Sladkaya Bulochka PosledovatelnostiSerial number of the same color candles - a popular method of how to find the exact entry zones and determine the trends and kickbacks.
The number of consecutive candles usually starts from 3 and up to 12 in some strategies.
5 candles in sequence - one of the most popular signals. Login at the close of the 5th candle.
---------------------------------------------
Последовательное число свечей одинакового цвета - популярный метод как поиска точных зон входа, так и определения трендов и откатов.
Число последовательных свечей, как правило, начинается с 3 и доходит до 12 в некоторых стратегиях.
5 свечей в последовательности - один из наиболее популярных сигналов. Вход на закрытии 5й свечи.
Cari skrip untuk "12月4号是什么星座"
MACD trend heatmap (by ChartArt)This is an overlay indicator which uses the classic period settings and signals from the MACD (Moving Average Convergence/Divergence) indicator to overlay a heatmap using all the information the MACD generates with its three periods (12,26,9).
The first two moving averages which the MACD uses (12 and 26) can be plotted on the chart like usual EMAs.
In addition to the background color function (the heatmap) and the EMAs, there is an optional bar color alert when the uptrend or the downtrend as measured by the MACD appears to be very strong.
Stoch_VX2Nothing New about a Stochastic but maybe in how you use them ( Other than Over bought / Sold cross over & divergence signals )
Running 3 bands
Standard stoch & tops & bottoms swing band
Optimised variables 12, 5 , 3 or fib 13, 5, 3 / - 12 / 3 / 3 a little bit tighter to combine both smoothness & accuracy. These are my own personal setting inc. Strategy.
MACD Color Trawler (by ChartArt)This version of the MACD indicator is 'trawling' (checking) if the MACD histogram and the zero line crossing with the MACD line are both positive or negative. The idea behind this is to show areas with higher or lower risk.
Features:
1. Enable the bar color
2. Enable the background color
3. Change zero line value
FYI:
"The MACD-Histogram is an indicator of an indicator. In fact, MACD is also an indicator of an indicator. This means that the MACD-Histogram is the fourth derivative of price."
First derivative: 12-day EMA and 26-day EMA
Second derivative: MACD (12-day EMA less the 26-day EMA)
Third derivative: MACD signal line (9-day EMA of MACD)
Fourth derivative: MACD-Histogram (MACD less MACD signal line)
Source: stockcharts.com
Price Channel Breakout Strategy — Long & ShortThis strategy is a dual-direction Price Channel breakout system designed for high-volatility indices such as US30, NAS100, and XAUUSD.
It enters long when price breaks above the highest high of the past N bars, and enters short when price breaks below the lowest low.
A key feature is the use of fixed dollar-based take-profit and stop-loss, making the strategy adaptive across symbols with different tick values.
Core Logic
Long entry when price breaks the N-bar high
Short entry when price breaks the N-bar low
Dollar-based TP and SL (converted to ticks automatically)
Suitable for trending and breakout-friendly markets
Backtest Notes (US30 Example)
Sharpe Ratio: 2.7
Profit Factor: 2.111
Total Return (12-month backtest): +46.89%
Max Drawdown: 0.26%
Trades: 3,666
This strategy performs well in sustained volatility environments and is particularly effective for intraday momentum bursts on US30.
Hash SupertrendHash Supertrend is a visually enhanced Supertrend-based indicator designed by Hash Capital Research, tuned specifically for crypto trend trading on Solana (SOL) and Bitcoin (BTC). It combines institutional-style color coding, an optional session time filter, and production-ready alerts for systematic and discretionary traders alike.
What This Indicator Is
Hash Supertrend is a trend-following volatility band indicator built on TradingView’s native ta.supertrend() function.
It’s optimized and visually styled for:
High-volatility crypto pairs (especially SOL/USDT, SOL/USD, BTC/USDT, BTC/USD)
Timeframes typically used by crypto traders (from 5m scalping to 4H swing and 1D trend following)
The script is an indicator, not a strategy:
It does not place trades or show backtest results.
It provides clear trend states, flips, and alerts that you can plug into your own execution stack or manual trading.
Key Features
✅ Tuned for Crypto (Solana & Bitcoin)
Parameters are chosen to respond well to the volatility profile of SOL and BTC, reducing noise while still catching strong moves.
✅ Non-repainting Supertrend Core
Uses TradingView’s built-in ta.supertrend — values may move intrabar as the bar forms, but once a bar closes, the historical line and signals do not repaint.
✅ Fluorescent Trend Visualization
Bright green for bullish phases
Bright red for bearish phases
Adaptive color intensity based on user setting
✅ Glow Layer & Trend Zones
Glow effect around the Supertrend line for instant visual recognition
Optional filled zones between price and line for “trend cloud” style visualization
✅ Time Filter (Session Control)
Option to only mark signals during specific hours for those wanting to integrate with webhooks
Designed for traders who avoid certain sessions (e.g., low-liquidity hours)
✅ Signal Dots & Alerts
Tiny green dots for bullish flips
Tiny red dots for bearish flips
Professional, preconfigured alerts for:
Long Entry
Short Entry
Any Trend Change
Filtered signals outside trading hours (for monitoring only)
The core logic is built on:
ATR Length (ATR Length) Default: 16
Lower values (7–10): more sensitive, more signals, more noise
Higher values (12–20): smoother, fewer but stronger trend signals
Factor (Factor) Default: 3.11
Lower values (1.5–2.5): tighter bands, earlier entries, higher whipsaws
Higher values (3.0–4.0+): wider bands, later entries, stronger trend confirmation
The indicator reads direction from ta.supertrend and classifies:
Bullish Trend: direction < 0
Bearish Trend: direction > 0
A trend flip happens when direction changes sign:
longSignal: Supertrend flips from above price to below price (bearish → bullish)
shortSignal: Supertrend flips from below price to above price (bullish → bearish)
Buffett Quality Filter (TTM)//@version=6
indicator("Buffett Quality Filter (TTM)", overlay = true, max_labels_count = 500)
// 1. Get financial data (TTM / FY / FQ)
// EPS (TTM) for P/E
eps = request.financial(syminfo.tickerid, "EARNINGS_PER_SHARE_BASIC", "TTM")
// Profitability & moat (annual stats)
roe = request.financial(syminfo.tickerid, "RETURN_ON_EQUITY", "FY")
roic = request.financial(syminfo.tickerid, "RETURN_ON_INVESTED_CAPITAL", "FY")
// Margins (TTM – rolling 12 months)
grossMargin = request.financial(syminfo.tickerid, "GROSS_MARGIN", "TTM")
netMargin = request.financial(syminfo.tickerid, "NET_MARGIN", "TTM")
// Balance sheet safety (quarterly)
deRatio = request.financial(syminfo.tickerid, "DEBT_TO_EQUITY", "FQ")
currentRat = request.financial(syminfo.tickerid, "CURRENT_RATIO", "FQ")
// Growth (1-year change, TTM)
epsGrowth1Y = request.financial(syminfo.tickerid, "EARNINGS_PER_SHARE_BASIC_ONE_YEAR_GROWTH", "TTM")
revGrowth1Y = request.financial(syminfo.tickerid, "REVENUE_ONE_YEAR_GROWTH", "TTM")
// Free cash flow (TTM) and shares to build FCF per share for P/FCF
fcf = request.financial(syminfo.tickerid, "FREE_CASH_FLOW", "TTM")
sharesOut = request.financial(syminfo.tickerid, "TOTAL_SHARES_OUTSTANDING", "FQ")
fcfPerShare = (not na(fcf) and not na(sharesOut) and sharesOut != 0) ? fcf / sharesOut : na
// 2. Valuation ratios from price
pe = (not na(eps) and eps != 0) ? close / eps : na
pFcf = (not na(fcfPerShare) and fcfPerShare > 0) ? close / fcfPerShare : na
// 3. Thresholds (Buffett-style, adjustable)
minROE = input.float(15.0, "Min ROE %")
minROIC = input.float(12.0, "Min ROIC %")
minGM = input.float(30.0, "Min Gross Margin %")
minNM = input.float(8.0, "Min Net Margin %")
maxDE = input.float(0.7, "Max Debt / Equity")
minCurr = input.float(1.3, "Min Current Ratio")
minEPSG = input.float(8.0, "Min EPS Growth 1Y %")
minREVG = input.float(5.0, "Min Revenue Growth 1Y %")
maxPE = input.float(20.0, "Max P/E")
maxPFCF = input.float(20.0, "Max P/FCF")
// 4. Individual conditions
cROE = not na(roe) and roe > minROE
cROIC = not na(roic) and roic > minROIC
cGM = not na(grossMargin) and grossMargin > minGM
cNM = not na(netMargin) and netMargin > minNM
cDE = not na(deRatio) and deRatio < maxDE
cCurr = not na(currentRat) and currentRat > minCurr
cEPSG = not na(epsGrowth1Y) and epsGrowth1Y > minEPSG
cREVG = not na(revGrowth1Y) and revGrowth1Y > minREVG
cPE = not na(pe) and pe < maxPE
cPFCF = not na(pFcf) and pFcf < maxPFCF
// 5. Composite “Buffett Score” (0–10) – keep it on ONE line to avoid line-continuation errors
score = (cROE ? 1 : 0) + (cROIC ? 1 : 0) + (cGM ? 1 : 0) + (cNM ? 1 : 0) + (cDE ? 1 : 0) + (cCurr ? 1 : 0) + (cEPSG ? 1 : 0) + (cREVG ? 1 : 0) + (cPE ? 1 : 0) + (cPFCF ? 1 : 0)
// Strictness
minScoreForPass = input.int(7, "Min score to pass (0–10)", minval = 1, maxval = 10)
passes = score >= minScoreForPass
// 6. Visuals
bgcolor(passes ? color.new(color.green, 80) : na)
plot(score, "Buffett Score (0–10)", color = color.new(color.blue, 0))
// Info label on last bar
var label infoLabel = na
if barstate.islast
if not na(infoLabel)
label.delete(infoLabel)
infoText = str.format(
"Buffett score: {0}\nROE: {1,number,#.0}% | ROIC: {2,number,#.0}%\nGM: {3,number,#.0}% | NM: {4,number,#.0}%\nP/E: {5,number,#.0} | P/FCF: {6,number,#.0}\nD/E: {7,number,#.00} | Curr: {8,number,#.00}",
