Hull TrendHere we are using Hull Moving Average crossovers as an experiment in trend detection.
The Hull Moving Average (HMA) is an extremely fast and smooth moving average.
Credit to alexgrover & RicardoSantos:
Поиск скриптов по запросу "moving average crossover"
Edge-Preserving FilterIntroduction
Edge-preserving smoothing is often used in image processing in order to preserve edge information while filtering the remaining signal. I introduce two concepts in this indicator, edge preservation and an adaptive cumulative average allowing for fast edge-signal transition with period increase over time. This filter have nothing to do with classic filters for image processing, those filters use kernels convolution and are most of the time in a spatial domain.
Edge Detection Method
We want to minimize smoothing when an edge is detected, so our first goal is to detect an edge. An edge will be considered as being a peak or a valley, if you recall there is one of my indicator who aim to detect peaks and valley (reference at the bottom of the post) , since this estimation return binary outputs we will use it to tell our filter when to stop filtering.
Filtering Increase By Using Multi Steps Cumulative Average
The edge detection is a binary output, using a exponential smoothing could be possible and certainly more efficient but i wanted instead to try using a cumulative average approach because it smooth more and is a bit more original to use an adaptive architecture using something else than exponential averaging. A cumulative average is defined as the sum of the price and the previous value of the cumulative average and then this result is divided by n with n = number of data points. You could say that a cumulative average is a moving average with a linear increasing period.
So lets call CMA our cumulative average and n our divisor. When an edge is detected CMA = close price and n = 1 , else n is equal to previous n+1 and the CMA act as a normal cumulative average by summing its previous values with the price and dividing the sum by n until a new edge is detected, so there is a "no filtering state" and a "filtering state" with linear period increase transition, this is why its multi-steps.
The Filter
The filter have two parameters, a length parameter and a smooth parameter, length refer to the edge detection sensitivity, small values will detect short terms edges while higher values will detect more long terms edges. Smooth is directly related to the edge detection method, high values of smooth can avoid the detection of some edges.
smooth = 200
smooth = 50
smooth = 3
Conclusion
Preserving the price edges can be useful when it come to allow for reactivity during important price points, such filter can help with moving average crossover methods or can be used as a source for other indicators making those directly dependent of the edge detection.
Rsi with a period of 200 and our filter as source, will cross triggers line when an edge is detected
Feel free to share suggestions ! Thanks for reading !
References
Peak/Valley estimator used for the detection of edges in price.
Short-Term Trend MasterThis is a short-term trend-following trading strategy.
Buy when there is a moving average crossover and green background signal.
Sell when there is a moving average crossover and red background signal.
Try different timeframes to find the best one.
Cheers!
Everyday 0002 _ MAC 1st Trading Hour WalkoverThis is the second strategy for my Everyday project.
Like I wrote the last time - my goal is to create a new strategy everyday
for the rest of 2016 and post it here on TradingView.
I'm a complete beginner so this is my way of learning about coding strategies.
I'll give myself between 15 minutes and 2 hours to complete each creation.
This is basically a repetition of the first strategy I wrote - a Moving Average Crossover,
but I added a tiny thing.
I read that "Statistics have proven that the daily high or low is established within the first hour of trading on more than 70% of the time."
(source: )
My first Moving Average Crossover strategy, tested on VOLVB daily, got stoped out by the volatility
and because of this missed one nice bull run and a very nice bear run.
So I added this single line: if time("60", "1000-1600") regarding when to take exits:
if time("60", "1000-1600")
strategy.exit("Close Long", "Long", profit=2000, loss=500)
strategy.exit("Close Short", "Short", profit=2000, loss=500)
Sweden is UTC+2 so I guess UTC 1000 equals 12.00 in Stockholm. Not sure if this is correct, actually.
Anyway, I hope this means the strategy will only take exits based on price action which occur in the afternoon, when there is a higher probability of a lower volatility.
When I ran the new modified strategy on the same VOLVB daily it didn't get stoped out so easily.
On the other hand I'll have to test this on various stocks .
Reading and learning about how to properly test strategies is on my todo list - all tips on youtube videos or blogs
to read on this topic is very welcome!
Like I said the last time, I'm posting these strategies hoping to learn from the community - so any feedback, advice, or corrections is very much welcome and appreciated!
/pbergden
MultiTradingSystemThis is example to show how you can combine two and more strategies for get
a cumulative signal. Result signal will return 1 if two (or more) strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
Chaikin's Volatility indicator compares the spread between a security's
high and low prices. It quantifies volatility as a widening of the range
between the high and the low price.
You can use in the xPrice1 and xPrice2 any series: Open, High, Low, Close, HL2,
HLC3, OHLC4 and ect...
Secon strategy
The Moving Average Crossover trading strategy is possibly the most popular
trading strategy in the world of trading. First of them were written in the
middle of XX century, when commodities trading strategies became popular.
This strategy is a good example of so-called traditional strategies.
Traditional strategies are always long or short. That means they are never
out of the market. The concept of having a strategy that is always long or
short may be scary, particularly in today’s market where you don’t know what
is going to happen as far as risk on any one market. But a lot of traders
believe that the concept is still valid, especially for those of traders who
do their own research or their own discretionary trading.
This version uses crossover of moving average and its exponential moving average.
MTF Dashboard Table - Sachin ThakareOne Dashboard, Complete Market View!
By - Sachin Thakare (India, Mumbai)
MTF HUD Indicator - All-in-One Market Dashboard
📊 Basic Information
Indicator Name: MTF HUD Table - Bias Column
Created By: Sachin Thakare
Version: Pine Script v5
Type: Multi-Timeframe Heads-Up Display (HUD)
Category: Strategy/Utility Tool
🎯 What This Indicator Does
This is a comprehensive Multi-Timeframe Market Dashboard that displays key technical indicators across 8 different timeframes (3min to Monthly) in a single, easy-to-read table format. It helps traders quickly assess market bias and make informed decisions.
✨ Key Features
📈 Multi-Timeframe Analysis
8 Timeframes: 3m, 5m, 15m, 1H, 4H, Daily, Weekly, Monthly
Real-time Updates: All timeframes update simultaneously
Color-coded Signals: Instant visual feedback
🔢 Technical Indicators Included
Price Change & % Change - Immediate price movement
VWAP - Volume Weighted Average Price
EMA 9/21 - Exponential Moving Average crossover
200 MA - Long-term trend indicator
SuperTrend 10/3 - Trend-following indicator
RSI 9 - Momentum oscillator
MACD 8/21/5 - Moving Average Convergence Divergence
ADX 7/7 - Average Directional Index
Alligator - Bill Williams' trend indicator
Stochastic 5/3/3 - Overbought/Oversold levels
ATR 10 - Average True Range (volatility)
PH/PL - Previous Day High/Low position
🎨 Visual Design
Color Psychology:
🟢 Green: Strong Bullish
🟩 Light Green: Bullish
🔴 Red: Strong Bearish
🟥 Light Red: Bearish
⚪ Gray: Neutral
Customizable Position: Top/Bottom, Left/Right, Center
Clean Table Format: Professional HUD-style display
⚙️ Smart Features
Bias Column: Automatic market bias calculation
Score-based System: 11 indicators contribute to bias score
Customizable Thresholds: Adjust bull/bear levels
Multi-timeframe Security: Accurate timeframe calculations
🚀 How to Use
For Beginners:
Install the indicator on any chart
Look at the BIAS column for overall market direction
Check consistency across timeframes
Stronger signals when multiple timeframes agree
For Advanced Traders:
Identify confluence - When multiple indicators align
Timeframe alignment - Look for agreements across timeframes
Divergence spotting - When timeframes show conflicting signals
Entry/Exit points - Use with price action confirmation
Trading Strategies:
Trend Following: Follow the dominant bias across higher timeframes
Mean Reversion: Look for extreme readings in oscillator columns
Breakout Trading: Use PH/PL and ATR columns
Swing Trading: Focus on 4H and Daily timeframes
⚙️ Customization Settings
Position Settings:
Choose from 5 display positions
Adjust to your preferred chart layout
Indicator Parameters:
Adjust all indicator lengths and periods
Modify OB/OS levels for RSI and Stochastic
Change MA types (SMA/EMA) for 200 MA
Bias Thresholds:
Strong Bull Threshold: 8 (default)
Bull Threshold: 3 (default)
Bear Threshold: -3 (default)
Strong Bear Threshold: -8 (default)
💡 Pro Tips
Start with Higher Timeframes - Daily and Weekly first
Look for Alignment - Best trades when 3+ timeframes agree
Watch the BIAS Column - Quick market sentiment check
Combine with Price Action - Use support/resistance with signals
Risk Management - Never trade on indicator alone
⚠️ Important Notes
Not a Standalone System: Use with other analysis methods
Lagging Indicators: Most components are trend-following
Market Conditions: Works best in trending markets
Customize for Your Style: Adjust parameters for your trading style
🔄 Updates & Support
The indicator is regularly updated based on user feedback and market changes. For suggestions or issues, please leave a comment on the TradingView script page.
