Multi Timeframe Trending State DetectionThis script shows the "trending" state of a symbol at a certain moment in time on a certain set of timeframes. A trending symbol is a symbol that is moving out of a current balanced state to search for a new accepted price level. The detection of the state is done by looking at the place where the current price is related to 2 bollinger bands.
Depending on the place where the price is, the symbol is ...
a) ... not trending. It is chopping around. (Color Gray)
b) ... trending. The trend shows a certain strength. (Color Green for uptrend, Color Red for downtrend)
c) ... trending and arriving at (a temporary) peak and can possibly revert. Good for profit taking, or entering counter-trend. (Color Yellow for uptrend, Color Orange for downtrend)
By moving over the current main chart, you can see in the data window at the right, what was the state on a certain date for all timeframes together. All states are color-coded. By checking the bubble help in input, a textual explanation of the actual colored states (1 per timeframe) is displayed on top of the history and is updated at every change. To read well the bubble help, the control has to be set on full-screen temporarily.
The script is dynamic in 2 dimensions.
a) When you select a certain timeframe, all lower timeframes will not be displayed. Only the higher supported timeframes are included.
b) In input, you can specifiy a subset of timeframes you want to follow by checking or unchecking the appropriate timeframes.
The combination of the 2 selections gives you the ultimate list of timeframes shown.
You can infuence the detection by selecting in input another set of bollinger bands, characterized by the number of standard deviations and the length of the mean needed for the calculation of the bollinger bands .
How to read the indictor ?
A horizontal line gives you the history of the "trending state" on 1 timeframe over all bars accessible.
A vertical column gives you the "trending state" on all timeframes at a certain bar.
The last vertical column gives you the most recent "trending state" on all timeframes.
Поиск скриптов по запросу "trend"
Trend Channel [Gu5]SMA 200 determines the trend
Bullish trend, green candles. Down trend, red candles.
If the market value is narrow to the SMA200 channel, yellow candles.
Setting recommended for SMA Range
BTCUSD = 100
EURUSD = 1000
SPX = 100
ETHUSD = 10
MSignal Trend Continuation Indicator Msignal Trend Continuation Indicator
Alerts continuation trading patterns and signals trades that take advantage of price action turning points.
It seeks to find near term support and resistance levels and then identifies places on the chart to entry, and take profit of the established short term trend.
The indicator is based in price action and market timing algorithms to determine these turning points at significant price levels in the markets.
That way, you can be sure you have chance to enter in the market at the best level of the trend and take a high probability trade and ride the best part of the trend.
Once the MSignal indicator has spotted a continuation pattern, it clearly displays a Buy or Sell signal on your chart, showing you exactly where possible entry to continue with the trend.
ITekSignal Full v1.0 Trend REVERSAL and CONTINUATION ITekSignal Trading System helps you identify trend reversals — quickly and accurately.
There’s a price action pattern that occurs in every market and on every time-frame.
This price pattern shows a fight for balance, between seller and buyers…
When the pattern is completed, that means the fight for balance has ended.
And you’d know which side has won: Seller or Buyers, Supply or Demand, Bulls or Bears.
Once ITekSignal indicator has spotted a reversal, it clearly displays these Buy or Sell alerts on your charts… showing you exactly where possible reversals may occur.
ITekSignal Indicator will draw an up/down arrow on your chart, telling you there’s a trade opportunity for you to consider. So we’d enter the market for a ride of the new trend.
The indicator is also capable of detecting CONTINUATION pattern (in addition to REVERSAL patterns)
ITekSignal indicator gives you all kinds of alerts you’ll ever need:
Trend Reversal alert & Trend Continuation alerts
Contact the Author for Subscription
@iteksignal
iteksignal@gmail.com
Trend Following Reflectometry🧭 Trend Following Reflectometry (TFR)
Author: Stef Jonker
Version: Pine Script® v6
The Trend Following Reflectometry (TFR) indicator translates market behavior into the language of impedance and signal reflection theory, providing a unique way to measure trend strength, stability, and purity.
🧩 Summary
Trend Following Reflectometry acts as a trend-quality meter, helping traders identify when a trend is strong, efficient, and worth following — or when the market is too noisy to trust.
It blends physics-inspired logic with practical trading insight, offering both a directional oscillator and a trend stability filter in one tool.
⚙️ Concept
Inspired by electrical impedance matching, this tool compares the market’s characteristic impedance (Z₀) — its natural volatility-to-price behavior — with the load impedance (Zₗ), representing current trend momentum.
The interaction between these two produces a reflection coefficient (Gamma) and a VSWR ratio, which reveal how efficiently market trends are transmitting energy (moving smoothly) versus reflecting noise (becoming unstable).
📊 Core Components
Z₀ (Characteristic Impedance): Market baseline, derived from ATR and SMA.
Zₗ (Load Impedance): Trend momentum based on fast and slow EMAs.
Γ (Gamma – Reflection Coefficient): Measures the mismatch between Z₀ and Zₗ.
VSWR (Voltage Standing Wave Ratio): Quantifies trend purity — lower = cleaner trend.
Impedance Oscillator: Combines momentum and reflection to produce directional bias.
⚡ Gamma & VSWR Interpretation
Gamma (Γ) represents the reflection coefficient — how much of the market’s trend energy is being reflected instead of transmitted.
When Gamma is low, the market trend is smooth and efficient, moving with little resistance.
When Gamma is high, the market becomes unstable or overextended, signaling potential turbulence, exhaustion, or reversal pressure.
VSWR (Voltage Standing Wave Ratio) measures trend purity — how clean or distorted the current trend is.
A low VSWR indicates a well-aligned, steady trend that’s likely to continue smoothly.
A high VSWR suggests an unbalanced or noisy market, where trends may struggle to sustain or could soon reverse.
Together, Gamma and VSWR help identify how well the market’s current momentum aligns with its natural behavior — whether the trend is stable and efficient or reflecting instability beneath the surface.
Trendline MTF Optimized1️⃣ What the Script Does
The script automatically draws trendlines connecting pivot highs and lows for multiple timeframes on your chart.
Pivot highs → connect recent tops
Pivot lows → connect recent bottoms
It also shows a legend so you can see which line belongs to which timeframe.
Why it’s useful:
Helps spot trend direction across multiple timeframes at a glance.
Highlights support and resistance levels automatically.
Useful for scalpers, swing traders, and multi-timeframe analysis.
2️⃣ Inputs the User Can Adjust
Input What it Means for the User
Pivot Left Bars How many bars to the left the script checks to confirm a pivot. More bars → stronger pivot, slower reaction.
Pivot Right Bars How many bars to the right it checks. Similar effect as left bars.
Show Debug Pivot Labels Shows the exact pivot values on the chart. Good for learning or checking accuracy.
Show Legend Shows the small table with line symbols and timeframes. Helps you quickly know which line belongs to which timeframe.
3️⃣ Timeframes
The script automatically calculates pivot points for multiple timeframes:
1 min, 3 min, 5 min, 15 min, 30 min, 1 hour, 4 hours, 1 day
Each timeframe gets its own color and line thickness. This helps distinguish them visually.
4️⃣ How Trendlines Are Drawn
Pivot Highs (Red lines): Connects the previous top to the most recent top on that timeframe.
Pivot Lows (Green lines): Connects the previous bottom to the most recent bottom.
If there’s no previous pivot yet, it just starts the line at the first pivot detected.
Optional debug labels show the price and timeframe of each pivot.
User Benefit: You can instantly see short-term and long-term trendlines without manual drawing.
5️⃣ Legend Table
Shows which line corresponds to which timeframe.
Uses small bar symbols (▁▁▁▁▁, ▂▂▂▂▂, etc.) to match line thickness.
Placed at the top-right corner by default.
User Benefit: Even if the chart is cluttered, you always know which line represents which timeframe.
6️⃣ How a User Reads It on the Chart
Red line going down → recent highs are decreasing → short-term downtrend.
Green line going up → recent lows are increasing → short-term uptrend.
Multiple lines of different thickness/colors → different timeframes.
Crossovers of lines or areas where green and red lines converge → potential support/resistance zones.
7️⃣ User Actionable Tips
Adjust left/right bars for sensitivity:
Lower bars → trendlines react faster (good for scalping).
Higher bars → trendlines smoother (good for swing trades).
Use debug labels initially to see pivot points.
Check legend to quickly identify which line belongs to which timeframe.
Combine trendlines with other indicators (like RSI, ADX) for better signals.
✅ Summary for Users
“This script automatically draws support/resistance trendlines across multiple timeframes, labels pivots optionally, and shows a legend so you know which line belongs to which timeframe. Adjust pivot sensitivity to match your trading style.”
Luxy Adaptive MA Cloud - Trend Strength & Signal Tracker V2Luxy Adaptive MA Cloud - Professional Trend Strength & Signal Tracker
Next-generation moving average cloud indicator combining ultra-smooth gradient visualization with intelligent momentum detection. Built for traders who demand clarity, precision, and actionable insights.
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WHAT MAKES THIS INDICATOR SPECIAL?
