ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
Pesquisar nos scripts por "text"
Global M2 Index Percentage### **Global M2 Index Percentage**
**Description:**
The **Global M2 Index Percentage** is a custom indicator designed to track and visualize the global money supply (M2) in a normalized percentage format. It aggregates M2 data from major economies (e.g., the US, EU, China, Japan, and the UK) and adjusts for exchange rates to provide a comprehensive view of global liquidity. This indicator helps traders and investors understand the broader macroeconomic environment, identify trends in money supply, and make informed decisions based on global liquidity conditions.
---
### **How It Works:**
1. **Data Aggregation**:
- The indicator collects M2 data from key economies and adjusts it using exchange rates to calculate a global M2 value.
- The formula for global M2 is:
\
2. **Normalization**:
- The global M2 value is normalized into a percentage (0% to 100%) based on its range over a user-defined period (default: 13 weeks).
- The formula for normalization is:
\
3. **Visualization**:
- The indicator plots the M2 Index as a line chart.
- Key reference levels are highlighted:
- **10% (Red Line)**: Oversold level (low liquidity).
- **50% (Black Line)**: Neutral level.
- **80% (Green Line)**: Overbought level (high liquidity).
---
### **How to Use the Indicator:**
#### **1. Understanding the M2 Index:**
- **Below 10%**: Indicates extremely low liquidity, which may signal economic contraction or tight monetary policy.
- **Above 80%**: Indicates high liquidity, which may signal loose monetary policy or potential inflationary pressures.
- **Between 10% and 80%**: Represents a neutral to moderate liquidity environment.
#### **2. Trading Strategies:**
- **Long-Term Investing**:
- Use the M2 Index to assess global liquidity trends.
- **High M2 Index (e.g., >80%)**: Consider investing in risk assets (stocks, commodities) as liquidity supports growth.
- **Low M2 Index (e.g., <10%)**: Shift to defensive assets (bonds, gold) as liquidity tightens.
- **Short-Term Trading**:
- Combine the M2 Index with technical indicators (e.g., RSI, MACD) for timing entries and exits.
- **M2 Index Rising + RSI Oversold**: Potential buying opportunity.
- **M2 Index Falling + RSI Overbought**: Potential selling opportunity.
#### **3. Macroeconomic Analysis**:
- Use the M2 Index to monitor the impact of central bank policies (e.g., quantitative easing, rate hikes).
- Correlate the M2 Index with inflation data (CPI, PPI) to anticipate inflationary or deflationary trends.
---
### **Key Features:**
- **Customizable Timeframe**: Adjust the lookback period (e.g., 13 weeks, 26 weeks) to suit your trading style.
- **Multi-Economy Data**: Aggregates M2 data from the US, EU, China, Japan, and the UK for a global perspective.
- **Normalized Output**: Converts raw M2 data into an easy-to-interpret percentage format.
- **Reference Levels**: Includes key levels (10%, 50%, 80%) for quick analysis.
---
### **Example Use Case:**
- **Scenario**: The M2 Index rises from 49% to 62% over two weeks.
- **Interpretation**: Global liquidity is increasing, potentially due to central bank stimulus.
- **Action**:
- **Long-Term**: Increase exposure to equities and commodities.
- **Short-Term**: Look for buying opportunities in oversold assets (e.g., RSI < 30).
---
### **Why Use the Global M2 Index Percentage?**
- **Macro Insights**: Understand the broader economic environment and its impact on financial markets.
- **Risk Management**: Identify periods of high or low liquidity to adjust your portfolio accordingly.
- **Enhanced Timing**: Combine with technical analysis for better entry and exit points.
---
### **Conclusion:**
The **Global M2 Index Percentage** is a powerful tool for traders and investors seeking to incorporate macroeconomic data into their strategies. By tracking global liquidity trends, this indicator helps you make informed decisions, whether you're trading short-term or planning long-term investments. Add it to your TradingView charts today and gain a deeper understanding of the global money supply!
---
**Disclaimer**: This indicator is for informational purposes only and should not be considered financial advice. Always conduct your own research and consult with a professional before making investment decisions.
Visible and Anchored OTE chart [SYNC & TRADE]Thanks for the start @twingall
Visible and Anchored OTE chart
Indicator for visualizing price levels and optimal trading zones (OTE - Optimal Trading Entry) using Fibonacci levels.