Perfect For: Day Traders, Swing Traders, Position Traders, Market Analysts, and anyone needing quick multi-timeframe analysis.
Best Results: When combined with fundamental analysis, risk management, and proper trading psychology.
Prowl's EMA 10/20/50 trend followingThis indicator is designed to simplify trend trading by visually filtering market noise. It removes the need to constantly analyze multiple moving average crossovers by converting complex trend alignment into a simple "Traffic Light" background system.
How it Works This script utilizes a triple-EMA (Exponential Moving Average) system to gauge market conditions on two levels:
Momentum: It analyzes the relationship between the Fast and Medium EMAs to determine immediate short-term momentum.
Trend Filter: It compares the current price action against a Slow (Baseline) EMA to ensure the major trend is respected.
Visual Guide
Green Background: This indicates a "High Probability Buy Zone." It only triggers when both the short-term momentum is positive (Fast EMA ≥ Medium EMA) AND the price is maintaining its structure above the long-term baseline (Price ≥ Trend EMA).
Red Background: Indicates neutral or bearish conditions where the trend alignment is broken.
The Lines:
Red Line: Fast EMA (Short-term reaction)
Orange Line: Medium EMA (Intermediate trend)
Green Line: Trend EMA (Long-term baseline)
Features
Visual Simplicity: The background color allows you to instantly see if the trend is in your favor without cluttering your mental space.
Fully Customizable: All EMA lengths are adjustable in the settings to fit your specific timeframe (Scalping vs. Swing Trading).
Gradient Colors: The lines are color-coded (Red to Green) to visually represent the time horizon.
Adjustable Opacity: Users can control the intensity of the background color to keep their charts clean.
Usage Strategy This tool is best used as a "Trend Filter." Traders can look for their specific entry setups (candlestick patterns, breakouts, etc.) only when the background is Green, and stand aside or look for shorts when the background is Red.
CS Institutional X-Ray (Perfect Sync)Title: CS Institutional X-Ray
Description:
CS Institutional X-Ray is an advanced Order Flow and Market Structure suite designed to reveal what happens inside Japanese candles.
Most traders only see open and close prices. This indicator utilizes VSA (Volume Spread Analysis) algorithms and Synthetic Footprint Logic to detect institutional intervention, liquidity manipulation, and market exhaustion.
🧠 1. The Mathematical Engine: Synthetic Footprint
The core of this indicator is not based on moving average crossovers, but on market physics: Effort vs. Result.
The script scans every candle and calculates:
Buy/Sell Pressure: Analyzes the close position relative to the total candle range and weights it by volume.
Synthetic Delta: Calculates the net difference between buyer and seller aggression.
Volume Anomalies: Detects when volume is abnormally high (Institutional) or low (Retail).
The Absorption Logic: The indicator hunts for divergences between candle color and internal flow.
Example: If price drops hard (Red Candle) with massive volume, but the close moves away from the low, the algorithm detects that massive LIMIT orders absorbed the selling pressure. Result: Institutional Buy Signal.
📊 2. The Institutional Semaphore (Visual Guide)
The indicator automatically recolors candles to show the real state of the auction:
🔵 CYAN (Whale Buy): Bullish Absorption. Institutions buying aggressively or absorbing selling pressure at support.
🟣 MAGENTA (Whale Sell): Bearish Absorption. Institutions selling into strength or stopping a rally with sell walls.
⚪ GREY (Exhaustion/Zombie): "No-Trade" Zone. Volume is extremely low. The movement lacks institutional backing and is prone to failure.
🟢/🔴 Normal: Market in equilibrium.
🛡️ 3. Smart Zone System (Market Memory)
The indicator draws and manages Support and Resistance levels based on volume events, not just pivots.
Virgin Zones (Bright): When a "Whale" appears, a solid line is projected. If price has not touched it again, it is a high-probability bounce zone.
Automatic Mitigation: The exact moment price touches a line, the indicator detects the mitigation. The line turns Grey and Dotted, and the label dims. This keeps the chart clean, showing only what is relevant now.
☠️ 4. Manipulation Detector (Liquidity Grabs)
The system distinguishes between a normal reversal and a "Stop Hunt".
Signal: ☠️ GRAB
Logic: If price breaks a previous Low/High to sweep liquidity and closes with an absorption candle (Whale), it is marked as a "Grab." This is the system's most powerful reversal signal.
🧱 5. FVG with Liquidity Score
The indicator draws Fair Value Gaps (Imbalances) and assigns them a volume score.
"Vol: 3.0x": Indicates that the gap was created with 3 times the average volume, making it a much stronger price magnet than a standard FVG.
🚀 How to Trade with CS Institutional X-Ray
Identify the Footprint: Wait for a Cyan or Magenta candle to appear.
Validate the Trap: If the signal comes with a "☠️ GRAB" label, the probability of success increases drastically.
The Retest (Entry): Do not chase price. Place a Limit order on the generated Zone Line or at the edge of the FVG.
Management: Use opposite zones or mitigated zones (grey) as Take Profit targets.
Included Settings:
Fully configurable Alerts for Whales, Grabs, and Retests.
Total customization of colors and styles.
One Minute AI scalper keep extended trading hours on# One Minute AI Scalper - Trading Indicator
## Overview
The One Minute AI Scalper is a precision-engineered trading indicator designed specifically for short-term scalping strategies on 1-minute timeframes. This indicator combines multiple technical analysis methods to identify high-probability entry points for both long and short positions, making it ideal for active traders seeking quick, momentum-based opportunities.
