LongWave | QuantumResearchQuantumResearch LongWave Indicator
The LongWave Indicator is a comprehensive trend-following system that integrates two universal strategies, two technical indicators, and one on-chain indicator tailored specifically for Bitcoin (BTC).
By blending advanced market dynamics with on-chain insights, this indicator provides precise long and short signals to help traders navigate the market with confidence. 📊🚀
1. Overview
This indicator is designed to:
Identify Market Trends: Combines multiple trend-based methodologies to define clear market directions. 🔄
Leverage On-Chain Data: Utilizes fundamental Bitcoin network activity for enhanced trend validation. ⚡
Provide Customization: Allows users to fine-tune sensitivity, thresholds, and visual preferences. 🎨
2. How It Works
A. Multi-Layer Trend Detection
Two Universal Strategies – These strategies apply proprietary trend-following algorithms to analyze price movements over multiple timeframes. 🕰️
Two Technical Indicators – A combination of statistical smoothing and momentum-based calculations refines trend signals. 📈
One On-Chain Indicator – Analyzes Bitcoin’s market valuation and investor behavior to confirm directional bias. 🏦
B. Trend Score Calculation
Each component contributes to a weighted trend score, ensuring robust and adaptive market assessments. 📊
The final LongWave Score is derived by averaging inputs from the five core systems. ⚖️
C. Dynamic Thresholds & Signal Generation
Long Entry Signal – Triggered when the LongWave Score exceeds the upper threshold, indicating strong bullish momentum. ✅
Short/Cash Signal – Triggered when the LongWave Score drops below the lower threshold, signaling market weakness. ❌
3. Visual Representation
Trend Bar Coloring:
Green Bars – Indicate bullish momentum (Long Signal). ✅
Blue Bars – Indicate bearish momentum (Short/Cash Signal). ❌
Trend Confirmation Line:
A Hull Moving Average (HMA) dynamically shifts color based on market conditions. 📊
Table-Based Signal Dashboard:
Displays real-time trend scores for each component. 🔢
Includes rate of change (ROC) metrics to assess momentum shifts. 🚀
LW signal ligne:
Aligns with the LongWave Score to confirm entry and exit decisions.
4. Customization & Parameters
The LongWave Indicator is designed with high flexibility to adapt to various trading styles:
Threshold Adjustments:
Users can modify long and short thresholds to optimize signal sensitivity. 🎛️
Trend Component Weights:
Custom weighting for each universal strategy and indicator to tailor output precision. ⚙️
On-Chain Sensitivity:
Fine-tune on-chain Z-score parameters to reflect market conditions accurately. 📡
Visual Preferences:
Color Modes: Choose from multiple pre-set themes for enhanced readability. 🎨
5. Trading Applications
Trend Following – Ideal for traders looking to capitalize on extended bullish and bearish trends. 📈
Market Timing – Helps identify optimal entry and exit points with trend-based validation. ⏳
On-Chain Confluence – Merges technical analysis with on-chain insights to confirm directional bias. 🔗
Risk Management – Provides clear buy/cash indications, reducing uncertainty in trading decisions. ⚠️
6. Final Thoughts
The QuantumResearch LongWave Indicator is a high-precision tool designed for trend confirmation, risk mitigation, and market positioning.
By integrating technical and fundamental insights, it offers traders a complete market perspective.
Important Disclaimer: No indicator guarantees future performance. Always use proper risk management and conduct additional research. ⚠️📊
Analisi trend
TASC 2025.03 A New Solution, Removing Moving Average Lag█ OVERVIEW
This script implements a novel technique for removing lag from a moving average, as introduced by John Ehlers in the "A New Solution, Removing Moving Average Lag" article featured in the March 2025 edition of TASC's Traders' Tips .
█ CONCEPTS
In his article, Ehlers explains that the average price in a time series represents a statistical estimate for a block of price values, where the estimate is positioned at the block's center on the time axis. In the case of a simple moving average (SMA), the calculation moves the analyzed block along the time axis and computes an average after each new sample. Because the average's position is at the center of each block, the SMA inherently lags behind price changes by half the data length.
As a solution to removing moving average lag, Ehlers proposes a new projected moving average (PMA) . The PMA smooths price data while maintaining responsiveness by calculating a projection of the average using the data's linear regression slope.
The slope of linear regression on a block of financial time series data can be expressed as the covariance between prices and sample points divided by the variance of the sample points. Ehlers derives the PMA by adding this slope across half the data length to the SMA, creating a first-order prediction that substantially reduces lag:
PMA = SMA + Slope * Length / 2
In addition, the article includes methods for calculating predictions of the PMA and the slope based on second-order and fourth-order differences. The formulas for these predictions are as follows:
PredictPMA = PMA + 0.5 * (Slope - Slope ) * Length
PredictSlope = 1.5 * Slope - 0.5 * Slope
Ehlers suggests that crossings between the predictions and the original values can help traders identify timely buy and sell signals.
█ USAGE
This indicator displays the SMA, PMA, and PMA prediction for a specified series in the main chart pane, and it shows the linear regression slope and prediction in a separate pane. Analyzing the difference between the PMA and SMA can help to identify trends. The differences between PMA or slope and its corresponding prediction can indicate turning points and potential trade opportunities.
The SMA plot uses the chart's foreground color, and the PMA and slope plots are blue by default. The plots of the predictions have a green or red hue to signify direction. Additionally, the indicator fills the space between the SMA and PMA with a green or red color gradient based on their differences:
Users can customize the source series, data length, and plot colors via the inputs in the "Settings/Inputs" tab.
█ NOTES FOR Pine Script® CODERS
The article's code implementation uses a loop to calculate all necessary sums for the slope and SMA calculations. Ported into Pine, the implementation is as follows:
pma(float src, int length) =>
float PMA = 0., float SMA = 0., float Slope = 0.
float Sx = 0.0 , float Sy = 0.0
float Sxx = 0.0 , float Syy = 0.0 , float Sxy = 0.0
for count = 1 to length
float src1 = src
Sx += count
Sy += src
Sxx += count * count
Syy += src1 * src1
Sxy += count * src1
Slope := -(length * Sxy - Sx * Sy) / (length * Sxx - Sx * Sx)
SMA := Sy / length
PMA := SMA + Slope * length / 2
However, loops in Pine can be computationally expensive, and the above loop's runtime scales directly with the specified length. Fortunately, Pine's built-in functions often eliminate the need for loops. This indicator implements the following function, which simplifies the process by using the ta.linreg() and ta.sma() functions to calculate equivalent slope and SMA values efficiently:
pma(float src, int length) =>
float Slope = ta.linreg(src, length, 0) - ta.linreg(src, length, 1)
float SMA = ta.sma(src, length)
float PMA = SMA + Slope * length * 0.5
To learn more about loop elimination in Pine, refer to this section of the User Manual's Profiling and optimization page.