score, roe, roic, grossMargin, netMargin, pe, pFcf, deRatio, currentRat)
infoLabel := label.new(bar_index, high, infoText,
style = label.style_label_right,
color = color.new(color.black, 0),
textcolor = color.white,
size = size.small)
Reversal_Detector//@version=6
indicator("상승 반전 탐지기 (Reversal Detector)", overlay=true)
// ==========================================
// 1. 설정 (Inputs)
// ==========================================
rsiLen = input.int(14, title="RSI 길이")
lbR = input.int(5, title="다이버전스 확인 범위 (오른쪽)")
lbL = input.int(5, title="다이버전스 확인 범위 (왼쪽)")
rangeUpper = input.int(60, title="RSI 과매수 기준")
rangeLower = input.int(30, title="RSI 과매도 기준")
// ==========================================
// 2. RSI 상승 다이버전스 계산 (핵심 로직)
// ==========================================
osc = ta.rsi(close, rsiLen)
// 피벗 로우(Pivot Low) 찾기: 주가의 저점
plFound = na(ta.pivotlow(osc, lbL, lbR)) ? false : true
// 다이버전스 조건 확인
// 1) 현재 RSI 저점이 이전 RSI 저점보다 높아야 함 (상승)
// 2) 현재 주가 저점이 이전 주가 저점보다 낮아야 함 (하락)
showBull = false
if plFound
// 이전 피벗 지점 찾기
oscLow = osc
priceLow = low
// 과거 데이터를 탐색하여 직전 저점과 비교
for i = 1 to 60
if not na(ta.pivotlow(osc, lbL, lbR) ) // 이전에 저점이 있었다면
prevOscLow = osc
prevPriceLow = low
// 다이버전스 조건: 가격은 더 떨어졌는데(Lower Low), RSI는 올랐을 때(Higher Low)
if priceLow < prevPriceLow and oscLow > prevOscLow and oscLow < rangeLower
showBull := true
break // 하나 찾으면 루프 종료
// ==========================================
// 3. 보조 조건 (MACD 골든크로스 & 이평선)
// ==========================================
= ta.macd(close, 12, 26, 9)
macdCross = ta.crossover(macdLine, signalLine) // MACD 골든크로스
ma5 = ta.sma(close, 5)
ma20 = ta.sma(close, 20)
maCross = ta.crossover(ma5, ma20) // 5일선이 20일선 돌파
// ==========================================
// 4. 시각화 (Plotting)
// ==========================================
// 1) 상승 다이버전스 발생 시 (강력한 바닥 신호)
plotshape(showBull,
title="상승 다이버전스",
style=shape.labelup,
location=location.belowbar,
color=color.red,
textcolor=color.white,
text="Bull Div\n(바닥신호)",
size=size.small,
offset=-lbR) // 과거 시점에 표시
// 2) MACD 골든크로스 (추세 확인용)
plotshape(macdCross and macdLine < 0, // 0선 아래에서 골든크로스 날 때만
title="MACD 골든크로스",
style=shape.triangleup,
location=location.belowbar,
color=color.yellow,
size=size.tiny,
text="MACD")
// 3) 이동평균선
plot(ma5, color=color.blue, title="5일선")
plot(ma20, color=color.orange, title="20일선")
// 알림 설정
alertcondition(showBull, title="상승 다이버전스 포착", message="상승 다이버전스 발생! 추세 반전 가능성")
MACD Momentum Structure & Volume Profile Sniper [MTF]**Description and Methodology**
This script offers a unique approach to Market Structure by moving away from traditional fractal-based highs and lows (which can be noisy). Instead, it utilizes **MACD Momentum Swings** to identify significant structural points, combined with an automated Fixed Range Volume Profile to pinpoint high-probability entry zones.
**1. Why MACD Structure? (The Core Concept)**
Traditional "ZigZag" or Fractal indicators rely solely on price action, often leading to fake-outs during low-volume consolidation.
* This script defines a "Swing High" only when the MACD Histogram crosses below zero (Momentum shifts Bearish).
* This script defines a "Swing Low" only when MACD crosses above zero (Momentum shifts Bullish).
By linking structure to momentum, we filter out weak price movements and focus on the true "heartbeat" of the trend.
**2. The "Mashup" Synergy: Structure + Volume + Logic**
This is not a random combination of indicators. Each component serves a specific step in the trading execution sequence:
* **Step 1 (Structure):** The script identifies a Change of Character (CHoCH) based on the MACD peaks described above.
* **Step 2 (Liquidity/Value):** When a CHoCH occurs, the script *automatically* draws a **Fixed Range Volume Profile (FRVP)** specifically covering the impulse leg that caused the break. This reveals the "Point of Control" (POC)—the hidden price level where the most volume occurred during the move.
* **Step 3 (The Sniper Entry):** The script creates a "Zone" around that POC. It then waits for Price to retrace into this zone.
* **Step 4 (Confirmation):** Once the zone is touched, the script monitors a lower timeframe (User selectable, default M1) for a fresh MACD crossover to trigger the final entry signal.
**Features**
* **Multi-Timeframe Dashboard:** Monitor the MACD Trend direction across 4 different timeframes simultaneously.
* **Dynamic Trendlines:** Automatically connects confirmed MACD peaks to visualize trend integrity.
* **Fibo Time Zones:** Projects potential future pivot points based on the duration of the previous swing.
* **Alert System:** Integrated alerts for Zone Touches and "Sniper" entries (Zone Touch + LTF Momentum Confirmation).
**How to Use**
1. **Identify Trend:** Look for the CHoCH labels. Green indicates a shift to Bullish, Red to Bearish.
2. **Wait for Pullback:** Do not chase the break. Wait for price to return to the Yellow POC Zone generated by the Volume Profile.
3. **Entry Trigger:** Watch for the "BUY" or "SELL" marks. These appear only when price hits the zone AND the lower-timeframe momentum aligns with the trade direction.
**Settings & Inputs**
* **Global MACD:** Adjust the sensitivity of the swing detection (Default 12, 26, 9).
* **Sniper Entry:** Select the timeframe used for the final confirmation (e.g., use M1 confirmation for an H1 chart structure).
* **VP Settings:** Customize how the Volume Profile looks on the chart.
*Disclaimer: This script is intended for educational purposes and market analysis. It does not provide financial advice.*
Grok/Claude Quantum Signal Pro * Enhanced v2# QSig Pro+ v2 — Dynamic RSI Enhancement
## Release: Quantum Signal Pro Enhanced v2
**Author:** ralis24 (with Claude assistance)
**Version:** 2.0
**Platform:** TradingView (Pine Script v6)
---
## Overview
Version 2 introduces **Trend-Adaptive RSI Thresholds** — a significant enhancement that dynamically adjusts buy and sell levels based on real-time trend strength. This allows the indicator to more effectively capture dips in uptrends and sell bounces in downtrends, rather than waiting for extreme oversold/overbought conditions that rarely occur during strong directional moves.
---
## The Problem v2 Solves
In the original QSig Pro+, RSI thresholds were fixed at 30 (oversold) and 70 (overbought). While these levels work well in ranging markets, they create issues in trending conditions:
- **Strong Uptrends:** Price rarely drops to RSI 30. Pullbacks typically bottom around RSI 40-50, causing missed buy opportunities.
- **Strong Downtrends:** Relief rallies rarely push RSI above 70. Bounces often exhaust around RSI 55-65, causing missed sell opportunities.
The v2 solution: **Let the market's trend strength dictate the appropriate RSI levels.**
---
## New Feature: Dynamic RSI Thresholds
### How It Works
The indicator now detects three distinct market states and applies corresponding RSI thresholds:
| Market State | Detection Criteria | RSI Buy Level | RSI Sell Level |
|--------------|-------------------|---------------|----------------|
| **Strong Uptrend** | +DI > -DI, ADX > 24, ADX rising | < 40 | > 80 |
| **Strong Downtrend** | -DI > +DI, ADX > 24, ADX rising | < 20 | > 60 |
| **Neutral/Ranging** | ADX < 24 or ADX falling | < 30 | > 70 |
### Trend State Detection Logic
```
Strong Uptrend = (+DI > -DI) AND (ADX > threshold) AND (ADX > ADX )
Strong Downtrend = (-DI > +DI) AND (ADX > threshold) AND (ADX > ADX )
Neutral = Neither condition met
```
### Anti-Whipsaw Protection
To prevent rapid switching between threshold sets during choppy transitions, a **confirmation buffer** requires the trend state to persist for a configurable number of bars (default: 2) before the indicator switches regimes.
---
## New Input Parameters
A new input group "**Dynamic RSI Thresholds**" has been added with the following settings:
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Enable Trend-Adaptive RSI Levels | ON | toggle | Master switch for the feature |
| ADX Strong Trend Threshold | 24 | 15-40 | ADX must exceed this to qualify as "strong" trend |
| ADX Rising Lookback (bars) | 3 | 1-10 | ADX must be higher than N bars ago to confirm rising |
| Trend Confirmation Bars | 2 | 1-5 | Bars trend must persist before switching thresholds |
| RSI Buy Level (Strong Uptrend) | 40 | 30-55 | Oversold threshold during confirmed uptrends |
| RSI Sell Level (Strong Uptrend) | 80 | 70-90 | Overbought threshold during confirmed uptrends |
| RSI Buy Level (Strong Downtrend) | 20 | 10-30 | Oversold threshold during confirmed downtrends |
| RSI Sell Level (Strong Downtrend) | 60 | 50-70 | Overbought threshold during confirmed downtrends |
| RSI Buy Level (Neutral/Ranging) | 30 | 20-40 | Standard oversold threshold |
| RSI Sell Level (Neutral/Ranging) | 70 | 60-80 | Standard overbought threshold |
---
## Enhanced Info Panel
The information panel now displays two new rows:
1. **Trend State** — Shows current regime: "STRONG UP" (green), "STRONG DOWN" (red), or "NEUTRAL" (gray)
2. **RSI Levels** — Displays the currently active thresholds (e.g., "40 / 80" during uptrends)
Additionally, the **ADX row** now includes a directional arrow (↑ or ↓) indicating whether ADX is rising or falling.
---
## Enhanced Signal Labels
Buy and sell labels on the chart now include contextual information:
**Before (v1):**
```
BUY: 97,234.50
```
**After (v2):**
```
BUY: 97,234.50
STRONG UP | RSI<40
```
This provides immediate visual confirmation of which threshold regime triggered the signal.
