Dynamic Staircase - AYNETExplanation
Step Logic:
Each step is created dynamically when the price exceeds the current step's level by the specified step_size.
Steps go up or down, depending on the price movement.
Dynamic Levels:
The script tracks the last_step_price to determine when a new step is required.
Visualization:
Steps are drawn using line.new, and their colors change based on the direction (green for up, red for down).
A simple stickman is placed at the latest step to represent movement dynamically.
Inputs
Step Size: Controls the price difference required to create a new step.
Colors: Customize the colors for up steps, down steps, and the stickman.
What You’ll See
A staircase-like chart that moves dynamically with the price.
Each new step appears when the price moves up or down by the specified step size.
A stickman drawn at the latest step to simulate movement.
Further Customizations
Step Direction Labels:
Add labels like "Up" or "Down" at each step.
Advanced Stickman Animation:
Modify the stickman design to show motion or additional shapes.
Historical Steps:
Store and display all past steps as part of the staircase visualization.
Let me know if you'd like to extend this further or add trading-specific functionality! 😊
Bands and Channels
Multi-Symbol Scanner: Advanced EMA-RSI-Volume Strategy# Multi-Symbol Tech Stock Scanner: Advanced EMA-RSI-Volume Strategy
## Technical Analysis Methodology
This scanner implements a sophisticated multi-timeframe analysis approach combining three key technical elements:
### 1. Dual EMA System (Primary Trend Detection)
- **Long-term EMA (820 periods)**: Acts as the primary trend identifier
- Chosen specifically for tech stocks' longer-term price waves
- Helps filter out minor market noise while capturing major trend changes
- 820 periods approximately represents 3.2 years of trading days
- **Medium-term EMA (320 periods)**: Serves as trend confirmation
- Approximately 1.25 years of trading data
- Provides earlier entry signals while maintaining trend reliability
- Helps identify potential trend reversals before the major trend shift
### 2. Volume Analysis Component
The script employs a dynamic volume analysis system:
- Calculates 20-period moving average of volume as baseline
- Requires 1.5x surge above baseline for signal confirmation
- Volume surge requirement helps filter out weak moves and potential false breakouts
- Different from standard volume indicators as it uses adaptive thresholds
### 3. RSI Momentum Filter
Implements a specialized RSI configuration:
- 14-period RSI with dynamic overbought/oversold levels
- Oversold threshold: 30 (customizable)
- Overbought threshold: 70 (customizable)
- Used as a confirmation tool rather than primary signal generator
## Signal Generation Logic
### Buy Signal Requirements
1. Price must cross above 820 EMA (PRIMARY CONDITION)
2. Current price must be above 320 EMA (CONFIRMATION)
3. RSI must be above 30 but below 70 (MOMENTUM CHECK)
4. Volume must be 1.5x above 20-period average (STRENGTH VALIDATION)
### Sell Signal Requirements
1. Price must cross below 820 EMA (PRIMARY CONDITION)
2. Current price must be below 320 EMA (CONFIRMATION)
3. RSI must be above 30 but below 70 (MOMENTUM CHECK)
4. Volume must be 1.5x above 20-period average (STRENGTH VALIDATION)
## Risk Management Integration
The script automatically calculates key risk levels based on volatility:
1. **Stop Loss Calculation**:
- Default: 2% below entry for buys
- Dynamically adjusted based on price point
- Can be modified through input parameters
2. **Take Profit Targets**:
- Primary target: 6% above entry (3:1 reward-risk ratio)
- Based on historical tech stock movement patterns
- Adjustable through input parameters
## Multi-Symbol Implementation
The scanner monitors 6 symbols simultaneously using:
- Separate security calls for each data point
- Optimized data requests to prevent overload
- Individual signal processing for each symbol
- Synchronized alert generation system
## Technical Implementation Details
1. **Data Processing**:
```
- Security data requests on 10-minute timeframe
- Individual EMA calculations per symbol
- Separate volume analysis threads
- RSI calculations with standard deviation normalization
```
2. **Signal Processing**:
```
- Cross-verification of all conditions
- Time-based signal validation
- Volume surge confirmation
- Trend alignment check
```
3. **Alert System**:
```
- Bar-close confirmation required
- Multi-condition validation
- Detailed price level inclusion
- Risk parameter integration
```
## Optimization Features
1. **Memory Usage**:
- Optimized security calls
- Efficient data structure
- Reduced redundant calculations
2. **Processing Efficiency**:
- Single-pass data analysis
- Combined indicator calculations
- Streamlined alert generation
## Practical Application
The system is designed for:
1. Swing Trading (primary use)
2. Position Trading (secondary use)
3. Technical Breakout Trading
Optimal timeframes:
- Primary: 4H charts
- Secondary: Daily charts
- Verification: 1H charts
## Default Configuration
The scanner is preset to monitor key tech stocks:
- TSLA: High-volatility tech leader
- NVDA: Semiconductor sector benchmark
- AVGO: Stable tech infrastructure
- TSM: Global chip manufacturer
- META: Social media sector leader
- AMZN: E-commerce/Cloud computing leader
Each symbol can be modified through input parameters.
## Version Information
- Current Version: 1.3
- Last Updated: November 2024
- Compatibility: TradingView Pro/Pro+/Premium
## Limitations & Considerations
- Limited to 6 symbols due to TradingView security request limits
- Requires consistent market volume for optimal performance
- Best suited for liquid stocks with significant daily volume
- May need parameter adjustments during extreme market conditions
Galagtic Radar Grid - AYNETFeatures:
Concentric Circles:
Drawn using points (•) placed around a center.
The number of circles and their spacing are customizable.
Radial Lines:
Straight lines radiate outward from the center.