Advanced Liquidity Trap & Squeeze Detector [MazzaropiYoussef]DESCRIPTION:
The "Advanced Liquidity Trap & Squeeze Detector" is designed to identify potential liquidity traps, short and long squeezes, and market manipulation based on open interest, funding rates, and aggressive order flow.
KEY FEATURES:
- **Relative Open Interest Normalization**: Avoids scale discrepancies across different timeframes.
- **Liquidity Trap Detection**: Identifies potential bull and bear traps based on open interest and funding imbalances.
- **Squeeze Identification**: Highlights conditions where aggressive buyers or sellers are trapped before a reversal.
- **Volume Surge Confirmation**: Alerts when abnormal volume activity supports liquidity events.
- **Customizable Parameters**: Adjust thresholds to fine-tune detection sensitivity.
HOW IT WORKS:
- **Long Squeeze**: Triggered when relative open interest is high, funding is negative, and aggressive selling occurs.
- **Short Squeeze**: Triggered when relative open interest is high, funding is positive, and aggressive buying occurs.
- **Bull Trap**: Triggered when relative open interest is high, funding is positive, and price crosses above the trend line but fails.
- **Bear Trap**: Triggered when relative open interest is high, funding is negative, and price crosses below the trend line but fails.
USAGE:
- This indicator is useful for traders looking to anticipate reversals and avoid being caught in market manipulation events.
- Works best in combination with order book analysis and volume profile tools.
- Can be applied to crypto, forex, and other leveraged markets.
**/
Relative Performance SuiteOverview
The Relative Performance Suite (RPS) is a versatile and comprehensive indicator designed to evaluate an asset's performance relative to a benchmark. By offering multiple methods to measure performance, including Relative Performance, Alpha, and Price Ratio, this tool helps traders and investors assess asset strength, resilience, and overall behavior in different market conditions.
Key Features:
✅ Multiple Performance Measures:
Choose from various relative performance calculations, including:
Relative Performance:
Measures how much an asset has outperformed or underperformed its benchmark over a given period.
Relative Performance (Proportional):
A proportional version of relative performance,
factoring in scaling effects.
Relative Performance (MA Based):
Uses moving averages to smooth performance fluctuations.
Alpha:
A measure of an asset’s performance relative to what would be expected based on its beta and the benchmark’s return. It represents the excess return above the risk-free rate after adjusting for market risk.
Price Ratio:
Compares asset prices directly to determine relative value over time.
✅ Customizable Moving Averages:
Apply different moving average types (SMA, EMA, SMMA, WMA, VWMA) to smooth price inputs and refine calculations.
✅ Beta Calculation:
Includes a Beta measure used in Alpha calculation, which users can toggle the visibility of helping users understand an asset's sensitivity to market movements.
✅ Risk-Free Rate Adjustment:
Incorporate risk-free rates (e.g., US Treasury yields, Fed Funds Rate) for a more accurate calculation of Alpha.
✅ Logarithmic Returns Option:
Users can switch between standard returns and log returns for more refined performance analysis.
✅ Dynamic Color Coding:
Identify outperformance or underperformance with intuitive color coding.
Option to color bars based on relative strength, making chart analysis easier.
✅ Customizable Tables for Data Display:
Overview table summarizing key metrics.
Explanation table offering insights into how values are derived.
How to Use:
Select a Benchmark: Choose a comparison symbol (e.g., TOTAL or SPX ).
Pick a Performance Metric: Use different modes to analyze relative performance.
Customize Calculation Methods: Adjust moving averages, timeframes, and log returns based on preference.
Interpret the Colors & Tables: Utilize the dynamic coloring and tables to quickly assess market conditions.
Ideal For:
Traders looking to compare individual asset performance against an index or benchmark.
Investors analyzing Alpha & Beta to understand risk-adjusted returns.
Market analysts who want a visually intuitive and data-rich performance tracking tool.
This indicator provides a powerful and flexible way to track relative asset strength, helping users make more informed trading decisions.
Stick Sandwich Pattern# Stick Sandwich Pattern Indicator
## Description
The Stick Sandwich Pattern Indicator is a custom TradingView script that identifies specific three-candle patterns in financial markets. The indicator uses a sandwich emoji (🥪) to mark pattern occurrences directly on the chart, making it visually intuitive and easy to spot potential trading opportunities.
## Pattern Types
### Bullish Stick Sandwich
A bullish stick sandwich pattern is identified when:
- First candle: Bullish (close > open)
- Second candle: Bearish (close < open)
- Third candle: Bullish (close > open)
- The closing price of the third candle is within 10% of the first candle's range from its closing price
### Bearish Stick Sandwich
A bearish stick sandwich pattern is identified when:
- First candle: Bearish (close < open)
- Second candle: Bullish (close > open)
- Third candle: Bearish (close < open)
- The closing price of the third candle is within 10% of the first candle's range from its closing price
## Technical Implementation
- Written in Pine Script v5
- Runs as an overlay indicator
- Uses a 10% tolerance range for closing price comparison
- Implements rolling pattern detection over the last 3 candles
- Break statement ensures only the most recent pattern is marked
## Visual Features
- Bullish patterns: Green sandwich emoji above the pattern
- Bearish patterns: Red sandwich emoji below the pattern
- Label size: Small
- Label styles:
- Bullish: Label points upward
- Bearish: Label points downward
## Usage
1. Add the indicator to your TradingView chart
2. Look for sandwich emojis that appear above or below price bars
3. Green emojis indicate potential bullish reversals
4. Red emojis indicate potential bearish reversals
## Code Structure
- Main indicator function with overlay setting
- Two separate functions for pattern detection:
- `bullishStickSandwich()`
- `bearishStickSandwich()`
- Pattern scanning loop that checks the last 3 candles
- Built-in label plotting for visual identification
## Formula Details
The closing price comparison uses the following tolerance calculation:
```
Tolerance = (High - Low of first candle) * 0.1
Valid if: |Close of third candle - Close of first candle| <= Tolerance
```
## Notes
- The indicator marks patterns in real-time as they form
- Only the most recent pattern within the last 3 candles is marked
- Pattern validation includes both candle direction and closing price proximity
- The 10% tolerance helps filter out weak patterns while catching meaningful ones
## Disclaimer
This indicator is for informational purposes only. Always use proper risk management and consider multiple factors when making trading decisions.
ADX with Moving AverageADX with Moving Average is a powerful indicator that enhances trend analysis by combining the standard Average Directional Index (ADX) with a configurable moving average.
