Price Action Dynamics Oscillator (PADO)1 minute ago
Price Action Dynamics Oscillator (PADO)
Indicator Overview and Technical Deep Dive
Concept and Philosophy
The Price Action Dynamics Oscillator (PADO) is a sophisticated technical analysis tool designed to provide multi-dimensional insights into market behavior by decomposing price action into manipulation and distribution metrics. The indicator goes beyond traditional momentum or trend indicators by introducing a nuanced approach to understanding market microstructure.
Key Architectural Components
1. Timeframe and Depth Selection
Pivot Depth Options:
Short Term (Length: 12 periods)
Intermediate Term (Length: 20 periods)
Long Term (Length: 100 periods)
This flexible configuration allows traders to adapt the indicator's sensitivity to different market conditions and trading styles.
2. Core Calculation Methodology
Manipulation Metrics
Calculates manipulation differently for green (bullish) and red (bearish) candles
Normalized against Average True Range (ATR) for consistent comparison across different volatility environments
Green Candle Manipulation: (Open - Low) / ATR
Red Candle Manipulation: (High - Open) / ATR
Distribution Metrics
Measures the directional strength and potential momentum shift
Green Candle Distribution: (Close - Open)
Red Candle Distribution: (Open - Close)
3. Normalization and Smoothing
Uses Simple Moving Average (SMA) for smoothing
Dynamic length calculation based on price range distance
Ensures minimum SMA length of 2 to prevent calculation errors
Unique Features
Visualization Toggles
Traders can selectively display:
Manipulation data
Distribution data
Long-term reference lines
Valuation metrics
Strategy signals
Valuation Comparative Analysis
Compares current manipulation and distribution metrics to 1000-bar long-term averages
Color-coded visualization for quick interpretation
Blue: Manipulation above average
Purple: Manipulation below average
Orange: Distribution above average
Yellow: Distribution below average
Strategy Deployment
Generates a composite strategy signal by comparing manipulation and distribution valuations
Uses Exponential Moving Average (EMA) for smoother signal generation
Incorporates volatility bands for context-aware signal interpretation
Quadrant Analysis
Classifies market state into four quadrants based on manipulation and distribution valuations:
Q1: Low Manipulation, High Distribution
Q2: High Manipulation, High Distribution
Q3: Low Manipulation, Low Distribution
Q4: High Manipulation, Low Distribution
Each quadrant is color-coded to provide visual market state representation.
Warning Signals
Manipulation Warning: When strategy crosses below low volatility band
Distribution Warning: When strategy crosses above high volatility band
Visual Indicators
Bar coloration based on strategy momentum
Multiple color states representing different market dynamics
Recommended Use Cases
Intraday and swing trading
Multi-timeframe market analysis
Volatility and momentum assessment
Trend reversal and continuation identification
Potential Limitations
Complexity might require significant trader education
Performance can vary across different market conditions
Requires careful parameter optimization
Recommended Settings
Best used on liquid markets with clear price action
Ideal for:
Forex
Futures
Large-cap stocks
Cryptocurrency pairs
Customization and Optimization
Traders should:
Backtest across multiple assets
Adjust timeframe settings
Calibrate visualization toggles
Use in conjunction with other technical indicators
Licensing
Mozilla Public License 2.0
Open-source and modification-friendly
Conclusion
The PADO represents an advanced approach to market analysis, blending traditional technical analysis with innovative metrics for deeper market understanding.
PADO Quadrant Color Analysis: Deep Dive
Quadrant Color Scheme Breakdown
Quadrant 1: Lime Green Background (RGB: 0, 255, 21, 90)
Condition: val_manip < 1 AND val_distr > 1
Market Interpretation:
Low Manipulation Pressure
High Distribution Activity
Potential Scenario:
Smart money might be gradually distributing positions
Trading Implications:
Caution for current trend followers
Potential preparation for trend change
Increased probability of consolidation or reversal
Quadrant 2: Bright Blue Background (RGB: 0, 191, 255, 90)
Condition: val_manip > 1 AND val_distr > 1
Market Interpretation:
High Manipulation Pressure
High Distribution Activity
Potential Scenario:
Strong institutional involvement
Potential market transition phase
Significant volume and momentum
Trading Implications:
High volatility expected
Increased market uncertainty
Potential for sharp price movements
Requires careful risk management
Quadrant 3: Light Gray Background (RGB: 252, 252, 252, 90)
Condition: val_manip < 1 AND val_distr < 1
Market Interpretation:
Low Manipulation Pressure
Low Distribution Activity
Potential Scenario:
Market consolidation
Reduced institutional activity
Potential low-volatility period
Trading Implications:
Range-bound market
Reduced trading opportunities
Potential setup for future breakout
Ideal for mean reversion strategies
Quadrant 4: Light Yellow Background (Hex: #f6ff0019)
Condition: val_manip > 1 AND val_distr < 1
Market Interpretation:
High Manipulation Pressure
Low Distribution Activity
Potential Scenario:
Accumulation of positions
Trading Implications:
Increased probability of directional move soon
Color Psychology and Technical Significance
Color Selection Rationale
Lime Green (Q1): Represents potential growth and transition
Bright Blue (Q2): Signifies high energy and institutional activity
Light Gray (Q3): Indicates neutrality and consolidation
Transparent Green (Q4): Suggests emerging trend potential
Advanced Interpretation Guidelines
Color Transition Analysis
Observe how the quadrant colors change
Rapid color shifts might indicate:
Market regime changes
Shifts in institutional sentiment
Potential trend acceleration or reversal
Technical Implementation Notes
Calculation Snippet
pinescriptCopyq1 = (val_manip < 1) and (val_distr > 1)
q2 = (val_manip > 1) and (val_distr > 1)
q3 = (val_manip < 1) and (val_distr < 1)
q4 = (val_manip > 1) and (val_distr < 1)
bgcolor(q1 ? color.rgb(0, 255, 21, 90):
q2 ? color.rgb(0, 191, 255, 90):
q3 ? color.rgb(252, 252, 252, 90):
q4 ? #f6ff0019:na)
Alpha Channel (Transparency)
90 and 0x19 values ensure background color doesn't overwhelm chart
Allows underlying price action to remain visible
Subtle visual cue without significant chart obstruction
Practical Trading Recommendations
Never Trade Solely on Quadrant Colors
Use as a complementary analysis tool
Combine with other technical and fundamental indicators
Timeframe Considerations
Validate quadrant signals across multiple timeframes
Longer timeframes provide more reliable signals
Risk Management
Set appropriate stop-loss levels
Use position sizing strategies
Be prepared for false signals
Recommended Workflow
Identify current quadrant
Assess overall market context
Confirm with other indicators
Execute with proper risk management
在腳本中搜尋"Exponential Moving Average"
Pi Cycle Bitcoin Top and Bottom (Daily)Pi Cycle Bitcoin Top and Bottom (Daily)
This indicator combines the renowned Pi Cycle Top and Pi Cycle Bottom indicators into one comprehensive tool designed to identify Bitcoin's market cycle tops and bottoms with precision.
Pi Cycle Top
The Pi Cycle Top indicator uses the 111-day moving average (111DMA) and a multiple of the 350-day moving average (350DMA x 2). Historically, this indicator has identified Bitcoin’s price cycle peaks with an accuracy of up to 3 days.
📈 When the 111DMA crosses above the 350DMA x 2, it signals a market cycle top.
Pi Cycle Bottom
The Pi Cycle Bottom indicator utilizes the 150-day exponential moving average (150EMA) and a multiple of the 471-day simple moving average (471SMA x 0.745). Over past cycles, this combination has effectively pinpointed Bitcoin’s market bottoms with the same level of accuracy.
📉 When the 150EMA crosses below the 471SMA x 0.745, it signals a market cycle bottom.
Parabola
As an additional feature, the indicator identifies moments when the 150EMA crosses back above the 471SMA x 0.745, suggesting a potential parabolic price movement.
Features
Precision: Both indicators have historically aligned with major market turning points.
Customizable settings: Adjust the short and long moving averages to fit your analysis needs.
Alerts: Real-time alerts can be enabled for identifying market tops and bottoms.
Clear visualization: Optional moving average lines and signal markers make it easy to track market trends.
Full credits to Philip Swift, PositiveCrypto, Tondy, BilzerianCandle.
RSI & Volume Impact Analyzer Ver.1.00Description:
The RSI VOL Score indicator combines the Relative Strength Index (RSI) and volume data through a mathematical calculation to assist traders in identifying and confirming potential trend reversals and continuations. By leveraging both momentum (RSI) and volume data, this indicator provides a more comprehensive view of market strength compared to using RSI or volume alone.
How It Works:
This indicator calculates a score by comparing the RSI against its moving average, adjusted by the volume data. The resulting score quantifies market momentum and strength. When the score crosses its signal line, it may indicate key moments where the market shifts between bullish and bearish trends, potentially helping traders spot these changes earlier.
Calculation Methods:
The RSI VOL Score allows users to select between several calculation methods to suit their strategy:
SMA (Simple Moving Average): Provides a balanced smoothing approach.
EMA (Exponential Moving Average): Reacts more quickly to recent price changes, offering faster signals.
VWMA (Volume Weighted Moving Average): Emphasizes high-volume periods, focusing on stronger market moves.
WMA (Weighted Moving Average): Applies greater weight to recent data for a more responsive signal.