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Unlike traditional MA indicators that show static lines, Luxy Adaptive MA Cloud creates a living, breathing visualization of market momentum. Here's what sets it apart:
Exponential Gradient Technology
This isn't just a simple fill between two lines. It's a professionally engineered gradient system with 26 precision layers using exponential density distribution. The result? An organic, cloud-like appearance where the center is dramatically darker (15% transparency - where crossovers and price action occur), while edges fade gracefully (75% transparency). Think of it as a visual "heat map" of trend strength.
Dynamic Momentum Intelligence
Most MA clouds only show structure (which MA is on top). This indicator shows momentum strength in real-time through four intelligent states:
- 🟢 Bright Green = Explosive bullish momentum (both MAs rising strongly)
- 🔵 Blue = Weakening bullish (structure intact, but momentum fading)
- 🟠 Orange = Caution zone (bearish structure forming, weak momentum)
- 🔴 Deep Red = Strong bearish momentum (both MAs falling)
The cloud literally tells you when trends are accelerating or losing steam.
Conditional Performance Architecture
Every calculation is optimized for speed. Disable a feature? It stops calculating entirely—not just hidden, but not computed . The 26-layer gradient only renders when enabled. Toggle signals off? Those crossover checks don't run. This makes it one of the most efficient cloud indicators available, even with its advanced visual system.
Zero Repaint Guarantee
All signals and momentum states are based on confirmed bar data only . What you see in historical data is exactly what you would have seen trading live. No lookahead bias. No repainting tricks. No signals that "magically" appear perfect in hindsight. If a signal shows in history, it would have triggered in real-time at that exact moment.
Educational by Design
Every single input includes comprehensive tooltips with:
- Clear explanations of what each parameter does
- Practical examples of when to use different settings
- Recommended configurations for scalping, day trading, and swing trading
- Real-world trading impact ("This affects entry timing" vs "This is visual only")
You're not just getting an indicator—you're learning how to use it effectively .
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THE GRADIENT CLOUD - TECHNICAL DETAILS
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Architecture:
26 precision layers for silk-smooth transitions
Exponential density curve - layers packed tightly near center (where crossovers happen), spread wider at edges
75%-15% transparency range - center is highly opaque (15%), edges fade gracefully (75%)
V-Gradient design - emphasizes the action zone between Fast and Medium MAs
The Four Momentum States:
🟢 GREEN - Strong Bullish
Fast MA above Medium MA
Both MAs rising with momentum > 0.02%
Action: Enter/hold LONG positions, strong uptrend confirmed
🔵 BLUE - Weak Bullish
Fast MA above Medium MA
Weak or flat momentum
Action: Caution - bullish structure but losing strength, consider trailing stops
🟠 ORANGE - Weak Bearish
Medium MA above Fast MA
Weak or flat momentum
Action: Warning - bearish structure developing, consider exits
🔴 RED - Strong Bearish
Medium MA above Fast MA
Both MAs falling with momentum < -0.02%
Action: Enter/hold SHORT positions, strong downtrend confirmed
Smooth Transitions: The momentum score is smoothed using an 8-bar EMA to eliminate noise and prevent whipsaws. You see the true trend , not every minor fluctuation.
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FLEXIBLE MOVING AVERAGE SYSTEM
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Three Customizable MAs:
Fast MA (default: EMA 10) - Reacts quickly to price changes, defines short-term momentum
Medium MA (default: EMA 20) - Balances responsiveness with stability, core trend reference
Slow MA (default: SMA 200, optional) - Long-term trend filter, major support/resistance
Six MA Types Available:
EMA - Exponential; faster response, ideal for momentum and day trading
SMA - Simple; smooth and stable, best for swing trading and trend following
WMA - Weighted; middle ground between EMA and SMA
VWMA - Volume-weighted; reflects market participation, useful for liquid markets
RMA - Wilder's smoothing; used in RSI/ADX, excellent for trend filters
HMA - Hull; extremely responsive with minimal lag, aggressive option
Recommended Settings by Trading Style:
Scalping (1m-5m):
Fast: EMA(5-8)
Medium: EMA(10-15)
Slow: Not needed or EMA(50)
Day Trading (5m-1h):
Fast: EMA(10-12)
Medium: EMA(20-21)
Slow: SMA(200) for bias
Swing Trading (4h-1D):
Fast: EMA(10-20)
Medium: EMA(34-50)
Slow: SMA(200)
Pro Tip: Start with Fast < Medium < Slow lengths. The gradient works best when there's clear separation between Fast and Medium MAs.
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CROSSOVER SIGNALS - CLEAN & RELIABLE
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Golden Cross ⬆ LONG Signal
Fast MA crosses above Medium MA
Classic bullish reversal or trend continuation signal
Most reliable when accompanied by GREEN cloud (strong momentum)
Death Cross ⬇ SHORT Signal
Fast MA crosses below Medium MA
Classic bearish reversal or trend continuation signal
Most reliable when accompanied by RED cloud (strong momentum)
Signal Intelligence:
Anti-spam filter - Minimum 5 bars between signals prevents noise
Clean labels - Placed precisely at crossover points
Alert-ready - Built-in ALERTS for automated trading systems
No repainting - Signals based on confirmed bars only
Signal Quality Assessment:
High-Quality Entry:
Golden Cross + GREEN cloud + Price above both MAs
= Strong bullish setup ✓
Low-Quality Entry (skip or wait):
Golden Cross + ORANGE cloud + Choppy price action
= Weak bullish setup, likely whipsaw ✗
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REAL-TIME INFO PANEL
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An at-a-glance dashboard showing:
Trend Strength Indicator:
Visual display of current momentum state
Color-coded header matching cloud color
Instant recognition of market bias
MA Distance Table:
Shows percentage distance of price from each enabled MA:
Green rows : Price ABOVE MA (bullish)
Red rows : Price BELOW MA (bearish)
Gray rows : Price AT MA (rare, decision point)
Distance Interpretation:
+2% to +5%: Healthy uptrend
+5% to +10%: Getting extended, caution
+10%+: Overextended, expect pullback
-2% to -5%: Testing support
-5% to -10%: Oversold zone
-10%+: Deep correction or downtrend
Customization:
4 corner positions
5 font sizes (Tiny to Huge)
Toggle visibility on/off
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HOW TO USE - PRACTICAL TRADING GUIDE
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STRATEGY 1: Trend Following
Identify trend : Wait for GREEN (bullish) or RED (bearish) cloud
Enter on signal : Golden Cross in GREEN cloud = LONG, Death Cross in RED cloud = SHORT
Hold position : While cloud maintains color
Exit signals :
• Cloud turns ORANGE/BLUE = momentum weakening, tighten stops
• Opposite crossover = close position
• Cloud turns opposite color = full reversal
STRATEGY 2: Pullback Entries
Confirm trend : GREEN cloud established (bullish bias)
Wait for pullback : Price touches or crosses below Fast MA
Enter when : Price rebounds back above Fast MA with cloud still GREEN
Stop loss : Below Medium MA or recent swing low
Target : Previous high or when cloud weakens
STRATEGY 3: Momentum Confirmation
Your setup triggers : (e.g., chart pattern, support/resistance)
Check cloud color :
• GREEN = proceed with LONG
• RED = proceed with SHORT
• BLUE/ORANGE = skip or reduce size
Use gradient as confluence : Not as primary signal, but as momentum filter
Risk Management Tips:
Never enter against the cloud color (don't LONG in RED cloud)
Reduce position size during BLUE/ORANGE (transition periods)
Place stops beyond Medium MA for swing trades
Use Slow MA (200) as final trend filter - don't SHORT above it in uptrends
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PERFORMANCE & OPTIMIZATION
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Tested On:
Crypto: BTC, ETH, major altcoins
Stocks: SPY, AAPL, TSLA, QQQ
Forex: EUR/USD, GBP/USD, USD/JPY
Indices: S&P 500, NASDAQ, DJI
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TRANSPARENCY & RELIABILITY
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Educational Focus:
Detailed tooltips on every input
Clear documentation of methodology
Practical examples in descriptions
Teaches you why , not just what
Open Logic:
Momentum calculation: (Fast slope + Medium slope) / 2
Smoothing: 8-bar EMA to reduce noise
Thresholds: ±0.02% for strong momentum classification
Everything is transparent and explainable
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COMPLETE FEATURE LIST
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Visual Components:
26-layer exponential gradient cloud
3 customizable moving average lines
Golden Cross / Death Cross labels
Real-time info panel with trend strength
MA distance table
Calculation Features:
6 MA types (EMA, SMA, WMA, VWMA, RMA, HMA)
Momentum-based cloud coloring
Smoothed trend strength scoring
Conditional performance optimization
Customization Options:
All MA lengths adjustable
All colors customizable (when gradient disabled)
Panel position (4 corners)
Font sizes (5 options)
Toggle any feature on/off
Signal Features:
Anti-spam filter (configurable gap)
Clean, non-overlapping labels
Built-in alert conditions
No repainting guarantee
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IMPORTANT DISCLAIMERS
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This indicator is for educational and informational purposes only
Not financial advice - always do your own research
Past performance does not guarantee future results
Use proper risk management - never risk more than you can afford to lose
Test on paper/demo accounts before using with real money
Combine with other analysis methods - no single indicator is perfect
Works best in trending markets; less effective in choppy/sideways conditions
Signals may perform differently in different timeframes and market conditions
The indicator uses historical data for MA calculations - allow sufficient lookback period
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CREDITS & TECHNICAL INFO
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Version: 2.0
Release: October 2025
Special Thanks:
TradingView community for feedback and testing
Pine Script documentation for technical reference
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SUPPORT & UPDATES
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Found a bug? Comment below with:
Ticker symbol
Timeframe
Screenshot if possible
Steps to reproduce
Feature requests? I'm always looking to improve! Share your ideas in the comments.