Main features
Visualization of price ranges using two OTE zones:
OTE 70% (79-62 Fibonacci levels)
OTE 30% (21-38 Fibonacci levels)
Setting up time periods:
Ability to use a custom date range
Option to work with a higher time frame
Flexible display settings:
Choose between using candle bodies or the full range for binding
Customizable appearance of OTE boxes
Customizable text labels
Additional levels:
Middle line (50.5%)
Optional levels of 29.5%, 70.5% and 88%
Customizable Fibonacci extensions
Indicator settings
Main parameters
Use Custom Dates - enable a custom date range
Start Date/End Date - set a time range
Use Higher Timeframe - use a higher time frame
Higher Timeframe - select a higher timeframe
Setting up OTE zones
Show Fib Box - displaying OTE zones
Enable Fib Box 79-62 - enabling OTE zone 70%
Enable Fib Box 21-38 - enabling OTE zone 30%
Show Text - displaying text labels in zones
Visual design
Text Size - text size (tiny/small/medium/large)
Text Color - text color
Text Alignment - text alignment
Line Thickness - line thickness (1-4)
Line Style - line style (Solid/Dashed/Dotted)
Fibonacci levels
High/Low Lines - displaying extreme levels
Midline - displaying the middle line (50.5%)
Show 29.5 Line - additional level 29.5%
Show 70.5 Line - additional level 70.5%
Show 88 Line - additional level 88%
Extensions Fibonacci
There are 6 customizable extension levels available:
Ext#1 (default 1.0)
Ext#2 (default 1.27)
Ext#3 (default 1.62)
Ext#4 (default 2.0)
Ext#5 (default 2.62)
Ext#6 (default 3.62)
For each level, you can configure:
On/Off
Color
Meaning
Alerts
The indicator provides the following types of alerts:
Entering/Exiting OTE Zones:
Entering 70% OTE Zone
Exiting 70% OTE Zone
Entering 30% OTE Zone
Exiting 30% OTE Zone
Crossing Additional Levels:
Crossing 29.5% Level
Crossing 70.5% Level
Crossing 88% Level
Reaching Extension Levels Fibonacci:
Alerts for each configured extension level
Support for both positive and negative extensions
Usage
Add the indicator to the chart
Configure the required display parameters
Set alerts if necessary
Use OTE zones to identify potential entry points into the market
Notes
The indicator automatically updates when the visible area of the chart changes
When using a custom date range, make sure the selected period contains data
For correct operation with a higher time frame, make sure that historical data is available
Visible and Anchored OTE chart
Индикатор для визуализации ценовых уровней и зон оптимальной торговли (OTE - Optimal Trading Entry) с использованием уровней Фибоначчи.
Основные возможности
Визуализация ценовых диапазонов с помощью двух OTE зон:
OTE 70% (79-62 уровни Фибоначчи)
OTE 30% (21-38 уровни Фибоначчи)
Настройка временных периодов:
Возможность использования пользовательского диапазона дат
Опция работы с высшим таймфреймом
Гибкая настройка отображения:
Выбор между использованием тел свечей или полного диапазона для привязки
Настраиваемый внешний вид боксов OTE
Настраиваемые текстовые метки
Дополнительные уровни:
Средняя линия (50.5%)
Опциональные уровни 29.5%, 70.5% и 88%
Настраиваемые расширения Фибоначчи
Настройка индикатора
Основные параметры
Use Custom Dates - включение пользовательского диапазона дат
Start Date/End Date - установка временного диапазона
Use Higher Timeframe - использование высшего таймфрейма
Higher Timeframe - выбор высшего таймфрейма
Настройка OTE зон
Show Fib Box - отображение зон OTE
Enable Fib Box 79-62 - включение зоны OTE 70%
Enable Fib Box 21-38 - включение зоны OTE 30%
Show Text - отображение текстовых меток в зонах
Визуальное оформление
Text Size - размер текста (tiny/small/medium/large)
Text Color - цвет текста
Text Alignment - выравнивание текста
Line Thickness - толщина линий (1-4)
Line Style - стиль линий (Solid/Dashed/Dotted)
Уровни Фибоначчи
High/Low Lines - отображение крайних уровней
Midline - отображение средней линии (50.5%)
Show 29.5 Line - дополнительный уровень 29.5%
Show 70.5 Line - дополнительный уровень 70.5%
Show 88 Line - дополнительный уровень 88%
Расширения Фибоначчи
Доступно 6 настраиваемых уровней расширения:
Ext#1 (по умолчанию 1.0)
Ext#2 (по умолчанию 1.27)
Ext#3 (по умолчанию 1.62)
Ext#4 (по умолчанию 2.0)
Ext#5 (по умолчанию 2.62)
Ext#6 (по умолчанию 3.62)
Для каждого уровня можно настроить:
Включение/выключение
Цвет
Значение
Оповещения
Индикатор предоставляет следующие типы оповещений:
Вход/выход из зон OTE:
Вход в зону OTE 70%
Выход из зоны OTE 70%
Вход в зону OTE 30%
Выход из зоны OTE 30%
Пересечение дополнительных уровней:
Пересечение уровня 29.5%
Пересечение уровня 70.5%
Пересечение уровня 88%
Достижение уровней расширения Фибоначчи:
Оповещения для каждого настроенного уровня расширения
Поддержка как положительных, так и отрицательных расширений
Использование
Добавьте индикатор на график
Настройте необходимые параметры отображения
При необходимости установите оповещения
Используйте зоны OTE для определения потенциальных точек входа в рынок
Примечания
Индикатор автоматически обновляется при изменении видимой области графика
При использовании пользовательского диапазона дат убедитесь, что выбранный период содержит данные
Для корректной работы с высшим таймфреймом убедитесь в доступности исторических данных
analytics_tablesLibrary "analytics_tables"
📝 Description
This library provides the implementation of several performance-related statistics and metrics, presented in the form of tables.
The metrics shown in the afforementioned tables where developed during the past years of my in-depth analalysis of various strategies in an atempt to reason about the performance of each strategy.
