XAUUSD Pro Setup Suite manuel_lnt.fx is an advanced Pine Script v6 indicator designed exclusively for XAUUSD, built to automatically detect the 5 highest-probability setups in gold day trading.
It combines institutional price action, volatility patterns, mean reversion logic, and momentum confirmation to generate clean, filtered, and actionable signals.
The indicator automatically detects:
⸻
1️⃣ Break & Retest Premium (BR)
Identifies valid breaks of key levels and signals the retest with rejection wick, EMA20 trend confirmation, and neutral RSI.
→ Excellent for trend continuation.
⸻
2️⃣ Fakeout Liquidity Trap (FO)
Detects liquidity grabs above highs or below lows with an opposite close + engulfing candle confirmation.
→ The strongest setup for fast and explosive reversals on gold.
⸻
3️⃣ MACD Zero-Line Shift (MACD)
Signals when the MACD crosses the zero line while price breaks micro-structure.
→ Perfect for spotting the start of a new trend.
⸻
4️⃣ Bollinger Squeeze → Breakout (BB)
Recognizes volatility compression and signals when a breakout is likely to explode.
→ Ideal for clean breakout trades.
⸻
5️⃣ Mean Reversion on EMA50 (MR)
Highlights price extensions far away from the EMA50 with ATR confirmation and a reversal candle.
→ Great for pullbacks back toward the mean value.
Volatilität
FVG & Market Structure//@version=5
indicator("FVG & Market Structure", overlay=true)
// Inputs
fvg_lookback = input.int(100, "FVG Lookback Period")
fvg_strength = input.int(1, "FVG Minimum Strength")
show_fvg = input.bool(true, "Show FVG")
show_liquidity = input.bool(true, "Show Liquidity Zones")
show_bos = input.bool(true, "Show BOS")
// Calculate swing highs and lows
swing_high = ta.pivothigh(high, 2, 2)
swing_low = ta.pivotlow(low, 2, 2)
// Detect Fair Value Gaps (FVG)
detect_fvg() =>
// Bullish FVG (current low > previous high + threshold)
bullish_fvg = low > high and show_fvg
// Bearish FVG (current high < previous low - threshold)
bearish_fvg = high < low and show_fvg
= detect_fvg()
// Plot FVG areas
bgcolor(bullish_fvg ? color.new(color.green, 95) : na, title="Bullish FVG")
bgcolor(bearish_fvg ? color.new(color.red, 95) : na, title="Bearish FVG")
// Breach of Structure (BOS) detection
detect_bos() =>
var bool bull_bos = false
var bool bear_bos = false
// Bullish BOS - price breaks above previous swing high
if high > ta.valuewhen(swing_high, high, 1) and not na(swing_high)
bull_bos := true
bear_bos := false
// Bearish BOS - price breaks below previous swing low
if low < ta.valuewhen(swing_low, low, 1) and not na(swing_low)
bear_bos := true
bull_bos := false
= detect_bos()
// Plot BOS signals
plotshape(bull_bos and show_bos, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small, title="Bullish BOS")
plotshape(bear_bos and show_bos, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small, title="Bearish BOS")
// Liquidity Zones (Recent Highs/Lows)
liquidity_range = input.int(20, "Liquidity Lookback")
buy_side_liquidity = ta.highest(high, liquidity_range)
sell_side_liquidity = ta.lowest(low, liquidity_range)
// Plot Liquidity Zones
plot(show_liquidity ? buy_side_liquidity : na, color=color.red, linewidth=1, title="Sell Side Liquidity")
plot(show_liquidity ? sell_side_liquidity : na, color=color.green, linewidth=1, title="Buy Side Liquidity")
// Order Block Detection (Simplified)
detect_order_blocks() =>
// Bullish Order Block - strong bullish candle followed by pullback
bullish_ob = close > open and (close - open) > (high - low) * 0.7 and show_fvg
// Bearish Order Block - strong bearish candle followed by pullback
bearish_ob = close < open and (open - close) > (high - low) * 0.7 and show_fvg
= detect_order_blocks()
// Plot Order Blocks
bgcolor(bullish_ob ? color.new(color.lime, 90) : na, title="Bullish Order Block")
bgcolor(bearish_ob ? color.new(color.maroon, 90) : na, title="Bearish Order Block")
// Alerts for key events
alertcondition(bull_bos, "Bullish BOS Detected", "Bullish Breach of Structure")
alertcondition(bear_bos, "Bearish BOS Detected", "Bearish Breach of Structure")
// Table for current market structure
var table info_table = table.new(position.top_right, 2, 4, bgcolor=color.white, border_width=1)
if barstate.islast
table.cell(info_table, 0, 0, "Market Structure", bgcolor=color.gray)
table.cell(info_table, 1, 0, "Status", bgcolor=color.gray)
table.cell(info_table, 0, 1, "Bullish BOS", bgcolor=bull_bos ? color.green : color.red)
table.cell(info_table, 1, 1, bull_bos ? "ACTIVE" : "INACTIVE")
table.cell(info_table, 0, 2, "Bearish BOS", bgcolor=bear_bos ? color.red : color.green)
table.cell(info_table, 1, 2, bear_bos ? "ACTIVE" : "INACTIVE")
table.cell(info_table, 0, 3, "FVG Count", bgcolor=color.blue)
table.cell(info_table, 1, 3, str.tostring(bar_index))
orb cody hoskinscody orb designed a 15 min range orb indicator for people to use dur8ng market open in asian and new york
ORB + INMERELO ADR + ATRThis indicator provides **two completely different but complementary lines of information** for intraday traders:
# **1. The ORB Line (ADR-Based Context Line)**
The ORB portion of the script focuses on **range expansion** relative to typical daily behavior.
