ZigZag++ + 4 EMA89 Trend Candles + BUY/SELL LabelsThis script combines ZigZag patterns, EMA89 trend detection, and custom buy/sell scalp signals. It helps identify trend direction and potential entry points in trending markets.
Features:
- ZigZag structure points
- EMA89 as dynamic trend filter
- Buy/Sell scalp markers
- HL/HH swing labels
- Works best on 15m–4h timeframes
Tìm kiếm tập lệnh với "trend"
ZigZag+4 EMA89 Trend Candles + BUY/SELL SCALPThis script combines ZigZag patterns, EMA89 trend detection, and custom buy/sell scalp signals. It helps identify trend direction and potential entry points in trending markets.
Features:
- ZigZag structure points
- EMA89 as dynamic trend filter
- Buy/Sell scalp markers
- HL/HH swing labels
- Works best on 15m–4h timeframes
Pivot Point TrendOverview
A trend-following trailing line built from confirmed pivot highs/lows and ATR bands. The line turns green in uptrends and red in downtrends. A flip happens only when price closes on the other side of the opposite trail, helping filter noise.
How it works:
Finds confirmed swing points (pivots) and builds a smoothed center from them.
From that center, creates ATR-based bands.
The active trail “locks” in the trend: in uptrends it never moves down; in downtrends it never moves up.
Close above the prior upper trail → bullish; close below the prior lower trail → bearish.
Inputs
Pivot Point Period (prd) – strictness of pivot confirmation (delay = prd bars).
ATR Period (pd) and ATR Factor (factor) – band width; higher values = fewer flips.
Calculation timeframe (calcTF) – leave empty to use chart TF, or set a hard TF like 1D, 4H.
Show Center Line – optional central guide.
Line Width – trail thickness.
Alerts
Bullish Flip – trend turns bullish.
Bearish Flip – trend turns bearish.
Trend Changed – any flip event.
Usage tips
Typical crypto intraday starters: prd 2–5, pd 10–14, factor 2.5–3.5.
For smoother signals, compute on a higher TF (e.g., calcTF = 1D) and time entries on your lower TF.
Prefer actions on bar close of the calculation TF to avoid intrabar whipsaw.
Notes on repainting
The script uses request.security(..., lookahead_off). Pivots confirm after prd bars by design; once confirmed, the center and trails do not use future data. Evaluate flips on bar close for consistency, especially when calcTF > chart TF.
Disclaimer
Educational use only. Not financial advice. Trading involves risk.
Auto Trend Channel with Fibonacci‼️ PLEASE USE WITH LOG CHART
🟠 Overview
This indicator introduces a novel approach to trend channel construction by implementing a touch-based validation system that ensures channels actually function as dynamic support and resistance levels. Unlike traditional linear regression channels that simply fit a mathematical line through price data, this indicator validates channel effectiveness by measuring how frequently price interacts with the boundaries, creating channels that traders can reliably use for entry and exit decisions.
🟠 Core Idea: Touch-Based Channel Validation
The fundamental problem with standard regression channels is that they often create mathematically correct but practically useless boundaries that price rarely respects. This indicator solves this by introducing a dual-scoring optimization system that evaluates each potential channel based on two critical factors:
Trend Correlation (70% weight): Measures how well prices follow the overall trend direction using Pearson correlation coefficient
Boundary Touch Frequency (30% weight): Counts actual instances where price highs touch the upper channel and lows touch the lower channel
This combination ensures the selected channel not only follows the trend but actively serves as support and resistance.
🟠 Trading Applications
Trend Following
Strong Uptrend: Price consistently bounces off lower channel and Fibonacci levels
Strong Downtrend: Price repeatedly fails at upper channel and Fibonacci resistance
Trend Weakening: Price fails to reach channel extremes or breaks through
Entry Strategies
Channel Bounce Entries: Enter long when price touches lower channel with confirmation; short at upper channel touches
Fibonacci Retracement Entries: Use 38.2% or 61.8% levels for pullback entries in trending markets
Breakout Entries: Trade breakouts when price closes beyond channels with increased volume
🟠 Customization Parameters
Automatic/Manual Period: Choose between intelligent auto-detection or fixed lookback period
Touch Sensitivity (0.1%-10%): Defines how close price must be to count as a boundary touch
Minimum Touches (1-10): Filter threshold for channel validation
Adaptive Deviation: Toggle between calculated or manual deviation multipliers
Block-Based Trend Breakout (YTK/DTK) – v1📌 Overview
Block Trend Breakout (YTK/DTK) is a lightweight, rule-based indicator that detects potential trend reversals or volatility bursts by tracking breakouts of key structural support/resistance levels — derived from block-wise trend patterns.
The logic is simple yet effective: if a trend has been confirmed across multiple blocks (custom-length bar groups), and the price breaks its own structural boundary, a potential reversal or volatility signal is triggered.
🟥 YTK (Uptrend Breakdown) → Price breaks below the lowest low of the most recent block in an uptrend.
🟩 DTK (Downtrend Breakout) → Price breaks above the highest high of the most recent block in a downtrend.
🔍 How It Works
Block Construction: User-defined bar groups (e.g., 6 bars on a 4H chart = 24H blocks).
Trend Validation: At least N consecutive blocks must show higher highs/lows (uptrend) or lower highs/lows (downtrend).
Breakout Test: If the current bar violates the structural limit (MR block high/low), the corresponding signal is plotted.
📉 This logic identifies weakening trends or failed momentum, often preceding reversals or volatility expansions.
⚙️ Features
Adjustable block size and trend confirmation count
Option to use only closed bars (to reduce repaint risk)
Inclusive mode for “<= / >=” logic
Visual signals:
MR Block high/low levels
Trend-colored bars
Arrows for YTK (🔻) and DTK (🔺)
Built-in alerts for automated strategies
🎯 Use Cases
Spotting fakeouts and false breakouts
Identifying trend exhaustion before reversal
Confirming structural support/resistance breaks
Visual tool for discretionary traders
Signal generator for automated systems
💬 Feedback & Contributions
This script is open-source and community-driven. We actively welcome feedback, ideas, improvements, forks, and questions.
📩 Contact for collaboration or discussion:
📧 senbrke@gmail.com
Dual Stochastic with Trend FilterThe "Dual Stochastic with Trend Filter" is an oscillator indicator designed to provide clearer, trend-aligned trading signals. It uses two distinct stochastic oscillators to identify potential entry points and incorporates an optional EMA-based trend filter to ensure that you are trading in the direction of the broader market momentum.
How It Works and How to Use It
This indicator combines two key technical analysis concepts: momentum (via stochastics) and trend (via moving averages).
Core Components:
Dual Stochastic Oscillators:
Signal Line 1 (Blue): A standard stochastic oscillator.
Signal Line 2 (Red): A second stochastic oscillator, often using a different source (like hlcc4) to provide a smoother, more reliable signal.
A buy signal is generated when the Blue Line (d1) crosses above the Red Line (d2).
A sell signal is generated when the Blue Line (d1) crosses below the Red Line (d2).