Questions? Check the tooltips first (hover over any input) - most answers are there. If still stuck, ask in comments.
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Happy Trading!
Remember: The best indicator is the one you understand and use consistently. Take time to learn how the cloud behaves in different market conditions. Practice on paper before going live. Trade smart, manage risk, and may the trends be with you! 🚀
ZynAlgo Trend Dashboard MiniZynAlgo Trend Dashboard™ is a professional-grade tool designed to simplify multi-timeframe trend analysis and bring visual clarity to any trading setup.
It instantly shows who’s in control — buyers or sellers — across all key timeframes, allowing traders to make faster and more confident decisions based on overall market direction.
Developed using advanced Pine Script architecture, this indicator provides a clean and efficient interface that can be used on its own or combined with other ZynAlgo tools for enhanced market confluence.
⚙️ CORE CONCEPT
Trends are rarely aligned across timeframes — that’s why most traders get caught trading against higher-timeframe momentum.
ZynAlgo Trend Dashboard™ solves this by displaying a synchronized overview of the market’s directional bias, from short-term to long-term, within a single compact panel.
Each timeframe is evaluated using one of three models that can be toggled according to user preference:
MA Cross Model: Detects when short-term momentum shifts in relation to the dominant trend.
Price vs Baseline Model: Highlights when price behavior transitions above or below a defined average baseline.
Momentum Model: Measures relative strength within adjustable thresholds to identify overextended or recovering market conditions.
Every timeframe is color-coded — 🟢 Bullish, 🔴 Bearish, 🟡 Neutral — providing an immediate read of trend alignment and potential turning points.
🧩 FEATURES
Multi-timeframe trend confluence panel (supports up to 9 custom timeframes)
Adjustable calculation models (MA, Price, or Momentum)
“Overall Trend” summary bar for quick bias identification
Clean interface optimized for all chart backgrounds
Custom color themes and dashboard placement controls
Detailed / Compact / Minimal display modes
Alert system for full or partial trend alignment
Lightweight and resource-efficient performance
🧠 HOW TO USE
Select your preferred signal mode (MA, Price, or Momentum).
Enable the timeframes you want to monitor.
Observe dashboard colors for alignment:
• When most timeframes turn 🟢 → uptrend confirmation.
• When most turn 🔴 → downtrend alignment.
Combine the Overall Trend with your entry strategy or confirmation tools.
Set alerts to receive notifications whenever confluence conditions are met.
📊 INTERPRETATION
Full Alignment: High probability of sustained directional momentum.
Mixed Signals: Possible consolidation or transition; exercise patience.
Sudden Shift: Early sign of momentum reversal or structural change.
This indicator is not intended to generate buy or sell orders.
It’s designed to clarify directional context, helping traders avoid low-probability setups and focus on trades aligned with dominant market flow.
⚙️ CUSTOMIZATION
Configure dashboard size, transparency, and layout
Select preferred average type (EMA, SMA, HMA, etc.)
Adjust baseline lengths and sensitivity
Switch between dark/light UI themes
Enable or disable Overall Trend aggregation
⚠️ DISCLAIMER
Trading involves substantial risk and is not suitable for every investor.
All information and tools provided by ZynAlgo are intended for educational and analytical purposes only. Past performance does not guarantee future results.
🔶 CONCLUSION
We believe that success lies in the association of the user with the indicator, opposed to many traders who have the perspective that the indicator itself can make them become profitable. The reality is much more complicated than that. The aim is to provide an indicator comprehensive, customizable, and intuitive enough that any trader can be led to understand this truth and develop an actionable perspective of technical indicators as support tools for decision making. You can see the Author's instructions below to get instant access to this indicator
🔶 RISK DISCLAIMER
Trading is risky & most day traders lose money. All content, tools, scripts, articles, & education provided by ZynAlgo are purely for informational & educational purposes only. Past performance does not guarantee future results.
VWAL Cloud + 200 Trend (v6) — Desh Videsh TradingDescription:
Visualize market trends easily with the VWAL Cloud + 200 Trend Indicator! This indicator is designed for traders who want a clear, intuitive view of trend direction using volume-weighted average lines (VWAL).
Features:
VWAL Cloud :
Shows the short-to-medium term trend zone.
Turns green when the cloud is above the 200-period VWAL (bullish).
Turns red when the cloud is below the 200-period VWAL (bearish).
Gray when the trend is neutral or mixed.
VWAL 200 Line:
Represents the long-term trend filter.
Helps identify overall market direction.
Trend Label:
Displays “TREND: BULL / BEAR / NEUTRAL” on the latest bar for quick visual reference.
How to Use:
Bullish Trend: Cloud above VWAL-200 → look for long setups.
Bearish Trend: Cloud below VWAL-200 → look for short setups.
Neutral Trend: Cloud overlapping VWAL-200 → avoid taking directional trades.
Customizable Inputs:
Cloud periods: can be changed as per your strategy
VWAL 200 period: adjust to suit longer-term trend detection
Cloud & line colors for personal preferences
Trendline Breakouts With Targets [ omerprıme ]Indicator Explanation (English)
This indicator is designed to detect trendline breakouts and provide early trading signals when the price breaks key support or resistance levels.
Trendline Detection
The indicator identifies recent swing highs and lows to construct dynamic trendlines.
These trendlines act as support in an uptrend and resistance in a downtrend.
Breakout Confirmation
When the price closes above a resistance trendline, the indicator generates a bullish breakout signal.
When the price closes below a support trendline, it generates a bearish breakout signal.
Filtering False Signals
To reduce false breakouts, additional conditions (such as candle confirmation, volume filters, or price momentum) can be applied.
Only significant and confirmed breakouts are highlighted.
Trading Logic
Buy signals are triggered when the price breaks upward through resistance with confirmation.
Sell signals are triggered when the price breaks downward through support with confirmation.
Trendlines Breakouts Pro V1.2 - 4TP [Wukong Algo]Trendlines Breakouts Pro
Trading method “High Tight Trendline Breakout”. This is a simple but effective and flexible method that can support many other methods such as: support and resistance, supply and demand, volume profile...
Automatically connect TradingView and MetaTrader 5 (MT5) for automatic trading and order management via PineConnector
The system includes a risk management grid including the levels: Stop Loss (SL), Break-even (BE), Trail Trigger, Trailing Stop, TP1 (1/4), TP2 (2/4), TP3 (3/4), TP4 (4/4). This grid helps you easily monitor and manage orders on TradingView in parallel with automatic order management on MT5.
Focus on tight capital and risk management, reduce emotion and stress when trading
Suitable for all markets: Forex, Gold, Crypto, Stocks, as long as you use MT5 and TradingView
If you do not need to trade automatically via MT5, the Trendlines Breakokuts Pro can also be used as an effective indicator in visual order management on TradingView charts, helps maintain discipline and good trading psychology (less Stress or FOMO)
Trendlines Breakouts Pro System User Guide
Step 1 - Draw trendline AB. Just click to select 2 points A, B on the chart
This is a straight line at the border of a chart pattern or support/resistance zone on the chart that you determine has high potential when it is broken, the price will have strong momentum and you will enter the order (Entry). The trendline AB can be a diagonal line or a horizontal line.
Step 2 - Entry Window: Set the time allowed for transactions
You can choose the earliest and latest time allowed for trading signals, called Entry Window. This means that the system will not allow trading outside the Entry Window. This option allows you to manage trading times as you wish, avoiding bad times for trading such as sideways, choppy, high volatility, news
Step 3 - Set up the input parameters for trading
You choose the direction you want to wait for trading: Wait Long (Buy), Wait Short (Sell), Turn Off, Hidden
You enter the ID of your PineConnector account if you want to trade automatically from TradingView to MT5
You enter the order parameters: Lotsize per order, Stop Loss (SL%), BE(%), Trail Trigger (%), TP1(%), TP2(%), TP3(%), TP4(%)
You enter the safe filter parameters for Entry: max distance from entry to swing high/low, max distance from entry to trendline's breakpoint C, max entries per trendlines
See more details in the screenshots
Step 4 - Set up automatic trading from TradingView via MT5
If you do not need automatic trading in MT5, skip this step. Entry signals and risk management grids will still be displayed on the TradingView chart for you to see, but there is no connection and automatic trading signal shooting and automatic order management from TradingView to MT5 via PineConnector.
We need to create an Alert in TradingView and attach it to this Indicator so that the Alert's trading signals are transmitted via MetaTrader 5 (MT5) via PineConnector.
When trading, you need to turn on 3 software at the same time to be able to connect to each other to operate: TradingView, MetaTrader 5 (MT5), PineConnector
See more details in the screenshots
Step 5 - Complete setup, and wait for trading signals
You have completed the setup steps for the Indicator, ready when there is a trading signal
You do not need to sit in front of the screen all day if you do not want. The system has been set up to execute and manage orders automatically.
