________________
DAILY:
├── Trades: ___
├── Wins: ___ | Losses: ___
├── Net P/L: $_____
└── Best setup: _______________________
```
---
## 🏆 GOLDEN RULES
> **"Wait for the session. Off-hours = noise."**
> **"Score 6+ is your edge. Anything less is gambling."**
> **"Zone + Tier = bread and butter combo."**
> **"One great trade beats five forced trades."**
> **"Leave every trade with money. YM gives you time."**
---
## 🔧 TROUBLESHOOTING
| Issue | Solution |
|-------|----------|
| No signals | Lower min score to 3-4 |
| Too many signals | Raise min score to 6+ |
| Zones cluttering | Reduce max zones to 8 |
| Missing sessions | Check timezone setting |
| Table not updating | Resize chart or refresh |
---
## 📝 TECHNICAL NOTES
- **Pine Script v6**
- **Works on**: YM, MYM, any Dow futures
- **Recommended TF**: 1-5 minute for day trading
- **Min TradingView Plan**: Free (no intrabar data required)
---
*© Alexandro Disla - YM Ultimate SNIPER v5*
*Clean Build | Proven Components Only*
Accumulation/Distribution Oscillator# Short description
A clean, volume-weighted Accumulation/Distribution Oscillator (ADO) that highlights buying/selling pressure by comparing cumulative AD to its EMA — ideal for confirming trends, spotting divergences, and timing entries with volume context.
# Full description
**Overview**
The Accumulation/Distribution Oscillator (ADO) measures the relationship between price and volume by taking a cumulative Accumulation/Distribution value and subtracting its exponential moving average. The resulting oscillator emphasizes recent shifts in accumulation (buying) and distribution (selling), making it easier to spot momentum changes and volume-driven confirmations or divergences.
**How it works (brief)**
* Computes the standard accumulation/distribution contribution each bar using price position within the range and multiplies it by volume.
* Builds a cumulative AD series and smooths it with an EMA.
* The oscillator = cumulative AD − EMA(cumulative AD). Positive values indicate rising accumulation relative to the trend, negative values indicate rising distribution.
**Inputs**
* `length` — EMA smoothing period (default: 20). Adjust to tune sensitivity: lower values = faster signals, higher values = smoother trend.
**Interpretation & signals**
* **Above zero**: recent accumulation momentum — bullish bias.
* **Below zero**: recent distribution momentum — bearish bias.
* **Crosses of zero**: simple entry/exit trigger (cross above = potential long, cross below = potential short).
* **Divergences**: price making new highs while ADO fails to make new highs → bearish divergence (sell signal). Price making new lows while ADO fails to make new lows → bullish divergence (buy signal).
* **Slope and magnitude**: steep, growing positive readings suggest strong buying pressure; steep, growing negative readings suggest strong selling pressure.
**Suggested usage**
* Use ADO to confirm breakout strength: a price breakout with ADO rising above zero has higher probability.
* Combine with trend filters (e.g., moving averages) to trade in the direction of the main trend.
* Use divergence with price action or candles for higher-probability reversal setups.
* Best applied on intraday and swing timeframes where volume data is reliable. May be less effective on low-volume or synthetic data.
**Alert examples (copy into TradingView alert message)**
* `ADO Bullish: Oscillator crossed above 0`
* `ADO Bearish: Oscillator crossed below 0`
* `ADO Momentum Up: Oscillator turned positive and rising`
* `ADO Divergence: Price made new high but ADO did not — check for potential reversal`
**Practical tips**
* Shorten `length` (e.g., 8–12) for more responsive signals on lower timeframes; lengthen (e.g., 30–50) for smoother, long-term signals.
* Confirm signals with volume profile or volume spike filters to avoid false breakouts.
* Always validate with support/resistance and manage risk with stops sized to your strategy.
**Disclaimer**
This indicator is a technical tool intended to assist analysis — not a standalone trading system. Backtest and paper-trade any strategy before using real capital. The author and publisher are not responsible for trading outcomes.
DTR Volume FVGDTR Volume FVG detects bullish and bearish Fair Value Gaps and shows how much volume occurred inside each gap. Instead of only drawing the imbalance, the indicator analyzes a lower timeframe and builds a small volume profile inside every FVG. This helps you understand which gaps are strong, weak, likely to hold, or likely to fill.
How It Works:
- The indicator finds FVGs using a lower timeframe (Auto mode or manual selection).
- Each FVG is drawn as a colored zone: green for bullish, purple for bearish.
- Inside the gap, the script shows volume distribution using horizontal boxes.
- The FVG extends forward in time until the gap is fully filled or invalidated.
- Once price closes through the gap, the zone is removed automatically.
How to Use:
- High volume inside the FVG suggests strong interest and possible support or resistance.
- Low volume suggests the gap may fill more easily.
- Bullish FVGs are used as retracement zones in uptrends.
- Bearish FVGs are used as retracement zones in downtrends.
- Use the Display option to hide the volume boxes if you want a cleaner chart.
Best For:
- Finding strong retracement zones
- Identifying which gaps matter
- Understanding how price and volume behaved during displacement
- Improving entries and stop placement with volume levels inside FVGs
This indicator gives a clearer view of which imbalances are important by combining FVG structure with real volume data.
detecteur de volume 🎯 Main Objective
This script analyzes Open Interest (open positions) calculated simply as Volume ÷ 2 and detects significant variations to identify important market movements.
🔧 How It Works
1. Open Interest Calculation
Open Interest = Bar Volume / 2
Each trading candle has a volume
The script divides this volume by 2 to get OI
OI approximately represents open positions in the market
2. Variation Calculation
Variation % = ((Current OI - Previous OI) / Previous OI) × 100
Compares current bar's OI to the previous bar
Expresses the result as a percentage
Example: If OI goes from 1000 to 1300 → Variation = +30%
📊 Visualization Modes
The script offers 3 modes to choose from:
Mode 1: "Open Interest Brut" (Raw Open Interest)
Displays an OI curve
Green color when OI rises
Red color when OI falls
Option to add a moving average (orange) to see the trend
Mode 2: "Variation %" (RECOMMENDED)
Displays bars showing % variation
Green bars = increases
Red bars = decreases
Reference lines at +25%, -25% and 0%
Easier to read for detecting movements
Mode 3: "Les Deux" (Both)
Combines both charts
Complete view but more crowded
🚨 2-Level Alert System
Level 1: Labels - 25% Threshold
Trigger: Variation ≥ 25% or ≤ -25%
Display: Label with exact percentage
"↑ +32.5%" (green) for an increase
"↓ -28.3%" (red) for a decrease
Purpose: Signal notable movements
Level 2: Triangles - 200% Threshold
Trigger: Variation ≥ 200% or ≤ -200%
Display:
🔺 GREEN Triangle (pointing up) = Extreme increase
🔻 RED Triangle (pointing down) = Extreme decrease
Purpose: Signal exceptional and rare movements
⚙️ Adjustable Parameters
ParameterDefaultDescriptionType de Visualisation"Variation %"Choose how to display dataSeuil de Variation25%When to show labelsSeuil pour Triangles200%When to show trianglesAfficher les FlèchesYESEnable/disable labels and trianglesAfficher Moyenne MobileYESAdd a trend linePériode Moyenne Mobile20Number of bars for the average
📈 Information Table
Top right corner of the chart:
RowInformationOpen InterestCurrent OI valueVariation% change (green/red depending on direction)SignalCurrent state: "↑ HAUSSE", "↓ BAISSE" or "Normal"
🔔 TradingView Alerts
The script generates 4 types of alerts:
🟢 Hausse OI > 25% - Normal increase alert
🔴 Baisse OI > 25% - Normal decrease alert
🚨🟢 STRONG ALERT: Increase > 200% - Exceptional upward movement
🚨🔴 STRONG ALERT: Decrease > 200% - Exceptional downward movement
💡 Signal Interpretation
Variations > 25% (Labels)
Indicate increased interest in the asset
Increase: More open positions → Possible upcoming movement
Decrease: Position closures → Possible reversal
Variations > 200% (Triangles)
VERY RARE and POWERFUL signal
Indicates a major event or anomaly
May precede significant price movements
Requires immediate verification
🎨 Color Code
🟢 Green = Increase, positive, buy
🔴 Red = Decrease, negative, sell
🟠 Orange = Moving average (trend)
🟣 Purple = Variation % line
⚪ Gray = 0% reference line
📌 Use Cases
For Day Trading
"Variation %" mode on 5min or 15min timeframe
Detect volume/OI spikes in real-time
Triangles = Exceptional opportunities
For Swing Trading
"Open Interest Brut" mode with moving average
1H or 4H timeframe
Follow the general OI trend
For Screening
Use alerts on multiple assets
Triangles signal "hot" assets
Labels to monitor general activity
⚠️ Limitations
OI = Volume/2 is an approximation
Real Open Interest requires specific data (futures/options)
This formula works but remains an estimate
No real OI history
Only calculates on available volume
Doesn't account for accumulated OI from previous days
Sensitivity to gaps
A volume gap can create false signals
Should be used with other indicators
✅ Strengths
✅ Simple and effective
✅ Works on all markets (stocks, crypto, forex, futures)
✅ Automatic detection of abnormal movements
✅ Configurable alerts
✅ Clear and intuitive visual
✅ Lightweight and fast (no complex calculations)
🎓 Usage Tips
Start with "Variation %" mode - More readable
Adjust thresholds to your style - 25% may be too sensitive on some assets
Combine with price analysis - OI alone isn't enough
Watch the triangles - These are the most important signals
Create alerts - To catch everything even off-screen
🔍 Technical Breakdown
Core Components:
1. Data Collection
Pulls volume data from each bar
Calculates OI as volume divided by 2
Stores previous bar's OI for comparison
2. Mathematical Processing
Computes percentage change between bars
Applies smoothing with optional moving average
Identifies threshold crossings (25% and 200%)
3. Visual Output
Plots OI curve or variation bars
Conditionally displays based on selected mode
Uses dynamic coloring (green/red) based on direction
4. Signal Generation
Boolean logic for threshold detection
Separate signals for labels and triangles
Triggers alerts when conditions are met
📊 Advanced Features
Multi-Mode Display
The script uses conditional plotting with na (not available) values to show/hide elements:
When "OI Brut" is selected → variation plot receives na
When "Variation %" is selected → OI plot receives na
When "Les Deux" is selected → both plots display
Dynamic Coloring
Colors update in real-time based on:
Current vs. previous bar comparison
Positive variations → green spectrum
Negative variations → red spectrum
Smart Labeling
Labels position automatically:
Above bar for decreases (yloc.abovebar)
Below bar for increases (yloc.belowbar)
Adapts to selected visualization mode
🎯 Best Practices
For Optimal Performance:
Timeframe Selection
Lower timeframes (1m-15m): More signals, more noise
Higher timeframes (1H-1D): Fewer but more reliable signals
Threshold Adjustment
Volatile assets: Increase thresholds (30%/250%)
Stable assets: Decrease thresholds (20%/150%)
Test different values to find your sweet spot
Combining Indicators
Use with volume profile
Pair with RSI for confirmation
Check price action before acting on signals
Alert Management
Set alerts only for triangles on multiple assets
Use label alerts for assets you actively monitor
Avoid alert fatigue by being selective
🚀 Performance Notes
Lightweight: Minimal CPU usage
Fast execution: Simple calculations only
Real-time updates: Instant signal detection
Low latency: No API calls or external data
Universal compatibility: Works on all TradingView plans
There you go! You now have a powerful tool to detect abnormal Open Interest movements. The two-level system (25% and 200%) allows you to filter noise and focus on what really matters. 🚀
Hammer Model [#]Hammer Model - HTF Candle Entry Model
Overview
The Hammer Model is a sophisticated technical indicator that identifies high-probability reversal setups based on Higher Timeframe (HTF) candlestick wick rejection patterns. Unlike traditional hammer pattern indicators that simply flag candle formations, this system provides a complete trading framework with precise entry zones, stop loss placement, and multiple take profit targets calculated using statistical projections.
