Trend Following Volatility TrailThe Trend Following Volatility Trail is a dynamic trend-following tool that adapts its stop, bias, and zones to real-time volatility and trend strength. Instead of using static ATR multiples like a normal Supertrend or Chandelier Stop, it continuously adjusts itself based on how stretched the market is and how persistent the trend has been.
This makes the system far more reactive during momentum phases and more conservative during consolidation, helping avoid fake flips and late entries.
How It Works
The indicator builds an adaptive trail around a smoothed price basis:
It starts with a short EMA as the “core trend line.”
It measures volatility expansion versus normal volatility.
It measures trend persistence by reading whether price has been rising or falling consistently.
These two components combine to adjust the ATR multiplier dynamically.
As volatility expands or the trend becomes more persistent, the bands widen. When volatility compresses or the trend weakens, the bands tighten.
These adaptive bands form the foundation of the trailing system.
Bull & Bear State Logic
The tool constantly tracks whether price is above or below the adaptive trail:
Price above the upper trail → Bullish regime
Price below the lower trail → Bearish regime
But instead of flipping immediately, it waits for confirmation bars to avoid noise. This greatly reduces whipsaws and keeps the focus on sustained moves.
Once a new regime is confirmed:
A coloured cloud appears (bull or bear)
A label marks the flip point
Alerts can be triggered automatically
Best Uses
Identifying regime shifts early
Riding sustained trends with confidence
Avoiding choppy markets by requiring confirmation
Using the adaptive cloud as a directional bias layer
Ketidakstabilan
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.
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.
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))
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
SuperTrend MA Fusion [CNU]SuperTrend MA Fusion is a next-generation upgrade of the classic SuperTrend indicator, engineered with a multi-MA adaptive ATR engine, advanced non-repaint logic, and clean trend-flip signal generation.
This version offers 18+ institutional-grade moving averages to smooth ATR volatility, allowing traders to customize trend sensitivity and signal responsiveness unlike anything possible with the standard SuperTrend.
Key Features
✔ 18+ Moving Average Options (MA Engine)
Customize volatility smoothing using any MA:
SMA, EMA, WMA, RMA
HMA, ZLEMA, LSMA, ALMA
KAMA, VIDYA
TEMA, DEMA
VWMA, WWMA, VAR
TILLSON T3, TSF
TMA
This allows extreme flexibility — from ultra-fast scalping signals to slow and smooth swing-trend filters.
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.
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.
Trend Zone BreakoutsThe HD Trend Zone Breakouts indicator identifies when the market is trending strongly on both your chart timeframe and a higher timeframe, then tracks moments where price becomes stretched inside that trend. When this stretch occurs, the indicator builds a dynamic zone capturing the full high–low range during that extension. Once the stretch ends, the zone is frozen, and the script waits to see how price reacts to it. Breakouts above or below these zones signal whether the trend is likely to continue or fail. This creates a powerful structure-based way to time entries, exits, and reversals without relying on noisy overbought/oversold signals.
How It Works
Confirms trend direction on both lower and higher timeframes using an EMA-based regime.
Detects stretched conditions using RSI only when both timeframes are aligned.
Draws a price zone around candles formed during these extreme trend pushes.
Freezes the zone once the stretch ends, creating a reference area.
Monitors for breakouts above/below the zone to confirm trend continuation or trend failure.
Breakout Logic
Bull continuation → price breaks above the top of a bullish zone.
Bull failure → price breaks below the bottom of a bullish zone.
Bear continuation → price breaks below the bottom of a bearish zone.
Bear failure → price breaks above the top of a bearish zone.
Why It’s Useful
Distinguishes meaningful extensions from ordinary RSI signals.
Provides clear structural levels for timing trades.
Identifies trend continuation early and flags potential reversals.
Works extremely well alongside EMAC Forecast, Trend Exhaustion Lite, and Volatility Squeeze.
orb cody hoskinscody orb designed a 15 min range orb indicator for people to use dur8ng market open in asian and new york
Emac ML Adaptive CrossoverThe HDAlgos EMAC ML Adaptive Crossover is an adaptive trend reading and crossover system that uses a lightweight machine learning style scoring engine to detect regime shifts in the market. It blends multiple normalised technical features and automatically adjusts EMA lengths based on the detected market regime.
How it works
Feature Engine
The script computes several normalised indicators including RSI, ATR percentage, and Rate of Change. Each feature is converted into a z score so that the values behave consistently across different markets and timeframes. These feature values are then averaged to form a composite regime score.