Trend Filter (Optional):
This feature uses a fast and a slow Exponential Moving Average (EMA) to determine the overall market trend.
When the fast EMA is above the slow EMA, the background will turn green, indicating an uptrend.
When the fast EMA is below the slow EMA, the background will turn red, indicating a downtrend.
This filter can be toggled on or off in the indicator settings.
How to Use:
With Trend Filter Enabled (Recommended):
Long (Buy) Entry: Look for a green triangle buy signal (▲). This signal only appears when:
The Blue Signal Line crosses above the Red Signal Line.
The market is in a confirmed uptrend (green background).
Short (Sell) Entry: Look for a red triangle sell signal (▼). This signal only appears when:
The Blue Signal Line crosses below the Red Signal Line.
The market is in a confirmed downtrend (red background).
Exit Signal:
A yellow circle (●) appears to suggest closing an open trade. This signal is triggered for a long position if either the stochastics have a bearish cross or the trend flips to a downtrend. Conversely, for a short position, it's triggered by a bullish stochastic cross or a trend flip to an uptrend.
With Trend Filter Disabled:
If you turn off the "Use Trend Filter" option, the indicator will function as a simple dual stochastic crossover system.
A green triangle (▲) will appear every time the Blue Line crosses above the Red Line.
A red triangle (▼) will appear every time the Blue Line crosses below the Red Line.
The background coloring and exit signals based on trend flips will be deactivated. This mode is more sensitive but may produce more false signals in choppy markets.
Key Visuals:
Blue Line: The primary signal line.
Red Line: The secondary, often smoother, signal line.
Green Triangle (▲): Bullish entry signal.
Red Triangle (▼): Bearish entry signal.
Yellow Circle (●): Suggested trade exit/stop.
Green/Red Background: Visual confirmation of the current uptrend or downtrend.
By filtering stochastic signals with the dominant trend, this indicator helps traders avoid common pitfalls like entering short positions during a strong uptrend or buying into a bearish market. This alignment of momentum and trend is key to improving signal quality.
Disclaimer
This indicator is provided for educational and informational purposes only and should not be considered as financial advice or a recommendation to buy or sell any asset. All trading and investment decisions are your own sole responsibility.
Trading financial markets involves a high level of risk, and you may lose more than your initial investment. Past performance is not indicative of future results. The signals generated by this indicator are not guaranteed to be accurate, and you should always use this tool in conjunction with other forms of analysis and sound risk management practices.
Before using this indicator in a live trading environment, it is strongly recommended that you backtest it thoroughly and practice with it on a demo account. The author is not responsible for any financial losses you may incur from using this script.
Advanced Trend Momentum [Alpha Extract]The Advanced Trend Momentum indicator provides traders with deep insights into market dynamics by combining exponential moving average analysis with RSI momentum assessment and dynamic support/resistance detection. This sophisticated multi-dimensional tool helps identify trend changes, momentum divergences, and key structural levels, offering actionable buy and sell signals based on trend strength and momentum convergence.
🔶 CALCULATION
The indicator processes market data through multiple analytical methods:
Dual EMA Analysis: Calculates fast and slow exponential moving averages with dynamic trend direction assessment and ATR-normalized strength measurement.
RSI Momentum Engine: Implements RSI-based momentum analysis with enhanced overbought/oversold detection and momentum velocity calculations.
Pivot-Based Structure: Identifies and tracks dynamic support and resistance levels using pivot point analysis with configurable level management.
Signal Integration: Combines trend direction, momentum characteristics, and structural proximity to generate high-probability trading signals.
Formula:
Fast EMA = EMA(Close, Fast Length)
Slow EMA = EMA(Close, Slow Length)
Trend Direction = Fast EMA > Slow EMA ? 1 : -1
Trend Strength = |Fast EMA - Slow EMA| / ATR(Period) × 100
RSI Momentum = RSI(Close, RSI Length)
Momentum Value = Change(Close, 5) / ATR(10) × 100
Pivot Support/Resistance = Dynamic pivot arrays with configurable lookback periods
Bullish Signal = Trend Change + Momentum Confirmation + Strength > 1%
Bearish Signal = Trend Change + Momentum Confirmation + Strength > 1%
🔶 DETAILS
Visual Features:
Trend EMAs: Fast and slow exponential moving averages with dynamic color coding (bullish/bearish)
Enhanced RSI: RSI oscillator with color-coded zones, gradient fills, and reference bands at overbought/oversold levels
Trend Fill: Dynamic gradient between EMAs indicating trend strength and direction
Support/Resistance Lines: Horizontal levels extending from pivot-based calculations with configurable maximum levels
Momentum Candles: Color-coded candlestick overlay reflecting combined trend and momentum conditions
Divergence Markers: Diamond-shaped signals highlighting bullish and bearish momentum divergences
Analysis Table: Real-time summary of trend direction, strength percentage, RSI value, and momentum reading
Interpretation:
Trend Direction: Bullish when Fast EMA crosses above Slow EMA with strength confirmation
Trend Strength > 1%: Strong trending conditions with institutional participation
RSI > 70: Overbought conditions, potential selling opportunity
RSI < 30: Oversold conditions, potential buying opportunity
Momentum Divergence: Price and momentum moving opposite directions signal potential reversals
Support/Resistance Proximity: Dynamic levels provide optimal entry/exit zones
Combined Signals: Trend changes with momentum confirmation generate high-probability opportunities
🔶 EXAMPLES
Trend Confirmation: Fast EMA crossing above Slow EMA with trend strength exceeding 1% and positive momentum confirms strong bullish conditions.
Example: During institutional accumulation phases, EMA crossovers with momentum confirmation have historically preceded significant upward moves, providing optimal long entry points.
15min
4H
Momentum Divergence Detection: RSI reaching overbought levels while momentum decreases despite rising prices signals potential trend exhaustion.
Example: Bearish divergence signals appearing at resistance levels have marked major market tops, allowing traders to secure profits before corrections.
Support/Resistance Integration: Dynamic pivot-based levels combined with trend and momentum signals create high-probability trading zones.
Example: Bullish trend changes occurring near established support levels offer optimal risk-reward entries with clearly defined stop-loss levels.
Multi-Dimensional Confirmation: The indicator's combination of trend, momentum, and structural analysis provides comprehensive market validation.
Example: When trend direction aligns with momentum characteristics near key structural levels, the confluence creates institutional-grade trading opportunities with enhanced probability of success.
🔶 SETTINGS
Customization Options:
Trend Analysis: Fast EMA Length (default: 12), Slow EMA Length (default: 26), Trend Strength Period (default: 14)
Support & Resistance: Pivot Length for level detection (default: 10), Maximum S/R Levels displayed (default: 3), Toggle S/R visibility
Momentum Settings: RSI Length (default: 14), Oversold Level (default: 30), Overbought Level (default: 70)
Visual Configuration: Color schemes for bullish/bearish/neutral conditions, transparency settings for fills, momentum candle overlay toggle
Display Options: Analysis table visibility, divergence marker size, alert system configuration
The Advanced Trend Momentum indicator provides traders with comprehensive insights into market dynamics through its sophisticated integration of trend analysis, momentum assessment, and structural level detection. By combining multiple analytical dimensions into a unified framework, this tool helps identify high-probability opportunities while filtering out market noise through its multi-confirmation approach, enabling traders to make informed decisions across various market cycles and timeframes.