What Makes This Different
Proprietary Signal Filtering: This indicator uses a proprietary algorithm that analyzes multiple market structure conditions to filter out low-quality hammer patterns. Only the highest-probability setups are displayed, significantly reducing false signals compared to standard pattern recognition tools.
Dynamic Quadrant Mapping: Rather than basic support/resistance levels, the system divides each qualified hammer candle into three distinct zones (Upper Wick, Body, and Lower Wick), with precise .25, .5, and .75 subdivision levels for granular entry and exit planning.
Multi-Standard Deviation Projections: The indicator automatically calculates TP1 and TP2 targets based on the wick's range, along with optional 1-4 standard deviation extension levels for position scaling and profit maximization.
How It Works
Signal Generation @ Candle Close/New Candle Open
The indicator monitors your chart for HTF candles that meet specific criteria:
Bullish Hammer: Lower wick must be significantly larger than the body
Bearish Hammer: Upper wick must be significantly larger than the body
When both wicks qualify, the indicator selects the larger wick as the primary signal, depending on conditions set.
Visual Components
Bullish Setups:
SL: Stop loss level (below lower wick)
ENTRY: Entry zone (candle body range)
.25/.5/.25: Wick quadrant levels for scaling entries
TP1/TP2: First and second take profit targets
1-4STDV: Advanced/Long Range Targets
Bearish Setups:
SL: Stop loss level (above upper wick)
ENTRY: Entry zone (candle body range)
.25/.5/.25: Wick quadrant levels for scaling entries
TP1/TP2: First and second take profit targets
1-4STDV: Advanced/Long Range Targets
HTF Candle Overlay (Optional):
Displays the actual HTF candle that generated the signal
Shows Open, High, Low, and Close lines for context
Trading the Signals
For Bullish Hammers (Long):
Entry is @ HTF Candle Close / New HTF Candle Open (or wait for a .25-.5 wick retrace)
Place stop loss at or 1 tick below the SL level (lower wick low)
Target TP1 (1x wick range above) and TP2 (2x wick range above) and STDV
Use .25/.5/.25 levels to scale into positions or manage partial exits
For Bearish Hammers (Short):
Entry is @ HTF Candle Close / New HTF Candle Open (or wait for a .25-.5 wick retrace)
Place stop loss at or above the SL level (upper wick high)
Target TP1 (1x wick range below) and TP2 (2x wick range below) and STDV
Use .25/.5/.25 levels to scale into positions or manage partial exits
Key Settings
Hammer Model Conditions
Bullish/Bearish: Toggle which direction setups to display
1-2STDV / 3-4STDV: Show extended projection levels
HTF Liquidity Sweep: Filter for setups that swept previous HTF highs/lows (proprietary)
Wick Size: Require larger wick-to-body ratio (1.75x vs 1x)
Time Filters: Isolate setups during specific trading sessions (NY AM/PM, Asia, London)
Hourly Filters: Target setups that form during specific hour segments (useful for lower timeframes)
Display Options
Show Recent Hammer Models: Limit how many setups display on chart (default: 4)
Unlimited: Show all historical setups
Candle Quadrants: Toggle .25, .5, .25 subdivision lines
HTF Candle Overlay: Display the actual HTF candle that generated the signal
Timeframes
1min chart → 15min HTF (scalping)
5min chart → 1H HTF (day trading)
15min chart → 4H HTF (swing trading)
1H chart → Daily HTF (position trading)
The indicator automatically selects appropriate HTF pairs
Why Closed Source
This indicator is closed source to protect proprietary filtering algorithms that determine which hammer patterns qualify as valid signals. These filters analyze specific market structure conditions, liquidity dynamics, and statistical thresholds that have been developed through extensive backtesting, data logging over 1 years time, and represent the core intellectual property of this system. The filtering methodology is what separates this from basic pattern recognition tools and delivers higher-probability setups. To learn how to learn more about this system see Author Notes.
Best Practices
Confluence: Use this indicator alongside trend analysis, key support/resistance levels, or volume profiles
Risk Management: The SL levels provide clear invalidation points - always honor them
Scaling: Use the quadrant levels (.25/.5/.25) to scale into positions rather than entering full size at once
Session Filters: Enable time filters to focus on setups during high-liquidity sessions
Backtesting: Review historical signals on your preferred instruments to understand typical behavior and win rates
Notes
The indicator displays a table in the top-right showing the current chart timeframe and HTF being analyzed
Only charts with sufficient historical data will display all past signals
The "Unlimited" option may cause performance issues on very low timeframes with extensive history
Disclaimer: This indicator is a tool for technical analysis and risk management education and does not guarantee profitable trades. Always practice proper risk management and position sizing. Past performance does not indicate future results
Orderbook Table1. Indicator Name
Orderbook Table
This is an order book style trading volume map
that upgraded the price from my first script to label
2. One-line Introduction
A visual heatmap-style orderbook simulator that displays volume and delta clustering across price levels.
3. Overall Description
Orderbook Table is a powerful visual tool designed to replicate an on-chart approximation of a traditional order book.
It scans historical candles within a specified lookback window and accumulates traded volume into price "bins" or levels.
Each level is color-coded based on total volume and directional bias (delta), offering a layered view of where market interest was concentrated.
The indicator approximates order flow by analyzing each candle's directional volume, separating bullish and bearish volume.
With adjustable parameters such as level depth, price bin density, delta sensitivity, and opacity, it provides a highly customizable visualization.
Displayed directly on the chart, each level shows the volume at that price zone, along with a price label, offset to the right of the current bar.
Traders can use this tool to detect high liquidity zones, support/resistance clusters, and volume imbalances that may precede future price movements.
4. Key Benefits (Title + Description)
✅ On-Chart Volume Heatmap
Shows volume distribution across price levels in real-time directly on the price chart, creating a live “orderbook” view.
✅ Delta-Based Bias Coloring
Color changes based on net buying/selling pressure (delta), making aggressive demand/supply zones easy to spot.
✅ High Customizability
Users can adjust lookback bars, price bins, opacity levels, and delta usage to fit any market condition or asset class.
✅ Lightweight Simulation
Approximates orderbook depth using candle data without needing L2 feed access—works on all assets and timeframes.
✅ Clear Visual Anchoring
Volume quantities and price levels are offset to the right for easy viewing without cluttering the active chart area.
✅ Fast Market Context Recognition
Quickly identify price levels where volume concentrated historically, improving decision-making for entries/exits.
5. Indicator User Guide
📌 Basic Concept
Orderbook Table analyzes a configurable number of past bars and distributes traded volume into price "bins."
Each bin shows how much volume occurred around that price level, optionally adjusted for bullish/bearish candle direction.