The ADX helps traders identify the strength of a trend. In general:
ADX 0-20 – Absent or Weak Trend
ADX 25-50 – Strong Trend
ADX 50-75 – Very Strong Trend
ADX 75-100 – Extremely Strong Trend
By adding a moving average we can judge if the ADX itself is trending upwards or downwards, i.e. if a new trend is emerging or an existing one is weakening.
This combination allows traders to better confirm strong trends and filter out weak or choppy market conditions.
Key Features & Customization:
✔ Configurable DI & ADX Lengths – Adjust how quickly the ADX reacts to price movements (default: 14, 14).
✔ Multiple Moving Average Options – Choose between SMA, EMA, WMA, VWMA, or T3 for trend confirmation.
✔ Custom MA Length – Fine-tune the sensitivity of the moving average to match your strategy.
🔹 Use this indicator to confirm strong trends before entering trades, filter out false signals, or refine existing strategies with a dynamic trend-strength component. 🚀
OI RSI - WuJianDAOOI RSI (Open Interest Relative Strength Index)
Overview: OI RSI is a technical indicator that applies the RSI concept to open interest data.
Key Features:
Traditional vs. OI RSI:
Traditional RSI measures price movements to identify overbought or oversold conditions.
OI RSI computes the relative strength of open interest over a specified period.
Purpose:
Provides insights into market participation and sentiment by evaluating open interest levels.
Application:
Assists traders in detecting potential reversals or confirming trends based on open interest dynamics.
ATR Volatility Expansion FilterThe ATR Volatility Expansion indicator helps traders identify when market volatility is increasing.
It compares two ATR values: the Baseline ATR, which tracks long-term volatility, and the Current ATR, which measures recent price movements.
The core concept is that when short-term volatility significantly surpasses the long-term average, it signals a period of heightened price movement. Traders can use this information to adjust their strategies accordingly.
Baseline ATR (blue): Represents long-term volatility, serving as a benchmark.
Current ATR (orange): Measures short-term volatility, highlighting recent market shifts.
Threshold ATR (red): A customizable multiplier of the Baseline ATR, setting the threshold for volatility expansion.
When the Current ATR exceeds the Threshold ATR, the background turns green, indicating volatility expansion. This provides traders with ability to get involved in moving markets or avoid choppy conditions.
The indicator is fully customizable, allowing you to adjust the ATR lengths, timeframe, and threshold multiplier to align with your trading strategy.
Pre-Market High & LowIndicator: Pre-Market High & Low
This indicator tracks the high and low price levels of a stock during the pre-market session (4:00 AM - 9:30 AM EST), before the official market open. It dynamically updates during pre-market hours, identifying the highest and lowest prices reached. Once the pre-market session ends, these levels are saved and plotted on the chart as reference points for the regular market session.
Key Features:
Dynamic Updates: Continuously tracks the high and low during pre-market hours.
Visual Indicators: Plots horizontal lines representing the pre-market high (green) and low (red).
Post-Market Reference: Once pre-market ends, these levels remain visible for the regular market session as reference points for potential breakout or breakdown levels.
How to Use:
Use this indicator to identify potential breakout or breakdown levels that may happen at the market open.
The green line represents the highest price reached during pre-market, while the red line indicates the lowest price.
The indicator will stop updating once the pre-market session closes (9:30 AM EST) and will remain visible as reference levels throughout the trading day.
Ideal for:
Day traders looking for pre-market support and resistance levels.
Traders analyzing the initial market reaction based on pre-market price action.
MT-Trend Zone IdentifierTrend Zone Identifier – A Dynamic Market Trend Mapping Tool
Overview
The Trend Zone Identifier is an advanced TradingView indicator that helps traders visualize different market trend phases. By leveraging Pivot Points, Moving Averages (MA), ADX (Average Directional Index), and Retest Confirmation, this tool identifies uptrend, downtrend, and ranging (sideways) conditions dynamically.
This indicator is designed to segment the market into clear trend zones, allowing traders to distinguish between confirmed trends, trend transitions (pending zones), and ranging markets. It provides an intuitive visual overlay to enhance market structure analysis and assist in decision-making.
Key Features
✔ Trend Zone Identification – Classifies price action into Uptrend (Green), Downtrend (Red), Pending Confirmation (Light Colors), and Sideways Market (Gray/Neutral)
✔ Pivot-Based Breakout & Breakdown Detection – Uses pivot highs/lows to determine trend shifts
✔ Moving Average & ADX Validation – Ensures the trend is backed by MA structure and ADX trend strength
✔ Pullback Confirmation – Allows trend confirmation based on price retesting key levels
✔ Extreme Volatility & Gaps Filtering – Optional ATR-based extreme movement filtering to avoid false signals
✔ Multi-Timeframe Support – Option to integrate higher timeframe trend validation
✔ Customizable Sensitivity – Fine-tune MA smoothing, ADX thresholds, pivot detection, and pullback range
How It Works
1. Trend Classification
• Uptrend (Green): Price is above a key MA, ADX confirms strength, and a pivot breakout occurs
• Downtrend (Red): Price is below a key MA, ADX confirms strength, and a pivot breakdown occurs
• Pending Trend (Light Colors): Initial trend breakout or breakdown is detected but requires further confirmation
• Sideways/Ranging (Gray): ADX signals a weak trend, and price remains within a neutral zone
2. Retest & Confirmation Logic
• A trend is only confirmed after a breakout or breakdown followed by a successful retest
• If the market fails the retest, the indicator resets to a neutral state
3. Custom Filters for Optimization
• Enable or disable volume filtering for confirmation
• Adjust pivot sensitivity to detect major or minor swing points
• Choose to require consecutive bars confirming the breakout/breakdown
Ideal Use Cases
🔹 Swing traders who want to capture trend transitions early
🔹 Trend-following traders who rely on confirmed market cycles
🔹 Range traders looking to identify sideways market zones
🔹 Algorithmic traders who need clean trend segmentation for automated strategies
Final Thoughts
The Trend Zone Identifier is a versatile market structure indicator that helps traders define trend cycles visually and avoid trading against weak trends. By providing clear breakout, breakdown, and retest conditions, it enhances market clarity and reduces decision-making errors.
➡ Add this to your TradingView workspace and start analyzing market trends like a pro! 🚀
FoundryFutures Filtered Tick**Foundry Futures Filtered Tick (FFFT) – TradingView Indicator**
Overview
The Foundry Futures Filtered Tick (FFFT) is a market breadth indicator that filters out noise to track only significant tick events. Using a Custom Composite Cumulative Tick formula, it monitors buying and selling pressure during large events or waves of orders across exchanges. This gives traders a clearer view of market sentiment and momentum shifts throughout the trading day, without the distraction of minor tick movements.
