Multi-Timeframe Anchored VWAP Valuation# Multi-Timeframe Anchored VWAP Valuation
## Overview
This indicator provides a unique perspective on potential price valuation by comparing the current price to the Volume Weighted Average Price (VWAP) anchored to the start of multiple timeframes: Weekly, Monthly, Quarterly, and Yearly. It synthesizes these comparisons into a single oscillator value, helping traders gauge if the current price is potentially extended relative to significant volume-weighted levels.
## Core Concept & Calculation
1. **Anchored VWAP:** The script calculates the VWAP separately for the current Week, Month, Quarter (3 Months), and Year (12 Months), starting the calculation from the first bar of each period.
2. **Price Deviation:** It measures how far the current `close` price is from each of these anchored VWAPs. This distance is measured in terms of standard deviations calculated *within* that specific anchor period (e.g., how many weekly standard deviations the price is away from the weekly VWAP).
3. **Deviation Score (Multiplier):** Based on this standard deviation distance, a score is assigned. The further the price is from the VWAP (in terms of standard deviations), the higher the absolute score. The indicator uses linear interpolation to determine scores between the standard deviation levels (defaulted at 1, 2, and 3 standard deviations corresponding to scores of +/-2, +/-3, +/-4, with a score of 1 at the VWAP).
4. **Timeframe Weighting:** Longer timeframes are considered more significant. The deviation scores are multiplied by fixed scalars: Weekly (x1), Monthly (x2), Quarterly (x3), Yearly (x4).
5. **Final Valuation Metric:** The weighted scores from all four timeframes are summed up to produce the final oscillator value plotted in the indicator pane.
## How to Interpret and Use
* **Histogram (Indicator Pane):**
* The main output is the histogram representing the `Final Valuation Metric`.
* **Positive Values:** Suggest the price is generally trading above its volume-weighted averages across the timeframes, potentially indicating strength or relative "overvaluation."
* **Negative Values:** Suggest the price is generally trading below its volume-weighted averages, potentially indicating weakness or relative "undervaluation."
* **Values Near Zero:** Indicate the price is relatively close to its volume-weighted averages.
* **Histogram Color:**
* The color of the histogram bars provides context based on the metric's *own recent history*.
* **Green (Positive Color):** The metric is currently *above* its recent average plus a standard deviation band (dynamic upper threshold). This highlights potentially significant "overvalued" readings relative to its normal range.
* **Red (Negative Color):** The metric is currently *below* its recent average minus a standard deviation band (dynamic lower threshold). This highlights potentially significant "undervalued" readings relative to its normal range.
* **Gray (Neutral Color):** The metric is within its typical recent range (between the dynamic upper and lower thresholds).
* **Orange Line:** Plots the moving average of the `Final Valuation Metric` itself (based on the "Threshold Lookback Period"), serving as the centerline for the dynamic thresholds.
* **On-Chart Table:**
* Provides a detailed breakdown for transparency.
* Shows the calculated VWAP, the raw deviation multiplier score, and the final weighted (adjusted) metric for each individual timeframe (W, M, Q, Y).
* Displays the current price, the final combined metric value, and a textual interpretation ("Overvalued", "Undervalued", "Neutral") based on the dynamic thresholds.
## Potential Use Cases
* Identifying potential exhaustion points when the indicator reaches statistically high (green) or low (red) levels relative to its recent history.
* Assessing whether price trends are supported by underlying volume-weighted average prices across multiple timeframes.
* Can be used alongside other technical analysis tools for confirmation.
## Settings
* **Calculation Settings:**
* `STDEV Level 1`: Adjusts the 1st standard deviation level (default 1.0).
* `STDEV Level 2`: Adjusts the 2nd standard deviation level (default 2.0).
* `STDEV Level 3`: Adjusts the 3rd standard deviation level (default 3.0).
* **Interpretation Settings:**
* `Threshold Lookback Period`: Defines the number of bars used to calculate the average and standard deviation of the final metric for dynamic thresholds (default 200).
* `Threshold StDev Multiplier`: Controls how many standard deviations above/below the metric's average are used to set the "Overvalued"/"Undervalued" thresholds (default 1.0).
* **Table Settings:** Customize the position and colors of the data table displayed on the chart.
## Important Considerations
* This indicator measures price deviation relative to *anchored* VWAPs and its *own historical range*. It is not a standalone trading system.
* The interpretation of "Overvalued" and "Undervalued" is relative to the indicator's logic and calculations; it does not guarantee future price movement.
* Like all indicators, past performance is not indicative of future results. Use this tool as part of a comprehensive analysis and risk management strategy.
* The anchored VWAP and Standard Deviation values reset at the beginning of each respective period (Week, Month, Quarter, Year).
"跨境通12月4日地天板" için komut dosyalarını ara
Intraday Macro & Flow Indicator# IntraMacroFlow Indicator
## Introduction
IntraMacroFlow is a volume and delta-based indicator that identifies significant price movements within trading sessions. It generates signals when volume spikes coincide with quality price movement, filtered by RSI to avoid overbought/oversold conditions.
> **Note:** This indicator provides multiple signals and should be combined with additional analysis methods such as support/resistance, trend direction, and price action patterns.
## Inputs
### Volume Settings
* **Volume Lookback Period** (14) - Number of bars for volume moving average calculation
* **Volume Threshold Multiplier** (1.5) - Required volume increase over average to generate signals
* **Delta Threshold** (0.3) - Required close-to-open movement relative to bar range (higher = stronger movement)
### Session Configuration
* **Use Dynamic Session Detection** (true) - Automatically determine session times
* **Highlight Market Open Period** (true) - Highlight first third of trading session
* **Highlight Mid-Session Period** (true) - Highlight middle portion of trading session
* **Detect Signals Throughout Whole Session** (true) - Find signals in entire session
* **Session Time** ("0930-1600") - Trading hours in HHMM-HHMM format
* **Session Type** ("Regular") - Select Regular, Extended, or Custom session
### Manual Session Settings
Used when dynamic detection is disabled:
* **Manual Session Open Hour** (9)
* **Manual Session Open Minute** (30)
* **Manual Session Open Duration** (60)
* **Manual Mid-Session Start Hour** (12)
* **Manual Mid-Session End Hour** (14)
## How It Works
The indicator analyzes each bar using three primary conditions:
1. **Volume Condition**: Current volume > Average volume × Threshold
2. **Delta Condition**: |Close-Open|/Range > Delta threshold
3. **Time Condition**: Bar falls within configured session times
When all conditions are met:
* Bullish signals appear when close > open and RSI < 70
* Bearish signals appear when close < open and RSI > 30
## Display Elements
### Shapes and Colors
* Green triangles below bars - Bullish signals
* Red triangles above bars - Bearish signals
* Blue background - Market open period
* Purple background - Mid-session period
* Bar coloring - Green (bullish), Red (bearish), or unchanged
### Information Panel
A dynamic label shows:
* Current volume relative to average (Vol)
* Delta value for current bar (Delta)
* RSI value (RSI)
* Session status (Active/Closed)
## Calculation Method
```
// Volume Condition
volumeMA = ta.sma(volume, lookbackPeriod)
volumeCondition = volume > volumeMA * volumeThreshold
// Delta Calculation (price movement quality)
priceRange = high - low
delta = math.abs(close - open) / priceRange
deltaCondition = delta > deltaThreshold
// Direction and RSI Filter
bullishBias = close > open and entrySignal and not (rsi > 70)
bearishBias = close < open and entrySignal and not (rsi < 30)
```
## Usage Recommendations
### Suitable Markets
* Equities during regular trading hours
* Futures markets
* Forex during active sessions
* Cryptocurrencies with defined volume patterns
### Recommended Timeframes
* 1-minute to 1-hour (optimal: 5 or 15-minute)
### Parameter Adjustments
* For fewer but stronger signals: increase Volume Threshold (2.0+) and Delta Threshold (0.4-0.6)
* For more signals: decrease Volume Threshold (1.2-1.5) and Delta Threshold (0.2-0.3)
### Usage Tips
* Combine with trend analysis for higher-probability entries
* Focus on signals occurring at session boundaries and mid-session
* Use opposite signals as potential exit points
* Configure alerts to receive notifications when signals occur
## Additional Notes
* RSI parameters are fixed at 14 periods with 70/30 thresholds
* The indicator handles overnight sessions correctly
* Fully compatible with TradingView alerts
* Customizable visual elements
## Release Notes
Initial release: This is a template indicator that should be customized to suit your specific trading strategies and preferences.
DEGA RMA | QuantEdgeB🧠 Introducing DEGA RMA (DGR ) by QuantEdgeB
🛠️ Overview
DEGA RMA (DGR) is a precision-engineered trend-following system that merges DEMA, Gaussian kernel smoothing, and ATR-based envelopes into a single, seamless overlay indicator. Its mission: to filter out market noise while accurately capturing directional bias using a layered volatility-sensitive trend core.
DGR excels at identifying valid breakouts, sustained momentum conditions, and trend-defining price behavior without falling into the trap of frequent signal reversals.
🔍 How It Works
1️⃣ Double Exponential Moving Average (DEMA)
The system begins by applying a DEMA to the selected price source. DEMA responds faster than a traditional EMA, making it ideal for capturing transitions in momentum.
2️⃣ Gaussian Filtering
A custom Gaussian kernel is used to smooth the DEMA signal. The Gaussian function applies symmetrical weights, centered around the most recent bar, effectively softening sharp price oscillations while preserving the underlying trend structure.
3️⃣ Recursive Moving Average (RMA) Core
The filtered Gaussian output is then processed through an RMA to generate a stable dynamic baseline. This baseline becomes the foundation for the final trend logic.
4️⃣ ATR-Scaled Breakout Zones
Upper and lower trend envelopes are calculated using a custom ATR filter built on DEMA-smoothed volatility.
• ✅ Long Signal when price closes above the upper envelope
• ❌ Short Signal when price closes below the lower envelope
• ➖ Neutral when inside the band (no signal noise)
✨ Key Features
🔹 Multi-Layer Trend Model
DEMA → Gaussian → RMA creates a signal structure that is both responsive and robust.
🔹 Volatility-Aware Entry System
Adaptive ATR bands adjust in real-time, expanding during high volatility and contracting during calm periods.
🔹 Noise-Reducing Gaussian Kernel
Sigma-adjustable kernel ensures signal smoothness without introducing excessive lag.
🔹 Clean Visual System
Candle coloring and band fills make trend state easy to read and act on at a glance.
⚙️ Custom Settings
• DEMA Source – Input source for trend core (default: close)
• DEMA Length – Length for initial smoothing (default: 30)
• Gaussian Filter Length – Determines smoothing depth (default: 4)
• Gaussian Sigma – Sharpness of Gaussian curve (default: 2.0)
• RMA Length – Core baseline smoothing (default: 12)
• ATR Length – Volatility detection period (default: 40)
• ATR Mult Up/Down – Controls the upper/lower threshold range for signals (default: 1.7)
📌 How to Use
1️⃣ Trend-Following Mode
• Go Long when price closes above the upper ATR band
• Go Short when price closes below the lower ATR band
• Remain neutral otherwise
2️⃣ Breakout Confirmation Tool
DGR’s ATR-based zone logic helps validate price breakouts and filter out false signals that occur inside compressed ranges.