⚙️ Settings Overview
Lookback Bars: Number of candles to scan for volume history
Levels (Total): Number of price levels to display around the current price
Price Bins: Granularity of price segmentation for volume distribution
Shift Right: How far to offset labels to the right of the current bar
Max/Min Opacity: Controls visual strength of volume coloring
Use Candle Delta Approx.: If enabled, colors the volume based on candle direction (green for up, red for down)
📈 Example Timing
Look for green clusters (bullish bias) below current price → possible strong demand zones
Price enters a high-volume level with previously aggressive buyers (green), suggesting support
📉 Example Timing
Red clusters (bearish bias) above current price can act as resistance or supply zones
Price stalling at a red-heavy volume band may indicate exhaustion or reversal opportunity
🧪 Recommended Use
Use as a support/resistance mapping tool in ranging and trending markets
Pair with candlestick analysis or momentum indicators for refined entry/exit points
Combine with VWAP or volume profile for multi-dimensional volume insight
🔒 Cautions
This is an approximation, not a true L2 orderbook—volume is based on historical candles, not actual limit order data
In low-volume markets or higher timeframes, bin granularity may be too coarse—adjust "Price Bins" accordingly
Delta calculation is based on open-close direction and does not reflect true buy/sell volume splits
Avoid overinterpreting low-opacity (light color) zones—they may indicate low interest rather than true resistance/support
+++
Wyckoff Accumulation/Distribution - Enhanced by ChakraWyckoff Accumulation/Distribution - Enhanced Indicator
Overview
An advanced Pine Script v6 indicator that detects Wyckoff accumulation and distribution patterns using RSI-based trend analysis, pivot detection, and volume confirmation. This enhanced version improves upon traditional Wyckoff indicators with cleaner code, English variable names, and additional market structure signals.
Key Features
Wyckoff Phase Detection
Accumulation Phase:
SC (Selling Climax): Bottom pivot with extreme bearish RSI and high volume
AR (Automatic Rally): First bounce after selling climax
ST (Secondary Test): Retest of lows without extreme RSI
SOS (Sign of Strength): Strong bullish breakout with volume confirmation ⭐ NEW
Distribution Phase:
BC (Buying Climax): Top pivot with extreme bullish RSI and high volume
DAR (Automatic Reaction): First drop after buying climax
DST (Distribution Secondary Test): Retest of highs
SOW (Sign of Weakness): Strong bearish breakdown with volume confirmation ⭐ NEW
Market Structure Events
Spring: False breakdown (RSI crosses above lower band) with background highlight
UTAD (Upthrust After Distribution): False breakout (RSI crosses below upper band) with background highlight
Visual Features
Range Boxes: Automatically draws consolidation ranges (gray) that change color on breakout:
🟢 Green = Accumulation (bullish breakout)
🔴 Red = Distribution (bearish breakout)
Pivot Markers: Orange triangles show regular (non-Wyckoff) pivot points
Bar Coloring: Lime bars for bullish trends, purple bars for bearish trends
Color-Coded Labels: All Wyckoff events clearly marked with descriptive text
Customizable Settings
RSI Settings:
RSI Length (default: 14)
Trend Sensitivity (default: 20) - Higher values = more sideways detection
Pivot Settings:
Pivot Length (default: 5) - Controls pivot point detection sensitivity
Display Options:
Toggle range boxes on/off
Toggle regular pivot markers
Toggle bar coloring by trend
Customize label text color
Advanced Detection:
Volume Confirmation toggle - Require high volume for climax events
Volume Threshold (default: 1.5x) - Adjustable volume multiplier
Alerts
8 comprehensive alert conditions:
Selling Climax (SC)
Buying Climax (BC)
Spring detection
UTAD detection
Sign of Strength (SOS)
Sign of Weakness (SOW)
Range Breakout
Improvements Over Original
✅ Pine Script v6 (latest version)
✅ English variable names (was Turkish)
✅ Fixed DAR label bug (was showing "AR")
✅ Added SOS (Sign of Strength) detection
✅ Added SOW (Sign of Weakness) detection
✅ Optional volume confirmation toggle
✅ Organized input groups for better UX
✅ Enhanced visual options
✅ Comprehensive alert system
✅ Cleaner, more maintainable code structure
Best Use Cases
Timeframes: Works on all timeframes; best on 4H, Daily, or Weekly
Markets: Stocks, Forex, Crypto, Indices
Trading Style: Swing trading, position trading, market structure analysis
Combine With: Support/Resistance, Volume Profile, Order Flow analysis
How It Works
The indicator uses RSI to identify market states (sideways, bullish, bearish) and combines this with pivot point detection and volume analysis to identify key Wyckoff events. When price is ranging (RSI between upper/lower bands), it draws a box. On breakout, the box color changes to indicate accumulation or distribution, helping traders identify smart money positioning.
Tips for Use
Lower Trend Sensitivity (10-15) for more signals in trending markets
Higher Trend Sensitivity (25-30) for clearer signals in choppy markets
Enable Volume Confirmation in high-volume markets (stocks, major crypto)
Disable Volume Confirmation in low-volume or forex markets
Watch for Spring/UTAD events within boxes for potential reversals
Version: 1.0
Pine Script: v6
Author: Chakrapani Chittabathina
Day-Type Detector — Rejection / FNL / Outside / StopRun (Clean)Day-Type Detector — Rejection / FNL / Outside / Stop-Run (Clean Version)
This indicator identifies four high-impact candlestick day-types commonly used in professional price-action and auction-market trading: Rejection Days, Failed New Low (FNL) Days, Outside Days, and Stop-Run Days. These patterns often precede major directional moves, reversals, and absorption events, making them particularly valuable for swing traders, positional traders, and short-term discretionary traders.
The script is designed to work across all timeframes and is built around volatility-adjusted measurements using Average Daily Range (ADR) for accuracy and consistency.
What This Indicator Detects
1. Rejection Day (Bullish & Bearish)
A Rejection Day is a wide-range bar that rejects a previous extreme.
The indicator identifies rejection based on:
Range > ADR × threshold
Long lower wick (for bullish) or long upper wick (for bearish)
Close located in the strong zone of the day’s range
These conditions highlight areas where aggressive counter-orderflow entered the market.
2. Failed New Low (FNL) / Failed New High
An FNL day traps traders who attempted breakout selling or buying.
The indicator checks for:
A break beyond the previous session’s low or high
Immediate rejection back inside
Midpoint recapture conditions
ADR-normalized range requirements
These days often trigger powerful directional reversals.
3. Outside Day (Bullish & Bearish)
An Outside Day is a statistically significant expansion day that breaks both the previous high and low.
The script validates:
High > previous high and low < previous low
Range > ADR threshold
Close beyond prior session extreme to complete the rejection sequence
Outside Days often represent stop runs, shakeouts, or trend accelerations.
4. Stop-Run Day (Bullish & Bearish)
Stop-Run Days are aggressive volatility expansions and tend to be the largest ranges within short windows.
This detector identifies them using:
Range > ADR × multiplier
Close located near the extreme of the day (top for bullish, bottom for bearish)
Strong body relative to total range
Break above/below previous session extreme
These patterns indicate capitulation or forced liquidation and are often followed by continuation or sharp counter-rotation.
Key Features
✔ Historical Pattern Marking
All qualifying bars are marked on the chart using plotshape() in global scope, ensuring full historical visibility.
✔ Event Logging & Table Display
A table (top-right of the chart) displays the most recent pattern detections, including:
Timestamp
Pattern type
Bar index
This allows users to monitor and study past pattern occurrences without scanning the chart manually.
✔ ADR-Adjusted Detection
Volatility uncertainty is removed by anchoring all thresholds to ADR.
This ensures consistency across:
Different symbols
Different timeframes
Different market regimes
✔ Alerts Included
Alerts are preconfigured for:
Rejection Day Bull / Bear
FNL Bull / Bear
Outside Day Bull / Bear
Stop-Run Bull / Bear
This allows the user to receive real-time notifications when major day-type structures develop.
How to Use
Add the indicator to any timeframe chart.
Enable or disable:
Historical markers
History table
ADR diagnostics
Watch for shape markers or use alerts for real-time signals.
Use the history table to review recent occurrences.
Combine these day-types with:
Market structure levels
High/low volume nodes (LVNs)
Support/resistance zones
Trend context
These day-types are most effective when they occur near meaningful structural levels because they show where strong order-flow entered the market.
Best Practices
Use higher timeframes (1H–1D) for swing entries.
Confirm signals with market structure or volume profile.
Treat these day-types as context, not standalone signals.
Observe follow-through behavior in the next 1–3 bars after detection.
Credits
This script is based on concepts commonly seen in auction-market theory and professional price-action frameworks, such as Rejection Days, Failed New Lows, Outside Days, and Stop-Run behaviors.
All calculations and logic have been rebuilt from scratch to ensure clean, reliable, and optimized Pine Script v6 execution.
Tactical Deviation🎯 TACTICAL DEVIATION - Volume-Backed VWAP Deviation Analysis
What Makes This Different?
Unlike basic VWAP indicators, Tactical Deviation combines:
• Multi-timeframe VWAP deviation bands (Daily/Weekly/Monthly)
• Volume spike intelligence - signals only appear with volume confirmation
• Pivot reversal detection at deviation extremes
• Optional multi-VWAP confluence system
• Smart defaults for quality over quantity
This unique combination filters weak setups and identifies high-probability entries at extreme price deviations from fair value.
