Ben's BTC Macro Fair Value OscillatorBen's BTC Macro Fair Value Oscillator
Overview
The **BTC Macro Fair Value Oscillator** is a non-crypto fair value framework that uses macro asset relationships (equities, dollar, gold) to estimate Bitcoin's "macro-driven fair value" and identify mean-reversion opportunities.
"Is BTC cheap or expensive right now?" on the 4 Hour Timeframe ONLY
### Key Features
✅ **Macro-driven**: Uses QQQ, DXY, XAUUSD instead of on-chain or crypto metrics
✅ **Dynamic weighting**: Assets weighted by rolling correlation strength
✅ **Mean-reversion signals**: Identifies when BTC is cheap/expensive vs macro
✅ **Validated parameters**: Optimized through 5-year backtest (Sharpe 6.7-9.9)
✅ **Visual transparency**: Live correlation panel, fair value bands, statistics
✅ **Non-repainting**: All calculations use confirmed historical data only
### What This Indicator Does
- Builds a **synthetic macro composite** from traditional assets
- Runs a **rolling regression** to predict BTC price from macro
- Calculates **deviation z-score** (how far BTC is from macro fair value)
- Generates **entry signals** when BTC is extremely cheap vs macro (dev < -2)
- Generates **exit signals** when BTC returns to fair value (dev > 0)
### What This Indicator Is NOT
❌ Not a high-frequency trading system (sparse signals by design)
❌ Not optimized for absolute returns (optimized for Sharpe ratio)
❌ Not suitable as standalone trading system (best as overlay/confirmation)
❌ Not predictive of short-term price movements (mean-reversion timeframe: days to weeks)
---
## Core Concept
### The Premise
Bitcoin doesn't trade in a vacuum. It's influenced by:
- **Risk appetite** (equities: QQQ, SPX)
- **Dollar strength** (DXY - inverse to risk assets)
- **Safe haven flows** (Gold: XAUUSD)
When macro conditions are "good for BTC" (risk-on, weak dollar, strong equities), BTC should trade higher. When macro conditions turn against it, BTC should trade lower.
### The Innovation
Instead of looking at BTC in isolation, this indicator:
1. **Measures how strongly** BTC currently correlates with each macro asset
2. **Builds a weighted composite** of those macro returns (the "D" driver)
3. **Regresses BTC price on D** to estimate "macro fair value"
4. **Tracks the deviation** between actual price and fair value
5. **Signals mean reversion** when deviation becomes extreme
### The Edge
The validated edge comes from:
- **Extreme deviations predict future returns** (dev < -2 → +1.67% over 12 bars)
- **Monotonic relationship** (more negative dev → higher forward returns)
- **Works out-of-sample** (test Sharpe +83-87% better than training)
- **Low correlation with buy & hold** (provides diversification value)
---
## Methodology
### Step 1: Macro Composite Driver D(t)
The indicator builds a weighted composite of macro asset returns:
**Process:**
1. Calculate **log returns** for BTC and each macro reference (QQQ, DXY, XAUUSD)
2. Compute **rolling correlation** between BTC and each reference over `corrLen` bars
3. **Weight each asset** by `|correlation|` if above `minCorrAbs` threshold, else 0
4. **Sign-adjust** weights (+1 for positive corr, -1 for negative) to handle inverse relationships
5. **Z-score normalize** each reference's returns over `fvWindow`
6. **Composite D(t)** = weighted sum of sign-adjusted z-scores
**Formula:**
```
For each reference i:
corr_i = correlation(BTC_returns, ref_i_returns, corrLen)
weight_i = |corr_i| if |corr_i| >= minCorrAbs else 0
sign_i = +1 if corr_i >= 0 else -1
z_i = (ref_i_returns - mean) / std
contrib_i = sign_i * z_i * weight_i
D(t) = sum(contrib_i) / sum(weight_i)
```
**Key Insight:** D(t) represents "how good macro conditions are for BTC right now" in a normalized, correlation-weighted way.
---
### Step 2: Fair Value Regression
Uses rolling linear regression to predict BTC price from D(t):
**Model:**
```
BTC_price(t) = α + β * D(t)
```
**Calculation (Pine Script approach):**
```
corr_CD = correlation(BTC_price, D, fvWindow)
sd_price = stdev(BTC_price, fvWindow)
sd_D = stdev(D, fvWindow)
cov = corr_CD * sd_price * sd_D
var_D = variance(D, fvWindow)
β = cov / var_D
α = mean(BTC_price) - β * mean(D)
fair_value(t) = α + β * D(t)
```
**Result:** A time-varying "macro fair value" line that adapts as correlations change.
---
### Step 3: Deviation Oscillator
Measures how far BTC price has deviated from fair value:
**Calculation:**
```
residual(t) = BTC_price(t) - fair_value(t)
residual_std = stdev(residual, normWindow)
deviation(t) = residual(t) / residual_std
```
**Interpretation:**
- `dev = 0` → BTC at fair value
- `dev = -2` → BTC is 2 standard deviations **cheap** vs macro
- `dev = +2` → BTC is 2 standard deviations **rich** vs macro
---
### Step 4: Signal Generation
**Long Entry:** `dev` crosses below `-2.0` (BTC extremely cheap vs macro)
**Long Exit:** `dev` crosses above `0.0` (BTC returns to fair value)
**No shorting** in default config (risk management choice - crypto volatility)
---
## How It Works
### Visual Components
#### 1. Price Chart (Main Panel)
**Fair Value Line (Orange):**
- The estimated "macro-driven fair value" for BTC
- Calculated from rolling regression on macro composite
**Fair Value Bands:**
- **±1σ** (light): 68% confidence zone
- **±2σ** (medium): 95% confidence zone
- **±3σ** (dark, dots): 99.7% confidence zone
**Entry/Exit Markers:**
- **Green "LONG" label** below bar: Entry signal (dev < -2)
- **Red "EXIT" label** above bar: Exit signal (dev > 0)
#### 2. Deviation Oscillator (Separate Pane)
**Line plot:**
- Shows current deviation z-score
- **Green** when dev < -2 (cheap)
- **Red** when dev > +2 (rich)
- **Gray** when neutral
**Histogram:**
- Visual representation of deviation magnitude
- Green bars = negative deviation (cheap)
- Red bars = positive deviation (rich)
**Threshold lines:**
- **Green dashed at -2.0**: Entry threshold
- **Red dashed at 0.0**: Exit threshold
- **Gray solid at 0**: Fair value line
#### 3. Correlation Panel (Top-Right)
Shows live correlation and weighting for each macro asset:
| Asset | Corr | Weight |
|-------|------|--------|
| QQQ | +0.45 | 0.45 |
| DXY | -0.32 | 0.32 |
| XAUUSD | +0.15 | 0.00 |
| Avg \|Corr\| | 0.31 | 0.77 |
**Reading:**
- **Corr**: Current rolling correlation with BTC (-1 to +1)
- **Weight**: How much this asset contributes to fair value (0 = excluded)
- **Avg |Corr|**: Average correlation strength (should be > 0.2 for reliable signals)
**Colors:**
- Green/Red corr = positive/negative correlation
- White weight = asset included, Gray = excluded (below minCorrAbs)
#### 4. Statistics Label (Bottom-Right)
```
━━━ BTC Macro FV ━━━
Dev: -2.34
Price: $103,192
FV: $110,500
Status: CHEAP ⬇
β: 103.52
```
**Fields:**
- **Dev**: Current deviation z-score
- **Price**: Current BTC close price
- **FV**: Current macro fair value estimate
- **Status**: CHEAP (< -2), RICH (> +2), or FAIR
- **β**: Current regression beta (sensitivity to macro)
---
## Installation & Setup
### TradingView Setup
1. Open TradingView and navigate to any **BTC chart** (BTCUSD, BTCUSDT, etc.)
2. Open **Pine Editor** (bottom panel)
3. Click **"+ New"** → **"Blank indicator"**
4. **Delete** all default code
5. **Copy** the entire Pine Script from `GHPT_optimized.pine`
6. **Paste** into the editor
7. Click **"Save"** and name it "BTC Macro Fair Value Oscillator"
8. Click **"Add to Chart"**
### Recommended Chart Settings
**Timeframe:** 4h (validated timeframe)
**Chart Type:** Candlestick or Heikin Ashi
**Overlay:** Yes (indicator plots on price chart + separate pane)
**Alternative Timeframes:**
- Daily: Works but slower signals
- 1h-2h: May work but not validated
- < 1h: Not recommended (too noisy)
### Symbol Requirements
**Primary:** BTC/USD or BTC/USDT on any exchange
**Macro References:** Automatically fetched
- QQQ (Nasdaq 100 ETF)
- DXY (US Dollar Index)
- XAUUSD (Gold spot)
**Data Requirements:**
- At least **90 bars** of history (warmup period)
- Premium TradingView recommended for full historical data
---
## Reading the Indicator
### Identifying Signals
#### Strong Long Signal (High Conviction)
- ✅ Deviation < -2.0 (extreme undervaluation)
- ✅ Avg |Corr| > 0.3 (strong macro relationships)
- ✅ Price touching or below -2σ band
- ✅ "LONG" label appears below bar
**Interpretation:** BTC is extremely cheap relative to macro conditions. Historical data shows +1.67% average return over next 12 bars (48 hours at 4h timeframe).
#### Moderate Long Signal (Lower Conviction)
- ⚠️ Deviation between -1.5 and -2.0
- ⚠️ Avg |Corr| between 0.2-0.3
- ⚠️ Price approaching -2σ band
**Interpretation:** BTC is cheap but not extreme. Consider as confirmation for other signals.
#### Exit Signal
- 🔴 Deviation crosses above 0 (returns to fair value)
- 🔴 "EXIT" label appears above bar
**Interpretation:** Mean reversion complete. Close long positions.
#### Strong Short/Avoid Signal
- 🔴 Deviation > +2.0 (extreme overvaluation)
- 🔴 Avg |Corr| > 0.3
- 🔴 Price touching or above +2σ band
**Interpretation:** BTC is expensive vs macro. Historical data shows -1.79% average return over next 12 bars. Consider exiting longs or reducing exposure.