Of course, sometimes you should still check your transaction status, in case of unexpected problems such as lost internet connection.
If you still have questions about this Indicator, please email tuanwukongvn@gmail.com for support.
Trend & Volatility ZoneUnlock the power of trend and volatility with the Dynamic Trend Zone, a complete trading suite for TradingView. Designed to help traders of all levels identify the direction and strength of market trends, this tool provides clean, actionable signals to remove guesswork and enhance your trading decisions.
Our system is built on a sophisticated logic that combines a smooth trend-following moving average with volatility bands based on the Average True Range (ATR). This creates an intuitive visual guide to the market's current state.
How It Works
The indicator is composed of two key elements:
The Trend Core: A central, responsive moving average acts as the baseline for determining the primary trend direction.
The Volatility Zone: Dynamic bands that expand and contract based on market volatility (ATR). These bands define the boundaries of the trend. When the price closes outside these bands, it signals a potential new trend is beginning.
The background color changes to provide an at-a-glance understanding of the market:
Blue Zone: Indicates a confirmed uptrend.
Red Zone: Indicates a confirmed downtrend.
Key Features
Visual Trend Zones: The colored background makes it effortless to see if the market is bullish or bearish, helping you stay on the right side of the trend.
Precise Entry Signals: Never miss a potential trend shift.
A green upward arrow appears when the trend officially flips from bearish to bullish, suggesting a buy opportunity.
A red downward arrow appears when the trend switches from bullish to bearish, highlighting a potential sell signal.
Fully Integrated Backtesting Strategy: This script isn't just an indicator; it's a complete, ready-to-use strategy. You can instantly backtest its performance on any asset and timeframe to validate its effectiveness.
Customizable Risk Management: The strategy includes optional Stop Loss and Take Profit parameters (in percent), allowing you to test different risk management approaches.
Highly Customizable Settings: Tailor the indicator to your preferred trading style by adjusting the sensitivity of the trend line and the width of the volatility zones.
Built-in Date Filter: Focus your backtesting on specific market conditions with a simple-to-use date filter, allowing you to analyze performance from any given start date.
How to Use
For a Long Position (Buy): Wait for the background to turn blue and a green arrow to appear below a candle. This signals that bullish momentum is taking control.
For a Short Position (Sell): Wait for the background to turn red and a red arrow to appear above a candle. This indicates that bearish momentum is building.
Confirmation: For best results, use these signals in conjunction with your own analysis, such as identifying key support/resistance levels or confirming with higher timeframe trends.
Customizable Settings
Trend Line Length: Controls the responsiveness of the central trend line. A lower value is faster; a higher value is smoother.
ATR Period: Sets the lookback period for calculating volatility.
ATR Multiplier: Adjusts the width of the trend zones. A higher value requires a stronger price move to signal a trend change.
Stop Loss % / Take Profit %: Define your risk-reward parameters for the backtesting strategy.
Disclaimer: The Dynamic Trend Zone is a tool designed for market analysis and backtesting. It is not financial advice. All forms of trading involve substantial risk, and past performance is not indicative of future results. Please use this tool responsibly as part of a well-rounded trading plan and risk management strategy.
Tzotchev Trend Measure [EdgeTools]Are you still measuring trend strength with moving averages? Here is a better variant at scientific level:
Tzotchev Trend Measure: A Statistical Approach to Trend Following
The Tzotchev Trend Measure represents a sophisticated advancement in quantitative trend analysis, moving beyond traditional moving average-based indicators toward a statistically rigorous framework for measuring trend strength. This indicator implements the methodology developed by Tzotchev et al. (2015) in their seminal J.P. Morgan research paper "Designing robust trend-following system: Behind the scenes of trend-following," which introduced a probabilistic approach to trend measurement that has since become a cornerstone of institutional trading strategies.
Mathematical Foundation and Statistical Theory
The core innovation of the Tzotchev Trend Measure lies in its transformation of price momentum into a probability-based metric through the application of statistical hypothesis testing principles. The indicator employs the fundamental formula ST = 2 × Φ(√T × r̄T / σ̂T) - 1, where ST represents the trend strength score bounded between -1 and +1, Φ(x) denotes the normal cumulative distribution function, T represents the lookback period in trading days, r̄T is the average logarithmic return over the specified period, and σ̂T represents the estimated daily return volatility.
This formulation transforms what is essentially a t-statistic into a probabilistic trend measure, testing the null hypothesis that the mean return equals zero against the alternative hypothesis of non-zero mean return. The use of logarithmic returns rather than simple returns provides several statistical advantages, including symmetry properties where log(P₁/P₀) = -log(P₀/P₁), additivity characteristics that allow for proper compounding analysis, and improved validity of normal distribution assumptions that underpin the statistical framework.
The implementation utilizes the Abramowitz and Stegun (1964) approximation for the normal cumulative distribution function, achieving accuracy within ±1.5 × 10⁻⁷ for all input values. This approximation employs Horner's method for polynomial evaluation to ensure numerical stability, particularly important when processing large datasets or extreme market conditions.
Comparative Analysis with Traditional Trend Measurement Methods
The Tzotchev Trend Measure demonstrates significant theoretical and empirical advantages over conventional trend analysis techniques. Traditional moving average-based systems, including simple moving averages (SMA), exponential moving averages (EMA), and their derivatives such as MACD, suffer from several fundamental limitations that the Tzotchev methodology addresses systematically.
Moving average systems exhibit inherent lag bias, as documented by Kaufman (2013) in "Trading Systems and Methods," where he demonstrates that moving averages inevitably lag price movements by approximately half their period length. This lag creates delayed signal generation that reduces profitability in trending markets and increases false signal frequency during consolidation periods. In contrast, the Tzotchev measure eliminates lag bias by directly analyzing the statistical properties of return distributions rather than smoothing price levels.
The volatility normalization inherent in the Tzotchev formula addresses a critical weakness in traditional momentum indicators. As shown by Bollinger (2001) in "Bollinger on Bollinger Bands," momentum oscillators like RSI and Stochastic fail to account for changing volatility regimes, leading to inconsistent signal interpretation across different market conditions. The Tzotchev measure's incorporation of return volatility in the denominator ensures that trend strength assessments remain consistent regardless of the underlying volatility environment.
Empirical studies by Hurst, Ooi, and Pedersen (2013) in "Demystifying Managed Futures" demonstrate that traditional trend-following indicators suffer from significant drawdowns during whipsaw markets, with Sharpe ratios frequently below 0.5 during challenging periods. The authors attribute these poor performance characteristics to the binary nature of most trend signals and their inability to quantify signal confidence. The Tzotchev measure addresses this limitation by providing continuous probability-based outputs that allow for more sophisticated risk management and position sizing strategies.
The statistical foundation of the Tzotchev approach provides superior robustness compared to technical indicators that lack theoretical grounding. Fama and French (1988) in "Permanent and Temporary Components of Stock Prices" established that price movements contain both permanent and temporary components, with traditional moving averages unable to distinguish between these elements effectively. The Tzotchev methodology's hypothesis testing framework specifically tests for the presence of permanent trend components while filtering out temporary noise, providing a more theoretically sound approach to trend identification.
Research by Moskowitz, Ooi, and Pedersen (2012) in "Time Series Momentum in the Cross Section of Asset Returns" found that traditional momentum indicators exhibit significant variation in effectiveness across asset classes and time periods. Their study of multiple asset classes over decades revealed that simple price-based momentum measures often fail to capture persistent trends in fixed income and commodity markets. The Tzotchev measure's normalization by volatility and its probabilistic interpretation provide consistent performance across diverse asset classes, as demonstrated in the original J.P. Morgan research.
Comparative performance studies conducted by AQR Capital Management (Asness, Moskowitz, and Pedersen, 2013) in "Value and Momentum Everywhere" show that volatility-adjusted momentum measures significantly outperform traditional price momentum across international equity, bond, commodity, and currency markets. The study documents Sharpe ratio improvements of 0.2 to 0.4 when incorporating volatility normalization, consistent with the theoretical advantages of the Tzotchev approach.
The regime detection capabilities of the Tzotchev measure provide additional advantages over binary trend classification systems. Research by Ang and Bekaert (2002) in "Regime Switches in Interest Rates" demonstrates that financial markets exhibit distinct regime characteristics that traditional indicators fail to capture adequately. The Tzotchev measure's five-tier classification system (Strong Bull, Weak Bull, Neutral, Weak Bear, Strong Bear) provides more nuanced market state identification than simple trend/no-trend binary systems.
Statistical testing by Jegadeesh and Titman (2001) in "Profitability of Momentum Strategies" revealed that traditional momentum indicators suffer from significant parameter instability, with optimal lookback periods varying substantially across market conditions and asset classes. The Tzotchev measure's statistical framework provides more stable parameter selection through its grounding in hypothesis testing theory, reducing the need for frequent parameter optimization that can lead to overfitting.