Auto-Fit Growth Trendline# **Theoretical Algorithmic Principles of the Auto-Fit Growth Trendline (AFGT)**
## **🎯 What Does This Algorithm Do?**
The Auto-Fit Growth Trendline is an advanced technical analysis system that **automates the identification of long-term growth trends** and **projects future price levels** based on historical cyclical patterns.
### **Primary Functionality:**
- **Automatically detects** the most significant lows in regular periods (monthly, quarterly, semi-annually, annually)
- **Constructs a dynamic trendline** that connects these historical lows
- **Projects the trend into the future** with high mathematical precision
- **Generates Fibonacci bands** that act as dynamic support and resistance levels
- **Automatically adapts** to different timeframes and market conditions
### **Strategic Purpose:**
The algorithm is designed to identify **fundamental value zones** where price has historically found support, enabling traders to:
- Identify optimal entry points for long positions
- Establish realistic price targets based on mathematical projections
- Recognize dynamic support and resistance levels
- Anticipate long-term price movements
---
## **🧮 Core Mathematical Foundations**
### **Adaptive Temporal Segmentation Theory**
The algorithm is based on **dynamic temporal partition theory**, where time is divided into mathematically coherent uniform intervals. It uses modular transformations to create bijective mappings between continuous timestamps and discrete periods, ensuring each temporal point belongs uniquely to a specific period.
**What does this achieve?** It allows the algorithm to automatically identify natural market cycles (annual, quarterly, etc.) without manual intervention, adapting to the inherent periodicity of each asset.
The temporal mapping function implements a **discrete affine transformation** that normalizes different frequencies (monthly, quarterly, semi-annual, annual) to a space of unique identifiers, enabling consistent cross-temporal comparative analysis.
---
## **📊 Local Extrema Detection Theory**
### **Multi-Point Retrospective Validation Principle**
Local minima detection is founded on **relative extrema theory with sliding window**. Instead of using a simple minimum finder, it implements a cross-validation system that examines the persistence of the extremum across multiple historical periods.
**What problem does this solve?** It eliminates false minima caused by temporal volatility, identifying only those points that represent true historical support levels with statistical significance.
This approach is based on the **statistical confirmation principle**, where a minimum is only considered valid if it maintains its extremum condition during a defined observation period, significantly reducing false positives caused by transitory volatility.
---
## **🔬 Robust Interpolation Theory with Outlier Control**
### **Contextual Adaptive Interpolation Model**
The mathematical core uses **piecewise linear interpolation with adaptive outlier correction**. The key innovation lies in implementing a **contextual anomaly detector** that identifies not only absolute extreme values, but relative deviations to the local context.
**Why is this important?** Financial markets contain extreme events (crashes, bubbles) that can distort projections. This system identifies and appropriately weights them without completely eliminating them, preserving directional information while attenuating distortions.
### **Implicit Bayesian Smoothing Algorithm**
When an outlier is detected (deviation >300% of local average), the system applies a **simplified Kalman filter** that combines the current observation with a local trend estimation, using a weight factor that preserves directional information while attenuating extreme fluctuations.
---
## **📈 Stabilized Extrapolation Theory**
### **Exponential Growth Model with Dampening**
Extrapolation is based on a **modified exponential growth model with progressive dampening**. It uses multiple historical points to calculate local growth ratios, implements statistical filtering to eliminate outliers, and applies a dampening factor that increases with extrapolation distance.
**What advantage does this offer?** Long-term projections in finance tend to be exponentially unrealistic. This system maintains short-to-medium term accuracy while converging toward realistic long-term projections, avoiding the typical "exponential explosions" of other methods.
### **Asymptotic Convergence Principle**
For long-term projections, the algorithm implements **controlled asymptotic convergence**, where growth ratios gradually converge toward pre-established limits, avoiding unrealistic exponential projections while preserving short-to-medium term accuracy.
---
## **🌟 Dynamic Fibonacci Projection Theory**
### **Continuous Proportional Scaling Model**
Fibonacci bands are constructed through **uniform proportional scaling** of the base curve, where each level represents a linear transformation of the main curve by a constant factor derived from the Fibonacci sequence.
**What is its practical utility?** It provides dynamic resistance and support levels that move with the trend, offering price targets and profit-taking points that automatically adapt to market evolution.
### **Topological Preservation Principle**
The system maintains the **topological properties** of the base curve in all Fibonacci projections, ensuring that spatial and temporal relationships are consistently preserved across all resistance/support levels.
---
## **⚡ Adaptive Computational Optimization**
### **Multi-Scale Resolution Theory**
It implements **automatic multi-resolution analysis** where data granularity is dynamically adjusted according to the analysis timeframe. It uses the **adaptive Nyquist principle** to optimize the signal-to-noise ratio according to the temporal observation scale.
**Why is this necessary?** Different timeframes require different levels of detail. A 1-minute chart needs more granularity than a monthly one. This system automatically optimizes resolution for each case.
### **Adaptive Density Algorithm**
Calculation point density is optimized through **adaptive sampling theory**, where calculation frequency is adjusted according to local trend curvature and analysis timeframe, balancing visual precision with computational efficiency.
---
## **🛡️ Robustness and Fault Tolerance**
### **Graceful Degradation Theory**
The system implements **multi-level graceful degradation**, where under error conditions or insufficient data, the algorithm progressively falls back to simpler but reliable methods, maintaining basic functionality under any condition.
**What does this guarantee?** That the indicator functions consistently even with incomplete data, new symbols with limited history, or extreme market conditions.
### **State Consistency Principle**
It uses **mathematical invariants** to guarantee that the algorithm's internal state remains consistent between executions, implementing consistency checks that validate data structure integrity in each iteration.
---
## **🔍 Key Theoretical Innovations**
### **A. Contextual vs. Absolute Outlier Detection**
It revolutionizes traditional outlier detection by considering not only the absolute magnitude of deviations, but their relative significance within the local context of the time series.
**Practical impact:** It distinguishes between legitimate market movements and technical anomalies, preserving important events like breakouts while filtering noise.
### **B. Extrapolation with Weighted Historical Memory**
It implements a memory system that weights different historical periods according to their relevance for current prediction, creating projections more adaptable to market regime changes.
**Competitive advantage:** It automatically adapts to fundamental changes in asset dynamics without requiring manual recalibration.
### **C. Automatic Multi-Timeframe Adaptation**
It develops an automatic temporal resolution selection system that optimizes signal extraction according to the intrinsic characteristics of the analysis timeframe.
**Result:** A single indicator that functions optimally from 1-minute to monthly charts without manual adjustments.
### **D. Intelligent Asymptotic Convergence**
It introduces the concept of controlled asymptotic convergence in financial extrapolations, where long-term projections converge toward realistic limits based on historical fundamentals.
