RSI Above 25 Buy and Sell ConditionBuy Signal: Triggered when RSI (25) is above 25, and a new candlestick forms.
Sell Signal: Triggered when RSI (25) falls below 75, and a new candlestick forms.
Small Buttons: We will use plotshape with a small size for the labels and make them as
Indicators and strategies
RSI Above 25 Buy ConditionCopy the script and paste it into the Pine Script Editor on TradingView.
Save the script and click "Add to Chart".
You'll see "BUY" and "SELL" labels on the chart when the conditions are met.
You can also set up alerts for when the conditions trigger (Buy or Sell).
RSI Above 25 Buy ConditionCopy the script and paste it into the Pine Script Editor on TradingView.
Save the script and click "Add to Chart".
You'll see "BUY" and "SELL" labels on the chart when the conditions are met.
You can also set up alerts for when the conditions trigger (Buy or Sell).
RSI Strategy with ButtonsCopy and paste this code into TradingView's Pine Script editor.
Save and click "Add to Chart".
You'll see Buy and Sell labels on the chart when the conditions are met.
RSI Strategy with ButtonsCopy and paste this code into TradingView's Pine Script editor.
Save and click "Add to Chart".
You'll see Buy and Sell labels on the chart when the conditions are met.
RSI Strategy with ButtonsCopy and paste this code into TradingView's Pine Script editor.
Save and click "Add to Chart".
You'll see Buy and Sell labels on the chart when the conditions are met.
Custom RSI StrategyGo to TradingView.
Click on "Pine Editor" at the bottom of the screen.
Paste the code into the editor.
Click "Save" and give the script a name.
Click "Add to Chart" to apply it to your chart
RSI + Chandelier Exit StrategyHere's a brief version of how to paste and apply the code in TradingView:
Go to TradingView.
Click on "Pine Editor" at the bottom of the screen.
Paste the code into the editor.
Click "Save" and give the script a name.
Click "Add to Chart" to apply it to your chart.
RSI + Chandelier Exit StrategyHere's a brief version of how to paste and apply the code in TradingView:
Go to TradingView.
Click on "Pine Editor" at the bottom of the screen.
Paste the code into the editor.
Click "Save" and give the script a name.
Click "Add to Chart" to apply it to your chart.
rsi wf breakoutRSI Breakout Asif
RSI Breakout Asif Indicator
Overview:
The RSI Breakout Asif indicator is a custom script designed to analyze and highlight potential
breakout points using the Relative Strength Index (RSI) combined with Williams Fractals. This
indicator is specifically developed for traders who want to identify key momentum shifts in the
market.
Features:
1. RSI Analysis:
- The RSI is calculated using a user-defined length and price source.
- Horizontal lines are plotted at levels 70 (overbought), 50 (neutral), and 30 (oversold) to visually
aid decision-making.
2. Williams Fractals on RSI:
- Detects fractal highs and lows based on RSI values.
- Highlights these fractal points with dynamic, symmetrical lines for better visibility.
3. Customization:
- Users can adjust the RSI length and price source for personalized analysis.
- Fractal settings (left and right bar length) are also adjustable, making the indicator versatile for
different trading styles.
4. Visual Enhancements:
- Fractal highs are marked in red, while fractal lows are marked in green.
Asif - Page 1
RSI Breakout Asif
- Precise line placement ensures clarity and reduces chart clutter.
5. Practical Utility:
- Use the fractal breakout signals in conjunction with other technical indicators for enhanced
decision-making.
Usage:
- Add the RSI Breakout Asif indicator to your TradingView chart.
- Adjust the settings according to your trading strategy.
- Observe the RSI values and fractal points to identify potential breakout zones.
Disclaimer:
This indicator is a technical analysis tool and should be used in combination with other analysis
methods. It does not guarantee profitable trades.
Watermarked by Asif.
Asif - Page 2
rsi wf breakoutRSI Breakout Asif
RSI Breakout Asif Indicator
Overview:
The RSI Breakout Asif indicator is a custom script designed to analyze and highlight potential
breakout points using the Relative Strength Index (RSI) combined with Williams Fractals. This
indicator is specifically developed for traders who want to identify key momentum shifts in the
market.
Features:
1. RSI Analysis:
- The RSI is calculated using a user-defined length and price source.
- Horizontal lines are plotted at levels 70 (overbought), 50 (neutral), and 30 (oversold) to visually
aid decision-making.
2. Williams Fractals on RSI:
- Detects fractal highs and lows based on RSI values.
- Highlights these fractal points with dynamic, symmetrical lines for better visibility.
3. Customization:
- Users can adjust the RSI length and price source for personalized analysis.
- Fractal settings (left and right bar length) are also adjustable, making the indicator versatile for
different trading styles.
4. Visual Enhancements:
- Fractal highs are marked in red, while fractal lows are marked in green.
Asif - Page 1
RSI Breakout Asif
- Precise line placement ensures clarity and reduces chart clutter.
5. Practical Utility:
- Use the fractal breakout signals in conjunction with other technical indicators for enhanced
decision-making.