### **What it measures**
* **20-day ADR (Average Daily Range)**
* **Today’s range as a % of ADR**
* **How much of the average range has been “used”** by the time you’re considering an Opening Range Breakout
### **Why it matters for ORB trading**
Successful ORBs thrive when:
* **ADR used% is low** (green) → plenty of fuel left for expansion
* **ADR used% is moderate** (orange) → breakout still possible but less explosive
* **ADR used% is high** (red) → breakout attempts often fail or reverse
### **What the indicator gives you**
A clean, color-coded readout of:
* ADR
* Today’s range
* Used%
* A simple green/orange/red evaluation of ORB quality
This allows a trader to quickly judge whether **conditions favor ORB continuation or mean-reversion reversal**—without manually calculating ranges or switching charts.
---
# **2. The INMERELO Line (ATR Stretch + MA Interaction)**
The INMERELO portion of the script is built around **mean-reversion mechanics**:
the market tends to revert back toward the **first daily MA it crosses under**.
### **How it determines the active MA**
At the start of each session, the script waits for price to cross under:
* **EMA10**
* **EMA21**
* **SMA50**
Whichever MA is crossed first becomes the **active MA** for the day.
If no cross has occurred yet, the indicator shows the **nearest MA**, so traders know exactly what the likely “INMERELO magnet” will be.
### **What it measures**
* **Stretch from the active MA (in ATR units)**
* **20-day ATR regime direction (expanding or contracting)**
* **Daily MA context: E10, E21, or S50**
### **Why it matters for INMERELOs**
This provides:
* The **target MA**
* The **distance to that MA in ATRs**
* A color-coded stretch score:
* **0.6–1.2 ATR** → prime INMERELO zone (Green)
* Moderately stretched → Orange
* Overstretched or dead zone → Red
An up/down arrow shows whether **volatility is expanding or compressing**, which affects expected retrace behavior.
### **What the indicator gives you**
All INMERELO data is displayed in a second compact line:
* Stretch to MA
* Active MA label (E10/E21/S50)
* ATR regime arrow
This allows fast identification of high-probability **mean-reversion trades back to the MA**.
---
# **Summary**
This indicator shows:
### **Line 1 → ORB Context (ADR)**
* Is the stock setup for a powerful breakout?
* How much ADR is left?
* Are you early (good) or late (risky)?
### **Line 2 → INMERELO Context (ATR + MA Stretch)**
* Which MA is in control today (EMA10, EMA21, or SMA50)?
* How many ATRs away from that MA are we?
* Is volatility expanding or contracting?
* Is this a clean INMERELO setup or not?
Together, these two lines give traders the **two most important intraday lenses**:
**range expansion (ORB)** and **mean reversion (INMERELO)**—updated every bar, without clutter.
VWAP D/W/M + MA100 & EMA100 albanThis TradingView indicator displays three independent VWAPs (Volume Weighted Average Prices) along with MA100 (Simple Moving Average) and EMA100 (Exponential Moving Average) on the chart.
Key Features:
VWAP #1, VWAP #2, VWAP #3: Each VWAP can be configured independently with:
Source (hlc3, close, etc.)
Anchor period (Session, Week, Month, Quarter, Year, Decade, Century, Earnings, Dividends, Splits)
Offset
Option to hide on daily or higher timeframes
MA100: 100-period Simple Moving Average
EMA100: 100-period Exponential Moving Average
Purpose:
This script is ideal for traders who want to track multiple VWAP levels simultaneously while also monitoring the 100-period moving averages for trend analysis. It provides a clean setup without bands or fills, focusing solely on price averages.
Use Cases:
Identify intraday or multi-timeframe VWAP levels
Combine VWAP levels with MA100/EMA100 for support/resistance analysis
Analyze trend direction and momentum using moving averages
Long Term indicator for financial marketsIts the indicator that i have made for my friends following the learnings which i have learnt over the last few years for momentum traders
GEX / Gamma - SPX Indicator Description – GEX / Gamma (SPX)
This indicator allows you to manually plot your daily +GEX, TRANS-GEX, and –GEX levels on SPX and visualize how price reacts around key gamma zones.
You enter the three levels each morning, and the script automatically draws:
+GEX / TRANS / –GEX zones with an adjustable buffer
Clean labels (e.g., “+GEX: 6850”) pinned to the right side of the chart
Today-only candle coloring (green above TRANS-GEX, red below)
Zones extend from yesterday’s session through the current session, helping highlight areas where dealer hedging flows may influence volatility, compression, or acceleration.
How to Use
Add the indicator to any intraday SPX chart.
Open settings and enter your +GEX, TRANS-GEX, and –GEX levels for the day.
Adjust the buffer, colors, and label style as needed.
Watch how price behaves as it moves above or below TRANS-GEX and interacts with +/- GEX zones.