**Added value:** Mathematically sound long-term projections that avoid the unrealistic extremes typical of other extrapolation methods.
---
## **📊 Complexity and Scalability Theory**
### **Optimized Linear Complexity Model**
The algorithm maintains **linear computational complexity** O(n) in the number of historical data points, guaranteeing scalability for extensive time series analysis without performance degradation.
### **Temporal Locality Principle**
It implements **temporal locality**, where the most expensive operations are concentrated in the most relevant temporal regions (recent periods and near projections), optimizing computational resource usage.
---
## **🎯 Convergence and Stability**
### **Probabilistic Convergence Theory**
The system guarantees **probabilistic convergence** toward the real underlying trend, where projection accuracy increases with the amount of available historical data, following **law of large numbers** principles.
**Practical implication:** The more history an asset has, the more accurate the algorithm's projections will be.
### **Guaranteed Numerical Stability**
It implements **intrinsic numerical stability** through the use of robust floating-point arithmetic and validations that prevent overflow, underflow, and numerical error propagation.
**Result:** Reliable operation even with extreme-priced assets (from satoshis to thousand-dollar stocks).
---
## **💼 Comprehensive Practical Application**
**The algorithm functions as a "financial GPS"** that:
1. **Identifies where we've been** (significant historical lows)
2. **Determines where we are** (current position relative to the trend)
3. **Projects where we're going** (future trend with specific price levels)
4. **Provides alternative routes** (Fibonacci bands as alternative targets)
This theoretical framework represents an innovative synthesis of time series analysis, approximation theory, and computational optimization, specifically designed for long-term financial trend analysis with robust and mathematically grounded projections.
25 Day and 125 Day EMA Trend IndicatorThe "25 and 125 EMA Trend indicator," is a powerful yet simple tool designed for use on any TradingView chart. Its primary purpose is to help traders visually identify both short-term and long-term trends in the market.
How the Script Works
The script is built around two Exponential Moving Averages (EMAs), which are a type of moving average that gives more weight to recent price data. This makes them more responsive to current market changes than a Simple Moving Average (SMA). The two EMAs are:
Fast EMA (25-day): Represented by the blue line, this EMA reacts quickly to price fluctuations. It's excellent for identifying the current short-term direction and momentum of the asset.
Slow EMA (125-day): Represented by the purple line, this EMA smooths out price action over a much longer period. It's used to determine the underlying, long-term trend of the market.
Trading Signals and Interpretation
The real value of this script comes from observing the relationship between the two EMA lines.
Uptrend: When the blue (25-day) EMA is above the purple (125-day) EMA, it indicates that the short-term trend is stronger than the long-term trend, signaling a bullish or upward-moving market.
Downtrend: Conversely, when the blue EMA is below the purple EMA, it suggests that the short-term trend is weaker, indicating a bearish or downward-moving market.
Cross-overs: The most important signals are often generated when the two lines cross.
A bullish cross (or "golden cross") occurs when the blue EMA crosses above the purple EMA. This can be a signal that a new, strong uptrend is beginning.
A bearish cross (or "death cross") occurs when the blue EMA crosses below the purple EMA. This may signal the start of a new downtrend.
Customisation
The script includes user-friendly input fields that allow you to customise the lengths of both EMAs directly from the indicator's settings on the chart. This lets you experiment with different time frames and tailor the indicator to your specific trading strategy.
TFO + ADX with Histogram & SignalTrend Flow Oscillator (TFO + ADX) – Histogram + Signal
This version of the original TFO+ADX introduces a MACD-style histogram and signal line overlay for clearer momentum and trend visualization.
The Trend Flow Oscillator (TFO+ADX) blends two powerful volume-based tools — the Money Flow Index (MFI) and Chaikin Money Flow (CMF) — along with a normalized Average Directional Index (ADX). The result is a comprehensive momentum and trend strength tool that offers a more precise read on when markets are gaining or losing conviction.
⸻
How It Works
1.Money Flow Index (MFI)
• Measures volume-weighted buying/selling pressure using price and volume.
• Scaled between –1 and +1 for visual clarity.
2.Chaikin Money Flow (CMF)
• Evaluates volume distribution over time — institutional buying (accumulation) or selling (distribution).
• Also scaled between –1 and +1.
3.TFO Composite Line
• Combines MFI and CMF into a single flow reading.
• A signal line (EMA) tracks the trend of this flow.
• A histogram plots the difference between the TFO and its signal, giving clear signals on shifts in momentum.
4.Normalized ADX Overlay
• Shows trend strength on the same scale (–1 to +1).
• ADX > 0 indicates strong trending conditions.
• ADX < 0 signals weak or consolidating conditions.
⸻
Visual Interpretation
1. Histogram Bars
• Green: TFO is above the signal line → bullish momentum accelerating
• Red: TFO is below the signal line → bearish momentum building
• Bar height represents the strength of the momentum shift
2. Signal Line
• Tracks the smoothed trend of the TFO composite
• Histogram crossing above or below zero reflects momentum crossover and can act as entry or exit signals
3. TFO Raw Line (Optional)
• Still available for reference alongside the histogram
• Shows the unsmoothed blended money flow direction (MFI + CMF)
4. Extreme Zones
• Background shading appears when TFO exceeds ±1.0
• Helps highlight areas of stretched or unsustainable momentum, useful for spotting potential reversals or exhaustion
EMA Trend Confirmation with Alerts此脚本是基于EMA 200周期 50周期 20周期加以合并并进行改进的一个脚本指标,主要作用是用于观察趋势走向,其中有上升下降和震荡趋势,经过多数测试,此指标适用于短线交易,推荐周期为20或15,大周期和长线交易详见RSI+EMA结合指标
This script is an improved script indicator based on the EMA 200 period, 50 period, and 20 period. Its main function is to observe the trend direction, including up, down, and oscillating trends. After many tests, this indicator is suitable for short-term trading, and the recommended period is 20 or 15. For large-cycle and long-term trading, please refer to the RSI+EMA combination indicator.
Multi timeframe trendDESCRIPTION
This indicator, Multi Timeframe Trend, is a powerful tool designed to give traders a comprehensive overview of market trends across multiple timeframes using a single, customizable Exponential Moving Average (EMA). It visually displays whether the price is trading above or below the EMA on each timeframe, helping traders quickly determine the dominant trend at a glance.
The real-time dashboard is plotted directly on your chart and color-coded to show bullish (green) or bearish (red) conditions per timeframe, from 15 minutes to 1 week. It is especially helpful for identifying trend alignment across multiple timeframes—an essential component of many professional trading strategies.