## Key Features
### Visual Signals
- **Long Entry Arrows**: Clear green triangle markers appear below price bars when bullish conditions align
- **Short Entry Arrows**: Clear red triangle markers appear above price bars when bearish conditions align
- Clean, uncluttered chart interface focusing on actionable signals
### Advanced Signal Generation
The indicator utilizes a sophisticated multi-factor approach to generate trading signals:
1. **Trend Analysis**: Employs moving average crossover methodology to identify the prevailing market direction
2. **Momentum Confirmation**: Analyzes candlestick patterns and price behavior to confirm momentum strength
3. **Volume Validation**: Incorporates volume analysis to distinguish between high-conviction and standard signals
4. **Reversal Detection**: Identifies potential trend reversals by examining recent price action patterns
5. **Precision Entry Filtering**: Uses specific candlestick characteristics to minimize false signals
### Alert System
Comprehensive alert functionality for all signal types:
- Long Entry alerts
- Short Entry alerts
## How It Works
### Long Position Signals
The indicator generates long entry signals when multiple bullish conditions simultaneously align, including:
- Confirmation of upward momentum through price action
- Specific candlestick structure indicating strong buying pressure
- Price position relative to key moving averages
- Recent price behavior suggesting reversal potential
- Volume characteristics supporting the move
### Short Position Signals
Short entry signals are generated when multiple bearish conditions converge, including:
- Confirmation of downward momentum through price action
- Specific candlestick structure indicating strong selling pressure
- Price position relative to key moving averages
- Recent price behavior suggesting reversal potential
- Volume characteristics supporting the move
### Position Management
The indicator includes intelligent position state tracking to:
- Prevent duplicate signals while in an active position
- Generate exit signals based on opposing price action
- Maintain clear status of whether you're in a long or short position
## Best Practices
### Recommended Usage
- **Timeframe**: Optimized for 1-minute charts
- **Extended Hours**: Keep extended trading hours enabled for full market coverage
- **Markets**: Works on stocks, forex, crypto, and futures
- **Strategy**: Best suited for scalping and day trading strategies
### Risk Management
- Always use proper stop-loss orders
- Consider position sizing based on account risk tolerance
- Pay attention to volume-indicated signals for higher conviction trades
- Avoid trading during low-liquidity periods
- Combine with your own risk management rules
### Trading Tips
- Higher volume signals generally indicate stronger conviction
- Wait for clear arrow signals rather than trying to anticipate them
- Monitor overall market conditions and major support/resistance levels
- Be aware of news events that may cause unusual volatility
- Practice in a paper trading account before using real capital
## Important Notes
### What This Indicator Does
✅ Provides clear visual entry signals for long and short positions
✅ Incorporates multiple technical factors for signal generation
✅ Includes volume analysis for conviction assessment
✅ Offers comprehensive alert options for all signal types
✅ Maintains position state awareness
### What This Indicator Doesn't Do
❌ Does not guarantee profitable trades
❌ Does not provide specific price targets or stop-loss levels
❌ Does not replace the need for proper risk management
❌ Does not account for fundamental analysis or news events
❌ Does not adapt settings automatically to market conditions
## Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results. Trading involves substantial risk of loss, and you should only trade with capital you can afford to lose. Always conduct your own research and consider consulting with a qualified financial advisor before making trading decisions.
## Configuration
This indicator uses fixed, optimized parameters that have been carefully calibrated for 1-minute scalping. No user configuration is required - simply add it to your chart and monitor for signals.
## Support
For questions, suggestions, or feedback about this indicator, please use the comments section or contact the author directly through TradingView.
---
**Version**: 6.0
**Category**: Momentum/Scalping
**Overlay**: Yes
**Timeframe**: 1 minute (optimized)
Quantum Range Filter by MRKcoin### Quantum Range Filter by MRKcoin
**Overview**
This indicator is a sophisticated range detection tool designed based on the principles of quantitative multi-factor models. Instead of relying on a single condition, it assesses the market from three different dimensions to provide a more robust and reliable identification of range-bound (sideways) markets.
When the background is highlighted in red, it indicates that the market is likely in a range phase, suggesting that trend-following strategies may be less effective, and mean-reversion (range trading) strategies could be more suitable.
---
**Core Logic: A Multi-Factor Approach**
The filter evaluates the market state using the following three independent factors:
1. **Momentum Volatility (RSI Bollinger Bandwidth):**
* **Question:** Is the momentum of the market contracting?
* **Method:** It measures the width of the Bollinger Bands applied to the RSI. A narrow bandwidth suggests that momentum is consolidating, which is a common characteristic of a range market.
2. **Price Volatility (ATR Ratio):**
* **Question:** Is the actual price movement shrinking?
* **Method:** It calculates the Average True Range (ATR) as a percentage of the closing price. A low ratio indicates that the price volatility itself is low, reinforcing the case for a range environment.
3. **Absence of Trend (ADX):**
* **Question:** Is there a lack of a clear directional trend?
* **Method:** It uses the Average Directional Index (ADX), a standard tool for measuring trend strength. A low ADX value provides active confirmation that the market is not in a trending phase.
---
**How to Use**
1. **Range Detection:** The primary use is to identify ranging markets. The red highlighted background serves as a visual cue.
2. **Strategy Selection:**
* **Inside the Red Zone:** Consider using range-trading strategies (e.g., buying at support, selling at resistance, using oscillators like RSI or Stochastics for overbought/oversold signals). Avoid using trend-following indicators like moving average crossovers, as they are prone to generating false signals in these conditions.
* **Outside the Red Zone:** The market is likely trending. Trend-following strategies are more appropriate.
3. **Parameter Tuning (In Settings):**
* **This is the key to adapting the filter to any market or timeframe.** Different assets (like BTC vs. ETH) and different timeframes have unique volatility characteristics. Don't hesitate to adjust the parameters to fit the specific chart you are analyzing.
* **Range Detection Score:** This is the most important setting. It determines how many of the three factors must agree to classify the market as a range. The default is `2`, which provides a good balance.
* If the filter seems **too sensitive** (highlighting too often), increase the score to `3`.
* If the filter seems **not sensitive enough** (missing obvious ranges), decrease the score to `1`.
* **Factor Thresholds:** For fine-tuning, adjust the thresholds for each factor.
* **`RSI BB Width Threshold`:** If you want to detect even tighter momentum consolidations, *decrease* this value.
* **`ATR Ratio Threshold`:** If you want to be stricter about price volatility, *decrease* this value.
* **`ADX Threshold`:** To be more lenient on what constitutes a "trendless" market, *increase* this value (e.g., to 30). To be stricter, *decrease* it (e.g., to 20).
* **Pro Tip:** Use the Debug Table (uncomment it in the script's code) to see the live values of each factor. This will give you a clear idea of how to set the thresholds for the specific asset you are trading.
**Disclaimer**
This indicator is a tool to assist in market analysis and should not be used as a standalone signal for making financial decisions. Always use it in conjunction with your own trading strategy, risk management, and analysis. Past performance is not indicative of future results.
**Credits**
* **Concept & Vision:** MRKcoin
52SIGNAL RECIPE Market Structure Reversal Signals═══ 52SIGNAL RECIPE Market Structure Reversal Signals ═══
◆ Overview
52SIGNAL RECIPE Market Structure Reversal Signals is a technical indicator designed to detect structural changes in price charts and identify potential trend reversals. By tracking highs and lows over a specified period, this indicator provides clear visual signals when significant price breakouts occur, helping traders capture directional changes in the market early.
