Ripster Clouds (EMA + MTF)v6🧠 Purpose
This indicator combines Ripster EMA Clouds and Multi-Timeframe (MTF) EMA Clouds into one script.
It allows you to visualize short vs long exponential (or simple) moving averages as colored “clouds” to identify trend direction and momentum — across both your current timeframe and a higher timeframe (e.g., daily).
⚙️ Main Features
1. EMA Clouds (Local Timeframe)
Up to 5 separate EMA/SMA cloud sets (8/9, 5/12, 34/50, 72/89, 180/200 by default).
Each can be individually enabled/disabled in the settings.
MA type toggle → Choose between EMA and SMA.
Optional line display toggle for showing the short and long MA lines.
Color-coded trend clouds:
Greenish tones = bullish (short > long)
Reddish tones = bearish (short < long)
Configurable leading offset and global offset for alignment.
2. MTF Clouds (Higher Timeframe)
Two sets of higher timeframe EMA clouds (default: 50/55 and 20/21).
Uses request.security() to pull EMA data from a selected higher timeframe (default = Daily).
Optional line visibility toggle (Display Lines).
Blue and teal semi-transparent fills to distinguish from local clouds.
Each MTF cloud can be toggled independently.
3. Unified Controls
Master toggles:
✅ Show EMA Clouds
✅ Show MTF Clouds
Transparent cloud fills with dynamically changing colors based on EMA crossovers and slope.
No local-scope plot() or fill() calls — fully compliant with Pine v6 rules.
🎨 Color Logic
Each EMA cloud uses a unique color pair (5 total).
Cloud color changes dynamically based on whether the short EMA is above or below the long EMA.
Line color changes with slope:
Olive = EMA rising
Maroon = EMA falling
📊 Technical Structure
Written in Pine Script v6.
All plot() and fill() calls are at global scope to prevent compilation errors.
Uses helper functions only for math/color logic.
Performance-optimized for TradingView’s rendering limits.
🧩 Quick Setup in TradingView
Paste the script into the Pine Editor.
Add to chart.
In settings:
Toggle on/off any EMA or MTF clouds.
Adjust timeframe (Resolution), line visibility, or offsets.
Choose EMA or SMA as the base calculation.
✅ Result
You now have one unified, customizable Ripster EMA + MTF Cloud indicator, stable in Pine v6, with complete flexibility to toggle, style, and analyze multiple timeframe trends on a single chart.
Поиск скриптов по запросу "乌德勒支+VS+赫拉克勒斯"
Tri-Align Crypto Trend (EMA + Slope)**Tri-Align Crypto Trend (EMA + Slope)**
Quickly see whether your coin is trending *with* Bitcoin. The indicator evaluates three pairs—**COIN/USDT**, **BTC/USDT**, and **COIN/BTC**—using a fast/slow EMA crossover plus the fast EMA’s slope. Each pair is tagged **Bullish / Bearish / Neutral** in a compact, color-coded table. Alerts fire when **all three** trends align (all bullish or all bearish).
**How to use**
1. Add the indicator to any crypto chart.
2. Set the three symbols (defaults: BNB/USDT, BTC/USDT, BNB/BTC) and optionally choose a signal timeframe.
3. Tune **Fast EMA**, **Slow EMA**, **Slope Lookback**, and **Min |Slope| %** to filter noise and require stronger momentum.
4. Create alerts: *Add alert →* choose the indicator and select **All Three Bullish**, **All Three Bearish**, or **All Three Aligned**.
**Logic**
* Bullish: `EMA_fast > EMA_slow` **and** fast EMA slope ≥ threshold
* Bearish: `EMA_fast < EMA_slow` **and** fast EMA slope ≤ −threshold
* Otherwise: Neutral
Tip: The **COIN/BTC** row reflects relative strength vs BTC—use it to avoid chasing coins that lag the benchmark. (For educational purposes; not financial advice.)
Tri-Align Crypto Trend (EMA + Slope)**Tri-Align Crypto Trend (EMA + Slope)**
Quickly see whether your coin is trending *with* Bitcoin. The indicator evaluates three pairs—**COIN/USDT**, **BTC/USDT**, and **COIN/BTC**—using a fast/slow EMA crossover plus the fast EMA’s slope. Each pair is tagged **Bullish / Bearish / Neutral** in a compact, color-coded table. Alerts fire when **all three** trends align (all bullish or all bearish).
**How to use**
1. Add the indicator to any crypto chart.
2. Set the three symbols (defaults: BNB/USDT, BTC/USDT, BNB/BTC) and optionally choose a signal timeframe.
3. Tune **Fast EMA**, **Slow EMA**, **Slope Lookback**, and **Min |Slope| %** to filter noise and require stronger momentum.
4. Create alerts: *Add alert →* choose the indicator and select **All Three Bullish**, **All Three Bearish**, or **All Three Aligned**.
**Logic**
* Bullish: `EMA_fast > EMA_slow` **and** fast EMA slope ≥ threshold
* Bearish: `EMA_fast < EMA_slow` **and** fast EMA slope ≤ −threshold
* Otherwise: Neutral
Tip: The **COIN/BTC** row reflects relative strength vs BTC—use it to avoid chasing coins that lag the benchmark. (For educational purposes; not financial advice.)
Percentile Rank Oscillator (Price + VWMA)A statistical oscillator designed to identify potential market turning points using percentile-based price analytics and volume-weighted confirmation.
What is PRO?
Percentile Rank Oscillator measures how extreme current price behavior is relative to its own recent history. It calculates a rolling percentile rank of price midpoints and VWMA deviation (volume-weighted price drift). When price reaches historically rare levels – high or low percentiles – it may signal exhaustion and potential reversal conditions.
How it works
Takes midpoint of each candle ((H+L)/2)
Ranks the current value vs previous N bars using rolling percentile rank
Maps percentile to a normalized oscillator scale (-1..+1 or 0–100)
Optionally evaluates VWMA deviation percentile for volume-confirmed signals
Highlights extreme conditions and confluence zones
Why percentile rank?