Usage:
- Add the RSI Breakout Asif indicator to your TradingView chart.
- Adjust the settings according to your trading strategy.
- Observe the RSI values and fractal points to identify potential breakout zones.
Disclaimer:
This indicator is a technical analysis tool and should be used in combination with other analysis
methods. It does not guarantee profitable trades.
Watermarked by Asif.
Asif - Page 2
Ultra Volume High Breakoutser Inputs:
length: Defines the period to calculate the moving average of volume.
multiplier: Sets the threshold above the moving average to consider as "Ultra Volume."
breakoutMultiplier: Allows for customization of breakout sensitivity.
Volume Calculation:
The script calculates a simple moving average (SMA) of the volume for a defined period (length).
It then detects if the current volume is higher than the moving average multiplied by the user-defined multiplier.
Breakout Condition:
The script checks if the price has moved above the highest close of the previous length periods while the volume condition for "Ultra Volume" is true.
Visuals:
The script marks the breakout with an upward label below the bar (plotshape), colored green for easy identification.
Ultra volume is highlighted with a red histogram plot.
Alert Condition:
An alert condition is included to trigger whenever an ultra volume high breakout occurs.
Customization:
You can adjust the length, multiplier, and breakoutMultiplier to fit your strategy and asset volatility.
Alerts can be set in TradingView to notify you when this condition is met.
Let me know if you'd like further customization or explanation!
Combined RSI StrategyGo to TradingView.
Click on "Pine Editor" at the bottom of the screen.
Paste the code into the editor.
Click "Save" and give the script a name.
Click "Add to Chart" to apply it to your chart.
Now, you'll see the Buy and Sell signals on the chart. Optionally, you can set up alerts for Buy/Sell conditions.
ADX with Middle Line - RehmanFeatures:
Customizable Parameters:
ADX Length: Set the length for calculating the ADX smoothing (default: 14).
Middle Line Value: A user-defined threshold (default: 25) to highlight trend strength.
Plots:
ADX Line: Indicates trend strength (blue line).
DI+ and DI- Lines: Show positive (green) and negative (red) directional movement.
Middle Line: A horizontal line for reference (red).
Background Highlights:
Green background when ADX is above the middle line, indicating a strong trend.
Red background when ADX is below the middle line, indicating a weak trend.
CJ - RSI - Daily, Weekly, MonthlyThe Single Indicator to showcase RSI - Daily, Weekly and Monthly Timeframe
JAR - 2ema_strategyusing 2 EMA to open trade and close trade. using D1 chart, EMA 10 & 20, crypto trade. buy only at the moment and will workout both directions.
Pro Stock Scanner + MACD# Pro Stock Scanner - Advanced Trading System
### Professional Scanning System Combining MACD, Momentum & Technical Analysis
## 🎯 Indicator Purpose
This indicator was developed to identify high-quality trading opportunities by combining:
- Strong positive momentum
- Clear technical trend
- Significant trading volume
- Precise MACD signals
## 💡 Core Mechanics
The indicator is based on three core components:
### 1. Advanced MACD Analysis (40%)
- MACD line crossover tracking
- Momentum strength measurement
- Positive/negative divergence detection
- Score range: 0-40 points
### 2. Trend Analysis (40%)
- Moving average relationships (MA20, MA50)
- Primary trend direction
- Current trend strength
- Score range: 0-40 points
### 3. Volume Analysis (20%)
- Comparison with 20-day average volume
- Volume breakout detection
- Score range: 0-20 points
## 📊 Scoring System
Total score (0-100) composition:
```
Total Score = MACD Score (40%) + Trend Score (40%) + Volume Score (20%)
```
### Score Interpretation:
- 80-100: Strong Buy Signal 🔥
- 65-79: Developing Bullish Trend ⬆️
- 50-64: Neutral ↔️
- 0-49: Technical Weakness ⬇️
## 📈 Chart Markers
1. **Large Blue Triangle**
- High score (80+)
- Positive MACD
- Bullish MACD crossover
2. **Small Triangles**
- Green: Bullish MACD crossover
- Red: Bearish MACD crossover
## 🎛️ Customizable Parameters
```
MACD Settings:
- Fast Length: 12
- Slow Length: 26
- Signal Length: 9
- Strength Threshold: 0.2%
Volume Settings:
- Threshold: 1.5x average
```
## 📱 Information Panel
Real-time display of:
1. Total Score
2. MACD Score
3. MACD Strength
4. Volume Score
5. Summary Signal
## ⚙️ Optimization Guidelines
Recommended adjustments:
1. **Bull Market**
- Decrease MACD sensitivity
- Increase volume threshold
- Focus on trend strength
2. **Bear Market**
- Increase MACD sensitivity
- Stricter trend conditions
- Higher score requirements
## 🎯 Recommended Trading Strategy
### Phase 1: Initial Scan
1. Look for 80+ total score
2. Verify sufficient trading volume
3. Confirm bullish MACD crossover
### Phase 2: Validation
1. Check long-term trend
2. Identify nearby resistance levels
3. Review earnings calendar
### Phase 3: Position Management
1. Set clear stop-loss
2. Define realistic profit targets
3. Monitor score changes
## ⚠️ Important Notes
1. This indicator is a supplementary tool
2. Combine with fundamental analysis
3. Strict risk management is essential
4. Not recommended for automated trading
## 📈 Usage Examples
Examples included:
1. Successful buy signal
2. Trend reversal identification
3. False signal analysis and lessons learned
## 🔄 Future Updates
1. RSI integration
2. Advanced alerts
3. Auto-optimization features
## 🎯 Key Benefits
1. Clear scoring system
2. Multiple confirmation layers
3. Real-time market feedback
4. Customizable parameters
## 🚀 Getting Started
1. Add indicator to chart
2. Adjust parameters if needed
3. Monitor information panel
4. Wait for strong signals (80+ score)
## 📊 Performance Metrics
- Success rate: Monitor and track
- Best performing in trending markets
- Optimal for swing trading
- Most effective on daily timeframe
## 🛠️ Technical Details
```pine
// Core components
1. MACD calculation
2. Volume analysis
3. Trend confirmation
4. Score computation
```
## 💡 Pro Tips
1. Use multiple timeframes
2. Combine with support/resistance
3. Monitor sector trends
4. Consider market conditions
## 🤝 Support
Feedback and improvement suggestions welcome!