Key Features
• Filters large tick events while ignoring minor fluctuations
• Tracks cumulative bullish/bearish threshold crossings ("Events") to highlight momentum shifts
• Uses dynamic color gradient visualization (red for selling, cyan for buying)
• Provides zero-line reference for directional bias
• Displays integrated real-time table for market context and large event tracking
How to Use
1. Add to favorites
2. Open chart, navigate to indicators tab > Favorites > Search "FoundryFutures Filtered Tick"
3. Apply to your chart
4. Select preferred market and begin using
Adjust Settings
• Set positive & negative thresholds to define meaningful tick events (Default +/-999)
• Customize line width and colors for better visibility if desired
• Interpret Signals above or below zero intraday as momentum shifts in sentiment across exchanges.
• Above zero & rising → Increasing bullish momentum
• Below zero & falling → Increasing selling pressure
• Frequent crossings → Potential market exhaustion or range bound activity
Risk Disclaimer & Release of Liability
Trading futures is highly speculative and involves substantial risk. The FFFT indicator does not predict market direction or guarantee profitability. It is for educational purposes only and should be used alongside proper risk management and independent analysis.
**By using this indicator, you acknowledge that:**
• You are solely responsible for your trading decisions
• Foundry Futures and its creator make no warranties or guarantees regarding accuracy or profitability
• You assume full responsibility for any financial losses incurred
• If you do not agree with these terms, do not use this indicator. Trade responsibly
ChillLax Relative Strength Line with NewHigh NewLow Blue DotThis is similar to the IBD MarketSurge (MarketSmith) Blue Dot:
This plots the Relative Strength line vs. an index (default index is SPX), with a Dot when the RS line is hitting a New High.
If the RS hits a New High over the past X bars (default is 50), it shows a Light Blue (user definable) Dot on the RS line, if RS hits New High before the instrument hits New High, it shows a bigger/darker Blue Dot. Reverse for New Lows (orange for RS NL, Red for RS NL before Price NL)
This Dot is similar to the IBD Marketsurge RS New High Blue Dot, this indicator shows all the previous dots (MarketSurge shows only the last one). This on, unlike IBD, also shows RS New Lows. This one distinguishes RS NH before Price NH, and RS NL before Price NL. Lastly, IBD's lookback period is 52 week, here it is default to 50 days, but it is changeable.
Blockchain Fundamentals: Liquidity Cycle MomentumLiquidity Cycle Momentum Indicator
Overview:
This indicator analyzes global liquidity trends by calculating a unique Liquidity Index and measuring its year-over-year (YoY) percentage change. It then applies a momentum oscillator to the YoY change, providing insights into the cyclical momentum of liquidity. The indicator incorporates a limited historical data workaround to ensure accurate calculations even when the chart’s history is short.
Features Breakdown:
1. Limited Historical Data Workaround
Function: The limit(length) function adjusts the lookback period when there isn’t enough historical data (i.e., near the beginning of the chart), ensuring that calculations do not break due to insufficient data.
2. Global Liquidity Calculation
Data Sources:
TVC:CN10Y (10-year yield from China)
TVC:DXY (US Dollar Index)
ECONOMICS:USCBBS (US Central Bank Balance Sheet)
FRED:JPNASSETS (Japanese assets)
ECONOMICS:CNCBBS (Chinese Central Bank Balance Sheet)
FRED:ECBASSETSW (ECB assets)
Calculation Methodology:
A ratio is computed (cn10y / dxy) to adjust for currency influences.
The Liquidity Index is then derived by multiplying this ratio with the sum of the other liquidity components.
3. Year-over-Year (YoY) Percent Change
Computation:
The indicator determines the number of bars that approximately represent one year.
It then compares the current Liquidity Index to its value one year ago, calculating the YoY percentage change.
4. Momentum Oscillator on YoY Change
Oscillator Components:
1. Calculated using the Chande Momentum Oscillator (CMO) applied to the YoY percent change with a user-defined momentum length.
2. A weighted moving average (WMA) that smooths the momentum signal.
3. Overbought and Oversold zones
Signal Generation:
Buy Signal: Triggered when the momentum crosses upward from an oversold condition, suggesting a potential upward shift in liquidity momentum.
Sell Signal: Triggered when crosses below an overbought condition, indicating potential downward momentum.
State Management:
The indicator maintains a state variable to avoid repeated signals, ensuring that a new buy or sell signal is only generated when there’s a clear change in momentum.
5. Visual Presentation and Alerts
Plots:
The oscillator value and signalline are plotted for visual analysis.
Overbought and oversold levels are marked with dashed horizontal lines.
Signal Markers:
Buy and sell signals are marked with green and maroon circles, respectively.
Background Coloration:
Optionally, the chart’s background bars are colored (yellow for buy signals and fuchsia for sell signals) to enhance visual cues when signals are triggered.
Conclusion
In summary, the Liquidity Cycle Momentum Indicator provides a robust framework to analyze liquidity trends by combining global liquidity data, YoY changes, and momentum oscillation. This makes it an effective tool for traders and analysts looking to identify cyclical shifts in liquidity conditions and potential turning points in the market.
SMA with Std Dev Bands (Futures/US Stocks RTH)Rolling Daily SMA With Std Dev Bands
Upgrade your technical analysis with Rolling Daily SMA With Std Dev Bands, a powerful indicator that dynamically adjusts to your trading instrument. Whether you’re analyzing futures or US stocks during regular trading hours (RTH), this indicator seamlessly applies the correct logic to calculate a rolling daily Simple Moving Average (SMA) with customizable standard deviation bands for precise trend and volatility tracking.
Key Features:
✅ Automatic Instrument Detection– The indicator automatically recognizes whether you're trading futures or US equities and applies the correct daily lookback period based on your chart’s timeframe.
- Futures: Uses full trading day lengths (e.g., 1380 bars for 1‑minute charts).
- US Stocks (RTH): Uses regular session lengths (e.g., 390 bars for 1‑minute charts).
✅ Rolling Daily SMA (3‑pt Purple Line) – A continuously updated daily moving average, giving you an adaptive trend indicator based on market structure.
✅ Three Standard Deviation Bands (1‑pt White Lines) –
- Customizable multipliers allow you to adjust each band’s width.
- Toggle each band on or off to tailor the indicator to your strategy.
- The inner band area is color-filled: light green when the SMA is rising, light red when falling, helping you quickly identify trend direction.
✅ Works on Any Chart Timeframe – Whether you trade on 1-minute, 3-minute, 5-minute, or 15-minute charts, the indicator adjusts dynamically to provide accurate rolling daily calculations.