### Regime Detection
**Strong Regime (Reliable Signals):**
- Avg |Corr| > 0.3
- Multiple assets weighted > 0
- Fair value line tracking price reasonably well
**Weak Regime (Unreliable Signals):**
- Avg |Corr| < 0.2
- Most weights = 0 (grayed out)
- Fair value line diverging wildly from price
- **Action:** Ignore signals until correlations strengthen
In den Scripts nach "entry" suchen
Average Price Calculator / VisualizerDCA Average Price Calculator - Visualize Your Breakeven & TP!
Ever wished you could visualize your trades and instantly see your average entry price right here on TradingView? Especially if you're a DCA (Dollar-Cost Averaging) trader like me, tracking multiple entries can be a hassle. You're constantly switching to a spreadsheet or calculator to figure out your breakeven and take-profit levels. Well I've developed this DCA Average Price Calculator to solve exactly that problem, bringing all your position planning directly onto your chart.
What It Does
This indicator is a interactive tool designed to calculate the weighted average price of up to 10 separate trade entries. It then plots your crucial breakeven (average price) and a customizable take-profit target directly on your chart, giving you a clear visual of your position.
Key Features
Up to 10 Order Entries: Plan complex DCA strategies with support for up to ten individual buys.
Flexible Size Input: Enter your position size in either USD Amount or Number of Shares/Contracts. The script is smart enough to know which one you're using.
Instant Average Price Calculation: Your weighted average price (your breakeven point) is calculated and plotted in real-time as a clean yellow line.
Customizable Take-Profit Target: Set your desired profit percentage and see your take-profit level instantly plotted as a green line.
Detailed On-Chart Labels: Each order you plot is marked with a detailed label showing the entry price, the number of shares purchased, and the total USD value of that entry.
Clean & Uncluttered UI: The main Average and TP labels are intelligently shifted to the right, ensuring they don't overlap with your entry markers, keeping your chart readable.
How to Use It - Simple Steps
Add the indicator to your chart.
Open the script's 'Settings' menu.
In the 'Take Profit' section, set your desired profit percentage (e.g., 1 for 1%).
Under the 'Orders' section, begin filling in your entries. For each 'Order #', enter the Price.
Next, enter the size. You can either fill in the 'Size (USD)' box OR the '/ Shares' box. Leave the one you're not using at 0.
As you add orders, the 'Avg' (yellow) and 'TP' (green) lines, along with the blue order labels, will automatically appear and adjust on your chart!
Who Is This For?
DCA Traders: This is the ultimate tool for you!
Position Traders: Keep track of scaling into a larger position over time.
Manual Backtesters: Quickly simulate and visualize how a series of buys would have played out.
Any Trader who wants a quick and easy way to calculate their average entry without leaving TradingView.
I built this tool to improve my own trading workflow, and I hope it helps you as much as it has helped me. If you find it useful, please consider giving it a 'Like' and feel free to leave any feedback or suggestions in the comments!
Happy trading
Volume Area 80 Rule Pro - Adaptive RTHSummary in one paragraph
Adaptive value area 80 percent rule for index futures large cap equities liquid crypto and major FX on intraday timeframes. It focuses activity only when multiple context gates align. It is original because the classic prior day value area traverse is fused with a daily regime classifier that remaps the operating parameters in real time.
Scope and intent
• Markets. ES NQ SPY QQQ large cap equities BTC ETH major FX pairs and other liquid RTH instruments
• Timeframes. One minute to one hour with daily regime context
• Default demo used in the publication. ES1 on five minutes
• Purpose. Trade only the balanced days where the 80 percent traverse has edge while standing aside or tightening rules during trend or shock
Originality and usefulness
• Unique fusion. Prior day value area logic plus a rolling daily regime classifier using percentile ranks of realized volatility and ADX. The regime remaps hold time end of window stop buffer and value area coverage on each session
• Failure mode addressed. False starts during strong trend or shock sessions and weak traverses during quiet grind
• Testability. All gates are visible in Inputs and debug flags can be plotted so users can verify why a suggestion appears
• Portable yardstick. The regime uses ATR divided by close and ADX percent ranks which behave consistently across symbols
Method overview in plain language
The script builds the prior session profile during regular trading hours. At the first regular bar it freezes yesterday value area low value area high and point of control. It then evaluates the current session open location the first thirty minute volume rank the open gap rank and an opening drive test. In parallel a daily series classifies context into Calm Balance Trend or Shock from rolling percentile ranks of realized volatility and ADX. The classifier scales the rules. Calm uses longer holds and a slightly wider value area. Trend and Shock shorten the window reduce holds and enlarge stop buffers.
Base measures
• Range basis. True Range smoothed over a configurable length on both the daily and intraday series
• Return basis. Not required. ATR over close is the unit for regime strength
Components
• Prior Value Area Engine. Builds yesterday value area low value area high and point of control from a binned volume profile with automatic TPO fallback and minimum integrity guards
• Opening Location. Detects whether the session opens above the prior value area or below it
• Inside Hold Counter. Counts consecutive bars that hold inside the value area after a re entry
• Volume Gate. Percentile of the first thirty minutes volume over a rolling sample
• Gap Gate. Percentile rank of the regular session open gap over a rolling sample
• Drive Gate. Opening drive check using a multiple of intraday ATR
• Regime Classifier. Percentile ranks of daily ATR over close and daily ADX classify Calm Balance Trend Shock and remap parameters
• Session windows optional. Windows follow the chart exchange time
Fusion rule
Minimum satisfied gates approach. A re entry must hold inside the value area for a regime scaled number of bars while the volume gap and drive gates allow the setup. The regime simultaneously scales value area coverage end minute time stop and stop buffer.
Signal rule
• Long suggestion appears when price opens below yesterday value area then re enters and holds for the required bars while all gates allow the setup
• Short suggestion appears when price opens above yesterday value area then re enters and holds for the required bars while all gates allow the setup
• WAIT shows implicitly when any required gate is missing
• Exit labels mark target touch stop touch or a time based close
Inputs with guidance
Setup
• Signal timeframe. Uses the chart by default
• Session windows optional. Start and end minutes inside regular trading hours
• Invert direction is not used. The logic is symmetric
Logic
• Hold bars inside value area. Typical range 3 to 12. Raising it reduces trades and favors better traverses. Lowering it increases frequency and risk of false starts
• Earliest minute since RTH open and Latest minute since RTH open. Typical range 0 to 390. Reducing the latest minute cuts late session trades
• Time stop bars after entry. Typical range 6 to 30. Larger values give setups more room
Filters
• Value area coverage. Typical range 0.70 to 0.85. Higher coverage narrows the traverse but accepts fewer days
• Bin size in ticks. Typical range 1 to 8. Larger bins stabilize noisy profiles
• Stop buffer ticks beyond edge. Typical range 2 to 20. Larger buffers survive noise
• First thirty minute volume percentile. Typical range 0.30 to 0.70. Higher values require more active opens
• Gap filter percentile. Typical range 0.70 to 0.95. Lower values block more gap days
• Opening drive multiple and bars. Higher multiple or longer bars block strong directional opens
Adaptivity
• Lookback days for regime ranks. Typical 150 to 500
• Calm RV percentile. Typical 25 to 45
• Trend ADX percentile. Typical 55 to 75
• Shock RV percentile. Typical 75 to 90
• End minute ratio in Trend and Shock. Typical 0.5 to 0.8
• Hold and Time stop scales per regime. Use values near one to keep behavior close to static settings
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Sessions use the chart exchange time
Honest limitations and failure modes
• Economic releases and thin liquidity can break the balance premise
• Gap heavy symbols may work better with stronger gap filters and a True Range focus
• Very quiet regimes reduce signal contrast. Consider longer windows or higher thresholds
Legal
Education and research only. Not investment advice. Test in simulation before any live use.
[Parth🇮🇳] Wall Street US30 Pro - Prop Firm Edition....Yo perfect! Here's the COMPLETE strategy in simple words:
***
## WALL STREET US30 TRADING STRATEGY - SIMPLE VERSION
### WHAT YOU'RE TRADING:
US30 (Dow Jones Index) on 1-hour chart using a professional indicator with smart money concepts.
---
### WHEN TO TRADE:
**6:30 PM - 10:00 PM IST every day** (London-NY overlap = highest volume)
***
### THE INDICATOR SHOWS YOU:
A table in top-right corner with 5 things:
1. **Signal Strength** - How confident (need 70%+)
2. **RSI** - Momentum (need OK status)
3. **MACD** - Trend direction (need UP for buys, DOWN for sells)
4. **Volume** - Real or fake move (need HIGH)
5. **Trend** - Overall direction (need UP for buys, DOWN for sells)
Plus **green arrows** (buy signals) and **red arrows** (sell signals).