The visualization and some statistics where inspired by the existing implementations of the "Seasonality" script, and the performance matrix implementations of @QuantNomad and @ZenAndTheArtOfTrading scripts.
While this library is meant to be used by my strategy framework "Template Trailing Strategy (Backtester)" script, I wrapped it in a library hoping this can be usefull for other community strategy scripts that will be released in the future.
🤔 How to Guide
To use the functionality this library provides in your script you have to import it first!
Copy the import statement of the latest release by pressing the copy button below and then paste it into your script. Give a short name to this library so you can refer to it later on. The import statement should look like this:
import jason5480/analytics_tables/1 as ant
There are three types of tables provided by this library in the initial release. The stats table the metrics table and the seasonality table.
Each one shows different kinds of performance statistics.
The table UDT shall be initialized once using the `init()` method.
They can be updated using the `update()` method where the updated data UDT object shall be passed.
The data UDT can also initialized and get updated on demend depending on the use case
A code example for the StatsTable is the following:
var ant.StatsData statsData = ant.StatsData.new()
statsData.update(SideStats.new(), SideStats.new(), 0)
if (barstate.islastconfirmedhistory or (barstate.isrealtime and barstate.isconfirmed))
var statsTable = ant.StatsTable.new().init(ant.getTablePos('TOP', 'RIGHT'))
statsTable.update(statsData)
A code example for the MetricsTable is the following:
var ant.StatsData statsData = ant.StatsData.new()
statsData.update(ant.SideStats.new(), ant.SideStats.new(), 0)
if (barstate.islastconfirmedhistory or (barstate.isrealtime and barstate.isconfirmed))
var metricsTable = ant.MetricsTable.new().init(ant.getTablePos('BOTTOM', 'RIGHT'))
metricsTable.update(statsData, 10)
A code example for the SeasonalityTable is the following:
var ant.SeasonalData seasonalData = ant.SeasonalData.new().init(Seasonality.monthOfYear)
seasonalData.update()
if (barstate.islastconfirmedhistory or (barstate.isrealtime and barstate.isconfirmed))
var seasonalTable = ant.SeasonalTable.new().init(seasonalData, ant.getTablePos('BOTTOM', 'LEFT'))
seasonalTable.update(seasonalData)
🏋️♂️ Please refer to the "EXAMPLE" regions of the script for more advanced and up to date code examples!
Special thanks to @Mrcrbw for the proposal to develop this library and @DCNeu for the constructive feedback 🏆.
getTablePos(ypos, xpos)
Get table position compatible string
Parameters:
ypos (simple string) : The position on y axise
xpos (simple string) : The position on x axise
Returns: The position to be passed to the table
method init(this, pos, height, width, positiveTxtColor, negativeTxtColor, neutralTxtColor, positiveBgColor, negativeBgColor, neutralBgColor)
Initialize the stats table object with the given colors in the given position
Namespace types: StatsTable
Parameters:
this (StatsTable) : The stats table object
pos (simple string) : The table position string
height (simple float) : The height of the table as a percentage of the charts height. By default, 0 auto-adjusts the height based on the text inside the cells
width (simple float) : The width of the table as a percentage of the charts height. By default, 0 auto-adjusts the width based on the text inside the cells
positiveTxtColor (simple color) : The text color when positive
negativeTxtColor (simple color) : The text color when negative
neutralTxtColor (simple color) : The text color when neutral
positiveBgColor (simple color) : The background color with transparency when positive
negativeBgColor (simple color) : The background color with transparency when negative
neutralBgColor (simple color) : The background color with transparency when neutral
method init(this, pos, height, width, neutralBgColor)
Initialize the metrics table object with the given colors in the given position
Namespace types: MetricsTable
Parameters:
this (MetricsTable) : The metrics table object
pos (simple string) : The table position string
height (simple float) : The height of the table as a percentage of the charts height. By default, 0 auto-adjusts the height based on the text inside the cells
width (simple float) : The width of the table as a percentage of the charts width. By default, 0 auto-adjusts the width based on the text inside the cells
neutralBgColor (simple color) : The background color with transparency when neutral
method init(this, seas)
Initialize the seasonal data
Namespace types: SeasonalData
Parameters:
this (SeasonalData) : The seasonal data object
seas (simple Seasonality) : The seasonality of the matrix data
method init(this, data, pos, maxNumOfYears, height, width, extended, neutralTxtColor, neutralBgColor)
Initialize the seasonal table object with the given colors in the given position
Namespace types: SeasonalTable
Parameters:
this (SeasonalTable) : The seasonal table object
data (SeasonalData) : The seasonality data of the table
pos (simple string) : The table position string
maxNumOfYears (simple int) : The maximum number of years that fit into the table
height (simple float) : The height of the table as a percentage of the charts height. By default, 0 auto-adjusts the height based on the text inside the cells
width (simple float) : The width of the table as a percentage of the charts width. By default, 0 auto-adjusts the width based on the text inside the cells
extended (simple bool) : The seasonal table with extended columns for performance
neutralTxtColor (simple color) : The text color when neutral