What the Indicator Plots:
Score Line: Represents a combined metric based on RSI and volume, helping traders gauge the overall strength of the trend.
Signal Line: A smoothed version of the score that helps traders identify potential trend changes. Bullish signals occur when the score crosses above the signal line, while bearish signals occur when the score drops below.
Key Features:
Trend Identification: The score and signal line crossovers can help confirm emerging bullish or bearish trends, allowing traders to act on upward or downward momentum.
Customizable Settings: Traders can adjust the lengths of the RSI and signal line and choose between different moving averages (SMA, EMA, VWMA, WMA) to tailor the indicator to their trading style.
Timeframe-Specific: The indicator works within the selected timeframe, ensuring accurate trend analysis based on the current market context.
Practical Use Cases:
Trending Markets: In trending markets, this indicator helps confirm bullish or bearish signals by validating price moves with volume. Traders can use the crossover of the score and signal line as a guide for entering or exiting trades based on trend strength.
Ranging Markets: In ranging markets, the indicator helps filter out false signals by confirming if price movements are backed by volume, making it a useful tool for traders looking to avoid entering during weak or uncertain market conditions.
Interpreting the Score and Signal Lines:
Bullish Signal: A bullish signal occurs when the score crosses above the signal line, indicating a potential upward trend in momentum and price.
Bearish Signal: A bearish signal is generated when the score crosses below the signal line, suggesting a potential downward trend or weakening market momentum.
By mathematically combining RSI and volume data into a single trend score, the RSI VOL Score indicator provides traders with a powerful tool for identifying trend shifts early and making more confident trading decisions.
Important Note:
The signals generated by this indicator should be interpreted in conjunction with other analysis tools. It is always advisable to confirm signals before making any trading decisions.
Disclaimer:
This indicator is designed to assist traders in their decision-making process and does not provide financial advice. The creators of this tool are not responsible for any financial losses or trading decisions made based on its signals. Trading involves significant risk, and users should seek professional advice or conduct their own research before making any trading decisions.
Zero-Lag MA Trend Levels [ChartPrime] The Zero-Lag MA Trend Levels indicator combines a Zero-Lag Moving Average (ZLMA) with a standard Exponential Moving Average (EMA) to provide a dynamic view of the market trend. This indicator uses a color-changing cloud to represent shifts in trend momentum and plots key levels when trend reversals are detected. The addition of trend level boxes helps identify significant price zones where market shifts occur, with retest signals aiding in spotting potential continuation or reversal points.
⯁ KEY FEATURES & HOW TO USE
⯌ Zero-Lag Moving Average (ZLMA) with EMA Cloud :
The indicator employs a Zero-Lag Moving Average (ZLMA) alongside a standard EMA.
series float emaValue = ta.ema(close, length) // EMA of the closing price
series float correction = close + (close - emaValue) // Correction factor for zero-lag calculation
series float zlma = ta.ema(correction, length) // Zero-Lag Moving Average (ZLMA)
The cloud between these averages changes color depending on the trend direction. During a downtrend, if the ZLMA begins to increase, the cloud partially turns green, signaling potential strength. Conversely, during an uptrend, if the ZLMA decreases, the cloud partially turns to the downtrend color (blue by default), indicating potential weakness.
Use : Traders can monitor the cloud's color shifts for early signs of changing momentum. A fully colored cloud aligning with the current trend indicates a strong directional move, while mixed colors suggest a potential trend change.
⯌ Trend Shift and Level Boxes :
Each time a crossover between the EMA and the ZLMA occurs, indicating a trend shift, the indicator plots a box around the price level where the shift occurred. This box remains on the chart to mark the price zone of the trend change.
Use : The boxes provide clear visual markers of where market sentiment shifted. These levels can act as support and resistance zones. Traders can use these boxes to identify potential entry or exit points when the market retests these key levels.
⯌ Retest Detection with Labels :
If the price action crosses a previously plotted trend level box, the indicator marks this event with triangle labels. An upward triangle (▲) appears when the price retests the top of a box during a bullish crossover, and a downward triangle (▼) appears when the price retests the bottom of a box during a bearish crossunder.
Use : These labels help traders identify potential continuation or reversal points at critical price levels, offering additional confirmation for trading decisions.
⯌ Dynamic Color-Coding :
The color of the ZLMA and the EMA is adjusted according to their current trend direction, with the ZLMA adopting green for upward trends and blue for downward trends. This visual representation makes it easier to quickly gauge the market's momentum at a glance.
Use : Traders can use the color-coding to quickly assess the strength and direction of the current trend, allowing for more informed decision-making.
⯁ USER INPUTS
Length : Sets the period for both the ZLMA and EMA calculations.
Trend Levels : Toggle to display the trend level boxes on the chart.
Colors (+ / -) : Define the colors for bullish and bearish trends.
⯁ CONCLUSION
The Zero-Lag MA Trend Levels - ChartPrime indicator offers a nuanced approach to trend detection by combining the ZLMA with a traditional EMA. Its dynamic cloud color changes, trend level boxes, and retest labels make it a versatile tool for traders seeking to identify trend shifts and key price zones effectively. By incorporating elements of support and resistance along with trend momentum, this indicator provides a comprehensive view of market dynamics for both trend-following and counter-trend trading strategies.
Uptrick: Momentum-Volatility Composite Signal### Title: Uptrick: Momentum-Volatility Composite Signal
### Overview
The "Uptrick: Momentum-Volatility Composite Signal" is an innovative trading tool designed to offer traders a sophisticated synthesis of momentum, volatility, volume flow, and trend detection into a single comprehensive indicator. This tool stands out by providing an integrated view of market dynamics, which is critical for identifying potential trading opportunities with greater precision and confidence. Its unique approach differentiates it from traditional indicators available on the TradingView platform, making it a valuable asset for traders aiming to enhance their market analysis.
### Unique Features
This indicator integrates multiple crucial elements of market behavior:
- Momentum Analysis : Utilizes Rate of Change (ROC) metrics to assess the speed and strength of market movements.
- Volatility Tracking : Incorporates Average True Range (ATR) metrics to measure market volatility, aiding in risk assessment.
- Volume Flow Analysis : Analyzes shifts in volume to detect buying or selling pressure, adding depth to market understanding.
- Trend Detection : Uses the difference between short-term and long-term Exponential Moving Averages (EMA) to detect market trends, providing insights into potential reversals or confirmations.
Customization and Inputs
The Uptrick indicator offers a variety of user-defined settings tailored to fit different trading styles and strategies, enhancing its adaptability across various market conditions:
Rate of Change Length (rocLength) : This setting defines the period over which momentum is calculated. Shorter periods may be preferred by day traders who need to respond quickly to market changes, while longer periods could be better suited for position traders looking at more extended trends.
ATR Length (atrLength) : Adjusts the timeframe for assessing volatility. A shorter ATR length can help day traders manage the quick shifts in market volatility, whereas longer lengths might be more applicable for swing or position traders who deal with longer-term market movements.
Volume Flow Length (volumeFlowLength): Determines the analysis period for volume flow to identify buying or selling pressure. Day traders might opt for shorter periods to catch rapid volume changes, while longer periods could serve swing traders to understand the accumulation or distribution phases better.
Short EMA Length (shortEmaLength): Specifies the period for the short-term EMA, crucial for trend detection. Shorter lengths can aid day traders in spotting immediate trend shifts, whereas longer lengths might help swing traders in identifying more sustainable trend changes.
Long EMA Length (longEmaLength): Sets the period for the long-term EMA, which is useful for observing longer-term market trends. This setting is particularly valuable for position traders who need to align with the broader market direction.
Composite Signal Moving Average Length (maLength): This parameter sets the smoothing period for the composite signal's moving average, helping to reduce noise in the signal output. A shorter moving average length can be beneficial for day traders reacting to market conditions swiftly, while a longer length might help swing and position traders in smoothing out less significant fluctuations to focus on significant trends.
These customization options ensure that traders can fine-tune the Uptrick indicator to their specific trading needs, whether they are scanning for quick opportunities or analyzing more prolonged market trends.
### Functionality Details
The indicator operates through a sophisticated algorithm that integrates multiple market dimensions:
1. Momentum and Volatility Calculation : Combines ROC and ATR to gauge the market’s momentum and stability.
2. Volume and Trend Analysis : Integrates volume data with EMAs to provide a comprehensive view of current market trends and potential shifts.
3. Signal Composite : Each component is normalized and combined into a composite signal, offering traders a nuanced perspective on when to enter or exit trades.
The indicator performs its calculations as follows:
Momentum and Volatility Calculation:
roc = ta.roc(close, rocLength)
atr = ta.atr(atrLength)
Volume and Trend Analysis:
volumeFlow = ta.cum(volume) - ta.ema(ta.cum(volume), volumeFlowLength)
emaShort = ta.ema(close, shortEmaLength)
emaLong = ta.ema(close, longEmaLength)
emaDifference = emaShort - emaLong
Composite Signal Calculation:
Normalizes each component (ROC, ATR, volume flow, EMA difference) and combines them into a composite signal:
rocNorm = (roc - ta.sma(roc, rocLength)) / ta.stdev(roc, rocLength)
atrNorm = (atr - ta.sma(atr, atrLength)) / ta.stdev(atr, atrLength)
volumeFlowNorm = (volumeFlow - ta.sma(volumeFlow, volumeFlowLength)) / ta.stdev(volumeFlow, volumeFlowLength)
emaDiffNorm = (emaDifference - ta.sma(emaDifference, longEmaLength)) / ta.stdev(emaDifference, longEmaLength)
compositeSignal = (rocNorm + atrNorm + volumeFlowNorm + emaDiffNorm) / 4
### Originality
The originality of the Uptrick indicator lies in its ability to merge diverse market metrics into a unified signal. This multi-faceted approach goes beyond traditional indicators by offering a deeper, more holistic analysis of market conditions, providing traders with insights that are not only based on price movements but also on underlying market dynamics.
