Pivot Oscillator█ OVERVIEW
Pivot Oscillator is a versatile oscillator that measures market strength by comparing the current price to local price pivots. Values are scaled by ATR, normalized to a 0–100 range, and displayed along with an SMA line.
Oscillator: generates signals suitable for pullback strategies.
SMA line: serves as a momentum indicator.
█ CONCEPTS
Pivot Oscillator is designed with dual functionality:
- Oscillator & signals: ideal for pullback strategies, detecting local highs/lows and short-term reversals.
- SMA (Momentum): shows stable market-side dominance and filters price impulses.
Calculation logic:
- Oscillator = closing price − pivot line (derived from average high/low pivots).
Scaled by ATR and normalized to 0–100:
50 – bullish dominance,
< 50 – bearish dominance.
SMA is computed from smoothed oscillator values and serves as a momentum indicator.
█ FEATURES
Pivot Calculation:
- Pivot Length (lenSwing) – the number of bars used to identify local pivots (highs/lows). Higher values filter only larger extremes, while lower values make the oscillator react faster to local highs and lows.
- Pivot Level (pivotLevel) – determines the position of the pivot line between the average low and high pivots. A value of 0.5 places the pivotLine exactly halfway between the average high and low pivots; values closer to 0 or 1 shift the line toward the low or high pivots, respectively.
- Pivot Lookback (lookback) – the number of recent pivots used to calculate the average pivot, which smooths the pivotLine and reduces noise caused by individual extremes.
- Oscillator calculation: closing price − pivotLine (average of pivots computed from the above parameters).
The pivotLine is then scaled by ATR and normalized to a 0–100 range.
ATR Scaling:
- ATR period (atrLen)
- Multipliers (multUp / multDown) for upper and lower scaling.
Dynamic Colors:
- Oscillator > 50 → green (bullish)
- Oscillator < 50 → red (bearish)
SMA Line (Momentum):
- Smoothed oscillator (SMA) serves as a momentum indicator.
- Dynamic color indicates direction of SMA.
- Helps identify dominant market side and trend.
Overbought / Oversold Zones:
- Configurable OB/OS levels for both oscillator and SMA.
- Dynamic band colors: change depending on SMA relative to maOverbought / maOversold.
- Provides visual confirmation for potential corrections or strong momentum.
Gradients & Visualization:
- Oscillator and SMA gradients (3 layers) with adjustable transparency.
- Gradient visualization for OB/OS zones and oscillator.
- Full customization of colors, line width, and transparency.
Signals:
- Oscillator leaving oversold zone → long signal
- Oscillator leaving overbought zone → short signal
- OB/OS band colors dynamically reflect SMA levels for additional confirmation.
Alerts:
- OB/OS cross alerts.
█ HOW TO USE
Add the indicator to your TradingView chart → Indicators → search for “Pivot Oscillator”.
Parameter Configuration:
- Pivot Settings: pivot length, pivot level, pivot lookback.
- ATR Settings: ATR period, scaling multipliers.
- Threshold Levels: OB/OS levels for oscillator and SMA.
- Signal Settings: SMA length, extra smoothing.
- Style Settings: bullish/bearish colors, OB/OS lines, midline, text colors.
- Gradient Settings: enable/disable gradients and transparency.
Signal Interpretation:
BUY (Long):
- Oscillator leaves the oversold zone (OS crossover).
- OB/OS band color may additionally confirm the signal when SMA < maOversold.
SELL (Short):
- Oscillator leaves the overbought zone (OB crossunder).
- OB/OS band color may additionally confirm the signal when SMA > maOverbought.
█ APPLICATIONS
Pivot Oscillator and SMA can be scaled for different strategies:
- Pullback strategies: oscillator detects local highs/lows.
- Momentum / Trend: SMA shows market-side dominance and trend direction.
Adjust pivot and ATR parameters:
- Lower settings: faster reaction, suitable for scalping or intraday trading.
- Higher settings: more stable readings, suitable for swing trading or longer timeframes.
█ NOTES
- In strong trends, the oscillator may remain in extreme zones for extended periods – reflects dominance, not necessarily a reversal.
- OB/OS levels should be adapted to the instrument and pivot/ATR settings.
- Works best when combined with other tools: support/resistance, market structure, and volume analysis.
Oszillatoren
MACD-V Multi-Timeframe Confluence DashboardThis indicator identifies high-probability trade entries by analyzing momentum alignment across multiple timeframes using the MACD-V (Volatility Normalized MACD) formula. It features a fully customizable signal engine that allows traders to specify exactly which timeframes must agree before a trade signal is generated.
Optimized Defaults
By default, the indicator is tuned to the 5-minute, 15-minute, and 1-hour timeframes. We have found this specific combination performs best for identifying robust trends while filtering out noise. However, the strategy is fully flexible—users can easily adjust these settings to fit scalping (1m/5m) or swing trading (4H/Daily) styles.
Indicator Features
Dynamic Confluence: A Buy or Sell signal (displayed as a large + on the chart) is generated only when all selected timeframes are in agreement. This ensures you are trading with the dominant trend across multiple time scales.
Alternating Signal Filter: To prevent repetitive alerts during strong trends, the script uses a smart filter: a new Buy signal will only trigger if the last confirmed signal was a Sell (and vice versa).
Live Dashboard: An on-screen table displays the real-time status of every timeframe (Trend, Curl, and MACD Value). Timeframes currently active in your strategy are highlighted in yellow.
Local Entry Arrows (Optional): The script includes smaller red/green arrows that indicate simple MACD line crosses on the current chart's timeframe. These can be useful for precise timing but can be noisy in choppy markets. These are turned off by default to keep the chart clean, but can be enabled in the "Visuals" settings if you require granular entry signals.
How to Use
Check the Dashboard: Look for the yellow-highlighted rows in the table to see which timeframes are currently driving your signals.
Wait for the Cross (+): A green + indicates bullish momentum is aligned across all your chosen timeframes.
Refine (Optional): Turn on "Show Local Arrows" if you want to see the specific moment the MACD crosses on your current timeframe to fine-tune your entry.
Take Profit XTake Profit X
Take Profit X solves the #1 problem in trading: knowing when to exit. Instead of guessing or using single indicators, it aggregates 8 technical signals to identify high-probability exit points through multi-confirmation consensus. This eliminates premature exits and emotional decision-making.
The indicator counts confirmations from your chosen technical tools:
Green dot = Multiple signals say "take profit on longs/exit shorts"
Red dot = Multiple signals say "take profit on shorts/exit longs"
Signals appear when you reach the minimum confirmations threshold you set.
Possible Settings:
Conservative (Swing Trading)
pine
Minimum Confirmations: 4
Use: RSI, MACD, CCI, Supertrend, Price Action
Disable: Stochastic, Bollinger Bands, EMA Cross
Look Back Bars: 10
Aggressive (Day Trading)
pine
Minimum Confirmations: 2
Use: All indicators ON
Look Back Bars: 3-5
RSI OB/OS: 75/25
Balanced (Most Markets)
pine
Minimum Confirmations: 3
Use: RSI, MACD, CCI, Supertrend
Price Action: ON
Look Back Bars: 5-7
Dynamic MAs Zscore | Lyro RSThe Dynamic MAs Zscore is an adaptive momentum and valuation oscillator built around advanced moving averages and statistical Z-Score normalization. By combining a wide selection of moving average types with dynamic deviation bands, this indicator delivers clear insights into trend strength , directional bias , and relative valuation — all in a clean, visually intuitive format.