You can customize the number of lines (e.g., 12 for 30° intervals).
Highlight Marker:
An orange marker is placed at a specific angle (customizable) on the outermost circle.
Key Customization Inputs:
Circle Count: Number of concentric circles.
Circle Spacing: Distance between circles.
Line Count: Number of radial lines.
Highlight Angle: Position of the orange marker in degrees.
Colors: Customize grid and marker colors.
Core Logic:
Circles and radial lines are calculated using trigonometric functions (math.cos and math.sin).
The x-coordinates are tied to bar_index (integer), ensuring compatibility with TradingView's requirements.
This script is ideal for creating a visual radar-like grid on TradingView charts. Let me know if you'd like further enhancements! 😊
Eagle-Inspired - AYNETOverview of the Code:
Parameters for Customization:
Wing Span: Horizontal distance (in bars) of the wings.
Wing Height: Vertical height (in price units) of the wings.
Body Height: Vertical size of the central "body" rectangle.
Colors: Separate colors for wings and the body.
Center Point:
The center of the logo is dynamically tied to the current bar (bar_index) and price (close).
Design Components:
Wings: Two angled lines for the left and right wings.
Body: A rectangular shape approximated using four lines.
Dynamic Adjustments:
The size and proportions of the wings and body can be adjusted via user inputs.
Key Features:
Visual Elements: Creates a logo-like shape directly on the chart.
Customizable: Adjust the size, position, and colors of the wings and body.
Dynamic: Updates its position based on the latest bar and price.
This script provides a minimalist symbolic eagle design and can be used to visually overlay the chart with basic graphical elements. Let me know if you need further adjustments! 😊
Dynamic Support and Resistance -AYNETExplanation of the Code
Lookback Period:
The lookback input defines how many candles to consider when calculating the support (lowest low) and resistance (highest high).
Support and Resistance Calculation:
ta.highest(high, lookback) identifies the highest high over the last lookback candles.
ta.lowest(low, lookback) identifies the lowest low over the same period.
Dynamic Lines:
The line.new function creates yellow horizontal lines at the calculated support and resistance levels, extending them to the right.
Optional Plot:
plot is used to display the support and resistance levels as lines for visual clarity.
Customization:
You can adjust the lookback period and toggle the visibility of the lines via inputs.
How to Use This Code
Open the Pine Script Editor in TradingView.
Paste the above code into the editor.
Adjust the "Lookback Period for High/Low" to customize how the levels are calculated.
Enable or disable the support and resistance lines as needed.
This will create a chart similar to the one you provided, with horizontal yellow lines dynamically indicating the support and resistance levels. Let me know if you'd like any additional features or customizations!
Multi-LTF ATR Trailing Stop - AYNETSimple Explanation of the Code
This Pine Script code implements a multi-timeframe ATR-based trailing stop indicator. It calculates and plots the trailing stop lines for up to six configurable timeframes. Users can enable or disable specific timeframes, and each trailing stop line is color-coded and labeled with the corresponding timeframe (e.g., "15m", "1H").
Key Features of the Code
Multi-Timeframe Support:
The script calculates trailing stops for six different timeframes, such as 15 minutes, 1 hour, 1 day, etc.
User Configurations:
The user can:
Select timeframes for each trailing stop (e.g., "15m", "1H").
Enable or disable each timeframe using checkboxes.
Adjust the ATR period and multiplier to customize the trailing stop calculation.
Color-Coded Lines:
Each timeframe's trailing stop is plotted with a unique color for easy distinction.
Labels for Timeframes:
Labels at the end of the lines indicate the timeframe of each trailing stop (e.g., "15m", "1H").
Summary
This code is a multi-timeframe ATR trailing stop tool that helps traders visualize and analyze trailing stops across multiple timeframes. It is customizable, dynamic, and visually intuitive, making it ideal for both trend-following and stop-loss management.
Wick Trend Analysis with Supertrend and RSI -AYNETScientific Explanation
1. Wick Trend Analysis
Upper and Lower Wicks:
Calculated based on the difference between the high or low price and the candlestick body (open and close).
The trend of these wick lengths is derived using the Simple Moving Average (SMA) over the defined trend_length period.
Trend Direction:
Positive change (ta.change > 0) indicates an increasing trend.
Negative change (ta.change < 0) indicates a decreasing trend.
2. Supertrend Indicator
ATR Bands:
The Supertrend uses the Average True Range (ATR) to calculate dynamic upper and lower bands:
upper_band
=
hl2
+
(
supertrend_atr_multiplier
×
ATR
)
upper_band=hl2+(supertrend_atr_multiplier×ATR)
lower_band
=
hl2
−
(
supertrend_atr_multiplier
×
ATR
)
lower_band=hl2−(supertrend_atr_multiplier×ATR)
Trend Detection:
If the price is above the upper band, the Supertrend moves to the lower band.
If the price is below the lower band, the Supertrend moves to the upper band.
The Supertrend helps identify the prevailing market trend.
3. RSI (Relative Strength Index)
The RSI measures the momentum of price changes and ranges between 0 and 100:
Overbought Zone (Above 70): Indicates that the price may be overextended and due for a pullback.
Oversold Zone (Below 30): Indicates that the price may be undervalued and due for a reversal.
Visualization Features
Wick Trend Lines:
Upper wick trend (green) and lower wick trend (red) show the relative strength of price rejection on both sides.
Wick Trend Area:
The area between the upper and lower wick trends is filled dynamically:
Green: Upper wick trend is stronger.
Red: Lower wick trend is stronger.
Supertrend Line:
Displays the Supertrend as a blue line to highlight the market's directional bias.
RSI:
Plots the RSI line, with horizontal dotted lines marking the overbought (70) and oversold (30) levels.