### Practical Application
The Uptrick indicator excels in environments where understanding the interplay between volume, momentum, and volatility is crucial. It is especially useful for:
- Day Traders : Can leverage real-time data to make quick decisions based on sudden market changes.
- Swing Traders : Benefit from understanding medium-term trends to optimize entry and exit points.
- Position Traders : Utilize long-term market trend data to align with overall market movements.
### Best Practices
To maximize the effectiveness of the Uptrick indicator, consider the following:
- Combine with Other Indicators : Use alongside other technical tools like RSI or MACD for additional validation.
- Adapt Settings to Market Conditions : Adjust the indicator settings based on the asset and market volatility to improve signal accuracy.
- Risk Management : Implement robust risk management strategies, including setting stop-loss orders based on the volatility measured by the ATR.
### Practical Examples and Demonstrations
- Example for Day Trading : In a volatile market, a trader notices a sharp increase in the momentum score coinciding with a surge in volume but stable volatility, signaling a potential bullish breakout.
- Example for Swing Trading : On a 4-hour chart, the indicator shows a gradual alignment of decreasing volatility and increasing buying volume, suggesting a strengthening upward trend suitable for a long position.
### Alerts and Their Uses
- Alert Configurations : Set alerts for when the composite score crosses predefined thresholds to capture potential buy or sell events.
- Strategic Application : Use alerts to stay informed of significant market moves without the need to continuously monitor the markets, enabling timely and informed trading decisions.
Technical Notes
Efficiency and Compatibility: The indicator is designed for efficiency, running smoothly across different trading platforms including TradingView, and can be easily integrated with existing trading setups. It leverages advanced mathematical models for normalizing and smoothing data, ensuring consistent and reliable signal quality across different market conditions.
Limitations : The effectiveness of the Uptrick indicator can vary significantly across different market conditions and asset classes. It is designed to perform best in liquid markets where data on volume, volatility, and price trends are readily available and reliable. Traders should be aware that in low-liquidity or highly volatile markets, the signals might be less reliable and require additional confirmation.
Usage Recommendations : While the Uptrick indicator is a powerful tool, it is recommended to use it in conjunction with other analysis methods to confirm signals. Traders should also continuously monitor the performance and adjust settings as needed to align with their specific trading strategies and market conditions.
### Conclusion
The "Uptrick: Momentum-Volatility Composite Signal" is a revolutionary tool that offers traders an advanced methodology for analyzing market dynamics. By combining momentum, volatility, volume, and trend detection into a single, cohesive indicator, it provides a powerful, actionable insight into market movements, making it an indispensable tool for traders aiming to optimize their trading strategies.
Liquidity weighted SupertrendOverview
The Liquidity Weighted Supertrend Indicator (LWST) is an advanced iteration of the traditional Supertrend indicator, meticulously crafted to improve trend detection by incorporating liquidity into its calculations. By weighting price movements according to trading volume, the LWST becomes more responsive to significant market activities, offering traders a more accurate depiction of market trends.
Indicator Description
The Liquidity Weighted Supertrend Indicator is a versatile and adaptive tool designed to assist traders in recognizing trends and potential reversal points within the market. This indicator features two operational modes: Aggressive and Smoothed, allowing traders to tailor trend detection to their specific trading style and market conditions.
Key Features
Two Supertrend Modes:
Aggressive Mode: This mode offers more responsive signals, ideal for short-term trading. It utilizes an Exponential Moving Average (EMA) to smooth the price data, resulting in quicker reactions to market changes.
Smoothed Mode: This mode provides more stable signals, suitable for longer-term trading, by employing a Simple Moving Average (SMA). Note that when "Smoothed" mode is selected, the "Fast MA length" input is not utilized, focusing instead on producing smoother trend lines.
LWMA Calculation:
The Liquidity Weighted Moving Average (LWMA) is a distinctive feature of the LWST, blending volume and price action to filter out market noise and pinpoint significant price movements. This calculation begins with the liquidity factor, determined by multiplying volume with the price change, which is then smoothed using an EMA for accuracy.
Customizable Parameters:
Factor: Adjusts the Supertrend line's sensitivity to price movements.
Supertrend Length: Defines the lookback period for the Average True Range (ATR) calculation, which affects the width of the Supertrend channel.
Fast and Slow MA Lengths: Allows customization of the fast and slow moving averages used in the LWMA calculation, offering further control over the indicator's responsiveness.
How the Indicator Works
LWMA Smoothing:
The LWST calculates liquidity by multiplying volume with the absolute difference between the close and open prices. This liquidity value is smoothed using an EMA and compared to its standard deviation, identifying significant price movements. Depending on the selected mode, the price data (hl2) is smoothed either with an EMA (in Aggressive Mode) or an SMA (in Smoothed Mode). It’s important to note that when Smoothed mode is active, the "Fast MA length" input does not affect the output.
Visual Signals:
The Supertrend line is visually represented on the chart, with different colors indicating bullish (lime) and bearish (red) trends.
Buy and sell signals are clearly marked with arrows: green triangles indicate potential buying opportunities (when the price crosses above the Supertrend line), and red triangles suggest selling opportunities (when the price crosses below the Supertrend line).
Additional arrows may appear, signaling potential trend reversals, providing further confirmation for traders.
How to Use the Indicator
Configuring the Indicator:
Supertrend Type: Choose between Aggressive and Smoothed modes depending on your trading strategy and the current market conditions. Aggressive mode is better suited for shorter timeframes, while Smoothed mode provides more consistent signals for longer-term analysis.
Factor and Length Settings: Customize the Factor, Supertrend Length, and Moving Average lengths to fine-tune the sensitivity and responsiveness of the Supertrend line, adapting the indicator to various market environments.
Interpreting the Signals:
Trend Identification: The Supertrend line offers a clear visualization of the current market trend. A green line indicates a bullish trend, suggesting upward price movement, while a red line indicates a bearish trend, signaling potential downward price movement.
Entry and Exit Points: The arrows plotted by the LWST provide straightforward entry and exit signals. Green arrows signal potential buy opportunities, indicating that the price may continue to rise, while red arrows signal potential sell opportunities, suggesting that the price may decline. These visual cues help traders make informed decisions based on the current market trend.
DataDoodles ATR RangeThe "DataDoodles ATR Range" indicator provides a comprehensive visual representation of the Average True Range (ATR) levels based on the previous bar's close price . It includes both the raw ATR and an Exponential Moving Average (EMA) of the ATR to offer a smoother view of the range volatility. This indicator is ideal for traders who want to quickly assess potential price movements relative to recent volatility.
Key Features:
ATR Levels Above and Below Close: The indicator calculates and displays three levels of ATR-based ranges above and below the previous close price. These levels are visualized on the chart using distinct colors:
- 1ATR Above/Below
- 2ATR Above/Below
- 3ATR Above/Below
EMA of ATR
Includes the EMA of ATR to provide a smoother trend of the ATR values, helping traders identify long-term volatility trends.
Color-Coded Ranges: The plotted ranges are color-coded for easy identification, with warm gradient tones applied to the corresponding data table for quick reference.
Customizable Table: A data table is displayed at the bottom right corner of the chart, providing real-time values for ATR, EMA ATR, and the various ATR ranges.
Usage
This indicator is useful for traders who rely on volatility analysis to set stop losses, take profit levels, or simply understand the current market conditions. By visualizing ATR ranges directly on the chart, traders can better anticipate potential price movements and adjust their strategies accordingly.
Customization
ATR Length: The default ATR length is set to 14 but can be customized to fit your trading strategy.
Table Positioning: The data table is placed in the bottom right corner by default but can be moved as needed.
How to Use
Add the "DataDoodles ATR Range" indicator to your chart.
Observe the plotted lines for potential support and resistance levels based on recent volatility.
Use the data table for quick reference to ATR values and range levels.
Disclaimer: This indicator is a tool for analysis and should be used in conjunction with other indicators and analysis methods. Always practice proper risk management and consider market conditions before making trading decisions.
Improved Volume Based Indicator# Improved Volume Based Indicator
## Overview
The Improved Volume Based Indicator is a technical analysis tool designed to identify potential trading opportunities based on volume patterns, price action, and trend direction. This indicator combines volume analysis with moving averages and the Average True Range (ATR) to generate buy and sell signals.
## Key Components
1. Volume Analysis
- Tracks consecutive volume direction (up or down) for 3 periods
- Calculates volume ratio compared to a short-term moving average
2. Trend Direction
- Uses a 200-period Exponential Moving Average (EMA) to determine overall trend
3. Volatility Measurement
- Incorporates the Average True Range (ATR) for stop-loss and take-profit calculations
## Signal Generation
### Buy Signal Criteria
1. Three consecutive periods of up volume (close > open)
2. Volume ratio > 1.5 (current volume is 50% higher than the short-term average)
3. Current price is above the 200 EMA
### Sell Signal Criteria
1. Three consecutive periods of down volume (close < open)
2. Volume ratio > 1.5 (current volume is 50% higher than the short-term average)
3. Current price is below the 200 EMA
## Risk Management
The indicator calculates stop-loss and take-profit levels based on the ATR:
- Stop Loss: ATR * 1.5 (default)
- Take Profit: ATR * 2.5 (default)
These levels are adjustable through input parameters.