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Key Features
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Dynamic Moving Average Engine
Applies one of 12 selectable moving average types (SMA, EMA, WMA, VWMA, HMA, ALMA, TEMA, etc.) to the chosen source. This allows fine-tuning between responsiveness and smoothness depending on market conditions.
Z-Score Normalization
Transforms the selected moving average into a standardized Z-Score:
(MA − mean) / standard deviation
This normalization makes momentum strength comparable across assets and timeframes.
Adaptive Deviation Bands
Upper and lower bands are derived from the rolling standard deviation of the Z-Score:
Custom band length
Independent positive and negative multipliers
These bands dynamically expand and contract with volatility.
Dual Signal Modes
Trend Mode – Focuses on directional continuation. Color changes and signals occur when Z-Score breaks above or below deviation bands.
Valuation Mode – Highlights relative overvaluation and undervaluation using a gradient color scale and predefined value zones.
Advanced Visual System
Includes bold layered plots, gradient fills, background shading, and candle/bar coloring to clearly reflect current market state.
Custom Color Palettes
Choose from multiple preset themes (Classic, Mystic, Accented, Royal) or define your own bullish and bearish colors.
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How It Works
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MA Calculation – The selected moving average type is applied to the chosen price source.
Z-Score Computation – The MA is normalized over a user-defined lookback period to quantify deviation from its mean.
Band Construction – Standard deviation of the Z-Score is calculated over the band length and scaled by positive/negative multipliers.
Mode-Dependent Logic
Trend Mode – Breaks above the upper band signal bullish momentum; breaks below the lower band signal bearish momentum.
Valuation Mode – A gradient reflects relative valuation from undervalued to overvalued, with background highlights at extreme Z-Score levels.
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Signal Interpretation
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Trend Confirmation
In Trend Mode, sustained moves beyond deviation bands indicate strong directional bias.
Momentum Strength
The distance of the Z-Score from zero reflects the intensity of trend momentum.
Relative Valuation
In Valuation Mode, deep negative Z-Scores suggest undervaluation, while high positive Z-Scores suggest overvaluation.
Visual Clarity
Bar and candle coloring aligned with oscillator state allows for rapid assessment of market conditions.
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Customization
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Adjust MA type and length to balance speed vs. smoothness.
Modify Z-Score length to control sensitivity.
Tune band length and multipliers for volatility adaptation.
Switch between Trend and Valuation modes depending on strategy.
Personalize visuals using preset or custom color palettes.
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Alerts
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Bullish condition when Z-Score > 0
Bearish condition when Z-Score < 0
Overvalued and undervalued valuation alerts
⚠️ Disclaimer
This indicator is intended for technical analysis and educational purposes only. It does not guarantee profitable outcomes and should be used alongside other tools, confirmation methods, and sound risk management. The author is not responsible for any financial decisions made using this indicator.
Strategy with VWRSI and SAVE orders Long or Short or BothVWRSI is very powerful indicator coded by Algo Alpha and I Make Strategy of it
But there is no stop loss instate the Strategy is using Save orders to minimize the market manipulation
The best to used is side way market with long and short enable
The Strategy trigger long or short market order -
long - ta.crossover(rsi, 20)
short - ta.crossunder(rsi, 80)
And if is not take profit from the first trade start with the save trades until will do
the sum of the first order - base order and the save order can be adjust from the user
as well the deviation from the first order
IF some user have questions let me know
Resampling Reverse Engineering Bands XRREB X: Visual Oscillator Projection Bands
Based on the innovative "Resampling Reverse Engineering" concept pioneered by Donovan Wall, this enhanced script fixes the core mathematical symmetry and provides anchored, non-repainting bands for reliable analysis.
This indicator transforms any RSI, Stochastic, or CCI calculation directly onto your price chart as dynamic support/resistance bands. Instead of watching an oscillator below your chart, you see its overbought/oversold levels projected as price levels the market must reach.
RREB X reverses standard oscillator formulas to answer one question: "What price must the market reach for my chosen oscillator to hit an extreme level like RSI=70, Stoch=80, or CCI=100?" It then plots these levels as actionable bands.
Key Improvements
Adjustable Oscillator Values - While the original was hard coded the reverse engineered oscillator length which limited its usefulness, this script finally allows you to visualize any length oscillator as dynamic OB/OS regions directly on the chart.
Dynamic OB/OS levels: This version also lets you dynamically adjust the OB/OS levels location, making bands tighter or wider as your strategy demands.
Mathematical Symmetry: Outer bands are perfect mirrors, providing reliable projected levels.
Fixed Anchoring: Bands don't repaint historically, offering stable reference lines.
Direct Price Translation: Oscillator overbought/oversold conditions are visualized as clear price levels.
The Band Calculation Type switch lets you project different oscillator logics, each with unique characteristics for different market conditions.
RRSI - General trend & momentum. Change RSI Period (e.g., 7 for fast, 21 for slow). Adjust OB/OS (e.g., 80/20 for strong trends). The bands show the price needed to push your custom RSI into overbought/oversold territory.
RStoch - Ranging markets & short-term reversals. Focus on the Stochastic Period. The projected bands are highly sensitive to recent highs/lows. Excellent for spotting reversals at the edges of a range.
RCCI - Strong trends & volatile markets. Use a higher Outer Bands Multiplier. CCI's lack of upper/lower bounds means bands reflect extreme momentum shifts. Great for identifying explosive breakout or breakdown levels in trends.
Use Middle Band as Filter: Price above the white middle band suggests a bullish bias for long setups; below suggests bearish for shorts. Same as the 50 midline on the RSI or Stochastic or 0 for CCI.
Customizing the Calculation:
The power lies in changing the oscillator lengths that the bands reflect. Adjust these in the settings:
Change from 14 to 7 for faster, more reactive bands, or to 21 for slower, smoother bands.
Overbought/Oversold: Change from 70/30 to 80/20 for stronger-trend filters, or to 60/40 for more frequent signals.
Trading the Bands:
Bands as Dynamic S/R: The solid cyan (Upper 100) and magenta (Lower 0) bands act as dynamic support and resistance. A touch and reversal can signal a trade.
Gradient as Momentum: The colored fills between bands visually represent the "pressure" needed to reach the next oscillator level.
Middle Band as Trend Filter: Price above the white middle band suggests a bullish bias for long setups; below suggests bearish for short setups.
Ultimate Adaptive RSIUltimate Adaptive RSI
RSI That Adapts to Any Market
This isn't your grandpa's RSI. It dynamically adjusts its sensitivity based on market conditions—smoother in trends, responsive in ranges.
Traditional RSI fails in strong trends and changing volatility. UA-RSI fixes both by adapting its sensitivity in real-time, giving you reliable signals whether the market is trending, ranging, or transitioning between regimes.
How It Adapts:
Smart Pre-Smoothing: Uses Efficiency Ratio to detect trend strength and automatically lengthens/shortens its smoothing window.
Dominant Cycle Detection: Matches its internal period to the market's actual rhythm.
Dynamic Bands: RMS-based overbought/oversold levels that expand/contract with volatility.
Smoothing Stack: ALMA pre-smoothing → Ultimate Smoother → Jurik filter creates the cleanest RSI you've ever seen.