Applications
Trend Confirmation:
Use the Supertrend and wick trends together to confirm the market's directional bias.
For example, a rising lower wick trend with a bullish Supertrend suggests strong bullish sentiment.
Momentum Analysis:
Combine the RSI with wick trends to assess the strength of price movements.
For example, if the RSI is oversold and the lower wick trend is increasing, it may signal a potential reversal.
Signal Generation:
Generate entry signals when all three indicators align:
Bullish Signal:
Lower wick trend increasing.
Supertrend bullish.
RSI rising from oversold.
Bearish Signal:
Upper wick trend increasing.
Supertrend bearish.
RSI falling from overbought.
Future Improvements
Alert System:
Add alerts for alignment of Supertrend, RSI, and wick trends:
pinescript
Kodu kopyala
alertcondition(upper_trend_direction == 1 and supertrend < close and rsi > 50, title="Bullish Signal", message="Bullish alignment detected.")
alertcondition(lower_trend_direction == 1 and supertrend > close and rsi < 50, title="Bearish Signal", message="Bearish alignment detected.")
Custom Thresholds:
Add thresholds for wick lengths and RSI levels to filter weak signals.
Multiple Timeframes:
Incorporate multi-timeframe analysis for more robust signal generation.
Conclusion
This script combines wick trends, Supertrend, and RSI to create a comprehensive framework for analyzing market sentiment and detecting potential trading opportunities. By visualizing trends, market bias, and momentum, traders can make more informed decisions and reduce reliance on single-indicator strategies.
Wick Trend Analysis - AYNETScientific Explanation
1. Wick Trend Lines
Upper Wick Trend Line: The upper_wick_trend is calculated as the Simple Moving Average (SMA) of the upper wick lengths over the user-defined period (trend_length).
pinescript
Kodu kopyala
float upper_wick_trend = ta.sma(upper_wick_length, trend_length)
Lower Wick Trend Line: The lower_wick_trend is similarly calculated for the lower wick lengths.
pinescript
Kodu kopyala
float lower_wick_trend = ta.sma(lower_wick_length, trend_length)
2. Filling Between Lines
fill Function: The fill function colors the area between two plotted lines (plot_upper and plot_lower) based on a defined condition.
pinescript
Kodu kopyala
fill(plot_upper, plot_lower, color=fill_color, title="Wick Trend Area")
Condition for Coloring: The color is determined based on whether the upper wick trend is greater or less than the lower wick trend:
Green Fill: Indicates that the upper wick trend is dominant (i.e., upper_wick_trend > lower_wick_trend).
Red Fill: Indicates that the lower wick trend is dominant (i.e., upper_wick_trend <= lower_wick_trend).
Visualization Features
Trend Lines:
Upper wick trend is plotted as a green line.
Lower wick trend is plotted as a red line.
Filled Area:
The area between the two trend lines is filled:
Green when the upper wick trend is dominant.
Red when the lower wick trend is dominant.
Dynamic Adjustments:
The user can adjust the trend_length to change the sensitivity of the SMA calculations.
Applications
Sentiment Analysis:
Green Fill (Upper Trend Dominance): Indicates stronger rejection at higher prices, suggesting bearish sentiment.
Red Fill (Lower Trend Dominance): Indicates stronger rejection at lower prices, suggesting bullish sentiment.
Signal Generation:
Transitions in the fill color (from green to red or vice versa) can serve as potential trade signals.
Volatility Assessment:
Wider gaps between the trend lines indicate higher market volatility, while narrower gaps suggest lower volatility.
Enhancements
1. Trend Strength Filtering
Add thresholds to filter out minor trends or insignificant wick activity:
pinescript
Kodu kopyala
bool significant_upper_wick = upper_wick_length > 10 // Minimum length for upper wick
bool significant_lower_wick = lower_wick_length > 10
2. Alerts for Trend Changes
Trigger alerts when the dominance of the trend changes:
pinescript
Kodu kopyala
alertcondition(upper_wick_trend > lower_wick_trend, title="Upper Wick Dominance", message="Upper wick trend is now dominant.")
alertcondition(lower_wick_trend > upper_wick_trend, title="Lower Wick Dominance", message="Lower wick trend is now dominant.")
3. Combined Wick Analysis
Incorporate total wick activity (upper + lower wicks) for holistic analysis:
pinescript
Kodu kopyala
float total_wick_trend = ta.sma(upper_wick_length + lower_wick_length, trend_length)
Conclusion
This script provides a robust visualization of wick trends with dynamic color filling to indicate trend dominance. By observing the relative strength of upper and lower wick trends, traders can assess market sentiment, detect potential reversals, and gauge volatility. This method can be further enhanced with additional filters, alerts, and composite indicators to refine trading strategies.
Renko Live Price Simulation-AYNETHow It Works:
Inputs:
Box Size (box_size): The size of a Renko brick (in price units).
Candle and Wick Colors: Users can customize colors for up and down candles and toggle wicks on or off.
Logic:
The script tracks the renko_open, renko_close, renko_high, and renko_low variables to simulate the formation of Renko bricks.
A new Renko brick is formed when the price moves up or down by the specified box size.
Candle Plotting:
The plotcandle function is used to draw the simulated Renko bricks on the chart.
Wicks are optional and controlled via the show_wicks input.
Visual Guides:
Two lines represent the thresholds for forming the next up or down Renko brick.
Features:
Real-Time Updates:
Bricks dynamically update as the live price moves.
Customizable Parameters:
Box size, candle colors, and wicks can be tailored to user preferences.
Overlay on Regular Chart:
The Renko simulation overlays the existing candlestick chart, providing context for real-time price action.