Best For
Intraday SPX / ES / SPY
Options traders
Volatility and gamma-aware strategies
Strategy Behind It (Tight Version)
GEX levels help identify where dealer hedging flows can influence SPX price behavior.
+GEX (Positive Gamma)
Market tends to stabilize here. Dealers hedge against price moves, creating mean-reversion and lower volatility.
TRANS-GEX (Transition Level)
Key pivot where gamma flips. Price crossing this level often signals a shift in volatility or intraday direction.
–GEX (Negative Gamma)
Market becomes more reactive. Dealers hedge with price, increasing volatility, momentum, and trend potential.
How traders use it:
Expect resistance or slowdown into +GEX
Watch for potential bottoming or increased volatility –GEX
Use TRANS-GEX as a bias line or trigger for intraday shifts
A move outside of either the +GEX or -GEX will likely result in some type of high volume move.
Swing Trade BUY/SELL + SCORING +COLOUR FIXBUY/SELL labels now appear with a score (1–3) next to them.
Color coding visually distinguishes signal strength:
BUY → 1 yellow, 2 light green, 3 dark green
SELL → 1 orange, 2 red, 3 burgundy
This allows you to instantly see the signal strength both numerically and visually.
VIX Calm vs Choppy (Bar Version, VIX High Threshold)This indicator tracks market stability by measuring how long the VIX stays below or above a chosen intraday threshold. Instead of looking at VIX closes, it uses VIX high, so even a brief intraday spike will flip the regime into “choppy.”
The tool builds a running clock of consecutive bars spent in each regime:
Calm regime: VIX high stays below the threshold
Choppy regime: VIX high hits or exceeds the threshold
Calm streaks plot as positive bars (light blue background).
Choppy streaks plot as negative bars (dark pink background).
This gives a clean picture of how long the market has been stable vs volatile — useful for trend traders, breakout traders, and anyone who watches risk-on/risk-off conditions. A table shows the current regime and streak length for quick reference.
Braid Filter StrategyThis strategy is like a sophisticated set of traffic lights and speed limit signs for trading. It only allows a trade when multiple indicators line up to confirm a strong move, giving it its "Braid Filter" name—it weaves together several conditions.
The strategy is set up to use 100% of your account equity (your trading funds) on a trade and does not "pyramid" (it won't add to an existing trade).
1. The Main Trend Check (The Traffic Lights)
The strategy uses three main filters that must agree before it considers a trade.
A. The "Chad Filter" (Direction & Strength)
This is the heart of the strategy, a custom combination of three different Moving AveragesThese averages have fast, medium, and slow settings (3, 7, and 14 periods).
Go Green (Buy Signal): The fastest average is higher than the medium average, AND the three averages are sufficiently separated (not tangled up, which indicates a strong move).
Go Red (Sell Signal): The medium average is higher than the fastest average, AND the three averages are sufficiently separated.
Neutral (Wait): If the averages are tangled or the separation isn't strong enough.
Key Trigger: A primary condition for a signal is when the Chad Filter changes color (e.g., from Red/Grey to Green).
B. The EMA Trend Bars (Secondary Confirmation)
This is a simpler, longer-term filter using a 34-period Exponential Moving Average (EMA). It checks if the current candle's average price is above or below this EMA.
Green Bars: The price is above the 34 EMA (Bullish Trend).
Red Bars: The price is below the 34 EMA (Bearish Trend).
Trades only happen if the signal direction matches the bar color. For a Buy, the bar must be Green. For a Sell, the bar must be Red.
C. ADX/DI Filter (The Speed Limit Sign)
This uses the Average Directional Index (ADX) and Directional Movement Indicators (DI) to check if a trend is actually in motion and getting stronger.
Must-Have Conditions:
The ADX value must be above 20 (meaning there is a trend, not just random movement).
The ADX line must be rising (meaning the trend is accelerating/getting stronger).
The strategy will only trade when the trend is strong and building momentum.
2. The Trading Action (Entry and Exit)
When all three filters (Chad Filter color change, EMA Trend Bar color, and ADX strength/slope) align, the strategy issues a signal, but it doesn't enter immediately.
Entry Strategy (The "Wait-for-Confirmation" Approach):
When a Buy Signal appears, the strategy sets a "Buy Stop" order at the signal candle's closing price.
It then waits for up to 3 candles (Candles Valid for Entry). The price must move up and hit that Buy Stop price within those 3 candles to confirm the move and enter the trade.
A Sell Signal works the same way but uses a "Sell Stop" at the closing price, waiting for the price to drop and hit it.
Risk Management (Stop Loss and Take Profit):
Stop Loss: To manage risk, the strategy finds a recent significant low (for a Buy) or high (for a Sell) over the last 20 candles and places the Stop Loss there. This is a logical place where the current move would be considered "broken" if the price reaches it.
Take Profit: It uses a fixed Risk:Reward Ratio (set to 1.5 by default). This means the potential profit (Take Profit distance) is $1.50 for every $1.00 of risk (Stop Loss distance).
3. Additional Controls
Time Filter: You can choose to only allow trades during specific hours of the day.
Visuals: It shows a small triangle on the chart where the signal happens and colors the background to reflect the Chad Filter's trend (Green/Red/Grey) and the candle bars to show the EMA trend (Lime/Red).