Trade Signals:
Buy: RSI crosses above lower band or midline + price confirms
Sell: RSI crosses below upper band or midline + price confirms
Bands expand in high volatility → wait for deeper extremes
Bands contract in low volatility → take earlier signals
Signal line for crossover entries
Adaptive smoothing = fewer false signals in trends
Day trading: Use 1.0 band multiplier
Swing trading: Use 1.2-1.5 multiplier
Ranging markets: Lower multiplier to 0.8
Trending markets: Raise multiplier to 1.5+
Bands widen in volatility = wait for deeper extremes
Bands tighten in calm markets = take earlier signals
Never trade RSI alone - always wait for price confirmation
RSI+Breadth Multi-Factor# RSI+ Breadth Multi-Factor Indicator
**Multi-factor scoring system for US market timing | 美股多因子择时评分系统**
[! (img.shields.io)](www.tradingview.com)
[! (img.shields.io)](www.tradingview.com)
[! (img.shields.io)](LICENSE)
---
## Overview | 概述
A quantitative indicator that combines **RSI**, **market breadth** (% above 20/50-day MA), and **up/down volume ratio** to generate actionable buy/sell signals for SPY, QQQ, and IWM.
这是一个结合 **RSI**、**市场广度**（站上20/50日均线比例）和 **涨跌成交量比** 的量化指标，为 SPY、QQQ 和 IWM 生成可操作的买卖信号。
---
## Features | 功能特点
| Feature | 功能 |
|---------|------|
| 🎯 Multi-factor scoring (-10 to +10) | 多因子评分系统 (-10 到 +10) |
| 📊 RSI + Breadth + Volume integration | RSI + 广度 + 成交量三重验证 |
| 🔀 Three markets: SPY, QQQ, IWM | 三大市场：SPY、QQQ、IWM |
| 🔥 Cross-market resonance detection | 跨市场共振信号检测 |
| 📈 Trend filter (MA-based) | 趋势过滤（均线判断） |
| ⏰ Auto-adapts to intraday timeframes | 自动适配日内时间周期 |
| 🎚️ Three modes: Aggressive/Standard/Conservative | 三种模式：激进/标准/保守 |
---
## Signal Reference | 信号说明
| Score | Emoji | Signal | 中文 | Action |
|:-----:|:-----:|--------|:----:|--------|
| ≥ 6 | 🚀 | **PANIC LOW** | 恐慌低点 | Strong buy 强烈买入 |
| ≥ 4 | 📈 | **BUY ZONE** | 低吸区 | Accumulate 分批建仓 |
| -3~3 | - | **HOLD** | 持有 | Hold position 持仓观望 |
| ≤ -4↑ | ⭐ | **ELEVATED** | 高估 | Hold cautious 持有但谨慎 |
| ≤ -4↓ | ⚡ | **CAUTION** | 观望 | Take profit 止盈 |
| ≤ -6↓ | ⚠️ | **REDUCE** | 减仓 | Reduce position 减少仓位 |
> **↑ = Uptrend** (price > MA) | **↓ = Downtrend** (price < MA)
### Resonance Signals | 共振信号
| Emoji | Signal | Description |
|:-----:|--------|-------------|
| 🔥 | Resonance Buy | Multiple markets in buy zone 多市场同时低吸 |
| ❄️ | Resonance Risk | Multiple markets in risk zone 多市场同时高估 |
---
## Scoring Logic | 评分逻辑
### Factors | 因子
| Factor | Weight | Buy Score | Sell Score |
|--------|--------|-----------|------------|
| **RSI** | 1x | RSI < 30 → +2, < 40 → +1 | RSI > 75 → -2, > 65 → -1 |
| **FI (50D MA%)** | Bottom focus | < 25% → +3, < 35% → +2 | > 85% → -2, > 78% → -1 |
| **TW (20D MA%)** | Top focus | < 30% → +1 | > 82% → -3, > 72% → -2 |
| **Volume Ratio** | 1x | UVOL/DVOL < 0.5 → +2 | > 2.5 → -2 |
### Breadth Symbols | 广度数据
| Market | TW Symbol | FI Symbol | Volume |
|--------|-----------|-----------|--------|
| SPY (S&P 500) | INDEX:S5TW | INDEX:S5FI | USI:UVOL/DVOL |
| QQQ (NASDAQ) | INDEX:NCTW | INDEX:NCFI | USI:UVOLQ/DVOLQ |
| IWM (Russell 2000) | INDEX:R2TW | INDEX:R2FI | USI:UVOL/DVOL |
---
## Settings | 设置说明
### Mode | 模式
- **Aggressive**: Lower thresholds, shorter cooldown (5 bars)
- **Standard**: Balanced defaults (10 bar cooldown)
- **Conservative**: Higher thresholds, longer cooldown (15 bars)
### Key Parameters | 关键参数
| Parameter | Default | Description |
|-----------|---------|-------------|
| RSI Length | 14 | RSI calculation period |
| Trend MA Length | 10 | MA for trend filter |
| Cooldown Bars | 10 | Min bars between same signals |
| Resonance Window | 3 | Bars to check for multi-market agreement |
| Min Markets | 2 | # of markets needed for resonance |
---
## Usage | 使用方法
### Installation | 安装
1. Copy the indicator code
2. In TradingView: **Pine Editor** → **New** → Paste code → **Add to Chart**
### Recommended Setup | 推荐设置
- **Timeframe**: Daily (D) for best accuracy | 推荐日线图
- **Markets**: Apply on SPY, QQQ, or IWM | 应用于SPY/QQQ/IWM
- **Mode**: Start with "Standard" | 建议从"标准"模式开始
### Intraday Mode | 日内模式
The indicator automatically detects intraday timeframes and adjusts:
- Uses only RSI + Volume factors (TW/FI are daily-only data)
- Lowers signal thresholds accordingly
指标会自动检测日内周期并调整：
- 仅使用 RSI + 成交量因子（TW/FI 仅有日线数据）
- 相应降低信号触发阈值
---
## Dashboard | 仪表盘
Displays real-time factor breakdown:
```
┌────────┬───────┬────────┐
│ Factor │ Score │ Weight │
├────────┼───────┼────────┤
│ RSI │ 1.0 │ 1x │
│ FI(50D)│ 2.0 │ Bottom │
│ TW(20D)│ -1.0 │ Top │
│ Vol │ 1.0 │ 1x │
│ Trend │ ↑ │ 10MA │
├────────┼───────┼────────┤
│ Total │ 3.0 │ HOLD │
└────────┴───────┴────────┘
```
---
## Alerts | 警报
Available alerts for each market (SPY/QQQ/IWM):
- Panic Low / Buy Zone (entry signals)
- Reduce / Caution (exit signals)
- Resonance Buy / Risk (cross-market confirmation)
每个市场（SPY/QQQ/IWM）可设置以下警报：
- 恐慌低点 / 低吸区（入场信号）
- 减仓 / 观望（出场信号）
- 共振买入 / 风险（跨市场确认）
---
## Trend Filter | 趋势过滤
**Key feature**: Risk signals (CAUTION/REDUCE) only trigger when **price is below the trend MA**.
When price is above MA (uptrend), the indicator shows **ELEVATED** ⭐ instead, preventing premature exits during strong rallies.