---
## Enhanced Alert System
### New Alert Conditions
Three new alerts have been added for trend state changes:
- **🔼 Strong Uptrend Started** — Fires when market transitions to strong uptrend (thresholds shift to 40/80)
- **🔽 Strong Downtrend Started** — Fires when market transitions to strong downtrend (thresholds shift to 20/60)
- **⚖️ Trend Neutralized** — Fires when trend weakens and thresholds reset to 30/70
### Enhanced Webhook JSON
The JSON alert payload now includes additional fields for bot integration:
```json
{
"action": "BUY",
"symbol": "BTC/USDT",
"price": "97234.50",
"rsi": "38.5",
"rsi_threshold": "40",
"adx": "28.3",
"fisher": "-1.87",
"trend_state": "STRONG UP"
}
```
---
## Bonus Enhancement: Dynamic Fisher Thresholds
As an additional refinement, the Fisher Transform thresholds now adjust slightly based on trend state:
| Trend State | Fisher Buy Level | Fisher Sell Level |
|-------------|------------------|-------------------|
| Strong Uptrend | -1.5 (loosened) | -2.0 (standard) |
| Strong Downtrend | -2.0 (standard) | +1.5 (loosened) |
| Neutral | -2.0 (standard) | +2.0 (standard) |
This allows the indicator to trigger signals in strong trends where momentum oscillators rarely reach extreme levels.
---
## Practical Trading Impact
### Strong Uptrend Example (BTC rally)
- **Before:** Waiting for RSI < 30 means missing most pullback entries
- **After:** RSI < 40 triggers buy signals on normal pullbacks within the trend
### Strong Downtrend Example (Bear market bounce)
- **Before:** Waiting for RSI > 70 means holding through entire relief rallies
- **After:** RSI > 60 triggers sell signals on bounce exhaustion
### Ranging Market
- Thresholds remain at traditional 30/70 levels where mean reversion works best
---
## Backward Compatibility
The dynamic RSI feature can be completely disabled by turning off "Enable Trend-Adaptive RSI Levels" in the settings. When disabled, the indicator behaves identically to v1 using the neutral threshold values (30/70).
---
## Summary of Changes
| Component | v1 | v2 |
|-----------|----|----|
| RSI Thresholds | Fixed 30/70 | Dynamic based on trend state |
| Trend State Detection | Not present | +DI/-DI + ADX + Rising confirmation |
| Whipsaw Protection | Not present | Configurable confirmation bars |
| Info Panel Rows | 10 | 12 (added Trend State, RSI Levels) |
| ADX Display | Value only | Value + direction arrow |
| Signal Labels | Price only | Price + Trend State + Threshold |
| Alert Conditions | 10 | 13 (added 3 trend state alerts) |
| Webhook Fields | 5 | 7 (added rsi_threshold, trend_state) |
| Fisher Thresholds | Fixed | Adaptive (subtle adjustment) |
---
## Recommended Settings by Market Type
### Crypto (High Volatility)
- ADX Strong Trend Threshold: 24
- RSI Buy (Uptrend): 40-45
- RSI Sell (Downtrend): 55-60
### Forex (Medium Volatility)
- ADX Strong Trend Threshold: 22
- RSI Buy (Uptrend): 38-42
- RSI Sell (Downtrend): 58-62
### Stocks/Indices (Lower Volatility)
- ADX Strong Trend Threshold: 20
- RSI Buy (Uptrend): 35-40
- RSI Sell (Downtrend): 60-65
---
## Installation
1. Open TradingView and navigate to Pine Editor
2. Remove or rename existing QSig Pro+ indicator
3. Paste the complete v2 code
4. Click "Add to Chart"
5. Configure Dynamic RSI Thresholds in settings as desired
---
*QSig Pro+ v2 — Smarter entries through trend-aware signal generation*
Real Relative Strength Indicator### What is RRS (Real Relative Strength)?
RRS is a volatility-normalized relative strength indicator that shows you – in real time – whether your stock, crypto, or any asset is genuinely beating or lagging the broader market after adjusting for risk and volatility. Unlike the classic “price ÷ SPY” line that gets completely fooled by volatility regimes, RRS answers the only question that actually matters to professional traders:
“Is this ticker moving better (or worse) than the market on a risk-adjusted basis right now?”
It does this by measuring the excess momentum of your ticker versus a benchmark (SPY, QQQ, BTC, etc.) and then dividing that excess by the average volatility (ATR) of both instruments. The result is a clean, centered-around-zero oscillator that works the same way in calm markets, crash markets, or parabolic bull runs.
### How to Use the RRS Indicator (Aqua/Purple Area Version) in Practice
The indicator is deliberately simple to read once you know the rules:
Positive area (aqua) means genuine outperformance.
Negative area (purple) means genuine underperformance.
The farther from zero, the stronger the leadership or weakness.
#### Core Signals and How to Trade Them
- RRS crossing above zero → one of the highest-probability long signals in existence. The asset has just started outperforming the market on a risk-adjusted basis. Enter or add aggressively if price structure agrees.
- RRS crossing below zero → leadership is ending. Tighten stops, take partial or full profits, or flip short if you trade both sides.
- RRS above +2 (bright aqua area) → clear leadership. This is where the real money is made in bull markets. Trail stops, add on pullbacks, let winners run.
- RRS below –2 (bright purple area) → clear distribution or capitulation. Avoid new longs, consider short entries or protective puts.
- Extreme readings above +4 or below –4 (background tint appears) → rare, very high-conviction moves. Treat these like once-a-month opportunities.
- Divergence (not plotted here, but easy to spot visually): price making new highs while the aqua area is shrinking → distribution. Price making new lows while the purple area is shrinking → hidden buying and coming reversal.
#### Best Settings by Style and Asset Class
For stocks and ETFs: keep benchmark as SPY (or QQQ for tech-heavy names) and length 14–20 on daily/4H charts.
For crypto: change the benchmark to BTCUSD (or ETHUSD) immediately — otherwise the reading is meaningless. Length 10–14 works best on 1H–4H crypto charts because volatility is higher.
For day trading: drop length to 10–12 and use 15-minute or 5-minute charts. Signals are faster and still extremely clean.
#### Highest-Edge Setups (What Actually Prints Money)
- RRS crosses above zero while price is still below a major moving average (50 EMA, 200 SMA, etc.) → early leadership, often catches the exact bottom of a new leg up.
- RRS already deep aqua (+3 or higher) and price pulls back to support without RRS dropping below +1 → textbook add-on or re-entry zone.
- RRS deep purple and suddenly turns flat or starts curling up while price is still falling → hidden accumulation, usually the exact low tick.
That’s it. Master these few rules and the RRS becomes one of the most powerful edge tools you will ever use for rotation trading...
MACD Forecast Colorful [DiFlip]MACD Forecast Colorful
The Future of Predictive MACD — is one of the most advanced and customizable MACD indicators ever published on TradingView. Built on the classic MACD foundation, this upgraded version integrates statistical forecasting through linear regression to anticipate future movements — not just react to the past.
With a total of 22 fully configurable long and short entry conditions, visual enhancements, and full automation support, this indicator is designed for serious traders seeking an analytical edge.
⯁ Real-Time MACD Forecasting
For the first time, a public MACD script combines the classic structure of MACD with predictive analytics powered by linear regression. Instead of simply responding to current values, this tool projects the MACD line, signal line, and histogram n bars into the future, allowing you to trade with foresight rather than hindsight.
⯁ Fully Customizable
This indicator is built for flexibility. It includes 22 entry conditions, all of which are fully configurable. Each condition can be turned on/off, chained using AND/OR logic, and adapted to your trading model.
Whether you're building a rules-based quant system, automating alerts, or refining discretionary signals, MACD Forecast Colorful gives you full control over how signals are generated, displayed, and triggered.
⯁ With MACD Forecast Colorful, you can:
• Detect MACD crossovers before they happen.
• Anticipate trend reversals with greater precision.
• React earlier than traditional indicators.
• Gain a powerful edge in both discretionary and automated strategies.
• This isn’t just smarter MACD — it’s predictive momentum intelligence.
⯁ Scientifically Powered by Linear Regression
MACD Forecast Colorful is the first public MACD indicator to apply least-squares predictive modeling to MACD behavior — effectively introducing machine learning logic into a time-tested tool.
It uses statistical regression to analyze historical behavior of the MACD and project future trajectories. The result is a forward-shifted MACD forecast that can detect upcoming crossovers and divergences before they appear on the chart.
⯁ Linear Regression: Technical Foundation
Linear regression is a statistical method that models the relationship between a dependent variable (y) and one or more independent variables (x). The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted variable (e.g., future MACD value)
x = independent variable (e.g., bar index)
β₀ = intercept
β₁ = slope
ε = random error (residual)
The regression model calculates β₀ and β₁ using the least squares method, minimizing the sum of squared prediction errors to produce the best-fit line through historical values. This line is then extended forward, generating a forecast based on recent price momentum.
⯁ Least Squares Estimation
The regression coefficients are computed with the following formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Regression in Machine Learning
Linear regression is a foundational model in supervised learning. Its ability to provide precise, explainable, and fast forecasts makes it critical in AI systems and quantitative analysis.
Applying linear regression to MACD forecasting is the equivalent of injecting artificial intelligence into one of the most widely used momentum tools in trading.
⯁ Visual Interpretation
Picture the MACD values over time like this:
Time →
MACD →
A regression line is fitted to recent MACD values, then projected forward n periods. The result is a predictive trajectory that can cross over the real MACD or signal line — offering an early-warning system for trend shifts and momentum changes.
The indicator plots both current MACD and forecasted MACD, allowing you to visually compare short-term future behavior against historical movement.
⯁ Scientific Concepts Used
Linear Regression: models the relationship between variables using a straight line.
Least Squares Method: minimizes squared prediction errors for best-fit.
Time-Series Forecasting: projects future data based on past patterns.
Supervised Learning: predictive modeling using labeled inputs.
Statistical Smoothing: filters noise to highlight trends.
⯁ Why This Indicator Is Revolutionary
First open-source MACD with real-time predictive modeling.
Scientifically grounded with linear regression logic.
Automatable through TradingView alerts and bots.
Smart signal generation using forecasted crossovers.
Highly customizable with 22 buy/sell conditions.
Enhanced visuals with background (bgcolor) and area fill (fill) support.
This isn’t just an update — it’s the next evolution of MACD forecasting.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the MACD?
The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram.
⯁ How to use the MACD?
The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line.
Here are the primary signals generated by the MACD:
• Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal.
• Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal.
• Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal.
• Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI.
⯁ How to use MACD forecast?
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
📈 BUY
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
📉 SELL
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
🤖 Automation
All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Titan AI: EWO Pro + Divergencias de VolumenBINANCE:BTCUSDT.P The indicator is only in Spanish.
Titan AI: EWO Pro is not your standard Elliott Wave Oscillator. It is a next-generation Order Flow & Volume engine designed to detect the true intent of the market. Unlike traditional oscillators that rely solely on price action, Titan EWO Pro incorporates a "Volume Efficiency" algorithm normalized via Z-Score (Standard Deviation).
This indicator is built for traders who need to see what is happening inside the candles. It answers the critical question: "Is the price moving with real institutional backing, or is it a fake-out with no volume?"