Threshold Levels:
Visual guides show how far the current price is from forming the next Renko brick.
Usage Instructions:
Copy and paste the script into the Pine Script editor in TradingView.
Customize the box size and colors to your preference.
Apply the indicator to your chart to visualize the Renko simulation in real time.
Applications:
Trend Analysis:
Renko bricks simplify price trends by filtering out minor fluctuations.
Entry/Exit Points:
Use Renko bricks as potential trade triggers when new bricks form.
Volatility Visualization:
The frequency of brick formation reflects the asset's volatility.
This code provides a live Renko simulation overlay that can be further customized based on user needs. Let me know if you'd like additional features, such as alerts or enhanced visualizations! 😊
Comprehensive Time Chain Indicator - AYNETFeatures and Enhancements
Dynamic Timeframe Handling:
The script monitors new intervals of a user-defined timeframe (e.g., daily, weekly, monthly).
Flexible interval selection allows skipping intermediate time periods (e.g., every 2 days).
Custom Marker Placement:
Markers can be placed at:
High, Low, or Close prices of the bar.
A custom offset above or below the close price.
Special Highlights:
Automatically detects the start of a week (Monday) and the start of a month.
Highlights these periods with a different marker color.
Connecting Lines:
Markers are connected with lines to visually link the events.
Line properties (color, width) are fully customizable.
Dynamic Labels:
Optional labels display the timestamp of the event, formatted as per user preferences (e.g., yyyy-MM-dd HH:mm).
How It Works:
Timeframe Event Detection:
The is_new_interval flag identifies when a new interval begins in the selected timeframe.
Special flags (is_new_week, is_new_month) detect key calendar periods.
Dynamic Marker Drawing:
Markers are drawn using label.new at the specified price levels.
Colors dynamically adjust based on the type of event (interval vs. special highlight).
Connecting Lines:
The script dynamically connects markers with line.new, creating a time chain.
Previous lines are updated for styling consistency.
Customization Options:
Timeframe (main_timeframe):
Adjust the timeframe for detecting new intervals, such as daily, weekly, or hourly.
Interval (interval):
Skip intermediate events (e.g., draw a marker every 2 days).
Visualization:
Enable or disable markers and labels independently.
Customize colors, line width, and marker positions.
Special Periods:
Highlight the start of a week or month with distinct markers.
Applications:
Event Tracking:
Highlight and connect key time intervals for easier analysis of patterns or trends.
Custom Time Chains:
Visualize periodic data, such as specific trading hours or cycles.
Market Session Analysis:
Highlight market opens, closes, or other critical time-based events.
Usage Instructions:
Copy and paste the code into the Pine Script editor on TradingView.
Adjust the input settings for your desired timeframe, visualization preferences, and special highlights.
Apply the script to a chart to see the time chain visualized.
This implementation provides robust functionality while remaining easy to customize. Let me know if further enhancements are required! 😊
Time Change Indicator-AYNETDetailed Scientific Explanation of the Time Change Indicator Code
This Pine Script code implements a financial indicator designed to measure and visualize the percentage change in the closing price of an asset over a specified timeframe. It uses historical data to calculate changes and displays them as a histogram for intuitive analysis. Below is a comprehensive scientific breakdown of the code:
1. User Inputs
The script begins by defining user-configurable parameters, enabling flexibility in analysis:
timeframe: The user selects the timeframe for measuring price changes (e.g., 1 hour, 1 day). This determines the granularity of the analysis.
positive_color and negative_color: Users choose the colors for positive and negative changes, enhancing visual interpretation.
2. Data Retrieval
The script employs request.security to fetch closing price data (close) for the specified timeframe. This function ensures that the indicator adapts to different timeframes, providing consistent results regardless of the chart's base timeframe.
Current Closing Price (current_close):
current_close
=
request.security(syminfo.tickerid, timeframe, close)
current_close=request.security(syminfo.tickerid, timeframe, close)
Retrieves the closing price for the defined timeframe.
Previous Closing Price (prev_close): The script uses a variable (prev_close) to store the previous closing price. This variable is updated dynamically as new data is processed.
3. Price Change Calculation
The script calculates both the absolute and percentage change in closing price:
Absolute Price Change (price_change):
price_change
=
current_close
−
prev_close
price_change=current_close−prev_close
Measures the difference between the current and previous closing prices.
Percentage Change (percent_change):
percent_change
=
price_change
prev_close
×
100
percent_change=
prev_close
price_change
×100
Normalizes the change relative to the previous closing price, making it easier to compare changes across different assets or timeframes.
4. Conditional Logic for Visualization
The script uses a conditional statement to determine the color of each histogram bar:
Positive Change: If price_change > 0, the bar is assigned the user-defined positive_color.
Negative Change: If price_change < 0, the bar is assigned the negative_color.
This differentiation provides a clear visual cue for understanding price movement direction.
5. Visualization
The script visualizes the percentage change using a histogram and enhances the chart with dynamic labels:
Histogram (plot.style_histogram):
Each bar represents the percentage change for a given timeframe.
Bars above the zero line indicate positive changes, while bars below the zero line indicate negative changes.
Zero Line (hline(0)): A reference line at zero provides a baseline for interpreting changes.
Dynamic Labels (label.new):
Each bar is annotated with its exact percentage change value.
The label's position and color correspond to the bar, improving clarity.
6. Algorithmic Flow
Data Fetching: Retrieve the current and previous closing prices for the specified timeframe.
Change Calculation: Compute the absolute and percentage changes between the two prices.
Bar Coloring: Determine the color of the histogram bar based on the change's direction.
Plotting: Visualize the changes as a histogram and add labels for precise data representation.