─────────────────────────────────────
◆ Key Features
• Structural Reversal Detection: Provides potential trend change signals when price breaks through recent N-day highs/lows
• Duplicate Signal Prevention: Filters out consecutive signals in the same direction
• Intuitive Visualization: Clearly distinguishes bullish/bearish reversal signals by color and position on the chart
• Confirmed Bar Based: Generates signals only after bars are completely closed, enhancing reliability
• Customizable Settings: Adjustable tracking period to optimize for various market environments and timeframes
─────────────────────────────────────
◆ Technical Foundation
■ Market Structure Analysis Principle
• High/Low Tracking: Identifies previous highs (LH) and lows (HL) over the specified period
• Structural Breakout: Interprets as structural change when closing price breaks above previous high or below previous low
• Confirmed Bar Verification: Minimizes false signals by generating signals only after the current bar has completely closed
■ Signal Filtering Mechanism
• Signal State Tracking: Prevents duplicate signals by tracking the direction of the last generated signal
• Directional Change Focus: Suppresses signals in the same direction until an opposite signal occurs
• Noise Reduction: Focuses only on important level breakouts, eliminating unnecessary signals
─────────────────────────────────────
◆ Practical Applications
■ Trend Reversal Point Identification
• Bullish Trend Starting Point:
▶ When bullish reversal signal occurs after a downtrend
▶ When upward momentum is confirmed by breaking previous high
• Bearish Trend Starting Point:
▶ When bearish reversal signal occurs after an uptrend
▶ When downward momentum is confirmed by breaking below previous low
• Range Breakout Detection:
▶ Potential trend formation signals when breaking upper/lower boundaries in a ranging market
■ Trading Strategy Application
• Trend Following Strategy:
▶ Consider buy entry when bullish reversal signal occurs
▶ Consider sell entry when bearish reversal signal occurs
• Reversal Trading:
▶ Signals occurring at support/resistance levels provide high-probability entry points
▶ Reversal signals in overbought/oversold conditions strengthen trend reversal possibility
• Risk Management:
▶ Consider closing or reducing positions when opposite signals occur
▶ Set precise stop-loss points by combining with key technical levels
─────────────────────────────────────
◆ Advanced Setting Options
■ Tracking Period (N-day) Adjustment
• Short-term Setting: 10-15 days (sensitive signals, quick reaction, suitable for short-term trading)
• Medium-term Setting: 20-30 days (balanced signals, general trend detection, recommended default)
• Long-term Setting: 40-50 days (strong filtering, detects only major trend reversals, suitable for long-term investment)
■ Timeframe Optimization
• Daily Chart: 20-30 day setting (medium-term trend change detection)
• 4-Hour Chart: 30-40 setting (short-term swing trading signals)
• Hourly Chart: 40-50 setting (intraday trend change detection)
• Intraday Chart: 10-20 setting (scalping and short-term trading)
■ Market Type Adjustment
• High Volatility Markets: Higher N values (30-50) to filter noise
• Trending Markets: Medium N values (20-30) to capture only major reversals
• Ranging Markets: Lower N values (10-20) to capture range-bound movements
─────────────────────────────────────
◆ Synergy with Other Indicators
• Moving Averages: Signal strength enhanced when Market Structure Reversal Signals align with key moving average crossovers
• RSI: Market Structure Reversal Signals occurring at overbought/oversold levels increase reversal probability
• Volume Indicators: Market Structure Reversal Signals accompanied by high volume enhance reliability
• Fibonacci Levels: Market Structure Reversal Signals occurring at key Fibonacci levels provide important turning points
• Channel Indicators: Powerful breakout confirmation when price channel upper/lower breakthroughs coincide with Market Structure Reversal Signals
─────────────────────────────────────
◆ Conclusion
52SIGNAL RECIPE Market Structure Reversal Signals objectively identifies structural changes in the market and clearly visualizes potential trend reversal points. Its simple yet powerful approach of detecting directional changes through recent N-day high/low breakouts provides flexibility applicable to various market environments and trading styles. The duplicate signal prevention mechanism and confirmed bar-based signal generation greatly enhance signal quality and reliability. When combined with other technical indicators, synergy effects can be maximized, providing traders with a valuable tool to capture market turning points early.
─────────────────────────────────────
※ Disclaimer: Past performance does not guarantee future results. Always use appropriate risk management strategies.
═══ 52SIGNAL RECIPE Market Structure Reversal Signals ═══
◆ 개요
52SIGNAL RECIPE Market Structure Reversal Signals는 가격 차트의 구조적 변화를 감지하여 잠재적인 추세 반전을 식별하는 기술적 지표입니다. 이 지표는 최근 N일 동안의 고점과 저점을 추적하여 의미 있는 가격 돌파가 발생할 때 명확한 시각적 신호를 제공함으로써, 트레이더가 시장의 방향성 변화를 조기에 포착할 수 있도록 도와줍니다.
─────────────────────────────────────
◆ 주요 특징
• 구조적 반전 탐지: 가격이 최근 N일 고점/저점을 돌파할 때 잠재적 추세 변화 신호 제공
• 중복 신호 방지: 동일한 방향의 신호가 연속으로 반복되지 않도록 필터링
• 직관적인 시각화: 상승/하락 반전 신호를 차트 상에서 색상과 위치로 명확히 구분
• 확정 봉 기반: 봉이 완전히 종료된 후에만 신호 생성하여 신뢰도 향상
• 사용자 정의 설정: 추적 기간을 조정하여 다양한 시장 환경과 타임프레임에 최적화 가능
─────────────────────────────────────
◆ 기술적 기반
■ 시장 구조 분석 원리
• 고점/저점 추적: 지정된 기간 동안의 이전 고점(LH)과 저점(HL) 식별
• 구조적 돌파: 종가가 이전 고점을 상향 돌파하거나 이전 저점을 하향 돌파할 때 구조적 변화로 해석
• 확정 봉 검증: 현재 봉이 완전히 종료된 후에만 신호 생성하여 오신호 최소화
■ 신호 필터링 메커니즘
• 신호 상태 저장: 마지막 생성된 신호의 방향을 추적하여 동일 방향 신호 중복 방지
• 방향성 전환 초점: 반대 방향 신호가 발생할 때까지 동일 방향 신호 억제
• 노이즈 감소: 중요 수준 돌파에만 집중하여 불필요한 신호 제거
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◆ 실용적 응용
■ 추세 전환점 식별
• 상승 추세 시작점:
▶ 하락 추세 후 상승 반전 신호 발생 시
▶ 이전 고점 돌파로 상승 모멘텀 확인 시
• 하락 추세 시작점:
▶ 상승 추세 후 하락 반전 신호 발생 시
▶ 이전 저점 이탈로 하락 모멘텀 확인 시
• 범위 돌파 감지:
▶ 횡보 시장에서 상/하 경계 돌파 시 잠재적 추세 형성 신호
■ 트레이딩 전략 적용
• 추세 추종 전략:
▶ 상승 반전 신호 발생 시 매수 진입 고려
▶ 하락 반전 신호 발생 시 매도 진입 고려
• 반전 트레이딩:
▶ 지지/저항 수준에서 반전 신호 발생 시 높은 확률의 진입점 제공
▶ 과매수/과매도 상태에서의 반전 신호는 추세 전환 가능성 강화
• 리스크 관리:
▶ 반대 방향 신호 발생 시 포지션 종료 또는 축소 고려
▶ 주요 기술적 수준과 결합하여 정밀한 손절점 설정 가능
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◆ 고급 설정 옵션
■ 추적 기간(N일) 조정
• 단기 설정: 10-15일 (민감한 신호, 빠른 반응, 단기 트레이딩에 적합)
• 중기 설정: 20-30일 (균형 잡힌 신호, 일반적 추세 감지, 기본 권장)
• 장기 설정: 40-50일 (강한 필터링, 주요 추세 전환만 감지, 장기 투자에 적합)
■ 타임프레임별 최적화
• 일봉 차트: 20-30일 설정 (중기 추세 변화 감지)
• 4시간 차트: 30-40 설정 (단기 스윙 트레이딩 신호)
• 시간봉 차트: 40-50 설정 (일중 추세 변화 감지)
• 일중 차트: 10-20 설정 (스캘핑 및 단기 거래)
■ 시장 유형별 조정
• 변동성 높은 시장: 높은 N값 (30-50) 설정으로 노이즈 필터링
• 추세 시장: 중간 N값 (20-30) 설정으로 주요 반전만 포착
• 횡보 시장: 낮은 N값 (10-20) 설정으로 범위 내 움직임 포착
─────────────────────────────────────
◆ 다른 지표와의 시너지
• 이동평균선: Market Structure Reversal Signals 신호와 주요 이동평균선 교차 지점이 일치할 때 신호 강화
• RSI: 과매수/과매도 수준에서의 Market Structure Reversal Signals 신호는 반전 가능성 높임
• 볼륨 지표: 높은 볼륨과 함께 발생하는 Market Structure Reversal Signals 신호는 신뢰도 향상
• 피보나치 레벨: 주요 피보나치 레벨에서 발생하는 Market Structure Reversal Signals 신호는 중요한 전환점 제공
• 채널 지표: 가격 채널의 상단/하단 돌파와 Market Structure Reversal Signals 신호 일치 시 강력한 돌파 확인
─────────────────────────────────────
◆ 결론
52SIGNAL RECIPE Market Structure Reversal Signals는 시장의 구조적 변화를 객관적으로 식별하여 잠재적인 추세 전환점을 명확하게 시각화합니다. 최근 N일 고점/저점 돌파를 통해 방향성 변화를 감지하는 단순하면서도 강력한 접근 방식은 다양한 시장 환경과 트레이딩 스타일에 적용할 수 있는 유연성을 제공합니다. 중복 신호 방지 메커니즘과 확정 봉 기반 신호 생성은 신호의 품질과 신뢰성을 크게 향상시킵니다. 다른 기술적 지표와 결합하여 사용할 때 시너지 효과를 극대화할 수 있으며, 트레이더에게 시장의 전환점을 조기에 포착할 수 있는 귀중한 도구를 제공합니다.