Advanced Noise Filtering and Market Regime Detection
A significant enhancement over the original Tzotchev methodology is the incorporation of a multi-factor noise filtering system designed to reduce false signals during sideways market conditions. The filtering mechanism employs four distinct approaches: adaptive thresholding based on current market regime strength, volatility-based filtering utilizing ATR percentile analysis, trend strength confirmation through momentum alignment, and a comprehensive multi-factor approach that combines all methodologies.
The adaptive filtering system analyzes market microstructure through price change relative to average true range, calculates volatility percentiles over rolling windows, and assesses trend alignment across multiple timeframes using exponential moving averages of varying periods. This approach addresses one of the primary limitations identified in traditional trend-following systems, namely their tendency to generate excessive false signals during periods of low volatility or sideways price action.
The regime detection component classifies market conditions into five distinct categories: Strong Bull (ST > 0.3), Weak Bull (0.1 < ST ≤ 0.3), Neutral (-0.1 ≤ ST ≤ 0.1), Weak Bear (-0.3 ≤ ST < -0.1), and Strong Bear (ST < -0.3). This classification system provides traders with clear, quantitative definitions of market regimes that can inform position sizing, risk management, and strategy selection decisions.
Professional Implementation and Trading Applications
The indicator incorporates three distinct trading profiles designed to accommodate different investment approaches and risk tolerances. The Conservative profile employs longer lookback periods (63 days), higher signal thresholds (0.2), and reduced filter sensitivity (0.5) to minimize false signals and focus on major trend changes. The Balanced profile utilizes standard academic parameters with moderate settings across all dimensions. The Aggressive profile implements shorter lookback periods (14 days), lower signal thresholds (-0.1), and increased filter sensitivity (1.5) to capture shorter-term trend movements.
Signal generation occurs through threshold crossover analysis, where long signals are generated when the trend measure crosses above the specified threshold and short signals when it crosses below. The implementation includes sophisticated signal confirmation mechanisms that consider trend alignment across multiple timeframes and momentum strength percentiles to reduce the likelihood of false breakouts.
The alert system provides real-time notifications for trend threshold crossovers, strong regime changes, and signal generation events, with configurable frequency controls to prevent notification spam. Alert messages are standardized to ensure consistency across different market conditions and timeframes.
Performance Optimization and Computational Efficiency
The implementation incorporates several performance optimization features designed to handle large datasets efficiently. The maximum bars back parameter allows users to control historical calculation depth, with default settings optimized for most trading applications while providing flexibility for extended historical analysis. The system includes automatic performance monitoring that generates warnings when computational limits are approached.
Error handling mechanisms protect against division by zero conditions, infinite values, and other numerical instabilities that can occur during extreme market conditions. The finite value checking system ensures data integrity throughout the calculation process, with fallback mechanisms that maintain indicator functionality even when encountering corrupted or missing price data.
Timeframe validation provides warnings when the indicator is applied to unsuitable timeframes, as the Tzotchev methodology was specifically designed for daily and higher timeframe analysis. This validation helps prevent misapplication of the indicator in contexts where its statistical assumptions may not hold.
Visual Design and User Interface
The indicator features eight professional color schemes designed for different trading environments and user preferences. The EdgeTools theme provides an institutional blue and steel color palette suitable for professional trading environments. The Gold theme offers warm colors optimized for commodities trading. The Behavioral theme incorporates psychology-based color contrasts that align with behavioral finance principles. The Quant theme provides neutral colors suitable for analytical applications.
Additional specialized themes include Ocean, Fire, Matrix, and Arctic variations, each optimized for specific visual preferences and trading contexts. All color schemes include automatic dark and light mode optimization to ensure optimal readability across different chart backgrounds and trading platforms.
The information table provides real-time display of key metrics including current trend measure value, market regime classification, signal strength, Z-score, average returns, volatility measures, filter threshold levels, and filter effectiveness percentages. This comprehensive dashboard allows traders to monitor all relevant indicator components simultaneously.
Theoretical Implications and Research Context
The Tzotchev Trend Measure addresses several theoretical limitations inherent in traditional technical analysis approaches. Unlike moving average-based systems that rely on price level comparisons, this methodology grounds trend analysis in statistical hypothesis testing, providing a more robust theoretical foundation for trading decisions.
The probabilistic interpretation of trend strength offers significant advantages over binary trend classification systems. Rather than simply indicating whether a trend exists, the measure quantifies the statistical confidence level associated with the trend assessment, allowing for more nuanced risk management and position sizing decisions.
The incorporation of volatility normalization addresses the well-documented problem of volatility clustering in financial time series, ensuring that trend strength assessments remain consistent across different market volatility regimes. This normalization is particularly important for portfolio management applications where consistent risk metrics across different assets and time periods are essential.
Practical Applications and Trading Strategy Integration
The Tzotchev Trend Measure can be effectively integrated into various trading strategies and portfolio management frameworks. For trend-following strategies, the indicator provides clear entry and exit signals with quantified confidence levels. For mean reversion strategies, extreme readings can signal potential turning points. For portfolio allocation, the regime classification system can inform dynamic asset allocation decisions.
The indicator's statistical foundation makes it particularly suitable for quantitative trading strategies where systematic, rules-based approaches are preferred over discretionary decision-making. The standardized output range facilitates easy integration with position sizing algorithms and risk management systems.
Risk management applications benefit from the indicator's ability to quantify trend strength and provide early warning signals of potential trend changes. The multi-timeframe analysis capability allows for the construction of robust risk management frameworks that consider both short-term tactical and long-term strategic market conditions.
Implementation Guide and Parameter Configuration
The practical application of the Tzotchev Trend Measure requires careful parameter configuration to optimize performance for specific trading objectives and market conditions. This section provides comprehensive guidance for parameter selection and indicator customization.
Core Calculation Parameters
The Lookback Period parameter controls the statistical window used for trend calculation and represents the most critical setting for the indicator. Default values range from 14 to 63 trading days, with shorter periods (14-21 days) providing more sensitive trend detection suitable for short-term trading strategies, while longer periods (42-63 days) offer more stable trend identification appropriate for position trading and long-term investment strategies. The parameter directly influences the statistical significance of trend measurements, with longer periods requiring stronger underlying trends to generate significant signals but providing greater reliability in trend identification.
The Price Source parameter determines which price series is used for return calculations. The default close price provides standard trend analysis, while alternative selections such as high-low midpoint ((high + low) / 2) can reduce noise in volatile markets, and volume-weighted average price (VWAP) offers superior trend identification in institutional trading environments where volume concentration matters significantly.
The Signal Threshold parameter establishes the minimum trend strength required for signal generation, with values ranging from -0.5 to 0.5. Conservative threshold settings (0.2 to 0.3) reduce false signals but may miss early trend opportunities, while aggressive settings (-0.1 to 0.1) provide earlier signal generation at the cost of increased false positive rates. The optimal threshold depends on the trader's risk tolerance and the volatility characteristics of the traded instrument.
Trading Profile Configuration
The Trading Profile system provides pre-configured parameter sets optimized for different trading approaches. The Conservative profile employs a 63-day lookback period with a 0.2 signal threshold and 0.5 noise sensitivity, designed for long-term position traders seeking high-probability trend signals with minimal false positives. The Balanced profile uses a 21-day lookback with 0.05 signal threshold and 1.0 noise sensitivity, suitable for swing traders requiring moderate signal frequency with acceptable noise levels. The Aggressive profile implements a 14-day lookback with -0.1 signal threshold and 1.5 noise sensitivity, optimized for day traders and scalpers requiring frequent signal generation despite higher noise levels.
Advanced Noise Filtering System
The noise filtering mechanism addresses the challenge of false signals during sideways market conditions through four distinct methodologies. The Adaptive filter adjusts thresholds based on current trend strength, increasing sensitivity during strong trending periods while raising thresholds during consolidation phases. The Volatility-based filter utilizes Average True Range (ATR) percentile analysis to suppress signals during abnormally volatile conditions that typically generate false trend indications.
The Trend Strength filter requires alignment between multiple momentum indicators before confirming signals, reducing the probability of false breakouts from consolidation patterns. The Multi-factor approach combines all filtering methodologies using weighted scoring to provide the most robust noise reduction while maintaining signal responsiveness during genuine trend initiations.
The Noise Sensitivity parameter controls the aggressiveness of the filtering system, with lower values (0.5-1.0) providing conservative filtering suitable for volatile instruments, while higher values (1.5-2.0) allow more signals through but may increase false positive rates during choppy market conditions.
Visual Customization and Display Options
The Color Scheme parameter offers eight professional visualization options designed for different analytical preferences and market conditions. The EdgeTools scheme provides high contrast visualization optimized for trend strength differentiation, while the Gold scheme offers warm tones suitable for commodity analysis. The Behavioral scheme uses psychological color associations to enhance decision-making speed, and the Quant scheme provides neutral colors appropriate for quantitative analysis environments.
The Ocean, Fire, Matrix, and Arctic schemes offer additional aesthetic options while maintaining analytical functionality. Each scheme includes optimized colors for both light and dark chart backgrounds, ensuring visibility across different trading platform configurations.
The Show Glow Effects parameter enhances plot visibility through multiple layered lines with progressive transparency, particularly useful when analyzing multiple timeframes simultaneously or when working with dense price data that might obscure trend signals.