📊 DEFAULT SETTINGS (Ready to Use)
✅ Daily VWAP with ±2σ deviation bands
✅ Volume spike detection (1.5x average required)
✅ 2σ minimum deviation for signals
❌ Weekly/Monthly VWAPs (enable for multi-timeframe)
❌ Pivot reversal requirement (enable for stronger signals)
❌ Fill zones (optional visual enhancement)
Why: Daily VWAP is most relevant for intraday trading. 2σ bands catch meaningful moves. Volume spikes ensure conviction. Clean chart focuses on what matters.
🚀 HOW TO USE
BASIC USAGE:
• Green triangles (below bars) = Long signals at oversold deviations
• Red triangles (above bars) = Short signals at overbought deviations
SIGNAL QUALITY:
• Normal size, bright colors = Volume spike (best quality)
• Small size, lighter colors = Volume momentum
• Tiny size = No volume confirmation
DEVIATION ZONES:
• ±2σ = Extreme deviation (signals appear here)
• ±1σ to ±2σ = Extended but not extreme
• Within ±1σ = Normal range
TRADING APPROACHES:
Mean Reversion:
→ Enter when price reaches ±2σ with volume spike
→ Target: Return to VWAP or opposite band
→ Stop: Beyond extreme deviation
Trend Continuation:
→ Use bands to identify pullbacks
→ Enter pullback to VWAP in trending market
→ Volume confirms continuation
Reversal Trading:
→ Enable "Require Pivot Reversal" for stronger signals
→ Signals only when deviation + pivot reversal occur
→ Higher probability, fewer signals
⚙️ EXPLORE SETTINGS FOR FULL USE
VWAP SETTINGS:
• Show Weekly/Monthly VWAP = Multi-timeframe context
• Show ±1σ Bands = Normal deviation range
• Show ±3σ Bands = Extreme extremes (rare but powerful)
SIGNAL SETTINGS:
• Min Deviation: 1σ (more signals) | 2σ (default) | 3σ (fewer, extreme only)
• Require Pivot Reversal: OFF (default) | ON (stronger but fewer)
• Volume Spike Threshold: 1.5x (default) | 2.0x+ (major spikes) | 1.2x (more signals)
CONFLUENCE SETTINGS:
• Require Multi-VWAP Confluence: OFF (default) | ON (2+ VWAPs must agree)
• Min VWAPs: 2 (Daily + Weekly/Monthly) | 3 (all must agree)
VISUAL SETTINGS:
• Show Fill Zones = Shaded areas between bands
• Fill Opacity = Transparency adjustment
• Line Widths = Customize thickness
💡 PRO TIPS
1. Start with defaults, then enable features as you learn
2. Volume spike requirement filters weak moves - keep it enabled
3. Enable Weekly/Monthly VWAPs for higher timeframe context
4. Enable confluence for swing trading setups
5. Pivot reversals: ON for reversals, OFF for continuations
6. Check top-right info table for current deviation levels
🎨 VISUAL GUIDE
• Cyan Line = Daily VWAP (fair value)
• Cyan Bands = Daily deviation zones
• Orange Line = Weekly VWAP (if enabled)
• Purple Line = Monthly VWAP (if enabled)
• Green Triangle = Long signal (oversold)
• Red Triangle = Short signal (overbought)
⚠️ IMPORTANT
Educational purposes only. Always use proper risk management. Signals are based on statistical deviation, not guarantees. Volume confirmation improves quality but doesn't guarantee outcomes. Combine with your own analysis.
The unique combination of VWAP deviation analysis, volume profile confirmation, pivot identification, and multi-timeframe confluence in a single clean interface makes Tactical Deviation different from basic VWAP indicators.
Happy Trading! 📈
A.I. 👑 Optimus Prime [RubiXalgo]A.I. Optimus Prime — Rubik’s Algo (2025 Edition) by StupidBitcoin
The ultimate all-in-one AI-powered trend & volume system inspired by the mathematics of a Rubik’s Cube and the fluid hand movements of speed-cubers.
Two “cubes” rotate inside each other:
-Figure 1 (outer cube) = Supply / Demand / Bull / Bear zones
-Figure 2 (inner core) = Trend / xTrend / Price / Volume relationships
Just as a speed-cuber solves the cube blindly while juggling, Optimus Prime solves the market in real time using adaptive Kalman filters, k-NN machine learning, LOWESS smoothing, dynamic volume delta, and color-gradient intelligence — turning chaos into an intuitive traffic-light trading experience.Core FeaturesDual Kalman “Rubik” lines (Fast & Slow) with zero-lag adaptive scaling
-AI candle coloring + gradient momentum oscillator
-Dynamic Linear Regression Volume Profile with auto-angled VPOC
-Liquidation Heatmap Window with entry, stop-loss, and 3 profit targets ( / auto-mark)
-Volume Profit-Trend polyline predictor (walk-forward volume delta + Ichimoku wave theory)
-Up to 5 multi-timeframe moving averages (SMA/DEMA/TEMA/VWMA) + trend table
-Speed-lane fill + Kalman target marker on current bar
-Full machine-learning color system (Classic or Crypto themes)
Why the Rubik’s metaphor works
The VSQC lookback (default 9) acts like the “speed” of the fast cube.
The Maximum Length + Accelerator Multiplier control the “slow” cube.
As market conditions change, the two cubes rotate and realign exactly like Ichimoku components — but fully adaptive and non-repainting.Top-Tier Signals (3:1+ RR)
Longs
Green Liquidation Window + green Volume Profit-Trend curving up → enter at ✪, SL below red stop, TP at ◆/❖/🞛
Price breaks above green Fast Rubik + green polyline → ride to 3rd target
Bounce off green VPOC center line with confirming green candle & volume surge
Shorts (mirror opposite with red/teal colors)Educational & Open-Source
Built for learning. Every module is heavily commented and credited to the Pine Script community that made it possible.
Licensed under CC BY-NC-SA 4.0 — free to study, modify, and share non-commercially with attribution.Settings HighlightsVSQC Dynamic Scaling Lookback (8-21) → speed of the fast cube (9 = developer default)
Accelerator Multiplier → how aggressively the slow cube adapts
k-Neighbors Count (63) → machine-learning prediction strength
Two gorgeous color themes: Classic (red/green) or Crypto (teal/purple)
If you ever wanted an indicator that feels like a living, breathing Rubik’s Cube solving the market in front of your eyes — this is it.Not financial advice • Trade at your own risk • Backtest thoroughly • 2025 StupidBitcoin
Chronos Reversal Labs - SPChronos Reversal Labs - Shadow Portfolio
Chronos Reversal Labs - Shadow Portfolio: combines reinforcement learning optimization with adaptive confluence detection through a shadow portfolio system. Unlike traditional indicator mashups that force traders to manually interpret conflicting signals, this system deploys 4 multi-armed bandit algorithms to automatically discover which of 5 specialized confluence strategies performs best in current market conditions, then validates those discoveries through parallel shadow portfolios that track virtual P&L for each strategy independently.
Core Innovation: Rather than relying on static indicator combinations, this system implements Thompson Sampling (Bayesian multi-armed bandits), contextual bandits (regime-specific learning), advanced chop zone detection (geometric pattern analysis), and historical pre-training to build a self-improving confluence detection engine. The shadow portfolio system runs 5 parallel virtual trading accounts—one per strategy—allowing the system to learn which confluence approach works best through actual position tracking with realistic exits.
Target Users: Intermediate to advanced traders seeking systematic reversal signals with mathematical rigor. Suitable for swing trading and day trading across stocks, forex, crypto, and futures on liquid instruments. Requires understanding of basic technical analysis and willingness to allow 50-100 bars for initial learning.
Why These Components Are Combined
The Fundamental Problem
No single confluence method works consistently across all market regimes. Kernel-based methods (entropy, DFA) excel during predictable phases but fail in chaos. Structure-based methods (harmonics, BOS) work during clear swings but fail in ranging conditions. Technical methods (RSI, MACD, divergence) provide reliable signals in trends but generate false signals during consolidation.
Traditional solutions force traders to either manually switch between methods (slow, error-prone) or interpret all signals simultaneously (cognitive overload). Both fail because they assume the trader knows which regime the market is in and which method works best.
The Solution: Meta-Learning Through Reinforcement Learning
This system solves the problem through automated strategy selection : Deploy 5 specialized confluence strategies designed for different market conditions, track their real-world performance through shadow portfolios, then use multi-armed bandit algorithms to automatically select the optimal strategy for the next trade.
Why Shadow Portfolios? Traditional bandit implementations use abstract "rewards." Shadow portfolios provide realistic performance measurement : Each strategy gets a virtual trading account with actual position tracking, stop-loss management, take-profit targets, and maximum holding periods. This creates risk-adjusted learning where strategies are evaluated on P&L, win rate, and drawdown—not arbitrary scores.