## Usage
1. Add the indicator to your chart
2. Adjust input parameters as needed:
- Volume Period (2-5)
- ATR Period (default 14)
- ATR Multipliers for Stop Loss and Take Profit
- EMA Period (default 200)
3. Monitor for buy and sell signals
4. Use the provided stop-loss and take-profit levels for risk management
## Interpretation
- Buy signals suggest potential upward price movement
- Sell signals suggest potential downward price movement
- Always consider other factors and perform additional analysis before making trading decisions
## Limitations
- This indicator may generate false signals in choppy or ranging markets
- It's best used in conjunction with other technical analysis tools and fundamental analysis
- Past performance does not guarantee future results
Remember to thoroughly test this indicator on historical data and in various market conditions before using it in live trading.
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# 改進的基於交易量的指標
＃＃ 概述
改進的基於成交量的指標是一種技術分析工具，旨在根據成交量模式、價格行為和趨勢方向識別潛在的交易機會。此指標將成交量分析與移動平均線和平均真實波動幅度 (ATR) 結合起來，以產生買入和賣出訊號。
＃＃ 關鍵部件
1. 成交量分析
- 追蹤 3 個週期的連續成交量方向（向上或向下）
- 計算與短期移動平均線相比的成交量比率
2. 趨勢方向
- 使用 200 週期指數移動平均線 (EMA) 來確定整體趨勢
3. 波動率測量
- 納入平均真實波動範圍 (ATR) 以進行停損和停盈計算
## 訊號生成
### 購買訊號標準
1. 連續三個週期的成交量上漲（收盤>開盤）
2.成交量比率>1.5（目前成交量較短期平均高50%）
3. 當前價格高於200 EMA
### 賣出訊號標準
1.連續三個週期的成交量下跌（收盤<開盤）
2.成交量比率>1.5（目前成交量較短期平均高50%）
3. 目前價格低於200 EMA
＃＃ 風險管理
此指標根據 ATR 計算停損和止盈水準：
- 停損：ATR * 1.5（預設）
- 止盈：ATR * 2.5（預設）
這些等級可透過輸入參數進行調整。
＃＃ 用法
1. 將指標加入您的圖表中
2. 根據需要調整輸入參數：
- 卷期 (2-5)
- ATR 週期（預設 14）
- 用於停損和止盈的 ATR 乘數
- EMA 週期（預設 200）
3. 監控買賣訊號
4. 使用提供的停損和停利水準進行風險管理
＃＃ 解釋
- 買進訊號表示價格可能上漲
- 賣出訊號表示價格可能下跌
- 在做出交易決策之前始終考慮其他因素並進行額外分析
## 限制
- 此指標可能會在波動或波動的市場中產生錯誤訊號
- 最好與其他技術分析工具和基本面分析結合使用
- 過去的表現並不能保證未來的結果
請記住，在實際交易中使用該指標之前，請根據歷史數據和各種市場條件徹底測試該指標。
Strategy SEMA SDI WebhookPurpose of the Code:
The strategy utilizes Exponential Moving Averages (EMA) and Smoothed Directional Indicators (SDI) to generate buy and sell signals. It includes features like leverage, take profit, stop loss, and trailing stops. The strategy is intended for backtesting and automating trades based on the specified indicators and conditions.
Key Components and Functionalities:
1.Strategy Settings:
Overlay: The strategy will overlay on the price chart.
Slippage: Set to 1.
Commission Value: Set to 0.035.
Default Quantity Type: Percent of equity.
Default Quantity Value: 50% of equity.
Initial Capital: Set to 1000 units.
Calculation on Order Fills: Enabled.
Process Orders on Close: Enabled.
2.Date and Time Filters:
Inputs for enabling/disabling start and end dates.
Filters to execute strategy only within specified date range.
3.Leverage and Quantity:
Leverage: Adjustable leverage input (default 3).
USD Percentage: Adjustable percentage of equity to use for trades (default 50%).
Initial Capital: Calculated based on leverage and percentage of equity.
4.Take Profit, Stop Loss, and Trailing Stop:
Inputs for enabling/disabling take profit, stop loss, and trailing stop.
Adjustable parameters for take profit percentage (default 25%), stop loss percentage (default 4.8%), and trailing stop percentage (default 1.9%).
Calculations for take profit, stop loss, trailing price, and maximum profit tracking.
5.EMA Calculations:
Fast and slow EMAs.
Smoothed versions of the fast and slow EMAs.
6.SDI Calculations:
Directional movement calculation for positive and negative directional indicators.
Difference between the positive and negative directional indicators, smoothed.
7.Buy/Sell Conditions:
Long (Buy) Condition: Positive DI is greater than negative DI, and fast EMA is greater than slow EMA.
Short (Sell) Condition: Negative DI is greater than positive DI, and fast EMA is less than slow EMA.
8.Strategy Execution:
If buy conditions are met, close any short positions and enter a long position.
If sell conditions are met, close any long positions and enter a short position.
Exit conditions for long and short positions based on take profit, stop loss, and trailing stop levels.
Close all positions if outside the specified date range.
Usage:
This strategy is used to automate trading based on the specified conditions involving EMAs and SDI. It allows backtesting to evaluate performance based on historical data. The strategy includes risk management through take profit, stop loss, and trailing stops to protect gains and limit losses. Traders can customize the parameters to fit their specific trading preferences and risk tolerance. Differently, it can perform leverage analysis and use it as a template.
By using this strategy, traders can systematically execute trades based on technical indicators, helping to remove emotional bias and improve consistency in trading decisions.
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
RSI Analysis with Statistical Summary Scientific Analysis of the Script "RSI Analysis with Statistical Summary"
Introduction
I observed that there are outliers in the price movement liquidity, and I wanted to understand the RSI value at those points and whether there are any notable patterns. I aimed to analyze this statistically, and this script is the result.
Explanation of Key Terms
1. Outliers in Price Movement Liquidity: An outlier is a data point that significantly deviates from other values. In this context, an outlier refers to an unusually high or low liquidity of price movement, which is the ratio of trading volume to the price difference between the open and close prices. These outliers can signal important market changes or unusual trading activities.
2. RSI (Relative Strength Index): The RSI is a technical indicator that measures the speed and change of price movements. It ranges from 0 to 100 and helps identify overbought or oversold conditions of a trading instrument. An RSI value above 70 indicates an overbought condition, while a value below 30 suggests an oversold condition.
3. Mean: The mean is a measure of the average of a dataset. It is calculated by dividing the sum of all values by the number of values. In this script, the mean of the RSI values is calculated to provide a central tendency of the RSI distribution.
4. Standard Deviation (stdev): The standard deviation is a measure of the dispersion or variation of a dataset. It shows how much the values deviate from the mean. A high standard deviation indicates that the values are widely spread, while a low standard deviation indicates that the values are close to the mean.
5. 68% Confidence Interval: A confidence interval indicates the range within which a certain percentage of values of a dataset lies. The 68% confidence interval corresponds to a range of plus/minus one standard deviation around the mean. It indicates that about 68% of the data points lie within this range, providing insight into the distribution of values.
Overview
This Pine Script™, written in Pine version 5, is designed to analyze the Relative Strength Index (RSI) of a stock or other trading instrument and create statistical summaries of the distribution of RSI values. The script identifies outliers in price movement liquidity and uses this information to calculate the frequency of RSI values. At the end, it displays a statistical summary in the form of a table.
Structure and Functionality of the Script
1. Input Parameters
- `rsi_len`: An integer input parameter that defines the length of the RSI (default: 14).
- `outlierThreshold`: An integer input parameter that defines the length of the outlier threshold (default: 10).
2. Calculating Price Movement Liquidity
- `priceMovementLiquidity`: The volume is divided by the absolute difference between the close and open prices to calculate the liquidity of the price movement.
3. Determining the Boundary for Liquidity and Identifying Outliers
- `liquidityBoundary`: The boundary is calculated using the Exponential Moving Average (EMA) of the price movement liquidity and its standard deviation.
- `outlier`: A boolean value that indicates whether the price movement liquidity exceeds the set boundary.
4. Calculating the RSI
- `rsi`: The RSI is calculated with a period length of 14, using various moving averages (e.g., SMA, EMA) depending on the settings.
5. Storing and Limiting RSI Values
- An array `rsiFrequency` stores the frequency of RSI values from 0 to 100.
- The function `f_limit_rsi` limits the RSI values between 0 and 100.
6. Updating RSI Frequency on Outlier Occurrence
- On an outlier occurrence, the limited and rounded RSI value is updated in the `rsiFrequency` array.
7. Statistical Summary
- Various variables (`mostFrequentRsi`, `leastFrequentRsi`, `maxCount`, `minCount`, `sum`, `sumSq`, `count`, `upper_interval`, `lower_interval`) are initialized to perform statistical analysis.