---
### THE RULES:
**When GREEN ▲ arrow appears:**
- Wait for 1-hour candle to close (don't rush in)
- Check the table:
- Signal Strength 70%+ ? ✅
- Volume HIGH? ✅
- RSI okay? ✅
- MACD up? ✅
- Trend up? ✅
- If all yes = ENTER LONG (BUY)
- Set stop loss 40-50 pips below entry
- Set take profit 2x the risk (2:1 ratio)
**When RED ▼ arrow appears:**
- Wait for 1-hour candle to close (don't rush in)
- Check the table:
- Signal Strength 70%+ ? ✅
- Volume HIGH? ✅
- RSI okay? ✅
- MACD down? ✅
- Trend down? ✅
- If all yes = ENTER SHORT (SELL)
- Set stop loss 40-50 pips above entry
- Set take profit 2x the risk (2:1 ratio)
***
### REAL EXAMPLE:
**7:45 PM IST - Green arrow appears**
Table shows:
- Signal Strength: 88% 🔥
- RSI: 55 OK
- MACD: ▲ UP
- Volume: 1.8x HIGH
- Trend: 🟢 UP
All checks pass ✅
**8:00 PM - Candle closes, signal confirmed**
I check table again - still strong ✓
**I enter on prop firm:**
- BUY 0.1 lot
- Entry: 38,450
- Stop Loss: 38,400 (50 pips below)
- Take Profit: 38,550 (100 pips above)
- Risk: $50
- Reward: $100
- Ratio: 1:2 ✅
**9:30 PM - Price hits 38,550**
- Take profit triggered ✓
- +$100 profit
- Trade closes
**Done for that signal!**
***
### YOUR DAILY ROUTINE:
**6:30 PM IST** - Open TradingView + prop firm
**6:30 PM - 10 PM IST** - Watch for signals
**When signal fires** - Check table, enter if strong
**10:00 PM IST** - Close all trades, done
**Expected daily** - 1-3 signals, +$100-300 profit
***
### EXPECTED RESULTS:
**Win Rate:** 65-75% (most trades win)
**Signals per day:** 1-3
**Profit per trade:** $50-200
**Daily profit:** $100-300
**Monthly profit:** $2,000-6,000
**Monthly return:** 20-30% (on $10K account)
---
### WHAT MAKES THIS WORK:
✅ Uses 7+ professional filters (not just 1 indicator)
✅ Checks volume (real moves only)
✅ Filters overbought/oversold (avoids tops/bottoms)
✅ Aligns with 4-hour trend (higher timeframe)
✅ Only trades peak volume hours (6:30-10 PM IST)
✅ Uses support/resistance (institutional levels)
✅ Risk/reward 2:1 minimum (math works out)
***
### KEY DISCIPLINE RULES:
**DO:**
- ✅ Only trade 6:30-10 PM IST
- ✅ Wait for candle to close
- ✅ Check ALL 5 table items
- ✅ Only take 70%+ strength signals
- ✅ Always use stop loss
- ✅ Always 2:1 reward ratio
- ✅ Risk 1-2% per trade
- ✅ Close all trades by 10 PM
- ✅ Journal every trade
- ✅ Follow the plan
**DON'T:**
- ❌ Trade outside 6:30-10 PM IST
- ❌ Enter before candle closes
- ❌ Take weak signals (below 70%)
- ❌ Trade without stop loss
- ❌ Move stop loss (lock in loss)
- ❌ Hold overnight
- ❌ Revenge trade after losses
- ❌ Overleverge (more than 0.1 lot start)
- ❌ Skip journaling
- ❌ Deviate from plan
***
### THE 5-STEP ENTRY PROCESS:
**Step 1:** Arrow appears on chart ➜
**Step 2:** Wait for candle to close ➜
**Step 3:** Check table (all 5 items) ➜
**Step 4:** If all good = go to prop firm ➜
**Step 5:** Enter trade with SL & TP
Takes 30 seconds once you practice!
***
### MONEY MATH (Starting with $5,000):
**If you take 20 signals per month:**
- Win 15, Lose 5 (75% rate)
- Wins: 15 × $100 = $1,500
- Losses: 5 × $50 = -$250
- Net: +$1,250/month = 25% return
**Month 2:** $5,000 + $1,250 = $6,250 account
**Month 3:** $6,250 + $1,562 = $7,812 account
**Month 4:** $7,812 + $1,953 = $9,765 account
**Month 5:** $9,765 + $2,441 = $12,206 account
**Month 6:** $12,206 + $3,051 = $15,257 account
**In 6 months = $10,000 account → $15,000+ (50% growth)**
That's COMPOUNDING, baby! 💰
***
### START TODAY:
1. Copy indicator code
2. Add to 1-hour US30 chart on TradingView
3. Wait until 6:30 PM IST tonight (or tomorrow if late)
4. Watch for signals
5. Follow the rules
6. Trade your prop firm
**That's it! Simple as that!**
***
### FINAL WORDS:
This isn't get-rich-quick. This is build-wealth-steadily.
You follow the plan, take quality signals only, manage risk properly, you WILL make money. Not every trade wins, but the winners are bigger than losers (2:1 ratio).
Most traders fail because they:
- Trade too much (overtrading)
- Don't follow their plan (emotions)
- Risk too much per trade (blown account)
- Chase signals (FOMO)
- Don't journal (repeat mistakes)
You avoid those 5 things = you'll be ahead of 95% of traders.
**Start trading 6:30 PM IST. Let's go! 🚀**
Smart Risk - Three Institutional Models📘 Smart Risk – Three Institutional Entry Models
A precision-engineered institutional framework that blends liquidity, structure, and multi-time-frame confirmation.
🧠 Concept Overview
The Smart Risk indicator models how institutional traders and algorithms engineer entries around liquidity, imbalance, and structural shifts .
It unifies t hree distinct institutional entry models —each built around core Smart Money Concepts (SMC)—and enhances them with a Multi-Time-Frame Confluence (MTF) engine for directional alignment.
This tool doesn’t simply merge indicators.
It connects l iquidity sweeps, order-block reactions, breaker validation, and fair-value-gap mitigation into one cohesive trading logic—filtering every setup through trend, structure, and volume confirmation.
⚙️ How It Works
Setup #1 – Liquidity Sweep + Order Block Revisit + FVG Mitigation
Identifies engineered stop-hunts where price sweeps external liquidity and returns to a prior Order Block or Fair Value Gap (FVG).
Signals reversal-style entries with high probability of mean-reversion or mitigation.
Setup #2 – Supply/Demand + Mitigation / Breaker / FVG Continuation
Captures continuation trades inside trending structure.
When trend bias (via moving-average context) aligns with breaker or mitigation blocks, signals confirm institutional continuation sequences.
Setup #3 – Sweep + Classic FVG Reaction
Tracks clean displacement gaps following a liquidity sweep—ideal for scalpers and intraday reversals where imbalances act as magnets for price.
Each setup can be independently enabled or disabled from the panel.
A built-in signal-cooldown prevents repetitive triggers on the same leg.
🕒 Multi-Time-Frame Confluence
The new MTF module aligns lower-time-frame precision entries with higher-time-frame market structure.
When enabled, each setup only validates if the HTF trend confirms the same directional bias as the LTF pattern—e.g. a 5-minute bullish FVG signal requires a bullish 1-hour structure.
This ensures institutional logic respects global liquidity flow and avoids counter-trend traps.
MTF Controls:
• ✅ Enable MTF Confluence toggle
• ⏱️ Lower Time-Frame (LTF) selector (default 5 min)
• ⏱️ Higher Time-Frame (HTF) selector (default 1 hour)
• 🔄 Automatic SMA-based HTF trend detection
🎨 Visualization & Dashboard
• Order Block / Supply–Demand Zones — highlight institutional footprints
• Fair Value Gaps (FVGs) — reveal displacement inefficiencies
• Liquidity Sweeps (X / $) — mark engineered stops
• BOS & CHoCH — confirm structure continuation or reversal
• Compact Dashboard — live “Armed” state for each setup and MTF bias
Color-coded background cues emphasize active trade phases without clutter.
🧩 Core Algorithm Highlights
• Dynamic swing and pivot structure detection
• Breaker / Mitigation / Volume confirmation filters
• Fair-Value-Gap logic with directional alignment
• Cooldown control for signal throttling
• Multi-Time-Frame bias filter for contextual precision
⸻
📈 How to Use
1. Apply indicator to any asset or timeframe.
2. Select which institutional setups you want active.
3. Optionally enable MTF Confluence (5 min → 1 hr recommended).
4. Wait for BOS/CHoCH confirmation + zone alignment before entry.
5. Use OB and FVG zones for entry/exit planning with risk management.
⸻
💡 Originality Statement
This script introduces a multi-layered institutional logic engine that merges liquidity, mitigation, and imbalance behavior into a unified framework—augmented with time-frame synchronization and signal-cooldown management.
All logic, calculations, and visualization structure were built from scratch for this model.
It is not a mash-up of existing public indicators and offers measurable analytical value through MTF-aware trade validation.
⸻
⚠️ Disclaimer
This tool is intended for educational and analytical purposes only.
It does not provide financial advice or guaranteed trading outcomes.
Always back-test, validate setups, and apply proper risk management.
MTF K-Means Price Regimes [matteovesperi] ⚠️ The preview uses a custom example to identify support/resistance zones. due to the fact that this identifier clusterizes, this is possible. this example was set up "in a hurry", therefore it has a possible inaccuracy. When setting up the indicator, it is extremely important to select the correct parameters and double-check them on the selected history.
📊 OVERVIEW
Purpose
MTF K-Means Price Regimes is a TradingView indicator that automatically identifies and classifies the current market regime based on the K-Means machine learning algorithm. The indicator uses data from a higher timeframe (Multi-TimeFrame, MTF) to build stable classification and applies it to the working timeframe in real-time.
Key Features
✅ Automatic market regime detection — the algorithm finds clusters of similar market conditions
✅ Multi-timeframe (MTF) — clustering on higher TF, application on lower TF
✅ Adaptive — model recalculates when a new HTF bar appears with a rolling window
✅ Non-Repainting — classification is performed only on closed bars
✅ Visualization — bar coloring + information panel with cluster characteristics
✅ Flexible settings — from 2 to 10 clusters, customizable feature periods, HTF selection
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🔬 TECHNICAL DETAILS
K-Means Clustering Algorithm
What is K-Means?
K-Means is one of the most popular clustering algorithms (unsupervised machine learning). It divides a dataset into K groups (clusters) so that similar elements are within each cluster, and different elements are between clusters.
Algorithm objective:
Minimize within-cluster variance (sum of squared distances from points to their cluster center).
How Does K-Means Work in Our Indicator?
Step 1: Data Collection
The indicator accumulates history from the higher timeframe (HTF):
RSI (Relative Strength Index) — overbought/oversold indicator
ATR% (Average True Range as % of price) — volatility indicator
ΔP% (Price Change in %) — trend strength and direction indicator
By default, 200 HTF bars are accumulated (clusterLookback parameter).
Step 2: Creating Feature Vectors
Each HTF bar is described by a three-dimensional vector:
Vector =
Step 3: Normalization (Z-Score)
All features are normalized to bring them to a common scale:
Normalized_Value = (Value - Mean) / StdDev
This is critically important, as RSI is in the range 0-100, while ATR% and ΔP% have different scales. Without normalization, one feature would dominate over others.
Step 4: K-Means++ Centroid Initialization
Instead of random selection of K initial centers, an improved K-Means++ method is used:
First centroid is randomly selected from the data
Each subsequent centroid is selected with probability proportional to the square of the distance to the nearest already selected centroid
This ensures better initial centroid distribution and faster convergence
Step 5: Iterative Optimization (Lloyd's Algorithm)
Repeat until convergence (or maxIterations):
1. Assignment step:
For each point find the nearest centroid and assign it to this cluster
2. Update step:
Recalculate centroids as the average of all points in each cluster
3. Convergence check:
If centroids shifted less than 0.001 → STOP
Euclidean distance in 3D space is used:
Distance = sqrt((RSI1 - RSI2)² + (ATR1 - ATR2)² + (ΔP1 - ΔP2)²)
Step 6: Adaptive Update
With each new HTF bar:
The oldest bar is removed from history (rolling window method)
New bar is added to history
K-Means algorithm is executed again on updated data
Model remains relevant for current market conditions
Real-Time Classification
After building the model (clusters + centroids), the indicator works in classification mode:
On each closed bar of the current timeframe, RSI, ATR%, ΔP% are calculated
Feature vector is normalized using HTF statistics (Mean/StdDev)
Distance to all K centroids is calculated
Bar is assigned to the cluster with minimum distance
Bar is colored with the corresponding cluster color
Important: Classification occurs only on a closed bar (barstate.isconfirmed), which guarantees no repainting .