3️⃣ Volatility Monitoring
Watch the ATR envelope width — a narrowing band often precedes expansion and potential directional shifts.
📌 Conclusion
DEGA RMA (DGR) is a thoughtfully constructed trend-following framework that goes beyond basic moving averages. Its Gaussian smoothing, adaptive ATR thresholds, and layered filtering logic provide a versatile solution for traders looking for cleaner signals, less noise, and real-time trend awareness.
Whether you're trading crypto, forex, or equities — DGR adapts to volatility while keeping your chart clean and actionable.
🔹 Summary
• ✅ Advanced Smoothing → DEMA + Gaussian + RMA = ultra-smooth trend core
• ✅ Volatility-Adjusted Zones → ATR envelope scaling removes whipsaws
• ✅ Fully Customizable → Tailor to any asset or timeframe
• ✅ Quant-Inspired Structure → Built for clarity, consistency, and confidence
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Gaussian Smooth Trend | QuantEdgeB🧠 Introducing Gaussian Smooth Trend (GST) by QuantEdgeB
🛠️ Overview
Gaussian Smooth Trend (GST) is an advanced volatility-filtered trend-following system that blends multiple smoothing techniques into a single directional bias tool. It is purpose-built to reduce noise, isolate meaningful price shifts, and deliver early trend detection while dynamically adapting to market volatility.
GST leverages the Gaussian filter as its core engine, wrapped in a layered framework of DEMA smoothing, SMMA signal tracking, and standard deviation-based breakout thresholds, producing a powerful toolset for trend confirmation and momentum-based decision-making.
🔍 How It Works
1️⃣ DEMA Smoothing Engine
The indicator begins by calculating a Double Exponential Moving Average (DEMA), which provides a responsive and noise-resistant base input for subsequent filtering.
2️⃣ Gaussian Filter
A custom Gaussian kernel is applied to the DEMA signal, allowing the system to detect smooth momentum shifts while filtering out short-term volatility.
This is especially powerful during low-volume or sideways markets where traditional MAs struggle.
3️⃣ SMMA Layer with Z-Filtering
The filtered Gaussian signal is then passed through a custom Smoothed Moving Average (SMMA). A standard deviation envelope is constructed around this SMMA, dynamically expanding/contracting based on market volatility.
4️⃣ Signal Generation
• ✅ Long Signal: Price closes above Upper SD Band
• ❌ Short Signal: Price closes below Lower SD Band
• ➖ No trade: Price stays within the band → market indecision
✨ Key Features
🔹 Multi-Stage Trend Detection
Combines DEMA → Gaussian Kernel → SMMA → SD Bands for robust signal integrity across market conditions.
🔹 Gaussian Adaptive Filtering
Applies a tunable sigma parameter for the Gaussian kernel, enabling you to fine-tune smoothness vs. responsiveness.
🔹 Volatility-Aware Trend Zones
Price must close outside of dynamic SD envelopes to trigger signals — reducing whipsaws and increasing signal quality.
🔹 Dynamic Color-Coded Visualization
Candle coloring and band fills reflect live trend state, making the chart intuitive and fast to read.
⚙️ Custom Settings
• DEMA Source: Price stream used for smoothing (default: close)
• DEMA Length: Period for initial exponential smoothing (default: 7)
• Gaussian Length / Sigma: Controls smoothing strength of kernel filter
• SMMA Length: Final smoothing layer (default: 12)
• SD Length: Lookback period for standard deviation filtering (default: 30)
• SD Mult Up / Down: Adjusts distance of upper/lower breakout zones (default: 2.5 / 1.8)
• Color Modes: Six distinct color palettes (e.g., Strategy, Warm, Cool)
• Signal Labels: Toggle on/off entry markers ("𝓛𝓸𝓷𝓰", "𝓢𝓱𝓸𝓻𝓽")
📌 Trading Applications
✅ Trend-Following → Enter on confirmed breakouts from Gaussian-smoothed volatility zones
✅ Breakout Validation → Use SD bands to avoid false breakouts during chop
✅ Volatility Compression Monitoring → Narrowing bands often precede large directional moves
✅ Overlay-Based Confirmation → Can complement other QuantEdgeB indicators like K-DMI, BMD, or Z-SMMA
📌 Conclusion
Gaussian Smooth Trend (GST) delivers a precision-built trend model tailored for modern traders who demand both clarity and control. The layered signal architecture, combined with volatility awareness and Gaussian signal enhancement, ensures accurate entries, clean visualizations, and actionable trend structure — all in real-time.
🔹 Summary Highlights
1️⃣ Multi-stage Smoothing — DEMA → Gaussian → SMMA for deep signal integrity
2️⃣ Volatility-Aware Filtering — SD bands prevent false entries
3️⃣ Visual Trend Mapping — Gradient fills + candle coloring for clean charts
4️⃣ Highly Customizable — Adapt to your timeframe, style, and volatility
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Z SMMA | QuantEdgeB📈 Introducing Z-Score SMMA (Z SMMA) by QuantEdgeB
🛠️ Overview
Z SMMA is a momentum-driven oscillator designed to track the standardized deviation of a Smoothed Moving Average (SMMA). By applying Z-score normalization, this tool dynamically adapts to price volatility, enabling traders to detect meaningful directional shifts and trend changes with enhanced clarity.
It serves both as a trend-following and mean-reversion system, identifying opportunities through standardized thresholds while remaining robust across volatile and calm market conditions.
✨ Key Features
🔹 Z-Score Normalization Engine
Applies Z-score to a custom SMMA baseline, allowing traders to compare price action relative to its recent volatility-adjusted mean.
🔹 Dynamic Trend Detection
Generates actionable long/short signals based on customizable Z-thresholds, making it adaptable across different asset classes and timeframes.
🔹 Overbought/Oversold Zones
Highlight reversion and profit-taking zones (default OB: +2 to +4, OS: -2 to -4), great for counter-trend or mean-reversion strategies.
🔹 Visual Reinforcement Tools
Includes candle coloring, gradient fills, and optional ALMA/EMA band overlays to visualize trend regime transitions.
🔍 How It Works
1️⃣ Z-Score SMMA Calculation
The core is a custom Smoothed Moving Average (SMMA) that is normalized by its standard deviation over a lookback period.
Final Formula:
Z = (SMMA - Mean) / StdDev
2️⃣ Signal Generation
• ✅ Long Bias: Z-Score > Long Threshold (default: 0)
• ❌ Short Bias: Z-Score < Short Threshold (default: 0)
3️⃣ Visual Aids
• Candle Color → Shows trend bias
• Band Fills → Highlight trend strength
• Overlays → Optional ALMA/EMA bands for structure analysis
⚙️ Custom Settings
• SMMA Length → Default: 12
• Z-Score Lookback → Default: 30
• Long Threshold → Default: 0
• Short Threshold → Default: 0
• Color Themes → Choose from 6 visual modes
• Extra Plots → Toggle advanced overlays (ALMA, EMA, bands)
• Label Display → Show/hide “𝓛𝓸𝓷𝓰” & “𝓢𝓱𝓸𝓻𝓽” markers
👥 Who Should Use It?
✅ Trend Traders → For early entries with confirmation from Z-score expansion
✅ Quantitative Analysts → Standardized deviation enables comparison across assets
✅ Mean-Reversion Traders → Use OB/OS zones to fade parabolic spikes
✅ Swing & Systematic Traders → Identify momentum shifts with optional ALMA/EMA overlays
📌 Conclusion
Z SMMA offers a smart, adaptive framework for tracking deviation from equilibrium in a quant-friendly format. Whether you're looking to follow trends or catch exhaustion points, Z SMMA provides a clear, standardized view of momentum and price extremes.
🔹 Key Takeaways:
1️⃣ Z-Score standardization ensures dynamic range awareness
2️⃣ SMMA base filters out noise, offering smoother signals
3️⃣ Color-coded visuals support faster reaction and cleaner charts
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before
MACD Volume Strategy (BBO + MACD State, Reversal Type)Overview
MACD Volume Strategy (BBO + MACD State, Reversal Type) is a momentum-based reversal system that combines MACD crossover logic with volume filtering to enhance signal accuracy and minimize noise. It aims to identify structural trend shifts and manage risk using predefined parameters.
※This strategy is for educational and research purposes only. All results are based on historical simulations and do not guarantee future performance.
Strategy Objectives
Identify early trend transitions with high probability
Filter entries using volume dynamics to validate momentum
Maintain continuous exposure using a reversal-style model
Apply a consistent 1:1.5 risk-to-reward ratio per trade
Key Features
Integrated MACD and volume oscillator filtering
Zero repainting (all signals confirmed on closed candles)
Automatic position flipping for seamless direction shifts
Stop-loss and take-profit based on recent structural highs/lows
Trading Rules
Long Entry Conditions
MACD crosses above the zero line (BBO Buy arrow)
Volume oscillator is positive (short EMA > long EMA)
MACD is above the signal line
Close any existing short and enter a new long
Short Entry Conditions
MACD crosses below the zero line (BBO Sell arrow)
Volume oscillator is positive
MACD is below the signal line
Close any existing long and enter a new short
Exit Rules
Take Profit (TP) = Entry ± (risk distance × 1.5)
Stop Loss (SL) = Recent swing low (for long) or high (for short)
Early Exit = Triggered when a reversal signal appears (flip logic)
Risk Management Parameters
Pair: ETH/USD
Timeframe: 10-minute
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pip
Risk per Trade: 5% of account equity (adjusted for sustainable practice)
Total Trades: 312 (backtest on selected dataset)
※Risk parameters are fully configurable and should be adjusted to suit each trader's personal setup and broker conditions.
Parameters & Configurations
Volume Short Length: 6
Volume Long Length: 12
MACD Fast Length: 11
MACD Slow Length: 21
Signal Smoothing: 10
Oscillator MA Type: SMA
Signal Line MA Type: SMA
Visual Support
Green arrow = Long entry
Red arrow = Short entry
MACD lines, signal line, and histogram
SL/TP markers plotted directly on the chart
Strategic Advantages & Uniqueness
Volume filtering eliminates low-participation, weak signals
Structurally aligned SL/TP based on recent market pivots
No repainting — decisions are made only on closed candles
Always in the market due to the reversal-style framework
Inspirations & Attribution
This strategy is inspired by the excellent work of:
Bitcoinblockchainonline – “BBO_Roxana_Signals MACD + vol”
Leveraging MACD zero-line cross and volume oscillator for intuitive signal generation.
HasanRifat – “MACD Fake Filter ”
Introduced a signal filter using MACD wave height averaging to reduce false positives.
This strategy builds upon those ideas to create a more automated, risk-aware, and technically adaptive system.
Summary
MACD Volume Strategy is a clean, logic-first automated trading system built for precision-seeking traders. It avoids discretionary bias and provides consistent signal logic under backtested historical conditions.
100% mechanical — no discretionary input required
Designed for high-confidence entries
Can be extended with filters, alerts, or trailing stops
※Strategy performance depends on market context. Past performance is not indicative of future results. Use with proper risk management and careful configuration.
MACD Boundary PSA - CoffeeKillerMACD Boundary PSA - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the MACD Boundary PSA indicator, a powerful market analysis tool developed by CoffeeKiller that enhances the traditional MACD with advanced boundary detection and peak signaling features.