neutralBgColor (simple color) : The background color with transparency when neutral
method update(this, wins, losses, numOfInconclusiveExits)
Update the strategy info data of the strategy
Namespace types: StatsData
Parameters:
this (StatsData) : The strategy statistics object
wins (SideStats)
losses (SideStats)
numOfInconclusiveExits (int) : The number of inconclusive trades
method update(this, stats, positiveTxtColor, negativeTxtColor, negativeBgColor, neutralBgColor)
Update the stats table object with the given data
Namespace types: StatsTable
Parameters:
this (StatsTable) : The stats table object
stats (StatsData) : The stats data to update the table
positiveTxtColor (simple color) : The text color when positive
negativeTxtColor (simple color) : The text color when negative
negativeBgColor (simple color) : The background color with transparency when negative
neutralBgColor (simple color) : The background color with transparency when neutral
method update(this, stats, buyAndHoldPerc, positiveTxtColor, negativeTxtColor, positiveBgColor, negativeBgColor)
Update the metrics table object with the given data
Namespace types: MetricsTable
Parameters:
this (MetricsTable) : The metrics table object
stats (StatsData) : The stats data to update the table
buyAndHoldPerc (float) : The buy and hold percetage
positiveTxtColor (simple color) : The text color when positive
negativeTxtColor (simple color) : The text color when negative
positiveBgColor (simple color) : The background color with transparency when positive
negativeBgColor (simple color) : The background color with transparency when negative
method update(this)
Update the seasonal data based on the season and eon timeframe
Namespace types: SeasonalData
Parameters:
this (SeasonalData) : The seasonal data object
method update(this, data, positiveTxtColor, negativeTxtColor, neutralTxtColor, positiveBgColor, negativeBgColor, neutralBgColor, timeBgColor)
Update the seasonal table object with the given data
Namespace types: SeasonalTable
Parameters:
this (SeasonalTable) : The seasonal table object
data (SeasonalData) : The seasonal cell data to update the table
positiveTxtColor (simple color) : The text color when positive
negativeTxtColor (simple color) : The text color when negative
neutralTxtColor (simple color) : The text color when neutral
positiveBgColor (simple color) : The background color with transparency when positive
negativeBgColor (simple color) : The background color with transparency when negative
neutralBgColor (simple color) : The background color with transparency when neutral
timeBgColor (simple color) : The background color of the time gradient
SideStats
Object that represents the strategy statistics data of one side win or lose
Fields:
numOf (series int)
sumFreeProfit (series float)
freeProfitStDev (series float)
sumProfit (series float)
profitStDev (series float)
sumGain (series float)
gainStDev (series float)
avgQuantityPerc (series float)
avgCapitalRiskPerc (series float)
avgTPExecutedCount (series float)
avgRiskRewardRatio (series float)
maxStreak (series int)
StatsTable
Object that represents the stats table
Fields:
table (series table) : The actual table
rows (series int) : The number of rows of the table
columns (series int) : The number of columns of the table
StatsData
Object that represents the statistics data of the strategy
Fields:
wins (SideStats)
losses (SideStats)
numOfInconclusiveExits (series int)
avgFreeProfitStr (series string)
freeProfitStDevStr (series string)
lossFreeProfitStDevStr (series string)
avgProfitStr (series string)
profitStDevStr (series string)
lossProfitStDevStr (series string)
avgQuantityStr (series string)
MetricsTable
Object that represents the metrics table
Fields:
table (series table) : The actual table
rows (series int) : The number of rows of the table
columns (series int) : The number of columns of the table
SeasonalData
Object that represents the seasonal table dynamic data
Fields:
seasonality (series Seasonality)
eonToMatrixRow (map)
numOfEons (series int)
mostRecentMatrixRow (series int)
balances (matrix)
returnPercs (matrix)
maxDDs (matrix)
eonReturnPercs (array)
eonCAGRs (array)
eonMaxDDs (array)
SeasonalTable
Object that represents the seasonal table
Fields:
table (series table) : The actual table
headRows (series int) : The number of head rows of the table
headColumns (series int) : The number of head columns of the table
eonRows (series int) : The number of eon rows of the table
seasonColumns (series int) : The number of season columns of the table
statsRows (series int)
statsColumns (series int) : The number of stats columns of the table
rows (series int) : The number of rows of the table
columns (series int) : The number of columns of the table
extended (series bool) : Whether the table has additional performance statistics
BooBee Digital - Enhanced Buy & Sell Alerts Suite
BooBee Digital - Enhanced Buy & Sell Alerts Suite
Introduction:
The “BooBee Digital - Enhanced Buy & Sell Alerts Suite” is a comprehensive trading tool designed to provide traders with precise buy and sell signals by integrating the Average True Range (ATR) trailing stop technique and the Volume Weighted Average Price (VWAP) indicator. This script is tailored to help traders make informed decisions by considering both market volatility and trading volume.
How It Works:
1. ATR Calculation:
• Purpose: Measures market volatility to set dynamic stop levels.
• Details: The Average True Range (ATR) is calculated over a user-defined period. The ATR value reflects the average range of price movements over the specified period, which is crucial for assessing market volatility.
2. ATR Trailing Stop:
• Purpose: Identifies potential trend reversals by setting trailing stops based on market volatility.