Performance Optimization Settings
The Maximum Bars Back parameter controls the historical data depth available for calculations, with values ranging from 5,000 to 50,000 bars. Higher values enable analysis of longer-term trend patterns but may impact indicator loading speed on slower systems or when applied to multiple instruments simultaneously. The optimal setting depends on the intended analysis timeframe and available computational resources.
The Calculate on Every Tick parameter determines whether the indicator updates with every price change or only at bar close. Real-time calculation provides immediate signal updates suitable for scalping and day trading strategies, while bar-close calculation reduces computational overhead and eliminates signal flickering during bar formation, preferred for swing trading and position management applications.
Alert System Configuration
The Alert Frequency parameter controls notification generation, with options for all signals, bar close only, or once per bar. High-frequency trading strategies benefit from all signals mode, while position traders typically prefer bar close alerts to avoid premature position entries based on intrabar fluctuations.
The alert system generates four distinct notification types: Long Signal alerts when the trend measure crosses above the positive signal threshold, Short Signal alerts for negative threshold crossings, Bull Regime alerts when entering strong bullish conditions, and Bear Regime alerts for strong bearish regime identification.
Table Display and Information Management
The information table provides real-time statistical metrics including current trend value, regime classification, signal status, and filter effectiveness measurements. The table position can be customized for optimal screen real estate utilization, and individual metrics can be toggled based on analytical requirements.
The Language parameter supports both English and German display options for international users, while maintaining consistent calculation methodology regardless of display language selection.
Risk Management Integration
Effective risk management integration requires coordination between the trend measure signals and position sizing algorithms. Strong trend readings (above 0.5 or below -0.5) support larger position sizes due to higher probability of trend continuation, while neutral readings (between -0.2 and 0.2) suggest reduced position sizes or range-trading strategies.
The regime classification system provides additional risk management context, with Strong Bull and Strong Bear regimes supporting trend-following strategies, while Neutral regimes indicate potential for mean reversion approaches. The filter effectiveness metric helps traders assess current market conditions and adjust strategy parameters accordingly.
Timeframe Considerations and Multi-Timeframe Analysis
The indicator's effectiveness varies across different timeframes, with higher timeframes (daily, weekly) providing more reliable trend identification but slower signal generation, while lower timeframes (hourly, 15-minute) offer faster signals with increased noise levels. Multi-timeframe analysis combining trend alignment across multiple periods significantly improves signal quality and reduces false positive rates.
For optimal results, traders should consider trend alignment between the primary trading timeframe and at least one higher timeframe before entering positions. Divergences between timeframes often signal potential trend reversals or consolidation periods requiring strategy adjustment.
Conclusion
The Tzotchev Trend Measure represents a significant advancement in technical analysis methodology, combining rigorous statistical foundations with practical trading applications. Its implementation of the J.P. Morgan research methodology provides institutional-quality trend analysis capabilities previously available only to sophisticated quantitative trading firms.
The comprehensive parameter configuration options enable customization for diverse trading styles and market conditions, while the advanced noise filtering and regime detection capabilities provide superior signal quality compared to traditional trend-following indicators. Proper parameter selection and understanding of the indicator's statistical foundation are essential for achieving optimal trading results and effective risk management.
References
Abramowitz, M. and Stegun, I.A. (1964). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Washington: National Bureau of Standards.
Ang, A. and Bekaert, G. (2002). Regime Switches in Interest Rates. Journal of Business and Economic Statistics, 20(2), 163-182.
Asness, C.S., Moskowitz, T.J., and Pedersen, L.H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929-985.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Fama, E.F. and French, K.R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Hurst, B., Ooi, Y.H., and Pedersen, L.H. (2013). Demystifying Managed Futures. Journal of Investment Management, 11(3), 42-58.
Jegadeesh, N. and Titman, S. (2001). Profitability of Momentum Strategies: An Evaluation of Alternative Explanations. Journal of Finance, 56(2), 699-720.
Kaufman, P.J. (2013). Trading Systems and Methods. 5th Edition. Hoboken: John Wiley & Sons.
Moskowitz, T.J., Ooi, Y.H., and Pedersen, L.H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228-250.
Tzotchev, D., Lo, A.W., and Hasanhodzic, J. (2015). Designing robust trend-following system: Behind the scenes of trend-following. J.P. Morgan Quantitative Research, Asset Management Division.
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution.
🔶 Advanced Noise Reduction
Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions.
advancedNoiseFilter(sourceData, filterLength, sigmaParam) =>
weightSum = 0.0
valueSum = 0.0
centerPoint = (filterLength - 1) / 2
for index = 0 to filterLength - 1
gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2))
weightSum += gaussianWeight
valueSum += sourceData * gaussianWeight
valueSum / weightSum
🔶 Adaptive Moving Average Core Engine
Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases.
// Calculate adaptive parameters
adaptiveLength = (periodLength - 1) / 2
logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0)
powerFactor = math.max(logFactor - 2, 0.5)
relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0
adaptivePower = math.pow(relativeVol, powerFactor)
bandwidthFactor = math.sqrt(adaptiveLength) * logFactor
🔶 Intelligent Market Structure Analysis
Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity.
🔶 Multi-Component Momentum Analysis
Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts.
// Z-score momentum analysis
rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod)
rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod)
rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation
if math.abs(rsiZScore) > zSignificanceLevel
rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal
❓How It Works
🔶 Dynamic Channel Configuration
Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy.
dynamicChannelEngine(baselineData, channelLength, methodType) =>
switch methodType
"ATR" => ta.atr(channelLength)
"Standard Deviation" => ta.stdev(baselineData, channelLength)
"Gaussian Deviation" =>
weightArray = array.new_float()
totalWeight = 0.0
for i = 0 to channelLength - 1
gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2))
weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i)
math.sqrt(weightedVariance / totalWeight)
🔶 Signal Processing Pipeline
Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation.
🔶 Confidence Transformation System
Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions.
🔶 Enhanced Visual Presentation
Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes.
🔶 Real-Time Information Dashboard
Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment.
🔶 Intelligent Alert System
Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration.
🔶 Performance Optimization
Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions.
This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
Draw Trend LinesSometimes the simplest indicators help traders make better decisions. This indicator draws simple trend lines, the same lines you would draw manually.
To trade with an edge, traders need to interpret the recent price action, whether it's noisy or choppy, or it's trending. Trend Lines will help traders with that interpretation.
The lines drawn are:
1. lower tops
2. higher bottoms
Because trends are defined as higher lows, or lower highs.
When you see "Wedges", formed by prices chopping between top and bottom trend lines, that's noisy environment not to be traded. When you learn to "stop yourself", you already have an edge.
Often when you see a trend, it's still not too late. Trend will continue until it doesn't. But the caveat is a very steep trend is unlikely to continue, because buying volume is extremely unbalanced to cause the steep trend, and that volume will run out of energy. (Same on the sell side of course)
Trends can reverse, and when price action breaks the trend line, Breakout/Breakdown traders can take this as an entry signal.
Enjoy, and good trading!
TrendPilot AI v2 — Adaptive Trend Day Trading StrategyOverview
TrendPilot AI v2 is a structured, rules-based day trading strategy that identifies and follows market momentum using a sophisticated blend of technical indicators. Optimized for 15-minute and higher timeframes on high market cap cryptocurrencies (AAVE, SOL, ETH, BCH, BTC) to minimize manipulation risks, it adapts to changing market conditions with dynamic risk management and controlled re-entry logic to maximize trend participation while minimizing noise.
Core Logic
Multiple EMA Trend Confirmation — Uses three Exponential Moving Averages (fast, medium, slow) to detect robust bullish, bearish, or neutral trends, ensuring trades align with the prevailing market direction.
ADX Momentum Filter — Employs an ADX-based filter to confirm strong trends, avoiding entries in choppy or low-momentum markets.
Smart Entry Filter — Optional ATR-based buffer (period 14, multiplier 1.5) around the fast EMA prevents entries at overextended prices, enhancing trade precision.
Flexible Exit System — Offers multiple exit options: fixed take-profit (default 1.7 offset), trend-reversal exits, or ATR-based trailing stops (period 14, multiplier 2.0), with secure modes requiring candle closes for confirmation to gain Max Profit.
Controlled Re-Entry Logic — Allows re-entries after take-profit or price-based stop-loss with configurable wait periods (default 6 bars), max attempts (default 2), and EMA touch requirements (fast, medium, or slow).
State-Aware Risk Management — Tracks trend states and recent exits to adapt entries, with daily trade limits (default 5 long/short) and loss cooldowns (default 2 stop-losses) for disciplined trading.
How to Use & Configuration
Markets & Timeframes
Works with high market cap cryptocurrencies (AAVE, SOL, ETH, BCH, BTC).
Optimized for intraday charts (15m–4h) but adaptable to higher timeframes (e.g., 1h, 4h).
Trade Direction Settings
Dual Trades — Trades both long and short, quickly re-aligning after trend reversals.
Long Only — Ignores bearish signals, ideal for bullish markets or strong uptrends.
Short Only — Ignores bullish signals, suited for bearish markets or downtrends.
Risk Management Settings
Stop Loss Types
Trend Reversal — Closes positions when an opposite trend signal is confirmed (default).