🔔 **Warning: This Indicator Has No Signal Line or MACD Line** 🔔 This indicator is my version of the MACD, that I use in conjunction with the Rev&Line indicator.
Core Concept: Enhanced MACD Analysis
The foundation of this indicator builds upon the classic Moving Average Convergence Divergence (MACD) indicator, adding boundary tracking and peak detection systems to provide clearer signals and market insights.
Histogram Bars: Market Momentum
- Positive Green Bars: Bullish momentum
- Negative Red Bars: Bearish momentum
- Color intensity varies based on momentum strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during a bullish phase
- Low Marker Line (Cyan): Tracks the lowest point reached during a bearish phase
- Acts as dynamic boundaries that help identify strength of current moves
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important momentum peaks
- Helps identify potential reversal points and momentum exhaustion
Core Components
1. MACD Calculation
- Customizable fast and slow moving averages
- Signal line smoothing options
- Flexible MA type selection (SMA or EMA)
- Custom source input options
2. Boundary Tracking System
- Automatic detection of highest values in bullish phases
- Automatic detection of lowest values in bearish phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Time Resolution Control
- Normal mode: calculations based on chart timeframe
- Custom resolution mode: calculations based on specified timeframe
Main Features
Time Resolution Settings
- Normal mode: calculations match your chart's timeframe
- Custom resolution mode: calculations based on specified timeframe
- Helps identify stronger signals from other timeframes
Visual Elements
- Color-coded histogram bars
- Dynamic marker lines for boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for momentum strength
- Peak formation for potential reversals
- Color changes for momentum direction
Customization Options
- MA types and lengths
- Signal smoothing
- Color schemes
- Marker line visibility
- Peak background display options
Trading Applications
1. Trend Identification
- Histogram crossing above zero: bullish trend beginning
- Histogram crossing below zero: bearish trend beginning
- Histogram color: indicates momentum direction
- Consistent color intensity: trend strength
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Histogram approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing momentum
3. Momentum Analysis
- Histogram breaking above previous high boundary: accelerating bullish momentum
- Histogram breaking below previous low boundary: accelerating bearish momentum
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Distance from zero line: overall momentum magnitude
4. Market Structure Assessment
- Consecutive higher peaks: strengthening bullish structure
- Consecutive lower troughs: strengthening bearish structure
- Peak comparisons: relative strength of momentum phases
- Boundary line steps: market structure levels
Optimization Guide
1. MACD Settings
- Fast Length: Shorter values (8-12) for responsiveness, longer values (20+) for smoother signals
- Slow Length: Shorter values (21-34) for more signals, longer values (72+) for major moves
- Default settings (22, 72, 9): balanced approach for most timeframes
- Consider using 8, 21, 5 for shorter timeframes and 34, 144, 5 for longer timeframes
2. MA Type Selection
- EMA: More responsive, follows price more closely
- SMA: Smoother, fewer false signals, potentially more lag
- Mix and match for oscillator and signal lines based on your preference
3. Time Resolution
- Match chart timeframe: for aligned analysis
- Use higher timeframe: for filtering signals
- Lower timeframe: for earlier entries but more noise
4. Color Customization
- Normal bullish/bearish colors: represent standard momentum
- High/low marker line colors: customize visibility
- Peak marker colors: adjust for your visual preference
- Consider chart background when selecting colors
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm trend changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong momentum
- Use custom timeframe option for higher timeframe confirmation
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Custom resolution: allows comparison across timeframes
- Consider using multiple timeframes for confirmation
3. Market Context
- Strong bullish phase: positive histogram breaking above marker line
- Strong bearish phase: negative histogram breaking below marker line
- Histogram approaching zero: potential trend change
- Peak formations: potential exhaustion points
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with oscillators for overbought/oversold conditions
- Combine with volume analysis for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when histogram breaks above previous high marker line
- Enter short when histogram breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in bullish phases for shorting opportunities
- Look for consecutive higher troughs in bearish phases for buying opportunities
- Use zero-line crosses as confirmation
3. Multi-Timeframe Strategy
- Use custom resolution for higher timeframe MACD trend
- Enter trades when both timeframes align
- Higher timeframe for trend direction
- Chart timeframe for precise entry
4. Histogram Color Strategy
- Enter long when histogram turns bright green (increasing momentum)
- Enter short when histogram turns bright red (increasing momentum)
- Exit when color intensity fades (decreasing momentum)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Histogram crosses above zero line
- Green bars grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant momentum peaks
Bearish Market Scenario
- Histogram crosses below zero line
- Red bars grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant momentum troughs
Consolidation Scenario
- Histogram oscillates around zero line
- Bar colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Histogram values remain small
Understanding Market Dynamics Through MACD Boundary PSA
At its core, this indicator provides a unique lens to visualize market momentum and boundaries:
1. Momentum Strength: The histogram height/depth shows the strength of current momentum, with color intensity providing additional context about acceleration or deceleration.
2. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of momentum in both directions, helping to identify when markets are making new momentum extremes.
3. Exhaustion Signals: The peak detection system highlights moments where momentum has reached a local maximum or minimum, often precursors to reversals or consolidations.
4. Trend Confirmation: The histogram color and intensity provide instant feedback about the current trend direction and strength, with special colors highlighting particularly significant moves.
Remember:
- Combine signals from histogram, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences
- Consider market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
**DISCLAIMER**: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
Correlation Coefficient TableThis Pine Script generates a dynamic table for analyzing how multiple assets correlate with a chosen benchmark (e.g., NZ50G). Users can input up to 12 asset symbols, customize the benchmark, and define the beta calculation periods (e.g., 15, 30, 90, 180 days). The script calculates Correlation values for each asset over these periods and computes the average beta for better insights.
The table includes:
Asset symbols: Displayed in the first row.
Correlation values: Calculated for each defined period and displayed in subsequent columns.
Average Correlation: Presented in the final column as an overall measure of correlation strength.
Color coding: Background colors indicate beta magnitude (green for high positive beta, yellow for near-neutral beta, red for negative beta).
Reversal + Confirm ZonesThis script is written in Pine Script (version 5) for TradingView and creates an indicator called **"Reversal + Confirm Zones"**. It overlays visual zones on a price chart to identify potential reversal points and confirmation signals for trading. The indicator combines **Bollinger Bands** and **RSI** to detect overbought/oversold conditions (reversal zones) and uses **EMA crosses** and **MACD zero-line crosses** to confirm bullish or bearish trends. Below is a detailed explanation:
---
### **1. Purpose**
- The script highlights:
- **Reversal Zones**: Areas where the price might reverse due to being overbought (green) or oversold (red).
- **Confirmation Zones**: Areas where a trend reversal is confirmed using EMA and MACD signals (green for bullish, red for bearish).
- It provides visual backgrounds and alerts to assist traders in spotting potential trade setups.
---
### **2. Components**
The script is divided into two main parts: **Reversal Logic** and **Confirmation Logic**.
---
### **3. Reversal Logic (Red & Green Zones)**
#### **Bollinger Bands**
- **Parameters**:
- Length: 20 periods.
- Source: Closing price (`close`).
- Multiplier: 2.0 (standard deviations).
- **Calculation**:
- `basis`: 20-period Simple Moving Average (SMA).
- `dev`: 2 times the standard deviation of the price over 20 periods.
- `upper`: `basis + dev` (upper band).
- `lower`: `basis - dev` (lower band).
- **Purpose**: Identifies when the price moves outside the normal range (beyond 2 standard deviations).
#### **Relative Strength Index (RSI)**
- **Parameters**:
- Length: 14 periods.
- Low Threshold: 30 (oversold).
- High Threshold: 70 (overbought).
- **Calculation**: `rsiValue = ta.rsi(close, rsiLength)`.
- **Purpose**: Measures momentum to confirm overbought or oversold conditions.
#### **Zone Conditions**
- **Red Zone (Oversold)**:
- Condition: `close < lower` (price below lower Bollinger Band) AND `rsiValue < rsiLowThreshold` (RSI < 30).
- Visual: Light red background (`color.new(color.red, 80)`).
- Alert: "Deep Oversold Signal triggered!".
- **Green Zone (Overbought)**:
- Condition: `close > upper` (price above upper Bollinger Band) AND `rsiValue > rsiHighThreshold` (RSI > 70).
- Visual: Light green background (`color.new(color.green, 80)`).
- Alert: "Deep Overbought Signal triggered!".
#### **Interpretation**
- Red Zone: Suggests the price is oversold and may reverse upward.
- Green Zone: Suggests the price is overbought and may reverse downward.
---
### **4. Confirmation Logic (EMA and MACD Crosses)**
#### **Exponential Moving Averages (EMAs)**
- **Parameters**:
- Short EMA Length: 9 periods (user adjustable).
- Long EMA Length: 21 periods (user adjustable).
- **Calculation**:
- `emaShort = ta.ema(close, emaShortLength)`.
- `emaLong = ta.ema(close, emaLongLength)`.
- **Conditions**:
- **Bullish EMA Cross**: `emaCrossBullish = ta.crossover(emaShort, emaLong)` (9 EMA crosses above 21 EMA).
- **Bearish EMA Cross**: `emaCrossBearish = ta.crossunder(emaShort, emaLong)` (9 EMA crosses below 21 EMA).
#### **MACD**
- **Parameters**:
- Fast Length: 12 periods (user adjustable).
- Slow Length: 26 periods (user adjustable).
- Signal Smoothing: 9 periods (user adjustable).
- **Calculation**:
- ` = ta.macd(close, macdFastLength, macdSlowLength, macdSignalSmoothing)`.
- Only the MACD line and signal line are used; the histogram is ignored (`_`).
- **Conditions**:
- **Bullish MACD Cross**: `macdCrossBullish = ta.crossover(macdLine, 0)` (MACD crosses above zero).
- **Bearish MACD Cross**: `macdCrossBearish = ta.crossunder(macdLine, 0)` (MACD crosses below zero).
#### **Combined Confirmation Conditions**
- **Bullish Confirmation**:
- Condition: `bullishConfirmation = emaCrossBullish and macdCrossBullish`.
- Visual: Very light green background (`color.new(color.green, 90)`).
- Meaning: A bullish trend is confirmed when the 9 EMA crosses above the 21 EMA AND the MACD crosses above zero.
- **Bearish Confirmation**:
- Condition: `bearishConfirmation = emaCrossBearish and macdCrossBearish`.
- Visual: Very light red background (`color.new(color.red, 90)`).
- Meaning: A bearish trend is confirmed when the 9 EMA crosses below the 21 EMA AND the MACD crosses below zero.
---
### **5. Visual Outputs**
- **Reversal Zones**:
- Red background for oversold conditions.
- Green background for overbought conditions.
- **Confirmation Zones**:
- Light green background for bullish confirmation.
- Light red background for bearish confirmation.
- Note: The script does not plot the Bollinger Bands, EMAs, or MACD lines—only the background zones are visualized.
---
### **6. Alerts**
- **Deep Oversold Alert**: Triggers when the red zone condition is met.
- **Deep Overbought Alert**: Triggers when the green zone condition is met.