Data Architecture
Persistent variables (var):
├── featureVectors - Normalized HTF feature vectors
├── centroids - Cluster center coordinates (K * 3 values)
├── assignments - Assignment of each HTF bar to a cluster
├── htfRsiHistory - History of RSI values from HTF
├── htfAtrHistory - History of ATR values from HTF
├── htfPcHistory - History of price changes from HTF
├── htfCloseHistory - History of close prices from HTF
├── htfRsiMean, htfRsiStd - Statistics for RSI normalization
├── htfAtrMean, htfAtrStd - Statistics for ATR normalization
├── htfPcMean, htfPcStd - Statistics for Price Change normalization
├── isCalculated - Model readiness flag
└── currentCluster - Current active cluster
All arrays are synchronized and updated atomically when a new HTF bar appears.
Computational Complexity
Data collection: O(1) per bar
K-Means (one pass):
- Assignment: O(N * K) where N = number of points, K = number of clusters
- Update: O(N * K)
- Total: O(N * K * I) where I = number of iterations (usually 5-20)
Example: With N=200 HTF bars, K=5 clusters, I=20 iterations:
200 * 5 * 20 = 20,000 operations (executes quickly)
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📖 USER GUIDE
Quick Start
1. Adding the Indicator
TradingView → Indicators → Favorites → MTF K-Means Price Regimes
Or copy the code from mtf_kmeans_price_regimes.pine into Pine Editor.
2. First Launch
When adding the indicator to the chart, you'll see a table in the upper right corner:
┌─────────────────────────┐
│ Status │ Collecting HTF │
├─────────────────────────┤
│ Collected│ 15 / 50 │
└─────────────────────────┘
This means the indicator is accumulating history from the higher timeframe. Wait until the counter reaches the minimum (default 50 bars for K=5).
3. Active Operation
After data collection is complete, the main table with cluster information will appear:
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
The arrow ► indicates the current active regime. Chart bars are colored with the corresponding cluster color.
Customizing for Your Strategy
Choosing Higher Timeframe (HTF)
Rule: HTF should be at least 4 times higher than the working timeframe.
| Working TF | Recommended HTF |
|------------|-----------------|
| 1 min | 15 min - 1H |
| 5 min | 1H - 4H |
| 15 min | 4H - D |
| 1H | D - W |
| 4H | D - W |
| D | W - M |
HTF Selection Effect:
Lower HTF (closer to working TF): More sensitive, frequently changing classification
Higher HTF (much larger than working TF): More stable, long-term regime assessment
Number of Clusters (K)
K = 2-3: Rough division (e.g., "uptrend", "downtrend", "flat")
K = 4-5: Optimal for most cases (DEFAULT: 5)
K = 6-8: Detailed segmentation (requires more data)
K = 9-10: Very fine division (only for long-term analysis with large windows)
Important constraint:
clusterLookback ≥ numClusters * 10
I.e., for K=5 you need at least 50 HTF bars, for K=10 — at least 100 bars.
Clustering Depth (clusterLookback)
This is the rolling window size for building the model.
50-100 HTF bars: Fast adaptation to market changes
200 HTF bars: Optimal balance (DEFAULT)
500-1000 HTF bars: Long-term, stable model
If you get an "Insufficient data" error:
Decrease clusterLookback
Or select a lower HTF (e.g., "4H" instead of "D")
Or decrease numClusters
Color Scheme
Default 10 colors:
Red → Often: strong bearish, high volatility
Orange → Transition, medium volatility
Yellow → Neutral, decreasing activity
Green → Often: strong bullish, high volatility
Blue → Medium bullish, medium volatility
Purple → Oversold, possible reversal
Fuchsia → Overbought, possible reversal
Lime → Strong upward momentum
Aqua → Consolidation, low volatility
White → Undefined regime (rare)
Important: Cluster colors are assigned randomly at each model recalculation! Don't rely on "red = bearish". Instead, look at the description in the table (RSI, ATR%, ΔP%).
You can customize colors in the "Colors" settings section.
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⚙️ INDICATOR PARAMETERS
Main Parameters
Higher Timeframe (htf)
Type: Timeframe selection
Default: "D" (daily)
Description: Timeframe on which the clustering model is built
Recommendation: At least 4 times larger than your working TF
Clustering Depth (clusterLookback)
Type: Integer
Range: 50 - 2000
Default: 200
Description: Number of HTF bars for building the model (rolling window size)
Recommendation:
- Increase for more stable long-term model
- Decrease for fast adaptation or if there's insufficient historical data
Number of Clusters (K) (numClusters)
Type: Integer
Range: 2 - 10
Default: 5
Description: Number of market regimes the algorithm will identify
Recommendation:
- K=3-4 for simple strategies (trending/ranging)
- K=5-6 for universal strategies
- K=7-10 only when clusterLookback ≥ 100*K
Max K-Means Iterations (maxIterations)
Type: Integer
Range: 5 - 50
Default: 20
Description: Maximum number of algorithm iterations
Recommendation:
- 10-20 is sufficient for most cases
- Increase to 30-50 if using K > 7
Feature Parameters
RSI Period (rsiLength)
Type: Integer
Default: 14
Description: Period for RSI calculation (overbought/oversold feature)
Recommendation:
- 14 — standard
- 7-10 — more sensitive
- 20-25 — more smoothed
ATR Period (atrLength)
Type: Integer
Default: 14
Description: Period for ATR calculation (volatility feature)
Recommendation: Usually kept equal to rsiLength
Price Change Period (pcLength)
Type: Integer
Default: 5
Description: Period for percentage price change calculation (trend feature)
Recommendation:
- 3-5 — short-term trend
- 10-20 — medium-term trend
Visualization
Show Info Panel (showDashboard)
Type: Checkbox
Default: true
Description: Enables/disables the information table on the chart
Cluster Color 1-10
Type: Color selection
Description: Customize colors for visual cluster distinction
Recommendation: Use contrasting colors for better readability
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📊 INTERPRETING RESULTS
Reading the Information Table
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
│ 4 │ 45.0 │ 1.20 │ -0.3 │ Low Vol,Bear │ │
│ 5 │ 72.1 │ 3.05 │ 2.8 │ High Vol,Bull│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
"ID" Column
Cluster number (1-K). Order doesn't matter.
"RSI" Column
Average RSI value in the cluster (0-100):
< 30: Oversold zone
30-45: Bearish sentiment
45-55: Neutral zone
55-70: Bullish sentiment
> 70: Overbought zone
"ATR%" Column
Average volatility in the cluster (as % of price):
< 1%: Low volatility (consolidation, narrow range)
1-2%: Normal volatility
2-3%: Elevated volatility
> 3%: High volatility (strong movements, impulses)
Compared to the average volatility across all clusters to determine "High Vol" or "Low Vol".
"ΔP%" Column
Average price change in the cluster (in % over pcLength period):
> +0.05%: Bullish regime
-0.05% ... +0.05%: Flat (sideways movement)
< -0.05%: Bearish regime
"Description" Column
Automatic interpretation:
"High Vol, Bull" → Strong upward momentum, high activity
"Low Vol, Flat" → Consolidation, narrow range, uncertainty
"High Vol, Bear" → Strong decline, panic, high activity
"Low Vol, Bull" → Slow growth, low activity
"Low Vol, Bear" → Slow decline, low activity
"Current" Column
Arrow ► shows which cluster the last closed bar of your working timeframe is in.
Typical Cluster Patterns
Example 1: Trend/Flat Division (K=3)
Cluster 1: RSI=65, ATR%=2.5, ΔP%=+1.5 → Bullish trend
Cluster 2: RSI=50, ATR%=0.8, ΔP%=0.0 → Flat/Consolidation
Cluster 3: RSI=35, ATR%=2.3, ΔP%=-1.4 → Bearish trend
Strategy: Open positions when regime changes Flat → Trend, avoid flat.
Example 2: Volatility Breakdown (K=5)
Cluster 1: RSI=72, ATR%=3.5, ΔP%=+2.5 → Strong bullish impulse (high risk)
Cluster 2: RSI=60, ATR%=1.5, ΔP%=+0.8 → Moderate bullish (optimal entry point)
Cluster 3: RSI=50, ATR%=0.7, ΔP%=0.0 → Flat
Cluster 4: RSI=40, ATR%=1.4, ΔP%=-0.7 → Moderate bearish
Cluster 5: RSI=28, ATR%=3.2, ΔP%=-2.3 → Strong bearish impulse (panic)
Strategy: Enter in Cluster 2 or 4, avoid extremes (1, 5).
Example 3: Mixed Regimes (K=7+)
With large K, clusters can represent condition combinations:
High RSI + Low volatility → "Quiet overbought"
Neutral RSI + High volatility → "Uncertainty with high activity"
Etc.
Requires individual analysis of each cluster.
Regime Changes
Important signal: Transition from one cluster to another!
Trading situation examples:
Flat → Bullish trend → Buy signal
Bullish trend → Flat → Take profit, close longs
Flat → Bearish trend → Sell signal
Bearish trend → Flat → Close shorts, wait
You can build a trading system based on the current active cluster and transitions between them.
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💡 USAGE EXAMPLES
Example 1: Scalping with HTF Filter
Task: Scalping on 5-minute charts, but only enter in the direction of the daily regime.
Settings:
Working TF: 5 min
HTF: D (daily)
K: 3 (simple division)
clusterLookback: 100
Logic:
IF current cluster = "Bullish" (ΔP% > 0.5)
→ Look for long entry points on 5M
IF current cluster = "Bearish" (ΔP% < -0.5)
→ Look for short entry points on 5M
IF current cluster = "Flat"
→ Don't trade / reduce risk
Example 2: Swing Trading with Volatility Filtering
Task: Swing trading on 4H, enter only in regimes with medium volatility.