- At the last bar (`bar_index == last_bar_index`), a loop is run to determine the most and least frequent RSI values and their frequencies. Sum and sum of squares of RSI values are also updated for calculating mean and standard deviation.
- The mean (`mean`) and standard deviation (`stddev`) are calculated. Additionally, a 68% confidence interval is determined.
8. Creating a Table for Result Display
- A table `resultsTable` is created and filled with the results of the statistical analysis. The table includes the most and least frequent RSI values, the standard deviation, and the 68% confidence interval.
9. Graphical Representation
- The script draws horizontal lines and fills to indicate overbought and oversold regions of the RSI.
Interpretation of the Results
The script provides a detailed analysis of RSI values based on specific liquidity outliers. By calculating the most and least frequent RSI values, standard deviation, and confidence interval, it offers a comprehensive statistical summary that can help traders identify patterns and anomalies in the RSI. This can be particularly useful for identifying overbought or oversold conditions of a trading instrument and making informed trading decisions.
Critical Evaluation
1. Robustness of Outlier Identification: The method of identifying outliers is solely based on the liquidity of price movement. It would be interesting to examine whether other methods or additional criteria for outlier identification would lead to similar or improved results.
2. Flexibility of RSI Settings: The ability to select various moving averages and period lengths for the RSI enhances the adaptability of the script, allowing users to tailor it to their specific trading strategies.
3. Visualization of Results: While the tabular representation is useful, additional graphical visualizations, such as histograms of RSI distribution, could further facilitate the interpretation of the results.
In conclusion, this script provides a solid foundation for analyzing RSI values by considering liquidity outliers and enables detailed statistical evaluation that can be beneficial for various trading strategies.
HTF Dynamic EMA Smoothing Indicator [CHE] with Kernel SelectionThe Dynamic EMA Smoothing Indicator with Kernel Selection is a powerful Pine Script indicator for TradingView designed to smooth moving averages and identify market trends more clearly. Here is a detailed description of its functionalities and settings:
Main Functions:
1. Time Period Display:
- Option to show or hide an info box displaying the current time period.
- Customizable info box: Users can adjust the size, position, and colors of the info box to suit their preferences.
2. Timeframe Type Selection:
- Auto Timeframe: Automatically calculates the best timeframe based on the current resolution.
- Multiplier: Allows using an alternate timeframe as a multiple of the current resolution.
- Manual Resolution: Users can manually set a specific timeframe.
3. Colors:
- Custom colors for various graphical elements, including EMA lines and signals.
4. Basic Settings:
- EMA and Signal Periods: Defines the periods for the exponential moving averages (EMA) and signal lines.
- Smoothing Length and Kernel Type: Allows selecting the smoothing length and the type of kernel used for weighting the EMAs.
- ATR Multiplier: Defines the multiplier for the ATR (Average True Range) to identify relevant price ranges.
5. EMA Calculations:
- The indicator calculates a weighted EMA using several methods like Linear, Exponential, Epanechnikov, Triangular, and Cosine kernels.
- Smoothing is achieved by adding and removing values in a float array that stores the EMA values.
6. Plotting EMA and Signal Lines:
- The indicator plots the smoothed EMA and signal lines on the chart. The line colors change according to the trend direction (green for uptrend, red for downtrend).
7. Trading Signals:
- Long Signals: An upward arrow is displayed when the smoothed EMA indicates an uptrend.
- Short Signals: A downward arrow is displayed when the smoothed EMA indicates a downtrend.
- Alert Conditions: Alerts are triggered when long or short signals are detected.
8. ATR Bands:
- The indicator shows upper and lower ATR bands to identify potential support and resistance zones.
9. Time Period Display on Chart:
- A table is used to display the selected time period on the chart when the corresponding option is enabled.
This indicator offers extensive customization and allows traders to conduct complex market analyses using smoothed EMAs and custom timeframes. The integration of various kernels for smoothing makes it a versatile tool adaptable to different trading strategies.
Velocity And Acceleration with Strategy: Traders Magazine◙ OVERVIEW
Hi, Ivestors and Traders... This Indicator, the focus is Scott Cong's article in the Stocks & Commodities September issue, “VAcc: A Momentum Indicator Based On Velocity And Acceleration”. I have also added a trading strategy for you to benefit from this indicator. First of all, let's look at what the indicator offers us and what its logic is. First, let's focus on the logic of the strategy.
◙ CONCEPTS
Here is a new indicator based on some simple physics concepts that is easy to use, responsive and precise. Learn how to calculate and use it.
The field of physics gives us some important principles that are highly applicable to analyzing the markets. In this indicator, I will present a momentum indicator. Scott Cong developed based on the concepts of velocity and acceleration this indicator. Of the many characteristics of price that traders and analysts often study, rate and rate of change are useful ones. In other words, it’s helpful to know: How fast is price moving, and is it speeding up or slowing down? How is price changing from one period to the next? The indicator I’m introducing here is calculated using the current bar (C) and every bar of a lookback period from the current bar. He named the indicator the VAcc since it’s based on the average of velocity line (av) and acceleration line (Acc) over the lookback period. For longer periods, the VAcc behaves the same way as the MACD, only it’s simpler, more responsive, and more precise. Interestingly, for shorter periods, VAcc exhibits characteristics of an oscillator, such as the stochastics oscillator.
◙ CALCULATION
The calculation of VAcc involves the following steps:
1. Relatively weighted average where the nearer price has the largest influence.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. The Velocity Average is smoothed with an exponential moving average. Now it get:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Similarly, accelerations for each bar within the lookback period and scale factor are calculated as:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEGY
In fact, Scott probably preferred to use it in periods 9 and 26 because it was similar to Macd and used the ratio of 0.5. However, I preferred to use the 8 and 21 periods to provide signals closer to the stochastic oscillator in the short term and used the 0.382 ratio. The logic of the strategy is this
Long Strategy → acc(Acceleration Line) > 0.1 and av(Velocity Average Line) > 0.1(Long Factor)
Short strategy → acc(Acceleration Line) < -0.1 and av(Velocity Average Line) < -0.1(Long Factor)
Here, you can change the Short Factor and Long Factor as you wish and produce more meaningful results that are closer to your own strategy.
I hope you benefits...
◙ GENEL BAKIŞ
Merhaba Yatırımcılar ve Yatırımcılar... Bu Gösterge, Scott Cong'un Stocks & Emtia Eylül sayısındaki “VAcc: Hız ve İvmeye Dayalı Bir Momentum Göstergesi” başlıklı makalesine odaklanmaktadır. Bu göstergeden faydalanabilmeniz için bir ticaret stratejisi de ekledim. Öncelikle göstergenin bize neler sunduğuna ve mantığının ne olduğuna bakalım. Öncelikle stratejinin mantığına odaklanalım.
◙ KAVRAMLAR
İşte kullanımı kolay, duyarlı ve kesin bazı basit fizik kavramlarına dayanan yeni bir gösterge. Nasıl hesaplanacağını ve kullanılacağını öğrenin.
Fizik alanı bize piyasaları analiz etmede son derece uygulanabilir bazı önemli ilkeler verir. Bu göstergede bir momentum göstergesi sunacağım. Scott Cong bu göstergeyi hız ve ivme kavramlarına dayanarak geliştirdi. Yatırımcıların ve analistlerin sıklıkla incelediği fiyatın pek çok özelliği arasında değişim oranı ve oranı yararlı olanlardır. Başka bir deyişle şunu bilmek faydalı olacaktır: Fiyat ne kadar hızlı hareket ediyor ve hızlanıyor mu, yavaşlıyor mu? Fiyatlar bir dönemden diğerine nasıl değişiyor? Burada tanıtacağım gösterge, mevcut çubuk (C) ve mevcut çubuktan bir yeniden inceleme döneminin her çubuğu kullanılarak hesaplanır. Göstergeye, yeniden inceleme dönemi boyunca hız çizgisinin (av) ve ivme çizgisinin (Acc) ortalamasına dayandığı için VAcc adını verdi. Daha uzun süreler boyunca VACc, MACD ile aynı şekilde davranır, yalnızca daha basit, daha duyarlı ve daha hassastır. İlginç bir şekilde, daha kısa süreler için VAcc, stokastik osilatör gibi bir osilatörün özelliklerini sergiliyor.
◙ HESAPLAMA
VAcc'nin hesaplanması aşağıdaki adımları içerir:
1. Yakın zamandaki fiyatın en büyük etkiye sahip olduğu göreceli ağırlıklı ortalamayı hesaplatıyoruz.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. Hız Ortalamasına üstel hareketli ortalamayla düzleştirme uygulanır. Şimdi bu şekilde aşağıdaki kod ile bunu şöyle elde ediyoruz:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Benzer şekilde, yeniden inceleme süresi ve ölçek faktörü içindeki her bir çubuk için fiyattaki ivmelenler yada momentum şu şekilde hesaplanır:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEJİ
Aslında Scott muhtemelen Macd'e benzediği ve 0,5 oranını kullandığı için 9. ve 26. periyotlarda kullanmayı tercih etmişti. Ancak kısa vadede stokastik osilatöre daha yakın sinyaller sağlamak için 8 ve 21 periyotlarını kullanmayı tercih ettim ve 0,382 oranını kullandım. Stratejinin mantığı şu
Uzun Strateji → acc(İvme Çizgisi) > 0,1 ve av(Hız Ortalama Çizgisi) > 0,1(Uzun Faktör)
Kısa strateji → acc(İvme Çizgisi) < -0,1 ve av(Hız Ortalama Çizgisi) < -0,1(Uzun Faktör)
Burada Kısa Faktör ve Uzun Faktör' ü dilediğiniz gibi değiştirip, kendi stratejinize daha yakın, daha anlamlı sonuçlar üretebilirsiniz.
umarım faydasını görürsün...