**核心功能**：风险信号（观望/减仓）仅在 **价格跌破趋势均线** 时触发。
当价格在均线之上（上升趋势）时，指标显示 **高估** ⭐，避免在强势上涨中过早离场。
---
## Disclaimer | 免责声明
This indicator is for **educational and informational purposes only**. It is not financial advice. Past performance does not guarantee future results. Always do your own research and consider your risk tolerance before trading.
本指标仅供 **教育和参考用途**，不构成投资建议。历史表现不代表未来收益。交易前请自行研究并考虑风险承受能力。
---
## License | 许可
MIT License - Free to use and modify with attribution.
MIT 许可证 - 可自由使用和修改，请注明出处。
---
## Author | 作者
Built with ❤️ for the trading community.
为交易社区精心打造 ❤️
[SM-021] Gaussian Trend System [Optimized]This script is a comprehensive trend-following strategy centered around a Gaussian Channel. It is designed to capture significant market movements while filtering out noise during consolidation phases. This version (v2) introduces code optimizations using Pine Script v6 Arrays and a new Intraday Time Control feature.
1. Core Methodology & Math
The foundation of this strategy is the Gaussian Filter, originally conceptualized by @DonovanWall.
Gaussian Poles: Unlike standard moving averages (SMA/EMA), this filter uses "poles" (referencing signal processing logic) to reduce lag while maintaining smoothness.
Array Optimization: In this specific iteration, the f_pole function has been refactored to utilize Pine Script Arrays. This improves calculation efficiency and rendering speed compared to recursive variable calls, especially when calculating deep historical data.
Channel Logic: The strategy calculates a "Filtered True Range" to create High and Low bands around the main Gaussian line.
Long Entry: Price closes above the High Band.
Short Entry: Price closes below the Low Band.
2. Signal Filtering (Confluence)
To reduce false signals common in trend-following systems, the strategy employs a "confluence" approach using three additional layers:
Baseline Filter: A 200-period (customizable) EMA or SMA acts as a regime filter. Longs are only taken above the baseline; Shorts only below.
ADX Filter (Volatility): The Average Directional Index (ADX) is used to measure trend strength. If the ADX is below a user-defined threshold (default: 20), the market is considered "choppy," and new entries are blocked.
Momentum Check: A Stochastic RSI check ensures that momentum aligns with the breakout direction.
3. NEW: Intraday Session Filter
Per user requests, a time-based filter has been added to restrict trading activity to specific market sessions (e.g., the New York Open).
How it works: Users can toggle a checkbox to enable/disable the filter.
Configuration: You can define a specific time range (Default: 09:30 - 16:00) and a specific Timezone (Default: New York).
Logic: The strategy longCondition and shortCondition now check if the current bar's timestamp falls within this window. If outside the window, no new entries are generated, though existing trades are managed normally.
4. Risk Management
The strategy relies on volatility-based exits rather than fixed percentage stops:
ATR Stop Loss: A multiple of the Average True Range (ATR) is calculated at the moment of entry to set a dynamic Stop Loss.
ATR Take Profit: An optional Reward-to-Risk (RR) ratio can be set to place a Take Profit target relative to the Stop Loss distance.
Band Exit: If the trend reverses and price crosses the opposite band, the trade is closed immediately to prevent large drawdowns.
Credits & Attribution
Original Gaussian Logic: Developed by @DonovanWalll. This script utilizes his mathematical formula for the pole filters.
Strategy Wrapper & Array Refactor: Developed by @sebamarghella.
Community Request: The Intraday Session Filter was added to assist traders focusing on specific liquidity windows.
Disclaimer: This strategy is for educational purposes. Past performance is not indicative of future results. Please use the settings menu to adjust the Session Time and Risk parameters to fit your specific asset class.
VixTrixVixTrix - Because markets move in both directions.
VixTrix was born from a fundamental limitation in traditional volatility indicators: they only measure downside panic, completely missing the greed-driven extremes that form market tops.
How It Works:
Dual-Component Analysis:
vixBear = Panic selling intensity (distance from recent highs)
vixBull = FOMO buying intensity (distance from recent lows)
Oscillator = vixBear - vixBull = Net fear/greed imbalance
When the oscillator is positive, fear dominates (potential bottom forming). When negative, greed dominates (potential top forming).
Professional-Grade Filtering:
The magic happens with the symmetric RMS (Root Mean Square) bands. Unlike fixed percentage bands or standard deviation, RMS:
Creates mathematically symmetric positive/negative thresholds
Naturally adapts to changing volatility regimes
Provides statistical significance to extremes
VixTrix also adds selectable MA smoothing for the RMS calculation:
WMA (default): Balanced – middle-ground approach
VWMA: Volume-weighted – filters low-volume noise
EMA: Responsive – catches quick reversals
SMA: Stable – for swing trading
HMA: Fast and smooth – ideal for day trading
Signals require triple confirmation:
Statistical Extreme: Oscillator beyond RMS band
Price Action Confirmation: Correct candle color (bullish for bottoms, bearish for tops)
Momentum Continuation: Oscillator still moving toward extreme (exhaustion)
This multi-filter approach reduces premature entries and false signals while maintaining early positioning at potential reversal points.
Why This Matters for Your Trading:
In bull markets, traditional fear indicators sit near zero, giving no warning of impending tops.
VixTrix identifies when greed becomes excessive – when FOMO buying reaches statistical extremes that often precede corrections.
In range-bound markets, VixTrix excels at identifying overreactions in both directions, providing high-probability mean reversion opportunities.
During crashes, it captures the panic selling with the same precision as VixFix, but with better timing through its momentum confirmation.
VixTrix spots continuations through:
"No Signal" = Healthy Trend – Oscillator stays between RMS bands (no exhaustion)
Failed Extremes – Touches band but no triple confirmation = trend likely continues
Hidden Divergence – Price makes higher low while oscillator makes shallower low = uptrend continues
Controlled Emotions – Oscillator negative but not extreme in uptrends (greed present but not excessive)
Key Insight: When VixTrix doesn't give a signal during a pullback, institutions aren't panicking – they're just pausing before resuming the trend.
Green columns = Bullish exhaustion (potential bottoms)
Red columns = Bearish exhaustion (potential tops)
Golden RMS bands = Dynamic thresholds adapting to current volatility
Background highlights = Active signal conditions
The Result: A professional-grade oscillator that works in all market conditions – trending up, trending down, or ranging – by measuring the complete emotional spectrum driving price action.
Density Zones (GM Crossing Clusters) + QHO Spin FlipsINDICATOR NAME
Density Zones (GM Crossing Clusters) + QHO Spin Flips
OVERVIEW
This indicator combines two complementary ideas into a single overlay: *this combines my earlier Geometric Mean Indicator with the Quantum Harmonic Oscillator (Overlay) with additional enhancements*
1) Density Zones (GM Crossing Clusters)
A “Density Zone” is detected when price repeatedly crosses a Geometric Mean equilibrium line (GM) within a rolling lookback window. Conceptually, this identifies regions where the market is repeatedly “snapping” across an equilibrium boundary—high churn, high decision pressure, and repeated re-selection of direction.
2) QHO Spin Flips (Regression-Residual σ Breaches)
A “Spin Flip” is detected when price deviates beyond a configurable σ-threshold (κ) from a regression-based equilibrium, using normalized residuals. Conceptually, this marks excursions into extreme states (decoherence / expansion), which often precede a reversion toward equilibrium and/or a regime re-scaling.
These two systems are related but not identical:
- Density Zones identify where equilibrium crossings cluster (a “singularity”/anchor behavior around GM).