With the integrated "GOD MODE" Dashboard, you get a tactical Heads-Up Display (HUD) that translates complex mathematical data into clear, actionable signals in real-time.
💎 Key Features
Z-Score Normalized EWO:
Standard EWO indicators can vary wildly depending on the asset price (BTC vs. Forex).
Titan EWO Pro normalizes the data using Standard Deviations (Z-Score). This means a value of +2.0 represents a statistically significant extreme move, regardless of the timeframe or asset.
Volume Efficiency Algorithm:
The core calculation measures (Close - Open) / Volume. This determines how much volume was required to move the price.
High efficiency means price is moving easily (strong trend). Low efficiency means high volume but little movement (absorption/reversal).
Volume Divergences:
Automatically detects discrepancies between Price Action and Order Flow.
Bullish Divergence: Price makes a Lower Low, but Titan EWO makes a Higher Low (Accumulation).
Bearish Divergence: Price makes a Higher High, but Titan EWO makes a Lower High (Distribution).
Institutional Extremes (Reversals):
The indicator marks the +2.0 and -2.0 Standard Deviation levels.
When the histogram crosses these levels, the market is statistically overextended. Watch for Triangle Signals indicating a potential "V" reversal or exhaustion.
GOD MODE Dashboard (HUD):
A professional panel fixed to your screen (customizable position).
Trend: Displays strict Bullish (Green) or Bearish (Red) status.
Strength (Z): The exact Z-Score value.
Momentum: Tells you if the move is "Accelerating" or "Braking" (Decelerating).
Divergence: Real-time alert status.
🚀 How to Use
1. Trend Following (The Wave)
Green Bars: Look for Longs. Momentum is bullish and Order Flow supports the move.
Red Bars: Look for Shorts. Momentum is bearish.
Darker Colors: If the bars turn dark green or dark red, momentum is slowing down (Deceleration). This is a warning to tighten Stop Losses or wait for a new impulse.
2. Trading Reversals (The Extremes)
Statistical Extremes: If the histogram punches through the +2.0 or -2.0 dotted lines, the move is overextended (climax).
Triangles: Small triangles appear at the top/bottom of the chart when these extremes are hit. This is often a "Take Profit" signal or a contrarian entry point if confirmed by price action.
3. Divergences (The Smart Entry)
Look for the "Vol" circles.
A Green Circle at the bottom indicates that sellers are exhausted, but volume flow is shifting bullish.
A Red Circle at the top indicates that buyers are exhausted (price up, but volume flow down).
4. The Dashboard
Use the dashboard for confirmation.
Ideally: You want "ALCISTA" (Bullish), "ACELERANDO" (Accelerating), and a high Z-Score (> 0.5) for a strong Long trade.
⚙️ Settings
EWO Length: The lookback period for the oscillator (Default: 12).
Smoothing: Helps reduce noise in the histogram (Default: 10).
Pivot Lookback: Sensitivity for divergence detection (Default: 5).
Dashboard: You can toggle the panel ON/OFF, change its size (Tiny/Small/Normal), and move it to any corner of the chart.
Disclaimer
This tool is for educational and analytical purposes only. Trading involves risk. Always use proper risk management. Past performance does not guarantee future results.
Anchored VWAP + Bands + Signals//@version=5
indicator("Anchored VWAP + Bands + Signals", overlay=true)
// ===== INPUTS =====
anchorTime = input.time(timestamp("2025-12-02 00:00"), "Anchor Date/Time")
std1 = input.float(1.0, "±1σ Band")
std2 = input.float(2.0, "±2σ Band")
// ===== VWAP CALCULATION =====
var float cumPV = 0.0
var float cumVol = 0.0
if time >= anchorTime
cumPV += close * volume
cumVol += volume
vwap = cumVol != 0 ? cumPV / cumVol : na
// ===== STANDARD DEVIATION =====
barsSinceAnchor = bar_index - ta.valuewhen(time >= anchorTime, bar_index, 0)
sd = barsSinceAnchor > 1 ? ta.stdev(close, barsSinceAnchor) : 0
// ===== BANDS =====
upper1 = vwap + std1 * sd
lower1 = vwap - std1 * sd
upper2 = vwap + std2 * sd
lower2 = vwap - std2 * sd
plot(vwap, color=color.orange, title="VWAP")
plot(upper1, color=color.green, title="+1σ Band")
plot(lower1, color=color.green, title="-1σ Band")
plot(upper2, color=color.red, title="+2σ Band")
plot(lower2, color=color.red, title="-2σ Band")
// ===== SIGNALS =====
buySignal = ta.crossover(close, lower1)
sellSignal = ta.crossunder(close, upper1)
plotshape(buySignal, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small, title="Buy Signal")
plotshape(sellSignal, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small, title="Sell Signal")
alertcondition(buySignal, title="Buy Alert", message="Price touched lower 1σ band – Buy Opportunity")
alertcondition(sellSignal, title="Sell Alert", message="Price touched upper 1σ band – Sell Opportunity")
MACD Ultimate MTF [Radisa] MACD Ultimate MTF - Enhanced MACD with Beautiful Fills
Based on the legendary CM_MacD_Ult_MTF by ChrisMoody - upgraded to Pine Script v5 with beautiful gradient fills and an informative dashboard.
🎯 FEATURES:
- Multi-timeframe support (MTF) - view higher timeframe MACD on any chart
- Beautiful fill between MACD & Signal line
- 4-color histogram (strong/weak bull & bear)
- Smooth lines on current timeframe (no stepping)
- Cross signals with dot markers
- Real-time info dashboard
- Fully customizable colors
📊 SIGNALS:
- 🟢 Bullish Cross: MACD crosses above Signal
- 🔴 Bearish Cross: MACD crosses below Signal
- Histogram color intensity shows momentum strength
📈 HISTOGRAM COLORS:
- Bright Green: Above zero + rising (strong bullish)
- Dark Green: Above zero + falling (weakening bullish)
- Bright Red: Below zero + falling (strong bearish)
- Dark Red: Below zero + rising (weakening bearish)
⚙️ SETTINGS:
- Fast/Slow/Signal Length (default: 12/26/9)
- Use current or custom timeframe
- Toggle MACD line, Signal line, Histogram
- Toggle fills and color changes
- Customizable colors for all elements
💡 DASHBOARD SHOWS:
- MACD value with colored background
- Signal value
- Histogram value
- Trend direction (Bullish/Bearish)
- Momentum strength (Strong/Fading)
- Current timeframe
Perfect for trend-following strategies. Combine with RSI or Supertrend for confirmation.
Works on Crypto, Forex, Stocks - all timeframes.
Weighted KDE Mode🙏🏻 The ‘ultimate’ typical value estimator, for the highest computational cost @ time complexity O(n^2). I am not afraid to say: this is the last resort BFG9000 you can ‘ever’ get to make dem market demons kneel before y’all
Quickguide
pls read it, you won’t find it anywhere else in open access
When to use:
If current market activity is so crazy || things on your charts are really so bad (contaminated data && (data has very heavy tails || very pronounced peak)), the only option left is to use the peak (mode) of Kernel Density Estimate , instead of median not even mentioning mean. So when WMA won’t help, when WPNR won’t help, you need this thing.
Setting it up:
Interval: choose what u need, you can use usual moving windows, but I also added yearly and session anchors alike in old VWAP (always prefer 24h instead of Session if your plan allows). Other options like cumulative window are also there.
Parameters: this script ain't no joke, it needs time to make calculations, so I added a setting to calculate only for the last N bars (when “starting at bar N” is put on 0). If it’s not zero it acts as a starting point after which the calculations happen (useful for backtesting). Other parameters keep em as they are, keep student5 kernel , turn off appropriate weights if u apply it to other than chart data, on other studies etc.
But instead of listening to me just experiment with parameters and see what they change, would take 5 mins max
Been always saying that VWAP is ish, not time-aware etc, volume info is incorporated in a lil bit wrong way… So I decided not just to fix VWAP (you can do it yourself in 5 mins), but instead to drop there the Ultimate xD typical value estimator that is ever possible to do. Time aware, volume / inferred volume aware, resistant to all kinds of BS. This is your shieldwall.
How it works:
You can easily do a weighted kernel density estimation, in our case including temporal and intensity information while accumulating densities. Here are some details worth mentioning about the thing:
Kernels are raw (not unit variance), that’s easier to work with later.
h_constants for each kernel were calculated ^^ given that ^^ with python mpmath module with high decimal precision.
In bandwidth calculation instead of using empirical standard deviation as a scaler, I use... ta.range(src, len) / math.sqrt(12)
...that takes data range and converts it to standard deviation, assuming data is uniformly distributed. That’s exactly what we need: a scaler that is coherent with the KDE, that has nothing to do with stdevs, as the kernels except for gaussian ones (that we don’t even need to use). More importantly, if u take multiple windows and see over time which distro they approach on the long term, that would be the uniform one (not the normal one as many think). Sometimes windows are multimodal, sometimes Laplace like etc, so in general all together they are uniform ish.
The one and only kernel you really need is Student t with v = 5 , for the use case I highlighted in the first part of the post for TV users. It’s as far as u can get until ish becomes crazy like undefined variance etc. It has the highest kurtosis = 9 of all distros, perfect for the real use case I mentioned. Otherwise, you don’t even need KDE 4 real, but still I included other senseful kernels for comparison or in case I am trippin there.
Btw, don’t believe in all that hype about Epanechnikov kernel which in essence is made from beta distribution with alpha = beta = 2, idk why folk call it with that weird name, it’s beta2 kernel. Yes on papers it really minimises AMISE (that’s how I calculated h constants for all dem kernels in the script), but for really crazy data (proper use case for us), it ain't provides even ‘closely’ compared with student5 kernel. Not much else to add.
Shout out to @RicardoSantos for inspiration, I saw your KDE script a long time ago brotha, finna got my hands on it.
∞
Dashboard AIO Pro: RSI, MACD & Stoch RSI [THF]Description:
This indicator provides a comprehensive "All-in-One" Dashboard that monitors three major momentum oscillators: RSI, MACD, and Stochastic RSI. It displays their real-time values and interprets their signals (Buy/Sell/Neutral) in a clean, customizable table directly on your chart.
Key Features:
Consolidated View: Instead of cluttering your chart with three separate indicator panes, this dashboard summarizes the market state in one compact table.
Dynamic Summary: The script calculates an "Overall Trend" based on a voting system. If 2 or more indicators agree on a direction, the summary updates to show a "Strong Trend".
Fully Customizable Colors: Users can customize the colors for Strong Buy, Buy, Sell, Strong Sell, and Neutral states via the settings menu to match their chart theme.