• Details: The ATR trailing stop is dynamically adjusted using the ATR value and a user-defined sensitivity factor. This trailing stop level helps identify trend reversals by moving in accordance with price fluctuations.
3. VWAP Calculation:
• Purpose: Provides a volume-weighted average price to benchmark fair value.
• Details: The VWAP is calculated by taking the sum of the product of price and volume, divided by the total volume. This indicator gives traders a reference point for the average price at which the asset has traded throughout the day, considering trading volume.
4. EMA Crossover:
• Purpose: Adds a confirmation layer for buy and sell signals.
• Details: A 1-period Exponential Moving Average (EMA) is used to identify short-term price movements. Buy and sell signals are generated based on the crossover of the EMA and the ATR trailing stop, adding an extra layer of confirmation for trade entries and exits.
Signal Generation:
Buy Signal:
• Generated when the price is above the ATR trailing stop and there is a bullish crossover of the EMA and ATR trailing stop.
• Indicator: Green label below the bar with “Buy” text.
Sell Signal:
• Generated when the price is below the ATR trailing stop and there is a bearish crossover of the EMA and ATR trailing stop.
• Indicator: Red label above the bar with “Sell” text.
VWAP Line:
• The VWAP line is plotted on the chart to help traders identify significant price levels based on trading volume.
• Indicator: Blue line representing the VWAP.
How to Use:
• Chart Type: The script is designed for use on standard chart types such as Candlestick and OHLC. It does not support non-standard chart types like Heikin Ashi, Renko, Kagi, Point & Figure, and Range, as they may produce unrealistic results.
• Clean Chart: Ensure your chart is clean and free of other indicators to avoid confusion. The signals and colors plotted by the script should be easily identifiable.
• Trade Confirmation: Use the buy and sell signals generated by the script in conjunction with other analysis methods to confirm trades.
Key Concepts:
• ATR Trailing Stop: This technique sets dynamic stop levels based on market volatility, helping to identify trend reversals.
• VWAP: This indicator provides a benchmark for the average price considering trading volume, helping traders identify fair value.
• EMA Crossover: This adds a layer of confirmation for buy and sell signals, improving the accuracy of trade entries and exits.
IndicatorsLibrary "Indicators"
this has a calculation for the most used indicators.
macd4C(fastMa, slowMa)
this calculates macd 4c
Parameters:
fastMa (simple int) : is the period for the fast ma. the minimum value is 7
slowMa (simple int) : is the period for the slow ma. the minimum value is 7
Returns: the macd 4c value for the current bar
rsi(rsiSourceInput, rsiLengthInput)
this calculates rsi
Parameters:
rsiSourceInput (float) : is the source for the rsi
rsiLengthInput (simple int) : is the period for the rsi
Returns: the rsi value for the current bar
ao(source, fastPeriod, slowPeriod)
this calculates ao
Parameters:
source (float) : is the source for the ao
fastPeriod (int) : is the period for the fast ma
slowPeriod (int) : is the period for the slow ma
Returns: the ao value for the current bar
kernelAoOscillator(kernelFastLookback, kernelSlowLookback, kernelFastWeight, kernelSlowWeight, kernelFastRegressionStart, kernelSlowRegressionStart, kernelFastSmoothPeriod, kernelSlowSmoothPeriod, kernelFastSmooth, kernelSlowSmooth, source)
this calculates our own kernel ao oscillator which we made
Parameters:
kernelFastLookback (simple int)
kernelSlowLookback (simple int)
kernelFastWeight (simple float)
kernelSlowWeight (simple float)
kernelFastRegressionStart (simple int)
kernelSlowRegressionStart (simple int)
kernelFastSmoothPeriod (int)
kernelSlowSmoothPeriod (int)
kernelFastSmooth (bool)
kernelSlowSmooth (bool)
source (float) : is the source for the ao
Returns: the kernel ao oscillator value for the current bar, the colors for both the fast and slow kernel, the fast & slow kernel
signalLineKernel(lag, h, r, x_0, smoothColors, _src, c_bullish, c_bearish)
Parameters:
lag (int)
h (float)
r (float)
x_0 (int)
smoothColors (bool)
_src (float)
c_bullish (color)
c_bearish (color)
zigzagCalc(Depth, Deviation, Backstep, repaint, Show_zz, line_thick, text_color)
Parameters:
Depth (int)
Deviation (int)
Backstep (int)
repaint (bool)
Show_zz (bool)
line_thick (int)
text_color (color)
Asay (1982) Margined Futures Option Pricing Model [Loxx]Asay (1982) Margined Futures Option Pricing Model is an adaptation of the Black-Scholes-Merton Option Pricing Model including Analytical Greeks and implied volatility calculations. The following information is an excerpt from Espen Gaarder Haug's book "Option Pricing Formulas". This version is to price Options on Futures where premium is fully margined. This means the Risk-free Rate, dividend, and cost to carry are all zero. The options sensitivities (Greeks) are the partial derivatives of the Black-Scholes-Merton ( BSM ) formula. Analytical Greeks for our purposes here are broken down into various categories:
Delta Greeks: Delta, DDeltaDvol, Elasticity
Gamma Greeks: Gamma, GammaP, DGammaDvol, Speed
Vega Greeks: Vega , DVegaDvol/Vomma, VegaP
Theta Greeks: Theta
Probability Greeks: StrikeDelta, Risk Neutral Density
(See the code for more details)
Black-Scholes-Merton Option Pricing
The Black-Scholes-Merton model can be "generalized" by incorporating a cost-of-carry rate b. This model can be used to price European options on stocks, stocks paying a continuous dividend yield, options on futures , and currency options:
c = S * e^((b - r) * T) * N(d1) - X * e^(-r * T) * N(d2)
p = X * e^(-r * T) * N(-d2) - S * e^((b - r) * T) * N(-d1)
where
d1 = (log(S / X) + (b + v^2 / 2) * T) / (v * T^0.5)
d2 = d1 - v * T^0.5
b = r ... gives the Black and Scholes (1973) stock option model.