7. Applications
This indicator has several practical applications in financial analysis:
Volatility Analysis: By visualizing percentage changes, traders can assess the volatility of an asset over specific timeframes.
Trend Identification: Positive and negative bars highlight periods of upward or downward momentum.
Cross-Asset Comparison: Normalized percentage changes enable the comparison of price movements across different assets, regardless of their nominal values.
Market Sentiment: Persistent positive or negative changes may indicate prevailing bullish or bearish sentiment.
8. Scientific Relevance
This script applies fundamental principles of data visualization and time-series analysis:
Statistical Normalization: Percentage change provides a scale-invariant metric for comparing price movements.
Dynamic Data Processing: By updating the prev_close variable with real-time data, the script adapts to new market conditions.
Visual Communication: The use of color and labels improves the interpretability of quantitative data.
Conclusion
This indicator combines advanced Pine Script functions with robust financial analysis techniques to create an effective tool for evaluating price changes. It is highly adaptable, providing users with the ability to tailor the analysis to their specific needs. If additional features, such as smoothing or multi-timeframe analysis, are required, the code can be further extended.
Math Art with Fibonacci, Trigonometry, and Constants-AYNETScientific Explanation of the Code
This Pine Script code is a dynamic visual representation that combines mathematical constants, trigonometric functions, and Fibonacci sequences to generate geometrical patterns on a TradingView chart. The code leverages Pine Script’s drawing functions (line.new) and real-time bar data to create evolving shapes. Below is a detailed scientific explanation of its components:
1. Inputs and User-Defined Parameters
num_points: Specifies the number of points used to generate the geometrical pattern. Higher values result in more complex and smoother shapes.
scale: A scaling factor to adjust the size of the shape.
rotation: A dynamic rotation factor that evolves the shape over time based on the bar index (bar_index).
shape_color: Defines the color of the drawn shapes.
2. Mathematical Constants
The script employs essential mathematical constants:
Phi (ϕ): Known as the golden ratio
(
1
+
5
)
/
2
(1+
5
)/2, which governs proportions in Fibonacci spirals and natural growth patterns.
Pi (π): Represents the ratio of a circle's circumference to its diameter, crucial for trigonometric calculations.
Euler’s Number (e): The base of natural logarithms, incorporated in exponential growth modeling.
3. Geometric and Trigonometric Calculations
Fibonacci-Based Radius: The radius for each point is determined using a Fibonacci-inspired formula:
𝑟
=
scale
×
𝜙
⋅
𝑖
num_points
r=scale×
num_points
ϕ⋅i
Here,
𝑖
i is the point index. This ensures the shape grows proportionally based on the golden ratio.
Angle Calculation: The angular position of each point is calculated as:
𝜃
=
𝑖
⋅
Δ
𝜃
+
rotation
⋅
bar_index
100
θ=i⋅Δθ+rotation⋅
100
bar_index
where
Δ
𝜃
=
2
𝜋
num_points
Δθ=
num_points
2π
. This generates evenly spaced points along a circle, with dynamic rotation.
Coordinates: Cartesian coordinates
(
𝑥
,
𝑦
)
(x,y) for each point are derived using:
𝑥
=
𝑟
⋅
cos
(
𝜃
)
,
𝑦
=
𝑟
⋅
sin
(
𝜃
)
x=r⋅cos(θ),y=r⋅sin(θ)
These coordinates describe a polar-to-Cartesian transformation.
4. Dynamic Line Drawing
Connecting Points: For each pair of consecutive points, a line is drawn using:
line.new
(
𝑥
1
,
𝑦
1
,
𝑥
2
,
𝑦
2
)
line.new(x
1
,y
1
,x
2
,y
2
)
The coordinates are adjusted by:
bar_index: Aligns the x-axis to the chart’s time-based bar index.
int() Conversion: Ensures x-coordinates are integers, as required by line.new.
Line Properties:
Color: Set by the user.
Width: Fixed at 1 for simplicity.
5. Real-Time Adaptation
The shapes evolve dynamically as new bars form:
Rotation Over Time: The rotation parameter modifies angles proportionally to bar_index, creating a rotating effect.
Bar Index Alignment: Shapes are positioned relative to the current bar on the chart, ensuring synchronization with market data.
6. Visualization and Applications
This script generates evolving geometrical shapes, which have both aesthetic and educational value. Potential applications include:
Mathematical Visualization: Demonstrating the interplay of Fibonacci sequences, trigonometry, and geometry.
Technical Analysis: Serving as a visual overlay for price movement patterns, highlighting cyclical or wave-like behavior.
Dynamic Art: Creating visually appealing and evolving patterns on financial charts.
Scientific Relevance
This code synthesizes principles from:
Mathematical Analysis: Incorporates constants and formulas central to calculus, trigonometry, and algebra.
Geometry: Visualizes patterns derived from polar coordinates and Fibonacci scaling.
Real-Time Systems: Adapts dynamically to market data, showcasing practical applications of mathematics in financial visualization.
If further optimization or additional functionality is required, let me know! 😊
[AWC] Vector -AYNETThis Pine Script code is a custom indicator designed for TradingView. Its purpose is to visualize the opening and closing prices of a specific timeframe (e.g., weekly, daily, or monthly) by drawing lines between these price points whenever a new bar forms in the specified timeframe. Below is a detailed explanation from a scientific perspective:
1. Input Parameters
The code includes user-defined inputs to customize its functionality:
tf1: This input defines the timeframe (e.g., 'W' for weekly, 'D' for daily). It determines the periodicity for analyzing price data.
icol: This input specifies the color of the lines drawn on the chart. Users can select from predefined options such as black, red, or blue.
2. Color Assignment
A switch statement maps the user’s color selection (icol) to the corresponding color object in Pine Script. This mapping ensures that the drawn lines adhere to the user's preference.