🎯 Summary of the Strategy's Goal
This strategy is designed to capture strong, confirmed momentum moves. It uses a fast, custom indicator ("Chad Filter") to detect the start of a new move, confirms that move with a slower trend filter (34 EMA), and then validates the move's strength with the ADX. By waiting a few candles for the price to hit the entry level, it aims to avoid false signals.
DAO - Demand Advanced Oscillator# DAO - Demand Advanced Oscillator
## 📊 Overview
DAO (Demand Advanced Oscillator) is a powerful momentum oscillator that measures buying and selling pressure by analyzing consecutive high-low relationships. It helps identify market extremes, divergences, and potential trend reversals.
**Values range from 0 to 1:**
- **Above 0.70** = Overbought (potential reversal down)
- **Below 0.30** = Oversold (potential reversal up)
- **0.30 - 0.70** = Neutral zone
---
## ✨ Key Features
✅ **Automatic Divergence Detection**
- Bullish divergences (price lower low + DAO higher low)
- Bearish divergences (price higher high + DAO lower high)
- Visual lines connecting divergence points
✅ **Multi-Timeframe Analysis**
- View higher timeframe DAO on current chart
- Perfect for trend alignment strategies
✅ **Signal Line (EMA)**
- Customizable EMA for trend confirmation
- Crossover signals for momentum shifts
✅ **Real-Time Statistics Dashboard**
- Current DAO value
- Market status (Overbought/Oversold/Neutral)
- Trend direction indicator
✅ **Complete Alert System**
- Overbought/Oversold signals
- Bullish/Bearish divergences
- Signal line crosses
- Level crosses
✅ **Fully Customizable**
- Adjustable periods and levels
- Customizable colors and zones
- Toggle features on/off
---
## 📈 Trading Signals
### 1. Divergences (Most Powerful)
**Bullish Divergence:**
- Price makes lower low
- DAO makes higher low
- Signal: Strong reversal up likely
**Bearish Divergence:**
- Price makes higher high
- DAO makes lower high
- Signal: Strong reversal down likely
### 2. Overbought/Oversold
**Overbought (>0.70):**
- Market may be overextended
- Consider taking profits or looking for shorts
- Can remain overbought in strong trends
**Oversold (<0.30):**
- Market may be oversold
- Consider buying opportunities
- Can remain oversold in strong downtrends
### 3. Signal Line Crossovers
**Bullish Cross:**
- DAO crosses above signal line
- Momentum turning positive
**Bearish Cross:**
- DAO crosses below signal line
- Momentum turning negative
### 4. Level Crosses
**Cross Above 0.30:** Exiting oversold zone (potential uptrend)
**Cross Below 0.70:** Exiting overbought zone (potential downtrend)
---
## ⚙️ Default Settings
📊 Oscillator Period: 14
Number of bars for calculation
📈 Signal Line Period: 9
EMA period for signal line
🔴 Overbought Level: 0.70
Upper threshold
🟢 Oversold Level: 0.30
Lower threshold
🎯 Divergence Detection: ON
Auto divergence identification
⏰ Multi-Timeframe: OFF
Higher TF overlay (optional)
All parameters are fully customizable!
---
## 🔔 Alerts
Six pre-configured alerts available:
1. DAO Overbought
2. DAO Oversold
3. DAO Bullish Divergence
4. DAO Bearish Divergence
5. DAO Signal Cross Up
6. DAO Signal Cross Down
**Setup:** Right-click indicator → Add Alert → Choose condition
---
## 💡 How to Use
### Best Practices:
✅ Focus on divergences (strongest signals)
✅ Combine with support/resistance levels
✅ Use multiple timeframes for confirmation
✅ Wait for price action confirmation
✅ Practice proper risk management
### Avoid:
❌ Trading on indicator alone
❌ Fighting strong trends
❌ Ignoring market context
❌ Overtrading
### Recommended Settings by Trading Style:
**Day Trading:** Period 7-10, All alerts ON
**Swing Trading:** Period 14-21, Divergence alerts
**Scalping:** Period 5-7, Signal crosses
**Position Trading:** Period 21-30, Weekly/Daily TF
---
## 🌍 Markets & Timeframes
**Works on all markets:**
- Forex (all pairs)
- Stocks (all exchanges)
- Cryptocurrencies
- Commodities
- Indices
- Futures
**Works on all timeframes:** 1m to Monthly
---
## 📊 How It Works
DAO calculates the ratio of buying pressure to total market pressure:
1. **Calculate Buying Pressure (DemandMax):**
- If current high > previous high: DemandMax = difference
- Otherwise: DemandMax = 0
2. **Calculate Selling Pressure (DemandMin):**
- If previous low > current low: DemandMin = difference
- Otherwise: DemandMin = 0
3. **Apply Smoothing:**
- Calculate SMA of DemandMax over N periods
- Calculate SMA of DemandMin over N periods
4. **Final Formula:**
```
DAO = SMA(DemandMax) / (SMA(DemandMax) + SMA(DemandMin))
```
This produces a normalized value (0-1) representing market demand strength.