USER INPUTS
* Enter the EMA length – Adjust the EMA period used in the trend calculation (default: 200)
* Table Size – Choose how large the on-chart table appears: "tiny", "small", "normal", or "large"
INDICATOR LOGIC
* The indicator calculates the EMA for each of the following timeframes: 1W, 1D, 4H, 1H, 30M, and 15M
* It checks whether the current close is above or below each EMA and labels it as:
* Bullish if close > EMA
* Bearish if close < EMA
* Each timeframe’s trend is displayed in a dynamic table in the top-right corner of the chart
* The background color of each cell changes according to trend condition for quick visual interpretation
* Real-time responsiveness: handles both historical and live bars to maintain accurate, flicker-free updates
WHY IT IS UNIQUE
* Combines multiple timeframe trend analysis into a single glance
* Clean and color-coded dashboard overlay for real-time trading decisions
* Avoids repainting using barstate logic for accurate trend updates
* Fully customizable table size and EMA length
* Works on any chart, including stocks, crypto, forex, indices
HOW USERS CAN BENEFIT FROM IT
* Multi-timeframe confirmation: Easily confirm alignment across timeframes before entering a trade
* Avoid false signals by ensuring higher timeframe trends agree with lower timeframe setups
* Enhance strategy filters: Use as a trend filter in combination with your existing entry indicators
* Quick market analysis: No need to switch between charts or manually calculate EMAs
* Visual clarity: Trend conditions are easy to read and interpret in real-time
Smart Deviation Trend Bands PRO + MTF Filter📌 Purpose
This indicator combines multi-level Deviation Bands (±1, ±2, ±3 standard deviations from SMA) with a Higher Timeframe (HTF) Trend Filter.
It helps traders identify potential bounce and breakout setups aligned with the dominant market trend.
🧠 How It Works
1. Deviation Bands
SMA(Length) is calculated as the centerline.
Standard deviations (±1, ±2, ±3) define multiple dynamic support and resistance zones.
Outer bands (±3) often mark overextended zones; inner bands (±1, ±2) show active trading areas.
2. HTF Trend Filter
A higher timeframe SMA (HTF SMA) acts as a trend confirmation tool.
Default filter timeframe: 1 Day.
Trend Up: Price > HTF SMA
Trend Down: Price < HTF SMA
3. Entry Signals
Long Signal: Price crosses above lower deviation band (+1) when HTF trend is UP.
Short Signal: Price crosses below upper deviation band (−1) when HTF trend is DOWN.
4. Visuals & Alerts
Bands plotted in red (upper) and green (lower).
Centerline = SMA in blue.
HTF SMA in orange.
Circles on chart mark entry points; alerts trigger automatically.
📈 How to Use
In trending markets: Trade with the HTF direction, using band touches for entries.
In mean-reversion setups: Outer bands can be used to spot potential overbought/oversold zones.
Combine with volume or price action for confirmation.
Recommended Timeframes: 1h, 4h, D.
Markets: Forex, Crypto, Stocks.
⚙️ Inputs
SMA Length
StdDev Multiplier 1 / 2 / 3
HTF Timeframe (default: D1)
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before live trading.
Smart Volatility Squeeze + Trend Filter📌 Purpose
This indicator detects volatility squeeze conditions when Bollinger Bands contract inside Keltner Channels and signals potential breakout opportunities.
It also includes an optional EMA-based trend filter to align signals with the dominant market direction.
🧠 How It Works
1. Squeeze Condition
Bollinger Bands (BB): Length = 20, StdDev = 2.0 (default)
Keltner Channels (KC): EMA Length = 20, ATR Multiplier = 1.5 (default)
Squeeze ON: Occurs when BB Upper < KC Upper and BB Lower > KC Lower (low volatility zone).
2. Breakout Signals
Long Breakout: Price crosses above BB Upper after squeeze.
Short Breakout: Price crosses below BB Lower after squeeze.
3. Trend Filter (optional)
EMA(50) used to confirm breakout direction:
Long signals allowed only if price > EMA(50)
Short signals allowed only if price < EMA(50)
Toggle Use Trend Filter to enable/disable.
4. Visual & Alerts
Green circle at chart bottom indicates Squeeze ON.
Green/Red triangles mark breakouts.
Background gradually brightens during squeeze buildup.
Alerts available for long and short breakouts.
📈 How to Use
Look for Squeeze ON → then wait for breakout arrows.
Trade in breakout direction, preferably with trend filter ON.
Works best on higher timeframes (1h, 4h, D) and trending markets.
Markets: Crypto, Forex, Stocks — effective in volatile assets.
⚙️ Inputs
BB Length / StdDev
KC EMA Length / ATR Multiplier
Use Trend Filter
Trend EMA Length
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before live trading.
Markov Chain Trend ProbabilityA Markov Chain is a mathematical model that predicts future states based on the current state, assuming that the future depends only on the present (not the past). Originally developed by Russian mathematician Andrey Markov, this concept is widely used in:
Finance: Risk modeling, portfolio optimization, credit scoring, algorithmic trading
Weather Forecasting: Predicting sunny/rainy days, temperature patterns, storm tracking
Here's an example of a Markov chain: If the weather is sunny, the probability that will be sunny 30 min later is say 90%. However, if the state changes, i.e. it starts raining, how the probability that will be raining 30 min later is say 70% and only 30% sunny.
Similar concept can be applied to markets price action and trends.
Mathematical Foundation
The core principle follows the Markov Property: P(X_{t+1}|X_t, X_{t-1}, ..., X_0) = P(X_{t+1}|X_t)
Transition Matrix :
-------------Next State
Current----
--------P11 P12
-----P21 P22
Probability Calculations:
P(Up→Up) = Count(Up→Up) / Count(Up states)
P(Down→Down) = Count(Down→Down) / Count(Down states)
Steady-state probability: π = πP (where π is the stationary distribution)
State Definition:
State = UPTREND if (Price_t - Price_{t-n})/ATR > threshold
State = DOWNTREND if (Price_t - Price_{t-n})/ATR < -threshold
How It Works in Trading
This indicator applies Markov Chain theory to market trends by:
Defining States: Classifies market conditions as UPTREND or DOWNTREND based on price movement relative to ATR (Average True Range)
Learning Transitions: Analyzes historical data to calculate probabilities of moving from one state to another
Predicting Probabilities: Estimates the likelihood of future trend continuation or reversal
How to Use
Parameters:
Lookback Period: Number of bars to analyze for trend detection (default: 14)
ATR Threshold: Sensitivity multiplier for state changes (default: 0.5)
Historical Periods: Sample size for probability calculations (default: 33)
Trading Applications:
Trend confirmation for entry/exit decisions
Risk assessment through probability analysis
Market regime identification
Early warning system for potential trend reversals
The indicator works on any timeframe and asset class. Enjoy!
Clarix Trend Filter Purpose
This indicator helps traders quickly identify strong bullish or bearish market conditions by combining a moving average and directional strength.
How It Works
SMMA (200): Smooths price to detect overall trend direction.
ADX (14): Measures trend strength, filtering out weak/noisy moves.
+DI / -DI: Directional movement indicators help confirm the dominant side.
Trend Logic
Bullish Trend: Price is above SMMA, ADX > threshold, and +DI > -DI
Bearish Trend: Price is below SMMA, ADX > threshold, and -DI > +DI
Otherwise, the trend is considered weak or unclear.