# How to Use:
📌 Identify Trends & Volatility Zones – The rolling daily SMA acts as a dynamic trend guide, while the standard deviation bands help spot potential overbought/oversold conditions.
📌 Customize for Precision – Adjust band multipliers and toggle each band on/off to match your trading style.
📌 Trade Smarter – The filled inner band offers instant visual feedback on market momentum, while the outer bands highlight potential breakout zones.
🔹 This is the perfect tool for traders looking to combine trend-following with volatility analysis in an easy-to-use, adaptive indicator.
🚀 Add Rolling Daily SMA With Std Dev Bands to your chart today and enhance your market insights!
---
*Disclaimer: This indicator is for informational and educational purposes only and should not be considered financial advice. Always use proper risk management and conduct your own research before trading.*
WaridTR15 Dakika ve Üzeri Periyotlar İçin Önerilen Ayarlar:
EMA Uzunlukları:
Kısa EMA: 9 yerine 12 veya 14 kullanılabilir.
Uzun EMA: 21 yerine 26 veya 50 kullanılabilir.
Golden Cross için 50 EMA ve 200 EMA zaten uzun vadeli trendleri yakalar, bu nedenle değiştirmeye gerek yok.
RSI Uzunluğu:
RSI uzunluğu 14 yerine 21 veya 28 yapılabilir. Bu, daha uzun vadeli aşırı alım/aşırı satım bölgelerini daha doğru tespit eder.
Volume Filtresi:
Volume ortalaması için 20 periyot yerine 50 veya 100 periyot kullanılabilir. Bu, daha uzun vadeli hacim eğilimlerini yakalar.
Ichimoku Parametreleri:
Ichimoku, varsayılan olarak 9-26-52 periyotlarıyla çalışır. Bu, zaten uzun vadeli trendleri yakalamak için uygundur. Ancak, daha uzun periyotlar için:
Tenkan-Sen: 9 yerine 14.
Kijun-Sen: 26 yerine 52.
Senkou Span B: 52 yerine 104.
Power of MovingThe Power of Moving indicator is a multi-moving average indicator designed to help traders identify strong trending conditions by analyzing the alignment and separation of multiple moving averages.
This indicator allows users to select between different types of moving averages (SMA, EMA, SMMA, WMA, VWMA) and plots four configurable moving averages on the chart. The background color dynamically changes when the moving averages are correctly stacked in a bullish (green) or bearish (yellow) formation, with sufficient distance between them. This ensures that trends are not only aligned but also have strong momentum. The indicator also includes alert conditions, notifying traders when the trend direction changes, allowing them to stay ahead of market moves.
This indicator works well in trending markets and should be combined with price action analysis or other confirmation indicators like RSI or volume for optimal results.
Dollar Cost Averaging (DCA) | FractalystWhat's the purpose of this strategy?
The purpose of dollar cost averaging (DCA) is to grow investments over time using a disciplined, methodical approach used by many top institutions like MicroStrategy and other institutions.
Here's how it functions:
Dollar Cost Averaging (DCA): This technique involves investing a set amount of money regularly, regardless of market conditions. It helps to mitigate the risk of investing a large sum at a peak price by spreading out your investment, thus potentially lowering your average cost per share over time.
Regular Contributions: By adding money to your investments on a pre-determined frequency and dollar amount defined by the user, you take advantage of compounding. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
Technical Analysis: The strategy employs a market trend ratio to gauge market sentiment. It calculates the ratio of bullish vs bearish breakouts across various timeframes, assigning this ratio a percentage-based score to determine the directional bias. Once this score exceeds a user-selected percentage, the strategy looks to take buy entries, signaling a favorable time for investment based on current market trends.
Fundamental Analysis: This aspect looks at the health of the economy and companies within it to determine bullish market conditions. Specifically, we consider:
Specifically, it considers:
Interest Rate: High interest rates can affect borrowing costs, potentially slowing down economic growth or making stocks less attractive compared to fixed income.
Inflation Rate: Inflation erodes purchasing power, but moderate inflation can be a sign of a healthy economy. We look for investments that might benefit from or withstand inflation.
GDP Rate: GDP growth indicates the overall health of the economy; we aim to invest in sectors poised to grow with the economy.
Unemployment Rate: Lower unemployment typically signals consumer confidence and spending power, which can boost certain sectors.
By integrating these elements, the strategy aims to:
Reduce Investment Volatility: By spreading out your investments, you're less impacted by short-term market swings.
Enhance Growth Potential: Using both technical and fundamental filters helps in choosing investments that are more likely to appreciate over time.
Manage Risk: The strategy aims to balance the risk of market timing by investing consistently and choosing assets wisely based on both economic data and market conditions.
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What are Regular Contributions in this strategy?
Regular Contributions involve adding money to your investments on a pre-determined frequency and dollar amount defined by the user. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
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How do regular contributions enhance compounding and reduce timing risk?
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
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How does the strategy integrate technical and fundamental analysis for investors?
A: The strategy combines technical and fundamental analysis in the following manner:
Technical Analysis: It uses a market trend ratio to determine the directional bias by calculating the ratio of bullish vs bearish breakouts. Once this ratio exceeds a user-selected percentage threshold, the strategy signals to take buy entries, optimizing the timing within the given timeframe(s).
Fundamental Analysis: This aspect assesses the broader economic environment to identify sectors or assets that are likely to benefit from current economic conditions. By understanding these fundamentals, the strategy ensures investments are made in assets with strong growth potential.
This integration allows the strategy to select investments that are both technically favorable for entry and fundamentally sound, providing a comprehensive approach to investment decisions in the crypto, stock, and commodities markets.
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How does the strategy identify market structure? What are the underlying calculations?
Q: How does the strategy identify market structure?
A: The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
What are the underlying calculations for identifying market structure?
A: The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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How does the script calculate trend score? What are the underlying calculations?
Market Trend Ratio: The script calculates the ratio of bullish to bearish breakouts. This involves:
Counting Bullish Breakouts: A bullish breakout is counted when the price breaks above a recent swing high (as identified in the strategy's market structure analysis).
Counting Bearish Breakouts: A bearish breakout is counted when the price breaks below a recent swing low.
Percentage-Based Score: This ratio is then converted into a percentage-based score:
For example, if there are 10 bullish breakouts and 5 bearish breakouts in a given timeframe, the ratio would be 10:5 or 2:1. This could be translated into a score where 66.67% (10/(10+5) * 100) represents the bullish trend strength.
The score might be calculated as (Number of Bullish Breakouts / Total Breakouts) * 100.