---
## 🎯 Trading Strategies
### Strategy 1: Divergence Trading
- Wait for divergence label
- Confirm at support/resistance
- Enter on confirming candle
- Stop loss beyond recent swing
- Target: opposite level or 0.50
### Strategy 2: Overbought/Oversold
- Best for ranging markets
- Wait for extreme readings
- Enter on reversal from extremes
- Target: middle line (0.50)
### Strategy 3: Trend Following
- Identify trend direction first
- Use DAO to time entries in trend direction only
- Enter on pullbacks to oversold (uptrend) or overbought (downtrend)
- Trade with the trend
### Strategy 4: Multi-Timeframe
- Enable MTF feature
- Trade only when both timeframes align
- Higher TF = trend direction
- Lower TF = precise entry
---
## 📂 Category
**Primary:** Oscillators
**Secondary:** Statistics, Volatility, Momentum
---
## 🏷️ Tags
dao, oscillator, momentum, overbought-oversold, divergence, reversal, demand-indicator, price-exhaustion, statistics, volatility, forex, stocks, crypto, multi-timeframe, technical-analysis
---
## ⚠️ Disclaimer
**This indicator is for educational purposes only.** It does not constitute financial advice. Trading involves substantial risk of loss. Always conduct your own research, use proper risk management, and consult with financial professionals before making trading decisions. Past performance does not guarantee future results.
---
## 📄 License
Open source - Free to use for personal trading, modify as needed, and share with attribution.
---
**Version:** 1.0
**Status:** Production Ready ✅
**Pine Script:** v5
**Trademark-Free:** 100% Safe to Publish
---
*Made with 💙 for traders worldwide*
Adaptive Momentum Pressure (AMP)🔹 Adaptive Momentum Pressure (AMP)
A hybrid momentum oscillator that adapts to volatility and trend dynamics.
AMP measures the rate of change of price pressure and automatically adjusts its sensitivity based on market volatility.
It reacts faster in trending markets and smooths out noise during consolidation — helping traders identify genuine momentum shifts early while avoiding whipsaws.
🧠 Core Concept
AMP fuses three elements into one adaptive momentum model:
Normalized Momentum (ROC) – captures directional acceleration of price.
Adaptive Smoothing – the smoothing length dynamically contracts when volatility rises and expands when it falls.
Directional Bias – derived from the short-term EMA slope to weight momentum toward the prevailing trend.
Combined, these form a pressure value oscillating between –100 and +100, revealing when momentum expands or fades.
⚙️ How It Works
Calculates a normalized rate of change (ROC) relative to recent volatility.
Adjusts its effective length using the ATR — more volatile periods shorten the lookback for quicker reaction.
Applies a custom EMA that adapts in real time.
Modulates momentum by a normalized EMA slope (“trend bias”).
Produces a smoothed AMP line with a Signal line and crossover markers.
🔍 How to Read It
Green AMP line rising above Signal → Building bullish momentum.
Red AMP line falling below Signal → Fading or bearish momentum.
White Signal line = smoothed confirmation of trend energy.
Green dots = early bullish crossovers.
Red dots = early bearish crossovers.
Typical interpretations:
AMP crossing above 0 from below → early bullish impulse.
AMP peaking near +50–100 and curling down → potential momentum exhaustion.
Crosses below 0 with red pressure → bearish confirmation.
⚡ Advantages
✅ Adaptive across all markets and timeframes
✅ Built-in trend bias filters false signals
✅ Reacts earlier than RSI/MACD while reducing noise
✅ No manual retuning required
🧩 Suggested Use
Combine with structure or volume tools to confirm breakouts.
Works well as a momentum confirmation filter for entries/exits.
Optimal display: separate oscillator pane (not overlay).
Use it responsibly — AMP is an analytical tool, not financial advice.
Average True Range Stop Loss Finder [MasterYodi]This indicator utilizes the Average True Range (ATR) to help traders identify optimal stop-loss levels that reduce the risk of premature exits caused by market volatility or tight stop placements. The default multiplier is set to 1.5, providing a balanced stop-loss buffer. For more conservative setups, a multiplier of 2 is recommended; for tighter risk management, use 1.
ATR values and corresponding stop-loss levels are displayed in a table at the bottom of the chart.
Use the high-based (red) level for short positions
Use the low-based (teal) level for long positions
ATR (No Gap) - Advanced Volatility IndicatorA customizable Average True Range indicator that eliminates gap distortion between trading sessions, providing cleaner volatility measurements for intraday and swing traders.
Key Features:
Gap Filtering: Optional toggle to ignore overnight/weekend gaps that distort volatility readings
EMA Smoothing: Defaults to EMA for more responsive volatility tracking (also supports RMA and SMA)
Half ATR Display: Shows 50% ATR value for quick stop-loss and take-profit calculations
Clean Value Table: Real-time values displayed on chart with configurable decimal precision
Flexible Settings: Customize length, smoothing method, and display options
Ideal for:
Setting dynamic stop losses and take profits
Position sizing based on current volatility
Comparing gap vs. no-gap volatility measurements
Trading instruments with large overnight gaps (indices, forex, crypto)
Use this indicator to get a more accurate picture of intraday volatility without the noise from session gaps!
Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
Stochastic + Bollinger Bands Multi-Timeframe StrategyThis strategy fuses the Stochastic Oscillator from the 4-hour timeframe with Bollinger Bands from the 1-hour timeframe, operating on a 10-hour chart to capture a unique volatility rhythm and temporal alignment discovered through observational alpha.