Features
Background shading for trend clarity
Optional buy/sell arrows based on trend confirmation
Configurable SMMA length and ADX threshold
Designed for 1-minute timeframes, but can be adjusted
Tips
Best used as a trend filter with your existing entry/exit strategy
Avoid trading signals when ADX is low (flat or ranging conditions)
Works well when combined with volume or momentum indicators
Price Volume Trend [sgbpulse]1. Introduction: What is Price Volume Trend (PVT)?
The Price Volume Trend (PVT) indicator is a powerful technical analysis tool designed to measure buying and selling pressure in the market based on price changes relative to trading volume. Unlike other indicators that focus solely on volume or price, PVT combines both components to provide a more comprehensive picture of trend strength.
How is it Calculated?
The PVT is calculated by adding or subtracting a proportional part of the daily volume from a cumulative total.
When the closing price rises, a proportional part of the daily volume (based on the percentage price change) is added to the previous PVT value.
When the closing price falls, a proportional part of the daily volume is subtracted from the previous PVT value.
If there is no change in price, the PVT value remains unchanged.
The result of this calculation is a cumulative line that rises when buying pressure is strong and falls when selling pressure dominates.
2. Why PVT? Comparison to Similar Indicators
While other indicators measure volume-price pressure, PVT offers a unique advantage:
PVT vs. On-Balance Volume (OBV):
OBV simply adds or subtracts the entire day's volume based on the closing direction (up/down), regardless of the magnitude of the price change. This means a 0.1% price change is treated the same as a 10% change.
PVT, on the other hand, gives proportional weight to volume based on the percentage price change. A trading day with a large price increase and high volume will impact the PVT significantly more than a small price increase with the same volume. This makes PVT more sensitive to trend strength and changes within it.
PVT vs. Accumulation/Distribution Line (A/D Line):
The A/D Line focuses on the relationship between the closing price and the bar's trading range (Close Location Value) and multiplies it by volume. It indicates whether the pressure is buying or selling within a single bar.
PVT focuses on the change between closing prices of consecutive bars, multiplying this by volume. It better reflects the flow of money into or out of an asset over time.
By combining volume with percentage price change, PVT provides deeper insights into trend confirmation, identifying divergences between price and volume, and spotting signs of weakness or strength in the current trend.
3. Indicator Settings (Inputs)
The "Price Volume Trend " indicator offers great flexibility for customization to your specific needs through the following settings:
Moving Average Type: Allows you to select the type of moving average used for the central line on the PVT. Your choice here will affect the line's responsiveness to PVT movements.
- "None" : No moving average will be displayed on the PVT.
- "SMA" (Simple Moving Average): A simple average, smoother, ideal for identifying longer-term trends in PVT.
- "SMA + Bollinger Bands": This unique option not only displays a Simple Moving Average but also activates the Bollinger Bands around the PVT. This is the recommended option for analyzing volatility and ranges using Bollinger Bands.
- "EMA" (Exponential Moving Average): An exponential average, giving more weight to recent data, responding faster to changes in PVT.
- "SMMA (RMA)" (Smoothed Moving Average): A smoothed average, providing extra smoothing, less sensitive to noise.
- "WMA" (Weighted Moving Average): A weighted average, giving progressively more weight to recent data, responding very quickly to changes in PVT.
Moving Average Length: Defines the number of bars used to calculate the moving average (and, if applicable, the standard deviation for the Bollinger Bands). A lower value will make the line more responsive, while a higher value will smooth it out.
PVT BB StdDev (Bollinger Bands Standard Deviation): Determines the width of the Bollinger Bands. A higher value will result in wider bands, making it less likely for the PVT to cross them. The standard value is 2.0.
4. Visual Aid: Current PVT Level Line
This indicator includes a unique and highly useful visual feature: a dynamic horizontal line displayed on the PVT graph.
Purpose: This line marks the exact level of the PVT on the most recent trading bar. It extends across the entire chart, allowing for a quick and intuitive comparison of the current level to past levels.
Why is it Important?
- Identifying Divergences: Often, an asset's price may be lower or higher than past levels, but the PVT level might be different. This auxiliary line makes it easy to spot situations where PVT is at a higher level when the price is lower, or vice-versa, which can signal potential trend changes (e.g., higher PVT than in the past while price is low could indicate strong accumulation).
- Quick Direction Indication: The line's color changes dynamically: it will be green if the PVT value on the last bar has increased (or remained the same) relative to the previous bar (indicating positive buying pressure), and red if the PVT value has decreased relative to the previous bar (indicating selling pressure). This provides an immediate visual cue about the direction of the cumulative momentum.
5. Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Monthly Seasonality Trend [DunesIsland]The Monthly Seasonality Trend is a indicator designed to analyze and visualize historical monthly seasonality patterns in financial markets. By calculating the average monthly return over a user-configurable lookback period (1 to 10 years), this indicator provides traders and investors with a clear projection of potential price movements for the current month, enabling data-driven decision-making.
How It Works
The indicator operates by retrieving monthly open and close prices for the specified lookback period (up to 10 years) and computing the average percentage return for the current month based on historical data. Key functionalities include:
Dynamic Trend Line: On the first trading day of each month, the indicator plots a line projecting the expected price trajectory, starting from the current close price and extending to the estimated end-of-month price based on the average historical return. The line is colored green for anticipated price increases or red for expected declines, offering an intuitive visual cue.
Average Return Label: A label is displayed at the start of each month, detailing the calculated average historical return for that month, expressed as a percentage, to provide context for the projected trend.
First Trading Day Marker: A small circle is plotted below the bar on the first trading day of each month, clearly marking the start of the projection period.
Adaptive Bar Counting: The indicator dynamically adjusts the length of the trend line based on the actual number of trading days in the previous month, ensuring accurate projections.
How to Interpret
Bullish Projection (Green Line): Indicates that historical data suggests an average price increase for the current month, potentially signaling buying opportunities.
Bearish Projection (Red Line): Suggests an average price decline based on historical trends, which may prompt caution or short-selling strategies.
Historical Context: The average return label provides a quantitative measure of past performance, helping traders assess the reliability of the projected trend.
BACAP PRICE STRUCTURE 21 EMA TREND21dma-STRUCTURE
Overview
The 21dma-STRUCTURE indicator is a sophisticated overlay indicator that visualizes price action relative to a triple 21-period exponential moving average structure. Originally developed by BalarezoCapital and enhanced by PrimeTrading, this indicator provides clear visual cues for trend direction and momentum through dynamic bar coloring and EMA structure analysis.