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※ 면책 조항: 과거 성과가 미래 결과를 보장하지 않습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
Regime Scope | mad_tiger_slayerRegimeScope by mad_tiger_slayer
Adapt to the Market’s Mood. Trade in Sync with Regime Scope.
Overview
Regime Scope is an advanced multi-factor market regime identifier meticulously engineered to determine whether an asset is exhibiting trending behavior (Markup/Markdown phases) or mean-reverting dynamics (Sideways - Accumulation/Distribution). By integrating and synthesizing outputs from nine rigorously chosen statistical and volatility-based models, this tool offers a unified framework for assessing regime conditions with precision.
This indicator is best used in conjunction with other tools in your trading arsenal—serving not as a standalone signal generator, but as a high-value filter for confluence and strategic alignment. Whether you're trading breakouts, reversals, or mean-reversion setups, Regime Scope can elevate your system’s contextual awareness and execution timing.
How It Works – Part 1
Regime Scope calculates a composite "regime score" by normalizing and averaging a range of volatility and statistical measures. This score, which ranges between -1 and +1, indicates the likelihood of the market being in a trending versus mean-reverting state.
Values near +1 suggest a strong trending environment.
Values near -1 suggest strong mean-reversion (sideways, volatile) conditions.
Values between -0.30 and +0.30 are considered neutral and indicate choppy or range-bound market behavior.
When the average regime score crosses above the upper threshold, the asset likely enters a trending state.
When it crosses below the lower threshold, the market likely shifts to a volatile, mean-reverting state.
The histogram and dynamic background color provide an intuitive visual guide to the current regime.
How It Works – Part 2: Components
Each of the following sub-models has been carefully selected for its contribution to understanding price behavior. All components are normalized to create a consistent, unified score:
Phillips-Perron Test: Detects the presence of a unit root to infer stationarity and mean-reverting characteristics.
Hurst Exponent: Measures long-term memory in a time series to identify persistence or anti-persistence.
KPSS Test: Tests for level stationarity to contrast against unit-root behavior and validate trending assumptions.
GARCH Volatility: Captures volatility clustering and regime shifts in conditional variance.
Wavelet Transform: Decomposes price action into time-frequency space to extract non-linear and localized dynamics.
Half-Life of Mean Reversion: Estimates the speed at which price returns to its mean, enhancing the timing of reversion plays.
Augmented Dickey-Fuller (ADF) Test: Statistically verifies whether a series exhibits mean-reverting tendencies.
Garman-Klass-Yang-Zhang Volatility: A robust historical volatility measure using open-high-low-close data.
ADX (Average Directional Index): A classic technical tool for quantifying the strength of trend directionality.
How It Works – Part 3: Output Interpretation
All sub-models are normalized and synthesized into a single histogram plot shown in the lower chart panel.
+1.0 to +0.30: Indicates high probability of a directional, trending market.
-1.0 to -0.30: Indicates high probability of a sideways, mean-reverting regime.
-0.30 to +0.30: Suggests a neutral, uncertain market condition.
Transitions above or below these thresholds signal regime shifts.
Background shading adapts in real-time to visually reflect regime classification.
Features
Customizable thresholds to fine-tune sensitivity for regime classification.
Visual overlay positioning (choose from top-left, bottom-right, etc.).
Toggleable reference lines for regime thresholds.
Cross-timeframe consistency through dynamic normalization.
Each sub-model includes adjustable settings for personalized optimization.
Use Cases
Dynamically switch between trend-following and mean-reversion strategies.
Filter out choppy, low-probability zones by avoiding neutral regime periods.
Use regime score as confluence with entry/exit signals from other indicators.
Adapt strategies across timeframes—works well from scalping to swing trading.
Best used on timeframes ≥12H for macro regime context, but scalpers can benefit by using it on shorter windows with tuned parameters.
Scalping Use Case
Overlay the regime score on low timeframes (e.g., 1m–15m) and use it to avoid high chop zones or confirm breakout volume spikes during trending periods.
Long-Term Use Case
On 1D–1W charts, Regime Scope can filter false breakouts and confirm macro trend alignment for position trades or swing setups.
Tip
Combine Regime Scope with traditional technical tools like RSI, MACD, Bollinger Bands, or moving average crossovers to enhance strategic coherence.
For example, only act on breakout or trend-following signals when the regime score exceeds the upper threshold, confirming a high-trend environment.
Conversely, mean-reversion strategies like fading RSI extremes or trading Bollinger Band bounces work best when the regime score is in the lower range.
Aligning your tactical entries with the broader regime can significantly reduce false signals, enhance trade probability, and improve overall system robustness.
Multi-Symbol Cross Indicator Template - Unleash Your Potential!Unlock your full trading potential with this powerful and versatile Multi-Symbol Cross Indicator Template! This script is designed to make you stand out from the crowd by enabling you to monitor multiple symbols on a single chart for specific events, such as a Golden Cross or Death Cross. With its high adaptability to include various technical indicators, you're in complete control of your trading decisions and market analysis.
By using the built-in request.security function, this template fetches data for your chosen symbols from the selected exchange and calculates the conditions (e.g., moving average crossovers) for each symbol. Although the current implementation focuses on Golden Crosses and Death Crosses, the sky is the limit when it comes to modifying the script to incorporate other technical indicators such as RSI, MACD, or Bollinger Bands.
You, as a discerning trader, can easily customize the script by selecting your preferred exchange and symbols through input options. This flexibility allows you to monitor your favorite markets without the need for any direct code modification, giving you the ultimate adaptability for various trading strategies and market analysis purposes.
Remember, this script is more than just an example or template; it's the key to unleashing your inner trading genius. While it's not intended to be a standalone trading strategy, it serves as the foundation for you to build upon and create your own customized multi-symbol indicators or strategies. You are awesome, and with this Multi-Symbol Cross Indicator Template, there's no doubt that you're on the path to achieving great success in your trading journey!
NexTrader v2.1Trading can be a profitable pursuit but it can also be a very risky one.
A lot of traders do not have the time to study the market all day long, which means they don’t have the time to study the patterns that develop over the course of a day or week.
There is a way to trade that overcomes this problem by trading indicators that help you catch the trend in the early stages, something that is all too easy to miss. (The way to do this is to use a trading system based on the previous months average price and the current months average price, that is described in this post.)
Yes, it is possible to trade without indicators. We can argue about how much better it is to trade with trading indicators, but all is better than nothing.
Here in Nextrader we decided to show you how to trade with average* monthly prices. The idea behind this trading indicator is that the average monthly price is a reflection of the price action of the instrument.
Some traders believe that there is a possibility that the price will go back to the average monthly price level. In general, the use of the average monthly price as a trading indicator is not new and is very common among advanced traders.
Everyone is looking for trading indicators that can predict future trends.
This one is based on past prices and goes well across all time frames. It uses the average price for the current month and the average price for the last month to predict future price direction.
The indicator is the result of a simple moving average crossover system.
The fast average(white crosses) is based on the current month price and the slow average(red crosses) is based on the last month price. When the current month price crosses above the previous month price the signal line turns up and indicates a positive trend.
The thing to keep in mind here is that the average is not an indicator of when to buy or sell, but rather a direction signal generator.
The wider distances between two lines the stronger trend direction is. The shorter distance meaning more sideways price action.