The Five Confluence Strategies
The system deploys 5 orthogonal strategies with different weighting schemes optimized for specific market conditions:
Strategy 1: Kernel-Dominant (Entropy/DFA focused, optimal in predictable markets)
Shannon Entropy weight × 2.5, DFA weight × 2.5
Detects low-entropy predictable patterns and DFA persistence/mean-reversion signals
Failure mode: High-entropy chaos (hedged by Technical-Dominant)
Strategy 2: Structure-Dominant (Harmonic/BOS focused, optimal in clear swing structures)
Harmonics weight × 2.5, Liquidity (S/R) weight × 2.0
Uses swing detection, break-of-structure, and support/resistance clustering
Failure mode: Range-bound markets (hedged by Balanced)
Strategy 3: Technical-Dominant (RSI/MACD/Divergence focused, optimal in established trends)
RSI weight × 2.0, MACD weight × 2.0, Trend weight × 2.0
Zero-lag RSI suite with 4 calculation methods, MACD analysis, divergence detection
Failure mode: Choppy/ranging markets (hedged by chop filter)
Strategy 4: Balanced (Equal weighting, optimal in unknown/transitional regimes)
All components weighted 1.2×
Baseline performance during regime uncertainty
Strategy 5: Regime-Adaptive (Dynamic weighting by detected market state)
Chop zones: Kernel × 2.0, Technical × 0.3
Bull/Bear trends: Trend × 1.5, DFA × 2.0
Ranging: Mean reversion × 1.5
Adapts explicitly to detected regime
Multi-Armed Bandit System: 4 Core Algorithms
What Is a Multi-Armed Bandit Problem?
Formal Definition: K arms (strategies), each with unknown reward distribution. Goal: Maximize cumulative reward while learning which arms are best. Challenge: Balance exploration (trying uncertain strategies) vs. exploitation (using known-best strategy).
Trading Application: Each confluence strategy is an "arm." After each trade, receive reward (P&L percentage). Bandits decide which strategy to trust for next signal.
The 4 Implemented Algorithms
1. Thompson Sampling (DEFAULT)
Category: Bayesian approach with probability distributions
How It Works: Model each strategy as Beta(α, β) where α = wins, β = losses. Sample from distributions, select highest sample.
Properties: Optimal regret O(K log T), automatic exploration-exploitation balance
When To Use: Best all-around choice, adaptive markets, long-term optimization
2. UCB1 (Upper Confidence Bound)
Category: Frequentist approach with confidence intervals
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Properties: Deterministic, interpretable, same optimal regret as Thompson
When To Use: Prefer deterministic behavior, stable markets
3. Epsilon-Greedy
Category: Simple baseline with random exploration
How It Works: With probability ε (0.15): random strategy. Else: best average reward.
Properties: Simple, fast initial learning
When To Use: Baseline comparison, short-term testing
4. Contextual Bandit
Category: Context-aware Thompson Sampling
Enhancement: Maintains separate alpha/beta for Bull/Bear/Ranging regimes
Learning: "Strategy 2: 60% win rate in Bull, 40% in Bear"
When To Use: After 100+ bars, clear regime shifts
Shadow Portfolio System
Why Shadow Portfolios?
Traditional bandits use abstract scores. Shadow portfolios provide realistic performance measurement through actual position simulation.
How It Works
Position Opening:
When strategy generates validated signal:
Opens virtual position for selected strategy
Records: entry price, direction, entry bar, RSI method
Optional: Open positions for ALL strategies simultaneously (faster learning)
Position Management (Every Bar):
Current P&L: pnl_pct = (close - entry) / entry × direction × 100
Exit if: pnl_pct <= -2.0% (stop-loss) OR pnl_pct >= +4.0% (take-profit) OR held ≥ 100 bars (time)
Position Closing:
Calculate final P&L percentage
Update strategy equity, track win rate, gross profit/loss, max drawdown
Calculate risk-adjusted reward:
text
base_reward = pnl_pct / 10.0
win_rate_bonus = (win_rate - 0.5) × 0.3
drawdown_penalty = -max_drawdown × 0.05
total_reward = sigmoid(base + bonus + penalty)
Update bandit algorithms with reward
Update RSI method bandit
Statistics Tracked Per Strategy:
Equity curve (starts at $10,000)
Win rate percentage
Max drawdown
Gross profit/loss
Current open position
This creates closed-loop learning : Strategies compete → Best performers selected → Bandits learn quality → System adapts automatically.
Historical Pre-Training System
The Problem with Live-Only Learning
Standard bandits start with zero knowledge and need 50-100 signals to stabilize. For weekly timeframe traders, this could take years.
The Solution: Historical Training
During Chart Load: System processes last 300-1000 bars (configurable) in "training mode":
Detect signals using Balanced strategy (consistent baseline)
For each signal, open virtual training positions for all 5 strategies
Track positions through historical bars using same exit logic (SL/TP/time)
Update bandit algorithms with historical outcomes
CRITICAL TRANSPARENCY: Signal detection does NOT look ahead—signals use only data available at entry bar. Exit tracking DOES look ahead (uses future bars for SL/TP), which is acceptable because:
✅ Entry decisions remain valid (no forward bias)
✅ Learning phase only (not affecting shown signals)
✅ Real-time mirrors training (identical exit logic)
Training Completion: Once chart reaches current bar, system transitions to live mode. Dashboard displays training vs. live statistics for comparison.
Benefit: System begins live trading with 100-500 historical trades worth of learning, enabling immediate intelligent strategy selection.
Advanced Chop Zone Detection Engine
The Innovation: Multi-Layer Geometric Chop Analysis
Traditional chop filters use simple volatility metrics (ATR thresholds) that can't distinguish between trending volatility (good for signals) and choppy volatility (bad for signals). This system implements three-layer geometric pattern analysis to precisely identify consolidation zones where reversal signals fail.
Layer 1: Micro-Structure Chop Detection
Method: Analyzes micro pivot points (5-bar left, 2-bar right) to detect geometric compression patterns.
Slope Analysis:
Calculates slope of pivot high trendline and pivot low trendline
Compression ratio: compression = slope_high - slope_low
Pattern Classification:
Converging slopes (compression < -0.05) → "Rising Wedge" or "Falling Wedge"
Flat slopes (|slope| < 0.05) → "Rectangle"
Parallel slopes (|compression| < 0.1) → "Channel"
Expanding slopes → "Expanding Range"
Chop Scoring:
Rectangle pattern: +15 points (highest chop)
Low average slope (<0.05): +15 points
Wedge patterns: +12 points
Flat structures: +10 points
Why This Works: Geometric patterns reveal market indecision. Rectangles and wedges create false breakouts that trap technical traders. By quantifying geometric compression, system detects these zones before signals fire.
Layer 2: Macro-Structure Chop Detection
Method: Tracks major swing highs/lows using ATR-based deviation threshold (default 2.0× ATR), projects channel boundaries forward.
Channel Position Calculation:
proj_high = last_swing_high + (swing_high_slope × bars_since)
proj_low = last_swing_low + (swing_low_slope × bars_since)
channel_width = proj_high - proj_low
position = (close - proj_low) / channel_width
Dead Zone Detection:
Middle 50% of channel (position 0.25-0.75) = low-conviction zone
Score increases as price approaches center (0.5)
Chop Scoring:
Price in dead zone: +15 points (scaled by centrality)
Narrow channel width (<3× ATR): +15 points
Channel width 3-5× ATR: +10 points
Why This Works: Price in middle of range has equal probability of moving either direction. Institutional traders avoid mid-range entries. By detecting "dead zones," system avoids low-probability setups.
Layer 3: Volume Chop Scoring
Method: Low volume indicates weak conviction—precursor to ranging behavior.
Scoring:
Volume < 0.5× average: +20 points
Volume 0.5-0.8× average: +15 points
Volume 0.8-1.0× average: +10 points
Overall Chop Intensity & Signal Filtering
Total Chop Calculation:
chop_intensity = micro_score + macro_score + (volume_score × volume_weight)
is_chop = chop_intensity >= 40
Signal Filtering (Three-Tier Approach):
1. Signal Blocking (Intensity > 70):
Extreme chop detected (e.g., tight rectangle + dead zone + low volume)
ALL signals blocked regardless of confluence
Chart displays red/orange background shading
2. Threshold Adjustment (Intensity 40-70):
Moderate chop detected
Confluence threshold increased: threshold += (chop_intensity / 50)
Only highest-quality signals pass
3. Strategy Weight Adjustment:
During Chop: Kernel-Dominant weight × 2.0 (entropy detects breakout precursors), Technical-Dominant weight × 0.3 (reduces false signals)
After Chop Exit: Weights revert to normal
Why This Three-Tier Approach Is Original: Most chop filters simply block all signals (loses breakout entries). This system adapts strategy selection during chop—allowing Kernel-Dominant (which excels at detecting low-entropy breakout precursors) to operate while suppressing Technical-Dominant (which generates false signals in consolidation). Result: System remains functional across full market regime spectrum.
Zero-Lag Filter Suite with Dynamic Volatility Scaling
Zero-Lag ADX (Trend Regime Detection)
Implementation: Applies ZLEMA to ADX components:
lag = (length - 1) / 2
zl_source = source + (source - source ) × strength
Dynamic Volatility Scaling (DVS):
Calculates volatility ratio: current_ATR / ATR_100period_avg
Adjusts ADX length dynamically: High vol → shorter length (faster), Low vol → longer length (smoother)
Regime Classification:
ADX > 25 with +DI > -DI = Bull Trend
ADX > 25 with -DI > +DI = Bear Trend
ADX < 25 = Ranging
Zero-Lag RSI Suite (4 Methods with Bandit Selection)
Method 1: Standard RSI - Traditional Wilder's RSI
Method 2: Ehlers Zero-Lag RSI
ema1 = ema(close, length)
ema2 = ema(ema1, length)
zl_close = close + (ema1 - ema2)
Method 3: ZLEMA RSI
lag = (length - 1) / 2
zl_close = close + (close - close )
Method 4: Kalman-Filtered RSI - Adaptive smoothing with process/measurement noise
RSI Method Bandit: Separate 4-arm bandit learns which calculation method produces best results. Updates independently after each trade.