3. New Bar Detection
The script uses the ta.change(time(tf1)) function to determine when a new bar forms in the specified timeframe (tf1):
ta.change checks if the timestamp of the current bar differs from the previous one within the selected timeframe.
If the value changes, it indicates that a new bar has formed, and further calculations are triggered.
4. Data Request
The script employs request.security to fetch price data from the specified timeframe:
o1: Retrieves the opening price of the previous bar.
c1: Calculates the average price (high, low, close) of the previous bar using the hlc3 formula.
These values represent the key price levels for visualizing the line.
5. Line Drawing
When a new bar is detected:
The script uses line.new to create a line connecting the previous bar's opening price (o1) and the closing price (c1).
The line’s properties are defined as follows:
x1, y1: The starting point corresponds to the opening price at the previous bar index.
x2, y2: The endpoint corresponds to the closing price at the current bar index.
color: Uses the user-defined color (col).
style: The line style is set to line.style_arrow_right.
Additionally, the lines are stored in an array (lines) for later reference, enabling potential modifications or deletions.
6. Visual Outcome
The script visually represents price movements over the specified timeframe:
Each line connects the opening and closing price of a completed bar in the given timeframe.
The lines are drawn dynamically, updating whenever a new bar forms.
Scientific Context
This script applies concepts of time series analysis and visualization in financial data:
Time Segmentation: By isolating specific timeframes (e.g., weekly), the script provides a focused analysis of price behavior.
Price Dynamics: Connecting opening and closing prices highlights key price transitions within each period.
User Customization: The inclusion of inputs allows for adaptable use, accommodating different analytical preferences.
Applications
Trend Analysis: Identifies how price evolves between opening and closing levels across periods.
Market Behavior Comparison: Facilitates the observation of patterns or anomalies in price transitions over time.
Technical Indicators: Serves as a supplementary tool for decision-making in trading strategies.
If further enhancements or customizations are needed, let me know! 😊
Vesica Piscis Visualization-Secret Geometry-AYNETExplanation
Customization Options:
circle_radius: Adjust the size of the circles.
line_color: Choose the color of the circles.
line_width: Adjust the thickness of the circle lines.
segments: Increase or decrease the smoothness of the circles (higher values make smoother circles but use more computational resources).
Placement:
The first circle is centered at circle1_x and the second is offset horizontally by 2 * circle_radius to ensure their centers intersect each other's circumference.
Intersection Highlight:
The intersection area is visually emphasized with a semi-transparent background (bgcolor), which can be customized or removed if unnecessary.
Smoothness:
The segments input determines how many points are used to create each circle. Higher values create smoother curves.
Adjustments
Ensure the circles fit within the visible chart area by adjusting circle1_x and circle_radius.
If needed, you can add additional features, such as drawing lines to connect the centers or labeling the Vesica Piscis region.
Let me know if you want further refinements or additional features!
Specific Time CandlesSpecific Time Candles Indicator
The Specific Time Candles indicator is a powerful tool designed for traders who want to focus on specific time intervals within their charts. This custom indicator allows you to highlight and analyze price action during user-defined time periods, providing clarity and precision in your trading strategy.
Key Features:
Custom Time Intervals: Select any start and end time to create candles that focus on your preferred trading hours. This is particularly useful for traders who want to concentrate on market sessions, such as the London or New York session, or any other specific time frame relevant to their trading plan.
Enhanced Visualization: By isolating specific time periods, this indicator helps reduce noise and provides a clearer view of market movements during key trading hours. This can be beneficial for identifying trends, reversals, and potential breakout opportunities.
Flexible Configuration: Easily adjust the indicator settings to match your trading schedule. Whether you are a day trader, swing trader, or scalper, you can customize the time frames to suit your needs.
Compatibility: The indicator is compatible with multiple asset classes, including forex, stocks, commodities, and cryptocurrencies, making it a versatile tool for any trader.
User-Friendly Interface: Designed with simplicity in mind, the Specific Time Candles indicator is easy to set up and use, even for those who are new to TradingView.
How to Use:
Add the indicator to your chart from the TradingView library.
Set your desired start and end times in the indicator settings.
Observe the newly formed candles that represent the specified time intervals.
Use these candles to make informed trading decisions based on the focused analysis of market activity during your chosen periods.
Benefits:
Precision Trading: Focus on the most relevant market data, eliminating distractions from other time periods.
Improved Decision-Making: Gain insights into market behavior during critical times, enhancing your ability to make strategic trades.
Time Management: Efficiently manage your trading by concentrating on specific times, allowing for better planning and execution.
The Specific Time Candles indicator is a must-have for traders looking to refine their strategies by concentrating on precise market windows. Whether you are targeting high-volatility periods or specific trading sessions, this indicator provides the tools you need to succeed.
Renko Periodic Spiral of Archimedes-Secret Geometry - AYNETHow It Works
Dynamic Center:
The spiral is centered on the close price of the chart, with an optional vertical offset (center_y_offset).
Spiral Construction:
The spiral is drawn using segments_per_turn to divide each turn into small line segments.
spacing determines the radial distance between successive turns.
num_turns controls how many full rotations the spiral will have.
Line Drawing:
Each segment is computed using trigonometric functions (cos and sin) to calculate its endpoints.
These segments are drawn sequentially to form the spiral.
Inputs
Center Y Offset: Adjusts the vertical position of the spiral relative to the close price.
Number of Spiral Turns: Total number of full rotations in the spiral.
Spacing Between Turns: Distance between consecutive turns.
Segments Per Turn: Number of segments used to create each turn (higher values make the spiral smoother).
Line Color: Customize the color of the spiral lines.