Settings:
Working TF: 4H
HTF: D (daily)
K: 5
clusterLookback: 200
Logic:
Allowed clusters for entry:
- ATR% from 1.5% to 2.5% (not too quiet, not too chaotic)
- ΔP% with clear direction (|ΔP%| > 0.5)
Prohibited clusters:
- ATR% > 3% → Too risky (possible gaps, sharp reversals)
- ATR% < 1% → Too quiet (small movements, commissions eat profit)
Example 3: Portfolio Rotation
Task: Managing a portfolio of multiple assets, allocate capital depending on regimes.
Settings:
Working TF: D (daily)
HTF: W (weekly)
K: 4
clusterLookback: 100
Logic:
For each asset in portfolio:
IF regime = "Strong trend + Low volatility"
→ Increase asset weight in portfolio (40-50%)
IF regime = "Medium trend + Medium volatility"
→ Standard weight (20-30%)
IF regime = "Flat" or "High volatility without trend"
→ Minimum weight or exclude (0-10%)
Example 4: Combining with Other Indicators
MTF K-Means as a filter:
Main strategy: MA Crossover
Filter: MTF K-Means on higher TF
Rule:
IF MA_fast > MA_slow AND Cluster = "Bullish regime"
→ LONG
IF MA_fast < MA_slow AND Cluster = "Bearish regime"
→ SHORT
ELSE
→ Don't trade (regime doesn't confirm signal)
This dramatically reduces false signals in unsuitable market conditions.
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📈 OPTIMIZATION RECOMMENDATIONS
Optimal Settings for Different Styles
Day Trading
Working TF: 5M - 15M
HTF: 1H - 4H
numClusters: 4-5
clusterLookback: 100-150
Swing Trading
Working TF: 1H - 4H
HTF: D
numClusters: 5-6
clusterLookback: 150-250
Position Trading
Working TF: D
HTF: W - M
numClusters: 4-5
clusterLookback: 100-200
Scalping
Working TF: 1M - 5M
HTF: 15M - 1H
numClusters: 3-4
clusterLookback: 50-100
Backtesting
To evaluate effectiveness:
Load historical data (minimum 2x clusterLookback HTF bars)
Apply the indicator with your settings
Study cluster change history:
- Do changes coincide with actual trend transitions?
- How often do false signals occur?
Optimize parameters:
- If too much noise → increase HTF or clusterLookback
- If reaction too slow → decrease HTF or increase numClusters
Combining with Other Techniques
Regime-Based Approach:
MTF K-Means (regime identification)
↓
+---+---+---+
| | | |
v v v v
Trend Flat High_Vol Low_Vol
↓ ↓ ↓ ↓
Strategy_A Strategy_B Don't_trade
Examples:
Trend: Use trend-following strategies (MA crossover, Breakout)
Flat: Use mean-reversion strategies (RSI, Bollinger Bands)
High volatility: Reduce position sizes, widen stops
Low volatility: Expect breakout, don't open positions inside range
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📞 SUPPORT
Report an Issue
If you found a bug or have a suggestion for improvement:
Describe the problem in as much detail as possible
Specify your indicator settings
Attach a screenshot (if possible)
Specify the asset and timeframe where the problem is observed
The VWAP OracleOverview
The VWAP Oracle is a sophisticated overlay indicator that elevates VWAP (Volume Weighted Average Price) from a simple benchmark to an intelligent oracle for intraday and swing decisions. It offers flexible anchoring (rolling MVWAP, weekly, monthly, yearly) with session options, augmented by heuristic "AI/ML" elements for trend forecasting, dynamic S/R identification, and mean-reversion pullback strategies. A comprehensive dashboard delivers at-a-glance intel on trends, roles, touch history, and trade stats, complemented by visual zones, entry shapes, and alerts. Tailored for active traders in equities, forex, or futures, this iteration refines state handling and role logic for seamless execution on Pine v6.
Core Mechanics
Built around robust VWAP computations with layered analytics:
VWAP Framework: Primary line via user-selected type—Rolling (volume-weighted over lookback bars for agility), or Anchored (resets on week/month/year changes). HLC3 source standard; regular or 24h sessions. Toggles for secondary lines (e.g., weekly in orange for context).
Heuristic Enhancements: ATR safeguards (min tick fallback) normalize zones (± sensitivity * ATR for touches) and distances (e.g., 3x for setups). Linear regression over lookback derives slope (ATR-scaled for cross-asset comparability), flagging strong trends (> threshold) with rising/falling confirmation and volume >20-bar SMA.
Role & Proximity Engine: Scans enabled VWAPs globally—assigns nearest as support (price above, higher value prioritized) or resistance (below, lower prioritized), e.g., "Weekly" if closest. Tracks main VWAP touches for strength tiers (Weak <3, Moderate 3-4, Strong 5-7, Proven ≥8).
Pullback Strategy: In validated trends (slope + price move + volume), distant deviations (> ATR multiple) trigger "awaiting" state. Confirms entries on fresh touches with directional candles (close > open for longs), setting ATR-based stops (1x offset from VWAP) and targets (2x extension). Manages to hit (success tally) or breach (reset); daily/anchor resets clear stats.
Outputs: Trend-colored VWAP (blue/red in strong regimes, gray in range), role-tinted zones (green/red fill), triangles for entries, labels for outcomes.
Why This Mashup Adds Value & Originality
Traditional VWAPs are passive lines; multi-anchor plots add clutter without synthesis. Here, the fusion of anchored/rolling VWAPs with regression-normalized "AI" slope (volatility-adjusted for invariance) and touch-based strength scoring forms a predictive layer—e.g., "Proven" supports from 8+ interactions signal higher-probability bounces than raw levels. Stateful pullback logic (distant setup → touch entry → managed exit) with explicit breach cancels differentiates it from basic deviation oscillators, while the 11-row dashboard (trend icons, nearest roles, live success %) consolidates what would take multiple indicators. Global role reassignment (no function var limits) ensures accuracy, creating a unified "oracle" for confluence without redundancy—ideal for evolving static VWAP into adaptive decision support.
How to Use
Configuration: Overlay on chart. VWAP: Pick Rolling for scalps (252-bar default); enable weeklies for bias. AI: ATR 14, sensitivity 0.5 (tighter for precision). Trade: 3x min distance setups, 2x/1x target/stop. Visuals: Dashboard top-right, zones on, signals toggled.
Dashboard Readout (semi-opaque black, size-adjustable):
Header/Type: "The VWAP Oracle" + active (e.g., "Rolling (MVWAP)").
Trend: 🔵/🔴 Strong or ⚪ Range—align trades accordingly.
Nearest S/R: "Main" support (green) for bounces; "Monthly" resistance (red) for fades.
Strength/Role: "Strong (5 touches)"; "Support" for current main bias.
Position: "🔄 Pullback Setup" flags opportunity; "⏳ Awaiting" pre-entry.
Success/Setup: "80% (4/5)"; 🟢 Long Active if running; volume "✅ Strong" validates.
Execution: Strong bull + distant alert → Long on green triangle touch → Trail to target label (✓) or stop (✗). Use zones for invalidation; alerts cover setups/hits. Suits 15m-4H on majors like NAS100.
Pro Tips: Backtest resets (daily intraday); tweak slope threshold (1.5) for noise.
Limitations & Disclaimer
Touches and entries confirm on close, introducing minor lag; rolling VWAP smooths but may trail sharp moves. Slope can oscillate in transitions—add manual filters. Stats reset periodically (e.g., daily), so sample sizes vary; "success" is backward-looking. No auto-sizing—cap risk at 1% equity. v6-optimized, but verify on live data. Not advice; simulate trades, as history ≠ future. Feedback welcome in comments.
SC_Reversal Confirmation 30 minutes by Claude (Version 1)📉 When to Use
Use this setup when the stock is in a downtrend and a bullish reversal is anticipated.
🔍 Recommended Usage This model is designed for pullback phases, where the asset is declining and a reversal is expected. It helps filter out weak signals and waits for technical confirmation before triggering an entry.
✅ Entry Signal Green triangles appear only when all reversal conditions are fully met. Entry may occur slightly after the bottom, but with a reduced likelihood of false signals.
📊 Suggested Settings Apply on a 30-minute chart using a 100-period Exponential Moving Average (EMA) based on close. Recommended for Cobalt Chart 0.
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VAGANZA Swings V1 LITE1. Introduction: The Philosophy Behind VAGANZA Swings
The VAGANZA Swings V1 LITE was developed to solve a common problem faced by swing traders: getting caught in low-probability trades during choppy, sideways markets. Many indicators can identify a trend, but few can effectively measure its quality and pinpoint optimal, low-risk entry points within that trend.
This script is not merely a "mashup" of existing indicators. It is a structured, multi-layered filtering system where each component is specifically chosen to address the weaknesses of the others. The core philosophy is to trade only when there is a clear market consensus, confirmed by trend, strength, momentum, and volume. This results in fewer signals, but each signal is designed to be of significantly higher quality.
2. The VAGANZA Confirmation Engine: A Deeper Look at the Logic
A signal is only generated when four distinct market conditions align. This sequential confirmation process is what makes the script unique and robust.
Layer 1: The Trend Regime Filter
What it does: The indicator first establishes the dominant market bias using a dual-speed baseline system. A faster-reacting baseline is compared against a slower, more stable baseline to determine if the market is in a long-term bullish or bearish "regime."
Why it's important: This foundational step ensures we are never fighting the primary market current. BUY signals are disabled during a bearish regime, and SELL signals are disabled during a bullish regime, instantly eliminating 50% of potentially bad trades.
Layer 2: The Trend Strength & Conviction Qualifier
What it does: This is the script's core intelligence. After confirming the trend's direction, this layer uses a directional volatility engine to measure the trend's strength or conviction. It analyzes the expansion between bullish and bearish price movements.
Why it's important: A simple moving average crossover can occur in a weak, drifting market, leading to false signals. This filter requires the trend to be demonstrably powerful (above a predefined strength threshold of 25) before allowing the system to even look for an entry. It's the primary filter for avoiding sideways market traps.
Layer 3: The Dynamic Pullback & Entry Trigger
What it does: Instead of chasing price at its peak, the script waits for a natural "breather" or pullback. It employs a momentum cycle oscillator to identify when the price has become temporarily oversold within a strong uptrend, or overbought within a strong downtrend. The signal is triggered at the precise moment momentum appears to be rejoining the primary trend.