User-Defined Threshold: The strategy uses this score to determine when to take buy entries. If the trend score exceeds a user-defined percentage threshold, it indicates a strong enough bullish trend to justify a buy entry. For instance, if the user sets the threshold at 60%, the script would look for a buy entry when the trend score is above this level.
Timeframe Consideration: The calculations are performed across the timeframes specified by the user, ensuring the trend score reflects the market's behavior over different periods, which could be daily, weekly, or any other relevant timeframe.
This method provides a quantitative measure of market trend strength, helping to make informed decisions based on the balance between bullish and bearish market movements.
What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP
- You can choose to set a take profit level at which your position gets fully closed.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
Incorporation of Fundamental Analysis:
This strategy integrates fundamental analysis by considering key economic indicators such as interest rates, inflation, GDP growth, and unemployment rates. These fundamentals help in assessing the broader economic health, which in turn influences sector performance and market trends. By understanding these economic conditions, the strategy can identify sectors or assets that are likely to thrive, ensuring investments are made in environments conducive to growth. This approach allows for a more informed investment decision, aligning technical entries with fundamentally strong market conditions, thus potentially enhancing the strategy's effectiveness over time.
Technical Analysis Without Classical Methods:
The strategy's technical analysis diverges from traditional methods like moving averages by focusing on market structure through a trend score system.
Instead of using lagging indicators, it employs a real-time analysis of market trends by calculating the ratio of bullish to bearish breakouts. This provides several benefits:
Immediate Market Sentiment: The trend score system reacts more dynamically to current market conditions, offering insights into the market's immediate sentiment rather than historical trends, which can often lag behind real-time changes.
Reduced Overfitting: By not relying on moving averages or similar classical indicators, the strategy avoids the common pitfall of overfitting to historical data, which can lead to poor performance in new market conditions. The trend score provides a fresh perspective on market direction, potentially leading to more robust trading signals.
Clear Entry Signals: With the trend score, entry decisions are based on a clear percentage threshold, making the strategy's decision-making process straightforward and less subjective than interpreting moving average crossovers or similar signals.
Regular Contributions and Reminders:
The strategy encourages regular investments through a system of predefined frequency and amount, which could be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach:
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
Long-Term Wealth Building:
Focused on long-term wealth accumulation, this strategy:
Promotes Patience and Discipline: By emphasizing regular contributions and a disciplined approach to both entry and risk management, it aligns with the principles of long-term investing, discouraging impulsive decisions based on short-term market fluctuations.
Diversification Across Asset Classes: Operating across crypto, stocks, and commodities, the strategy provides diversification, which is a key component of long-term wealth building, reducing risk through varied exposure.
Growth Over Time: The strategy's design to work with the market's natural growth cycles, supported by fundamental analysis, aims for sustainable growth rather than quick profits, aligning with the goals of investors looking to build wealth over decades.
This comprehensive approach, combining fundamental insights, innovative technical analysis, disciplined investment habits, and a focus on long-term growth, offers a unique and potentially effective pathway for investors seeking to build wealth steadily over time.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
G-FRAMA | QuantEdgeBIntroducing G-FRAMA by QuantEdgeB
Overview
The Gaussian FRAMA (G-FRAMA) is an adaptive trend-following indicator that leverages the power of Fractal Adaptive Moving Averages (FRAMA), enhanced with a Gaussian filter for noise reduction and an ATR-based dynamic band for trade signal confirmation. This combination results in a highly responsive moving average that adapts to market volatility while filtering out insignificant price movements.
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1. Key Features
- 📈 Gaussian Smoothing – Utilizes a Gaussian filter to refine price input, reducing short-term noise while maintaining responsiveness.
- 📊 Fractal Adaptive Moving Average (FRAMA) – A self-adjusting moving average that adapts its sensitivity to market trends.
- 📉 ATR-Based Volatility Bands – Dynamic upper and lower bands based on the Average True Range (ATR), improving signal reliability.
- ⚡ Adaptive Trend Signals – Automatically detects shifts in market structure by evaluating price in relation to FRAMA and its ATR bands.
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2. How It Works
- Gaussian Filtering
The Gaussian function preprocesses the price data, giving more weight to recent values and smoothing fluctuations. This reduces whipsaws and allows the FRAMA calculation to focus on meaningful trend developments.
- Fractal Adaptive Moving Average (FRAMA)
Unlike traditional moving averages, FRAMA uses fractal dimension calculations to adjust its smoothing factor dynamically. In trending markets, it reacts faster, while in sideways conditions, it reduces sensitivity, filtering out noise.
- ATR-Based Volatility Bands
ATR is applied to determine upper and lower thresholds around FRAMA:
- 🔹 Long Condition: Price closes above FRAMA + ATR*Multiplier
- 🔻 Short Condition: Price closes below FRAMA - ATR
This setup ensures entries are volatility-adjusted, preventing premature exits or false signals in choppy conditions.
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3. Use Cases
✔ Adaptive Trend Trading – Automatically adjusts to different market conditions, making it ideal for both short-term and long-term traders.
✔ Noise-Filtered Entries – Gaussian smoothing prevents false breakouts, allowing for cleaner entries.
✔ Breakout & Volatility Strategies – The ATR bands confirm valid price movements, reducing false signals.
✔ Smooth but Aggressive Shorts – While the indicator is smooth in overall trend detection, it reacts aggressively to downside moves, making it well-suited for traders focusing on short opportunities.
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4. Customization Options
- Gaussian Filter Settings – Adjust length & sigma to fine-tune the smoothness of the input price. (Default: Gaussian length = 4, Gaussian sigma = 2.0, Gaussian source = close)
- FRAMA Length & Limits – Modify how quickly FRAMA reacts to price changes.(Default: Base FRAMA = 20, Upper FRAMA Limit = 8, Lower FRAMA Limit = 40)
- ATR Multiplier – Control how wide the volatility bands are for long/short entries.(Default: ATR Length = 14, ATR Multiplier = 1.9)
- Color Themes – Multiple visual styles to match different trading environments.
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Conclusion
The G-FRAMA is an intelligent trend-following tool that combines the adaptability of FRAMA with the precision of Gaussian filtering and volatility-based confirmation. It is versatile across different timeframes and asset classes, offering traders an edge in trend detection and trade execution.
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🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Ichimoku(TF)This Pine Script indicator is a comprehensive Ichimoku Cloud implementation designed for TradingView. Its uniqueness lies in the precisely calculated settings for each timeframe, offering a tailored Ichimoku experience across different chart resolutions.
Key Features:
Timeframe-Specific Presets: The indicator includes a wide range of pre-defined settings optimized for various timeframes (1m, 2m, 3m, 5m, 10m, 15m, 30m, 45m, 1H, 2H, 3H, 4H, 6H, 12H, 18H, 1D, 3D, 1W, 1M). This ensures accurate Ichimoku calculations and relevant signals for your chosen timeframe.