Regime Detection
The composite score is compared to a dynamic upper and lower threshold. If the score rises above the upper boundary the regime becomes bullish. If the score falls below the lower boundary it becomes bearish. If it stays between the two boundaries the market is classified as neutral.
Adaptive EMAs
The fast and slow EMA lengths are automatically adjusted depending on the detected regime.
• In bullish regimes the fast and slow EMAs shorten.
• In bearish regimes they lengthen.
• In neutral regimes they revert to their base lengths.
This creates an EMA crossover system that responds to market volatility and directional strength rather than using fixed lookback values.
Crossovers
When the adaptive fast EMA crosses above the adaptive slow EMA, a bullish signal appears. When it crosses below, a bearish signal appears.
Visual Aids
• The fast EMA changes color to reflect the current regime.
• Candles can be optionally painted in regime colors.
• A label on the last bar shows the detected regime, score, and active EMA lengths.
• A compact table can be shown in the corner summarizing regime state and metrics.
Alerts
Alerts trigger when the regime changes, when a bullish adaptive crossover occurs, and when a bearish adaptive crossover occurs.
What it is designed for
This indicator is built for traders who want a crossover system that adapts to real market conditions instead of reacting to fixed length EMAs. It provides:
Smoother identification of trend phases
Dynamic sensitivity during strong conditions
Dampened reactions during noise and low conviction periods
Clear and simple signals that remain easy to interpret
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.
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*
ADR % Used (Subpane)I am Useless at reading ADR so I built this ADR Indicator With a dashboard to Inform me of the percentage of the range Used I use it with other Indicators especially price action and it tells you if it is safe to trade or not Quite Useful for me maybe you too
Multi-TF Volatility Channel DashboardThis tool tracks where price sits inside a volatility channel on two timeframes at once and turns it into a simple trend state.
What it does
Builds a volatility channel around price using a midline and a volatility based band.
Converts the position of price inside that band into an oscillator that moves roughly between -100 and +100.
Calculates this oscillator on:
The current chart timeframe (LTF)
A selected higher timeframe (HTF)
From that it classifies each timeframe as:
Bull: oscillator above zero
Bear: oscillator below zero
Neutral: oscillator near zero
You can then see:
LTF oscillator line
HTF oscillator line
A small table showing LTF state, HTF state, and whether they are aligned
When both LTF and HTF are bullish or both are bearish, the background can highlight that period, and optional alerts fire.
How to use it
Trade in the direction of the higher timeframe when both lines agree.
Avoid taking counter trend trades when LTF and HTF are in strong but opposite states.
Use the LTF line for timing and the HTF line for directional bias.
Emac ForecastEMAC Forecast System
What it measures
The EMAC Forecast measures the speed and persistence of trend movement. Instead of only looking at whether one EMA is above or below another, the forecast quantifies how quickly momentum is building or fading across multiple time horizons.
It captures three things at once:
The direction of the underlying trend
The rate at which the trend is strengthening or weakening
The consistency of that change across several smoothing speeds
This produces a forward leaning view of trend conditions, not a trailing confirmation.
How to read the forecast
The EMAC Forecast is displayed as a scaled oscillator, typically ranging between negative and positive values.
Positive forecast values
Indicate that bullish trend pressure is increasing.
Higher readings mean stronger acceleration, not just price rising.
Negative forecast values
Indicate increasing bearish pressure.
Again, the strength of the negative reading reflects how quickly selling momentum is building.
Rising forecast (slope up)
Shows improving momentum, even if the value is still below zero.
Useful for catching early reversals or transitions from chop to trend.
Falling forecast (slope down)
Shows momentum fading, even when trend direction has not flipped yet.
Helps anticipate exhaustions and pullbacks.
Flat forecast
Indicates low conviction and lack of directional drive.
Often corresponds to chop or range conditions.
Why the EMAC Forecast is different from a regular EMAC
A standard EMAC or EMA crossover follows a simple rule:
When fast EMA crosses above slow EMA, bullish.
When fast EMA crosses below slow EMA, bearish.
This is reactive and only changes after price has already moved.
The EMAC Forecast works differently:
1. Uses multiple EMAs rather than two
Instead of comparing one fast and one slow average, it blends several time constants into a composite signal.
This creates a smoother, more reliable directional read.
2. Measures acceleration, not just position
Traditional crossovers only monitor whether lines have crossed.
EMAC Forecast measures the speed and force behind the movement.
It tells you how strong the trend is becoming, not just whether one line is above the other.
3. Adapts to volatility
Sharp markets increase weighting of fast components.
Calm markets increase influence of slower components.