Median-based percentiles ignore outliers and read the market statistically – not by fixed thresholds. Instead of guessing “overbought/oversold” values, the indicator adapts to current volatility and structure.
Key features
Rolling percentile rank of price action
Optional VWMA-based percentile confirmation
Adaptive, noise-robust structure
User-selectable thresholds (default 95/5)
Confluence highlighting for price + VWMA extremes
Optional smoothing (RMA)
Visual extreme zone fills for rapid signal recognition
How to use
High percentile values –> statistically extreme upward deviation (potential top)
Low percentile values –> statistically extreme downward deviation (potential bottom)
Price + VWMA confluence strengthens reversal context
Best used as part of a broader trading framework (market structure, order flow, etc.)
Tip: Look for percentile spikes at key HTF levels, after extended moves, or where liquidity sweeps occur. Strong moves into rare percentile territory may precede mean reversion.
Suggested settings
Default length: 100 bars
Thresholds: 95 / 5
Smoothing: 1–3 (optional)
Important note
This tool does not predict direction or guarantee outcomes. It provides statistical context for price extremes to help traders frame probability and timing. Always combine with sound risk management and other tools.
FVG MagicFVG Magic — Fair Value Gaps with Smart Mitigation, Inversion & Auto-Clean-up
FVG Magic finds every tradable Fair Value Gap (FVG), shows who powered it, and then manages each gap intelligently as price interacts with it—so your chart stays actionable and clean.
Attribution
This tool is inspired by the idea popularized in “Volumatic Fair Value Gaps ” by BigBeluga (licensed CC BY-NC-SA 4.0). Credit to BigBeluga for advancing FVG visualization in the community.
Important: This is a from-scratch implementation—no code was copied from the original. I expanded the concept substantially with a different detection stack, a gap state machine (ACTIVE → 50% SQ → MITIGATED → INVERSED), auto-clean up rules, lookback/nearest-per-side pruning, zoom-proof volume meters, and timeframe auto-tuning for 15m/H1/H4.
What makes this version more accurate
Full-coverage detection (no “missed” gaps)
Default ICT-minimal rule (Bullish: low > high , Bearish: high < low ) catches all valid 3-candle FVGs.
Optional Strict filter (stricter structure checks) for traders who prefer only “clean” gaps.
Optional size percentile filter—off by default so nothing is hidden unless you choose to filter.
Correct handling of confirmations (wick vs close)
Mitigation Source is user-selectable: high/low (wick-based) or close (strict).
This avoids false “misses” when you expect wick confirmations (50% or full fill) but your logic required closes.
State-aware labelling to prevent misleading data
The Bull%/Bear% meter is shown only while a gap is ACTIVE.
As soon as a gap is 50% SQ, MITIGATED, or INVERSED, the meter is hidden and replaced with a clear tag—so you never read stale participation stats.
Robust zoom behaviour
The meter uses a fixed bar-width (not pixels), so it stays proportional and readable at any zoom level.
Deterministic lifecycle (no stale boxes)
Remove on 50% SQ (instant or delayed).
Inversion window after first entry: if price enters but doesn’t invert within N bars, the box auto-removes once fully filled.
Inversion clean up: after a confirmed flip, keep for N bars (context) then delete (or 0 = immediate).
Result: charts auto-maintain themselves and never “lie” about relevance.
Clarity near current price
Nearest-per-side (keep N closest bullish & bearish gaps by distance to the midpoint) focuses attention where it matters without altering detection accuracy.
Lookback (bars) ensures reproducible behaviour across accounts with different data history.
Timeframe-aware defaults
Sensible auto-tuning for 15m / H1 / H4 (right-extension length, meter width, inversion windows, clean up bars) to reduce setup friction and improve consistency.
What it does (under the hood)
Detects FVGs using ICT-minimal (default) or a stricter rule.
Samples volume from a 10× lower timeframe to split participation into Bull % / Bear % (sum = 100%).
Manages each gap through a state machine:
ACTIVE → 50% SQ (midline) → MITIGATED (full) → INVERSED (SR flip after fill).
Auto-clean up keeps only relevant levels, per your rules.
Dashboard (top-right) displays counts by side and the active state tags.
How to use it
First run (show everything)
Use Strict FVG Filter: OFF
Enable Size Filter (percentile): OFF
Mitigation Source: high/low (wick-based) or close (stricter), as you prefer.
Remove on 50% SQ: ON, Delay: 0
Read the context
While ACTIVE, use the Bull%/Bear% meter to gauge demand/supply behind the impulse that created the gap.
Confluence with your HTF structure, sessions, VWAP, OB/FVG, RSI/MACD, etc.
Trade interactions
50% SQ: often the highest-quality interaction; if removal is ON, the box clears = “job done.”
Full mitigation then rejection through the other side → tag changes to INVERSED (acts like SR). Keep for N bars, then auto-remove.
Keep the chart tidy (optional)
If too busy, enable Size Filter or set Nearest per side to 2–4.
Use Lookback (bars) to make behaviour consistent across symbols and histories.
Inputs (key ones)
Use Strict FVG Filter: OFF(default)/ON
Enable Size Filter (percentile): OFF(default)/ON + threshold
Mitigation Source: high/low or close
Remove on 50% SQ + Delay
Inversion window after entry (bars)
Remove inversed after (bars)
Lookback (bars), Nearest per side (N)
Right Extension Bars, Max FVGs, Meter width (bars)
Colours: Bullish, Bearish, Inversed fill
Suggested defaults (per TF)
15m: Extension 50, Max 12, Inversion window 8, Clean up 8, Meter width 20
H1: Extension 25, Max 10, Inversion window 6, Clean up 6, Meter width 15
H4: Extension 15, Max 8, Inversion window 5, Clean up 5, Meter width 10
Notes & edge cases
If a wick hits 50% or the far edge but state doesn’t change, you’re likely on close mode—switch to high/low for wick-based behaviour.