## 📜 License
MIT License - Free to use and modify
## 📚 Additional Resources
- Recommended timeframes: Daily, 4H
- Best performing markets: Stocks, ETFs
- Optimal market conditions: Trending markets
- Risk management guidelines included
## 🔍 Final Notes
Remember:
- No indicator is 100% accurate
- Always use proper position sizing
- Combine with other analysis tools
- Practice proper risk management
// @version=5
// @description Pro Stock Scanner - Advanced trading system combining MACD, momentum and volume analysis
// @author AviPro
// @license MIT
//
// This indicator helps identify high-quality trading opportunities by analyzing:
// 1. MACD momentum and crossovers
// 2. Trend strength and direction
// 3. Volume patterns and breakouts
//
// The system provides:
// - Total score (0-100)
// - Visual signals on chart
// - Information panel with key metrics
// - Customizable parameters
//
// IMPORTANT: This indicator is for educational and informational purposes only.
// Always conduct your own analysis and use proper risk management.
//
// If you find this indicator helpful, please consider leaving a like and comment!
// Feedback and suggestions for improvement are always welcome.
PineTraderLibraryPineTrader Library Documentation
Overview
The PineTrader Library provides functionality to generate standardized order tickets for trading operations. The library's main function GenerateOT creates JSON-formatted order tickets that can be sent via webhook.
Main Function: GenerateOT
Purpose
Creates a formatted JSON order ticket string following Pinetrader.io specifications, handling both simple and complex order scenarios.
Parameters
Required Parameters
license_id (string): Your license identifier
symbol (string): Trading symbol/instrument
action (string): Order execution method
Valid values: "MRKT" (market) or "PENDING"
order_type (string): Direction of the trade
Valid values: "BUY" or "SELL"
trade_type (string): Trade execution category
Valid values: "SPREAD" or "SINGLE"
Optional Parameters
size (float, default=0.0): Trade size in units
price (float, default=0.0): Execution price (required for pending orders)
tp (float, default=0.0): Take profit level
sl (float, default=0.0): Stop loss level
risk (float, default=0.0): Risk percentage (used when size is not specified)
trailPrice (float, default=0.0): Starting price for trailing stop
trailOffset (float, default=0.0): Trailing amount
Return Value
Returns a JSON-formatted string containing the order ticket information. The function automatically handles:
Proper JSON formatting with curly braces
Removal of trailing commas
Inclusion of only non-zero values
Numeric formatting for float values
Output Format
{
"license_id": "string",
"symbol": "string",
"action": "string",
"order_type": "string",
"trade_type": "string",
"size": number, // Optional
"price": number, // Optional
"tp": number, // Optional
"sl": number, // Optional
"risk": number, // Optional
"trail_price": number, // Optional
"trail_offset": number // Optional
}
Implementation Notes
The function uses dynamic string construction for flexibility
Optional parameters are only included in the output if their value is non-zero
JSON formatting follows standard conventions for webhook compatibility
The library operates under Mozilla Public License 2.0
The function handles proper numeric formatting for all float values
BTCUSDT.P Binance ve BTCUSD.P Bitmex Fiyat KontrolüBitmex Ve Binance arasındaki BTC fiyat farkına göre AL ve SAT sinyalleri üretir. BTC için geçerlidir.
GB_Sir : 15 Min Inside Bar15 Min Inside Bar Setup are fetched by this indicator. Persistent lines are drawn on High and Low of 2nd bar. These lines remains persistent even after changing timeframe of chart to lower time frame.
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
Sum Trend OscillatorPublishing my first indicator.
This one accumulates bars over two short period and divide that by the difference between a long term mean value of high-low
Buy/Sell signal is when both line cross at close below or above the center line.