This reduces whipsaws in low-volatility conditions and improves responsiveness in high-volatility environments.
4. Gives actionable information before a crossover happens
The forecast often turns before the EMAC direction flips, allowing early detection of:
Trend ignition
Trend fade
Momentum squeezes
Impending reversals
It effectively “leans forward” into the trend instead of waiting for a full reversal.
Practical Use Cases
Early trend identification
When the forecast first turns positive or negative, trend acceleration is beginning.
This is often visible before the EMAC lines cross.
Confirming the Combined Forecast System
Use the EMAC Forecast to validate signals from your other forecast models.
If both agree, conviction is notably higher.
Filtering noise
Short-term whipsaws are reduced because the composite structure dilutes erratic fast movements.
Trend aging and exhaustion
A falling forecast during a positive trend suggests reduced conviction and potential exhaustion.
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.
ES + NQ vs VIX Risk-On / Risk-Off Toolkit [SB1]ES + NQ vs VIX Risk-On / Risk-Off Toolkit — Indicator Description
This toolkit provides a full market-sentiment dashboard by comparing S&P 500 (ES), Nasdaq 100 (NQ), and VIX behavior in real time. It is designed to quickly identify when conditions align into Risk-On, Risk-Off, or Neutral market states and to highlight high-conviction candles that support trend continuation.
🔹 Core Logic
The script evaluates:
ES & NQ Candle Bias
Each index is classified as Bullish, Bearish, or Neutral based on its current candle (close vs open).
VIX Direction
Rising VIX = Risk-Off pressure
Falling VIX = Risk-On relief
Market Sentiment Alignment
Risk-On: ES Bullish + NQ Bullish + VIX Falling
Risk-Off: ES Bearish + NQ Bearish + VIX Rising
Neutral: Anything not aligned
🔹 Normalized Trend Strength (n-value)
The indicator introduces a normalized trend metric for both ES and NQ:
Uses fast and slow EMAs to measure directional strength
Normalizes the EMA distance by ATR
Produces an n-value that shows trend intensity regardless of volatility regime
Alerts trigger when the trend reaches a configurable strength range
This helps identify when either index is entering a strong trend environment.
🔹 Movable Dashboard
A clean on-chart dashboard displays:
ES bias & n-value
NQ bias & n-value
VIX direction (Rising / Falling / Flat)
You can place the dashboard in any chart corner (Top-Left, Top-Right, Bottom-Left, Bottom-Right).
🔹 VIX Background Context
Optionally color the chart background automatically:
Green: Risk-On alignment
Red: Risk-Off alignment
Gray: Neutral
This provides immediate visual context behind price action.
🔹 Strong Candle Detection
The script highlights powerful bullish and bearish candles using objective criteria:
Body must exceed a minimum % of the total range
Close must occur near the session extreme
Automatically marks strong candles with up/down triangles
Optionally colors the candle bar for added clarity
Alerts also fire when a strong candle aligns with Risk-On or Risk-Off sentiment.
🔹 Alert System
Built-in alerts cover:
Risk-On alignment
Risk-Off alignment
Neutral/Out-of-alignment context
Strong Bull/Bear Candle + Sentiment alignment
High-trend n-value signals for ES and NQ
All alerts use clear descriptions for automated strategy integration.
📌 Summary
This tool provides a complete multi-asset sentiment engine by combining:
ES & NQ directional bias
VIX volatility pressure
Normalized trend strength
Strong candle confirmation
Visual dashboard
Automated alerts
It is built to support traders who rely on intermarket context, trend strength, and high-confluence entries. Release Notes
🆕 Update: Added Normalized Trend Strength (n-Value)
This update introduces a Normalized Trend Strength metric, displayed as a small numeric value next to each trend signal. It measures how strong the current trend is relative to market volatility.
How It Works
The n-value uses the difference between the Fast EMA and Slow EMA, divided by ATR:
n = | Fast EMA – Slow EMA | ÷ ATR
This transforms raw price movement into a volatility-adjusted trend strength score, making it easier to compare trend quality across different market conditions.
How to Read the n-Value
n-Value Meaning
< 0.10 No trend / Chop / Noise
0.10 – 0.30 Weak trend
0.30 – 0.60 Moderate trend
0.60 – 1.00 Strong trend
1.00+ Very strong momentum
Why It Matters
This addition helps you:
Filter weak signals
Confirm when a trend has real strength
Avoid low-quality setups
Spot strong momentum early
The n-value works automatically with your existing Fast/Slow EMA trend logic and appears inline with the trend label so you can evaluate signals at a glance.
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.