Alerts Included: Built-in alert conditions for "Strong Buy Consensus" and "Strong Sell Consensus".
How it Works (The Logic):
RSI (14):
Value > 70: Considered Overbought (Bearish signal).
Value < 30: Considered Oversold (Bullish signal).
MACD (12, 26, 9):
Bullish: MACD Line > Signal Line AND Histogram is rising.
Bearish: MACD Line < Signal Line AND Histogram is falling.
Stoch RSI (14, 14, 3, 3):
Evaluates K% line position relative to 80/20 levels and crossovers with D% line.
Overall Summary:
The script assigns a score (+1 for Bullish, 0 for Neutral).
If the total score >= 2, the trend is identified as "Uptrend".
If the indicators show divergent signals, the status remains "Ranging".
Settings:
You can change the length of all indicators (RSI, MACD, Stoch).
You can change the table position and text size.
Color Customization: Dedicated section to change the dashboard colors.
Wyckoff + VSA Ultimate - Complete Market Analysis
**Wyckoff + VSA Ultimate** combines three proven methodologies into one powerful indicator:
🔷 **Wyckoff Method** - Identifies market accumulation and distribution phases
🔷 **Volume Spread Analysis** - Confirms moves with volume and price spread
🔷 **Random Walk Index** - Validates trend strength and direction
**MAIN SIGNALS:**
📊 **Wyckoff Signals** (Green = Bullish, Red = Bearish)
• SC (Selling Climax) - Major buying opportunity
• BC (Buying Climax) - Major selling opportunity
• AR (Automatic Rally) - Confirms accumulation
• DAR (Automatic Reaction) - Confirms distribution
• ST (Secondary Test) - Final test before move
📊 **VSA Patterns**
• Upthrust bars (weakness after rally)
• Reverse upthrust (strength after decline)
• No demand/supply bars
• Stopping volume
• Effort failures
**KEY FEATURES:**
✅ Multiple signal confirmation reduces false signals
✅ Real-time info table shows phase, volume, trends
✅ Dynamic stop loss levels calculated automatically
✅ Accumulation/Distribution boxes on chart
✅ Customizable filters for your trading style
✅ 12 alert conditions for all major signals
**HOW TO USE:**
For Swing Trading (4H/Daily):
1. Enable "Require VSA Confirmation"
2. Wait for SC or BC signals
3. Use displayed stop levels
4. Target next opposite phase
For Day Trading (15m/1H):
1. Enable "Require Trend Confirmation"
2. Trade only trend-aligned signals
3. Increase volume threshold to 1.5
4. Use tighter risk management
**BEST FOR:**
✅ Stocks (high volume)
✅ Forex majors
✅ Crypto (BTC, ETH)
✅ Index futures
**SETTINGS:**
Customize everything:
• RSI & Pivot parameters
• Volume & Spread analysis
• Trend periods (RWI)
• Signal filters
• Visual display options
**ALERTS:**
Pre-configured alerts for:
• All Wyckoff signals
• VSA reversals
• Strong buy/sell combinations
**Credits:** Integrates Wyckoff (faytterro) and VSA (theehoganator) methods.
**Disclaimer:** Educational purposes only. Use proper risk management. Past performance doesn't guarantee future results.
---
Pine Script™ v6
---
Viprasol Elite Advanced Pattern Scanner# 🚀 Viprasol Elite Advanced Pattern Scanner
## Overview
The **Viprasol Elite Advanced Pattern Scanner** is a sophisticated technical analysis tool designed to identify high-probability double bottom (DISCOUNT) and double top (PREMIUM) patterns with unprecedented accuracy. Unlike basic pattern detectors, this elite scanner employs an AI-powered quality scoring system to filter out false signals and highlight only the most reliable trading opportunities.
## 🎯 Key Features
### Advanced Pattern Detection
- **DISCOUNT Patterns** (Double Bottoms): Identifies bullish reversal zones where price may bounce
- **PREMIUM Patterns** (Double Tops): Detects bearish reversal zones where price may decline
- Multi-point validation system (5-point structure)
- Symmetry analysis with customizable tolerance
### 🤖 AI Quality Scoring System
Each pattern receives a quality score (0-100) based on:
- **Symmetry Analysis** (32% weight): How closely the two bottoms/tops match
- **Trend Context** (22% weight): Strength of the preceding trend using ADX
- **Volume Profile** (22% weight): Volume confirmation at key points
- **Pattern Depth** (16% weight): Significance of the pattern's price range
- **Structure Quality** (16% weight): Overall pattern formation quality
Quality Grades:
- ⭐ **ELITE** (88-100): Highest probability setups
- ✨ **VERY STRONG** (77-87): Strong trade opportunities
- ✓ **STRONG** (67-76): Valid patterns with good potential
- ○ **VALID** (65-66): Acceptable patterns meeting minimum criteria
### 🎯 Intelligent Target System
Three target modes per pattern direction:
- **Conservative**: 0.618 Fibonacci extension (safer, closer targets)
- **Balanced**: 1.0 extension (moderate risk/reward)
- **Aggressive**: 1.618 extension (higher risk/reward)
Targets automatically adjust based on pattern quality score.
### 🔧 Advanced Filtering Options
- **Volatility Filter (ATR)**: Excludes patterns during extreme volatility
- **Momentum Filter (ADX)**: Ensures sufficient trend strength
- **Liquidity Filter (Volume)**: Confirms adequate trading volume
### 📊 Pattern Lifecycle Management
- Real-time neckline tracking with extension multiplier
- Pattern invalidation after extended wait period
- Breakout/breakdown confirmation
- Reversal detection (pattern failure scenarios)
- Target achievement tracking
### 🌈 Premium Visual System
- Color-coded quality levels
- Cyber-themed color scheme (Neon Green/Hot Pink/Purple/Cyan)
- Transparent fills for pattern zones
- Dynamic labels with pattern information
- Elite dashboard showing live pattern stats
## 📈 How To Use
### Basic Setup
1. Add indicator to your chart
2. Enable desired patterns (DISCOUNT and/or PREMIUM)
3. Adjust quality threshold (default: 65) - higher = fewer but better signals
4. Set your preferred target mode
### Trading DISCOUNT Patterns (Bullish)
1. Wait for pattern detection (labeled points 1-4)
2. Check quality score on dashboard
3. Entry on breakout above neckline (point 5)
4. Stop loss below the lowest bottom
5. Target shown automatically based on your mode
6. ⚠️ Watch for pattern failure (break below bottoms = SHORT signal)
### Trading PREMIUM Patterns (Bearish)
1. Wait for pattern detection (labeled points 1-4)
2. Check quality score on dashboard
3. Entry on breakdown below neckline (point 5)
4. Stop loss above the highest top
5. Target shown automatically based on your mode
6. ⚠️ Watch for pattern failure (break above tops = LONG signal)
## ⚙️ Input Settings Guide
### 🔍 Detection Engine
- **Left/Right Pivots**: Higher = fewer but cleaner patterns (default: 6/4)
- **Min Pattern Width**: Minimum bars between bottoms/tops (default: 12)
- **Symmetry Tolerance**: Max % difference allowed between levels (default: 1.8%)
- **Extension Multiplier**: How long to wait for breakout (default: 2.2x pattern width)
### ⭐ Quality AI
- **Min Quality Score**: Only show patterns above this score (default: 65)
- **Weight Distribution**: Customize what matters most (symmetry/trend/volume/depth/structure)
### 🔧 Filters
- **Volatility Filter**: Avoid choppy markets (recommended: ON)
- **Momentum Filter**: Ensure trend strength (recommended: ON)
- **Liquidity Filter**: Volume confirmation (recommended: ON)
### 💎 Target System
- Choose target aggression for each pattern type and direction
- Higher quality patterns get adjusted targets automatically
## 🎨 Visual Customization
- Adjust colors for DISCOUNT/PREMIUM patterns
- Set quality-based color coding
- Customize label sizes
- Toggle dashboard visibility and position
- Show/hide historical patterns
## 🚨 Alert System
Set up TradingView alerts for:
- 🚀 **LONG Signals**: DISCOUNT breakout, PREMIUM failure
- 📉 **SHORT Signals**: PREMIUM breakdown, DISCOUNT failure
- ✅ **Target Achievement**: When price hits your target
## 💡 Pro Tips
1. **Higher Timeframes = Better Signals**: Patterns on 4H, Daily, Weekly are more reliable
2. **Quality Over Quantity**: Focus on ELITE and VERY STRONG grades
3. **Combine with Trend**: DISCOUNT in uptrend, PREMIUM in downtrend = best results
4. **Watch Pattern Failures**: Failed patterns often provide strong counter-trend signals
5. **Adjust for Your Style**: Intraday traders use Conservative, swing traders use Aggressive
## 🔒 Pattern Invalidation
Patterns become invalid if:
- No breakout/breakdown within extension period
- Support/resistance levels are broken prematurely
- Pattern shown in faded colors = no longer active
## ⚠️ Risk Disclaimer
This indicator is a tool for technical analysis and does not guarantee profitable trades. Always:
- Use proper risk management
- Combine with other analysis methods
- Never risk more than you can afford to lose
- Past performance does not indicate future results
Relative Strength Heatmap [BackQuant]Relative Strength Heatmap
A multi-horizon RSI matrix that compresses 20 different lookbacks into a single panel, turning raw momentum into a visual “pressure gauge” for overbought and oversold clustering, trend exhaustion, and breadth of participation across time horizons.
What this is
This indicator builds a strip-style heatmap of 20 RSIs, each with a different length, and stacks them vertically as colored tiles in a single pane. Every tile is colored by its RSI value using your chosen palette, so you can see at a glance:
How many “fast” versus “slow” RSIs are overbought or oversold.
Whether momentum is concentrated in the short lookbacks or spread across the whole curve.
When momentum extremes cluster, signalling strong market pressure or exhaustion.
On top of the tiles, the script plots two simple breadth lines:
A white line that counts how many RSIs are above 70 (overbought cluster).
A black line that counts how many RSIs are below 30 (oversold cluster).
This turns a single symbol’s RSI ladder into a compact “market pressure gauge” that shows not only whether RSI is overbought or oversold, but how many different horizons agree at the same time.
Core idea
A single RSI looks at one length and one timescale. Markets, however, are driven by flows that operate on multiple horizons at once. By computing RSI over a ladder of lengths, you approximate a “term structure” of strength:
Short lengths react to immediate swings and very recent impulses.
Medium lengths reflect swing behaviour and local trends.
Long lengths reflect structural bias and higher timeframe regime.
When many lengths agree, for example 10 or more RSIs all above 70, it suggests broad participation and strong directional pressure. When only a few fast lengths stretch to extremes while longer ones stay neutral, the move is more fragile and more likely to mean-revert.