* The average is just a mathematical tool that will help you to generate a trading rule.
wtfBUYorSELLffsMultiple timeframe Hull moving averages. 1 Hull period, 3 timeframes.
With Info Panel
This strategy is for any pair but the settings are tuned for DOGEUSDT
It is 3 Hull moving averages crossovers.
The first HMA is taken from the timeframe of the chart.
The second and third HMA's have a setting for TIMEFRAME.
For example the user can have the chart on 15m, 2nd HMA on 60m(1H), 3rd HMA on 240m(1H)
A info panel is on chart with the signal from each timeframe.
The binance (where DOGEUSDT can be traded) commission fee of 0.1% is added to the results.
Adjust the commission fee to suit your broker and pair.
Tuned for trading cryptocurrency Elon Musk has constantly been backing – dogecoin.
Ultimate Trader Oscillator - UTO v1Note; this is experimental / learning work -- has nothing to do with the existing "Ultimate Oscillator" -- i call this project UTOpia :)
This is based on some research work i was doing around the Balance Of Power - which i posted about in the past
the conclusion form there was a questions of, what would we get if we create an indicator that takes into consideration other factors that may be affecting momentum - so while the classic Balance of Power formula looks at where the open and close of a bar are compared to the full bar range, this is only a small part of the insight we need - when we visually inspect a price chart, we also look at many other factors. for example, how the bar closes compared to previous bar(s), how much did the bulls (or bears) managed to move the high (or low) of the bar compared to previous one, how much volume, how is the price spread ...etc
so i wanted to build an indicator that does exactly that - we will give a score of +100 / -100 to each bar based on these factors (some were identified in the linked post) -- imagine here that we are a judge in a tug of war contest (or a beauty contest if you would :)) and we give a score to the participating teams - the scores are given in different "categories" as these teams make effort to win the game (each bar) - to be totally fair, in some scoring categories, we choose to take the average of 3 points for a fair assessment - the final score is calculated based on the average from all judges - and then and average over the desired length is calculated. this score should be very fair and represents the true effort from all angles, right? that would be our UTOPIA :)
in our case, we don't use an average of total score after each category is evaluated, but rather create a directional index (similar to RSI) -- so we can avoid big spikes in the resulting numbers, and maintain a oscillator -like result.
-- the code is commented to explain the various pieces - and how the scoring happen.
the results are interesting - and you can see how the UTO stacks against the classic RSI and BoP - but it's more of a work to build on, rather than a usable indicator - although i do use it in my own trading :)
one final thought here, i came to learn after few years that the best indicators do not necessarily lead to profitable trading. from an indicator standpoint, if everyone else is trading using (for example) a moving average crossover or RSI, then a successful trader should be looking at these classic indicators too, cause these common indicators will drive the mass behavior - and will at many times trigger "self- fulfilling prophesies" in price action - but that's not the only or the biggest reason - the big reasons have to do with the fact that trading needs a lot of effort outside the charts, in researching markets, learning the discipline, then managing positions and managing the portfolio. these are all big topics to put in such short words.
i hope some will find this work inspiring.
Hull Moving Average x3 StrategyThree Hull Moving Average Crossovers , user can choose different history data periods, and timeframe ( indicator can look at timeframes other than just the current chart timeframe )
commission is already included in this result
EMA Trend Following Strategy🎯 EMA TREND FOLLOWING STRATEGY
A simple yet powerful trend-following strategy designed for 1-hour timeframes across multiple markets including cryptocurrencies, commodities, indices, and forex pairs.
📊 STRATEGY LOGIC
This strategy is based on the classic moving average crossover technique, one of the most reliable trend-following methods in technical analysis:
- LONG ENTRIES: When the fast EMA crosses above the slow EMA, indicating the beginning of an uptrend
- SHORT ENTRIES: When the fast EMA crosses below the slow EMA, indicating the beginning of a downtrend
- EXITS: Positions are closed when the opposite crossover occurs, capturing the trend reversal
🛡️ RISK MANAGEMENT
The strategy includes professional risk management features:
- Dynamic stop-loss based on market volatility
- Automatic position sizing to risk only a fixed percentage per trade
- Optional take-profit levels for securing gains
- Customizable risk parameters to fit your trading style
⚙️ RECOMMENDED SETTINGS
- Timeframe: 1 Hour (H1)
- Fast EMA: 20 periods
- Slow EMA: 50 periods
- Risk per trade: 1-2% of capital
- Stop-loss: 2x ATR (Average True Range)
💡 BEST USE CASES
This strategy works particularly well on:
✅ BTC/USD and major cryptocurrencies
✅ GOLD and precious metals
✅ S&P 500, NASDAQ, and major indices
✅ EUR/USD, GBP/USD and major forex pairs
⚠️ IMPORTANT NOTES
- Always backtest on your specific market before live trading
- Past performance does not guarantee future results
- Use appropriate position sizing and never risk more than you can afford to lose
- This strategy works best in trending markets
📈 Perfect for swing traders and those looking for a systematic approach to capture market trends!
Long Only EMA Strategy (9/20 with 200 EMA Filter)Details:
This strategy is built around a very simple idea: follow the primary trend and enter only when momentum supports it.
It uses three EMAs on a standard candlestick chart:
1. 9‑period EMA – short‑term momentum
2. 20‑period EMA – medium‑term structure
3. 200‑period EMA – long‑term trend filter
The strategy is ** long‑only ** and is mainly designed for swing trading and positional trading.
It avoids counter‑trend trades by taking entries only when price is trading ** above the 200 EMA **, which is commonly used as a long‑term trend reference.
The rules are deliberately kept simple so that they are easy to understand, modify, and test on different markets and timeframes.
---
Key Features
1. **Trend‑Filtered Entries**
- Fresh long positions are considered only when:
- The 9 EMA crosses above the 20 EMA
- The closing price is **above** the 200 EMA
- This attempts to combine short‑term momentum with a higher‑timeframe trend filter.
2. **Clean Exit Logic**
- The long position is exited when the closing price crosses **below** the 20 EMA.
- This creates an objective, rule‑based way to trail the trade as long as the medium‑term structure remains intact.
3. **Long‑Only, No Short Selling**
- The script intentionally ignores short setups.
- This makes it suitable for markets or accounts where short selling is restricted, or for traders who prefer to participate only on the long side of the market.
4. **Simple Visuals**
- All three EMAs are plotted directly on the chart:
- 9 EMA (fast)
- 20 EMA (medium)
- 200 EMA (trend)
- Trade entries and exits are handled by TradingView’s strategy engine, so users can see results in the Strategy Tester as well as directly on the chart.
5. **Backtest‑Friendly Structure**
- Uses TradingView’s built‑in `strategy()` framework.
- Can be applied to different symbols, timeframes, and markets (equities, indices, crypto, etc.).
- Works on standard candlestick charts, which are supported by TradingView’s backtesting engine.
6. **Configurable in Code**
- The EMA periods are defined in the code and can be easily adjusted.
- Users can tailor the parameters to fit their own style (for example, faster EMAs for intraday trading, slower EMAs for positional trades).
---
How to Use
1. **Add the Strategy to Your Chart**
1. Open any symbol and select a **standard candlestick chart**.
2. Apply the strategy from your “My Scripts” section.
3. Make sure it is enabled so that the trades and results appear.
2. **Select Timeframe**
- The logic can be tested on various timeframes:
- Higher timeframes (1H, 4H, 1D) for swing and positional setups.
- Lower timeframes (5m, 15m) for more active trading, if desired.
- Users should experiment and see where the strategy behaves more consistently for their chosen market.
3. **Read the Signals**
- **Entry:**
- A long trade is opened when the 9 EMA crosses above the 20 EMA while the closing price is above the 200 EMA.
- **Exit:**
- The open long position is closed when the closing price crosses below the 20 EMA.
- All orders are generated automatically once the strategy is attached to the chart.