- No alerts are set for the confirmation zones (EMA/MACD crosses).
---
### **7. How It Works**
1. **Reversal Detection**:
- The script uses Bollinger Bands and RSI to flag extreme price levels (red for oversold, green for overbought).
- These zones suggest potential reversals but are not confirmed yet.
2. **Trend Confirmation**:
- EMA crosses (9/21) and MACD zero-line crosses provide confirmation of a trend direction.
- Bullish confirmation (green) occurs when both indicators align upward.
- Bearish confirmation (red) occurs when both indicators align downward.
3. **Trading Strategy**:
- Look for a red zone (oversold) followed by a bullish confirmation for a potential long entry.
- Look for a green zone (overbought) followed by a bearish confirmation for a potential short entry.
---
### **8. How to Use**
1. Add the script to TradingView.
2. Adjust inputs (EMA lengths, MACD settings) if desired.
3. Monitor the chart:
- Red zones indicate oversold conditions—watch for a potential upward reversal.
- Green zones indicate overbought conditions—watch for a potential downward reversal.
- Light green/red backgrounds confirm the trend direction after a reversal zone.
4. Set up alerts for oversold/overbought conditions to catch reversal signals early.
---
### **9. Key Features**
- **Dual Purpose**: Combines reversal detection (Bollinger Bands + RSI) with trend confirmation (EMA + MACD).
- **Visual Simplicity**: Uses background colors instead of plotting lines, keeping the chart clean.
- **Customizable**: Allows users to tweak EMA and MACD periods.
- **Alerts**: Notifies users of extreme conditions for timely action.
---
### **10. Limitations**
- No plotted indicators (e.g., Bollinger Bands, EMAs, MACD) for visual reference—relies entirely on background shading.
- Confirmation signals (EMA/MACD) may lag behind reversal zones, potentially missing fast reversals.
- No alerts for confirmation zones, limiting real-time notification of trend confirmation.
This script is ideal for traders who want a straightforward way to spot potential reversals and confirm them with trend-following indicators, all overlaid on the price chart.
Moving Average Convergence DivergenceThis script is written in Pine Script (version 6) for TradingView and implements the **Moving Average Convergence Divergence (MACD)** indicator. The MACD is a popular momentum oscillator used to identify trend direction, strength, and potential reversals. This version includes customizable inputs, visual enhancements (like crossover markers), and alerts for key events. Below is a detailed explanation of the script:
---
### **1. Purpose**
- The script calculates and displays the MACD line, signal line, and histogram.
- It highlights key events such as MACD/signal line crossovers and zero-line crosses with shapes and colors.
- It provides alerts for changes in the histogram's direction (rising to falling or vice versa).
---
### **2. User Inputs**
- **Fast Length**: Period for the fast moving average (default: 12).
- **Slow Length**: Period for the slow moving average (default: 26).
- **Source**: Data input for calculation (default: closing price, `close`).
- **Signal Smoothing**: Period for the signal line (default: 9, range: 1–50).
- **Oscillator MA Type**: Type of moving average for MACD calculation (options: SMA or EMA, default: EMA).
- **Signal Line MA Type**: Type of moving average for the signal line (options: SMA or EMA, default: EMA).
---
### **3. MACD Calculation**
The MACD is calculated in three parts:
1. **MACD Line**: Difference between the fast and slow moving averages.
- Fast MA: Either SMA or EMA of the source over `fast_length`.
- Slow MA: Either SMA or EMA of the source over `slow_length`.
- Formula: `macd = fast_ma - slow_ma`.
2. **Signal Line**: A moving average (SMA or EMA) of the MACD line over `signal_length`.
- Formula: `signal = sma_signal == "SMA" ? ta.sma(macd, signal_length) : ta.ema(macd, signal_length)`.
3. **Histogram**: Difference between the MACD line and the signal line.
- Formula: `hist = macd - signal`.
---
### **4. Key Events Detection**
#### **MACD/Signal Line Crossovers**
- **Bullish Cross**: MACD crosses above the signal line (`ta.crossover(macd, signal)`).
- **Bearish Cross**: MACD crosses below the signal line (`ta.crossunder(macd, signal)`).
#### **Zero Line Crosses**
- **Cross Above Zero**: MACD crosses above 0 (`ta.crossover(macd, 0)`).
- **Cross Below Zero**: MACD crosses below 0 (`ta.crossunder(macd, 0)`).
---
### **5. Colors**
- **MACD Line**: Green (#089981) if MACD > signal (bullish), red (#f23645) if MACD < signal (bearish).
- **Signal Line**: White (`color.white`).
- **Histogram**:
- Positive (MACD > signal): Light green (#B2DFDB) if decreasing, darker green (#26A69A) if increasing.
- Negative (MACD < signal): Light red (#FFCDD2) if increasing in magnitude, darker red (#FF5252) if decreasing in magnitude.
- **Zero Line**: Gray with 50% transparency (`color.new(#787B86, 50)`).
---
### **6. Visual Outputs**
#### **Plotted Lines**
- **MACD Line**: Plotted with dynamic coloring based on its position relative to the signal line.
- **Signal Line**: Plotted in white.
- **Histogram**: Displayed as columns, with colors indicating direction and momentum.
- **Zero Line**: Horizontal line at 0 for reference.
#### **Shapes for Key Events**
- **Bullish Cross Below Zero**: Green circle on the MACD line when MACD crosses above the signal line while still below zero.
- **Bearish Cross Above Zero**: Red circle on the MACD line when MACD crosses below the signal line while still above zero.
- **Cross Above Zero**: Green upward label at the zero line when MACD crosses above 0.
- **Cross Below Zero**: Red downward label at the zero line when MACD crosses below 0.
---
### **7. Alerts**
- **Rising to Falling**: Triggers when the histogram switches from positive (or zero) to negative.
- Condition: `hist >= 0 and hist < 0`.
- Message: "MACD histogram switched from rising to falling".
- **Falling to Rising**: Triggers when the histogram switches from negative (or zero) to positive.
- Condition: `hist <= 0 and hist > 0`.
- Message: "MACD histogram switched from falling to rising".
---
### **8. How It Works**
1. **Trend Direction**:
- MACD above signal line (green) suggests bullish momentum.
- MACD below signal line (red) suggests bearish momentum.
2. **Momentum Strength**:
- Histogram height shows the strength of the momentum (larger bars = stronger momentum).
- Histogram color changes indicate whether momentum is increasing or decreasing.
3. **Reversal Signals**:
- Crossovers between MACD and signal lines often signal potential trend changes.
- Zero-line crosses indicate shifts between bullish (above 0) and bearish (below 0) territory.
---
### **9. How to Use**
1. Add the script to TradingView.
2. Adjust inputs (e.g., fast/slow lengths, MA types) to suit your trading style.
3. Monitor the chart:
- Green MACD and upward histogram bars suggest bullish conditions.
- Red MACD and downward histogram bars suggest bearish conditions.
- Watch for circles (crossovers) and labels (zero-line crosses) for trade signals.
4. Set up alerts to notify you of histogram direction changes.
---
### **10. Key Features**
- **Customization**: Flexible MA types and periods.
- **Visual Clarity**: Dynamic colors and shapes highlight key events.
- **Alerts**: Notifies users of momentum shifts via histogram changes.
- **Intuitive**: Combines all MACD components (line, signal, histogram) in one indicator.
This script is ideal for traders who rely on MACD for momentum analysis and want clear visual cues and alerts for decision-making.
Composite Reversal IndicatorOverview
The "Composite Reversal Indicator" aggregates five technical signals to produce a composite score that ranges from -5 (strongly bearish) to +5 (strongly bullish). These signals come from:
Relative Strength Index (RSI)
Moving Average Convergence Divergence (MACD)
Accumulation/Distribution (A/D)
Volume relative to its moving average
Price proximity to support and resistance levels
Each signal contributes a value of +1 (bullish), -1 (bearish), or 0 (neutral) to the total score. The raw score is plotted as a histogram, and a smoothed version is plotted as a colored line to highlight trends.
Step-by-Step Explanation
1. Customizable Inputs
The indicator starts with user-defined inputs that allow traders to tweak its settings. These inputs include:
RSI: Length (e.g., 14), oversold level (e.g., 30), and overbought level (e.g., 70).
MACD: Fast length (e.g., 12), slow length (e.g., 26), and signal length (e.g., 9).
Volume: Moving average length (e.g., 20) and multipliers for high (e.g., 1.5) and low (e.g., 0.5) volume thresholds.
Price Levels: Period for support and resistance (e.g., 50) and proximity percentage (e.g., 2%).
Score Smoothing: Length for smoothing the score (e.g., 5).
These inputs make the indicator adaptable to different trading styles, assets, or timeframes.
2. Indicator Calculations
The script calculates five key indicators using the input parameters:
RSI: Measures momentum and identifies overbought or oversold conditions.
Formula: rsi = ta.rsi(close, rsi_length)
Example: With a length of 14, it analyzes the past 14 bars of closing prices.
MACD: Tracks trend and momentum using two exponential moving averages (EMAs).
Formula: = ta.macd(close, macd_fast, macd_slow, macd_signal)
Components: MACD line (fast EMA - slow EMA), signal line (EMA of MACD line).
Accumulation/Distribution (A/D): A volume-based indicator showing buying or selling pressure.
Formula: ad = ta.accdist
Reflects cumulative flow based on price and volume.
Volume Moving Average: A simple moving average (SMA) of trading volume.
Formula: vol_ma = ta.sma(volume, vol_ma_length)
Example: A 20-bar SMA smooths volume data.
Support and Resistance Levels: Key price levels based on historical lows and highs.
Formulas:
support = ta.lowest(low, price_level_period)
resistance = ta.highest(high, price_level_period)
Example: Over 50 bars, it finds the lowest low and highest high.
These calculations provide the raw data for generating signals.
3. Signal Generation
Each indicator produces a signal based on specific conditions:
RSI Signal:
+1: RSI < oversold level (e.g., < 30) → potential bullish reversal.
-1: RSI > overbought level (e.g., > 70) → potential bearish reversal.
0: Otherwise.
Logic: Extreme RSI values suggest price may reverse.
MACD Signal:
+1: MACD line > signal line → bullish momentum.
-1: MACD line < signal line → bearish momentum.
0: Equal.
Logic: Crossovers indicate trend shifts.
A/D Signal:
+1: Current A/D > previous A/D → accumulation (bullish).
-1: Current A/D < previous A/D → distribution (bearish).
0: Unchanged.
Logic: Rising A/D shows buying pressure.
Volume Signal:
+1: Volume > high threshold (e.g., 1.5 × volume MA) → strong activity (bullish).
-1: Volume < low threshold (e.g., 0.5 × volume MA) → weak activity (bearish).
0: Otherwise.
Logic: Volume spikes often confirm reversals.
Price Signal:
+1: Close near support (within proximity %, e.g., 2%) → potential bounce.
-1: Close near resistance (within proximity %) → potential rejection.
0: Otherwise.
Logic: Price near key levels signals reversal zones.
4. Composite Score
The raw composite score is the sum of the five signals:
Formula: score = rsi_signal + macd_signal + ad_signal + vol_signal + price_signal
Range: -5 (all signals bearish) to +5 (all signals bullish).