By blending momentum confirmation from the higher timeframe with short-term volatility extremes, the strategy leverages what some traders refer to as “rotating volatility” — a phenomenon where multi-timeframe oscillations sync to reveal hidden trade opportunities.
🧠 Strategy Logic
✅ Long Entry Condition:
Stochastic on the 4H timeframe:
%K crosses above %D
Both %K and %D are below 20 (oversold zone)
Bollinger Bands on the 1H timeframe:
Price crosses above the lower Bollinger Band, indicating a potential reversal
→ A long trade is opened when both momentum recovery and volatility reversion align.
✅ Long Exit Condition:
Stochastic on the 4H:
%K crosses below %D
Both %K and %D are above 80 (overbought zone)
Bollinger Bands on the 1H:
Price reaches or exceeds the upper Bollinger Band, suggesting exhaustion
→ The long trade is closed when either signal suggests a potential reversal or overextension.
🧬 Temporal Structure & Alpha
This strategy is deployed on a 10-hour chart — a non-standard timeframe that may align more effectively with multi-timeframe mean reversion dynamics.
This subtle adjustment exploits what some traders identify as “temporal drift” — the desynchronization of volatility across timeframes that creates hidden rhythm in price action.
→ For example, Stochastic on 4H (lookback 17) and Bollinger Bands on 1H (lookback 20) may periodically sync around 10H intervals, offering unique alpha windows.
📊 Indicator Components
🔹 Stochastic Oscillator (4H, Length 17)
Detects momentum reversals using %K and %D crossovers
Helps define overbought/oversold zones from a mid-term view
🔹 Bollinger Bands (1H, Length 20, ±2 StdDev)
Measures price volatility using standard deviation around a moving average
Entry occurs near lower band (support), exits near upper band (resistance)
🔹 Multi-Timeframe Logic
Uses request.security() to safely reference 4H and 1H indicators from a 10H chart
Avoids repainting by using closed higher-timeframe candles only
📈 Visualization
A plot selector input allows toggling between:
Stochastic Plot (%K & %D, with overbought/oversold levels)
Bollinger Bands Plot (Upper, Basis, Lower from 1H data)
This helps users visually confirm entry/exit triggers in real time.
🛠 Customization
Fully configurable Stochastic and BB settings
Timeframes are independently adjustable
Strategy settings like position sizing, slippage, and commission are editable
⚠️ Disclaimer
This strategy is intended for educational and informational purposes only.
It does not constitute financial advice or a recommendation to buy or sell any asset.
Market conditions vary, and past performance does not guarantee future results.
Always test any trading strategy in a simulated environment and consult a licensed financial advisor before making real-world investment decisions.
VWAP CATS background flipped 4.0VWAP CATS Background Flipped 4.0 is a sophisticated Pine Script v5 indicator for TradingView that combines a configurable moving average (MA) with dynamic Gann Square of 9 levels to create a multi-layered background shading system for price action analysis. It visualizes support/resistance zones around a central MA (often VWAP or RVWAP) using incremental offsets (either % or absolute points), generating symmetrical bands that resemble a "CATS" (Concentric Adaptive Tiered System) — hence the name.The background is "flipped" in the sense that shading intensity and structure emphasize higher-tier zones, and labels are placed to the right of the chart for future projection.Key FeaturesFeature
Description
Multi-MA Engine
Supports 20+ MA types: EMA, DEMA, TEMA, SMA, VWAP, RVWAP, HMA, ALMA, custom volume blends (CVB1–4)
RVWAP Mode
Rolling VWAP with adaptive or fixed time window (days/hours/minutes)
Gann Square of 9 Logic
Generates 80+ symmetric levels (0.25x to 17x increment) above/below the MA
Dual Increment Mode
Choose Percent or Points for spacing
Background Fills
Tiered transparency fills between Gann levels (darker = stronger zones)
Visual MA Offset
Shift MA line left/right without breaking fill alignment
Smart Labels
Projected labels on last bar: "FV", "normal", "high", "3/4" at key levels
Performance Optimized
Hidden plots + label cleanup to prevent lag
Primary Use Cases
1. Institutional VWAP Anchoring
Use RVWAP (1-day fixed) as maRaw
Set Increment = 0.5 points or 0.05%
Watch price interaction with "normal" (2x), "high" (4x), "3/4" (6x) zones
Ideal for intraday scalping on indices (ES, NQ) or forex
2. Swing Trading with Gann Projections
Use 400-period SMA/EMA on daily chart
Increment in Percent mode (~1.22%)
Identify confluence when price rejects at 2x, 4x, or 6x bands
Labels project future targets to the right
3. Volume-Weighted Mean Reversion
Select CVB1–CVB4 for heavy volume smoothing
Use Points mode for stocks with stable tick sizes (e.g. $0.50 increments)
Trade mean reversion between ±1x and ±2x bands
4. Risk Management & Stop Placement
Place stops beyond 2x or 4x bands
Take profits at next major tier (e.g. 4x → 6x)
Pro Tips
Enable "Use Fixed Time Period" for RVWAP to avoid session reset issues
Increase i_label_offset on lower timeframes to avoid overlap
Combine with volume profile or order flow for confluence
The "FV" label marks the Fair Value MA — core anchor
Summary"VWAP CATS Background Flipped 4.0" turns any moving average into a dynamic Gann-based pricing grid with intelligent background shading and forward-projected labels — perfect for institutional-style mean reversion, swing targeting, and risk-defined trading."