Ichimoku Cloud: Plots the standard Ichimoku Cloud components: Tenkan-sen (Conversion Line), Kijun-sen (Base Line), Senkou Span A & B (Leading Spans), and Chikou Span (Lagging Span).
Configurable Display: Allows toggling the Ichimoku Cloud display, coloring bars based on the trend (above or below the cloud), and customizing table visibility, style, font size and position.
Trend Analysis Table: A summary table provides a quick overview of the current trend based on Ichimoku components. It assesses the strength of the trend based on the price's relation to the Tenkan-sen, Kijun-sen, Kumo Cloud, Chikou Span and Kumo Twist. The table offers both detailed and short styles.
Buy/Sell Signals: Generates buy and sell signals based on Tenkan-sen/Kijun-sen crossovers.
Uniqueness:
The primary advantage of this indicator is its meticulous configuration for different timeframes. Instead of using a single set of parameters for all timeframes, it provides optimized values that are more suitable for specific chart resolutions. The summary table provides an easy and quick way to assess the trend.
Этот индикатор Pine Script представляет собой комплексную реализацию облака Ишимоку, разработанную для TradingView. Его уникальность заключается в точно рассчитанных настройках для каждого таймфрейма, предлагая индивидуальный опыт Ишимоку для различных разрешений графиков.
Ключевые особенности:
Предустановки для конкретных таймфреймов: Индикатор включает в себя широкий спектр предопределенных настроек, оптимизированных для различных таймфреймов (1m, 2m, 3m, 5m, 10m, 15m, 30m, 45m, 1H, 2H, 3H, 4H, 6H, 12H, 18H, 1D, 3D, 1W, 1M). Это обеспечивает точные вычисления Ишимоку и релевантные сигналы для выбранного вами таймфрейма.
Облако Ишимоку: Отображает стандартные компоненты облака Ишимоку: Tenkan-sen (линия конверсии), Kijun-sen (базовая линия), Senkou Span A & B (ведущие диапазоны) и Chikou Span (запаздывающий диапазон).
Настраиваемое отображение: Позволяет переключать отображение облака Ишимоку, окрашивать бары в зависимости от тренда (выше или ниже облака), а также настраивать видимость таблицы, стиль, размер шрифта и положение.
Таблица анализа тренда: Сводная таблица обеспечивает быстрый обзор текущего тренда на основе компонентов Ишимоку. Он оценивает силу тренда на основе отношения цены к Tenkan-sen, Kijun-sen, облаку Kumo, Chikou Span и Kumo Twist. Таблица предлагает как подробный, так и краткий стили.
Сигналы покупки/продажи: Генерирует сигналы покупки и продажи на основе пересечений Tenkan-sen/Kijun-sen.
Уникальность:
Основным преимуществом этого индикатора является его тщательная настройка для разных таймфреймов. Вместо использования единого набора параметров для всех таймфреймов он предоставляет оптимизированные значения, которые больше подходят для конкретных разрешений графиков. Сводная таблица обеспечивает простой и быстрый способ оценки тренда.
Smart Trend Tracker Name: Smart Trend Tracker
Description:
The Smart Trend Tracker indicator is designed to analyze market cycles and identify key trend reversal points. It automatically marks support and resistance levels based on price dynamics, helping traders better navigate market structure.
Application:
Trend Analysis: The indicator helps determine when a trend may be nearing a reversal, which is useful for making entry or exit decisions.
Support and Resistance Levels: Automatically marks key levels, simplifying chart analysis.
Reversal Signals: Provides visual signals for potential reversal points, which can be used for counter-trend trading strategies.
How It Works:
Candlestick Sequence Analysis: The indicator tracks the number of consecutive candles in one direction (up or down). If the price continues to move N bars in a row in one direction, the system records this as an impulse phase.
Trend Exhaustion Detection: After a series of directional bars, the market may reach an overbought or oversold point. If the price continues to move in the same direction but with weakening momentum, the indicator records a possible trend slowdown.
Chart Display: The indicator marks potential reversal points with numbers or special markers. It can also display support and resistance levels based on key cycle points.
Settings:
Cycle Length: The number of bars after which the possibility of a reversal is assessed.
Trend Sensitivity: A parameter that adjusts sensitivity to trend movements.
Dynamic Levels: Setting for displaying key levels.
Название: Smart Trend Tracker
Описание:
Индикатор Smart Trend Tracker предназначен для анализа рыночных циклов и выявления ключевых точек разворота тренда. Он автоматически размечает уровни поддержки и сопротивления, основываясь на динамике цены, что помогает трейдерам лучше ориентироваться в структуре рынка.
Применение:
Анализ трендов: Индикатор помогает определить моменты, когда тренд может быть близок к развороту, что полезно для принятия решений о входе или выходе из позиции.
Определение уровней поддержки и сопротивления: Автоматически размечает ключевые уровни, что упрощает анализ графика.
Сигналы разворота: Индикатор предоставляет визуальные сигналы о возможных точках разворота, что может быть использовано для стратегий, основанных на контртрендовой торговле.
Как работает:
Анализ последовательности свечей: Индикатор отслеживает количество последовательных свечей в одном направлении (вверх или вниз). Если цена продолжает движение N баров подряд в одном направлении, система фиксирует это как импульсную фазу.
Выявление истощения тренда: После серии направленных баров рынок может достичь точки перегрева. Если цена продолжает двигаться в том же направлении, но с ослаблением импульса, индикатор фиксирует возможное замедление тренда.
Отображение на графике: Индикатор отмечает точки потенциального разворота номерами или специальными маркерами. Также возможен вывод уровней поддержки и сопротивления, основанных на ключевых точках цикла.
Настройки:
Длина цикла (Cycle Length): Количество баров, после которых оценивается возможность разворота.
Фильтрация тренда (Trend Sensitivity): Параметр, регулирующий чувствительность к трендовым движениям.
Уровни поддержки/сопротивления (Dynamic Levels): Настройка для отображения ключевых уровней.
Harish algo for nifty and bankniftyHarish algo for nifty and banknifty
Overview
Harish Algo - Buy and Sell 11 is a powerful trading indicator designed for intraday traders, incorporating multiple technical analysis concepts to identify potential breakout and breakdown levels. It uses pivot points, exponential moving averages (EMAs), and volatility-based levels to generate buy and sell signals with visual markers for better decision-making.
Features & Functionality
✅ Pivot Points Calculation:
The indicator calculates daily pivot points along with resistance (R1) and support (S1) levels.
Helps in identifying potential reversal or breakout areas.