4. **Use the Strategy Tester**
- Go to the **Strategy Tester** tab in TradingView.
- Check:
- Net profit / drawdown
- Win rate and average trade
- List of trades and the equity curve
- Change the date range and timeframe to see how stable the results are over different periods.
5. **Adjust Parameters if Needed**
- Advanced users can open the code and experiment with:
- EMA lengths (for example 8/21 with 200, or 10/30 with 200)
- Risk sizing and capital settings within the `strategy()` call
- Any changes should be thoroughly re‑tested before considering real‑world application.
---
Practical Applications
1. **Swing Trading on Daily Charts**
- Can be applied to stocks, indices, or ETFs on the daily timeframe.
- The 200 EMA acts as a trend filter to stay aligned with the broad direction, while the 9/20 crossover helps catch medium‑term swings inside that trend.
2. **Positional Trades on Higher Timeframes**
- On 4H or 1D charts, this approach can help in holding trades for several days to weeks.
- The exit rule based on the 20 EMA crossing helps avoid emotional decisions and provides a rules‑based way to trail the trend.
3. **Trend‑Following Filter**
- Even if used purely as a filter, the 200 EMA condition can help traders:
- Avoid taking long trades when the market is in a clear downtrend.
- Focus only on instruments that are trading above their long‑term average.
4. **Educational Use**
- The script is intentionally kept straightforward so that newer users can:
- Learn how a moving average crossover strategy works.
- See how to combine a short‑term signal with a long‑term filter.
- Understand how TradingView’s strategy engine handles entries and exits.
5. **Basis for Further Development**
- This can serve as a starting point for more advanced systems.
- Traders can extend it by adding:
- Additional filters (RSI, volume, volatility filters, time‑of‑day filters, etc.)
- Risk management rules (fixed stop loss, take profit, trailing stops).
- The current version is kept minimal on purpose, so modifications are easy to implement and test.
---
Important Notes & Disclaimer
1. This strategy is provided **for testing, research, and educational purposes only**.
2. It is ** not ** a recommendation to buy or sell any financial instrument.
3. Past performance on historical data does not guarantee similar results in live markets.
4. Markets are risky and trading can lead to financial loss; users should always do their own research, manage risk appropriately, and consult a qualified financial professional if needed.
5. Before using any strategy with real capital, it is strongly advised to:
- Forward test it on a demo / paper trading account.
- Check how it behaves during different market phases (trending, sideways, high‑volatility conditions).
You are free to modify the parameters and logic to better align it with your own trading style and risk tolerance.
ANN TREND SPX500 1m-1HHappy Trading! This indicator is the successor to my previous ANN Trend Prediction, now featuring improved feature vectors, refined backpropagation, and a stronger focus on asset- and timeframe-specific patterns for more precise predictions.
Internally is a collection of nine artificial neural networks (ANNs) trained on the S&P 500 to forecast uptrends, downtrends, or ranging markets. Each ANN is trained on one of the following timeframes: 1m, 2m, 3m, 5m, 10m, 15m, 30m, 45m, and 60m, and the appropriate model is selected automatically.
1. Settings
In the settings menu shown in the image below, you’ll find six options:
Indicator Timeframe – Choose between 1m and 1H.
Intrabar – Choose between Alerts been send intrabar or only at bar closing.
Lookback – Define how many previous bars the ANN should use in its calculations.
Smoothing – To reduce short-term switching of the prediction you can activate Smoothing. Here-by the input datas get filtered by a mean function.
Range Filter – Enable a third class, Ranging, in addition to Uptrend and Downtrend. This enables you to avoid choppy markets.
Class Colors – Here you can change each Class (Up, Down Trend etc) color.
2. Comparison with EMA crossover
The Prediction of the ANN Trend SPX500 1m-1H is more reliable as the prediction of the EMA crossover, shown in the Image below.
Both indicators use the same period of 65 bars and source their input data from the same chart.
While the EMA crosses over multiple times (shown as red vertical lines in the image), the ANN Trend maintains its prediction signal as Uptrend.
This advantage of the ANN comes from its learned knowledge. During training, it was exposed to a vast number of price charts, enabling it to distinguish between a trend setback and a true trend reversal.
3. Alerts
The indicator generates two types of alert signals:
Trade Signal:
1 = Uptrend
0 = Ranging
-1 = Downtrend
-2 = no prediction
Signal Age: Counts the number of bars since the last signal change. With the Signal Age you have access to the entry-price of the actual Trend. If you use You just call close to get the last entry-price.
4. Declaration for TradingView House Rules on Script Publishing
The unique feature of ANN Trend SPX500 1m-1H is it's real-time range detection capability and it's capability to distinguishes between a Trend set back and a Trend reversal which results in longer lasting trend predictions in comparison to any Moving Average Crossover Indicators.
This script is closed-source and invite-only, to support and compensate for months of development work.
5. Disclaimer
Trading involves risk, and losses can and do occur. This script is intended for informational and educational purposes only. All examples are hypothetical and not financial advice.
Decisions to buy, sell, hold, or trade securities, commodities, or other assets should be based on the advice of qualified financial professionals. Past performance does not guarantee future results.
Use this script at your own risk. It may contain bugs, and I cannot be held responsible for any financial losses resulting from its use.
Cheers!
KI-StageSpot V1KI-StageSpot V1 – Stage & Base Structure Analysis
Concept & Purpose
KI-StageSpot identifies Stage 1 to Stage 3 transitions by quantifying weekly base structures instead of relying only on moving average crossovers. Each base is derived from confirmed weekly pivot highs and lows that meet predefined duration and depth criteria. When a new low undercuts the prior base, the logic automatically merges the bases to preserve structural continuity. This framework is designed for traders studying trend evolution and Stage 2 continuation patterns.
Why this combination matters:
The script integrates structural (base tracking) and momentum (EMA Cloud) signals within one visual system. Weekly pivots and SMA-based stage markers outline the long-term structure, while the Daily EMA(10/20) Cloud reveals shorter-term momentum shifts inside each base. This cross-timeframe alignment helps confirm whether a breakout is supported by real strength or not.
How it works (conceptual overview)
•Weekly logic isolates each confirmed pivot high as a Base High (BH) and tracks the Base Low (BL) dynamically.
•Once price breaks above a BH, a Breakout (BO) label is triggered, and the base statistics freeze.
•Base statistics include Depth % and Duration (weeks), with optional color alerts for extended or deep corrections.
•Stage arrows derive from SMA(50/150/200) interactions to signal ST–MT–LT trend transitions.
•Timeframe-aware plotting ensures EMA clouds appear only on Daily, while SMAs and base logic stay internally synchronized on Weekly.
Key Features
•Automatic detection of Base Highs / Breakouts
•Base depth % and duration (weeks) labels
•Merge logic for undercut bases
•Daily EMA(10/20) Cloud for momentum tracking
•SMA 50 / 150 / 200 with stage arrows
•Customizable labels, offsets, and alerts
•Clean multi-TF plotting (Daily + Weekly)
Usage
•Start / End Date: Define your back-test window (e.g., post Stage 1 lockout or pre-Stage 2 base).
•Base Stats: Enable Depth % + Weeks; use alert levels Depth ≥ 30 %, Weeks > 12.
•EMA Cloud: Show = ON, Fast = 10, Slow = 20.
•SMAs: Show = ON (50 / 150 / 200 Daily; auto ≈ 10 / 30 / 40 Weekly).
•Labels: Compact or Expanded View per preference.
Analyze the structural setup on the Weekly chart and confirm early momentum through the Daily EMA cloud. When a breakout forms above a validated base high with supportive momentum, it often marks a Stage 2 expansion.