If a gap disappears, it likely met a clean up condition (50% removal, inversion window, inversion clean up, nearest-per-side, lookback, or max-cap).
Meters are hidden after ACTIVE to avoid stale percentages.
Rolling Correlation vs Another Symbol (SPY Default)This indicator visualizes the rolling correlation between the current chart symbol and another selected asset, helping traders understand how closely the two move together over time.
It calculates the Pearson correlation coefficient over a user-defined period (default 22 bars) and plots it as a color-coded line:
• Green line → positive correlation (move in the same direction)
• Red line → negative correlation (move in opposite directions)
• A gray dashed line marks the zero level (no correlation).
The background highlights periods of strong relationship:
• Light green when correlation > +0.7 (strong positive)
• Light red when correlation < –0.7 (strong negative)
Use this tool to quickly spot diversification opportunities, confirm hedges, or understand how assets interact during different market regimes.
Buying/Selling PressureBuying/Selling Pressure - Volume-Based Market Sentiment
Buying/Selling Pressure identifies market dominance by separating volume into buying and selling components. The indicator uses Volume ATR normalization to create a universal pressure oscillator that works consistently across all markets and timeframes.
What is Buying/Selling Pressure?
This indicator answers a fundamental question: Are buyers or sellers in control? By analyzing how volume distributes within each bar, it calculates cumulative buying and selling pressure, then normalizes the result using Volume ATR for cross-market comparability.
Formula: × 100
Where Delta = Buying Volume - Selling Volume
Calculation Methods
Money Flow (Recommended):
Volume weighted by close position in bar range. Close near high = buying pressure, close near low = selling pressure.
Formula: / (high - low)
Simple Delta:
Basic approach where bullish bars = 100% buying, bearish bars = 100% selling.
Weighted Delta:
Volume weighted by body size relative to total range, focusing on candle strength.
Key Features
Volume ATR Normalization: Adapts to volume volatility for consistent readings across assets
Cumulative Delta: Tracks net buying/selling pressure over time (similar to OBV)
Signal Line: EMA smoothing for trend identification and crossover signals
Zero Line: Clear visual separation between buyer and seller dominance
Color-Coded Display: Green area = buyers control, red area = sellers control
Interpretation
Above Zero: Buyers dominating - cumulative buying pressure exceeds selling
Below Zero: Sellers dominating - cumulative selling pressure exceeds buying
Cross Signal Line: Momentum shift - pressure trend changing direction
Increasing Magnitude: Strengthening pressure in current direction
Decreasing Magnitude: Weakening pressure, potential reversal
Volume vs Pressure
High volume with low pressure indicates balanced battle between buyers and sellers. High pressure with high volume confirms strong directional conviction. This separation provides insights beyond traditional volume analysis.
Best Practices
Use with price action for confirmation
Divergences signal potential reversals (price makes new high/low but pressure doesn't)
Large volume with near-zero pressure = indecision, breakout preparation
Signal line crossovers provide momentum change signals
Extreme readings suggest potential exhaustion
Settings
Calculation Method: Choose Money Flow, Simple Delta, or Weighted Delta
EMA Length: Period for cumulative delta smoothing (default: 21)
Signal Line: Optional EMA of oscillator for crossover signals (default: 9)
Buying/Selling Pressure transforms volume analysis into actionable market sentiment, revealing whether buyers or sellers control price action beneath surface volatility.
This indicator is designed for educational and analytical purposes. Past performance does not guarantee future results. Always conduct thorough research and consider consulting with financial professionals before making investment decisions.
🔥 QUANT MOMENTUM SKORQUANT MOMENTUM SCORE – Description (EN)
Summary: This indicator fuses Price ROC, RSI, MACD, Trend Strength (ADX+EMA) and Volume into a single 0-100 “Momentum Score.” Guide bands (50/60/70/80) and ready-to-use alert conditions are included.
How it works
Price Momentum (ROC): Rate of change normalized to 0-100.
RSI Momentum: RSI treated as a momentum proxy and mapped to 0-100.
MACD Momentum: MACD histogram normalized to capture acceleration.
Trend Strength: ADX is direction-aware (DI+ vs DI–) and blended with EMA state (above/below) to form a combined trend score.
Volume Momentum: Volume relative to its moving average (ratio-based).
Weighting: All five components are weighted, auto-normalized, and summed into the final 0-100 score.
Visuals & Alerts: Score line with 50/60/70/80 guides; threshold-cross alerts for High/Strong/Ultra-Strong regimes.
Inputs, weights and thresholds are configurable; total weights are normalized automatically.
How to use
Timeframes: Works on any timeframe—lower TFs react faster; higher TFs reduce noise.
Reading the score:
<50: Weak momentum
50-60: Transition
60-70: Moderate-Strong (potential acceleration)
≥70: Strong, ≥80: Ultra Strong
Practical tip: Use it as a filter, not a stand-alone signal. Combine score breakouts with market structure/trend context (e.g., pullback-then-re-acceleration) to improve selectivity.
Disclaimer: This is not financial advice; past performance does not guarantee future results.
5x Relative Volume vs 30-Day AverageRelative Volume.
If today's volume is more than average of last 30 days volume by 5x.
Up vs Down Volume Compared to PriceHi team,
I’ve put together a simple TradingView indicator that breaks down the last N candles into up-moves and down-moves, showing how much volume supported each side. It helps you quickly see whether the market is rallying on strong participation or just drifting higher on weak volume.
The tool tracks total up-volume versus down-volume, compares their ratios, and flags when pullbacks are happening with noticeably lower volume than the prior push up — a setup that often signals a healthy continuation rather than a reversal.
It also shows key metrics like total volume, price change, and up/down ratios directly on the chart for quick assessment. You’ll instantly know if you’re looking at a light-volume pullback or a heavy-volume sell-off.