Line Width: Adjust the thickness of the spiral lines.
Example
If num_turns = 5, spacing = 2, and segments_per_turn = 100:
The spiral will have 5 turns, with a radial distance of 2 between each turn, divided into 100 segments per turn.
Let me know if you have further requests or adjustments to the visualization!
Mandala Visualization-Secret Geometry-AYNETCode Explanation
Dynamic Center:
The center Y coordinate is dynamic and defaults to the close price.
You can change it to a fixed level if desired.
Concentric Rings:
The script draws multiple circular rings spaced evenly using ring_spacing.
Symmetry Lines:
The Mandala includes num_lines radial symmetry lines emanating from the center.
Customization Options:
num_rings: Number of concentric circles.
ring_spacing: Distance between each ring.
num_lines: Number of radial lines.
line_color: Color of the rings and lines.
line_width: Thickness of the rings and lines.
How to Use
Add the script to your TradingView chart.
Adjust the input parameters to fit the Mandala within your chart view.
Experiment with different numbers of rings, lines, and spacing for unique Mandala patterns.
Let me know if you'd like additional features or visual tweaks!
Torus Visualization-Secret Geometry-AYNETExplanation:
Outer and Inner Circles:
The script draws two main circles: the outer boundary and the inner boundary of the Torus.
Bands Between Circles:
Additional concentric circles are drawn to create the illusion of a Torus structure.
Customizable Inputs:
You can control the outer radius, inner radius, number of segments for smoother circles, and the number of bands to improve visualization.
Parameters:
center_x and center_y define the center of the Torus on the chart.
outer_radius and inner_radius control the size of the Torus.
segments define the resolution of the circles (more segments = smoother appearance).
Visualization:
The Torus appears as a series of concentric circles, giving a 2D approximation of the 3D structure.
This script can be visualized on any chart, and the Torus will adjust its position based on the specified center and radius values.
Platonic Solids Visualization-Scret Geometry-AYNETExplanation:
Input Options:
solid: Choose the type of Platonic Solid (Tetrahedron, Cube, Octahedron, etc.).
size: Adjust the size of the geometry.
color_lines: Choose the color for the edges.
line_width: Set the width of the edges.
Geometry Calculations:
Each solid is drawn based on predefined coordinates and connected using the line.new function.
Geometric Types Supported:
Tetrahedron: A triangular pyramid.
Cube: A square-based 2D projection.
Octahedron: Two pyramids joined at the base.
Unsupported Solids:
Dodecahedron and Icosahedron are geometrically more complex and not rendered in this basic implementation.
Visualization:
The chosen Platonic Solid will be drawn relative to the center position (center_y) on the chart.
Adjust the size and center_y inputs to position the shape correctly.
Let me know if you need improvements or have a specific geometry to implement!
Sri Yantra-Scret Geometry - AYNETExplanation of the Script
Inputs:
periods: Number of bars used for calculating the moving average and standard deviation.
yloc: Chooses the display location (above or below the bars).
Moving Average and Standard Deviation:
ma: Moving average of the close price for the specified period.
std: Standard deviation, used to set the range for the Sri Yantra triangle points.
Triangle Points:
p1, p2, and p3 are the points for constructing the triangle, with p1 and p2 set at two standard deviations above and below the moving average, and p3 at the moving average itself.
Sri Yantra Triangle Drawing:
Three lines form a triangle, with the moving average line serving as the midpoint anchor.
The triangle pattern shifts across bars as new moving average values are calculated.
Moving Average Plot:
The moving average is plotted in red for visual reference against the triangle pattern.
This basic script emulates the Sri Yantra pattern using price data, creating a spiritual and aesthetic overlay on price charts, ideal for users looking to incorporate sacred geometry into their technical analysis.
Fibonacci Levels Strategy with High/Low Criteria-AYNETThis code represents a TradingView strategy that uses Fibonacci levels in conjunction with high/low price criteria over specified lookback periods to determine buy (long) and sell (short) conditions. Below is an explanation of each main part of the code:
Explanation of Key Sections
User Inputs for Higher Time Frame and Candle Settings
Users can select a higher time frame (timeframe) for analysis and specify whether to use the "Current" or "Last" higher time frame (HTF) candle for calculating Fibonacci levels.
The currentlast setting allows flexibility between using real-time or the most recent closed higher time frame candle.
Lookback Periods for High/Low Criteria
Two lookback periods, lowestLookback and highestLookback, allow users to set the number of bars to consider when finding the lowest and highest prices, respectively.
This determines the criteria for entering trades based on how recent highs or lows compare to current prices.
Fibonacci Levels Configuration
Fibonacci levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, and 100%) are configurable. These are used to calculate price levels between the high and low of the higher time frame candle.
Each level represents a retracement or extension relative to the high/low range of the HTF candle, providing important price levels for decision-making.
HTF Candle Calculation
HTF candle data is calculated based on the higher time frame selected by the user, using the newbar check to reset htfhigh, htflow, and htfopen values.
The values are updated with each new HTF bar or as prices move within the same HTF bar to track the highest high and lowest low accurately.
Set Fibonacci Levels Array
Using the calculated HTF candle's high, low, and open, the Fibonacci levels are computed by interpolating these values according to the user-defined Fibonacci levels.
A fibLevels array stores these computed values.
Plotting Fibonacci Levels
Each Fibonacci level is plotted on the chart with a different color, providing visual indicators for potential support/resistance levels.
High/Low Price Criteria Calculation
The lowest and highest prices over the specified lookback periods (lowestLookback and highestLookback) are calculated and plotted on the chart. These serve as dynamic levels to trigger long or short entries.