Squeeze Hour Frequency [CHE]Squeeze Hour Frequency (ATR-PR) — Standalone — Tracks daily squeeze occurrences by hour to reveal time-based volatility patterns
Summary
This indicator identifies periods of unusually low volatility, defined as squeezes, and tallies their frequency across each hour of the day over historical trading sessions. By aggregating counts into a sortable table, it helps users spot hours prone to these conditions, enabling better scheduling of trading activity to avoid or target specific intraday regimes. Signals gain robustness through percentile-based detection that adapts to recent volatility history, differing from fixed-threshold methods by focusing on relative lowness rather than absolute levels, which reduces false positives in varying market environments.
Motivation: Why this design?
Traders often face uneven intraday volatility, with certain hours showing clustered low-activity phases that precede or follow breakouts, leading to mistimed entries or overlooked calm periods. The core idea of hourly squeeze frequency addresses this by binning low-volatility events into 24 hourly slots and counting distinct daily occurrences, providing a historical profile of when squeezes cluster. This reveals time-of-day biases without relying on real-time alerts, allowing proactive adjustments to session focus.
What’s different vs. standard approaches?
- Reference baseline: Classical volatility tools like simple moving average crossovers or fixed ATR thresholds, which flag squeezes uniformly across the day.
- Architecture differences:
- Uses persistent arrays to track one squeeze per hour per day, preventing overcounting within sessions.
- Employs custom sorting on ratio arrays for dynamic table display, prioritizing top or bottom performers.
- Handles timezones explicitly to ensure consistent binning across global assets.
- Practical effect: Charts show a persistent table ranking hours by squeeze share, making intraday patterns immediately visible—such as a top hour capturing over 20 percent of total events—unlike static overlays that ignore temporal distribution, which matters for avoiding low-liquidity traps in crypto or forex.
How it works (technical)
The indicator first computes a rolling volatility measure over a specified lookback period. It then derives a relative ranking of the current value against recent history within a window of bars. A squeeze is flagged when this ranking falls below a user-defined cutoff, indicating the value is among the lowest in the recent sample.
On each bar, the local hour is extracted using the selected timezone. If a squeeze occurs and the bar has price data, the count for that hour increments only if no prior mark exists for the current day, using a persistent array to store the last marked day per hour. This ensures one tally per unique trading day per slot.
At the final bar, arrays compile counts and ratios for all 24 hours, where the ratio represents each hour's share of total squeezes observed. These are sorted ascending or descending based on display mode, and the top or bottom subset populates the table. Background shading highlights live squeezes in red for visual confirmation. Initialization uses zero-filled arrays for counts and negative seeds for day tracking, with state persisting across bars via variable declarations.
No higher timeframe data is pulled, so there is no repaint risk from external fetches; all logic runs on confirmed bars.
Parameter Guide
ATR Length — Controls the lookback for the volatility measure, influencing sensitivity to short-term fluctuations; shorter values increase responsiveness but add noise, longer ones smooth for stability — Default: 14 — Trade-offs/Tips: Use 10-20 for intraday charts to balance quick detection with fewer false squeezes; test on historical data to avoid over-smoothing in trending markets.
Percentile Window (bars) — Sets the history depth for ranking the current volatility value, affecting how "low" is defined relative to past; wider windows emphasize long-term norms — Default: 252 — Trade-offs/Tips: 100-300 bars suit daily cycles; narrower for fast assets like crypto to catch recent regimes, but risks instability in sparse data.
Squeeze threshold (PR < x) — Defines the cutoff for flagging low relative volatility, where values below this mark a squeeze; lower thresholds tighten detection for rarer events — Default: 10.0 — Trade-offs/Tips: 5-15 percent for conservative signals reducing false positives; raise to 20 for more frequent highlights in high-vol environments, monitoring for increased noise.
Timezone — Specifies the reference for hourly binning, ensuring alignment with market sessions — Default: Exchange — Trade-offs/Tips: Set to "America/New_York" for US assets; mismatches can skew counts, so verify against chart timezone.
Show Table — Toggles the results display, essential for reviewing frequencies — Default: true — Trade-offs/Tips: Disable on mobile for performance; pair with position tweaks for clean overlays.
Pos — Places the table on the chart pane — Default: Top Right — Trade-offs/Tips: Bottom Left avoids candle occlusion on volatile charts.
Font — Adjusts text readability in the table — Default: normal — Trade-offs/Tips: Tiny for dense views, large for emphasis on key hours.
Dark — Applies high-contrast colors for visibility — Default: true — Trade-offs/Tips: Toggle false in light themes to prevent washout.
Display — Filters table rows to focus on extremes or full list — Default: All — Trade-offs/Tips: Top 3 for quick scans of risky hours; Bottom 3 highlights safe low-squeeze periods.
Reading & Interpretation
Red background shading appears on bars meeting the squeeze condition, signaling current low relative volatility. The table lists hours as "H0" to "H23", with columns for daily squeeze counts, percentage share of total squeezes (summing to 100 percent across hours), and an arrow marker on the top hour. A summary row above details the peak count, its share, and the leading hour. A label at the last bar recaps total days observed, data-valid days, and top hour stats. Rising shares indicate clustering, suggesting regime persistence in that slot.
Practical Workflows & Combinations
- Trend following: Scan for hours with low squeeze shares to enter during stable regimes; confirm with higher highs or lower lows on the 15-minute chart, avoiding top-share hours post-news like tariff announcements.
- Exits/Stops: Tighten stops in high-share hours to guard against sudden vol spikes; use the table to shift to conservative sizing outside peak squeeze times.
- Multi-asset/Multi-TF: Defaults work across crypto pairs on 5-60 minute timeframes; for stocks, widen percentile window to 500 bars. Combine with volume oscillators—enter only if squeeze count is below average for the asset.
Behavior, Constraints & Performance
Logic executes on closed bars, with live bars updating counts provisionally but finalizing on confirmation; table refreshes only at the last bar, avoiding intrabar flicker. No security calls or higher timeframes, so no repaint from external data. Resources include a 5000-bar history limit, loops up to 24 iterations for sorting and totals, and arrays sized to 24 elements; labels and table are capped at 500 each for efficiency. Known limits: Skips hours without bars (e.g., weekends), assumes uniform data availability, and may undercount in sparse sessions; timezone shifts can alter profiles without warning.
Sensible Defaults & Quick Tuning
Start with ATR Length at 14, Percentile Window at 252, and threshold at 10.0 for broad crypto use. If too many squeezes flag (noisy table), raise threshold to 15.0 and narrow window to 100 for stricter relative lowness. For sluggish detection in calm markets, drop ATR Length to 10 and threshold to 5.0 to capture subtler dips. In high-vol assets, widen window to 500 and threshold to 20.0 for stability.
What this indicator is—and isn’t
This is a historical frequency tracker and visualization layer for intraday volatility patterns, best as a filter in multi-tool setups. It is not a standalone signal generator, predictive model, or risk manager—pair it with price action, news filters, and position sizing rules.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Thanks to Duyck
for the ma sorter
oscillator fast cryptosmart (Bands on Scale)The oscillator fast cryptosmart is a high-sensitivity momentum indicator designed to generate signals more rapidly than many traditional oscillators, such as the MACD. It is engineered to detect potential price breakouts by analyzing short-term market cycles.
At its core, the indicator uses a Detrended Price Oscillator (DPO) to remove the longer-term trend from price action, allowing it to focus purely on the underlying momentum cycles. It then calculates dynamic volatility bands around this oscillator line.
Signals are generated when momentum breaks out from a normal range, providing traders with an early warning of a potential acceleration in price.
How to Interpret the Signals:
Buy Signal (Green Vertical Line): A buy signal is generated when the oscillator's main line (yellow) crosses above its upper statistical band. This indicates a sharp surge in positive momentum, suggesting a potential upward move is beginning.
Sell Signal (Red Vertical Line): A sell signal is generated when the oscillator's main line crosses below its lower statistical band. This indicates a significant increase in negative momentum, suggesting a potential downward move is starting.
By focusing on momentum breakouts rather than lagging moving average crossovers, the oscillator fast cryptosmart aims to provide an edge in identifying opportunities in fast-moving markets.