Let’s test it out across a few symbols and discuss any tweaks we’d like — maybe layering an EMA or VWAP filter for cleaner trend confirmation.
Double Weighted Moving Average (DWMA)# DWMA: Double Weighted Moving Average
## Overview and Purpose
The Double Weighted Moving Average (DWMA) is a technical indicator that applies weighted averaging twice in sequence to create a smoother signal with enhanced noise reduction. Developed in the late 1990s as an evolution of traditional weighted moving averages, the DWMA was created by quantitative analysts seeking enhanced smoothing without the excessive lag typically associated with longer period averages. By applying a weighted moving average calculation to the results of an initial weighted moving average, DWMA achieves more effective filtering while preserving important trend characteristics.
## Core Concepts
* **Cascaded filtering:** DWMA applies weighted averaging twice in sequence for enhanced smoothing and superior noise reduction
* **Linear weighting:** Uses progressively increasing weights for more recent data in both calculation passes
* **Market application:** Particularly effective for trend following strategies where noise reduction is prioritized over rapid signal response
* **Timeframe flexibility:** Works across multiple timeframes but particularly valuable on daily and weekly charts for identifying significant trends
The core innovation of DWMA is its two-stage approach that creates more effective noise filtering while minimizing the additional lag typically associated with longer-period or higher-order filters. This sequential processing creates a more refined output that balances noise reduction and signal preservation better than simply increasing the length of a standard weighted moving average.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Length | 14 | Controls the lookback period for both WMA calculations | Increase for smoother signals in volatile markets, decrease for more responsiveness |
| Source | close | Price data used for calculation | Consider using hlc3 for a more balanced price representation |
**Pro Tip:** For trend following, use a length of 10-14 with DWMA instead of a single WMA with double the period - this provides better smoothing with less lag than simply increasing the period of a standard WMA.
## Calculation and Mathematical Foundation
**Simplified explanation:**
DWMA first calculates a weighted moving average where recent prices have more importance than older prices. Then, it applies the same weighted calculation again to the results of the first calculation, creating a smoother line that reduces market noise more effectively.
**Technical formula:**
```
DWMA is calculated by applying WMA twice:
1. First WMA calculation:
WMA₁ = (P₁ × w₁ + P₂ × w₂ + ... + Pₙ × wₙ) / (w₁ + w₂ + ... + wₙ)
2. Second WMA calculation applied to WMA₁:
DWMA = (WMA₁₁ × w₁ + WMA₁₂ × w₂ + ... + WMA₁ₙ × wₙ) / (w₁ + w₂ + ... + wₙ)
```
Where:
- Linear weights: most recent value has weight = n, second most recent has weight = n-1, etc.
- n is the period length
- Sum of weights = n(n+1)/2
**O(1) Optimization - Inline Dual WMA Architecture:**
This implementation uses an advanced O(1) algorithm with two complete inline WMA calculations. Each WMA uses the dual running sums technique:
1. **First WMA (source → wma1)**:
- Maintains buffer1, sum1, weighted_sum1
- Recurrence: `W₁_new = W₁_old - S₁_old + (n × P_new)`
- Cached denominator norm1 after warmup
2. **Second WMA (wma1 → dwma)**:
- Maintains buffer2, sum2, weighted_sum2
- Recurrence: `W₂_new = W₂_old - S₂_old + (n × WMA₁_new)`
- Cached denominator norm2 after warmup
**Implementation details:**
- Both WMAs fully integrated inline (no helper functions)
- Each maintains independent state: buffers, sums, counters, norms
- Both warm up independently from bar 1
- Performance: ~16 operations per bar regardless of period (vs ~10,000 for naive O(n²) implementation)
**Why inline architecture:**
Unlike helper functions, the inline approach makes all state variables and calculations visible in a single scope, eliminating function call overhead and making the dual-pass nature explicit. This is ideal for educational purposes and when debugging complex cascaded filters.
> 🔍 **Technical Note:** The dual-pass O(1) approach creates a filter that effectively increases smoothing without the quadratic increase in computational cost. Original O(n²) implementations required ~10,000 operations for period=100; this optimized version requires only ~16 operations, achieving a 625x speedup while maintaining exact mathematical equivalence.
## Interpretation Details
DWMA can be used in various trading strategies:
* **Trend identification:** The direction of DWMA indicates the prevailing trend
* **Signal generation:** Crossovers between price and DWMA generate trade signals, though they occur later than with single WMA
* **Support/resistance levels:** DWMA can act as dynamic support during uptrends and resistance during downtrends
* **Trend strength assessment:** Distance between price and DWMA can indicate trend strength
* **Noise filtering:** Using DWMA to filter noisy price data before applying other indicators
## Limitations and Considerations
* **Market conditions:** Less effective in choppy, sideways markets where its lag becomes a disadvantage
* **Lag factor:** More lag than single WMA due to double calculation process
* **Initialization requirement:** Requires more data points for full calculation, showing more NA values at chart start
* **Short-term trading:** May miss short-term trading opportunities due to increased smoothing
* **Complementary tools:** Best used with momentum oscillators or volume indicators for confirmation
## References
* Jurik, M. "Double Weighted Moving Averages: Theory and Applications in Algorithmic Trading Systems", Jurik Research Papers, 2004
* Ehlers, J.F. "Cycle Analytics for Traders," Wiley, 2013
Weighted Moving Average (WMA)This implementation uses O(1) algorithm that eliminates the need to loop through all period values on each bar. It also generates valid WMA values from the first bar and is not returning NA when number of bars is less than period.
## Overview and Purpose
The Weighted Moving Average (WMA) is a technical indicator that applies progressively increasing weights to more recent price data. Emerging in the early 1950s during the formative years of technical analysis, WMA gained significant adoption among professional traders through the 1970s as computational methods became more accessible. The approach was formalized in Robert Colby's 1988 "Encyclopedia of Technical Market Indicators," establishing it as a staple in technical analysis software. Unlike the Simple Moving Average (SMA) which gives equal weight to all prices, WMA assigns greater importance to recent prices, creating a more responsive indicator that reacts faster to price changes while still providing effective noise filtering.