Fixed Offset — Static stop at 3.5 offset from entry price (adjustable).
ATR Based — Dynamic trailing stop using ATR (period 14, multiplier 2.0), adjusting to market volatility.
Secure SL Mode — Optional setting to trigger price-based stops only on candle closes, reducing false exits.
Maximum recommended risk per trade is 5–10% of account equity.
Trade size is configurable (default 20 units) to match individual risk appetite.
Take Profit Options
Fixed Offset — Predefined target at 1.7 offset from entry (adjustable, e.g., 2.5 for SOL).
Secure TP Mode — Exits only when a candle closes beyond the target, ensuring reliable profit capture.
Trend Reversal — Exits on opposite trend signals when fixed TP is disabled, ideal for riding longer trends.
Trade Management Controls
Smart Entry Filter — Optional ATR-based buffer (period 14, multiplier 1.5) prevents chasing overextended prices.
Max Re-Entries — Limits continuation trades per trend cycle (default 2).
Daily Trade Limits — Caps long/short trades per day (default 5 each) for disciplined trading.
Daily Loss Cooldown — Pauses trading after a set number of stop-losses (default 2) per day.
Max Bars in Trade — Closes positions after a set duration (default 1440 bars) to prevent stale trades.
Configuration Steps
Apply the strategy to your chosen symbol (e.g., AAVE/USDT, SOL/USDT) and timeframe (15m or higher).
Select Trade Direction mode (Dual, Long Only, or Short Only).
Set Stop Loss (Trend Reversal, Fixed Offset, or ATR Based) and Take Profit (fixed or trend-reversal).
Adjust Smart Entry Filter, Max Re-Entries, Daily Limits, and Loss Cooldown as needed.
Test across multiple market conditions using the performance panel (top-right, showing Total Trades, Wins, Losses, Win Rate).
Enables automated trading via webhook integration with platforms like Binance Futures.
Set up alerts for long/short entries (🟢 Long, 🔴 Short) and exits (🎯 Max TP, 🛑 Max SL, 🚨 Force Exit).
Backtesting Guidance
Use realistic commission (default 0.01%) and slippage (default 2 ticks) matching your broker and instrument.
Validate performance over long historical periods (e.g., 3–6 months) to ensure >100 trades across different market regimes.
Avoid curve-fitting by testing on multiple high market cap coins (AAVE, SOL, ETH, BCH, BTC) and avoiding over-optimization.
EMA and ATR parameters are set to balanced, industry-standard values for realistic backtesting.
Best Practices, Defaults & Disclaimer
Best Practices
Use consistent and conservative position sizing (default 20 units).
Match commission and slippage to your broker’s actual rates.
Enable secure TP/SL modes for entries and exits to reduce false signals.
Test across different symbols, timeframes, and market phases before live trading.
Keep parameters simple to avoid overfitting.
Default Settings (Recommended Starting Point)
Initial Capital: $10,000
Order Size: Fixed, 20 units
Commission: 0.01%
Slippage: 2 ticks
Take Profit Offset: 1.7 (adjustable, e.g., 2.5 for SOL)
Stop Loss Type: Trend Reversal (default), Fixed Offset (3.5), or ATR Based (period 14, multiplier 2.0)
Smart Entry Filter: ATR period 14, multiplier 1.5 (optional)
Max Re-Entries: 2 per trend cycle
Daily Trade Limits: 5 long, 5 short
Daily Loss Cooldown: 2 stop-losses
Max Bars in Trade: 1440 bars
Subscription Information
TrendPilot AI v2 is an invite-only strategy, accessible only to approved subscribers.
Benefits include full access to all features, priority support, and regular updates.
Access is limited to ensure a high-quality user experience.
Compliance Status
No functional warnings in the script.
The script uses closed candle logic, ensuring no repainting or lookahead issues.
Designed for realistic backtesting with a $10,000 account and sustainable risk (≤5–10% per trade).
Disclaimer
This strategy is intended for educational and analytical purposes only. Trading involves substantial risk, and past performance does not guarantee future results. You are solely responsible for your own trading decisions and risk management.
Developed by: TrendPilotAI Team
For questions, setup guidance, or enhancement suggestions, contact TrendPilotAI Team via TradingView.
Trend Strength Oscillator📌 Trend Strength Oscillator
📄 Description
Trend Strength Oscillator measures the directional strength of price relative to an adaptive dynamic trend band. It evaluates how far the current price is from the midpoint of a trend channel and normalizes this value by recent volatility range, allowing traders to detect trend strength, direction, and potential exhaustion in any market condition.
📌 Features
🔹 Adaptive Trend Band Logic: Uses a modified ATR and time-dependent spread formula to dynamically adjust upper and lower trend bands.
🔹 Trendline Midpoint Calculation: The central trendline is defined as the average between upper and lower bands.
🔹 Relative Positioning: Measures how far the close is from the center of the band as a percentage.
🔹 Range Normalization: Uses a normalized range to account for recent volatility, reducing noise in the oscillator reading.
🔹 Oscillator Output (±100 scale):
+100 indicates strong bullish momentum
-100 indicates strong bearish momentum
0 is the neutral centerline
🛠️ How to Use
✅ Trend Strength > +50: Indicates a strong bullish phase.
✅ Trend Strength < -50: Indicates a strong bearish phase.
⚠️ Crossing above 0: Potential bullish trend initiation.
⚠️ Crossing below 0: Potential bearish trend initiation.
📉 Values near 0: Suggest trend weakness or ranging conditions.
Best suited timeframes: 1H, 4H, Daily
Ideal combination with: RSI, MACD, volume-based oscillators, moving average crosses
✅ TradingView House Rules Compliance
This indicator is written in Pine Script v5 and fully open-source.
The script does not repaint, does not generate false alerts, and does not access external or private data.
It is intended strictly as a technical analysis tool, and not a buy/sell signal generator.
Users are encouraged to combine this tool with other confirmations and independent judgment in trading decisions.
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📌 Trend Strength Oscillator
📄 설명 (Description)
Trend Strength Oscillator는 가격이 동적 추세 밴드 내 어디에 위치해 있는지를 정량적으로 분석하여, 추세의 방향성과 강도를 시각적으로 보여주는 오실레이터 지표입니다. 최근 변동성을 반영한 밴드를 기반으로 가격 위치를 정규화하여, 과매수·과매도 상태나 추세의 소멸 가능성까지 탐지할 수 있도록 설계되었습니다.
📌 주요 특징 (Features)
🔹 적응형 추세 밴드 계산: ATR과 시간 경과를 기반으로 상단/하단 밴드를 동적으로 조정
🔹 중심 추세선 산출: 상단과 하단 밴드의 평균값을 중심선으로 활용하여 기준 축 제공
🔹 상대 위치 계산: 현재 종가가 중심선에서 얼마나 떨어져 있는지를 정규화하여 추세 강도 계산
🔹 변동성 기반 정규화: 최근 밴드 범위를 기준으로 상대 거리를 0~100 사이 값으로 변환
🔹 오실레이터 출력 (범위: ±100):
+100에 가까울수록 강한 상승 추세
-100에 가까울수록 강한 하락 추세
0에 가까울수록 횡보 구간 가능성
🛠️ 사용법 (How to Use)
✅ +50 이상: 강한 상승 추세 지속 중
✅ -50 이하: 강한 하락 추세 지속 중
⚠️ 0선 돌파 상향: 상승 추세 시작 가능성
⚠️ 0선 돌파 하향: 하락 추세 시작 가능성
🟡 0 근처 유지: 추세 약화 또는 횡보장 가능성
추천 시간대: 1시간봉, 4시간봉, 일봉
보조 지표로 추천: RSI, MACD, OBV, 이동평균 크로스 등과 함께 활용 시 효과적
✅ 트레이딩뷰 하우스룰 준수사항 (TradingView House Rules Compliance)
본 지표는 Pine Script v5로 작성된 오픈소스 공개용 스크립트입니다.
리페인트(Repaint) 현상이 없으며, **허위 경고(Spam Alerts)**나 성능 저하 요소도 없습니다.
외부 데이터 접근 없이 완전히 자체 계산으로 동작합니다.
이 지표는 투자 판단을 돕기 위한 분석용 도구이며, 직접적인 매수·매도 신호로 사용해서는 안 됩니다.
모든 트레이딩은 사용자의 독립적인 판단과 책임 하에 이루어져야 합니다.
Trend Band Oscillator📌 Trend Band Oscillator
📄 Description
Trend Band Oscillator is a momentum-based trend indicator that calculates the spread between two EMAs and overlays it with a volatility filter using a standard deviation band. It helps traders visualize not only the trend direction but also the strength and stability of the trend.
📌 Features
🔹 EMA Spread Calculation: Measures the difference between a fast and slow EMA to quantify short-term vs mid-term trend dynamics.
🔹 Volatility Band Overlay: Applies an EMA of standard deviation to the spread to filter noise and highlight valid momentum shifts.
🔹 Color-Based Visualization: Positive spread values are shown in lime (bullish), negative values in fuchsia (bearish) for quick directional insight.
🔹 Upper/Lower Bands: Help detect potential overbought/oversold conditions or strong trend continuation.