Leading MACDThe Moving Average Convergence Divergence (MACD) indicator is one of the most popular and versatile tools used by traders to identify potential buy and sell signals. It helps traders determine the strength and direction of a trend by comparing different moving averages of a security's price. The traditional MACD uses two exponential moving averages (EMAs), a fast EMA (typically 12 periods) and a slow EMA (typically 26 periods), along with a signal line (typically a 9-period EMA of the MACD line) to generate trading signals.
Our "Custom MACD with Leading Length" script for TradingView enhances the traditional MACD by introducing an additional smoothing factor called the "leading length." This customization aims to reduce noise and provide a potentially earlier indication of trend changes, making it a valuable tool for traders seeking to optimize their trading strategies.
- **Purpose:** This additional smoothing factor is designed to reduce noise and provide a potentially leading signal, enhancing the accuracy of trend identification.
## How It Works
1. **Calculate the MACD Line:**
The MACD line is calculated by subtracting the slow EMA from the fast EMA. This difference represents the convergence or divergence between the two EMAs.
2. **Calculate the Signal Line:**
The signal line is an EMA of the MACD line. This additional smoothing helps to generate clearer buy and sell signals based on crossovers with the MACD line.
3. **Calculate the Histogram:**
The histogram represents the difference between the MACD line and the signal line. It visually indicates the strength and direction of the trend. A positive histogram suggests a bullish trend, while a negative histogram indicates a bearish trend.
4. **Apply Leading Length Smoothing:**
To incorporate the leading length, the script applies a simple moving average (SMA) to both the MACD and signal lines using the leading length parameter. This additional smoothing helps to further reduce noise and potentially provides earlier signals of trend changes.
## Benefits of the Leading MACD
### Reduced Noise
The leading length parameter adds an extra layer of smoothing to the MACD and signal lines, helping to filter out market noise. This can be particularly beneficial in volatile markets, where frequent price fluctuations can generate false signals.
### Potential Early Signals
By smoothing the MACD and signal lines, the leading length can help to provide earlier indications of trend changes. This can give traders a potential edge in entering or exiting trades before the broader market reacts.
### Enhanced Trend Identification
The combination of the traditional MACD with the leading length smoothing can enhance the accuracy of trend identification. Traders can use this tool to confirm the strength and direction of trends, making it easier to make informed trading decisions.
### Versatility
The Custom MACD with Leading Length can be applied to various timeframes and asset classes, including stocks, forex, commodities, and cryptocurrencies. Its adaptability makes it a valuable tool for traders with different strategies and preferences.
## Practical Applications
### Buy Signal
A typical buy signal occurs when the MACD line crosses above the signal line. With the additional smoothing provided by the leading length, traders might receive this signal slightly earlier, allowing them to enter a long position sooner. This can be particularly advantageous in capturing the beginning of a bullish trend.
### Sell Signal
Conversely, a sell signal is generated when the MACD line crosses below the signal line. The leading length smoothing can help to provide this signal earlier, enabling traders to exit a long position or enter a short position before the trend reversal is fully recognized by the market.
### Divergence Analysis
Traders can also use the Custom MACD with Leading Length for divergence analysis. Bullish divergence occurs when the price makes a new low, but the MACD line forms a higher low. This suggests that the downward momentum is weakening, potentially leading to a bullish reversal. Bearish divergence is the opposite, where the price makes a new high, but the MACD line forms a lower high, indicating a potential bearish reversal.
### Confirmation Tool
The Custom MACD with Leading Length can be used in conjunction with other technical indicators to confirm trading signals. For example, traders might use it alongside support and resistance levels, trendlines, or other momentum indicators to validate their trade entries and exits.
## Conclusion
The Custom MACD with Leading Length is a powerful enhancement of the traditional MACD indicator. By introducing an additional smoothing factor, it aims to reduce noise and provide earlier signals of trend changes. This makes it a valuable tool for traders seeking to improve their market analysis and trading strategies.
Whether you are a day trader, swing trader, or long-term investor, the Custom MACD with Leading Length can help you make more informed decisions by offering clearer insights into market trends. Its adaptability to different timeframes and asset classes further enhances its utility, making it a versatile addition to any trader's toolkit.
Experiment with the parameters to find the optimal settings that suit your trading style and preferences. Use the Custom MACD with Leading Length to gain a deeper understanding of market dynamics and enhance your trading performance.
Triple EMA + QQE Trend Following Strategy [TradeDots]The "Triple EMA + QQE Trend Following Strategy" harnesses the power of two sophisticated technical indicators, the Triple Exponential Moving Average (TEMA) and the Qualitative Quantitative Estimation (QQE), to generate precise buy and sell signals. This strategy excels in capturing shifts in trends by identifying short-term price momentum and dynamic overbought or oversold conditions.
HOW IT WORKS
This strategy integrates two pivotal indicators:
Triple Exponential Moving Average (TEMA): TEMA enhances traditional moving averages by reducing lag and smoothing the data more effectively. It achieves this by applying the EMA formula three times onto the price, as follows:
tema(src, length) =>
ema1 = ta.ema(src, length)
ema2 = ta.ema(ema1, length)
ema3 = ta.ema(ema2, length)
tema = 3*ema1 - 3*ema2 + ema3
This computation helps to sharpen the sensitivity to price movements.
Qualitative Quantitative Estimation (QQE): The QQE indicator improves upon the standard RSI by incorporating a smoothing mechanism. It starts with the standard RSI, overlays a 5-period EMA on this RSI, and then enhances the result using a double application of a 27-period EMA. A slow trailing line is then derived by multiplying the result with a factor number. This approach establishes a more refined and less jittery trend-following signal, complementing the TEMA to enhance overall market timing during fluctuating conditions.
APPLICATION
Referenced from insights on "Trading Tact," the strategy implementation follows:
First of all, we utilize two TEMA lines: one set at a 20-period and the other at a 40-period. Then following the rules below:
40-period TEMA is rising
20-period TEMA is above 40-period TEMA
Price closes above 20-period TEMA
Today is not Monday
RSI MA crosses the Slow trailing line
This strategy does not employ an active take profit mechanism; instead, it utilizes a trailing stop loss to allow the price to reach the stop loss naturally, thereby maximizing potential profit margins.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Reference:
Trading Tact. What Is the QQE Indicator? Retrieved from: tradingtact.com
Session MasterSession Master Indicator
Overview
The "Session Master" indicator is a unique tool designed to enhance trading decisions by providing visual cues and relevant information during the critical last 15 minutes of a trading session. It also integrates advanced trend analysis using the Average Directional Index (ADX) and Directional Movement Index (DI) to offer insights into market trends and potential entry/exit points.
Originality and Functionality
This script combines session timing, visual alerts, and trend analysis in a cohesive manner to give traders a comprehensive view of market behavior as the trading day concludes. Here’s a breakdown of its key features:
Last 15 Minutes Highlight : The script identifies the last 15 minutes of the trading session and highlights this period with a semi-transparent blue background, helping traders focus on end-of-day price movements.
Previous Session High and Low : The script dynamically plots the high and low of the previous trading session. These levels are crucial for identifying support and resistance and are highlighted with dashed lines and labeled for easy identification during the last 15 minutes of the current session.
Directional Movement and Trend Analysis : Using a combination of ADX and DI, the script calculates and plots trend strength and direction. A 21-period Exponential Moving Average (EMA) is plotted with color coding (green for bullish and red for bearish) based on the DI difference, offering clear visual cues about the market trend.
Technical Explanation
Last 15 Minutes Highlight:
The script checks the current time and compares it to the session’s last 15 minutes.
If within this period, the background color is changed to a semi-transparent blue to alert the trader.
Previous Session High and Low:
The script retrieves the high and low of the previous daily session.
During the last 15 minutes of the session, these levels are plotted as dashed lines and labeled appropriately.
ADX and DI Calculation:
The script calculates the True Range, Directional Movement (both positive and negative), and smoothes these values over a specified length (28 periods by default).
It then computes the Directional Indicators (DI+ and DI-) and the ADX to gauge trend strength.
The 21-period EMA is plotted with dynamic color changes based on the DI difference to indicate trend direction.
How to Use
Highlight Key Moments: Use the blue background highlight to concentrate on market movements in the critical last 15 minutes of the trading session.
Identify Key Levels: Pay attention to the plotted high and low of the previous session as they often act as significant support and resistance levels.
Assess Trend Strength: Use the ADX and DI values to understand the strength and direction of the market trend, aiding in making informed trading decisions.
EMA for Entry/Exit: Use the color-coded 21-period EMA for potential entry and exit signals based on the trend direction indicated by the DI.
Conclusion
The "Session Master" indicator is a powerful tool designed to help traders make informed decisions during the crucial end-of-session period. By combining session timing, previous session levels, and advanced trend analysis, it provides a comprehensive overview that is both informative and actionable. This script is particularly useful for intraday traders looking to optimize their strategies around session close times.