## Core Concepts
* **Linear weighting:** WMA applies progressively increasing weights to more recent price data, creating a recency bias that improves responsiveness
* **Market application:** Particularly effective for identifying trend changes earlier than SMA while maintaining better noise filtering than faster-responding averages like EMA
* **Timeframe flexibility:** Works effectively across all timeframes, with appropriate period adjustments for different trading horizons
The core innovation of WMA is its linear weighting scheme, which strikes a balance between the equal-weight approach of SMA and the exponential decay of EMA. This creates an intuitive and effective compromise that prioritizes recent data while maintaining a finite lookback period, making it particularly valuable for traders seeking to reduce lag without excessive sensitivity to price fluctuations.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Length | 14 | Controls the lookback period | Increase for smoother signals in volatile markets, decrease for responsiveness |
| Source | close | Price data used for calculation | Consider using hlc3 for a more balanced price representation |
**Pro Tip:** For most trading applications, using a WMA with period N provides better responsiveness than an SMA with the same period, while generating fewer whipsaws than an EMA with comparable responsiveness.
## Calculation and Mathematical Foundation
**Simplified explanation:**
WMA calculates a weighted average of prices where the most recent price receives the highest weight, and each progressively older price receives one unit less weight. For example, in a 5-period WMA, the most recent price gets a weight of 5, the next most recent a weight of 4, and so on, with the oldest price getting a weight of 1.
**Technical formula:**
```
WMA = (P₁ × w₁ + P₂ × w₂ + ... + Pₙ × wₙ) / (w₁ + w₂ + ... + wₙ)
```
Where:
- Linear weights: most recent value has weight = n, second most recent has weight = n-1, etc.
- The sum of weights for a period n is calculated as: n(n+1)/2
- For example, for a 5-period WMA, the sum of weights is 5(5+1)/2 = 15
**O(1) Optimization - Dual Running Sums:**
The key insight is maintaining two running sums:
1. **Unweighted sum (S)**: Simple sum of all values in the window
2. **Weighted sum (W)**: Sum of all weighted values
The recurrence relation for a full window is:
```
W_new = W_old - S_old + (n × P_new)
```
This works because when all weights decrement by 1 (as the window slides), it's mathematically equivalent to subtracting the entire unweighted sum. The implementation:
- **During warmup**: Accumulates both sums as the window fills, computing denominator each bar
- **After warmup**: Uses cached denominator (constant at n(n+1)/2), updates both sums in constant time
- **Performance**: ~8 operations per bar regardless of period, vs ~100+ for naive O(n) implementation
> 🔍 **Technical Note:** Unlike EMA which theoretically considers all historical data (with diminishing influence), WMA has a finite memory, completely dropping prices that fall outside its lookback window. This creates a cleaner break from outdated market conditions. The O(1) optimization achieves 12-25x speedup over naive implementations while maintaining exact mathematical equivalence.
## Interpretation Details
WMA can be used in various trading strategies:
* **Trend identification:** The direction of WMA indicates the prevailing trend with greater responsiveness than SMA
* **Signal generation:** Crossovers between price and WMA generate trade signals earlier than with SMA
* **Support/resistance levels:** WMA can act as dynamic support during uptrends and resistance during downtrends
* **Moving average crossovers:** When a shorter-period WMA crosses above a longer-period WMA, it signals a potential uptrend (and vice versa)
* **Trend strength assessment:** Distance between price and WMA can indicate trend strength
## Limitations and Considerations
* **Market conditions:** Still suboptimal in highly volatile or sideways markets where enhanced responsiveness may generate false signals
* **Lag factor:** While less than SMA, still introduces some lag in signal generation
* **Abrupt window exit:** The oldest price suddenly drops out of calculation when leaving the window, potentially causing small jumps
* **Step changes:** Linear weighting creates discrete steps in influence rather than a smooth decay
* **Complementary tools:** Best used with volume indicators and momentum oscillators for confirmation
## References
* Colby, Robert W. "The Encyclopedia of Technical Market Indicators." McGraw-Hill, 2002
* Murphy, John J. "Technical Analysis of the Financial Markets." New York Institute of Finance, 1999
* Kaufman, Perry J. "Trading Systems and Methods." Wiley, 2013
Quantum Portfolio vs S&P 500 (Base: May 2, 2021)This script compares the performance of a custom Quantum Portfolio — a weighted basket of quantum computing, semiconductor, and cybersecurity stocks — against the S&P 500 Index, with both series rebased to 100 on May 2 2021.
It provides a clear, normalized view of cumulative returns, allowing you to visualize portfolio outperformance or underperformance relative to the broader market benchmark.
Auto Chart PatternsAuto Chart Patterns automatically scans the chart for major technical patterns and marks them directly on price action. It detects:
• Head & Shoulders (bearish reversal)
• Inverse Head & Shoulders (bullish reversal)
• Rising and Falling Wedges
• Double / Triple Tops and Bottoms
• Cup & Handle (bullish continuation)
For each pattern, the script draws the structure (trendlines / neckline), shades the pattern zone, and places a label with the pattern name.
It also generates optional trade signals:
• “BUY” when a bullish pattern breaks out with confirmation
• “SELL” when a bearish pattern breaks down with confirmation
Confirmations can include:
• Follow-through candle in the breakout direction
• Volume spike vs recent average
• RSI momentum agreement
Inputs let you control:
• Pivot sensitivity (left/right bars)
• Pattern types to display
• Cup & Handle depth rules
• Confirmation rules for entry/exit signals
This tool is designed to help you visually spot reversal and continuation setups, highlight potential breakout levels (necklines / wedge boundaries), and time trades with clearer confirmation instead of guessing.
Disclaimer: This script is for educational/technical analysis purposes only. It does not guarantee future performance, does not execute trades, and is not financial advice. Always confirm signals with your own analysis and risk management before entering any position.