- Spin Flips identify when price exceeds statistically extreme displacement from the regression equilibrium (LSR), indicating expansion beyond typical variance.
CORE CONCEPTS AND FORMULAS
SECTION A — GEOMETRIC MEAN EQUILIBRIUM (GM)
We define two moving averages:
(1) MA1_t = SMA(close_t, L1)
(2) MA2_t = SMA(close_t, L2)
We define the equilibrium anchor as the geometric mean of MA1 and MA2:
(3) GM_t = sqrt( MA1_t * MA2_t )
This GM line acts as an equilibrium boundary. Repeated crossings are interpreted as high “equilibrium churn.”
SECTION B — CROSS EVENTS (UP/DOWN)
A “cross event” is registered when the sign of (close - GM) changes:
Define a sign function s_t:
(4) s_t =
+1 if close_t > GM_t
-1 if close_t < GM_t
s_{t-1} if close_t == GM_t (tie-breaker to avoid false flips)
Then define the crossing event indicator:
(5) crossEvent_t = 1 if s_t != s_{t-1}
0 otherwise
Additionally, the indicator plots explicit cross markers:
- Cross Above GM: crossover(close, GM)
- Cross Below GM: crossunder(close, GM)
These provide directional visual cues and match the original Geometric Mean Indicator behavior.
SECTION C — DENSITY MEASURE (CROSSING CLUSTER COUNT)
A Density Zone is based on the number of cross events occurring in the last W bars:
(6) D_t = Σ_{i=0..W-1} crossEvent_{t-i}
This is a “crossing density” score: how many times price has toggled across GM recently.
The script implements this efficiently using a cumulative sum identity:
Let x_t = crossEvent_t.
(7) cumX_t = Σ_{j=0..t} x_j
Then:
(8) D_t = cumX_t - cumX_{t-W} (for t >= W)
cumX_t (for t < W)
SECTION D — DENSITY ZONE TRIGGER
We define a Density Zone state:
(9) isDZ_t = ( D_t >= θ )
where:
- θ (theta) is the user-selected crossing threshold.
Zone edges:
(10) dzStart_t = isDZ_t AND NOT isDZ_{t-1}
(11) dzEnd_t = NOT isDZ_t AND isDZ_{t-1}
SECTION E — DENSITY ZONE BOUNDS
While inside a Density Zone, we track the running high/low to display zone bounds:
(12) dzHi_t = max(dzHi_{t-1}, high_t) if isDZ_t
(13) dzLo_t = min(dzLo_{t-1}, low_t) if isDZ_t
On dzStart:
(14) dzHi_t := high_t
(15) dzLo_t := low_t
Outside zones, bounds are reset to NA.
These bounds visually bracket the “singularity span” (the churn envelope) during each density episode.
SECTION F — QHO EQUILIBRIUM (REGRESSION CENTERLINE)
Define the regression equilibrium (LSR):
(16) m_t = linreg(close_t, L, 0)
This is the “centerline” the QHO system uses as equilibrium.
SECTION G — RESIDUAL AND σ (FIELD WIDTH)
Residual:
(17) r_t = close_t - m_t
Rolling standard deviation of residuals:
(18) σ_t = stdev(r_t, L)
This σ_t is the local volatility/width of the residual field around the regression equilibrium.
SECTION H — NORMALIZED DISPLACEMENT AND SPIN FLIP
Define the standardized displacement:
(19) Y_t = (close_t - m_t) / σ_t
(If σ_t = 0, the script safely treats Y_t = 0.)
Spin Flip trigger uses a user threshold κ:
(20) spinFlip_t = ( |Y_t| > κ )
Directional spin flips:
(21) spinUp_t = ( Y_t > +κ )
(22) spinDn_t = ( Y_t < -κ )
The default κ=3.0 corresponds to “3σ excursions,” which are statistically extreme under a normal residual assumption (even though real markets are not perfectly normal).
SECTION I — QHO BANDS (OPTIONAL VISUALIZATION)
The indicator optionally draws the standard σ-bands around the regression equilibrium:
(23) 1σ bands: m_t ± 1·σ_t
(24) 2σ bands: m_t ± 2·σ_t
(25) 3σ bands: m_t ± 3·σ_t
These provide immediate context for the Spin Flip events.
WHAT YOU SEE ON THE CHART
1) MA1 / MA2 / GM lines (optional)
- MA1 (blue), MA2 (red), GM (green).
- GM is the equilibrium anchor for Density Zones and cross markers.
2) GM Cross Markers (optional)
- “GM↑” label markers appear on bars where close crosses above GM.
- “GM↓” label markers appear on bars where close crosses below GM.
3) Density Zone Shading (optional)
- Background shading appears while isDZ_t = true.
- This is the period where the crossing density D_t is above θ.
4) Density Zone High/Low Bounds (optional)
- Two lines (dzHi / dzLo) are drawn only while in-zone.
- These bounds bracket the full churn envelope during the density episode.
5) QHO Bands (optional)
- 1σ, 2σ, 3σ shaded zones around regression equilibrium.
- These visualize the current variance field.
6) Regression Equilibrium (LSR Centerline)
- The white centerline is the regression equilibrium m_t.
7) Spin Flip Markers
- A circle is plotted when |Y_t| > κ (beyond your chosen σ-threshold).
- Marker size is user-controlled (tiny → huge).
HOW TO USE IT
Step 1 — Pick the equilibrium anchor (GM)
- L1 and L2 define MA1 and MA2.
- GM = sqrt(MA1 * MA2) becomes your equilibrium boundary.
Typical choices:
- Faster equilibrium: L1=20, L2=50 (default-like).
- Slower equilibrium: L1=50, L2=200 (macro anchor).
Interpretation:
- GM acts like a “center of mass” between two moving averages.
- Crosses show when price flips from one side of equilibrium to the other.
Step 2 — Tune Density Zones (W and θ)
- W controls the time window measured (how far back you count crossings).
- θ controls how many crossings qualify as a “density/singularity episode.”
Guideline:
- Larger W = slower, broader density detection.
- Higher θ = only the most intense churn is labeled as a Density Zone.
Interpretation:
- A Density Zone is not “bullish” or “bearish” by itself.
- It is a condition: repeated equilibrium toggling (high churn / high compression).
- These often precede expansions, but direction is not implied by the zone alone.
Step 3 — Tune the QHO spin flip sensitivity (L and κ)
- L controls regression memory and σ estimation length.
- κ controls how extreme the displacement must be to trigger a spin flip.
Guideline:
- Smaller L = more reactive centerline and σ.
- Larger L = smoother, slower “field” definition.
- κ=3.0 = strong extreme filter.
- κ=2.0 = more frequent flips.
Interpretation:
- Spin flips mark when price exits the “normal” residual field.
- In your model language: a moment of decoherence/expansion that is statistically extreme relative to recent equilibrium.
Step 4 — Read the combined behavior (your key thesis)
A) Density Zone forms (GM churn clusters):
- Market repeatedly crosses equilibrium (GM), compressing into a bounded churn envelope.
- dzHi/dzLo show the envelope range.
B) Expansion occurs:
- Price can release away from the density envelope (up or down).
- If it expands far enough relative to regression equilibrium, a Spin Flip triggers (|Y| > κ).
C) Re-coherence:
- After a spin flip, price often returns toward equilibrium structures:
- toward the regression centerline m_t
- and/or back toward the density envelope (dzHi/dzLo) depending on regime behavior.