✅ EMA Trend Confirmation:
Uses three EMAs (21, 55, and 200) to confirm trend direction.
Ensures that buy signals align with uptrends and sell signals align with downtrends.
✅ 15-Minute Candle Analysis for Precision:
Captures the last three 15-minute closes of the previous day.
Computes an average and determines volatility-based price levels to anticipate price movements.
✅ Dynamic Buy & Sell Signals:
Bullish (Buy) Signals:
Price breaks above key resistance levels and EMAs confirm an uptrend.
Displayed as yellow (tiny) or green (small) upward triangles below candles.
Bearish (Sell) Signals:
Price drops below key support levels with EMA confirmation of a downtrend.
Displayed as fuchsia (tiny) or red (small) downward triangles above candles.
✅ Alerts for Trade Execution:
Get notified instantly with alerts when a buy or sell signal is triggered.
✅ Customizable Settings:
Modify EMA lengths and adjust parameters to fit different trading strategies.
Usage & Benefits
🔹 Helps traders identify potential entry and exit points with precision.
🔹 Reduces false signals by combining pivot points, EMAs, and price action.
🔹 Works best for intraday traders in the Indian stock markets, but can be applied to other markets as well.
🔹 Suitable for both beginners and experienced traders looking for a structured approach to trading.
How to Use
Add the indicator to your chart.
Observe the plotted pivot points, EMAs, and price levels.
Watch for triangle markers (buy/sell signals).
Use alerts to receive real-time notifications.
Combine with your own risk management strategy for best results.
🔹 Works on all timeframes but optimized for intraday trading.
Disclaimer
📢 This indicator is for educational purposes only and should not be considered financial advice. Always perform your own analysis before taking trades.
HMA 4H and 15M overlay Notes:
HMA Calculation: We calculate three HMAs for the 15-minute timeframe (ma1, ma2, ma3) based on the settings from your original script, but only ma3 is plotted to keep it consistent with your initial setup.
4-hour HMA: An additional HMA is calculated for the 4-hour timeframe (hma4h) using the hma3 period since it was the longest in your original setup, which might be suitable for a 4-hour chart comparison.
Plotting: Both the 15-minute ma3 and 4-hour hma4h HMAs are plotted with distinct colors for easy visual differentiation.
Timeframe Security: request.security() is used to fetch data from different timeframes. Remember, using request.security() with historical data can sometimes lead to misalignments or delayed data, especially during live trading.
This script will overlay the 15-minute HMA (using the ma3 from your settings) with a new 4-hour HMA on any chart timeframe you apply it to. Remember, if you're looking at a chart timeframe that's not 15 minutes or 4 hours, the HMAs might appear less smooth or aligned due to how Pine Script handles different timeframes.
Range Filtered Trend Signals [AlgoAlpha]Introducing the Range Filtered Trend Signals , a cutting-edge trading indicator designed to detect market trends and ranging conditions with high accuracy. This indicator leverages a combination of Kalman filtering and Supertrend analysis to smooth out price fluctuations while maintaining responsiveness to trend shifts. By incorporating volatility-based range filtering, it ensures traders can differentiate between trending and ranging conditions effectively, reducing false signals and enhancing trade decision-making.
:key: Key Features
:white_check_mark: Kalman Filter Smoothing – Minimizes market noise while preserving trend clarity.
:bar_chart: Supertrend Integration – A dynamic trend-following mechanism for spotting reversals.
:fire: Volatility-Based Range Detection – Detects trending vs. ranging conditions with precision.
:art: Color-Coded Trend Signals – Instantly recognize bullish, bearish, and ranging market states.
:gear: Customizable Inputs – Fine-tune Kalman parameters, Supertrend settings, and color themes to match your strategy.
:bell: Alerts for Trend Shifts – Get real-time notifications when market conditions change!
:tools: How to Use
Add the Indicator – Click the star icon to add it to your TradingView favorites.
Analyze Market Conditions – Observe the color-coded signals and range boundaries to identify trend strength and direction.
Use Alerts for Trade Execution – Set alerts for trend shifts and market conditions to stay ahead without constantly monitoring charts.
:mag: How It Works
The Kalman filter smooths price fluctuations by dynamically adjusting its weighting based on market volatility. It helps remove noise while keeping the signal reactive to trend changes. The Supertrend calculation is then applied to the filtered price data, providing a robust trend-following mechanism. To enhance signal accuracy, a volatility-weighted range filter is incorporated, creating upper and lower boundaries that define trend conditions. When price breaks out of these boundaries, the indicator confirms trend continuation, while signals within the range indicate market consolidation. Traders can leverage this tool to enhance trade timing, filter false breakouts, and identify optimal entry/exit zones.
SIOVERSE EMA 15 with Buy/Sell Signals, Support & ResistanceThis Pine Script indicator is designed for TradingView and combines Exponential Moving Averages (EMAs), support and resistance levels, buy/sell signals, and volume percentage labels filtered by buy/sell conditions. It is a comprehensive tool for traders who want to analyze price trends, identify key levels, and make informed decisions based on volume and EMA crossovers.
Key Features of the Indicator
EMA 15 (Purple Dashed Line):
A 15-period Exponential Moving Average (EMA) is plotted on the chart as a dashed purple line.
This EMA helps traders identify short-term trends and potential entry/exit points.
Hidden EMA 21 and EMA 34:
The 21-period and 34-period EMAs are calculated but not displayed on the chart.
These EMAs are used to generate buy and sell signals based on crossovers.
Buy/Sell Signals:
Buy Signal: Occurs when the EMA 21 crosses above the EMA 34. A green "BUY" label is displayed below the candle.
Sell Signal: Occurs when the EMA 21 crosses below the EMA 34. A red "SELL" label is displayed above the candle.
These signals help traders identify potential trend reversals or continuations.
Support and Resistance Levels:
Support: The lowest price level over the last lookback_period candles, plotted as a green dashed horizontal line.
Resistance: The highest price level over the last lookback_period candles, plotted as a red dashed horizontal line.
These levels help traders identify key price zones for potential breakouts or reversals.
Volume Percentage Labels (Filtered by Buy/Sell Signals):
The volume percentage is calculated relative to the average volume over the last volume_lookback candles.
Buy Volume Label: When a buy signal occurs, a green label is displayed above the candle with the text "Buy Vol: X.XX%", where X.XX is the volume percentage.
Sell Volume Label: When a sell signal occurs, a red label is displayed below the candle with the text "Sell Vol: X.XX%", where X.XX is the volume percentage.
These labels help traders assess the strength of the buy/sell signals based on volume.
Alerts:
Alerts are triggered when buy or sell signals occur, notifying traders of potential trading opportunities.