Quantum Portfolio vs NASDAQ (Base: May 2, 2021)This custom Pine Script indicator tracks and compares the cumulative performance of a multi-asset “Quantum Portfolio” against the NASDAQ 100 benchmark, rebased to a common starting point on May 2, 2021.
Both series are normalized to a base value of 100 on that date, allowing direct visual comparison of percentage growth or decline over time.
Volume Profile Area [BigBeluga]🔵 OVERVIEW
The Volume Profile Area is an advanced profiling tool that calculates and visualizes the value area within a chosen period’s volume distribution. It first builds a main profile of the entire range, then constructs a secondary profile inside the defined value area, allowing traders to examine market balance and key trading zones in greater detail.
🔵 CONCEPTS
Volume Profile – Distributes traded volume across price levels to highlight areas of market activity.
Value Area (VA) – The price range containing a chosen percentage of total volume (commonly 50–70%).
Point of Control (PoC) – The price level with the highest traded volume, often acting as a magnet for price.
Nested Profiles – A profile inside the VA adds a second layer of precision, showing where liquidity clusters within the “fair value” zone.
🔵 FEATURES
Main Profile – Full distribution of volume over the selected lookback period.
Secondary Profile – Built only inside the VA of the main profile, highlighting intrabalance structure.
Customizable PoC Selection – Choose between showing the PoC of the
Main Profile ,
the Area Profile ,
their Average ,
or None .
Dynamic Value Area Levels – Automatically plots VAL (Value Area Low) and VAH (Value Area High) with labels.
Overlay Toggles – Show/hide range extremes, VA lines, or PoCs for a cleaner chart view.
Visual Profiles – Main profile shaded in darker blue; the VA profile inside is lighter for clear separation.
Automatic Scaling – Profiles adapt to period highs/lows and auto-adjust bins for consistent resolution.
Volume Labels – PoCs can display traded volume, giving numeric confirmation of liquidity concentration.
🔵 HOW TO USE
Set the Period to define how many bars to include in the main profile.
Adjust the Value Area % to control how much volume defines the VA (e.g., 50% by default).
Pick your PoC option: Main , Area , or Average , depending on focus.
Use VAH/VAL lines as support/resistance levels where most trading occurred.
Compare reactions at Main vs VA PoC levels to spot potential breakouts or mean reversions.
🔵 CONCLUSION
The Volume Profile Area extends traditional profiling by nesting a secondary VA profile inside the main distribution. This dual-layer approach reveals not just where the market was active overall, but where liquidity concentrated within the “fair value” zone—powerful for refining entries, exits, and risk placement across intraday and swing horizons.
Momentum Breakout Filter + ATR ZonesMomentum Breakout Filter + ATR Zones - User Guide
What This Indicator Does
This indicator helps you with your MACD + volume momentum strategy by:
Filtering out fake breakouts - Shows ⚠️ warnings when breakouts lack confirmation
Showing clear entry signals - 🚀 LONG and 🔻 SHORT labels when all conditions align
Automatic stop loss & profit targets - Based on ATR (Average True Range)
Visual trend confirmation - Background color + EMA alignment
Signal Types
🚀 LONG Entry Signal (Green Label)
Appears when ALL conditions met:
✅ MACD crosses above signal line
✅ Volume > 1.5× average
✅ Price > EMA 9 > EMA 21 > EMA 200 (bullish trend)
✅ Price closes above recent 20-bar high
🔻 SHORT Entry Signal (Red Label)
Appears when ALL conditions met:
✅ MACD crosses below signal line
✅ Volume > 1.5× average
✅ Price < EMA 9 < EMA 21 < EMA 200 (bearish trend)
✅ Price closes below recent 20-bar low
⚠️ FAKE Breakout Warning (Orange Label)
Appears when price breaks high/low BUT lacks confirmation:
❌ Low volume (below 1.5× average), OR
❌ Wick break only (didn't close through level), OR
❌ MACD not aligned with direction
Hover over the warning label to see what's missing!
ATR Stop Loss & Targets
When you get a signal, colored lines automatically appear:
Long Position
Red solid line = Stop Loss (Entry - 1.5×ATR)
Green dashed lines = Profit Targets:
Target 1: Entry + 2×ATR
Target 2: Entry + 3×ATR
Target 3: Entry + 4×ATR
Short Position
Red solid line = Stop Loss (Entry + 1.5×ATR)
Green dashed lines = Profit Targets:
Target 1: Entry - 2×ATR
Target 2: Entry - 3×ATR
Target 3: Entry - 4×ATR
The lines move with each bar until you exit the position.