b = r — q ... gives the Merton (1973) stock option model with continuous dividend yield q.
b = 0 ... gives the Black (1976) futures option model.
b = 0 and r = 0 ... gives the Asay (1982) margined futures option model. <== this is the one used for this indicator!
b = r — rf ... gives the Garman and Kohlhagen (1983) currency option model.
Inputs
S = Stock price.
X = Strike price of option.
T = Time to expiration in years.
r = Risk-free rate
d = dividend yield
v = Volatility of the underlying asset price
cnd (x) = The cumulative normal distribution function
nd(x) = The standard normal density function
convertingToCCRate(r, cmp ) = Rate compounder
gImpliedVolatilityNR(string CallPutFlag, float S, float x, float T, float r, float b, float cm , float epsilon) = Implied volatility via Newton Raphson
gBlackScholesImpVolBisection(string CallPutFlag, float S, float x, float T, float r, float b, float cm ) = implied volatility via bisection
Implied Volatility: The Bisection Method
The Newton-Raphson method requires knowledge of the partial derivative of the option pricing formula with respect to volatility ( vega ) when searching for the implied volatility . For some options (exotic and American options in particular), vega is not known analytically. The bisection method is an even simpler method to estimate implied volatility when vega is unknown. The bisection method requires two initial volatility estimates (seed values):
1. A "low" estimate of the implied volatility , al, corresponding to an option value, CL
2. A "high" volatility estimate, aH, corresponding to an option value, CH
The option market price, Cm , lies between CL and cH . The bisection estimate is given as the linear interpolation between the two estimates:
v(i + 1) = v(L) + (c(m) - c(L)) * (v(H) - v(L)) / (c(H) - c(L))
Replace v(L) with v(i + 1) if c(v(i + 1)) < c(m), or else replace v(H) with v(i + 1) if c(v(i + 1)) > c(m) until |c(m) - c(v(i + 1))| <= E, at which point v(i + 1) is the implied volatility and E is the desired degree of accuracy.
Implied Volatility: Newton-Raphson Method
The Newton-Raphson method is an efficient way to find the implied volatility of an option contract. It is nothing more than a simple iteration technique for solving one-dimensional nonlinear equations (any introductory textbook in calculus will offer an intuitive explanation). The method seldom uses more than two to three iterations before it converges to the implied volatility . Let
v(i + 1) = v(i) + (c(v(i)) - c(m)) / (dc / dv (i))
until |c(m) - c(v(i + 1))| <= E at which point v(i + 1) is the implied volatility , E is the desired degree of accuracy, c(m) is the market price of the option, and dc/ dv (i) is the vega of the option evaluaated at v(i) (the sensitivity of the option value for a small change in volatility ).
Things to know
Only works on the daily timeframe and for the current source price.
You can adjust the text size to fit the screen
Black-76 Options on Futures [Loxx]Black-76 Options on Futures is an adaptation of the Black-Scholes-Merton Option Pricing Model including Analytical Greeks and implied volatility calculations. The following information is an excerpt from Espen Gaarder Haug's book "Option Pricing Formulas". This version is to price Options on Futures. The options sensitivities (Greeks) are the partial derivatives of the Black-Scholes-Merton ( BSM ) formula. Analytical Greeks for our purposes here are broken down into various categories:
Delta Greeks: Delta, DDeltaDvol, Elasticity
Gamma Greeks: Gamma, GammaP, DGammaDvol, Speed
Vega Greeks: Vega , DVegaDvol/Vomma, VegaP
Theta Greeks: Theta
Rate/Carry Greeks: Rho futures option
Probability Greeks: StrikeDelta, Risk Neutral Density
(See the code for more details)
Black-Scholes-Merton Option Pricing
The Black-Scholes-Merton model can be "generalized" by incorporating a cost-of-carry rate b. This model can be used to price European options on stocks, stocks paying a continuous dividend yield, options on futures , and currency options:
c = S * e^((b - r) * T) * N(d1) - X * e^(-r * T) * N(d2)
p = X * e^(-r * T) * N(-d2) - S * e^((b - r) * T) * N(-d1)
where
d1 = (log(S / X) + (b + v^2 / 2) * T) / (v * T^0.5)
d2 = d1 - v * T^0.5
b = r ... gives the Black and Scholes (1973) stock option model.
b = r — q ... gives the Merton (1973) stock option model with continuous dividend yield q.
b = 0 ... gives the Black (1976) futures option model. <== this is the one used for this indicator!
b = 0 and r = 0 ... gives the Asay (1982) margined futures option model.
b = r — rf ... gives the Garman and Kohlhagen (1983) currency option model.