Smarter Money Volume Rejection Blocks [PhenLabs]📊 Smarter Money Volume Rejection Blocks – Institutional Rejection Zone Detection
The Smarter Money Volume Rejection Blocks indicator combines high-volume analysis with statistical confidence intervals to identify where institutional traders are actively defending price levels through volume spikes and rejection patterns.
🔥 Core Methodology
Volume Spike Detection analyzes when current volume exceeds moving average by configurable multipliers (1.0-5.0x) to identify institutional activity
Rejection Candle Analysis uses dual-ratio system measuring wick percentage (30-90%) and maximum body ratio (10-60%) to confirm genuine rejections
Statistical Confidence Channels create three-level zones (upper, center, lower) based on ATR or Standard Deviation calculations
Smart Invalidation Logic automatically clears zones when price significantly breaches confidence levels to maintain relevance
Dynamic Channel Projection extends confidence intervals forward up to 200 bars with customizable length
Support Zone Identification detects bullish rejections where smart money absorbs selling pressure with high volume and strong lower wicks
Resistance Zone Mapping identifies bearish rejections where institutions defend price levels with volume spikes and pronounced upper wicks
Visual Information Dashboard displays real-time status table showing volume spike conditions and active support/resistance zones
⚙️ Technical Configuration
Dual Confidence Interval Methods: Choose between ATR-Based for trend-following environments or StdDev-Based for range-bound statistical precision
Volume Moving Average: Configurable period (default 20) for baseline volume comparison calculations
Volume Spike Multiplier: Adjustable threshold from 1.0 to 5.0 times average volume to filter institutional activity
Rejection Wick Percentage: Set minimum wick size from 30% to 90% of candle range for valid rejection detection
Maximum Body Ratio: Configure body-to-range ratio from 10% to 60% to ensure genuine rejection structures
Confidence Multiplier: Statistical multiplier (default 1.96) for 95% confidence interval calculations
Channel Projection Length: Extend confidence zones forward from 10 to 200 bars for anticipatory analysis
ATR Period: Customize Average True Range lookback from 5 to 50 bars for volatility-based calculations
StdDev Period: Adjust Standard Deviation period from 10 to 100 bars for statistical precision
🎯 Real-World Trading Applications
Identify high-probability support zones where institutional buyers have historically defended price with significant volume
Map resistance levels where smart money sellers consistently reject higher prices with volume confirmation
Combine with price action analysis to confirm breakout validity when price approaches confidence channel boundaries
Use invalidation signals to exit positions when smart money zones are definitively breached
Monitor the real-time dashboard to quickly assess current market structure and active rejection zones
Adapt strategy based on calculation method: ATR for trending markets, StdDev for ranging conditions
Set alerts on confidence level breaches to catch potential trend reversals or continuation patterns
📈 Visual Interpretation Guide
Green Zones indicate bullish rejection blocks where buyers defended with high volume and lower wicks
Red Zones indicate bearish rejection blocks where sellers defended with high volume and upper wicks
Solid Center Lines represent the core rejection price level where maximum volume activity occurred
Dashed Confidence Boundaries show upper and lower statistical limits based on volatility calculations
Zone Opacity decreases as channels extend forward to indicate decreasing confidence over time
Dashboard Color Coding provides instant visual feedback on active volume spike and zone conditions
⚠️ Important Considerations
Volume-based indicators identify historical rejection zones but cannot predict future price action with certainty
Market conditions change rapidly and institutional activity patterns evolve continuously
High volume does not guarantee level defense as market structure can shift without warning
Confidence intervals represent statistical probabilities, not guaranteed price boundaries
VWAP – Pivot Pairs (SECONDS‑BASED RESET)VWAP – Pivot Pairs (SECONDS-BASED RESET) is a Pine Script v6 indicator for TradingView that combines pivot-based breakout detection with resettable VWAP (Volume Weighted Average Price) calculations over user-defined rolling time periods in seconds.It identifies high and low swing pivots via breakout logic, then calculates two VWAP lines per anchor:One using high/low as the price source,
One using close as the price source.
These form "pivot pairs" that reset automatically at the start of each custom-duration period (e.g., every 300 seconds), starting from a user-defined UTC time of day (default: 09:30 UTC).Visuals include:Colored VWAP lines (high pair: red, low pair: green),
Semi-transparent fill zones between each pair,
Optional toggles to show/hide high or low pairs.
Use CasesUse Case
Description
Intraday Scalping (1–15 min charts)
Use 60–300 second resets to capture micro-trends within larger sessions. VWAP pairs act as dynamic support/resistance after breakouts.
High-Frequency / Algo Validation
Backtest strategies on tick/second charts where traditional session resets fail. Align resets with exchange micro-sessions or volatility windows.
Opening Range Breakout (ORB) Enhancement
Set period_seconds = 1800 (30 min) and start time = 09:30 UTC → VWAP builds only on first 30 mins post-open, then floats. Pairs show deviation from ORB mean.
Range-Bound Market Analysis
In choppy markets, VWAP pairs converge near fair value. Divergence signals potential breakout. Fill color intensity shows conviction.