Chart Elements
Moving Averages
Blue line = EMA 9 (fast)
Orange line = EMA 21 (medium)
White line = EMA 200 (trend filter)
Volume
Yellow bars = High volume (above threshold)
Gray bars = Normal volume
Background Color
Light green = Bullish trend (all EMAs aligned up)
Light red = Bearish trend (all EMAs aligned down)
No color = Neutral/mixed
MACD (Bottom Pane)
Green/Red columns = MACD Histogram
Blue line = MACD Line
Orange line = Signal Line
Info Dashboard (Bottom Right)
ItemWhat It ShowsVolumeCurrent volume vs average (✓ HIGH or ✗ Low)MACDDirection (BULLISH or BEARISH)TrendEMA alignment (BULL, BEAR, or NEUTRAL)ATRCurrent ATR value in dollarsPositionCurrent position (LONG, SHORT, or NONE)R:RRisk-to-Reward ratio (shows when in position)
How To Use It
Basic Workflow
Wait for setup
Watch for MACD to approach signal line
Volume should be building
Price should be near EMA structure
Get confirmation
Wait for 🚀 LONG or 🔻 SHORT label
Check dashboard shows "✓ HIGH" volume
Verify trend is aligned (green or red background)
Enter the trade
Enter when signal appears
Note your stop loss (red line)
Note your targets (green dashed lines)
Manage the trade
Exit at first target for partial profit
Move stop to breakeven
Trail remaining position
What To Avoid
❌ Don't trade when you see:
⚠️ FAKE labels (wait for confirmation)
Neutral background (no clear trend)
"✗ Low" volume in dashboard
MACD and Trend not aligned
Settings You Can Adjust
Volume Sensitivity
High Volume Threshold: Default 1.5×
Increase to 2.0× for cleaner signals (fewer trades)
Decrease to 1.2× for more signals (more trades)
Fake Breakout Filters
You can toggle these ON/OFF:
Volume Confirmation: Requires high volume
Close Through: Requires candle close, not just wick
MACD Alignment: Requires MACD direction match
Tip: Turn all three ON for highest quality signals
ATR Stop/Target Multipliers
Default settings (conservative):
Stop Loss: 1.5×ATR
Target 1: 2×ATR (1.33:1 R:R)
Target 2: 3×ATR (2:1 R:R)
Target 3: 4×ATR (2.67:1 R:R)
Aggressive traders might use:
Stop Loss: 1.0×ATR
Target 1: 2×ATR (2:1 R:R)
Target 2: 4×ATR (4:1 R:R)
Conservative traders might use:
Stop Loss: 2.0×ATR
Target 1: 3×ATR (1.5:1 R:R)
Target 2: 5×ATR (2.5:1 R:R)
Example Trade Scenarios
Scenario 1: Perfect Long Setup ✅
Stock consolidating near EMA 21
MACD curling up toward signal line
Volume bar turns yellow (high volume)
🚀 LONG label appears
Red stop line and green target lines appear
Result: High probability trade
Scenario 2: Fake Breakout Avoided ✅
Price breaks above resistance
Volume is normal (gray bar)
⚠️ FAKE label appears (hover shows "Low volume")
No entry signal
Price falls back below breakout level
Result: Avoided losing trade
Scenario 3: Premature Entry ❌
MACD crosses up
Volume is high
BUT trend is NEUTRAL (no background color)
No signal appears (trend filter blocks it)
Result: Avoided choppy/sideways market
Quick Reference
Entry Checklist
🚀 or 🔻 label on chart
Dashboard shows "✓ HIGH" volume
Dashboard shows aligned MACD + Trend
Colored background (green or red)
ATR lines visible
No ⚠️ FAKE warning
Exit Strategy
Target 1 (2×ATR): Take 50% profit, move stop to breakeven
Target 2 (3×ATR): Take 25% profit, trail stop
Target 3 (4×ATR): Take remaining profit or trail aggressively
Stop Loss: Exit entire position if hit
Alerts
Set up these alerts:
Long Entry: Fires when 🚀 LONG signal appears
Short Entry: Fires when 🔻 SHORT signal appears
Fake Breakout Warning: Fires when ⚠️ appears (optional)
Tips for Success
Use on 5-minute charts for day trading momentum plays
Only trade high volume stocks ($5-20 range works best)
Wait for full confirmation - don't jump early
Respect the stop loss - it's calculated based on volatility
Scale out at targets - don't hold for home runs
Avoid trading first 15 minutes - let market settle
Best during 10am-11am and 2pm-3pm - peak momentum times
Common Questions
Q: Why didn't I get a signal even though MACD crossed?
A: All conditions must be met - check dashboard for what's missing (likely volume or trend alignment)
Q: Can I use this on any timeframe?
A: Yes, but it's designed for 5-15 minute charts. On daily charts, adjust ATR multipliers higher.
Q: The stop loss seems too tight, can I widen it?
A: Yes, increase "Stop Loss (×ATR)" from 1.5 to 2.0 or 2.5 in settings.
Q: I keep seeing FAKE warnings but price keeps going - what gives?
A: The filter is conservative. You can disable some filters in settings, but expect more false signals.
Q: Can I use this for swing trading?
A: Yes, but use larger timeframes (1H or 4H) and adjust ATR multipliers up (3× for stops, 6-9× for targets).
Smart Money Concept: FVG Block Filter Smart Money Concept: FVG Block Filter (FVG Block Range vs N Range) with Candle Highlighter
Summary:
Smart Money Concept (SMC): An advanced indicator designed to visualize and filter Fair Value Gaps (FVG) blocks based on their size (Range) compared to the preceding N Range candle movement. It also includes a customizable Candle Highlighter function that marks the specific candle responsible for creating the FVG. The indicator allows full color customization for both blocks and the highlighter, and features clean, label-free charts by default.
Key Features:
FVG Block Detection: Automatically identifies and groups sequential FVG imbalances to form consolidated FVG blocks.
FVG Block Filtering (N Range): Filters blocks based on a user-defined rule, comparing the block's size (Range) to the range of the preceding N candles (e.g., requiring the FVG block to be larger than the range of the previous 6 candles).
Customizable Candle Highlighter: Marks the central candle (B) within the FVG structure (A-B-C) to highlight the source of the price imbalance. Highlighter colors are fully adjustable via inputs.
Visualization Control: Labels are turned OFF by default to keep the chart clean but can be easily enabled via the indicator settings.
Full Color Customization: Allows independent customization of Bullish and Bearish FVG Block colors, Block Transparency, and Bullish/Bearish Highlighter colors.
Keywords:
Smart Money Concept, SMC, Fair Value Gap, FVG, Imbalance, Block Filter, Candle Highlighter, Range.
WaveTrend RBF What it does
WT-RBF extracts a “wave” of momentum by subtracting a fast Gaussian-weighted smoother from a slow one, then robust-normalizes that wave with a median/MAD proxy to produce a z-score (z). A short EMA of z forms the signal line. Optional dynamic thresholds use the MAD of z itself so overbought/oversold levels adapt to volatility regimes.