Kalman Adaptive Filters
Fast Kalman: Low process noise → Responsive to genuine moves
Slow Kalman: Higher measurement noise → Filters noise
Application: Crossover logic for trend detection, acceleration analysis for momentum inflection
What Makes This Original
Innovation 1: Shadow Portfolio Validation
First TradingView script to implement parallel virtual portfolios for multi-armed bandit reward calculation. Instead of abstract scoring metrics, each strategy's performance is measured through realistic position tracking with stop-loss, take-profit, time-based exits, and risk-adjusted reward functions (P&L + win rate + drawdown). This provides orders-of-magnitude better reward signal quality for bandit learning than traditional score-based approaches.
Innovation 2: Three-Layer Geometric Chop Detection
Novel multi-scale geometric pattern analysis combining: (1) Micro-structure slope analysis with pattern classification (wedges, rectangles, channels), (2) Macro-structure channel projection with dead zone detection, (3) Volume confirmation. Unlike simple volatility filters, this system adapts strategy weights during chop —boosting Kernel-Dominant (breakout detection) while suppressing Technical-Dominant (false signal reduction)—allowing operation across full market regime spectrum without blind signal blocking.
Innovation 3: Historical Pre-Training System
Implements two-phase learning : Training phase (processes 300-1000 historical bars on chart load with proper state isolation) followed by live phase (real-time learning). Training positions tracked separately from live positions. System begins live trading with 100-500 trades worth of learned experience. Dashboard displays training vs. live performance for transparency.
Innovation 4: Contextual Multi-Armed Bandits with Regime-Specific Learning
Beyond standard bandits (global strategy quality), implements regime-specific alpha/beta parameters for Bull/Bear/Ranging contexts. System learns: "Strategy 2: 60% win rate in ranging markets, 45% in bull trends." Uses current regime's learned parameters for strategy selection, enabling regime-aware optimization.
Innovation 5: RSI Method Meta-Learning
Deploys 4 different RSI calculation methods (Standard, Ehlers ZL, ZLEMA, Kalman) with separate 4-arm bandit that learns which calculation works best. Updates RSI method bandit independently based on trade outcomes, allowing automatic adaptation to instrument characteristics.
Innovation 6: Dynamic Volatility Scaling (DVS)
Adjusts ALL lookback periods based on current ATR ratio vs. 100-period average. High volatility → shorter lengths (faster response). Low volatility → longer lengths (smoother signals). Applied system-wide to entropy, DFA, RSI, ADX, and Kalman filters for adaptive responsiveness.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Theory Mode: Start with "BALANCED" (APEX for aggressive, CONSERVATIVE for defensive)
Enable RL: Toggle "Enable RL Auto-Optimization" to TRUE, select "Thompson Sampling"
Enable Confluence Modules: Divergence, Volume Analysis, Liquidity Mapping, RSI OB/OS, Trend Analysis, MACD (all recommended)
Enable Chop Filter: Toggle "Enable Chop Filter" to TRUE, sensitivity 1.0 (default)
Historical Training: Enable "Enable Historical Pre-Training", set 300-500 bars
Dashboard: Enable "Show Dashboard", position Top Right, size Large
Learning Phase (First 50-100 Bars)
Monitor Thompson Sampling Section:
Alpha/beta values should diverge from initial 1.0 after 20-30 trades
Expected win% should stabilize around 55-60% (excellent), >50% (acceptable)
"Pulls" column should show balanced exploration (not 100% one strategy)
Monitor Shadow Portfolios:
Equity curves should diverge (different strategies performing differently)
Win rate > 55% is strong
Max drawdown < 15% is healthy
Monitor Training vs Live (if enabled):
Delta difference < 10% indicates good generalization
Large negative delta suggests overfitting
Large positive delta suggests system adapting well
Optimization:
Too few signals: Lower "Base Confluence Threshold" to 2.5-3.0
Too many signals: Raise threshold to 4.0-4.5
One strategy dominates (>80%): Increase "Exploration Rate" to 0.20-0.25
Excessive chop blocking: Lower "Chop Sensitivity" to 0.7-0.8
Signal Interpretation
Dashboard Indicators:
"WAITING FOR SIGNAL": No confluence
"LONG ACTIVE ": Validated long entry
"SHORT ACTIVE ": Validated short entry
Chart Visuals:
Triangle markers: Entry signal (green = long, red = short)
Orange/red background: Chop zone
Lines: Support/resistance if enabled
Position Management
Entry: Enter on triangle marker, confirm direction matches dashboard, check confidence >60%
Stop-Loss: Entry ± 1.5× ATR or at structural swing point
Take-Profit:
TP1: Entry + 1.5R (take 50%, move SL to breakeven)
TP2: Entry + 3.0R (runner) or trail
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Account × Risk%) / (Entry - SL)
Recommended Settings by Instrument
Stocks (Large Cap): Balanced mode, Threshold 3.5, Thompson Sampling, Chop 1.0, 15min-1H, Training 300-500 bars
Forex Majors: Conservative-Balanced mode, Threshold 3.5-4.0, Thompson Sampling, Chop 0.8-1.0, 5min-30min, Training 400-600 bars
Cryptocurrency: Balanced-APEX mode, Threshold 3.0-3.5, Thompson Sampling, Chop 1.2-1.5, 15min-4H, Training 300-500 bars
Futures: Balanced mode, Threshold 3.5, UCB1 or Thompson, Chop 1.0, 5min-30min, Training 400-600 bars
Technical Approximations & Limitations
1. Thompson Sampling: Pseudo-Random Beta Distribution
Standard: Cryptographic RNG with true beta sampling
This Implementation: Box-Muller transform using market data as entropy source
Impact: Not cryptographically random but maintains exploration-exploitation balance. Sufficient for strategy selection.
2. Shadow Portfolio: Simplified Execution Model
Standard: Order book simulation with slippage, partial fills
This Implementation: Perfect fills at close price, no fees modeled
Impact: Real-world performance ~0.1-0.3% worse per trade due to execution costs.
3. Historical Training: Forward-Looking for Exits Only
Entry signals: Use only past data (causal, no bias)
Exit tracking: Uses future bars to determine SL/TP (forward-looking)
Impact: Acceptable because: (1) Entry logic remains valid, (2) Live trading mirrors training, (3) Improves learning quality. Training win rates reflect 8-bar evaluation window—live performance may differ if positions held longer.
4. Shannon Entropy & DFA: Simplified Calculations
Impact: 10-15% precision loss vs. academic implementations. Still captures predictability and persistence signals effectively.
General Limitations
No Predictive Guarantee: Past performance ≠ future results
Learning Period Required: Minimum 50-100 bars for stable statistics
Overfitting Risk: May not generalize to unprecedented conditions
Single-Instrument: No multi-asset correlation or sector context
Execution Assumptions: Degrades in illiquid markets (<100k volume), major news events, flash crashes
Risk Warnings & Disclaimers
No Guarantee of Profit: All trading involves substantial risk of loss. This indicator is a tool, not a guaranteed profit system.
System Failures: Software bugs possible despite testing. Use appropriate position sizing.
Market Regime Changes: Performance may degrade during extreme volatility (VIX >40), low liquidity periods, or fundamental regime shifts.
Broker-Specific Issues: Real-world execution includes slippage (0.1-0.5%), commissions, overnight financing costs, partial fills.
Forward-Looking Bias in Training: Historical training uses 8-bar forward window for exit evaluation. Dashboard "Training Win%" reflects this method. Real-time performance may differ.
Appropriate Use
This Indicator IS:
✅ Entry trigger system with confluence validation
✅ Risk management framework (automated SL/TP)
✅ Adaptive strategy selection engine
✅ Learning system that improves over time
This Indicator IS NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for due diligence
❌ Guaranteed profit generator
❌ Suitable for complete beginners
Recommended Complementary Analysis: Market context, volume profile, fundamental catalysts, higher timeframe alignment, support/resistance from other sources.
Conclusion
Chronos Reversal Labs V2.0 - Elite Edition synthesizes research from multi-armed bandit theory (Thompson Sampling, UCB, contextual bandits), market microstructure (geometric chop detection, zero-lag filters), and machine learning (shadow portfolio validation, historical pre-training, RSI method meta-learning).
Unlike typical indicator mashups, this system implements mathematically rigorous bandit algorithms with realistic performance validation, three-layer chop detection with adaptive strategy weighting, regime-specific learning, and full transparency on approximations and limitations.
The system is designed for intermediate to advanced traders who understand that no indicator is perfect, but through proper machine learning and realistic validation, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Understand the limitations. Risk disclosure applies. Past performance does not guarantee future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Swiftedge – Smart Volume DominanceSwiftedge – Daily Volume Profile
A professional-grade volume indicator that shows real USD buying and selling pressure for each weekday (Monday–Friday), live intraday lines, and smart volume context using median and average daily volume.
Features
• Real USD volume split: Green = Buying pressure (up bars), Red = Selling pressure (down bars)
• Live EMA-smoothed intraday buyer/seller lines with fill
• Daily table (Mon–Fri) with Buyers, Sellers, Net, Total and dominance coloring
• "vs Median" column – instantly see if today’s volume is HIGH, LOW or normal (±30% threshold)
• Median & Average daily volume over the last X days (default 30, adjustable)
• Weekly summary table
• Clean, fully customizable table positions
• Works on all markets and timeframes (best on 1H and lower for intraday precision)
Why this indicator?