- The indicator does not guarantee return, but it highlights the condition where return-to-field is statistically likely in many regimes.
IMPORTANT NOTES / DISCLAIMERS
- This indicator is an analytical overlay. It does not provide financial advice.
- Density Zones are condition states derived from GM crossing frequency; they do not predict direction.
- Spin Flips are statistical excursions based on regression residuals and rolling σ; markets have fat tails and non-stationarity, so σ-based thresholds are contextual, not absolute.
- All parameters (L1, L2, W, θ, L, κ) should be tuned per asset, timeframe, and volatility regime.
PARAMETER SUMMARY
Geometric Mean / Density Zones:
- L1: MA1 length
- L2: MA2 length
- GM_t = sqrt(SMA(L1)*SMA(L2))
- W: crossing-count lookback window
- θ: crossing density threshold
- D_t = Σ crossEvent_{t-i} over W
- isDZ_t = (D_t >= θ)
- dzHi/dzLo track envelope bounds while isDZ is true
QHO / Spin Flips:
- L: regression + residual σ length
- m_t = linreg(close, L, 0)
- r_t = close_t - m_t
- σ_t = stdev(r_t, L)
- Y_t = r_t / σ_t
- spinFlip_t = (|Y_t| > κ)
Visual Controls:
- toggles for GM lines, cross markers, zone shading, bounds, QHO bands
- marker size options for GM crosses and spin flips
ALERTS INCLUDED
- Density Zone START / END
- Spin Flip UP / DOWN
- Cross Above GM / Cross Below GM
SUMMARY
This indicator treats the Geometric Mean as an equilibrium boundary and identifies “Density Zones” when price repeatedly crosses that equilibrium within a rolling window, forming a bounded churn envelope (dzHi/dzLo). It also models a regression-based equilibrium field and triggers “Spin Flips” when price makes statistically extreme σ-excursions from that field. Used together, Density Zones highlight compression/decision regions (equilibrium churn), while Spin Flips highlight extreme expansion states (σ-breaches), allowing the user to visualize how price compresses around equilibrium, releases outward, and often re-stabilizes around equilibrium structures over time.
Filtered TEMA CrossoverFiltered Dual TEMA Crossover
This indicator is a trend-following tool based on the classic Dual Triple Exponential Moving Average (TEMA) Crossover strategy, enhanced with two robust filters: the Chop Index and the Average Directional Index (ADX).
The TEMA is known for its low lag and high responsiveness, making the crossover an effective signal for trend reversals. However, trading TEMA crossovers during sideways, choppy markets often leads to false signals. This is where the filters come in.
Key Features
▪️Dual TEMA Crossover: Plots two customizable TEMA lines (Fast and Slow) for clear visualization of the primary trend direction.
▪️Intelligent Signal Filtering: Buy and Sell signals are generated only when the market confirms it is in a trending state, thanks to two integrated filters:
➖Chop Index Filter: Blocks signals when the market is detected as sideways or consolidating (Chop Index reading above a user-defined threshold).
➖ADX Filter: Ensures signals are only taken when the trend strength is sufficient (ADX reading above a user-defined minimum threshold).
▪️Customizable Signals: Full control over the signal shapes (Arrows, Triangles, etc.), colors, text, and size.
How to Use It
Use the Filtered Dual TEMA Crossover to enter positions on trend continuation or reversal while dramatically reducing exposure to low-quality, whipsawing signals common in non-trending environments.
Before the filters:
After the filters:
Minimize Noise. Maximize Clarity. Trade the Trend.
DeMarker (DeM)The DeMarker (DeM) indicator is a momentum oscillator designed to identify overbought and oversold conditions by comparing the most recent price extremes (highs and lows) to those of the previous candle. It moves between 0 and 1 and is especially useful for spotting potential trend reversals, exhaustion, and better-timed entries within larger trends.
How the DeMarker works
The DeMarker focuses on the relationship between today’s highs and lows and those of the previous bar:
• When price is pushing to new highs but not making significantly lower lows, DeM tends to rise toward 1, reflecting buying pressure and potential overbought conditions.
• When price is making lower lows but not significantly higher highs, DeM falls toward 0, reflecting selling pressure and potential oversold conditions.
Internally, the indicator measures the positive difference between the current high and the previous high (up-move strength) and the positive difference between the previous low and the current low (down-move strength). These values are smoothed over a user-defined period and combined into a ratio that keeps the output bounded between 0 and 1, making it easy to interpret visually.
Default settings and parameters
Typical default settings are aimed at providing a balance between responsiveness and noise reduction:
• Length: 14
• Overbought level: 0.7
• Oversold level: 0.3
With these settings, readings above 0.7 suggest that the market may be overheated to the upside, while readings below 0.3 suggest potential exhaustion on the downside. Traders can adjust these parameters depending on their style and the volatility of the asset.
Example configurations
Here are a few practical configurations that can be suggested to users:
• Swing trading setup:
• Length: 14–21
• Overbought: 0.7–0.75
• Oversold: 0.25–0.3
This works well on 4H and daily charts for spotting potential swing highs and lows.
• Short-term intraday setup:
• Length: 7–10
• Overbought: 0.8
• Oversold: 0.2
A shorter length increases sensitivity, better for 5–15 minute charts, but also increases the number of signals.
• Trend-following filter:
• Length: 20–30
• Overbought: 0.65–0.7
• Oversold: 0.3–0.35
This smoother configuration can be used together with moving averages to filter trades in the direction of the main trend.
Basic trading usage
Traders commonly use DeMarker in three main ways:
• Mean-reversion entries:
• Look for DeM below the oversold level (for example, 0.3 or 0.25) while price is approaching a support zone.
• Consider long entries when DeM turns back up and crosses above the oversold level, ideally confirmed by a bullish candle pattern or break of minor resistance.
• Taking profits or trimming positions:
• When DeM moves above the overbought level (for example, 0.7–0.8) near a known resistance level, traders may choose to take partial profits or tighten stops.
• A downward turn from overbought after a strong rally often signals momentum exhaustion.
• Divergence signals:
• Bullish divergence: price makes a lower low while DeM makes a higher low. This can hint at weakening downside momentum and a possible reversal upward.
• Bearish divergence: price makes a higher high while DeM makes a lower high. This can warn of weakening upside momentum before a pullback.
Combining with other tools
DeMarker often performs best as part of a confluence-based approach rather than as a standalone signal generator:
• Combine with trend filters:
• Use a moving average (for example, 50 or 200 EMA) to define trend direction and take DeM oversold entries only in uptrends, or overbought entries only in downtrends.
• Use with support/resistance and price action:
• Prioritize DeM signals that occur near well-defined horizontal levels, trendlines, or supply/demand zones.
• Add volume or volatility tools:
• Strong signals tend to appear when DeM reverses from extreme zones in sync with a volume spike or volatility contraction/expansion.
Relative Strength IndexRSI for indian market buy low and sell high.
rsi 3 low belo 15 buy and rsi high above 85 sell
Hicham tight/wild rangeHere’s a complete Pine Script indicator that draws colored boxes around different types of ranges!
Main features:
📦 Types of ranges detected:
Tight Range (30–60 pips): Gray boxes
Wild Range (80+ pips): Yellow boxes
Ichimoku Kijun OPTIMISED FOR 15MIN EURUSDWhen to Enter a Trade (The Kijun Bounce)
We only enter when the market is clearly trending and we get a good pullback to the Kijun-sen (the red line).