Why it's important: This ensures a more favorable risk-to-reward ratio. By entering on a pullback, traders can avoid buying the top or selling the bottom of a short-term swing, which is a common mistake.
Layer 4: The Volume Participation Check
What it does: As a final confirmation, the script checks the volume on the signal candle. It requires the volume to be higher than its recent average.
Why it's important: A price move without significant volume can be a trap. This final check confirms that there is genuine market participation and conviction behind the signal, suggesting that larger market players are supporting the move.
3. The Synergy of the System (Why This Combination is Original)
The originality of VAGANZA Swings lies not in its individual components, but in their synergistic interaction:
The Trend Regime Filter sets the stage.
The Trend Strength Qualifier prevents signals when the stage is poorly lit (i.e., a weak trend).
The Pullback & Entry Trigger tells the actor exactly when to enter the stage for maximum impact.
The Volume Check ensures the audience is actually watching.
Without the strength filter, the trend filter would fail in ranging markets. Without the pullback trigger, entries would have poor risk-reward. This interdependent, sequential logic provides a unique and useful tool that goes beyond what a single indicator can offer.
4. How to Use This Script
Timeframe: Optimized for the 4-Hour (H4) chart, as this provides a balance between meaningful swings and actionable signals. It can also be used on the Daily (D1) chart for longer-term analysis.
BUY Signal (Green "BUY" Arrow): Appears only when a strong, confirmed uptrend experiences a temporary, oversold pullback and volume confirms renewed buying interest. This is a high-probability signal to consider a long position.
SELL Signal (Red "SELL" Arrow): Appears only when a strong, confirmed downtrend experiences a temporary, overbought rally and volume confirms renewed selling pressure. This is a high-probability signal to consider a short position.
Risk Management: This indicator provides entry signals only. It is crucial that you apply your own risk management rules. Always use a stop-loss and have a clear take-profit strategy for every trade.
Disclaimer: This tool is for decision-support and does not constitute financial advice. All trading involves risk. Past performance is not indicative of future results. Please backtest thoroughly before using this script with real capital.
Luxy Adaptive MA Cloud - Trend Strength & Signal Tracker V2Luxy Adaptive MA Cloud - Professional Trend Strength & Signal Tracker
Next-generation moving average cloud indicator combining ultra-smooth gradient visualization with intelligent momentum detection. Built for traders who demand clarity, precision, and actionable insights.
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WHAT MAKES THIS INDICATOR SPECIAL?
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Unlike traditional MA indicators that show static lines, Luxy Adaptive MA Cloud creates a living, breathing visualization of market momentum. Here's what sets it apart:
Exponential Gradient Technology
This isn't just a simple fill between two lines. It's a professionally engineered gradient system with 26 precision layers using exponential density distribution. The result? An organic, cloud-like appearance where the center is dramatically darker (15% transparency - where crossovers and price action occur), while edges fade gracefully (75% transparency). Think of it as a visual "heat map" of trend strength.
Dynamic Momentum Intelligence
Most MA clouds only show structure (which MA is on top). This indicator shows momentum strength in real-time through four intelligent states:
- 🟢 Bright Green = Explosive bullish momentum (both MAs rising strongly)
- 🔵 Blue = Weakening bullish (structure intact, but momentum fading)
- 🟠 Orange = Caution zone (bearish structure forming, weak momentum)
- 🔴 Deep Red = Strong bearish momentum (both MAs falling)
The cloud literally tells you when trends are accelerating or losing steam.
Conditional Performance Architecture
Every calculation is optimized for speed. Disable a feature? It stops calculating entirely—not just hidden, but not computed . The 26-layer gradient only renders when enabled. Toggle signals off? Those crossover checks don't run. This makes it one of the most efficient cloud indicators available, even with its advanced visual system.
Zero Repaint Guarantee
All signals and momentum states are based on confirmed bar data only . What you see in historical data is exactly what you would have seen trading live. No lookahead bias. No repainting tricks. No signals that "magically" appear perfect in hindsight. If a signal shows in history, it would have triggered in real-time at that exact moment.
Educational by Design
Every single input includes comprehensive tooltips with:
- Clear explanations of what each parameter does
- Practical examples of when to use different settings
- Recommended configurations for scalping, day trading, and swing trading
- Real-world trading impact ("This affects entry timing" vs "This is visual only")
You're not just getting an indicator—you're learning how to use it effectively .
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THE GRADIENT CLOUD - TECHNICAL DETAILS
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Architecture:
26 precision layers for silk-smooth transitions
Exponential density curve - layers packed tightly near center (where crossovers happen), spread wider at edges
75%-15% transparency range - center is highly opaque (15%), edges fade gracefully (75%)
V-Gradient design - emphasizes the action zone between Fast and Medium MAs
The Four Momentum States:
🟢 GREEN - Strong Bullish
Fast MA above Medium MA
Both MAs rising with momentum > 0.02%
Action: Enter/hold LONG positions, strong uptrend confirmed
🔵 BLUE - Weak Bullish
Fast MA above Medium MA
Weak or flat momentum
Action: Caution - bullish structure but losing strength, consider trailing stops
🟠 ORANGE - Weak Bearish
Medium MA above Fast MA
Weak or flat momentum
Action: Warning - bearish structure developing, consider exits
🔴 RED - Strong Bearish
Medium MA above Fast MA
Both MAs falling with momentum < -0.02%
Action: Enter/hold SHORT positions, strong downtrend confirmed
Smooth Transitions: The momentum score is smoothed using an 8-bar EMA to eliminate noise and prevent whipsaws. You see the true trend , not every minor fluctuation.
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FLEXIBLE MOVING AVERAGE SYSTEM
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Three Customizable MAs:
Fast MA (default: EMA 10) - Reacts quickly to price changes, defines short-term momentum
Medium MA (default: EMA 20) - Balances responsiveness with stability, core trend reference
Slow MA (default: SMA 200, optional) - Long-term trend filter, major support/resistance
Six MA Types Available:
EMA - Exponential; faster response, ideal for momentum and day trading
SMA - Simple; smooth and stable, best for swing trading and trend following
WMA - Weighted; middle ground between EMA and SMA
VWMA - Volume-weighted; reflects market participation, useful for liquid markets
RMA - Wilder's smoothing; used in RSI/ADX, excellent for trend filters
HMA - Hull; extremely responsive with minimal lag, aggressive option
Recommended Settings by Trading Style:
Scalping (1m-5m):
Fast: EMA(5-8)
Medium: EMA(10-15)
Slow: Not needed or EMA(50)
Day Trading (5m-1h):
Fast: EMA(10-12)
Medium: EMA(20-21)
Slow: SMA(200) for bias
Swing Trading (4h-1D):
Fast: EMA(10-20)
Medium: EMA(34-50)
Slow: SMA(200)
Pro Tip: Start with Fast < Medium < Slow lengths. The gradient works best when there's clear separation between Fast and Medium MAs.
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CROSSOVER SIGNALS - CLEAN & RELIABLE
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Golden Cross ⬆ LONG Signal
Fast MA crosses above Medium MA
Classic bullish reversal or trend continuation signal
Most reliable when accompanied by GREEN cloud (strong momentum)
Death Cross ⬇ SHORT Signal
Fast MA crosses below Medium MA
Classic bearish reversal or trend continuation signal
Most reliable when accompanied by RED cloud (strong momentum)
Signal Intelligence:
Anti-spam filter - Minimum 5 bars between signals prevents noise
Clean labels - Placed precisely at crossover points
Alert-ready - Built-in ALERTS for automated trading systems
No repainting - Signals based on confirmed bars only
Signal Quality Assessment:
High-Quality Entry:
Golden Cross + GREEN cloud + Price above both MAs
= Strong bullish setup ✓
Low-Quality Entry (skip or wait):
Golden Cross + ORANGE cloud + Choppy price action
= Weak bullish setup, likely whipsaw ✗
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REAL-TIME INFO PANEL
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An at-a-glance dashboard showing:
Trend Strength Indicator:
Visual display of current momentum state
Color-coded header matching cloud color
Instant recognition of market bias
MA Distance Table:
Shows percentage distance of price from each enabled MA:
Green rows : Price ABOVE MA (bullish)
Red rows : Price BELOW MA (bearish)
Gray rows : Price AT MA (rare, decision point)
Distance Interpretation:
+2% to +5%: Healthy uptrend
+5% to +10%: Getting extended, caution
+10%+: Overextended, expect pullback
-2% to -5%: Testing support
-5% to -10%: Oversold zone
-10%+: Deep correction or downtrend
Customization:
4 corner positions
5 font sizes (Tiny to Huge)
Toggle visibility on/off
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HOW TO USE - PRACTICAL TRADING GUIDE
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STRATEGY 1: Trend Following
Identify trend : Wait for GREEN (bullish) or RED (bearish) cloud
Enter on signal : Golden Cross in GREEN cloud = LONG, Death Cross in RED cloud = SHORT
Hold position : While cloud maintains color
Exit signals :
• Cloud turns ORANGE/BLUE = momentum weakening, tighten stops
• Opposite crossover = close position
• Cloud turns opposite color = full reversal
STRATEGY 2: Pullback Entries
Confirm trend : GREEN cloud established (bullish bias)
Wait for pullback : Price touches or crosses below Fast MA
Enter when : Price rebounds back above Fast MA with cloud still GREEN
Stop loss : Below Medium MA or recent swing low
Target : Previous high or when cloud weakens
STRATEGY 3: Momentum Confirmation
Your setup triggers : (e.g., chart pattern, support/resistance)
Check cloud color :
• GREEN = proceed with LONG
• RED = proceed with SHORT
• BLUE/ORANGE = skip or reduce size
Use gradient as confluence : Not as primary signal, but as momentum filter
Risk Management Tips:
Never enter against the cloud color (don't LONG in RED cloud)
Reduce position size during BLUE/ORANGE (transition periods)
Place stops beyond Medium MA for swing trades
Use Slow MA (200) as final trend filter - don't SHORT above it in uptrends
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PERFORMANCE & OPTIMIZATION
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Tested On:
Crypto: BTC, ETH, major altcoins
Stocks: SPY, AAPL, TSLA, QQQ
Forex: EUR/USD, GBP/USD, USD/JPY
Indices: S&P 500, NASDAQ, DJI
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TRANSPARENCY & RELIABILITY
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Educational Focus:
Detailed tooltips on every input
Clear documentation of methodology
Practical examples in descriptions
Teaches you why , not just what
Open Logic:
Momentum calculation: (Fast slope + Medium slope) / 2
Smoothing: 8-bar EMA to reduce noise
Thresholds: ±0.02% for strong momentum classification
Everything is transparent and explainable
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COMPLETE FEATURE LIST
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Visual Components:
26-layer exponential gradient cloud
3 customizable moving average lines
Golden Cross / Death Cross labels
Real-time info panel with trend strength
MA distance table
Calculation Features:
6 MA types (EMA, SMA, WMA, VWMA, RMA, HMA)
Momentum-based cloud coloring
Smoothed trend strength scoring
Conditional performance optimization
Customization Options:
All MA lengths adjustable
All colors customizable (when gradient disabled)
Panel position (4 corners)
Font sizes (5 options)
Toggle any feature on/off
Signal Features:
Anti-spam filter (configurable gap)
Clean, non-overlapping labels
Built-in alert conditions
No repainting guarantee
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IMPORTANT DISCLAIMERS
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This indicator is for educational and informational purposes only
Not financial advice - always do your own research
Past performance does not guarantee future results
Use proper risk management - never risk more than you can afford to lose
Test on paper/demo accounts before using with real money
Combine with other analysis methods - no single indicator is perfect
Works best in trending markets; less effective in choppy/sideways conditions
Signals may perform differently in different timeframes and market conditions
The indicator uses historical data for MA calculations - allow sufficient lookback period
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CREDITS & TECHNICAL INFO
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Version: 2.0
Release: October 2025
Special Thanks:
TradingView community for feedback and testing
Pine Script documentation for technical reference
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SUPPORT & UPDATES
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Found a bug? Comment below with:
Ticker symbol
Timeframe
Screenshot if possible
Steps to reproduce
Feature requests? I'm always looking to improve! Share your ideas in the comments.