Purpose: Combines multiple perspectives into one number.
5. Smoothed Score
A smoothed version of the score reduces noise:
Formula: score_ma = ta.sma(score, score_ma_length)
Example: With a length of 5, it averages the score over 5 bars.
Purpose: Highlights the trend rather than short-term fluctuations.
6. Visualization
The indicator plots two elements:
Raw Score: A gray histogram showing the composite score per bar.
Style: plot.style_histogram
Color: Gray.
Smoothed Score: A line that changes color:
Green: Score > 0 (bullish).
Red: Score < 0 (bearish).
Gray: Score = 0 (neutral).
Style: plot.style_line, thicker line (e.g., linewidth=2).
These visuals make it easy to spot potential reversals.
How It Works Together
The indicator combines signals from:
RSI: Momentum extremes.
MACD: Trend shifts.
A/D: Buying/selling pressure.
Volume: Confirmation of moves.
Price Levels: Key reversal zones.
By summing these into a composite score, it filters out noise and provides a unified signal. A high positive score (e.g., +3 to +5) suggests a bullish reversal, while a low negative score (e.g., -3 to -5) suggests a bearish reversal. The smoothed score helps traders focus on the trend.
Practical Use
Bullish Reversal: Smoothed score is green and rising → look for buying opportunities.
Bearish Reversal: Smoothed score is red and falling → consider selling or shorting.
Neutral: Score near 0 → wait for clearer signals.
Traders can adjust inputs to suit their strategy, making it versatile for stocks, forex, or crypto.
Master Global Liquidity Shifted 75 DaysThe Global Liquidity Index is a Pine Script (version 5) technical indicator designed to measure and visualize global financial liquidity by aggregating data from various central bank balance sheets and money supply metrics. The indicator is plotted as an overlay on the price chart using the left scale, with the entire line shifted left by 75 days.
Key features:
Data Sources: Incorporates balance sheet data from major central banks including the Federal Reserve (FED), European Central Bank (ECB), People's Bank of China (PBC), Bank of Japan (BOJ), and other central banks, along with optional M2 money supply data from various countries.
Components: Includes options to toggle specific liquidity factors such as FED balance sheet, Treasury General Account (TGA), Reverse Repurchase Agreements (RRP), and regional M2 money supplies, all converted to USD.
75-Day Shift: The indicator's output is shifted left by 75 days on the chart, aligning historical liquidity data with earlier price action, with this shift period adjustable via the "Shift Days Left" input.
Calculations:
Computes a total liquidity value by summing enabled central bank and M2 data (adjusted for RRP and TGA as drains)
Scales the total by dividing by 1 trillion (10^12)
Applies a Simple Moving Average (SMA) and Rate of Change (ROC) with user-defined periods
Final output is either the SMA of ROC or SMA alone, depending on ROC length
Visualization: Plots the shifted result as a yellow line with a linewidth of 2.
True Open CalculationsIndicator Description: True Open Calculations
This custom Pine Script indicator calculates and plots key "True Open" levels based on specific time intervals and trading sessions. The True Open levels represent significant price points on the chart, helping traders identify key reference points tied to various market opening times. These levels are important for understanding price action in relation to market sessions and trading cycles. The indicator is designed to plot lines corresponding to different "True Opens" on the chart and display labels with the associated information.
Key Features:
True Year Open:
This represents the opening price on the first Monday of April each year. It serves as a reference point for the yearly price level.
Plot Color: Green.
True Month Open:
This represents the opening price on the second Monday of each month. It helps in identifying monthly trends and provides a key reference for monthly price movements.
Plot Color: Blue.
True Week Open:
This represents the opening price every Monday at 6:00 PM. It gives traders a level to track weekly opening movements and can be useful for weekly trend analysis.
Plot Color: Orange.
True Day Open:
This represents the opening price at 12:00 AM (midnight) each day. It serves as a daily benchmark for price action at the start of the trading day.
Plot Color: Red.
True New York Session Open:
This represents the opening price at 7:30 AM (New York session start time). This level is crucial for traders focused on the New York trading session.
Plot Color: Purple.
Additional Features:
Labels: The indicator displays labels to the right of each plotted line to describe which "True Open" it represents (e.g., "True Year Open," "True Month Open," etc.).
Dynamic Plotting: The lines are only plotted on the current candle, and the lines are dynamically updated for each time period based on the corresponding "True Open."
Visual Cues: The colors of the plotted lines (green, blue, orange, red, purple) help quickly distinguish between different "True Open" levels, making it easy for traders to track price action and make informed decisions.
Use Cases:
Yearly, Monthly, Weekly, Daily, and Session Benchmarking: This indicator provides traders with important price levels to use as benchmarks for the current year, month, week, and day, helping to identify trends and potential reversals.
Session Awareness: It is particularly useful for traders who want to track key market sessions, such as the New York session, and their impact on price movement.
Long-term Analysis: By including the yearly open, this indicator helps traders gain a broader perspective on market trends and provides context for analyzing shorter-term price movements.
Benefits:
Helps identify important reference points for longer-term trends (yearly, monthly) as well as shorter-term moves (daily, weekly, and session).
Visually intuitive with color-coded lines and labels, allowing quick and easy identification of key market open levels.
Dynamic and real-time: The indicator plots and updates the True Open levels dynamically as the market progresses.
Multi-Fibonacci Trend Average[FibonacciFlux]Multi-Fibonacci Trend Average (MFTA): An Institutional-Grade Trend Confluence Indicator for Discerning Market Participants
My original indicator/Strategy:
Engineered for the sophisticated demands of institutional and advanced traders, the Multi-Fibonacci Trend Average (MFTA) indicator represents a paradigm shift in technical analysis. This meticulously crafted tool is designed to furnish high-definition trend signals within the complexities of modern financial markets. Anchored in the rigorous principles of Fibonacci ratios and augmented by advanced averaging methodologies, MFTA delivers a granular perspective on trend dynamics. Its integration of Multi-Timeframe (MTF) filters provides unparalleled signal robustness, empowering strategic decision-making with a heightened degree of confidence.
MFTA indicator on BTCUSDT 15min chart with 1min RSI and MACD filters enabled. Note the refined signal generation with reduced noise.
MFTA indicator on BTCUSDT 15min chart without MTF filters. While capturing more potential trading opportunities, it also generates a higher frequency of signals, including potential false positives.
Core Innovation: Proprietary Fibonacci-Enhanced Supertrend Averaging Engine
The MFTA indicator’s core innovation lies in its proprietary implementation of Supertrend analysis, strategically fortified by Fibonacci ratios to construct a truly dynamic volatility envelope. Departing from conventional Supertrend methodologies, MFTA autonomously computes not one, but three distinct Supertrend lines. Each of these lines is uniquely parameterized by a specific Fibonacci factor: 0.618 (Weak), 1.618 (Medium/Golden Ratio), and 2.618 (Strong/Extended Fibonacci).
// Fibonacci-based factors for multiple Supertrend calculations
factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval=0.01, step=0.01, tooltip='Factor 1 (Weak/Fibonacci)', group="Fibonacci Supertrend")
factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval=0.01, step=0.01, tooltip='Factor 2 (Medium/Golden Ratio)', group="Fibonacci Supertrend")
factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval=0.01, step=0.01, tooltip='Factor 3 (Strong/Extended Fib)', group="Fibonacci Supertrend")
This multi-faceted architecture adeptly captures a spectrum of market volatility sensitivities, ensuring a comprehensive assessment of prevailing conditions. Subsequently, the indicator algorithmically synthesizes these disparate Supertrend lines through arithmetic averaging. To achieve optimal signal fidelity and mitigate inherent market noise, this composite average is further refined utilizing an Exponential Moving Average (EMA).
// Calculate average of the three supertends and a smoothed version
superlength = input.int(21, 'Smoothing Length', tooltip='Smoothing Length for Average Supertrend', group="Fibonacci Supertrend")
average_trend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_trend = ta.ema(average_trend, superlength)
The resultant ‘Smoothed Trend’ line emerges as a remarkably responsive yet stable trend demarcation, offering demonstrably superior clarity and precision compared to singular Supertrend implementations, particularly within the turbulent dynamics of high-volatility markets.
Elevated Signal Confluence: Integrated Multi-Timeframe (MTF) Validation Suite
MFTA transcends the limitations of conventional trend indicators by incorporating an advanced suite of three independent MTF filters: RSI, MACD, and Volume. These filters function as sophisticated validation protocols, rigorously ensuring that only signals exhibiting a confluence of high-probability factors are brought to the forefront.
1. Granular Lower Timeframe RSI Momentum Filter
The Relative Strength Index (RSI) filter, computed from a user-defined lower timeframe, furnishes critical momentum-based signal validation. By meticulously monitoring RSI dynamics on an accelerated timeframe, traders gain the capacity to evaluate underlying momentum strength with precision, prior to committing to signal execution on the primary chart timeframe.
// --- Lower Timeframe RSI Filter ---
ltf_rsi_filter_enable = input.bool(false, title="Enable RSI Filter", group="MTF Filters", tooltip="Use RSI from lower timeframe as a filter")
ltf_rsi_timeframe = input.timeframe("1", title="RSI Timeframe", group="MTF Filters", tooltip="Timeframe for RSI calculation")
ltf_rsi_length = input.int(14, title="RSI Length", minval=1, group="MTF Filters", tooltip="Length for RSI calculation")
ltf_rsi_threshold = input.int(30, title="RSI Threshold", minval=0, maxval=100, group="MTF Filters", tooltip="RSI value threshold for filtering signals")
2. Convergent Lower Timeframe MACD Trend-Momentum Filter
The Moving Average Convergence Divergence (MACD) filter, also calculated on a lower timeframe basis, introduces a critical layer of trend-momentum convergence confirmation. The bullish signal configuration rigorously mandates that the MACD line be definitively positioned above the Signal line on the designated lower timeframe. This stringent condition ensures a robust indication of converging momentum that aligns synergistically with the prevailing trend identified on the primary timeframe.
// --- Lower Timeframe MACD Filter ---
ltf_macd_filter_enable = input.bool(false, title="Enable MACD Filter", group="MTF Filters", tooltip="Use MACD from lower timeframe as a filter")
ltf_macd_timeframe = input.timeframe("1", title="MACD Timeframe", group="MTF Filters", tooltip="Timeframe for MACD calculation")
ltf_macd_fast_length = input.int(12, title="MACD Fast Length", minval=1, group="MTF Filters", tooltip="Fast EMA length for MACD")
ltf_macd_slow_length = input.int(26, title="MACD Slow Length", minval=1, group="MTF Filters", tooltip="Slow EMA length for MACD")
ltf_macd_signal_length = input.int(9, title="MACD Signal Length", minval=1, group="MTF Filters", tooltip="Signal SMA length for MACD")
3. Definitive Volume Confirmation Filter
The Volume Filter functions as an indispensable arbiter of trade conviction. By establishing a dynamic volume threshold, defined as a percentage relative to the average volume over a user-specified lookback period, traders can effectively ensure that all generated signals are rigorously validated by demonstrably increased trading activity. This pivotal validation step signifies robust market participation, substantially diminishing the potential for spurious or false breakout signals.