Market Quality Check (Anti-Chop):
The price must be completely outside the Ichimoku Cloud (Kumo). This ensures we are not trading in a choppy, sideways market.
Buy (Long) Entry:
The price (low of the candle) drops down and touches the Kijun-sen (red line).
The candle then closes above the Kijun-sen, confirming the trend is holding and the bounce is real.
Sell (Short) Entry:
The price (high of the candle) rises up and touches the Kijun-sen (red line).
The candle then closes below the Kijun-sen, confirming the downtrend is holding and the rejection is real.
How to Manage Risk and Exit
We use a fixed profit target (Take Profit) and a dynamic Stop Loss (Trailing Stop) that follows the Kijun-sen.
Risk per Trade:
We risk 1.0 percent of the total account equity per trade.
The initial Stop Loss distance is limited to 1.0 times the ATR, and is strictly capped at 1.0 percent of the price to prevent any single catastrophic loss.
Take Profit (TP):
The fixed profit target is set to a 1.5 Risk to Reward ratio (1.5 R:R) . This means the profit target is 1.5 times the size of the initial stop loss.
Stop Loss (SL):
The Stop Loss is a Trailing Stop that automatically moves with the Kijun-sen (red line).
The Stop Loss will trail slightly below the Kijun-sen for a Buy trade, and slightly above the Kijun-sen for a Sell trade, protecting profits dynamically as the trend continues.
Understanding the Trade Signals
🟢🟡 The Round Dots (Entry Signals)
The small, round dots are placed directly on the candle where the strategy decided to enter a trade. The color tells you the direction:
Lime Green Dot: Signals a confirmed Long (Buy) Entry. This happens on the candle where the price successfully bounced off the Kijun-sen (red line) and closed higher, and the market was outside the Kumo (the cloud).
Red Dot: Signals a confirmed Short (Sell) Entry. This happens on the candle where the price was successfully rejected by the Kijun-sen (red line) and closed lower, and the market was outside the Kumo.
⬆️⬇️ The Arrows (Exit Signals)
The arrows appear at the exact price level where the trade was closed (exited). The direction of the arrow indicates where the exit occurred relative to the market action, but the color is more important for determining the result:
Exit Arrow (Often Green/Red): This signals a trade was closed for one of two reasons:
Take Profit (Limit Hit): The trade moved in your favor and hit the fixed 1.5 R:R profit target. This is a successful, profitable exit.
Stop Loss (Trailing Stop Hit): The market reversed against the position, and the trade was closed by the dynamic Kijun-sen Trailing Stop. This is a risk-controlled loss or a break-even exit.
The size of these arrows is the default setting used by the strategy.exit() function in Pine Script to clearly mark the exit price on the chart.
In Summary
The dots tell you when to get in (Entry) based on the Kijun Reversion rule, and the arrows tell you when you got out (Exit) due to hitting either the target profit or the trailing stop loss.
RSI-ACCURATE+ (RSI + MACD + MA)UPDATED V5 Blah Blah Blah Blah Blah Blah Blah Blah Blah Blah Blah Blah
VEGA (Velocity of Efficient Gain Adaptation)VEGA (Velocity of Efficient Gain Adaptation)
VEGA is a momentum oscillator that measures the velocity of an efficiency-weighted adaptive moving average. Unlike traditional momentum indicators that react uniformly to all price movements, VEGA intelligently adapts its sensitivity based on market conditions—responding quickly during trending periods and filtering noise during consolidation.
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What Makes VEGA Different
Efficiency-Driven Adaptation
At its core, VEGA uses the Efficiency Ratio (ER) to distinguish between trending and choppy markets. When price moves efficiently in one direction, VEGA's underlying adaptive MA speeds up to capture the move. When price chops sideways, it slows down to avoid whipsaws. This creates a momentum reading that's inherently cleaner than fixed-period alternatives.
Linear Regression Smoothed Source
VEGA offers an optional LinReg-smoothed price source that blends regular candles with linear regression values. This pre-smoothing reduces noise before it ever enters the calculation, resulting in a histogram that's easier to read without sacrificing responsiveness. The mix ratio lets you dial in exactly how much smoothing you want.
Z-Score Normalization with Dead Zone
Rather than arbitrary oscillator bounds, VEGA normalizes output as standard deviations from the mean. This gives statistically meaningful levels: readings above +2σ or below -2σ represent genuinely extreme momentum. The configurable dead zone (with Snap, Soft Fade, or None modes) filters out insignificant movements near zero, keeping you focused on signals that matter.
--------------------------------
How It Works
1. Source Preparation — Price is smoothed via a LinReg/regular candle blend
2. Efficiency Ratio — Measures directional movement vs total movement over the lookback period
3. Adaptive MA — Applies variable smoothing based on efficiency (fast during trends, slow during chop)
4. Velocity — Calculates the rate of change of the adaptive MA
5. Normalization — Converts to Z-Score (standard deviations) or ATR-normalized percentage
6. Dead Zone — Optionally filters near-zero values to reduce noise
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How To Read VEGA
Signal and Interpretation
Histogram above zero | Bullish momentum
Histogram below zero | Bearish momentum
Bright color | Momentum accelerating
Faded color | Momentum decelerating
Beyond ±1σ bands | Above-average momentum
Beyond ±2σ bands | Extreme momentum (potential reversal zone)
Zero line cross*| Momentum shift
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Key Settings
ER Length — Lookback for efficiency ratio calculation. Higher = smoother, slower adaptation.
Fast/Slow Smoothing — Controls the adaptive MA's responsiveness range. The MA blends between these based on efficiency.
LinReg Settings — Enable smoothed candles and adjust the blend ratio (0 = regular candles, 1 = full LinReg, 0.5 = 50/50 mix).
Z-Score Lookback — Period for calculating mean and standard deviation. Shorter = more reactive normalization.
Dead Zone Type — How to handle near-zero values:
Snap — Hard cutoff to zero
Soft Fade — Gradual reduction toward zero
None — No filtering
Dead Zone Threshold — Values within this Z-Score range are affected by the dead zone setting.
VEGA works on any timeframe and any market. For best results, adjust the ER Length and LinReg settings to match your trading style and the volatility characteristics of your instrument.
SB - RSI EW OscillatorAdd EW with RSI.
Makes sense take a call if RSI is above 50 and EW turns green and vice versa.
Jurik Angle Flow [Kodexius]Jurik Angle Flow is a Jurik based momentum and trend strength oscillator that converts Jurik Moving Average behavior into an intuitive angle based flow gauge. Instead of showing a simple moving average line, this tool measures the angular slope of a smoothed Jurik curve, normalizes it and presents it as a bounded oscillator between plus ninety and minus ninety degrees.
The script uses two Jurik engines with different responsiveness, then blends their information into a single power score that drives both the oscillator display and the on chart gauge. This makes it suitable for identifying trend direction, trend strength, exhaustion conditions and early shifts in market structure. Built in divergence detection between price and the Jurik angle slope helps highlight potential reversal zones while bar coloring and a configurable no trade zone assist with visual filtering of choppy conditions.
🔹 Features
🔸 Dual Jurik slope engine
The indicator internally runs two Jurik Moving Average calculations on the selected source price. A slower Jurik stream models the primary trend while a faster Jurik stream reacts more quickly to recent changes. Their slopes are measured as angles in degrees, scaled by Average True Range so that the slope is comparable across different instruments and timeframes.