Multi-Timeframe Confluence
Overlay on 1-second chart with 300s reset → matches 5-minute structure. Use close-based VWAP for entries, high/low-based for stops.
Key Features SummaryFeature
Function
period_seconds
Rolling window length in seconds (e.g., 300 = 5 min)
period_start_time
UTC time-of-day anchor (default: 09:30)
new_period logic
Triggers full reset of pivots + VWAP on exact second boundary
breakingHigher / breakingLower
Detects confirmed breakouts (not just close above high)
Dual VWAP per anchor
ta.vwap(high) and ta.vwap(close) for range-aware mean
Fill zones
Visual value area between high/close VWAPs
Toggle visibility
Independently show/hide high or low pivot pairs
How It Works – Step-by-StepTime Engine Converts user inputs → milliseconds
Calculates current period start time using integer division from epoch
Detects exact bar when new period begins (new_period = true)
On New Period Resets both high/low anchors to current bar’s h and l
Forces VWAP recalculation from this bar forward
Breakout Detection Only triggers on strong candles (rising/falling, non-doji)
Requires open/close beyond prior pivot → avoids wicks-only breaks
VWAP Accumulation ta.vwap(source, reset_condition) restarts when anchor resets
Two sources per side → shows where volume clustered (at highs vs closes)
Plotting Four lines + two fills
Clean, customizable, overlay-friendly
Pro TipsUse on Heikin Ashi for smoother breakout signals.
Combine with volume profile to validate VWAP clusters.
For crypto, set period_start_time = 0 (00:00 UTC) for clean 4-hour resets.
Add alerts on new_period or breakingHigher for automation.
In short: This is a precision VWAP tool for time-boxed, pivot-driven mean reversion and breakout trading, ideal for scalpers, day traders, and algo developers needing sub-session granularity.
ATR / Price RatioDescription:
This indicator plots the ratio of the Average True Range (ATR) to the current price, showing volatility as a percentage of price rather than in absolute terms. It helps compare volatility across assets and timeframes by normalizing for price level.
A higher ATR/Price ratio means the market is moving a larger percentage of its value each bar (high relative volatility). A lower ratio indicates tighter, quieter price action (low relative volatility).
Traders can use this ratio to:
• Compare volatility between instruments
• Identify shifts into high or low volatility regimes
• Adjust position sizing and stop distances relative to risk
Contango/Backwardation Monitor
This is an indicator to display the spread difference between two products. I designed it around VX1! and VX2! but any other two products can be chosen. It is a simple subtraction of VX2-VX1. I will go through the options first and what they do followed by what contango/backwardation is in my own words. You will need the data package for VX futures for the default version to work.
INPUTS
-Apply Smoothing: choose to apply smoothing or not.
-Smoothing Method: choose between SMA,EMA,WMA, etc.
-Line Width: Width of line if line is chosen style(can be changed in style section)
-Threshold 1-5: This is the level at which the line will change colors(defaults are for VX)
-Color 1-5: The color the line will change to when crossing threshold.
Towards Backwardation: Background color change when line is slanted down
Towards Contango: Background color change when line is slanted up
Bars to Confirm Trend: This is my method to cut down on background color changes. It is how many bars consecutive going back needed to change color.
STYLE
-All colors and whatnot can be changed here(threshold colors can be changed here or on the input page).
T1 Line-T5 line: These are simple horizontal lines that can be used to denote threshold areas or whatever you want.
Contango/Backwardation-These terms are used mostly with futures to define the calendar spread between two contracts. Contango is when that spread is is getting longer and backwardation is when that spread is closing. In terms of VIX futures, Contango would imply that volatility is stabilizing and the S and P will likely gain. Backwardation, woudl eb the opposite.
The most simple way to read this indicator with default settings- If the line is up, red, and the background is red, then you can assume S and P prices are going down. And if the opposite is true, then prices are likely going up.
Please feel free to ask any questions and I will do my best to answer them.
Order-Flow Proxy (VWAP Deviation Zones)Order-Flow Proxy (VWAP Deviation Zones) helps traders visualize when market price moves unusually far away from its Volume-Weighted Average Price (VWAP) — a key fair-value level used by institutional participants.
When price stretches too far above or below VWAP, it often signals temporary imbalance between buying and selling pressure.
This tool highlights those moments using simple color zones and an optional statistical Z-Score filter for deeper precision.
In short: it’s a clean, minimal mean-reversion indicator showing when price is statistically “too far” from fair value.
Red zone → Price extended above VWAP → possible buyer exhaustion or short setup.
Green zone → Price extended below VWAP → possible seller exhaustion or long setup.
VWAP line → Acts as a dynamic fair-value anchor.
Concept:
VWAP combines both price and traded volume to define where most transactions occurred.
Deviations from it — measured either by a fixed distance (1%) or by Z-Score — can reveal overvaluation or undervaluation zones used by professional traders for contrarian setups.
How to use:
Apply the indicator to any intraday chart (1m–1h recommended).
Watch for background color shifts — red or green.
Optionally enable the Z-Score filter to focus only on statistically extreme deviations.
Combine with volume spikes, liquidity sweeps, or your own order-flow tools for confirmation.
Tip:
Best used as a visual overlay for detecting stretched markets and potential reversals.