Inputs
S = Stock price.
X = Strike price of option.
T = Time to expiration in years.
r = Risk-free rate
d = dividend yield
v = Volatility of the underlying asset price
cnd (x) = The cumulative normal distribution function
nd(x) = The standard normal density function
convertingToCCRate(r, cmp ) = Rate compounder
gImpliedVolatilityNR(string CallPutFlag, float S, float x, float T, float r, float b, float cm , float epsilon) = Implied volatility via Newton Raphson
gBlackScholesImpVolBisection(string CallPutFlag, float S, float x, float T, float r, float b, float cm ) = implied volatility via bisection
Implied Volatility: The Bisection Method
The Newton-Raphson method requires knowledge of the partial derivative of the option pricing formula with respect to volatility ( vega ) when searching for the implied volatility . For some options (exotic and American options in particular), vega is not known analytically. The bisection method is an even simpler method to estimate implied volatility when vega is unknown. The bisection method requires two initial volatility estimates (seed values):
1. A "low" estimate of the implied volatility , al, corresponding to an option value, CL
2. A "high" volatility estimate, aH, corresponding to an option value, CH
The option market price, Cm , lies between CL and cH . The bisection estimate is given as the linear interpolation between the two estimates:
v(i + 1) = v(L) + (c(m) - c(L)) * (v(H) - v(L)) / (c(H) - c(L))
Replace v(L) with v(i + 1) if c(v(i + 1)) < c(m), or else replace v(H) with v(i + 1) if c(v(i + 1)) > c(m) until |c(m) - c(v(i + 1))| <= E, at which point v(i + 1) is the implied volatility and E is the desired degree of accuracy.
Implied Volatility: Newton-Raphson Method
The Newton-Raphson method is an efficient way to find the implied volatility of an option contract. It is nothing more than a simple iteration technique for solving one-dimensional nonlinear equations (any introductory textbook in calculus will offer an intuitive explanation). The method seldom uses more than two to three iterations before it converges to the implied volatility . Let
v(i + 1) = v(i) + (c(v(i)) - c(m)) / (dc / dv (i))
until |c(m) - c(v(i + 1))| <= E at which point v(i + 1) is the implied volatility , E is the desired degree of accuracy, c(m) is the market price of the option, and dc/ dv (i) is the vega of the option evaluaated at v(i) (the sensitivity of the option value for a small change in volatility ).
Things to know
Only works on the daily timeframe and for the current source price.
You can adjust the text size to fit the screen
Garman and Kohlhagen (1983) for Currency Options [Loxx]Garman and Kohlhagen (1983) for Currency Options is an adaptation of the Black-Scholes-Merton Option Pricing Model including Analytical Greeks and implied volatility calculations. The following information is an excerpt from Espen Gaarder Haug's book "Option Pricing Formulas". This version of BSMOPM is to price Currency Options. The options sensitivities (Greeks) are the partial derivatives of the Black-Scholes-Merton ( BSM ) formula. Analytical Greeks for our purposes here are broken down into various categories:
Delta Greeks: Delta, DDeltaDvol, Elasticity
Gamma Greeks: Gamma, GammaP, DGammaDSpot/speed, DGammaDvol/Zomma
Vega Greeks: Vega , DVegaDvol/Vomma, VegaP, Speed
Theta Greeks: Theta
Rate/Carry Greeks: Rho, Rho futures option, Carry Rho, Phi/Rho2
Probability Greeks: StrikeDelta, Risk Neutral Density
(See the code for more details)
Black-Scholes-Merton Option Pricing for Currency Options
The Garman and Kohlhagen (1983) modified Black-Scholes model can be used to price European currency options; see also Grabbe (1983). The model is mathematically equivalent to the Merton (1973) model presented earlier. The only difference is that the dividend yield is replaced by the risk-free rate of the foreign currency rf:
c = S * e^(-rf * T) * N(d1) - X * e^(-r * T) * N(d2)
p = X * e^(-r * T) * N(-d2) - S * e^(-rf * T) * N(-d1)
where
d1 = (log(S / X) + (r - rf + v^2 / 2) * T) / (v * T^0.5)
d2 = d1 - v * T^0.5
For more information on currency options, see DeRosa (2000)
Inputs
S = Stock price.
X = Strike price of option.