// --- Volume Filter ---
volume_filter_enable = input.bool(false, title="Enable Volume Filter", group="MTF Filters", tooltip="Use volume level as a filter")
volume_threshold_percent = input.int(title="Volume Threshold (%)", defval=150, minval=100, group="MTF Filters", tooltip="Minimum volume percentage compared to average volume to allow signal (100% = average)")
These meticulously engineered filters operate in synergistic confluence, requiring all enabled filters to definitively satisfy their pre-defined conditions before a Buy or Sell signal is generated. This stringent multi-layered validation process drastically minimizes the incidence of false positive signals, thereby significantly enhancing entry precision and overall signal reliability.
Intuitive Visual Architecture & Actionable Intelligence
MFTA provides a demonstrably intuitive and visually rich charting environment, meticulously delineating trend direction and momentum through precisely color-coded plots:
Average Supertrend: Thin line, green/red for uptrend/downtrend, immediate directional bias.
Smoothed Supertrend: Bold line, teal/purple for uptrend/downtrend, cleaner, institutionally robust trend.
Dynamic Trend Fill: Green/red fill between Supertrends quantifies trend strength and momentum.
Adaptive Background Coloring: Light green/red background mirrors Smoothed Supertrend direction, holistic trend perspective.
Precision Buy/Sell Signals: ‘BUY’/‘SELL’ labels appear on chart when trend touch and MTF filter confluence are satisfied, facilitating high-conviction trade action.
MFTA indicator applied to BTCUSDT 4-hour chart, showcasing its effectiveness on higher timeframes. The Smoothed Length parameter is increased to 200 for enhanced smoothness on this timeframe, coupled with 1min RSI and Volume filters for signal refinement. This illustrates the indicator's adaptability across different timeframes and market conditions.
Strategic Applications for Institutional Mandates
MFTA’s sophisticated design provides distinct advantages for advanced trading operations and institutional investment mandates. Key strategic applications include:
High-Probability Trend Identification: Fibonacci-averaged Supertrend with MTF filters robustly identifies high-probability trend continuations and reversals, enhancing alpha generation.
Precision Entry/Exit Signals: Volume and momentum-filtered signals enable institutional-grade precision for optimized risk-adjusted returns.
Algorithmic Trading Integration: Clear signal logic facilitates seamless integration into automated trading systems for scalable strategy deployment.
Multi-Asset/Timeframe Versatility: Adaptable parameters ensure applicability across diverse asset classes and timeframes, catering to varied trading mandates.
Enhanced Risk Management: Superior signal fidelity from MTF filters inherently reduces false signals, supporting robust risk management protocols.
Granular Customization and Parameterized Control
MFTA offers unparalleled customization, empowering users to fine-tune parameters for precise alignment with specific trading styles and market conditions. Key adjustable parameters include:
Fibonacci Factors: Adjust Supertrend sensitivity to volatility regimes.
ATR Length: Control volatility responsiveness in Supertrend calculations.
Smoothing Length: Refine Smoothed Trend line responsiveness and noise reduction.
MTF Filter Parameters: Independently configure timeframes, lookback periods, and thresholds for RSI, MACD, and Volume filters for optimal signal filtering.
Disclaimer
MFTA is meticulously engineered for high-quality trend signals; however, no indicator guarantees profit. Market conditions are unpredictable, and trading involves substantial risk. Rigorous backtesting and forward testing across diverse datasets, alongside a comprehensive understanding of the indicator's logic, are essential before live deployment. Past performance is not indicative of future results. MFTA is for informational and analytical purposes only and is not financial or investment advice.
Standard Deviation SMA RSI | mad_tiger_slayerOverview of the Script
The Standard Deviation SMA RSI is a custom TradingView indicator that enhances the Relative Strength Index (RSI) by incorporating a Simple Moving Average (SMA) and Standard Deviation bands . This approach smooths RSI calculations while factoring in volatility to provide clearer trend signals . Additionally, the indicator includes overbought and oversold thresholds, trend-coded RSI signals , and dynamic volatility bands for improved market analysis. This indicator is designed for swing traders and long-term investors looking to capture high-probability trend shifts.
How Do Traders Use the Standard Deviation SMA RSI?
In the provided chart image, the indicator is displayed on a price chart. Each visual component serves a distinct function in identifying trend conditions and volatility levels .
INTENDED USES
⚠️ NOT INTENDED FOR SCALPING
With the smoothing nature of the SMA-based RSI , this indicator is not designed for low-timeframe scalping. It works best on timeframes above 1-hour , with optimal performance in 12-hour, daily, and higher timeframes.
📈 TREND-FOLLOWING & MEAN REVERSION
The Standard Deviation SMA RSI functions as both a trend-following and mean-reverting indicator:
Trend-Following: Identifies strong, sustained trends using RSI signals and SMA confirmation.
Mean Reversion: Detects overbought/oversold conditions based on standard deviation bands and RSI thresholds .
A VISUAL REPRESENTATION OF INTENDED USES
RSI Line (Green/Pink/Gray): The RSI line dynamically changes color based on trend conditions .
Green RSI → Strong uptrend, RSI above the uptrend threshold.
Pink RSI → Downtrend, RSI below the downtrend threshold.
Gray RSI → Neutral state or consolidation.
If the SMA of RSI is above Long Threshold , the market is in a bullish trend.
If it’s below Short Threshold, bearish conditions prevail.
Threshold Lines (Teal/Purple):
Green Line → Long Entry Threshold
Red Line → Short Entry Threshold
Standard Deviation Bands:
Upper Band → Measures bullish volatility expansion
Lower Band → Measures bearish volatility expansion
Colored Candles: Price candles adjust color based on RSI conditions , visually aligning price action with market trends.
Indicator's Primary Elements
Input Parameters
The script includes several configurable settings, allowing users to tailor the indicator to different market environments:
RSI Length: Controls the number of periods for RSI calculations.
SMA Length: Defines the period for the SMA applied to RSI , creating a smoothed trend line.
Standard Deviation Period: Determines the length for volatility calculations.
Overbought and Oversold Levels:
Can be adjusted to customize sensitivity.
Standard Deviation SMA RSI Calculation
The SMA-based RSI smooths fluctuations while the standard deviation bands measure price volatility.
Upper and Lower Bands: Calculated by adding/subtracting standard deviation to/from the SMA-based RSI.
Trend Signal Calculation:
RSI is compared to uptrend and downtrend thresholds to determine buy/sell conditions.
Long and Short Conditions
Buy and sell conditions are determined by RSI relative to key thresholds :
Bullish Signal: RSI above long threshold & SMA confirms trend .
Bearish Signal: RSI below short threshold & SMA confirms downtrend .
Reversals: RSI entering overbought/oversold areas suggests possible trend reversals.
Conclusion
The Standard Deviation SMA RSI is a powerful trend-following and mean-reverting tool , offering enhanced insights into RSI movements, volatility, and market strength . By combining SMA smoothing, standard deviation bands, and dynamic thresholds , traders can better identify trend confirmations, reversals, and overextended conditions .
✅ Customizable settings allow traders to optimize sensitivity.
✅ Works best on high timeframes (12H, Daily, Weekly).
✅ Ideal for swing traders and long-term investors.
DateTimeLibrary with enums that can be used as script inputs to allow users to set their preferred date and/or time formats. The user-selected formats can be passed to the library functions (which use 𝚜𝚝𝚛.𝚏𝚘𝚛𝚖𝚊𝚝_𝚝𝚒𝚖𝚎() under the hood) to get formatted date and time strings from a UNIX time.
PREFACE
The target audience of this publication is users creating their own indicators/strategies.
Sometimes a date and/or time needs to be displayed to the user. As a Pine Coder, it is natural to focus our initial attention on the primary calculations or functions of a script, which can lead to the display format of dates and times being an afterthought. While it may not be crucial for the main use case of a script, increased customizability can help push indicators/strategies to the next level in the eyes of the user.
The purpose of this library is to provide an easy-to-use mechanism for allowing script users to choose the formats of dates and times that are displayed to them. Not only is this helpful for users from around the world who may be accustomed to different date/time formats, but it also makes it easier for the script author because it offloads the date/time formatting decision from the author to the user.
HOW TO USE
Step 1
Import the library. Replace with the latest available version number for this library.
//@version=6
indicator("Example")
import n00btraders/DateTime/ as dt
Step 2
Select a date format and/or time format enum to be used as an input.
dateFormatInput = input.enum(dt.DateFormat.FORMAT_3, "Date format")
timeFormatInput = input.enum(dt.TimeFormat.TWENTY_FOUR_HOURS, "Time hours format")
Step 3
Pass the user's selection as the `format` parameter in the formatting functions from this library. The `timestamp` & `timezone` parameters can be any value that would otherwise be used in 𝚜𝚝𝚛.𝚏𝚘𝚛𝚖𝚊𝚝_𝚝𝚒𝚖𝚎(𝚝𝚒𝚖𝚎, 𝚏𝚘𝚛𝚖𝚊𝚝, 𝚝𝚒𝚖𝚎𝚣𝚘𝚗𝚎).
string formattedDate = dt.formatDate(timestamp, dateFormatInput, timezone)
string formattedTime = dt.formatTime(timestamp, timeFormatInput, timezone)
LIMITATIONS
The library's ease-of-use comes at a few costs:
Fixed date/time formats.
Using the library's pre-defined date & time formats means that additional custom formats cannot be utilized. For example, this library does not include seconds or fractional seconds in formatted time strings. If a script's use case requires displaying the 'seconds' from a time of day, then 𝚜𝚝𝚛.𝚏𝚘𝚛𝚖𝚊𝚝_𝚝𝚒𝚖𝚎() must be used directly.
Fixed time zone offset format.
The `formatTime()` function of this library can optionally add the time zone offset at the end of the time string, but the format of the offset cannot be specified. Note: if the default format for time zone offset is not sufficient, the Timezone library can be imported directly to get the time zone offset string in a preferred format.
ADVANTAGES
There are benefits to utilizing this library instead of directly using 𝚜𝚝𝚛.𝚏𝚘𝚛𝚖𝚊𝚝_𝚝𝚒𝚖𝚎():
Easy to use from the user's perspective.
The date & time format enums provide a similar look and feel to the "Date format" and "Time hours format" options that already exist in the TradingView chart settings.
Easy to use from the author's perspective.
The exported functions from this library are modeled to behave similarly to the 𝚜𝚝𝚛.𝚏𝚘𝚛𝚖𝚊𝚝_𝚝𝚒𝚖𝚎(𝚝𝚒𝚖𝚎, 𝚏𝚘𝚛𝚖𝚊𝚝, 𝚝𝚒𝚖𝚎𝚣𝚘𝚗𝚎) built-in function from Pine Script.
Format quarter of the year.
The date formatting function from this library can display a fiscal quarter if it's included in the user-selected format. This is currently not possible with the built-in 𝚜𝚝𝚛.𝚏𝚘𝚛𝚖𝚊𝚝_𝚝𝚒𝚖𝚎().
EXPORTED ENUM TYPES
This section will list the available date/time formats that can be used as a script input. Each enum type has a detailed //@𝚏𝚞𝚗𝚌𝚝𝚒𝚘𝚗 description in the source code to help determine the best choice for your scripts.