Most volume indicators only show raw ticks or shares. This one shows real money flow in USD and puts today’s activity in historical context using the powerful median volume – far more reliable than average when spotting truly unusual days.
Created by Swiftedge – trusted by thousands of traders worldwide.
Enjoy responsibly and trade well!
VWAP + Volume Spikes See Where Smart Money ExhaustsVolume tells the truth. VWAP tells the bias. This script shows both — live.
If you trade intraday momentum, reversals, or liquidity sweeps, this indicator is built for you.
It shows where volume spikes hit extreme levels, anchored around VWAP and its dynamic bands, so you can instantly spot capitulation or hidden absorption.
🎯 What This Indicator Does
✅ Plots VWAP — session-anchored, updates automatically
✅ Adds dynamic VWAP bands — standard deviation envelopes showing volatility context
✅ Highlights volume spikes — colored candles + background for abnormal prints
✅ Includes alerts — “Volume Spike”, “VWAP Cross”, or a combined alert with direction
✅ Clean visual design — instantly readable in fast markets
It’s your visual orderflow radar — whether you’re trading gold, indices, or small caps.
🔍 Why It Works
Institutions build and unwind positions around VWAP.
Retail often chases volume… this script shows you when that volume becomes too extreme.
A spike above VWAP near resistance? → Likely distribution.
A spike below VWAP near support? → Likely capitulation.
Combine volume exhaustion + VWAP context, and you’ll see market turning points form before most indicators react.
⚙️ Inputs You Can Tune
Bands lookback: adjusts how reactive the VWAP bands are
Band width (σ): set how tight or wide your deviation envelope is
Volume baseline length: controls how “abnormal” a spike must be
Spike threshold: multiplier vs. average volume
Toggle color-coding, bands, and labels
Default settings work well across 1m–15m intraday charts and 1h–4h swing frames.
💡 How Traders Use It
1️⃣ Fade Parabolics:
When a green spike candle pierces upper VWAP band on high volume → smart money unloading.
Look for rejection and short into VWAP.
2️⃣ Catch Capitulations:
When a red spike candle dumps below lower VWAP band → panic selling.
Watch for stabilization and long back to VWAP.
3️⃣ VWAP Rotation Plays:
Alerts for price crossing VWAP help you spot shift in intraday control.
Above VWAP = buyers in charge.
Below VWAP = sellers in charge.
🧠 Best Practices
Pair it with Volume Profile or Delta/Flow tools to confirm exhaustion.
Don’t chase — wait for spike confirmation + reversal candle.
Use it on liquid tickers (NASDAQ, SPY, GOLD, BTC, etc.).
Great for Dux-style small-cap shorts or index pullbacks.
🔔 Alerts Ready
Choose from:
Volume Spike (single-bar explosion)
VWAP Cross Up/Down (trend shift confirmation)
One Combined Alert (any signal, includes ticker, price, and volume)
Set once — get real-time push notifications, Telegram, or webhook signals.
📊 My Favorite Setups
US100 / NASDAQ: fade rallies above VWAP + spike
Gold / Silver: trade reversals from VWAP bands
Small caps: short back-side after volume climax
ES, DAX, Oil: scalp VWAP rotation with confluence
❤️ Support This Work
I release free and premium scripts weekly — combining smart money concepts, VWAP tools, and volume analytics.
👉 Follow me on TradingView for more indicators and setups.
👉 Comment “🔥” if you want me to post the multi-timeframe VWAP + Volume Pressure version next.
👉 Share this with your team — it helps the community grow.
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent 🎭
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent ⚡
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2σ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trend—enters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent 💧
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR)
Signal Logic: Breakout anticipation—enters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent 📊
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ε)% of the time
Explores randomly ε% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal → outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (▲): Long signal confirmed
Red triangle (▼): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with ► marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (█████ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5× ATR)
Take-profit 1 (2.0× ATR)
Take-profit 2 (3.5× ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models)
✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint
⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Fair Value Gap Pro by Bifrost InstituteFair Value Gap Pro brings institutional-style FVGs to TradingView with the precision and controls traders actually need. It detects clean 3-candle gaps on any higher timeframe, projects them onto your active chart, and overlays precise buy/sell volume ratios so you can judge the quality of a gap at a glance. Everything is customizable—from colors and line styles to tag markers, and volume display—so the tool adapts to your workflow instead of the other way around.
🔭 Multi-Timeframe Engine
Higher Timeframe Detection: Choose any HTF (M5, H1, H4, D1, etc.) and view those gaps on any lower-TF chart
Smart Gap Detection: Strict 3-candle mode ensures only successive bars form gaps—automatically rejects weekend gaps and market closures
Configurable History: Scan back 1-500+ bars with intelligent processing
Extend Until Filled: Gaps dynamically extend forward until price fills them, or use fixed-width mode
Advanced Fill Logic: Fill Rules - Close only, wick only, or close/wick; Fill Depth: TouchAny (immediate edge touch) or TouchMid (requires 50% penetration)
TouchMid Margin: Fine-tune difficulty with -50% to +50% adjustment (e.g., -10% = easier fill at 40% depth)
Weekend Gap Protection: Prevents false fills from market gaps—only real price action counts
📊 HTF-Accurate Volumetrics
True HTF Volume: Uses higher timeframe bar data for accurate volume matching across all chart timeframes
Buy vs Sell Delta: Integrated volume analysis for every FVG shows institutional pressure
Display Formats: Decimal ratios, percentages, or raw values (with K/M/B suffixes)
Volume Modes: Bar Delta (fast & reliable, recommended), Tick Delta (optional, feed-dependent)
Clear "+" (buy) and "–" (sell) prefixes for instant reading
🎨 Fully Customizable Appearance
Color Control: Color pickers for Bullish/Bearish FVG fills & Filled state colors (different from active), Band lines, midlines, and text labels.
Formation and fill tag markers
Line Styling: Color & Width
🔔 Alerts
Toggle formation/fill alerts independently
🏷 Tags
Visual Tags: Show markers - Text / Icon per event type
Icon choices: Circle, Square, Diamond, Star, Up/Down Arrow
Independent colors for formation vs fill tags
Auto-remove "formed" tag when "filled" tag appears
Configurable size and positioning
🧩 Rendering & Fill Display
Triple-Band Display: Upper, mid, and lower boundary lines with configurable styles
Filled Rectangle: Semi-transparent fill between boundaries for clear visualization
Fill State Management: Hide filled gaps completely, or keep them visible with distinct "filled" colors.
"Use Filled Colours" option for easy state identification
Quality Filters: Minimum body size filter (in chart points) to exclude noise from low-volatility periods
⚙️ Quality-of-Life Features
Performance Optimized: Efficient HTF/LTF time mapping with binary search algorithms
Cross-Symbol Compatible: Robust handling across all symbols and data feeds
Sensible Defaults: Works beautifully out of the box—tweak only what you need
Minimal Chart Clutter: Designed to keep critical information visible without overwhelming your workspace
💡 Perfect For
Institutional gap traders who need precision and control
Multi-timeframe analysts requiring HTF context on LTF charts
Volume profile traders seeking buy/sell pressure confirmation
Traders who value clean, professional chart aesthetics
Anyone tired of indicators that force rigid workflows
Fair Value Gap Pro doesn't just show you gaps—it gives you the complete institutional picture with the flexibility to trade your way.
Force DashboardScalping Dashboard - Complete User Guide
Overview
This scalping system consists of two complementary TradingView indicators designed for intraday trading with no overnight holds:
Force Dashboard - Single-row table showing real-time market bias and entry signals
Large Order Detection - Visual diamonds showing institutional order flow
Together, they provide a complete at-a-glance view of market conditions optimized for quick entries and exits.