How it’s built:
Radial (Gaussian) smoothers
Causal, exponentially-decaying weights over the last radius bars using σ (sigma) to control spread.
fast = rbf_smooth(src, fastR, fastSig)
slow = rbf_smooth(src, slowR, slowSig)
wave = fast − slow (band-pass)
Robust normalization
A two-stage EMA approximates the median; MAD is estimated from EMA of absolute deviations and scaled by 1.4826 to be stdev-comparable.
z = (wave − center) / MAD
Thresholds
Dynamic OB/OS: ±2.5 × MAD(z) (or fixed levels when disabled)
Reading the indicator
Bull Cross: z crosses above sig → momentum turning up.
Bear Cross: z crosses below sig → momentum turning down.
Exits / Bias flips: zero-line crosses (below 0 → exit long bias; above 0 → exit short bias).
Overbought/Oversold: z > +thrOB or z < thrOS. With dynamics on, the bands widen/narrow with recent noise; with dynamics off, static guides at ±2 / ±2.5 are shown.
Core Inputs
Source: Price series to analyze.
Fast Radius / Fast Sigma (defaults 6 / 2.5): Shorter radius/smaller σ = snappier, higher-freq.
Slow Radius / Slow Sigma (defaults 14 / 5.0): Larger radius/σ = smoother, lower-freq baseline.
Normalization
Robust Z-Score Window (default 200): Lookback for median/MAD proxy (stability vs responsiveness).
Small ε for MAD: Floor to avoid division by zero.
Signal & Thresholds
Dynamic Thresholds (MAD-based) (on by default): Adaptive OB/OS; toggle off to use fixed guides.
Visuals
Shade OB/OS Regions: Background highlights when z is beyond thresholds.
Show Zero Line: Midline reference.
(“Plot Cross Markers” input is present for future use.)
Rolling Performance Metrics TableRolling Performance Metrics Table
A clean, customizable table overlay that displays rolling performance metrics across multiple time periods. Perfect for quickly assessing price momentum and performance trends at a glance.
FEATURES:
- Displays performance across 5 time periods: 1 Week, 3 Month, 6 Month, 1 Year, and 2 Year
- Shows historical price at the start of each period
- Calculates both absolute price change and percentage change
- Color-coded results: Green for positive performance, Red for negative performance
- Fully transparent design with no background or borders - text floats cleanly over your chart
- Customizable table position (9 placement options)
DISPLAY COLUMNS:
1. Period - The lookback timeframe
2. Price - The historical price at the start of the period
3. Change (Value) - Absolute price change from the period start
4. Change (%) - Percentage return over the period
CUSTOMIZATION:
- Adjust the number of bars for each period (default: 1 Week = 5 bars, 3 Month = 63 bars, 6 Month = 126 bars, 1 Year = 252 bars, 2 Year = 504 bars)
- Choose from 9 table positions: Top, Middle, Bottom combined with Left, Center, Right
- Default position: Middle Left
USAGE:
Perfect for traders who want to quickly assess momentum across multiple timeframes. The transparent overlay design ensures minimal obstruction of chart analysis while providing critical performance data at a glance.
NOTE:
- The table only appears on the last bar of your chart
- Customize bar counts in settings to match your specific timeframe needs (e.g., daily vs hourly charts)
- "N/A" appears when historical data is insufficient for the selected period
Liquidity Sniper V3 (ANTI-FAKEOUT)An advanced institutional trading indicator combining liquidity pool targeting, smart money concepts, and momentum-based entries with comprehensive risk management.
🎯 CORE FEATURES:
- Liquidity Sniper Module: Identifies and targets major liquidity pools (PDH/PDL, PWH/PWL, Equal Highs/Lows, HVN/LVN edges)
- Anti-Fakeout Stack: 10-layer confirmation system including VWAP reclaim, micro BOS, displacement, relative volume, and mitigation entries
- Momentum Engulf Add-On: Catches high-velocity impulsive moves with engulfing candles, volume spikes, and volatility breakouts
- GARCH Volatility Filter: Dynamic volatility analysis to avoid choppy conditions
- Multi-Timeframe Confirmation: Ensures alignment across timeframes before entries
📊 SIGNAL CLASSIFICATION:
- BEST (Green): Highest probability setups with all confirmations aligned - 6.0+ score
- BETTER (Medium Green): Strong setups with most confirmations - 4.5-6.0 score
- GOOD (Light Green): Valid setups with basic confirmations - 3.0-4.5 score
🔍 TRADE SCENARIOS:
S1: Liquidity Reversal - Sweeps + reversals at key levels with displacement
S2: Continuation - Trend following with VWAP mean reversion
S3: Mean Reversion - Extreme deviations (2σ+) with Fibonacci exhaustion
S4: Deep Sweep - 3σ sweeps at major liquidity with high confluence
⚡ MOMENTUM TRIGGERS:
- MET (Momentum Engulf): Bullish/bearish engulfing with 1.5x+ volume spike and ATR impulse
- VBT (Volatility Breakout): Range breakouts with sigma bursts and participation
🛡️ RISK MANAGEMENT:
- Dynamic TP/SL based on ATR, VWAP bands, and liquidity pools
- 3-tier targets (T1: VWAP, T2: Nearest pool, T3: 5R extension)
- Early invalidation tracking (0.5R movement monitoring)
- Minimum 2:1 RR requirement with cooldown periods
- RTH session filters and anti-spam protection
📈 TECHNICAL EDGE:
- SMT Divergence detection vs ES correlation
- CVD (Cumulative Volume Delta) divergence confirmation
- FVG (Fair Value Gap) and Order Block mitigation entries
- Equal highs/lows clustering analysis
- Volume profile HVN/LVN identification
⚙️ FULLY CUSTOMIZABLE:
All parameters adjustable including cooldowns, proximity thresholds, ATR multipliers, RR floors, and scenario weights.
Perfect for: ES/NQ futures, forex majors, and liquid stocks. Works on 1-15 min timeframes. Best results during NY session (9:35-11:00 AM & 1:30-3:30 PM ET).
Created for serious traders seeking institutional-grade edge with quantifiable risk/reward and high-probability setups