Questions? Check the tooltips first (hover over any input) - most answers are there. If still stuck, ask in comments.
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Happy Trading!
Remember: The best indicator is the one you understand and use consistently. Take time to learn how the cloud behaves in different market conditions. Practice on paper before going live. Trade smart, manage risk, and may the trends be with you! 🚀
Smart Money Concepts Pro – OB, FVG, Liquidity + Trade SetupsThis script is a complete Smart Money Concepts (SMC) toolkit designed for traders who want clean and actionable charts without clutter.
It combines the most important institutional concepts into one indicator:
Order Blocks (OB): auto-detection of bullish and bearish order blocks with mitigation tracking, merging and TTL (time-to-live).
Fair Value Gaps (FVG): automatic gap recognition with size filters, mitigation tracking and lifetime control.
Liquidity Pools (EQH/EQL): equal highs and equal lows marked with tolerance (ATR-based or fixed).
Break of Structure (BOS): up/down structure shifts plotted directly on the chart.
Multi-Timeframe (HTF): option to use higher timeframe data (e.g. H4, Daily) for stronger zones.
Trend Filter: show zones only in the direction of market structure.
Trade Setups: automatic signals for OB Retest + Trend setups, with entry, stop-loss and take-profit levels (custom R-R).
Flexible Zone Extension: choose between extending zones to the live bar or fixed box width for a cleaner look when scrolling.
Features
Fully customizable (pivot length, ATR filters, box width, TTL, zone colors)
Separate presets for Scalping, Intraday, Swing trading styles
Visual trade planning with entry/SL/TP lines and optional labels
Works across all markets (crypto, forex, indices, stocks)
How to use
Bias: identify overall direction (BOS + HTF zones).
Wait: for price to return to an unmitigated OB or FVG.
Entry: take the setup signal (OB retest + trend filter).
Risk: stop-loss at opposite OB boundary.
Target: TP based on chosen R-R multiple (default 2R).
⚡ Whether you scalp short-term moves or swing trade HTF zones, this indicator gives you a clear institutional edge in spotting supply/demand imbalances and high-probability setups.
Reversal Entries [akshaykiriti1443]Reversal Entries : An In-Depth Guide
This indicator is designed to identify high-probability trend reversal points. Its primary goal is to pinpoint moments where the price attempts to break a key level, fails, and then snaps back with force. These "fakeouts" or "liquidity grabs" are often powerful signals that the market is about to reverse course.
The indicator provides two clear signals:
* 🟢 **A Bullish "Bounce Point"**: A potential buy signal after price dips below support and recovers.
* 🔴 **A Bearish "Rejection Point"**: A potential sell signal after price spikes above resistance and is pushed back down.
---
## The Core Logic: What Makes a Signal?
The indicator doesn't just look at one factor. Instead, it requires **three key conditions** to be met simultaneously before it generates a signal. This multi-layered approach helps filter out noise and identify only the most promising setups.
### 1. The Price Action "Fakeout" 🕵️♂️
This is the foundation of the signal. The indicator first identifies a short-term support or resistance level.
* **Support:** The lowest price over the `Lookback` period.
* **Resistance:** The highest price over the `Lookback` period.
It then waits for a specific pattern:
* For a **Bullish Bounce**, the current candle's low must dip **below** the support level, but its closing price must be **above** that same support level. This shows that sellers tried to push the price down but buyers stepped in with overwhelming force.
* For a **Bearish Rejection**, the current candle's high must poke **above** the resistance level, but its closing price must be **below** that same resistance level. This shows that buyers tried to break out, but sellers took control and slammed the price back down.
### 2. Volume Confirmation 🔊
A true reversal is almost always accompanied by a surge in trading activity. The indicator confirms the price action by checking for a **volume spike**.
It calculates the recent average volume and only accepts the signal if the volume on the reversal candle is significantly higher than that average (the default is 1.5 times higher). This confirms that there is real conviction and money behind the move, making it much more reliable.
### 3. Recovery Strength & Probability Score 💯
This is the indicator's "secret sauce." It doesn't just see a reversal; it measures *how strong* that reversal is.
* **Measuring the Recovery:** It uses the Average True Range (ATR) to measure the size of the price's recovery. For a bullish bounce, it measures the distance from the candle's low to its close. For a bearish rejection, it measures the distance from the high to the close. A long wick in the direction of the reversal signifies a powerful rejection of lower or higher prices.
* **Calculating a Probability Score:** The indicator takes the volume spike confirmation and the recovery strength and feeds them into a mathematical formula (a sigmoid function) to generate a "probability score" between 0 and 1. Think of this as a confidence score.
* **Applying the Threshold:** A signal is only plotted on your chart if this confidence score is above the `Probability Threshold` (default is 0.7, or 70%). This is the final filter that ensures only high-conviction setups are shown.
---
## How to Use the Indicator in Your Trading
This indicator provides entry signals, but it should be used as part of a complete trading plan.
### Understanding the Signals
* **Green `+` (Bounce Point):** When you see this signal below a candle, it's a potential **BUY entry**. It suggests that the downward momentum has been rejected and the price may be ready to move higher.
* **Red `-` (Rejection Point):** When you see this signal above a candle, it's a potential **SELL entry**. It suggests that the upward momentum has failed and the price may be ready to fall.
### Example Trading Strategy
1. **Entry:** Enter a trade when a signal appears. For a green `+`, place a buy order. For a red `-`, place a sell order.
2. **Stop Loss:** A logical stop loss is crucial.
* For a **buy trade**, place your stop loss just below the low of the signal candle. If the price breaks this low, the reversal idea is invalidated.
* For a **sell trade**, place your stop loss just above the high of the signal candle. If the price breaks this high, the setup has failed.
3. **Take Profit:** Your take profit should be based on your own strategy. A common approach is to target the next significant support or resistance level or use a fixed risk-to-reward ratio (e.g., 1:1.5 or 1:2).
**Important:** Always consider the overall market context. These signals tend to be more powerful when they align with the broader trend or occur at major, higher-timeframe support and resistance zones.
---
## Customizing the Settings
You can fine-tune the indicator's sensitivity in the settings menu to match your trading style and the asset you are trading.
* **`Support/Resistance Lookback`**: Controls how far back the indicator looks to find support and resistance. A **smaller number** makes it more sensitive to very recent price action. A **larger number** will focus on more significant, longer-term levels.
* **`Volume Spike Multiplier`**: Defines what counts as a "spike." Increasing this value (e.g., to 2.0) will demand a much larger volume surge, leading to fewer but potentially more reliable signals.
* **`ATR for Recovery`**: This sets the period for the ATR calculation, which is used to measure the recovery strength. It's generally best to leave this at its default unless you are an advanced user.
* **`Probability Threshold`**: This is the most important sensitivity setting.
* **Increase it** (e.g., to 0.85) for fewer, very high-quality signals.
* **Decrease it** (e.g., to 0.60) to see more potential setups, though some may be less reliable.
TrendViz - Smart Money ConceptsTrendViz – Smart Money Concepts
See structure, liquidity, and institutional footprints in real time.
Overview
Trend Viz – Smart Money Concepts is a comprehensive SMC toolkit that fuses market-structure (BOS / CHoCH), volumetric order blocks, fair-value gaps (FVG / Breakers), Swing Failure Patterns (SFP), equal highs / lows, and liquidity zones into one clean, on-chart visualization.
It’s designed for intraday precision (0DTE / indices) and swing confluence, with windowed processing for performance on large histories.
Key Capabilities
Market Structure Engine – Detects BOS / CHoCH with adjustable swing length, “Extreme vs Adjusted Points” logic, optional trend-based candle coloring, sweep marks, and labeled lines / bubbles.
Volumetric Order Blocks – Builds bullish / bearish OBs (including breaker blocks), mitigation methods (Close / Wick / Avg), overlap control, mid-line, and activity split (buy vs sell) with per-OB volume metrics.
Fair Value Gaps (FVG & Breakers) – Auto-detects FVGs, mitigations, optional extension, mid-lines, overlap filtering, and raid marking.
Swing Failure Pattern (SFP) – Volume-aware SFPs, directional filters (Trend-Following / Counter-Trade), deviation projections (levels + optional fill).
Equal Highs / Lows & Liquidity Concepts – Marks EQH / EQL across multiple horizons, buyside / sellside zones (area or line), liquidity prints on candles, and sweep zones after BOS / CHoCH.