Exponential SAR based MA**Description:**
The "Exponential SAR" (ESAR) indicator is a modified version of the classic Parabolic SAR (Stop and Reverse) indicator, incorporating an exponential moving average (EMA) smoothing technique. It aims to provide traders with a smoother representation of trend changes in the price action of a financial instrument.
**Functionality:**
The indicator calculates the Parabolic SAR values using specified parameters for start, increment, and maximum values. These parameters control the acceleration factor of the SAR. The calculated SAR values are then smoothed using an exponential moving average with a user-defined length, providing a more refined interpretation of trend dynamics.
**Inputs:**
- **Length:** Specifies the length of the exponential moving average used to smooth the Parabolic SAR values.
- **Alpha:** Defines the smoothing factor for the exponential moving average, allowing users to adjust the level of smoothing applied to the SAR.
- **Start, Increment, Maximum:** Parameters controlling the acceleration factor of the Parabolic SAR.
**Usage:**
- **Trend Identification:** Traders can use the Exponential SAR to identify trend reversals and continuations in the price action of a security. Bullish signals occur when the price moves above the ESAR, indicating an upward trend, while bearish signals occur when the price moves below the ESAR, signaling a downtrend.
- **Trend Confirmation:** The smoothed nature of the ESAR helps traders confirm trend changes more reliably, reducing the impact of false signals commonly associated with the standard Parabolic SAR.
- **Risk Management:** By incorporating a smoothed SAR, traders can make more informed decisions regarding entry and exit points, improving risk management strategies.
**Customization:**
Users can customize the indicator by adjusting the input parameters according to their trading preferences and market conditions. Experimenting with different lengths and alpha values can provide insights into the effectiveness of the ESAR in various trading scenarios.
**Note:**
As with any technical indicator, the Exponential SAR should be used in conjunction with other analytical tools and risk management techniques to validate signals and mitigate potential losses. Additionally, traders should consider market conditions and adapt their strategies accordingly.
Exponential Directional Index (DI)Exponential Directional Index (DI)
This indicator calculates the Exponential Directional Index (DI) using the Exponential Moving Average (EMA) of true range and directional movement. The DI is a widely used technical analysis tool that measures the strength of a trend by comparing positive and negative directional movements.
How it Works:
- **EMA Length:** Traders can adjust the length of the EMA calculation according to their trading preferences. A longer EMA length will result in a smoother DI line, while a shorter length will be more responsive to recent price action.
- **True Range (TR):** The true range is the greatest of the following: current high minus the current low, absolute value of the current high minus the previous close, and the absolute value of the current low minus the previous close.
- **Positive Directional Movement (+DM):** Calculates the difference between the current high and the previous high if positive, otherwise, it assigns a value of zero.
- **Negative Directional Movement (-DM):** Calculates the difference between the previous low and the current low if positive, otherwise, it assigns a value of zero.
- **Smoothed True Range (ATR):** Calculates the Exponential Moving Average (EMA) of the true range over the specified EMA length.
- **Smoothed Positive Directional Movement (+DI):** Calculates the Exponential Moving Average (EMA) of the positive directional movement over the specified EMA length.
- **Smoothed Negative Directional Movement (-DI):** Calculates the Exponential Moving Average (EMA) of the negative directional movement over the specified EMA length.
- **Directional Movement Index (DMI):** Calculates the DI values by dividing the smoothed positive and negative directional movements by the smoothed true range and multiplying by 100.
- **Bar Color:** The bar color changes based on whether the +DI is greater than, less than, or equal to the -DI. Green bars indicate that +DI is greater than -DI, red bars indicate that -DI is greater than +DI, and blue bars indicate that +DI is equal to -DI.
- **Background Highlight:** A background highlight is applied when the +DI crosses over the -DI or vice versa, providing a visual indication of potential trend changes.
Ideal Usage:
- **Trend Strength:** Traders can use the DI to gauge the strength of a trend. A rising +DI indicates bullish strength, while a rising -DI indicates bearish strength.
- **Trend Reversals:** Changes in the relationship between +DI and -DI, along with crossover signals, can indicate potential trend reversals.
- **Customization:** The indicator offers flexibility through customizable parameters, allowing traders to adapt it to various market conditions and trading strategies.
Warnings:
- **False Signals:** Like any technical indicator, false signals may occur, especially during periods of low volume or choppy market conditions. It's essential to use additional analysis and risk management techniques to avoid potential losses.
- **Parameter Sensitivity:** Adjusting the EMA length can affect the indicator's sensitivity to price movements. Traders should test different parameter settings and consider market conditions when using the indicator.
Uptrick: Trend Analysis 1 Trend Identification:
• The indicator primarily aims to identify trends in the market. It does this by computing two EMAs (fast and slow) and deriving the MACD line, which is the difference between these two EMAs. The MACD line is a momentum indicator that shows the relationship between two moving averages. When the MACD line is above the signal line, it suggests bullish momentum, while below indicates bearish momentum.
2 Entry and Exit Signals:
• The indicator generates potential entry and exit signals based on several conditions:
• Price vs. 20-period EMA: It checks whether the price is above or below the 20-period Exponential Moving Average. This is a common technique used to determine the overall direction of the trend. If the price is above the 20-period EMA, it suggests a bullish trend, and if it's below, it indicates a bearish trend.
• MACD Slope: It calculates the slope of the MACD line over a specified number of bars. A positive slope suggests increasing bullish momentum, while a negative slope indicates increasing bearish momentum.
• Signal Line Crossings: Traders often look for crossovers between the MACD line and the signal line as potential buy or sell signals. When the MACD line crosses above the signal line, it's considered a bullish signal (buy), and when it crosses below, it's seen as a bearish signal (sell).
3 Visual Representation:
• The indicator provides a visual representation of these conditions by plotting the MACD line with different colors depending on the market conditions (bullish, bearish, or neutral). Additionally, it draws vertical lines at the start of negative MACD slopes to highlight potential shifts in momentum.
4 Volume Analysis:
• It incorporates volume analysis by coloring the volume histogram differently based on whether the price is above or below the 20-period EMA. This can provide additional confirmation of trend strength. Higher volumes during price movements above the EMA may confirm bullish trends, while higher volumes during price movements below the EMA may confirm bearish trends.
5 Customization:
• Traders can customize the input parameters such as the fast and slow EMA periods according to their trading strategies and the specific market they're analyzing.
Trend Deviation strategy - BTC [IkkeOmar]Intro:
This is an example if anyone needs a push to get started with making strategies in pine script. This is an example on BTC, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay.
This strategy integrates several technical indicators to determine market trends and potential trade setups. These indicators include:
Directional Movement Index (DMI)
Bollinger Bands (BB)
Schaff Trend Cycle (STC)
Moving Average Convergence Divergence (MACD)
Momentum Indicator
Aroon Indicator
Supertrend Indicator
Relative Strength Index (RSI)
Exponential Moving Average (EMA)
Volume Weighted Average Price (VWAP)
It's crucial for you guys to understand the strengths and weaknesses of each indicator and identify synergies between them to improve the strategy's effectiveness.
Indicator Settings:
DMI (Directional Movement Index):
Length: This parameter determines the number of bars used in calculating the DMI. A higher length may provide smoother results but might lag behind the actual price action.
Bollinger Bands:
Length: This parameter specifies the number of bars used to calculate the moving average for the Bollinger Bands. A longer length results in a smoother average but might lag behind the price action.
Multiplier: The multiplier determines the width of the Bollinger Bands. It scales the standard deviation of the price data. A higher multiplier leads to wider bands, indicating increased volatility, while a lower multiplier results in narrower bands, suggesting decreased volatility.
Schaff Trend Cycle (STC):
Length: This parameter defines the length of the STC calculation. A longer length may result in smoother but slower-moving signals.
Fast Length: Specifies the length of the fast moving average component in the STC calculation.
Slow Length: Specifies the length of the slow moving average component in the STC calculation.
MACD (Moving Average Convergence Divergence):
Fast Length: Determines the number of bars used to calculate the fast EMA (Exponential Moving Average) in the MACD.
Slow Length: Specifies the number of bars used to calculate the slow EMA in the MACD.
Signal Length: Defines the number of bars used to calculate the signal line, which is typically an EMA of the MACD line.
Momentum Indicator:
Length: This parameter sets the number of bars over which momentum is calculated. A longer length may provide smoother momentum readings but might lag behind significant price changes.
Aroon Indicator:
Length: Specifies the number of bars over which the Aroon indicator calculates its values. A longer length may result in smoother Aroon readings but might lag behind significant market movements.
Supertrend Indicator:
Trendline Length: Determines the length of the period used in the Supertrend calculation. A longer length results in a smoother trendline but might lag behind recent price changes.
Trendline Factor: Specifies the multiplier used in calculating the trendline. It affects the sensitivity of the indicator to price changes.
RSI (Relative Strength Index):
Length: This parameter sets the number of bars over which RSI calculates its values. A longer length may result in smoother RSI readings but might lag behind significant price changes.
EMA (Exponential Moving Average):
Fast EMA: Specifies the number of bars used to calculate the fast EMA. A shorter period results in a more responsive EMA to recent price changes.
Slow EMA: Determines the number of bars used to calculate the slow EMA. A longer period results in a smoother EMA but might lag behind recent price changes.
VWAP (Volume Weighted Average Price):
Default settings are typically used for VWAP calculations, which consider the volume traded at each price level over a specific period. This indicator provides insights into the average price weighted by trading volume.
backtest range and rules:
You can specify the start date for backtesting purposes.