Date Format Enums:
𝙳𝚊𝚝𝚎𝙵𝚘𝚛𝚖𝚊𝚝
𝙳𝚊𝚝𝚎𝙵𝚘𝚛𝚖𝚊𝚝𝙳𝚊𝚢𝙾𝚏𝚆𝚎𝚎𝚔𝙰𝚋𝚋𝚛
𝙳𝚊𝚝𝚎𝙵𝚘𝚛𝚖𝚊𝚝𝙳𝚊𝚢𝙾𝚏𝚆𝚎𝚎𝚔𝙵𝚞𝚕𝚕
𝙲𝚞𝚜𝚝𝚘𝚖𝙳𝚊𝚝𝚎𝙵𝚘𝚛𝚖𝚊𝚝
Supporting Date Enums:
𝙳𝚊𝚝𝚎𝙿𝚛𝚎𝚏𝚒𝚡
Time Format Enums:
𝚃𝚒𝚖𝚎𝙵𝚘𝚛𝚖𝚊𝚝
Supporting Time Enums:
𝚃𝚒𝚖𝚎𝙰𝚋𝚋𝚛𝚎𝚟𝚒𝚊𝚝𝚒𝚘𝚗
𝚃𝚒𝚖𝚎𝚂𝚎𝚙𝚊𝚛𝚊𝚝𝚘𝚛
𝚃𝚒𝚖𝚎𝙿𝚘𝚜𝚝𝚏𝚒𝚡
Note: all exported enums have custom titles for each field. This means that the supporting enums could also be exposed to the end-user as script inputs if necessary. The supporting enums are used as optional parameters in this library's formatting functions to allow further customizability.
EXPORTED FUNCTIONS
formatDate(timestamp, format, timezone, prefix, trim)
Converts a UNIX time into a date string formatted according to the selected `format`.
Parameters:
timestamp (series int) : A UNIX time.
format (series DateFormat) : A date format.
timezone (series string) : A UTC/GMT offset or IANA time zone identifier.
prefix (series DatePrefix) : Optional day of week prefix.
trim (series bool) : Optional truncation of numeric month / day.
Returns: Calendar date string using the selected format.
⸻⸻⸻⸻⸻⸻⸻⸻
Required parameters: `timestamp`, `format`.
Note: there is a version of this function for each Date Format enum type. The only difference is the type of the `format` parameter.
Tip: hover over the `formatDate()` function in the Pine Editor to display useful details:
Function description
Parameter descriptions + default values
Example function usage
formatTime(timestamp, format, timezone, trim, separator, postfix, space, offset)
Converts a UNIX time into a formatted time string using the 24-hour clock or 12-hour clock.
Parameters:
timestamp (series int) : A UNIX time.
format (series TimeFormat) : A time format.
timezone (series string) : A UTC/GMT offset or IANA time zone identifier.
trim (series TimeAbbreviation) : Optional truncation of the hour and minute portion.
separator (series TimeSeparator) : Optional time separator.
postfix (series TimePostfix) : Optional format for the AM/PM postfix.
space (series bool) : Optional space between the time and the postfix.
offset (series bool) : Optional UTC offset as a suffix.
Returns: Time of day string using the selected format.
⸻⸻⸻⸻⸻⸻⸻⸻
Required parameters: `timestamp`, `format`.
Note: the `trim`, `postfix`, and `space` optional parameters are not applicable and will be ignored when using the 24-hour clock (`format` = TimeFormat.TWENTY_FOUR_HOURS).
Tip: hover over the `formatTime()` function in the Pine Editor to display useful details:
Function description
Parameter descriptions + default values
Example function usage
Example outputs for combinations of TimeFormat.* enum values & optional parameters
NOTES
This library can be used in conjunction with the Timezone library to increase the usability of scripts that can benefit from allowing the user to input their preferred time zone.
Credits to HoanGhetti for publishing an informative Markdown resource which I referenced to create the formatted function descriptions that pop up when hovering over `formatDate()` and `formatTime()` function calls in the Pine Editor.
Air Gap MTF with alert settingsWhat it shows:
This indicator will show a horizontal line at a price where each EMAs are on on different time frames, which will remove the effort of having to flick through different time frames or look at different chart.
The lines itself will move in real time as price moves and therefore as the EMA values changes so no need to manually adjustment the lines.
How to use it:
The price gap between each of the lines are known as "air gaps", which are essentially zones price can move with less resistance. Therefore bigger the airgap there is more likely more movement in price.
In other words, where lines are can be a resistance (or support) and can expect price stagnation or rejection.
On the chart it is clear to see lines are acting as resistances/supports.
Key settings:
The time frame are fixed to: 30min, 1hr and 4hr. This cannot be changed as of now.
EMA values for each time frame are user changeable in the settings, and up to 4 different values can be chosen for each time frame. Default is 5,12,34 and 50 for each timeframe.
Line colour, thickness and style can be user adjusted. Start point for where line will be drawn can be changed in the settings, either: start of day, user defined start or across the chart. In case of user defined scenario user can input a number that specifies a offset from current candle.
Label colour, font, alignment, text size and text itself can be user adjusted in the settings. Price can be also displayed if user chooses to do so. Position of label (offset from current candle) is user specified and can be adjusted by the user.
Both the lines and labels can be turned off (both and individually), for each lines.
Alert Settings:
Manually, user can set alerts for when price crosses a specific line.
This can be done by:
right click on any of line
choose first option (add alert on...)
On the second option under condition, use the dropdown menu to choose the desired EMA/timeframe to set alert for.
Hit "create" at bottom right of option
----------------------------------------------------------------------
If anything is not clear please let me know!
Multi-Faceted Analysis ToolHere’s a detailed description for the **Multi-Faceted Analysis Tool** TradingView indicator:
---
## Multi-Faceted Analysis Tool
### Overview
The **Multi-Faceted Analysis Tool** is a powerful TradingView indicator designed to enhance your technical analysis by combining several popular indicators: Simple Moving Average (SMA), Relative Strength Index (RSI), and Moving Average Convergence Divergence (MACD). This indicator provides traders with insightful market signals that can be tailored to fit various trading strategies and timeframes.
### Key Features
1. **Simple Moving Average (SMA)**:
- Plots a customizable SMA on the price chart. The length of the SMA can be adjusted to suit your analysis needs (default is set to 50). The SMA helps identify the overall trend direction.
2. **Relative Strength Index (RSI)**:
- Calculates and plots RSI values, providing insights into potential overbought or oversold market conditions. The user can customize the length of the RSI calculation (default is 14).
- Overbought (70) and oversold (30) levels are visually marked, helping traders identify potential reversal points.
3. **MACD**:
- Computes MACD values with customizable parameters for fast length, slow length, and signal length (defaults are 12, 26, and 9 respectively).
- The MACD histogram is displayed, highlighting the difference between the MACD line and the signal line, which can help traders visualize momentum shifts.
4. **Buy and Sell Signals**:
- Generates clear buy and sell signals based on RSI crossover with established thresholds (buy when RSI crosses above 30, sell when RSI crosses below 70). These signals are visually represented on the chart for easy decision-making.
5. **User-Friendly Customization**:
- All parameters are adjustable, allowing traders to set their preferred values based on individual strategies or market conditions. This flexibility ensures that the tool can cater to a wide range of trading styles.
[F.B]_ZLEMA MACD ZLEMA MACD – A Zero-Lag Variant of the Classic MACD
Introduction & Motivation
The Moving Average Convergence Divergence (MACD) is a standard indicator for measuring trend strength and momentum. However, it suffers from the latency of traditional Exponential Moving Averages (EMAs).
This variant replaces EMAs with Zero Lag Exponential Moving Averages (ZLEMA), reducing delay and increasing the indicator’s responsiveness. This can potentially lead to earlier trend change detection, especially in highly volatile markets.
Calculation Methodology
2.1 Zero-Lag Exponential Moving Average (ZLEMA)
The classic EMA formula is extended with a correction factor:
ZLEMA_t = EMA(2 * P_t - EMA(P_t, L), L)
where:
P_t is the closing price,
L is the smoothing period length.
2.2 MACD Calculation Using ZLEMA
MACD_t = ZLEMA_short,t - ZLEMA_long,t
with standard parameters of 12 and 26 periods.
2.3 Signal Line with Adaptive Methodology
The signal line can be calculated using ZLEMA, EMA, or SMA:
Signal_t = f(MACD, S)
where f is the chosen smoothing function and S is the period length.
2.4 Histogram as a Measure of Momentum Changes
Histogram_t = MACD_t - Signal_t
An increasing histogram indicates a relative acceleration in trend strength.
Potential Applications in Data Analysis
Since the indicator is based solely on price time series, its effectiveness as a standalone trading signal is limited. However, in quantitative models, it can be used as a feature for trend quantification or for filtering market phases with strong trend dynamics.
Potential use cases include:
Trend Classification: Segmenting market phases into "trend" vs. "mean reversion."
Momentum Regime Identification: Analyzing histogram dynamics to detect increasing or decreasing trend strength.
Signal Smoothing: An alternative to classic EMA smoothing in more complex multi-factor models.
Important: Using this as a standalone trading indicator without additional confirmation mechanisms is not recommended, as it does not demonstrate statistical superiority over other momentum indicators.
Evaluation & Limitations
✅ Advantages:
Reduced lag compared to the classic MACD.
Customizable signal line smoothing for different applications.
Easy integration into existing analytical pipelines.
⚠️ Limitations:
Not a standalone trading system: Like any moving average, this indicator is susceptible to noise and false signals in sideways markets.
Parameter sensitivity: Small changes in period lengths can lead to significant signal deviations, requiring robust optimization.
Conclusion
The ZLEMA MACD is a variant of the classic MACD with reduced latency, making it particularly useful for analytical purposes where faster adaptation to price movements is required.
Its application in trading strategies should be limited to multi-factor models with rigorous evaluation. Backtests and out-of-sample analyses are essential to avoid overfitting to past market data.
Disclaimer: This indicator is provided for informational and educational purposes only and does not constitute financial advice. The author assumes no responsibility for any trading decisions made based on this indicator. Trading involves significant risk, and past performance is not indicative of future results.
Market Trend Levels Non-Repainting [BigBeluga X PineIndicators]This strategy is based on the Market Trend Levels Detector developed by BigBeluga. Full credit for the concept and original indicator goes to BigBeluga.
The Market Trend Levels Detector Strategy is a non-repainting trend-following strategy that identifies market trend shifts using two Exponential Moving Averages (EMA). It also detects key price levels and allows traders to apply multiple filters to refine trade entries and exits.
This strategy is designed for trend trading and enables traders to:
Identify trend direction based on EMA crossovers.
Detect significant market levels using labeled trend lines.
Use multiple filter conditions to improve trade accuracy.
Avoid false signals through non-repainting calculations.
How the Market Trend Levels Detector Strategy Works
1. Core Trend Detection Using EMA Crossovers
The strategy detects trend shifts using two EMAs:
Fast EMA (default: 12 periods) – Reacts quickly to price movements.
Slow EMA (default: 25 periods) – Provides a smoother trend confirmation.
A bullish crossover (Fast EMA crosses above Slow EMA) signals an uptrend , while a bearish crossover (Fast EMA crosses below Slow EMA) signals a downtrend .