Performance-First Design – Window size limits structure computations; configurable max objects; overlap suppression reduces clutter.
Inputs & Settings
Market Structure – Window size, Swing limit, Candle coloring, Text size, Algorithmic mode, Swing length, Strong/Weak HL, Sweeps, Bubbles, Mapping.
Volumetric Order Blocks – Show Last N blocks, Breakers, Construction mode, ATR length, Mitigation method, Metrics + Mid-line, Hide Overlap.
Fair Value Gap / Breakers – Enable mode, Show Last N, Threshold, Mid-line + Extension, Hide Overlap, Raid Display.
Swing Failure Pattern (SFP) – Count, Deviation Area, Colors, Filtering mode (Trend / Counter), Volume threshold, Label size.
Liquidity Concepts – Equal H&L scope, Liquidity prints, Buyside/Sellside zones (area or line), Sweep Area threshold.
How to Use It
Quick Start
Add the indicator to your chart → leave defaults.
For 0DTE / intraday use 1 – 5 min timeframes; for swing use 1H – 4H.
Turn on Color Candles to see bullish / bearish bias.
Enable Order Blocks (Show Last 5 – 10) and FVG (3 – 5) with Mitigation = Wick.
Activate SFP with Volume Threshold ≈ 0.5 – 1.0 and Trend-Following filter.
Core Workflows
Trend-Continuation Entry – Wait for CHoCH → BOS alignment → FVG mitigation or OB mid-line retest.
Reversal Entry – Opposing CHoCH + sweep (x) + fresh OB confirmation.
Liquidity Sweep Fade – Raid EQH/EQL + SFP (Counter-Trade) → target prior FVG or opposite OB.
0DTE / Index Checklist
Timeframe 1–5 min · Adjusted Points · mslen = 3–5.
OB Show Last = 5–10 · Mitigation = Wick · Hide Overlap = Recent.
FVG Show = 3–5 · Threshold = 0.1–0.3.
SFP Trend-Following for momentum, Counter-Trade for range.
Trade only after CHoCH → BOS alignment near OB / FVG.
Tips & Behavior
Confirmation / Repainting – Structure anchors confirm after right bars; no repaint once locked.
Performance – Reduce Window size, counts, and overlaps for speed.
Clutter Control – Hide Overlap, limit count, prefer mid-lines over fills.
Mitigation Choice – Wick (strict), Close (lenient), Avg (balanced).
Alerts – Not included by default (visual tool only).
Example Setups
Momentum Pullback – After BOS up, FVG fill + OB reclaim = entry.
Liquidity Sweep Fade – EQH raid + bear SFP = fade to prior FVG.
Breaker Flip – Mitigated OB turns breaker; trade retest.
Disclaimer
This indicator is for educational and analytical purposes only.
Not financial advice. Backtest and apply proper risk management before using live.
Tags
#SmartMoneyConcepts #OrderBlocks #BOS #CHoCH #FVG #Breakers #SFP #Liquidity #EQH #EQL #0DTE #SPX #MarketStructure #TrendViz #TradingView
Options Position Size CalculatorOptions Position Size Calculator
Automate your options position sizing directly on the chart.
This indicator calculates the optimal number of options contracts to buy based on your risk management parameters, entry price, stop loss, and expected options decay.
📋 What It Does
Eliminates the need for external calculators by computing your position size directly on TradingView. Simply set your entry and stop loss prices, configure your risk parameters, and the indicator instantly shows you how many contracts to buy.
✨ Key Features
Visual Price Lines: Set entry and stop loss prices with draggable horizontal lines
Custom Loss Table: Input your own options loss percentages for distances from 0.1% to 1.5% (with interpolation between values)
Automatic Calculations: Calculates distance to stop loss, expected options loss, dollar risk, and final contract quantity
Live Display: All calculations shown in a clean info box on your chart
Accounts for Contract Multiplier: Correctly factors in the standard 100x options multiplier
🎯 How to Use
1. Configure Settings First
Add the indicator to your chart (set any initial prices when prompted)
Open indicator Settings (gear icon)
Enter your Portfolio Size (e.g., $10,000)
Set Risk Percentage (e.g., 2%)
Enter the Contract Price (the premium per contract, e.g., $1.50)
2. Fill Your Options Loss Table
This is crucial - you must input your own data
For each distance (0.1%, 0.2%, up to 1.5%), enter the expected % loss your options will suffer
Base this on your strategy (calls/puts), strike selection, and expiration
Use historical data from your trades or an options calculator
Example: If underlying moves 0.5% to your stop, your option might lose 30%
3. Set Entry & Stop Loss on Chart
Go back to indicator settings
Adjust Entry Price and Stop Loss Price to match your trade setup
The indicator calculates your position size instantly
4. Read Results
The indicator displays:
Distance to stop loss (%)
Expected options loss (%)
Dollar risk amount
CONTRACTS TO BUY - your position size
📊 Example
Portfolio: $10,000 | Risk: 2% | Entry: $150 | Stop: $149 (0.67% distance)
Expected loss: 38% | Contract price: $2.00
→ Buy 2 contracts
⚠️ Important
Your loss table values depend on your specific options strategy, strike, DTE, and IV
Different strategies require different loss tables
This is for educational purposes - always verify calculations
Never risk more than you can afford to lose
Made by traders, for traders. Trade safe, size smart.
aEMA Cross - Long EditionaEMA Cross – Long Edition
Smart, Automated, and Rule-Based Trading Framework
Overview:
The aEMA Cross – Long Edition is an advanced automated trading system that intelligently identifies trends, filters weak signals, and manages trades with precision. It integrates EMA crossover logic, breakout candle confirmation, and time-based exits to help traders capture consistent opportunities while minimizing risk and manual intervention.
Designed and developed with algorithmic trading platforms in mind, the indicator can be seamlessly integrated with most Algo platforms through TradingView alerts for automated execution.
Note: The default setup is optimized for the ETHUSD chart.
Core Concept:
The strategy is built around two Exponential Moving Averages (EMAs):
- Short EMA – Responds quickly to short-term market changes.
- Long EMA (default 200) – Represents the overall market trend.
When the Short EMA crosses specific buffer zones around the Long EMA, it confirms genuine momentum before generating Buy or Sell signals. This ensures cleaner and more reliable trade entries.
Key Features:
1. Signal Generation
• Dual logic modes: Candle-based or EMA-based signal detection.
• Breakout Candle System to confirm strong price movements before entries.
• Integrated RSI and ADX filters to ensure trades occur only in favorable market conditions.
2. Smart Trade Management
• Automated Target and Stoploss management.
• Trailing Stop Loss (TSL) dynamically locks in profits as prices move favorably.
• Sequential Signal Logic ensures no repeated or conflicting trade signals.
3. Universal Exit (Time-Based Auto Exit)
• Automatically exits all positions at a specified time (e.g., 23:40).
• Works consistently across all timeframes (1m, 3m, 5m, etc.).
• Can be configured for selected weekdays or every trading day.
• Prevents overnight exposure and resets trading cleanly for the next session.
4. Safety and Control
• EMA buffer zones help avoid false breakouts and choppy market signals.
• Blocks new entries after a Universal Exit until a fresh crossover occurs.
• Automatically resets breakout levels and internal logic daily for consistency.
5. Visualization and Alerts
• Plots EMAs, buffer zones, breakout levels, and entry/exit markers directly on the chart.
• Highlights the Universal Exit visually with background shading.
• Sends real-time alerts for Buy, Sell, Exit, and Universal Exit events.
Why It Stands Out:
• Works reliably across multiple timeframes.
• Fully rule-based with no emotional bias.
• Highly customizable – adjust filters, targets, buffers, and exit rules as needed.
• Complete framework – handles entry, management, and exit automatically.
• Engineered for compatibility – can be integrated with most Algo trading platforms.
How It Works:
1. The Short EMA and Long EMA define the primary market direction.
2. A breakout or EMA crossover triggers a potential signal.
3. RSI and ADX filters confirm market strength before allowing entry.
4. Target, Stoploss, and TSL manage trades automatically.
5. Universal Exit closes all trades at a defined time, resetting the logic for the next session.
How to Use:
1. Apply the aEMA Cross – Long Edition indicator to your chart.
2. Choose your primary logic: Candle-based or Short EMA-based.
3. Adjust RSI, ADX, Buffer, and Target/SL settings according to your trading style.
4. Configure Universal Exit time and alert options.
5. Use the “Once Per Bar Close” alert type for confirmed signals.
6. Always backtest your configuration before enabling automation or live execution.
Important Note on Alert Setup:
- When using the RSI filter, signals may fluctuate if RSI hovers near the trigger level. To avoid this, use “Once Per Bar Close” for stable and confirmed alerts.
- If RSI is disabled, “Once Per Bar” alerts can be safely used, even when the Breakout Candle High/Low Crossover option is enabled.
Disclaimer:
• This strategy is intended for educational and research purposes only.
• It does not guarantee profits. Always perform proper backtesting and apply sound risk management before live trading.
• The author is not responsible for any financial losses resulting from its use.
Developer Information:
Developer: ikunalsingh
Built using AI + the best of human logic.
TTM Squeeze Range Lines (with Forward Extension) By Gautam KumarThis TTM Squeeze Range Lines script helps visualize breakout levels by marking the recent squeeze’s high and low, making it easier to identify potential trade setups. Each signal line is extended for visibility, showing possible entry levels after a squeeze.
Interpreting the LinesLight blue background marks periods when the TTM squeeze is active (tight volatility).
Green line is drawn at the highest price during the squeeze, extended forward—this is commonly used as the breakout level for long entries.
Red line shows the lowest price during the squeeze, indicating the bottom of the range—potential stop loss positioning or an invalidation level.
When the squeeze background disappears, the horizontal lines will have just appeared and extended forward for several bars after the squeeze ends.
If the price breaks above the green line (the squeeze high), it signals a possible momentum breakout, which traders often use as a long entry.
The red line can be used for placing stop losses or monitoring failed breakouts if price falls below this level.
Best Practices
Combine these levels with volume and momentum confirmation for strong entries.
Adjust the extension length (number of bars forward) from the settings menu to fit your preference.
For systematic trading, use these breakout signals alongside chart pattern or histogram confirmation.
This makes it easy to visualize strong entry zones based on the end of squeeze compression, supporting both discretionary and automated swing trading approaches