Trade Signal Conditions
longCondition: A long (buy) signal is generated when the price crosses above both the lowest price criteria and the 50% Fibonacci level.
shortCondition: A short (sell) signal is generated when the price crosses below both the highest price criteria and the 50% Fibonacci level.
Executing Trades
Based on the longCondition and shortCondition, trades are entered with the strategy.entry() function, using the labels "Long" and "Short" for tracking on the chart.
Strategy Use
This strategy allows traders to utilize Fibonacci retracement levels and recent highs/lows to identify trend continuation or reversal points, potentially providing entry points aligned with larger market structure. Adjusting the lowestLookback and highestLookback along with Fibonacci levels enables a customizable approach to suit different trading styles and market conditions.
Star of David Drawing-AYNETExplanation of Code
Settings:
centerTime defines the center time for the star pattern, defaulting to January 1, 2023.
centerPrice is the center Y-axis level for positioning the star.
size controls the overall size of the star.
starColor and lineWidth allow customization of the color and thickness of the lines.
Utility Function:
toRadians converts degrees to radians, though it’s not directly used here, it might be useful for future adjustments to angles.
Star of David Drawing Function:
The drawStarOfDavid function calculates the position of each point on the star relative to the center coordinates (centerTime, centerY) and size.
The pattern has six key points that form two overlapping triangles, creating the Star of David pattern.
The time offsets (offset1 and offset2) determine the horizontal spread of the star, scaling according to size.
The line.new function is used to draw the star lines with the calculated coordinates, casting timestamps to int to comply with line.new requirements.
Star Rendering:
Finally, drawStarOfDavid is called to render the Star of David pattern on the chart based on the input parameters.
This code draws the Star of David on a chart at a specified time and price level, with customizable size, color, and line width. Adjust centerTime, centerPrice, and size as needed for different star placements on the chart.
Holt-Winters Forecast BandsDescription:
The Holt-Winters Adaptive Bands indicator combines seasonal trend forecasting with adaptive volatility bands. It uses the Holt-Winters triple exponential smoothing model to project future price trends, while Nadaraya-Watson smoothed bands highlight dynamic support and resistance zones.
This indicator is ideal for traders seeking to predict future price movements and visualize potential market turning points. By focusing on broader seasonal and trend data, it provides insight into both short- and long-term market directions. It’s particularly effective for swing trading and medium-to-long-term trend analysis on timeframes like daily and 4-hour charts, although it can be adjusted for other timeframes.
Key Features:
Holt-Winters Forecast Line: The core of this indicator is the Holt-Winters model, which uses three components — level, trend, and seasonality — to project future prices. This model is widely used for time-series forecasting, and in this script, it provides a dynamic forecast line that predicts where price might move based on historical patterns.
Adaptive Volatility Bands: The shaded areas around the forecast line are based on Nadaraya-Watson smoothing of historical price data. These bands provide a visual representation of potential support and resistance levels, adapting to recent volatility in the market. The bands' fill colors (red for upper and green for lower) allow traders to identify potential reversal zones without cluttering the chart.
Dynamic Confidence Levels: The indicator adapts its forecast based on market volatility, using inputs such as average true range (ATR) and price deviations. This means that in high-volatility conditions, the bands may widen to account for increased price movements, helping traders gauge the current market environment.
How to Use:
Forecasting: Use the forecast line to gain insight into potential future price direction. This line provides a directional bias, helping traders anticipate whether the price may continue along a trend or reverse.
Support and Resistance Zones: The shaded bands act as dynamic support and resistance zones. When price enters the upper (red) band, it may be in an overbought area, while the lower (green) band may indicate oversold conditions. These bands adjust with volatility, so they reflect the current market conditions rather than fixed levels.
Timeframe Recommendations:
This indicator performs best on daily and 4-hour charts due to its reliance on trend and seasonality. It can be used on lower timeframes, but accuracy may vary due to increased price noise.
For traders looking to capture swing trades, the daily and 4-hour timeframes provide a balance of trend stability and signal reliability.
Adjustable Settings:
Alpha, Beta, and Gamma: These settings control the level, trend, and seasonality components of the forecast. Alpha is generally the most sensitive setting for adjusting responsiveness to recent price movements, while Beta and Gamma help fine-tune the trend and seasonal adjustments.
Band Smoothing and Deviation: These settings control the lookback period and width of the volatility bands, allowing users to customize how closely the bands follow price action.
Parameters:
Prediction Length: Sets the length of the forecast, determining how far into the future the prediction line extends.
Season Length: Defines the seasonality cycle. A setting of 14 is typical for bi-weekly cycles, but this can be adjusted based on observed market cycles.
Alpha, Beta, Gamma: These parameters adjust the Holt-Winters model's sensitivity to recent prices, trends, and seasonal patterns.
Band Smoothing: Determines the smoothing applied to the bands, making them either more reactive or smoother.
Ideal Use Cases:
Swing Trading and Trend Following: The Holt-Winters model is particularly suited for capturing larger market trends. Use the forecast line to determine trend direction and the bands to gauge support/resistance levels for potential entries or exits.
Identifying Reversal Zones: The adaptive bands act as dynamic overbought and oversold zones, giving traders potential reversal areas when price reaches these levels.
Important Notes:
No Buy/Sell Signals: This indicator does not produce direct buy or sell signals. It’s intended for visual trend analysis and support/resistance identification, leaving trade decisions to the user.
Not for High-Frequency Trading: Due to the nature of the Holt-Winters model, this indicator is optimized for higher timeframes like the daily and 4-hour charts. It may not be suitable for high-frequency or scalping strategies on very short timeframes.
Adjust for Volatility: If using the indicator on lower timeframes or more volatile assets, consider adjusting the band smoothing and prediction length settings for better responsiveness.