Recommended Timeframes
Primary Scalping Timeframes
1-minute chart: Ultra-fast scalps (30 seconds - 3 minutes hold time)
2-minute chart: Quick scalps (2-5 minutes hold time)
5-minute chart: Standard scalps (5-15 minutes hold time)
Best Practices
Use 1-2 minute for highly liquid instruments (ES, NQ, major forex pairs)
Use 5-minute for less liquid markets or if you prefer fewer signals
Never hold past the last hour of trading to avoid overnight risk
Set hard stop times (e.g., exit all positions by 3:45 PM EST)
Dashboard Components Explained
Core Indicators (Circles ●)
MACD (5/13/5)
Green ● = Bullish momentum (MACD histogram positive)
Red ● = Bearish momentum (MACD histogram negative)
Gray ● = No clear momentum
Use: Confirms trend direction and momentum shifts
EMA (9/20/50)
Green ● = Price > EMA9 > EMA20 (uptrend)
Red ● = Price < EMA9 < EMA20 (downtrend)
Gray ● = Choppy/sideways
Use: Identifies the immediate micro-trend
Stoch (5-period Stochastic)
Green ● = Oversold (<20) - potential reversal up
Red ● = Overbought (>80) - potential reversal down
Gray ● = Neutral zone (20-80)
Use: Spots reversal opportunities at extremes
RSI (7-period)
Green ● = Oversold (<30)
Red ● = Overbought (>70)
Gray ● = Neutral
Use: Confirms overbought/oversold conditions
CVD (Cumulative Volume Delta)
Green ● = CVD above its moving average (buying pressure)
Red ● = CVD below its moving average (selling pressure)
Gray ● = Neutral
Use: Shows overall buying vs selling pressure
ΔCVD (Delta CVD - Rate of Change)
Green ● = CVD accelerating upward (buying acceleration)
Red ● = CVD accelerating downward (selling acceleration)
Gray ● = No acceleration
Use: Detects momentum shifts in order flow
Imbal (Order Flow Imbalance)
Green ● = Buy pressure >2x sell pressure
Red ● = Sell pressure >2x buy pressure
Gray ● = Balanced
Use: Identifies extreme one-sided order flow
Vol (Volume Strength)
Green ● = Volume >1.5x average (strong interest)
Red ● = Volume <0.7x average (low interest)
Gray ● = Normal volume
Yellow background = Volume surge (>2x average) - BIG MOVE ALERT
Use: Confirms conviction behind price moves
Tape (Tape Speed)
Green ● = Fast order flow (>1.3x normal)
Red ● = Slow order flow (<0.7x normal)
Gray ● = Normal speed
Yellow background = Very fast tape (>1.5x) - RAPID EXECUTION ALERT
Use: Measures urgency and speed of orders
Key Levels
Support (Supp)
Shows the nearest high-volume support level below current price
Bright Green background = Price is AT support (within 0.3%) - BOUNCE ZONE
Green background = Price above support (healthy)
Red background = Price below support (broken support, now resistance)
Resistance (Res)
Shows the nearest high-volume resistance level above current price
Bright Orange background = Price is AT resistance (within 0.3%) - REJECTION ZONE
Red background = Price below resistance (facing overhead supply)
Green background = Price above resistance (breakout)
These levels update automatically every 3 bars based on volume profile
Entry Signal Components
Score
Displays format: "6L" (6 long indicators) or "4S" (4 short indicators)
Bright Green = 6-7 indicators aligned for long
Light Green = 5 indicators aligned for long
Yellow = 4 indicators aligned (weaker setup)
Gray = No alignment
Red/Orange colors = Same scale for short setups
Score of 5+ indicates high-probability setup
SCALP (Main Entry Signal)
BRIGHT GREEN "LONG" = High-quality long scalp (Score 5+)
Green "LONG" = Decent long scalp (Score 4)
BRIGHT ORANGE "SHORT" = High-quality short scalp (Score 5+)
Red "SHORT" = Decent short scalp (Score 4)
Gray "WAIT" = No clear setup - STAY OUT
Entry Strategies
Strategy 1: High-Probability Scalps (Conservative)
When to Enter:
SCALP column shows BRIGHT GREEN "LONG" or BRIGHT ORANGE "SHORT"
Score is 5 or higher
Vol or Tape has yellow background (volume surge)
Example Long Setup:
SCALP = BRIGHT GREEN "LONG"
Score = 6L
Vol = Yellow background
Price AT Support (bright green Supp cell)
EMA, MACD, CVD, ΔCVD, Imbal all green
Entry: Enter immediately on next candle
Target: 0.5-1% move or resistance level
Stop: Below support or -0.3%
Hold Time: 2-10 minutes
Strategy 2: Momentum Scalps (Aggressive)
When to Enter:
Tape has yellow background (fast tape)
Vol has yellow background (volume surge)
ΔCVD is green (for longs) or red (for shorts)
Imbal shows strong imbalance in your direction
Score is 4+
Example Short Setup:
Tape & Vol = Yellow backgrounds
ΔCVD = Red, Imbal = Red
Price AT Resistance (bright orange)
Score = 5S
Entry: Enter immediately
Target: Quick 0.3-0.7% move
Stop: Tight -0.2%
Hold Time: 1-5 minutes
Strategy 3: Reversal Scalps (Mean Reversion)
When to Enter:
Stoch shows oversold (green) or overbought (red)
RSI confirms the extreme
Price is AT Support (for longs) or AT Resistance (for shorts)
ΔCVD and Imbal start reversing direction
Score is 4+
Example Long Setup:
Stoch = Green (oversold)
RSI = Green (oversold)
Supp = Bright green (at support)
ΔCVD turns green
Imbal turns green
Score = 4L or 5L
Entry: Wait for confirmation candle
Target: Move back to EMA9 or mid-range
Stop: Below the low
Hold Time: 3-8 minutes
Large Order Detection Usage
Diamond Signals
Green diamonds below bar = Large buy orders (institutional buying)
Red diamonds above bar = Large sell orders (institutional selling)
Size matters: Larger diamonds = larger order flow
How to Use with Dashboard
Confirmation Entries
Dashboard shows "LONG" signal
Green diamond appears
Enter immediately - institutions are buying
Divergence Alerts (CAUTION)
Dashboard shows "LONG" signal
RED diamond appears (institutions selling)
DO NOT ENTER - conflicting order flow
Cluster Patterns
Multiple green diamonds in row = Strong accumulation, stay long
Multiple red diamonds in row = Strong distribution, stay short
Alternating colors = Chop, avoid trading
Risk Management Rules
Position Sizing
Risk 0.5-1% of account per scalp
Maximum 3 concurrent positions
Reduce size after 2 consecutive losses
Stop Loss Guidelines
Tight stops: 0.2-0.3% for 1-2 min charts
Standard stops: 0.3-0.5% for 5 min charts
Always use stop loss - no exceptions
Place stops below support (longs) or above resistance (shorts)
Take Profit Targets
Target 1: 0.3-0.5% (take 50% off)
Target 2: 0.7-1% (take remaining 50%)
Move stop to breakeven after Target 1 hit
Trail stop if Score remains high
Time-Based Exits
Exit immediately if:
SCALP changes from LONG/SHORT to WAIT
Score drops below 3
Large diamond appears in opposite direction
Maximum hold time: 15 minutes (even if profitable)
Hard exit time: 30 minutes before market close
Trading Sessions
Best Times to Scalp
High-Liquidity Sessions
9:30-11:00 AM EST (Market open, highest volume)
2:00-3:30 PM EST (Afternoon session, good moves)
Avoid
11:30 AM-1:30 PM EST (Lunch, low volume)
Last 30 minutes (unpredictable, don't initiate new trades)
News releases (wait 5 minutes for volatility to settle)
Common Patterns & Setups
The Perfect Storm (Highest Probability)
Score = 6L or 7L
SCALP = BRIGHT GREEN
Vol + Tape = Yellow backgrounds
Green diamond appears
Price AT Support
Win rate: ~70-80%
The Fade Setup (Counter-Trend)
Price hits resistance (bright orange)
Stoch + RSI overbought (red)
Red diamond appears
CVD starts turning red
SCALP shows "SHORT"
Win rate: ~60-70%
The Breakout Continuation
Price breaks resistance (Res turns green)
EMA, MACD green
Vol surge (yellow)
Multiple green diamonds
SCALP = "LONG"
Win rate: ~65-75%
Warning Signs - DO NOT TRADE
Red Flags
❌ SCALP shows "WAIT"
❌ Score below 3
❌ Vol and Tape both gray (no volume)
❌ Conflicting signals (dashboard says LONG but red diamonds appearing)
❌ Alternating green/red circles (choppy market)
❌ Support and Resistance very close together (tight range)
Market Conditions to Avoid
Low volume periods
Major news releases (first 5 minutes after)
First 2 minutes after market open
Wide spreads
Consecutive losing trades (take a break after 2 losses)
Quick Reference Checklist
Before Taking ANY Trade:
☑ SCALP shows LONG or SHORT (not WAIT)
☑ Score is 4 or higher
☑ Vol or Tape shows activity
☑ No conflicting diamond signals
☑ Stop loss level identified
☑ Target profit level identified
☑ Not in restricted time periods
After Entering:
☑ Set stop loss immediately
☑ Set profit targets
☑ Watch SCALP column - exit if changes to WAIT
☑ Watch for opposite-colored diamonds
☑ Move stop to breakeven after first target
☑ Exit all by market close
Advanced Tips
Scalping Psychology
Be patient: Wait for Score 5+ setups
Be decisive: When signal appears, act immediately
Be disciplined: Follow your stop loss always
Be flexible: Exit quickly if dashboard reverses
Optimization
Backtest on your specific instrument
Adjust RSI/Stoch levels for your market
Fine-tune volume thresholds
Keep a trade journal to track which setups work best
Multi-Timeframe Confirmation
Use 5-min dashboard as "trend filter"
Take 1-min trades only in direction of 5-min SCALP signal
Increases win rate by ~10-15%
Troubleshooting
Q: Dashboard shows WAIT most of the time
Normal - scalping is about patience. Quality > Quantity
3-8 good setups per day is excellent
Q: Too many false signals
Increase minimum Score requirement to 5 or 6
Only trade with volume surge (yellow backgrounds)
Add large order detection confirmation
Q: Signals too slow
You may be on too high a timeframe
Try 1-minute chart for faster signals
Ensure real-time data feed is active
Q: Support/Resistance not updating
Normal - updates every 3 bars
If completely stuck, remove and re-add indicator
Summary
This scalping system works best when:
✅ Multiple indicators align (Score 5+)
✅ Volume and tape speed confirm the move
✅ Order flow (diamonds) confirms direction
✅ Price is at key levels (support/resistance)
✅ You manage risk strictly
✅ You exit before market close
The golden rule: When SCALP says WAIT, you WAIT. Discipline beats frequency.