Key Features
Triple EMA Structure
- 21 EMA High: Tracks the exponential moving average of high prices
- 21 EMA Close: Tracks the exponential moving average of closing prices
- 21 EMA Low: Tracks the exponential moving average of low prices
- Dynamic Cloud: Gray fill between high and low EMAs for visual structure reference
Smart Bar Coloring System
- Blue Bars: Price closes above all three EMAs (strong bullish momentum)
- Pink Bars: Daily high falls below the lowest EMA (strong bearish signal)
- Gray Bars: Neutral conditions or transitional phases
- Color Memory: Maintains previous color until new condition is met
Dynamic Center Line
- Trend-Following Color: Green when all EMAs are rising, red when all are falling
- Color Persistence: Maintains trend color during sideways movement
- Visual Clarity: Thicker center line for easy trend identification
Customizable Visual Elements
- Adjustable line thickness for all EMA plots
- Customizable colors for bullish and bearish conditions
- Configurable trend colors for uptrend and downtrend phases
- Optional bar color changes with toggle control
How to Use
Trend Identification
- Rising Green Center Line: All EMAs trending upward (bullish structure)
- Falling Red Center Line: All EMAs trending downward (bearish structure)
- Flat Center Line: Maintains last trend color during consolidation
Momentum Analysis
- Blue Bars: Strong bullish momentum with price above entire EMA structure
- Pink Bars: Strong bearish momentum with high below lowest EMA
- Gray Bars: Neutral or transitional momentum phases
Entry and Exit Signals
- Bullish Setup: Look for blue bars during green center line periods
- Bearish Setup: Look for pink bars during red center line periods
- Exit Consideration: Watch for color changes as potential momentum shifts
Structure Trading
- Support/Resistance: Use EMA cloud as dynamic support and resistance zones
- Breakout Confirmation: Bar color changes can confirm structure breakouts
- Trend Continuation: Color persistence suggests ongoing momentum
Settings
Visual Customization
- Change Bar Color: Toggle to enable/disable bar coloring
- Line Size: Adjust thickness of EMA lines (default: 3)
- Bullish Candle Color: Customize blue bar color
- Bearish Candle Color: Customize pink bar color
Trend Colors
- Uptrend Color: Color for rising EMA center line (default: green)
- Downtrend Color: Color for falling EMA center line (default: red)
- Cloud Color: Fill color between high and low EMAs (default: gray)
Advanced Features
Modified Bar Logic
Unlike traditional EMA systems, this indicator uses refined conditions:
- Bullish signals require close above ALL three EMAs
- Bearish signals require high below the LOWEST EMA
- Enhanced precision reduces false signals compared to single EMA systems
Trend Memory System
- Intelligent color persistence during sideways movement
- Reduces noise from minor EMA fluctuations
- Maintains trend context during consolidation periods
Performance Optimization
- Efficient calculation methods for real-time performance
- Clean visual design that doesn't clutter charts
- Compatible with all timeframes and instruments
Best Practices
Multi-Timeframe Analysis
- Use higher timeframes to identify overall trend direction
- Apply on multiple timeframes for confluence
- Combine with weekly/monthly charts for position trading
Risk Management
- Use bar color changes as early warning signals
- Consider position sizing based on EMA structure strength
- Set stops relative to EMA support/resistance levels
Combination Strategies
- Pair with volume indicators for confirmation
- Use alongside RSI or MACD for momentum confirmation
- Combine with key support/resistance levels
Market Context
- More effective in trending markets than choppy conditions
- Consider overall market environment and sector strength
- Adjust expectations during high volatility periods
Technical Specifications
- Based on 21-period exponential moving averages
- Uses Pine Script v6 for optimal performance
- Overlay indicator that works with any chart type
- Maximum 500 lines for clean performance
Ideal Applications
- Swing trading on daily charts
- Position trading on weekly charts
- Intraday momentum trading (adjust timeframe accordingly)
- Trend following strategies
- Structure-based trading approaches
Disclaimer
This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis, proper risk management, and consider your individual trading plan and risk tolerance.
Compatible with Pine Script v6 | Works on all timeframes | Optimized for trending markets
Kaufman Trend Strength Signal█ Overview
Kaufman Trend Strength Signal is an advanced trend detection tool that decomposes price action into its underlying directional trend and localized oscillation using a vector-based Kalman Filter.
By integrating adaptive smoothing and dynamic weighting via a weighted moving average (WMA), this indicator provides real-time insight into both trend direction and trend strength — something standard moving averages often fail to capture.
The core model assumes that observed price consists of two components:
(1) a directional trend, and
(2) localized noise or oscillation.
Using a two-step Predict & Update cycle, the filter continuously refines its trend estimate as new market data becomes available.
█ How It Works
This indicator employs a Kalman Filter model that separates the trend from short-term fluctuations in a price series.
Predict & Update Cycle : With each new bar, the filter predicts the price state and updates that prediction using the latest observed price, producing a smooth but adaptive trend line.
Trend Strength Normalization : Internally, the oscillator component is normalized against recent values (N periods) to calculate a trend strength score between -100 and +100.
(Note: The oscillator is not plotted on the chart but is used for signal generation.)
Filtered MA Line : The trend component is plotted as a smooth Kalman Filter-based moving average (MA) line on the main chart.
Threshold Cross Signals : When the internal trend strength crosses a user-defined threshold (default: ±60), visual entry arrows are displayed to signal momentum shifts.
█ Key Features
Adaptive Trend Estimation : Real-time filtering that adjusts dynamically to market changes.
Visual Buy/Sell Signals : Entry arrows appear when the trend strength crosses above or below the configured threshold.
Built-in Range Filter : The MA line turns blue when trend strength is weak (|value| < 10), helping you filter out choppy, sideways conditions.
█ How to Use
Trend Detection :
• Green MA = bullish trend
• Red MA = bearish trend
• Blue MA = no trend / ranging market
Entry Signals :
• Green triangle = trend strength crossed above +Threshold → potential bullish entry
• Red triangle = trend strength crossed below -Threshold → potential bearish entry
█ Settings
Entry Threshold : Level at which the trend strength triggers entry signals (default: 60)
Process Noise 1 & 2 : Control the filter’s responsiveness to recent price action. Higher = more reactive; lower = smoother.
Measurement Noise : Sets how much the filter "trusts" price data. High = smoother MA, low = faster response but more noise.
Trend Lookback (N2) : Number of bars used to normalize trend strength. Lower = more sensitive; higher = more stable.
Trend Smoothness (R2) : WMA smoothing applied to the trend strength calculation.
█ Visual Guide
Green MA Line → Bullish trend
Red MA Line → Bearish trend
Blue MA Line → Sideways/range
Green Triangle → Entry signal (trend strengthening)
Red Triangle → Entry signal (trend weakening)
█ Best Practices
In high-volatility conditions, increase Measurement Noise to reduce false signals.
Combine with other indicators (e.g., RSI, MACD, EMA) for confirmation and filtering.
Adjust "Entry Threshold" and noise settings depending on your timeframe and trading style.
❗ Disclaimer
This script is provided for educational purposes only and should not be considered financial advice or a recommendation to buy/sell any asset.
Trading involves risk. Past performance does not guarantee future results.
Always perform your own analysis and use proper risk management when trading.
Arnaud Legoux Trend Aggregator | Lyro RSArnaud Legoux Trend Aggregator
Introduction
Arnaud Legoux Trend Aggregator is a custom-built trend analysis tool that blends classic market oscillators with advanced normalization, advanced math functions and Arnaud Legoux smoothing. Unlike conventional indicators, 𝓐𝓛𝓣𝓐 aggregates market momentum, volatility and trend strength.