This script makes that structure visible as a heatmap instead of forcing you to run many separate RSI panes.
How it works
1) Generating RSI lengths
You control three parameters in the calculation settings:
RS Period – the base RSI length used for the shortest strip.
RSI Step – the amount added to each successive RSI length.
RSI Multiplier – a global scaling factor applied after the step.
Each of the 20 RSIs uses:
RSI length = round((base_length + step × index) × multiplier) , where the index goes from 0 to 19.
That means:
RSI 1 uses (len + step × 0) × mult.
RSI 2 uses (len + step × 1) × mult.
…
RSI 20 uses (len + step × 19) × mult.
You can keep the ladder dense (small step and multiplier) or stretch it across much longer horizons.
2) Heatmap layout and grouping
Each RSI is plotted as an “area” strip at a fixed vertical level using histbase to stack them:
RSI 1–5 form Group 1.
RSI 6–10 form Group 2.
RSI 11–15 form Group 3.
RSI 16–20 form Group 4.
Each group has a toggle:
Show only Group 1 and 2 if you care mainly about fast and medium horizons.
Show all groups for a full spectrum from very short to very long.
Hide any group that feels redundant for your workflow.
The actual numeric RSI values are not plotted as lines. Instead, each strip is drawn as a horizontal band whose fill color represents the current RSI regime.
3) Palette-based coloring
Each tile’s color is driven by the RSI value and your chosen palette. The script includes several palettes:
Viridis – smooth green to yellow, good for subtle reading.
Jet – strong blue to red sequence with high contrast.
Plasma – purple through orange to yellow.
Custom Heat – cool blues to neutral grey to hot reds.
Gray – grayscale from white to black for minimalistic layouts.
Cividis, Inferno, Magma, Turbo, Rainbow – additional scientific and rainbow-style maps.
Internally, RSI values are bucketed into ranges (for example, below 10, 10–20, …, 90–100). Each bucket maps to a unique colour for that palette. In all schemes, low RSI values are mapped to the “cold” or darker side and high RSI values to the “hot” or brighter side.
The result is a true momentum heatmap:
Cold or dark tiles show low RSI and oversold or compressed conditions.
Mid tones show neutral or mid-range RSI.
Warm or bright tiles show high RSI and overbought or stretched conditions.
4) Bull and bear breadth counts
All 20 RSI values are collected into an array each bar. Two counters are then calculated:
Bull count – how many RSIs are above 70.
Bear count – how many RSIs are below 30.
These are plotted as:
A white line (“RSI > 70 Count”) for the overbought cluster.
A black line (“RSI < 30 Count”) for the oversold cluster.
If you enable the “Show Bull and Bear Count” option, you get an immediate reading of how many of the 20 horizons are stretched at any moment.
5) Cluster alerts and background tagging
Two alert conditions monitor “strong cluster” regimes:
RSI Heatmap Strong Bull – triggers when at least 10 RSIs are above 70.
RSI Heatmap Strong Bear – triggers when at least 10 RSIs are below 30.
When one of these conditions is true, the indicator can tint the background of the chart using a soft version of the current palette. This visually marks stretches where momentum is extreme across many lengths at once, not just on a single RSI.
What it plots
In one oscillator window, the indicator provides:
Up to 20 horizontal RSI strips, each representing a different RSI length.
Color-coded tiles reflecting the current RSI value for each length.
Group toggles to show or hide each block of five RSIs.
An optional white line that counts how many RSIs are above 70.
An optional black line that counts how many RSIs are below 30.
Optional background highlights when the number of overbought or oversold RSIs passes the strong-cluster threshold.
How it measures breadth and pressure
Single-symbol breadth
Breadth is usually defined across a basket of symbols, such as how many stocks advance versus decline. This indicator uses the same concept across time horizons for a single symbol. The question becomes:
“How many different RSI lengths are stretched in the same direction at once?”
Examples:
If only 2 or 3 of the shortest RSIs are above 70, bull count stays low. The move is fast and local, but not yet broadly supported.
If 12 or more RSIs across short, medium and long lengths are above 70, the bull count spikes. The move has broad momentum and strong upside pressure.
If 10 or more RSIs are below 30, bear count spikes and you are in a broad oversold regime.
This is breadth of momentum within one market.
Market pressure gauge
The combination of heatmap tiles and breadth lines acts as a pressure gauge:
High bull count with warm colors across most strips indicates strong upside pressure and crowded long positioning.
High bear count with cold colors across most strips indicates strong downside pressure and capitulation or forced selling.
Low counts with a mixed heatmap indicate neutral pressure, fragmented flows, or range-bound conditions.
You can treat the strong-cluster alerts as “extreme pressure” signals. When they fire, the market is heavily skewed in one direction across many horizons.
How to read the heatmap
Horizontal patterns (through time)
Look along the time axis and watch how the colors evolve:
Persistent hot tiles across many strips show sustained bullish pressure and trend strength.
Persistent cold tiles across many strips show sustained bearish pressure and weak demand.
Frequent flipping between hot and cold colours indicates a choppy or mean-reverting environment.
Vertical structure (across lengths at one bar)
Focus on a single bar and read the column of tiles from top to bottom:
Short RSIs hot, long RSIs neutral or cool: early trend or short-term fomo. Price has moved fast, longer horizons have not caught up.
Short and long RSIs all hot: mature, entrenched uptrend. Broad participation, high pressure, greater risk of blow-off or late-entry vulnerability.
Short RSIs cold but long RSIs mid to high: pullback in a higher timeframe uptrend. Dip-buy and continuation setups are often found here.
Short RSIs high but long RSIs low: countertrend rallies within a broader downtrend. Good hunting ground for fades and short entries after a bounce.
Bull and bear breadth lines
Use the two lines as simple, numeric breadth indicators:
A rising white line shows more RSIs pushing above 70, so bullish pressure is expanding in breadth.
A rising black line shows more RSIs pushing below 30, so bearish pressure is expanding in breadth.
When both lines are low and flat, few horizons are extreme and the market is in mid-range territory.
Cluster zones
When either count crosses the strong threshold (for example 10 out of 20 RSIs in extreme territory):
A strong bull cluster marks a broadly overbought regime. Trend followers may see this as confirmation. Mean-reversion traders may see it as a late-stage or blow-off context.
A strong bear cluster marks a broadly oversold regime. Downtrend traders see strong pressure, but the risk of sharp short-covering bounces also increases.
Trading applications
Trend confirmation
Use the heatmap and breadth lines as a trend filter:
Prefer long setups when the heatmap shows mostly mid to high RSIs and the bull count is rising.
Avoid fresh shorts when there is a strong bull cluster, unless you are specifically trading exhaustion.
Prefer short setups when the heatmap is mostly low RSIs and the bear count is rising.
Avoid aggressive longs when a strong bear cluster is active, unless you are trading reflexive bounces.
Mean-reversion timing
Treat cluster extremes as exhaustion zones:
Look for reversal patterns, failed breakouts, or order flow shifts when bull count is very high and price starts to stall or diverge.
Look for reflexive bounce potential when bear count is very high and price stops making new lows or shows absorption at the lows.
Use the palette and counts together: hot tiles plus a peaking white line can mark blow-off conditions, cold tiles plus a peaking black line can mark capitulation.
Regime detection and risk toggling
Use the overall shape of the ladder over time:
If upper strips stay warm and lower strips stay neutral or warm for extended periods, the market is in an uptrend regime. You can justify higher risk for long-biased strategies.
If upper strips stay cold and lower strips stay neutral or cold, the market is in a downtrend regime. You can justify higher risk for short-biased strategies or defensive positioning.
If colours and counts flip frequently, you are likely in a range or choppy regime. Consider reducing size or using more tactical, short-term strategies.
Multi-horizon synchronization
You can think of each RSI length as a proxy for a different “speed” of the same market:
When only fast RSIs are stretched, the move is local and less robust.
When fast, medium and slow RSIs align, the move has multi-horizon confirmation.
You can require a minimum bull or bear count before allowing your main strategy to engage.
Spotting hidden shifts
Sometimes price appears flat or drifting, but the heatmap quietly cools or warms:
If price is sideways while many hot tiles fade toward neutral, momentum is decaying under the surface and trend risk is increasing.
If price is sideways while many cold tiles climb back toward neutral, selling pressure is decaying and the tape is repairing itself.
Settings overview
Calculation Settings
RS Period – base RSI length for the shortest strip.
RSI Step – the increment added to each successive RSI length.
RSI Multiplier – scales all generated RSI lengths.
Calculation Source – the input series, such as close, hlc3 or others.
Plotting and Coloring Settings
Heatmap Color Palette – choose between Viridis, Jet, Plasma, Custom Heat, Gray, Cividis, Inferno, Magma, Turbo or Rainbow.
Show Group 1 – toggles RSI 1–5.
Show Group 2 – toggles RSI 6–10.
Show Group 3 – toggles RSI 11–15.
Show Group 4 – toggles RSI 16–20.
Show Bull and Bear Count – enables or disables the two breadth lines.
Alerts
RSI Heatmap Strong Bull – fires when the number of RSIs above 70 reaches or exceeds the configured threshold (default 10).
RSI Heatmap Strong Bear – fires when the number of RSIs below 30 reaches or exceeds the configured threshold (default 10).
Tuning guidance
Fast, tactical configurations
Use a small base RS Period, for example 2 to 5.
Use a small RSI Step, for tight clustering around the fast horizon.
Keep the multiplier near 1.0 to avoid extreme long lengths.
Focus on Group 1 and Group 2 for intraday and short-term trading.
Swing and position configurations
Use a mid-range RS Period, for example 7 to 14.
Use a moderate RSI Step to fan out into slower horizons.
Optionally use a multiplier slightly above 1.0.
Keep all four groups enabled for a full view from fast to slow.
Macro or higher timeframe configurations
Use a larger base RS Period.
Use a larger RSI Step so the top of the ladder reaches very slow lengths.
Focus on Group 3 and Group 4 to see structural momentum.
Treat clusters as regime markers rather than frequent trading signals.
Notes
This indicator is a contextual tool, not a standalone trading system. It does not model execution, spreads, slippage or fundamental drivers. Use it to:
Understand whether momentum is narrow or broad across horizons.
Confirm or filter existing signals from your primary strategy.
Identify environments where the market is crowded into one side.
Distinguish between isolated spikes and truly broad pressure moves.
The Relative Strength Heatmap is designed to answer a simple but powerful question:
“How many versions of RSI agree with what I am seeing on the chart?”
By compressing those answers into a single panel with clear colour coding and breadth lines, it becomes a practical, visual gauge of momentum breadth and market pressure that you can overlay on any trading framework.