You can can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
LONG:
DMI Cross Up: The Directional Movement Index (DMI) indicates a bullish trend when the positive directional movement (+DI) crosses above the negative directional movement (-DI).
Bollinger Bands (BB): The price is below the upper Bollinger Band, indicating a potential reversal from the upper band.
Momentum Indicator: Momentum is positive, suggesting increasing buying pressure.
MACD (Moving Average Convergence Divergence): The MACD line is above the signal line, indicating bullish momentum.
Supertrend Indicator: The Supertrend indicator signals an uptrend.
Schaff Trend Cycle (STC): The STC indicates a bullish trend.
Aroon Indicator: The Aroon indicator signals a bullish trend or crossover.
When all these conditions are met simultaneously, the strategy considers it a favorable opportunity to enter a long trade.
SHORT:
DMI Cross Down: The Directional Movement Index (DMI) indicates a bearish trend when the negative directional movement (-DI) crosses above the positive directional movement (+DI).
Bollinger Bands (BB): The price is above the lower Bollinger Band, suggesting a potential reversal from the lower band.
Momentum Indicator: Momentum is negative, indicating increasing selling pressure.
MACD (Moving Average Convergence Divergence): The MACD line is below the signal line, signaling bearish momentum.
Supertrend Indicator: The Supertrend indicator signals a downtrend.
Schaff Trend Cycle (STC): The STC indicates a bearish trend.
Aroon Indicator: The Aroon indicator signals a bearish trend or crossover.
When all these conditions align, the strategy considers it an opportune moment to enter a short trade.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Furthermore this strategy uses both trend and mean-reversion systems, that is usually a no-go if you want to build robust trend systems .
Don't hesitate to comment if you have any questions or if you have some good notes for a beginner.
Composite Bull-Bear Dominance IndexNote: CREDITS: This is based on the Up Down Volume Indicator (published in Trading View) and Elder Ray Index (Bull Bear Power).
The Composite Bull Bear Dominance Index (CBBDI) is a indicator that combines up down volume analysis with Bull and Bear Power to provide a comprehensive view of market dynamics. It calculates Z-scores for up down volume delta and bull bear power measures, averages them, and then smoothes the result using Weighted Moving Average (WMA) for Bull and Bear Power and Volume Weighted Moving Average (VWMA) for Up and Down Volume Delta. The advantages include responsiveness to short-term trends, noise reduction through weighting, incorporation of volume information, and the ability to identify significant changes in buying and selling pressure. The indicator aims to offer clear signals for traders seeking insights into overall market dominance and indicate if the bulls or the bears have the upper hand.
Volume Analysis (Up/Down Volume Delta):
Up/Down Volume Delta reflects the net difference between buying and selling volume, providing insights into the prevailing market sentiment.
Positive Delta: Indicates potential bullish dominance due to higher buying volume.
Negative Delta: Suggests potential bearish dominance as selling volume surpasses buying volume.
Price Analysis (Bull and Bear Power):
Bull and Bear Power measure the strength of buying and selling forces based on price movements and the Exponential Moving Average (EMA) of the closing price.
Positive Bull Power: Reflects bullish dominance, indicating potential upward momentum.
Positive Bear Power: Suggests bearish dominance, indicating potential downward momentum.
Composite Bull Bear Dominance Index (CBBDI):
CBBDI combines the standardized Z-scores of Up/Down Volume Delta and Bull Bear Power, providing an average measure of both volume and price-related dominance.
Positive CBBDI: Indicates an overall bullish dominance in both volume and price dynamics.
Negative CBBDI: Suggests an overall bearish dominance in both volume and price dynamics.
Smoothing Techniques:
The use of Weighted Moving Average (WMA) for smoothing Bull and Bear Power Z-scores, and Volume Weighted Moving Average (VWMA) for smoothing Up/Down Volume Delta, reduces noise and provides a clearer trend signal.
Smoothing helps filter out short-term fluctuations and emphasizes more significant trends in both volume and price movements.
Color Coding:
CBBDI values are color-coded based on their direction, visually representing the prevailing market sentiment.
Green Colors: Positive values indicate potential bullish dominance.
Red Colors: Negative values suggest potential bearish dominance.
{Gunzo} Trend Sniper (Multiple MAs with coefficient)Updated GUNZO's Trend Sniper script by adding in different MA types to choose from. This can help reduce false signals and sharpen the trend reversal points.
Here's a summary of the key changes:
1. Multiple Moving Average Types: The original script was focused solely on the Weighted Moving Average (WMA) with a coefficient. The updated script introduces flexibility by allowing users to choose from a variety of Moving Average types, including WMA, VWMA (Volume Weighted Moving Average), EMA (Exponential Moving Average), SMA (Simple Moving Average), HullMA (Hull Moving Average), TEMA (Triple Exponential Moving Average), DEMA (Double Exponential Moving Average), T3, and RMA (Running Moving Average).
2. Coefficient Integration: In the original script, the coefficient was specifically designed for the WMA calculation. The updated script extends this concept to all the selected Moving Average types. This coefficient is applied differently depending on the type of MA, often affecting the length of the MA calculation.
3. Dynamic Length Calculation: For MAs that traditionally use an integer length (like SMA, EMA, etc.), the updated script calculates this length dynamically by multiplying the user-defined length by the coefficient and then rounding it to the nearest integer. This ensures compatibility with Pine Script's requirements for these functions.
All credits to GUNZO
original script:
MACD of Relative Strenght StrategyMACD Relative Strenght Strategy :
INTRODUCTION :
This strategy is based on two well-known indicators: MACD and Relative Strenght (RS). By coupling them, we obtain powerful buy signals. In fact, the special feature of this strategy is that it creates an indicator from an indicator. Thus, we construct a MACD whose source is the value of the RS. The strategy only takes buy signals, ignoring SHORT signals as they are mostly losers. There's also a money management method enabling us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RELATIVE STRENGHT :
RS is an indicator that measures the anomaly between momentum and the assumption of market efficiency. It is used by professionals and is one of the most robust indicators. The idea is to own assets that do better than average, based on their past performance. We calculate RS using this formula :
RS = close/highest_high(RS_Length)
Where highest_high(RS_Length) = highest value of the high over a user-defined time period (which is the RS_Length).
We can thus situate the current price in relation to its highest price over this user-defined period.
MACD (Moving Average Convergence - Divergence) :
This is one of the best-known indicators, measuring the distance between two exponential moving averages : one fast and one slower. A wide distance indicates fast momentum and vice versa. We'll plot the value of this distance and call this line macdline. The MACD uses a third moving average with a lower period than the first two. This last moving average will give a signal when it crosses the macdline. It is therefore constructed using the values of the macdline as its source.
It's important to note that the first two MAs are constructed using RS values as their source. So we've just built an indicator of an indicator. This kind of method is very powerful because it is rarely used and brings value to the strategy.
PARAMETERS :
RS Length : Relative Strength length i.e. the number of candles back to find the highest high and compare the current price with this high. Default is 300.
MACD Fast Length : Relative Strength fast EMA length used to plot the MACD. Default is 14.
MACD Slow Length : Relative Strength slow EMA length used to plot the MACD. Default is 26.
MACD Signal Smoothing : Macdline SMA length used to plot the MACD. Default is 10.
Max risk per trade (in %) : The maximum loss a trade can incur (in percentage of the trade value). Default is 8%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. Default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:ETHUSD in 8h timeframe with the parameters set by default.
ENTER RULES :
The entry rules are very simple : we open a long position when the MACD value turns positive. You are therefore LONG when the MACD is green.
EXIT RULES :
We exit a position (whether losing or winning) when the MACD becomes negative, i.e. turns red.
RISK MANAGEMENT :
This strategy can incur losses, so it's important to manage our risks well. If the position is losing and has incurred a loss of -8%, our stop loss is activated to limit losses.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
Enjoy the strategy and don't forget to take the trade :)
Open, Open +/- EMA ATR Lines with LabelsThis indicator provides traders with a clear visualization of the opening price and its potential movement range for a specific timeframe, based on the Exponential Moving Average (EMA) of the Average True Range (ATR).
Features:
Opening Price Line: A green line representing the opening price for the chosen timeframe.
EMA ATR Lines:
An upper blue line, calculated as the opening price plus the EMA of the ATR.
A lower blue line, calculated as the opening price minus the EMA of the ATR.
Labels: Each line comes with a label on its right side, displaying the price level and, for the EMA ATR lines, the distance in pips from the opening price.
Custom Timeframes: Users can select their desired timeframe for calculations, making this tool versatile for different trading strategies.
Usage:
The EMA-smoothed ATR provides a measure of volatility. By plotting this value above and below the opening price, traders get a sense of potential price movement for the selected timeframe. This can be particularly useful for setting stop losses, take profit levels, or identifying breakout points.
For instance, if the price breaks above the upper EMA ATR line, it might indicate a potential upward move, especially if other market conditions align.
Customization:
Timeframe: Choose from various timeframes like 1-minute, 5-minutes, daily, weekly, and more.
ATR Length: Adjust the length of the ATR for more or less sensitivity.
This indicator is designed to offer traders a quick way to gauge potential price movement for their chosen timeframe. By combining the principles of the opening price and volatility measured by the EMA-smoothed ATR, it provides a straightforward yet powerful tool for various trading scenarios.