🔸 Angle based oscillator output
Both Jurik streams are converted into angle values by comparing the current value to a lookback value and normalizing by ATR. The result is passed through the arctangent function and expressed in degrees. This creates a smooth oscillator that directly represents steepness and direction of the Jurik curve instead of raw price distance.
🔸 Normalized power score
The angle values are transformed into a normalized score between zero and one hundred based on their absolute magnitude, then the sign of the angle is reapplied. This yields a symmetric score where extreme positive values represent strong bullish pressure and extreme negative values represent strong bearish pressure. The final power score is a weighted blend of the slow and fast Jurik scores.
🔸 Adaptive color gradients
The main oscillator area and the fast slope line use gradient colors that react to the angle strength and direction. Rising green tones reflect bullish angular momentum while red tones reflect bearish pressure. Neutral or shallow slopes remain visually softer to indicate indecision or consolidation.
🔸 Trend flip markers
Whenever the primary Jurik slope crosses through zero from negative to positive, an up marker is printed at the bottom of the oscillator panel. Whenever it crosses from positive to negative, a down marker is drawn at the top. These flips act as clean visual signals of potential trend initiation or termination.
🔸 Divergence detection on Jurik slope
The script optionally scans the fast Jurik slope for pivot highs and lows. It then compares those oscillator pivots against corresponding price pivots.
Regular bullish divergence is detected when the oscillator prints a higher low while price prints a lower low.
Regular bearish divergence is detected when the oscillator prints a lower high while price prints a higher high.
When detected, the tool draws matching divergence lines both on the oscillator and on the chart itself, making divergence zones easy to notice at a glance.
🔸 Bar coloring and no trade filter
Bars can be colored according to the primary Jurik slope gradient so that price bars reflect the same directional information as the oscillator. Additionally a configurable no trade threshold can visually mute bars when the absolute angle is small. This highlights trending sequences and visually suppresses noisy sideways stretches.
🔸 On chart power gauge
A creative on chart gauge displays the composite power score beside the current price action. It shows a vertical range from plus ninety to minus ninety with a filled block that grows proportionally to the normalized score. Color and label updates occur in real time and provide a quick visual summary of current Jurik flow strength without needing to read exact oscillator levels.
🔹 Calculations
Below are the main calculation blocks that drive the core logic of Jurik Angle Flow.
Jurik core update
method update(JMA self, float _src) =>
self.src := _src
float phaseRatio = self.phase < -100 ? 0.5 : self.phase > 100 ? 2.5 : self.phase / 100.0 + 1.5
float beta = 0.45 * (self.length - 1) / (0.45 * (self.length - 1) + 2)
float alpha = math.pow(beta, self.power)
if na(self.e0)
self.e0 := _src
self.e1 := 0.0
self.e2 := 0.0
self.jma := 0.0
self.e0 := (1 - alpha) * _src + alpha * self.e0
self.e1 := (_src - self.e0) * (1 - beta) + beta * self.e1
float prevJma = self.jma
self.e2 := (self.e0 + phaseRatio * self.e1 - prevJma) * math.pow(1 - alpha, 2) + math.pow(alpha, 2) * self.e2
self.jma := self.e2 + prevJma
self.jma
This method implements the Jurik Moving Average engine with internal state and phase control, producing a smooth adaptive value stored in self.jma.
Angle calculation in degrees
method getAngle(float src, int lookback=1) =>
float rad2degree = 180 / math.pi
float slope = (src - src ) / ta.atr(14)
float ang = rad2degree * math.atan(slope)
ang
The slope between the current value and a lookback value is divided by ATR, then converted from radians to degrees through the arctangent. This creates a volatility normalized angle oscillator.
Normalized score from angle
method normScore(float ang) =>
float s = math.abs(ang)
float p = s / 60.0 * 100.0
if p > 100
p := 100
p
The absolute angle is scaled so that sixty degrees corresponds to a score of one hundred. Values above that are capped, which keeps the final score within a fixed range. The sign is later reapplied to restore direction.
Slow and fast Jurik streams and power score
var JMA jmaSlow = JMA.new(jmaLen, jmaPhase, jmaPower, na, na, na, na, na)
var JMA jmaFast = JMA.new(jmaLen, jmaPhase, 2.0, na, na, na, na, na)
float jmaValue = jmaSlow.update(src)
float jmaFastValue = jmaFast.update(src)
float jmaSlope = jmaValue.getAngle()
float jmaFastSlope = jmaFastValue.getAngle()
float scoreJma = normScore(jmaSlope) * math.sign(jmaSlope)
float scoreJmaFast = normScore(jmaFastSlope) * math.sign(jmaFastSlope)
float totalScore = (scoreJma * 0.6 + scoreJmaFast * 0.4)
A slower Jurik and a faster Jurik are updated on each bar, each converted to an angle and then to a signed normalized score. The final composite power score is a weighted blend of the slow and fast scores, where the slow score has slightly more influence. This composite drives the on chart gauge and summarizes the overall Jurik flow.
Squeeze Momentum OscillatorTitle: Squeeze Momentum Oscillator
Description: This indicator is a panel-based oscillator designed to visualize the relationship between market volatility and momentum. Based on the classic TTM Squeeze concept, it helps traders identify periods of consolidation ("The Squeeze") and the subsequent release of energy ("The Breakout").
Originality & Enhancements: Standard squeeze oscillators only show when a squeeze fires (turning from red to green). This enhanced version adds a specific Breakout Validation layer. It changes the center-line dot color to Fuchsia or Blue only if the squeeze release is confirmed by the slope of the 20-period Moving Average, filtering out weak or false fires.
How It Works:
1. The Center Line (Volatility State): The dots along the zero line tell you the current volatility condition:
🔴 Red Dot: Squeeze ON. Bollinger Bands are inside Keltner Channels. Volatility is compressed. The market is charging up.
🟣 Fuchsia Dot: Bullish Breakout. The squeeze has fired upward, and the underlying trend (20 SMA slope) is positive.
🔵 Blue Dot: Bearish Breakout. The squeeze has fired downward, and the underlying trend (20 SMA slope) is negative.
🟢 Green Dot: Squeeze OFF. Normal volatility conditions.
2. The Histogram (Momentum): The bars indicate the strength and direction of the price movement using Linear Regression logic:
Cyan/Green: Bullish momentum. (Darker = weakening).
Red/Maroon: Bearish momentum. (Darker = weakening).
Visual Guide:
Setup: Wait for a series of Red Dots.
Trigger: Look for the first Fuchsia (Bullish) or Blue (Bearish) dot accompanied by an expanding Histogram in the same direction.
Settings:
Feature Toggle: You can turn the "Breakout Colors" (Fuchsia/Blue) on or off if you prefer the classic look.
Sensitivity: Fully customizable lengths and multipliers for Bollinger Bands and Keltner Channels.
Credits: Based on the foundational TTM Squeeze oscillator logic. Linear regression momentum calculation adapted from standard open-source methods. Breakout validation logic added for enhanced reliability.
Directional Movement Index (SHADED)Shaded red in between DMI lines when DMI- > DMI+
Shaded blue in between DMI lines when DMI+ > DMI-
RSI with Multi-Level OB/OS (65/70 & 35/30)With a revised 65 and 35 level for higher probability of winning