Viprasol Elite Flow Pro - Premium Order Flow & Trend System═══════════════════════════════════════════════════════════════
🔥 VIPRASOL ELITE FLOW PRO
Professional Order Flow & Trend Detection System
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📊 WHAT IS THIS INDICATOR?
Viprasol Elite Flow Pro is a comprehensive trading system that combines institutional order flow analysis with adaptive trend detection. Unlike basic indicators, this tool identifies high-probability setups by analyzing where smart money is likely positioning, while filtering signals through multiple confirmation layers.
This indicator is designed for traders who want to:
✓ Identify premium (supply) and discount (demand) zones automatically
✓ Detect trend direction with adaptive cloud technology
✓ Spot high-volume rejection points before major moves
✓ Filter low-quality signals with intelligent confirmation logic
✓ Track market strength in real-time via elite dashboard
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🎯 CORE FEATURES
═══════════════════════════════════════════════════════════════
1️⃣ ELITE TREND ENGINE
• Adaptive Moving Average system (Fast/Adaptive/Smooth modes)
• Dynamic trend cloud that expands/contracts with volatility
• Real-time trend state tracking (Bullish/Bearish/Ranging)
• Trend strength meter (0-10 scale)
• ATR-based volatility adjustments
2️⃣ ORDER FLOW DETECTION
• Automatic Premium Zone (Supply) identification
• Automatic Discount Zone (Demand) identification
• Smart zone extension - zones remain valid until broken
• Zone rejection detection with price action confirmation
• Customizable zone strength (5-30 bars lookback)
3️⃣ VOLUME INTELLIGENCE
• Volume spike detection (configurable threshold)
• Climax bar identification (exhaustion signals)
• Volume filter for signal validation
• Institutional activity detection
4️⃣ SMART SIGNAL SYSTEM
• 3 Signal Modes: Aggressive, Balanced, Conservative
• Multi-layer confirmation logic
• Automatic profit targets (2:1 risk-reward)
• Stop loss suggestions based on ATR
• Prevents overtrading with bars-since-signal filter
5️⃣ ELITE DASHBOARD (HUD)
• Real-time trend direction and strength
• Volume status monitoring
• Active zones counter
• Market volatility gauge
• Current signal status
• 4 positioning options, compact mode available
6️⃣ PREMIUM STYLING
• 4 Professional color themes (Cyber/Gold/Ocean/Fire)
• Adjustable transparency and label sizes
• Clean, institutional-grade visuals
• Optimized for all chart types
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📖 HOW TO USE THIS INDICATOR
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STEP 1: TREND IDENTIFICATION
→ Green Cloud = Bullish trend - look for LONG opportunities
→ Red Cloud = Bearish trend - look for SHORT opportunities
→ Purple Cloud = Ranging - wait for breakout or fade extremes
STEP 2: ZONE ANALYSIS
→ PREMIUM (Red) zones = Potential resistance/supply areas
→ DISCOUNT (Green) zones = Potential support/demand areas
→ Price rejecting from zones = high-probability setups
STEP 3: SIGNAL CONFIRMATION
→ Wait for "LONG" or "SHORT" labels to appear
→ Check dashboard for trend strength (Moderate/Strong preferred)
→ Confirm volume status is "HIGH" or "CLIMAX"
→ Entry: Enter when label appears
→ Stop Loss: Use dotted line (1 ATR away)
→ Take Profit: Use dashed line (2 ATR away)
STEP 4: RISK MANAGEMENT
→ Never risk more than 1-2% per trade
→ Use the provided stop loss levels
→ Trail stops as price moves in your favor
→ Avoid trading during low volatility periods
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⚙️ RECOMMENDED SETTINGS
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FOR SCALPING (1M - 5M):
- Trend Type: Fast
- Sensitivity: 15
- Signal Mode: Aggressive
- Zone Strength: 8
FOR DAY TRADING (15M - 1H):
- Trend Type: Adaptive
- Sensitivity: 21 (default)
- Signal Mode: Balanced
- Zone Strength: 12 (default)
FOR SWING TRADING (4H - Daily):
- Trend Type: Smooth
- Sensitivity: 34
- Signal Mode: Conservative
- Zone Strength: 20
BEST MARKETS:
✓ Crypto (BTC, ETH, major altcoins)
✓ Forex (Major pairs: EUR/USD, GBP/USD)
✓ Indices (S&P 500, NASDAQ, DAX)
✓ High-liquidity stocks
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🎓 UNDERSTANDING THE METHODOLOGY
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This indicator is built on three core concepts:
1. ORDER FLOW THEORY
Markets move between premium (expensive) and discount (cheap) zones. Smart money accumulates in discount zones and distributes in premium zones. This indicator identifies these zones automatically.
2. ADAPTIVE TREND FOLLOWING
Unlike fixed-period moving averages, the Elite Trend Engine adjusts to current market volatility, providing more accurate trend signals in both trending and ranging conditions.
3. CONFLUENCE-BASED ENTRIES
Signals only trigger when multiple conditions align:
- Price in correct zone (premium for shorts, discount for longs)
- Trend confirmation (cloud color matches direction)
- Volume validation (spike or climax present)
- Price action strength (strong rejection candles)
This multi-layer approach dramatically reduces false signals.
═══════════════════════════════════════════════════════════════
🔔 ALERT SETUP
═══════════════════════════════════════════════════════════════
This indicator includes 5 alert types:
1. Long Signal → Triggers when buy conditions met
2. Short Signal → Triggers when sell conditions met
3. Volume Climax → Warns of pot
Superior-Range Bound Renko - Strategy - 11-29-25 - SignalLynxSuperior-Range Bound Renko Strategy with Advanced Risk Management Template
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
Welcome to Superior-Range Bound Renko (RBR) — a volatility-aware, structure-respecting swing-trading system built on top of a full Risk Management (RM) Template from Signal Lynx.
Instead of relying on static lookbacks (like “14-period RSI”) or plain MA crosses, Superior RBR:
Adapts its range definition to market volatility in real time
Emulates Renko Bricks on a standard, time-based chart (no Renko chart type required)
Uses a stack of Laguerre Filters to detect genuine impulse vs. noise
Adds an Adaptive SuperTrend powered by a small k-means-style clustering routine on volatility
Under the hood, this script also includes the full Signal Lynx Risk Management Engine:
A state machine that separates “Signal” from “Execution”
Layered exit tools: Stop Loss, Trailing Stop, Staged Take Profit, Advanced Adaptive Trailing Stop (AATS), and an RSI-style stop (RSIS)
Designed for non-repainting behavior on closed candles by basing execution-critical logic on previous-bar data
We are publishing this as an open-source template so traders and developers can leverage a professional-grade RM engine while integrating their own signal logic if they wish.
2. Quick Action Guide (TL;DR)
Best Timeframe:
4 Hours (H4) and above. This is a high-conviction swing-trading system, not a scalper.
Best Assets:
Volatile instruments that still respect market structure:
Bitcoin, Ethereum, Gold (XAUUSD), high-volatility Forex pairs (e.g., GBPJPY), indices with clean ranges.
Strategy Type:
Volatility-Adaptive Trend Following + Impulse Detection.
It hunts for genuine expansion out of ranges, not tiny mean-reversion nibbles.
Key Feature:
Renko Emulation on time-based candles.
We mathematically model Renko Bricks and overlay them on your standard chart to define:
“Equilibrium” zones (inside the brick structure)
“Breakout / impulse” zones (when price AND the impulse line depart from the bricks)
Repainting:
Designed to be non-repainting on closed candles.
All RM execution logic uses confirmed historical data (no future bars, no security() lookahead). Intrabar flicker during formation is allowed, but once a bar closes the engine’s decisions are stable.
Core Toggles & Filters:
Enable Longs and Shorts independently
Optional Weekend filter (block trades on Saturday/Sunday)
Per-module toggles: Stop Loss, Trailing Stop, Staged Take Profits, AATS, RSIS
3. Detailed Report: How It Works
A. The Strategy Logic: Superior RBR
Superior RBR builds its entry signal from multiple mathematical layers working together.
1) Adaptive Lookback (Volatility Normalization)
Instead of a fixed 100-bar or 200-bar range, the script:
Computes ATR-based volatility over a user-defined period.
Normalizes that volatility relative to its recent min/max.
Maps the normalized value into a dynamic lookback window between a minimum and maximum (e.g., 4 to 100 bars).
High Volatility:
The lookback shrinks, so the system reacts faster to explosive moves.
Low Volatility:
The lookback expands, so the system sees a “bigger picture” and filters out chop.
All the core “Range High/Low” and “Range Close High/Low” boundaries are built on top of this adaptive window.
2) Range Construction & Quick Ranges
The engine constructs several nested ranges:
Outer Range:
rangeHighFinal – dynamic highest high
rangeLowFinal – dynamic lowest low
Inner Close Range:
rangeCloseHighFinal – highest close
rangeCloseLowFinal – lowest close
Quick Ranges:
“Half-length” variants of those, used to detect more responsive changes in structure and volatility.
These ranges define:
The macro box price is trading inside
Shorter-term “pressure zones” where price is coiling before expansion
3) Renko Emulation (The Bricks)
Rather than using the Renko chart type (which discards time), this script emulates Renko behavior on your normal candles:
A “brick size” is defined either:
As a standard percentage move, or
As a volatility-driven (ATR) brick, optionally inhibited by a minimum standard size
The engine tracks a base value and derives:
brickUpper – top of the emulated brick
brickLower – bottom of the emulated brick
When price moves sufficiently beyond those levels, the brick “shifts”, and the directional memory (renkoDir) updates:
renkoDir = +2 when bricks are advancing upward
renkoDir = -2 when bricks are stepping downward
You can think of this as a synthetic Renko tape overlaid on time-based candles:
Inside the brick: equilibrium / consolidation
Breaking away from the brick: momentum / expansion
4) Impulse Tracking with Laguerre Filters
The script uses multiple Laguerre Filters to smooth price and brick-derived data without traditional lag.
Key filters include:
LagF_1 / LagF_W: Based on brick upper/lower baselines
LagF_Q: Based on HLCC4 (high + low + 2×close)/4
LagF_Y / LagF_P: Complex averages combining brick structures and range averages
LagF_V (Primary Impulse Line):
A smooth, high-level impulse line derived from a blend of the above plus the outer ranges
Conceptually:
When the impulse line pushes away from the brick structure and continues in one direction, an impulse move is underway.
When its direction flips and begins to roll over, the impulse is fading, hinting at mean reversion back into the range.