🔹 Zero Line Reference: A horizontal baseline at zero helps identify trend reversals and neutral zones.
🛠️ How to Use
✅ Spread > 0: Indicates a bullish trend. Consider maintaining or entering long positions.
✅ Spread < 0: Indicates a bearish trend. Consider maintaining or entering short positions.
⚠️ Spread exceeds bands: May signal overextension or strong momentum; consider using with additional confirmation indicators.
🔄 Band convergence: Suggests weakening trend and potential transition to a ranging market.
Recommended timeframes: 1H, 4H, Daily
Suggested complementary indicators: RSI, MACD, OBV, SuperTrend
✅ TradingView House Rules Compliance
This script is open-source and published under Pine Script v5.
It does not repaint, spam alerts, or cause performance issues.
It is designed as an analytical aid only and should not be considered financial advice.
All calculations are transparent, and no external data sources or insecure functions are used.
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📌 Trend Band Oscillator
📄 설명 (Description)
Trend Band Oscillator는 두 개의 EMA 간 스프레드(차이)를 기반으로 한 모멘텀 중심의 추세 오실레이터입니다. 여기에 표준편차 기반의 변동성 밴드를 적용하여, 추세의 방향뿐 아니라 강도와 안정성까지 시각적으로 분석할 수 있도록 설계되었습니다.
📌 주요 특징 (Features)
🔹 EMA 기반 스프레드 계산: Fast EMA와 Slow EMA의 차이를 활용해 시장 추세를 정량적으로 표현합니다.
🔹 표준편차 필터링: Spread에 대해 EMA 및 표준편차 기반의 밴드를 적용해 노이즈를 줄이고 유효한 추세를 강조합니다.
🔹 컬러 기반 시각화: 오실레이터 값이 양수일 경우 초록색, 음수일 경우 마젠타 색으로 추세 방향을 직관적으로 파악할 수 있습니다.
🔹 밴드 범위 시각화: 상·하위 밴드를 통해 스프레드의 평균 편차 범위를 보여주며, 추세의 강약과 포화 여부를 진단할 수 있습니다.
🔹 제로 라인 표시: 추세 전환 가능 지점을 시각적으로 확인할 수 있도록 중심선(0선)을 제공합니다.
🛠️ 사용법 (How to Use)
✅ 오실레이터가 0 이상 유지: 상승 추세 구간이며, 롱 포지션 유지 또는 진입 검토
✅ 오실레이터가 0 이하 유지: 하락 추세 구간이며, 숏 포지션 유지 또는 진입 검토
⚠️ 상·하위 밴드를 이탈: 일시적인 과매수/과매도 혹은 강한 추세 발현 가능성 있음 → 다른 보조지표와 함께 필터링 권장
🔄 밴드 수렴: 추세가 약해지고 있음을 나타냄 → 변동성 하락 또는 방향성 상실 가능성 있음
권장 적용 시간대: 1시간봉, 4시간봉, 일봉
보조 적용 지표: RSI, MACD, OBV, SuperTrend 등과 함께 사용 시 신호 필터링에 유리
✅ 트레이딩뷰 하우스룰 준수사항 (TV House Rules Compliance)
이 지표는 **무료 공개용(Open-Source)**이며, Pine Script Version 5로 작성되어 있습니다.
과도한 리페인트, 비정상적 반복 경고(alert spam), 실시간 성능 저하 등의 요소는 포함되어 있지 않습니다.
사용자는 본 지표를 투자 결정의 참고용 보조 도구로 활용해야 하며, 독립적인 매매 판단이 필요합니다.
데이터 소스 및 계산 방식은 완전히 공개되어 있으며, 외부 API나 보안 취약점을 유발하는 구성 요소는 없습니다.
Two Poles Trend Finder MTF [BigBeluga]🔵 OVERVIEW
Two Poles Trend Finder MTF is a refined trend-following overlay that blends a two-pole Gaussian filter with a multi-timeframe dashboard. It provides a smooth view of price dynamics along with a clear summary of trend directions across multiple timeframes—perfect for traders seeking alignment between short and long-term momentum.
🔵 CONCEPTS
Two-Pole Filter: A smoothing algorithm that responds faster than traditional moving averages but avoids the noise of short-term fluctuations.
var float f = na
var float f_prev1 = na
var float f_prev2 = na
// Apply two-pole Gaussian filter
if bar_index >= 2
f := math.pow(alpha, 2) * source + 2 * (1 - alpha) * f_prev1 - math.pow(1 - alpha, 2) * f_prev2
else
f := source // Warm-up for first bars
// Shift state
f_prev2 := f_prev1
f_prev1 := f
Trend Detection Logic: Trend direction is determined by comparing the current filtered value with its value n bars ago (shifted comparison).
MTF Alignment Dashboard: Trends from 5 configurable timeframes are monitored and visualized as colored boxes:
• Green = Uptrend
• Magenta = Downtrend
Summary Arrow: An average trend score from all timeframes is used to plot an overall arrow next to the asset name.
🔵 FEATURES
Two-Pole Gaussian Filter offers ultra-smooth trend curves while maintaining responsiveness.
Multi-Timeframe Trend Detection:
• Default: 1H, 2H, 4H, 12H, 1D (fully customizable)
• Each timeframe is assessed independently using the same trend logic.
Visual Trend Dashboard positioned at the bottom-right of the chart with color-coded trend blocks.
Dynamic Summary Arrow shows overall market bias (🢁 / 🢃) based on majority of uptrends/downtrends.
Bold + wide trail plot for the filter value with gradient coloring based on directional bias.
🔵 HOW TO USE
Use the multi-timeframe dashboard to identify aligned trends across your preferred trading horizons.
Confirm trend strength or weakness by observing filter slope direction .
Look for dashboard consensus (e.g., 4 or more timeframes green] ) as confirmation for breakout, continuation, or trend reentry strategies.
Combine with volume or price structure to enhance entry timing.
🔵 CONCLUSION
Two Poles Trend Finder MTF delivers a clean and intuitive trend-following solution with built-in multi-timeframe awareness. Whether you’re trading intra-day or positioning for swing setups, this tool helps filter out market noise and keeps you focused on directional consensus.
EMA Trend Dashboard
Trend Indicator using 3 custom EMA lines. Displays a table with 5 rows(position configurable)
-First line shows relative position of EMA lines to each other and outputs Bull, Weak Bull, Flat, Weak Bear, or Bear. EMA line1 should be less than EMA line2 and EMA line 2 should be less than EMA line3. Default is 9,21,50.
-Second through fourth line shows the slant of each EMA line. Up, Down, or Flat. Threshold for what is considered a slant is configurable. Also added a "steep" threshold configuration for steep slants.
-Fifth line shows exhaustion and is a simple, configurable calculation of the distance between EMA line1 and EMA line2.
--Lines one and five change depending on its value but ALL other colors are able to be changed.
--Default is somewhat set to work well with Micro E-mini Futures but this indicator can be changed to work on anything. I created it to help get a quick overview of short-term trend on futures. I used ChatGPT to help but I am still not sure if it actually took longer because of it.
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Trend Finder Using Pull Back Method {Darkoexe}This indicator predicts trends using pull backs structure to predict the trend direction. It builds off the flag pattern concept but it uses precise precise measurements to determine trend direction.
A pull back occurs every time the price direction switches then closes either below or above the open of the previous candle depending on the type of pull back, bullish or bearish.
For an up trend to be a defined, when a bullish pull back occurs and does not go below the previous low, if the price then passes above the start of the pull back, an up trend signal will be printed. Only bullish pull backs will be displayed during an up trend.
For a down trend to be defined, when a bearish pull back occurs and does not go above the previous high, if the price then passes below the start of the pull back, a down trend signal will be printed. Only bearish pull backs will be displayed during a down trend.
If the conditions for an up trend or down trend are not met, no trend will be printed. Both bearish and bullish pull backs will be displayed during a no trend.
All the labels colors can be changed.
//Darkoexe
Trend Table ZeeZeeMonMulti-Timeframe Trend Indicator
Overview
This indicator identifies trends across multiple higher timeframes and displays them in a widget on the right side of the chart. It serves as an alternative trend-filtering tool, helping traders align with the dominant market direction. Unlike traditional moving average-based trend detection (e.g., price above/below a 200 MA), this indicator assesses whether higher timeframes are genuinely trending by analyzing swing highs and lows.
Trend Definition
Uptrend: Higher highs and higher lows.
Downtrend: Lower highs and lower lows.
A trend reversal occurs when a prior high/low is breached (e.g., in a downtrend, breaking the last high signals an uptrend).
Customization Options
Lookback Period: Adjusts the sensitivity for identifying swing highs/lows (pivot points). A shorter lookback detects more frequent pivots.
Historical Pivot Visibility: Toggle to display past swing highs/lows for verification.
Support/Resistance Lines: Show dynamic levels from recent pivots on higher timeframes. Breaching these lines indicates potential trend changes.
Purpose
Helps traders:
Confirm higher timeframe trends before entering trades.
Monitor proximity to trend reversals.
Fine-tune pivot sensitivity for optimal trend detection.
Note: Works best as a supplementary trend filter alongside other trading strategies.