2. Market Level Detection & Visualization
Each time an EMA crossover occurs, a trend level line is drawn:
Bullish crossover → A green line is drawn at the low of the crossover candle.
Bearish crossover → A purple line is drawn at the high of the crossover candle.
Lines can be extended to act as support and resistance zones for future price action.
Additionally, a small label (●) appears at each crossover to mark the event on the chart.
3. Trade Entry & Exit Conditions
The strategy allows users to choose between three trading modes:
Long Only – Only enters long trades.
Short Only – Only enters short trades.
Long & Short – Trades in both directions.
Entry Conditions
Long Entry:
A bullish EMA crossover occurs.
The trade direction setting allows long trades.
Filter conditions (if enabled) confirm a valid long signal.
Short Entry:
A bearish EMA crossover occurs.
The trade direction setting allows short trades.
Filter conditions (if enabled) confirm a valid short signal.
Exit Conditions
Long Exit:
A bearish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid long position.
Short Exit:
A bullish EMA crossover occurs.
Exit filters (if enabled) indicate an invalid short position.
Additional Trade Filters
To improve trade accuracy, the strategy allows traders to apply up to 7 additional filters:
RSI Filter: Only trades when RSI confirms a valid trend.
MACD Filter: Ensures MACD histogram supports the trade direction.
Stochastic Filter: Requires %K line to be above/below threshold values.
Bollinger Bands Filter: Confirms price position relative to the middle BB line.
ADX Filter: Ensures the trend strength is above a set threshold.
CCI Filter: Requires CCI to indicate momentum in the right direction.
Williams %R Filter: Ensures price momentum supports the trade.
Filters can be enabled or disabled individually based on trader preference.
Dynamic Level Extension Feature
The strategy provides an optional feature to extend trend lines until price interacts with them again:
Bullish support lines extend until price revisits them.
Bearish resistance lines extend until price revisits them.
If price breaks a line, the line turns into a dotted style , indicating it has been breached.
This helps traders identify key levels where trend shifts previously occurred, providing useful support and resistance insights.
Customization Options
The strategy includes several adjustable settings :
Trade Direction: Choose between Long Only, Short Only, or Long & Short.
Trend Lengths: Adjust the Fast & Slow EMA lengths.
Market Level Extension: Decide whether to extend support/resistance lines.
Filters for Trade Confirmation: Enable/disable individual filters.
Color Settings: Customize line colors for bullish and bearish trend shifts.
Maximum Displayed Lines: Limit the number of drawn support/resistance lines.
Considerations & Limitations
Trend Lag: As with any EMA-based strategy, signals may be slightly delayed compared to price action.
Sideways Markets: This strategy works best in trending conditions; frequent crossovers in sideways markets can produce false signals.
Filter Usage: Enabling multiple filters may reduce trade frequency, but can also improve trade quality.
Line Overlap: If many crossovers occur in a short period, the chart may become cluttered with multiple trend levels. Adjusting the "Display Last" setting can help.
Conclusion
The Market Trend Levels Detector Strategy is a non-repainting trend-following system that combines EMA crossovers, market level detection, and customizable filters to improve trade accuracy.
By identifying trend shifts and key price levels, this strategy can be used for:
Trend Confirmation – Using EMA crossovers and filters to confirm trend direction.
Support & Resistance Trading – Identifying dynamic levels where price reacts.
Momentum-Based Trading – Combining EMA crossovers with additional momentum filters.
This strategy is fully customizable and can be adapted to different trading styles, timeframes, and market conditions.
Full credit for the original concept and indicator goes to BigBeluga.
Moving Average Convergence Divergence with Enhanced Cross Alerts
Overview of Features and Settings
- Customizable Parameters:
- Fast and Slow Periods: Users can set the duration for both the fast (default 12) and slow (default 26) moving averages.
- Source Selection: The indicator uses the closing price (close) by default, though this can be modified to any other data source.
- Signal Smoothing: The smoothing period for the signal line is adjustable (default 9), and you can choose whether to use SMA or EMA for both the oscillator and the signal line calculations.
Calculation Logic
1. Calculation of Moving Averages:
- The fast and slow moving averages are computed based on the chosen moving average type (SMA or EMA) over the specified periods.
- The MACD line is then determined as the difference between these two moving averages.
2. Signal Line and Histogram:
- Signal Line: Created by smoothing the MACD line, with the option to choose between SMA and EMA.
- Histogram: Represents the difference between the MACD line and the signal line, visually indicating the divergence between the two.
Detection of Cross Events
The script identifies two specific cross events with additional filtering conditions:
- Bullish Cross:
- The MACD line **crosses above** the signal line.
- The previous value of the histogram is negative, and both the MACD and the signal line are below zero.
- This condition suggests that a cross occurring in the negative territory might indicate a potential upward trend reversal.
- **Bearish Cross:**
- The MACD line **crosses below** the signal line.
- The previous value of the histogram is positive, and both the MACD and the signal line are above zero.
- This condition indicates that a cross in the positive territory may signal a potential downward trend reversal.
For each event, there are dedicated alert conditions defined that trigger notifications when the criteria are met.
Visualization
- Displayed Elements:
- Histogram: Rendered as a column chart with colors that change based on the rate of change. For instance, a rising positive histogram uses a stronger green, whereas a declining positive histogram uses a lighter shade.
- MACD and Signal Lines: Displayed as separate lines with distinct colors to differentiate them.
- Zero Line: A horizontal line is drawn to help visually pinpoint the zero level.
- Crossing Signals:
- Optional markers in the form of arrows appear on the chart:
- **Bullish Cross: A green, upward-pointing triangle at the bottom.
- **Bearish Cross: A red, downward-pointing triangle at the top.
Summary
This indicator not only incorporates the traditional MACD components but also offers the following additional benefits:
- **Enhanced Accuracy:** Extra conditions (such as checking the previous histogram value and the position of the lines relative to zero) improve the identification of significant cross events.
- **Customization:** Users can personalize the moving average types and periods, making the indicator adaptable to different trading strategies.
- **Visual Assistance:** The combination of histogram columns, lines, and markers helps quickly pinpoint potential trend reversals, thereby aiding trading decisions.
This comprehensive description is intended to clearly demonstrate to users how the indicator works, outlining its calculations, filtering conditions, and its role in identifying cross events within technical analysis.
TestMA-STATEOverview:
This Pine Script (version 6) is designed to generate trading events based on moving average (MA) behavior and dynamically calculated percentiles. It leverages a custom state machine library (version 7) from decrypt_capital to track and manage state transitions related to MA conditions, and it triggers alerts (and optionally, chart labels) when specific state transitions occur.
Key Components:
License & Metadata:
The script is distributed under the Mozilla Public License 2.0.
It carries copyright by decrypt_capital.
The title ("TestMA-STATE") and short title ("MA-STATE") are defined, and the script runs on an overlay with extended backtracking and drawing limits.
State Machine Integration:
The script imports the lib_statemachine_modified library (version 7) using the alias modSM.
A persistent state machine instance (MovingAverageDirection_SM) is created to manage various MA-related states.
Several state constants are defined to represent different market conditions, such as:
MA_SHORT_ABOVE_OVERBOUGHT: When the short MA low is above the overbought threshold.
MA_SHORT_CROSSUNDER_MID & MA_SHORT_CROSSUNDER_BIG: Conditions for bearish crossunders.
MA_SHORT_BELOW_OVERSOLD: When the short MA high is below the oversold threshold.
MA_SHORT_CROSSOVER_MID & MA_SHORT_CROSSOVER_BIG: Conditions for bullish crossovers.
Inputs & MA Calculation:
Users can choose the type of moving average (EMA, SMA, WMA, VWMA) and adjust lengths for short, mid, and big MAs.
Additional inputs include lookback length for percentile calculations and percentile thresholds for determining overbought and oversold boundaries.
The script computes:
Short MA Low and High: Based on the low and high series.
Mid MA and Big MA: Based on the average price (ohlc4).
Dynamic Percentile Boundaries:
Two functions (f_getPercentile() and f_getPercentileArr()) calculate dynamic percentile values from the MA data.
These functions determine the oversold and overbought boundaries used in the state transition conditions.
Timestamp & Alert Header Formatting:
A helper function (f_formatTimestamp()) formats timestamps into a human-readable form (e.g., "Tue 12 Mar 16:30").
This formatted time, along with ticker information and other details, is used to build an alert header.
State Transitions & Alerts:
The script calls the state machine’s step() method multiple times with conditions based on the relationship between MA values and the percentile boundaries.
For example:
A bullish condition is triggered when the short MA low moves above the overbought threshold.
A bearish condition is triggered when the short MA high falls below the oversold boundary.
Transitions are further refined by checking if the MA is rising or falling.
When specific state transitions occur (e.g., MA_SHORT_CROSSOVER_MID after MA_SHORT_BELOW_OVERSOLD), the script:
Checks that the transition is recent (using the barsSinceState() method).
Optionally creates a label on the chart.
Triggers an alert with a descriptive message.
Chart Plotting:
The script plots the calculated moving averages (short, mid, and optionally big) on the chart.
It also plots the dynamic percentile boundaries for visual reference.
Purpose & Usage:
Trading Signal Generation:
The primary goal is to monitor key MA conditions and trigger alerts when significant crossovers or crossunders occur. These events—such as bullish crossovers when the market recovers from oversold conditions or bearish crossunders when the market retracts from overbought conditions—can be used as trading signals.
Visualization:
Users have options to display the various moving averages and percentile boundaries directly on the chart, as well as optional labels that mark when an alert is generated.
Alerting:
When specific state transitions are detected, the script constructs and sends an alert message with a timestamp, ticker, and descriptive text, aiding traders in making timely decisions.
MACD Crossover Strategy MACD Crossover Strategy:
This strategy is based on the Moving Average Convergence Divergence (MACD) indicator, a popular tool used in technical analysis to identify potential trend changes and momentum in price movements. The strategy focuses on MACD crossovers within a specific "important zone" to generate trading signals.
Key Components:
1. MACD Calculation: The strategy uses customizable parameters for fast length (default 12), slow length (default 26), and signal length (default 9) to calculate the MACD line and signal line.
2. Important Zone: Defined by upper and lower thresholds (default 0.5 and -0.5), this zone helps filter out potentially less significant crossovers.
3. Entry Conditions:
- Long (Buy) Entry: When the MACD line crosses above the signal line within the important zone.
- Short (Sell) Entry: When the MACD line crosses below the signal line within the important zone.
4. Exit Conditions: The strategy closes positions on opposite crossover signals. Long positions are closed on bearish crossovers, and short positions on bullish crossovers.
5. Visualization:
- MACD line (blue) and signal line (orange) are plotted.
- The zero line, upper threshold, and lower threshold are displayed for reference.
- Buy signals are represented by green triangles at the bottom of the chart.
- Sell signals are shown as red triangles at the top of the chart.
This strategy aims to capture trend changes while filtering out potentially false signals that occur when the MACD is at extreme values. By focusing on crossovers within the important zone, the strategy attempts to identify more reliable trading opportunities.
Traders can adjust the MACD parameters and the important zone thresholds to fine-tune the strategy for different assets or timeframes. As with any trading strategy, it's crucial to thoroughly backtest and consider risk management before using it in live trading.