5) Fib-Based Structure & Swaps
The system also layers in Fib levels derived from the adaptive ranges:
Standard levels (12%, 23.6%, 38.2%, 50%, 61%, 76.8%, 88%) from the main range
A secondary “swap” set derived from close-range dynamics (fib12Swap, fib23Swap, etc.)
These Fibs are used to:
Bucket price into structural zones (below 12, between 23–38, etc.)
Detect breakouts when price and Laguerre move beyond key Fib thresholds
Drive zSwap logic (where a secondary Fib set becomes the active structure once certain conditions are met)
6) Adaptive SuperTrend with K-Means-Style Volatility Clustering
Under the hood, the script uses a small k-means-style clustering routine on ATR:
ATR is measured over a fixed period
The range of ATR values is split into Low, Medium, High volatility centroids
Current ATR is assigned to the nearest centroid (cluster)
From that, a SuperTrend variant (STK) is computed with dynamic sensitivity:
In quiet markets, SuperTrend can afford to be tighter
In wild markets, it widens appropriately to avoid constant whipsaw
This SuperTrend-based oscillator (LagF_K and its signals) is then combined with the brick and Laguerre stack to confirm valid trend regimes.
7) Final Baseline Signals (+2 / -2)
The “brain” of Superior RBR lives in the Baseline & Signal Generation block:
Two composite signals are built: B1 and B2:
They combine:
Fib breakouts
Renko direction (renkoDir)
Expansion direction (expansionQuickDir)
Multiple Laguerre alignments (LagF_Q, LagF_W, LagF_Y, LagF_Z, LagF_P, LagF_V)
They also factor in whether Fib structures are expanding or contracting.
A user toggle selects the “Baseline” signal:
finalSig = B2 (default) or B1 (alternate baseline)
finalSig is then filtered through the RM state machine and only when everything aligns, we emit:
+2 = Long / Buy signal
-2 = Short / Sell signal
0 = No new trade
Those +2 / -2 values are what feed the Risk Management Engine.
B. The Risk Management (RM) Engine
This script features the Signal Lynx Risk Management Engine, a proprietary state machine built to separate Signal from Execution.
Instead of firing orders directly on indicator conditions, we:
Convert the raw signal into a clean integer (Fin = +2 / -2 / 0)
Feed it into a Trade State Machine that understands:
Are we flat?
Are we in a long or short?
Are we in a closing sequence?
Should we permit re-entry now or wait?
Logic Injection / Template Concept:
The RM engine expects a simple integer:
+2 → Buy
-2 → Sell
Everything else (0) is “no new trade”
This makes the script a template:
You can remove the Superior RBR block
Drop in your own logic (RSI, MACD, price action, etc.)
As long as you output +2 or -2 into the same signal channel, the RM engine can drive all exits and state transitions.
Aggressive vs Conservative Modes:
The input AgressiveRM (Aggressive RM) governs how we interpret signals:
Conservative Mode (Aggressive RM = false):
Uses a more filtered internal signal (AF) to open trades
Effectively waits for a clean trend flip / confirmation before new entries
Minimizes whipsaw at the cost of fewer trades
Aggressive Mode (Aggressive RM = true):
Reacts directly to the fresh alert (AO) pulses
Allows faster re-entries in the same direction after RM-based exits
Still respects your pyramiding setting; this script ships with pyramiding = 0 by default, so it will not stack multiple positions unless you change that parameter in the strategy() call.
The state machine enforces discipline on top of your signal logic, reducing double-fires and signal spam.
C. Advanced Exit Protocols (Layered Defense)
The exit side is where this template really shines. Instead of a single “take profit or stop loss,” it uses multiple, cooperating layers.
1) Hard Stop Loss
A classic percentage-based Stop Loss (SL) relative to the entry price.
Acts as a final “catastrophic protection” layer for unexpected moves.
2) Standard Trailing Stop
A percentage-based Trailing Stop (TS) that:
Activates only after price has moved a certain percentage in your favor (tsActivation)
Then trails price by a configurable percentage (ts)
This is a straightforward, battle-tested trailing mechanism.
3) Staged Take Profits (Three Levels)
The script supports three staged Take Profit levels (TP1, TP2, TP3):
Each stage has:
Activation percentage (how far price must move in your favor)
Trailing amount for that stage
Position percentage to close
Example setup:
TP1:
Activate at +10%
Trailing 5%
Close 10% of the position
TP2:
Activate at +20%
Trailing 10%
Close another 10%
TP3:
Activate at +30%
Trailing 5%
Close the remaining 80% (“runner”)
You can tailor these quantities for partial scaling out vs. letting a core position ride.
4) Advanced Adaptive Trailing Stop (AATS)
AATS is a sophisticated volatility- and structure-aware stop:
Uses Hirashima Sugita style levels (HSRS) to model “floors” and “ceilings” of price:
Dungeon → Lower floors → Mid → Upper floors → Penthouse
These levels classify where current price sits within a long-term distribution.
Combines HSRS with Bollinger-style envelopes and EMAs to determine:
Is price extended far into the upper structure?
Is it compressed near the lower ranges?
From this, it computes an adaptive factor that controls how tight or loose the trailing level (aATS / bATS) should be:
High Volatility / Penthouse areas:
Stop loosens to avoid getting wicked out by inevitable spikes.
Low Volatility / compressed structure:
Stop tightens to lock in and protect profit.
AATS is designed to be the “smart last line” that responds to context instead of a single fixed percentage.
5) RSI-Style Stop (RSIS)
On top of AATS, the script includes a RSI-like regime filter:
A McGinley Dynamic mean of price plus ATR bands creates a dynamic channel.
Crosses above the top band and below the lower band change a directional state.
When enabled (UseRSIS):
RSIS can confirm or veto AATS closes:
For longs: A shift to bearish RSIS can force exits sooner.
For shorts: A shift to bullish RSIS can do the same.
This extra layer helps avoid over-reactive stops in strong trends while still respecting a regime change when it happens.
D. Repainting Protection
Many strategies look incredible in the Strategy Tester but fail in live trading because they rely on intrabar values or future-knowledge functions.
This template is built with closed-candle realism in mind:
The Risk Management logic explicitly uses previous bar data (open , high , low , close ) for the key decisions on:
Trailing stop updates
TP triggers
SL hits
RM state transitions
No security() lookahead or future-bar access is used.
This means:
Backtest behavior is designed to match what you can actually get with TradingView alerts and live automation.
Signals may “flicker” intrabar while the candle is forming (as with any strategy), but on closed candles, the RM decisions are stable and non-repainting.
4. For Developers & Modders
We strongly encourage you to mod this script.
To plug your own strategy into the RM engine:
Look for the section titled:
// BASELINE & SIGNAL GENERATION
You will see composite logic building B1 and B2, and then selecting:
baseSig = B2
altSig = B1
finalSig = sigSwap ? baseSig : altSig
You can replace the content used to generate baseSig / altSig with your own logic, for example:
RSI crosses
MACD histogram flips
Candle pattern detectors
External condition flags
Requirements are simple:
Your final logic must output:
2 → Buy signal
-2 → Sell signal
0 → No new trade
That output flows into the RM engine via finalSig → AlertOpen → state machine → Fin.
Once you wire your signals into finalSig, the entire Risk Management system (Stops, TPs, AATS, RSIS, re-entry logic, weekend filters, long/short toggles) becomes available for your custom strategy without re-inventing the wheel.
This makes Superior RBR not just a strategy, but a reference architecture for serious Pine dev work.
5. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Mebane Faber GTAA 5In 2007, Mebane Faber published research that challenged the conventional wisdom of buy-and-hold investing. His paper, titled "A Quantitative Approach to Tactical Asset Allocation" and published in the Journal of Wealth Management, demonstrated that a simple timing mechanism could reduce portfolio volatility and drawdowns while maintaining competitive returns (Faber, 2007). This indicator implements his Global Tactical Asset Allocation strategy, known as GTAA5, following the original methodology.
The core insight of Faber's research stems from a century of market data. By analyzing asset class performance from 1901 onwards, Faber found that a ten-month simple moving average served as an effective trend filter across major asset classes. When an asset trades above its ten-month moving average, it tends to continue its upward trajectory; when it falls below, significant drawdowns often follow (Faber, 2007, pp. 12-16). This observation aligns with momentum research by Jegadeesh and Titman (1993), who documented that intermediate-term momentum persists across equity markets.
The GTAA5 strategy allocates capital equally across five diversified asset classes: domestic equities (SPY), international developed markets (EFA), aggregate bonds (AGG), commodities (DBC), and real estate investment trusts (VNQ). Each asset receives a twenty percent allocation when trading above its ten-month moving average. When an asset falls below this threshold, its allocation moves to short-term treasury bills (SHY), creating a dynamic cash position that scales with market risk (Cambria Investment Management, 2013).
The strategy's historical performance during market crises illustrates its function. During the 2008 financial crisis, traditional sixty-forty portfolios experienced drawdowns exceeding forty percent. The GTAA5 strategy limited losses to approximately twelve percent by reducing equity exposure as prices declined below their moving averages (Faber, 2013). This asymmetric return profile represents the strategy's primary characteristic.
This implementation uses monthly closing prices retrieved via request.security() to calculate the ten-month simple moving average. This distinction matters, as approximations using daily data (such as a 200-day moving average) can generate different signals during volatile periods. Monthly data ensures the indicator produces signals consistent with published academic research.
The indicator provides position monitoring, automatic rebalancing detection on either the first or last trading day of each month, and share calculations based on user-defined capital. A dashboard displays current trend status for each asset class, target versus actual weightings, and trade instructions for rebalancing. Performance metrics including annualized volatility and Sharpe ratio provide ongoing risk assessment.
Several limitations warrant acknowledgment. First, the strategy rebalances monthly, meaning it cannot respond to intra-month market crashes. Second, transaction costs and taxes from monthly rebalancing may reduce net returns for taxable accounts. Third, the ten-month lookback period, while historically robust, offers no guarantee of future effectiveness. As Ilmanen (2011) notes in "Expected Returns", all timing strategies face the risk of regime change, where historical relationships break down.
This indicator serves educational purposes and portfolio monitoring. It does not constitute financial advice.
References:
Cambria Investment Management (2013). Global Tactical Asset Allocation: An Introduction to the Approach. Research Report, Los Angeles.
Faber, M.T. (2007). A Quantitative Approach to Tactical Asset Allocation. Journal of Wealth Management, Spring 2007, pp. 9-79.
Faber, M.T. (2013). Global Asset Allocation: A Survey of the World's Top Asset Allocation Strategies. Cambria Investment Management, Los Angeles.
Ilmanen, A. (2011). Expected Returns: An Investor's Guide to Harvesting Market Rewards. John Wiley and Sons, Chichester.
Jegadeesh, N. and Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), pp. 65-91.