Signal Insight
The 𝓐𝓛𝓣𝓐 line visually reflects the aggregated directional bias. A rise above the middle line threshold signals bullish strength, while a drop below the middle line indicates bearish momentum.
Another way to interpret the 𝓐𝓛𝓣𝓐 is through overbought and oversold conditions. When the 𝓐𝓛𝓣𝓐 rises above the +0.7 threshold, it suggests an overbought market and signals a strong uptrend. Conversely, a drop below the -0.7 level indicates an oversold condition and a strong downtrend.
When the oscillator hovers near the zero line, especially within the neutral ±0.3 band, it suggests that no single directional force is dominating—common during consolidation phases or pre-breakout compression.
Real-World Example
Usually 𝓐𝓛𝓣𝓐 is used by following the bar color for simple signals; however, like most indicators there are unique ways to use an indicator. Let’s dive deep into such ways.
The market begins with a green bar color, raising awareness for a potential long setup—but not a direct entry. In this methodology, bar coloring serves as an alert mechanism rather than a strict entry trigger.
The first long position was initiated when the 𝓐𝓛𝓣𝓐 signal line crossed above the +0.3 threshold, suggesting a shift in directional acceleration. This entry coincided with a rising price movement, validating the trade.
As price advanced, the position was exited into cash—not reversed into a short—because the short criteria for this use case are distinct. The exit was prompted by 𝓐𝓛𝓣𝓐 crossing back below the +0.3 level, signaling the potential weakening of the long trend.
Later, as 𝓐𝓛𝓣𝓐 crossed below 0, attention shifted toward short opportunities. A short entry was confirmed when 𝓐𝓛𝓣𝓐 dipped below -0.3, indicating growing downside momentum. The position was eventually closed when 𝓐𝓛𝓣𝓐 crossed back above the -0.3 boundary—signaling a possible deceleration of the bearish move.
This logic was consistently applied in subsequent setups, emphasizing the role of 𝓐𝓛𝓣𝓐’s thresholds in guiding both entries and exits.
Framework
The Arnaud Legoux Trend Aggregator (ALTA) combines multiple technical indicators into a single smoothed signal. It uses RSI, MACD, Bollinger Bands, Stochastic Momentum Index, and ATR.
Each indicator's output is normalized to a common scale to eliminate bias and ensure consistency. These normalized values are then transformed using a hyperbolic tangent function (Tanh).
The final score is refined with a custom Arnaud Legoux Moving Average (ALMA) function, which offers responsive smoothing that adapts quickly to price changes. This results in a clear signal that reacts efficiently to shifting market conditions.
⚠️ WARNING ⚠️: THIS INDICATOR, OR ANY OTHER WE (LYRO RS) PUBLISH, IS NOT FINANCIAL OR INVESTMENT ADVICE. EVERY INDICATOR SHOULD BE COMBINED WITH PRICE ACTION, FUNDAMENTALS, OTHER TECHNICAL ANALYSIS TOOLS & PROPER RISK. MANAGEMENT.
21-Day Trend Direction📈 21-Day Trend Direction Indicator
📊 How It Works:
🎯 Trend Detection Logic:
Analyzes last 21 daily candles
Calculates total price change from start to end
Compares against sideways threshold (default 2%)
Counts bullish vs bearish days
Tracks higher highs and lower lows
📈 Trend Classifications:
• 📈 UPTREND: Price change > +2% over 21 days
• 📉 DOWNTREND: Price change < -2% over 21 days
• ➡️ SIDEWAYS: Price change between -2% and +2%
💪 Trend Strength Levels:
• 🔥 Very Strong: >5% price change
• 💪 Strong: 3-5% price change
• 📊 Moderate: 1.5-3% price change
• 📉 Weak: <1.5% price change
🎨 Visual Features:
📋 Information Table Shows:
• Trend Direction with color coding
• Price Change % over 21 days
• Trend Strength classification
• Bull/Bear Days count
• Higher Highs/Lower Lows count
• Analysis Period (customizable)
📊 Chart Indicators:
• Trend Line (21-day moving average)
• Background Color for quick trend identification
• Trend Arrows (▲ ▼ ➡) on chart
• Customizable display options
⚙️ Customizable Settings:
🎯 Analysis Settings:
• Lookback Days: 5-50 days (default: 14)
• Sideways Threshold: 0.5-10% (default: 2%)
• Trend Strength: Low/Medium/High sensitivity
🎨 Display Options:
• Table Position: 9 different positions
• Table Size: Tiny to Large
• Show/Hide: Table, Trend Line, Background, Arrows
🚨 Alert Options:
• Trend Change to Uptrend
• Trend Change to Downtrend
• Trend Change to Sideways
This indicator gives you a clear, objective view of the 21-day trend with multiple confirmation signals! 🚀
MFI Candle Trend🎯 Purpose:
The MFI Candle Trend is a custom TradingView indicator that transforms the Money Flow Index (MFI) into candle-style visuals using various smoothing and transformation techniques. Rather than displaying MFI as a line, this script generates synthetic candles from MFI values, helping traders visualize money flow trends, strength, and potential reversals with more clarity.
📌 Trend strength can be analyzed based on buying and selling pressures in the trend direction.
🧩 How It Works:
Calculates MFI values for open, high, low, and close prices.
Applies optional smoothing using the user-selected moving average (EMA, SMA, WMA, etc.).
Transforms the smoothed MFI data into synthetic candles using a selected method:
Normal: Uses raw MFI data
Heikin-Ashi: Applies HA transformation to MFI
Linear: Uses linear regression on MFI values
Rational Quadratic: Applies advanced rational quadratic filtering via an external kernel library
Colors candles based on MFI momentum:
Cyan: Strong positive MFI movement
Red: Strong negative MFI movement
⚙️ Key Inputs:
Method:
The type of smoothing method to apply to MFI
Options: None, EMA, SMA, SMMA (RMA), WMA, VWMA, HMA, Mode
Length:
Period for both the MFI and smoothing calculation
Candle:
Selects the transformation mode for generating synthetic candles
Options: Normal, Heikin-Ashi, Linear, Rational Quadratic
Rational Quadratic:
Adjusts the depth of smoothing for the Rational Quadratic filter (applies only if selected)
📊 Outputs:
Synthetic MFI Candlesticks:
Plotted using the smoothed and transformed MFI values.
Dynamic Coloring:
Cyan when MFI momentum is increasing
Red when MFI momentum is decreasing
Horizontal Lines:
80: Overbought zone
20: Oversold zone
🧠 Why Use This Indicator?
Unlike traditional MFI indicators that use a line plot, this tool gives traders:
A candle-based visualization of money flow momentum
Enhanced trend and reversal detection using color-coded MFI candles
A choice of smoothing filters and transformations for noise reduction
A powerful combination of momentum and structure-based analysis
To combine volume and price strength into a single chart element
❗Important Note:
This indicator is for educational and analytical purposes only. It does not constitute financial advice. Always use proper risk management and validate with additional tools or analysis.