T = Time to expiration in years.
r = Risk-free rate
rf = Risk-free rate of the foreign currency
v = Volatility of the underlying asset price
cnd (x) = The cumulative normal distribution function
nd(x) = The standard normal density function
convertingToCCRate(r, cmp ) = Rate compounder
gImpliedVolatilityNR(string CallPutFlag, float S, float x, float T, float r, float b, float cm , float epsilon) = Implied volatility via Newton Raphson
gBlackScholesImpVolBisection(string CallPutFlag, float S, float x, float T, float r, float b, float cm ) = implied volatility via bisection
Implied Volatility: The Bisection Method
The Newton-Raphson method requires knowledge of the partial derivative of the option pricing formula with respect to volatility ( vega ) when searching for the implied volatility . For some options (exotic and American options in particular), vega is not known analytically. The bisection method is an even simpler method to estimate implied volatility when vega is unknown. The bisection method requires two initial volatility estimates (seed values):
1. A "low" estimate of the implied volatility , al, corresponding to an option value, CL
2. A "high" volatility estimate, aH, corresponding to an option value, CH
The option market price, Cm , lies between CL and cH . The bisection estimate is given as the linear interpolation between the two estimates:
v(i + 1) = v(L) + (c(m) - c(L)) * (v(H) - v(L)) / (c(H) - c(L))
Replace v(L) with v(i + 1) if c(v(i + 1)) < c(m), or else replace v(H) with v(i + 1) if c(v(i + 1)) > c(m) until |c(m) - c(v(i + 1))| <= E, at which point v(i + 1) is the implied volatility and E is the desired degree of accuracy.
Implied Volatility: Newton-Raphson Method
The Newton-Raphson method is an efficient way to find the implied volatility of an option contract. It is nothing more than a simple iteration technique for solving one-dimensional nonlinear equations (any introductory textbook in calculus will offer an intuitive explanation). The method seldom uses more than two to three iterations before it converges to the implied volatility . Let
v(i + 1) = v(i) + (c(v(i)) - c(m)) / (dc / dv (i))
until |c(m) - c(v(i + 1))| <= E at which point v(i + 1) is the implied volatility , E is the desired degree of accuracy, c(m) is the market price of the option, and dc/ dv (i) is the vega of the option evaluaated at v(i) (the sensitivity of the option value for a small change in volatility ).
Things to know
Only works on the daily timeframe and for the current source price.
You can adjust the text size to fit the screen
Related indicators:
BSM OPM 1973 w/ Continuous Dividend Yield
Black-Scholes 1973 OPM on Non-Dividend Paying Stocks
Generalized Black-Scholes-Merton w/ Analytical Greeks
Generalized Black-Scholes-Merton Option Pricing Formula
Sprenkle 1964 Option Pricing Model w/ Num. Greeks
Modified Bachelier Option Pricing Model w/ Num. Greeks
Bachelier 1900 Option Pricing Model w/ Numerical Greeks
BSM OPM 1973 w/ Continuous Dividend Yield [Loxx]Generalized Black-Scholes-Merton w/ Analytical Greeks is an adaptation of the Black-Scholes-Merton Option Pricing Model including Analytical Greeks and implied volatility calculations. The following information is an excerpt from Espen Gaarder Haug's book "Option Pricing Formulas". The options sensitivities (Greeks) are the partial derivatives of the Black-Scholes-Merton ( BSM ) formula. Analytical Greeks for our purposes here are broken down into various categories:
Delta Greeks: Delta, DDeltaDvol, Elasticity
Gamma Greeks: Gamma, GammaP, DGammaDSpot/speed, DGammaDvol/Zomma
Vega Greeks: Vega , DVegaDvol/Vomma, VegaP
Theta Greeks: Theta
Rate/Carry Greeks: Rho, Rho futures option, Carry Rho, Phi/Rho2
Probability Greeks: StrikeDelta, Risk Neutral Density
(See the code for more details)
Black-Scholes-Merton Option Pricing
The Black-Scholes-Merton model can be "generalized" by incorporating a cost-of-carry rate b. This model can be used to price European options on stocks, stocks paying a continuous dividend yield, options on futures, and currency options:
c = S * e^((b - r) * T) * N(d1) - X * e^(-r * T) * N(d2)
p = X * e^(-r * T) * N(-d2) - S * e^((b - r) * T) * N(-d1)
where
d1 = (log(S / X) + (b + v^2 / 2) * T) / (v * T^0.5)
d2 = d1 - v * T^0.5
b = r ... gives the Black and Scholes (1973) stock option model.
b = r — q ... gives the Merton (1973) stock option model with continuous dividend yield q. <== this is the one used for this indicator!
b = 0 ... gives the Black (1976) futures option model.
b = 0 and r = 0 ... gives the Asay (1982) margined futures option model.
b = r — rf ... gives the Garman and Kohlhagen (1983) currency option model.
Inputs
S = Stock price.
X = Strike price of option.
T = Time to expiration in years.
r = Risk-free rate
d = dividend yield
v = Volatility of the underlying asset price
cnd (x) = The cumulative normal distribution function
nd(x) = The standard normal density function
convertingToCCRate(r, cmp ) = Rate compounder
gImpliedVolatilityNR(string CallPutFlag, float S, float x, float T, float r, float b, float cm , float epsilon) = Implied volatility via Newton Raphson
gBlackScholesImpVolBisection(string CallPutFlag, float S, float x, float T, float r, float b, float cm ) = implied volatility via bisection
Implied Volatility: The Bisection Method
The Newton-Raphson method requires knowledge of the partial derivative of the option pricing formula with respect to volatility ( vega ) when searching for the implied volatility . For some options (exotic and American options in particular), vega is not known analytically. The bisection method is an even simpler method to estimate implied volatility when vega is unknown. The bisection method requires two initial volatility estimates (seed values):
1. A "low" estimate of the implied volatility , al, corresponding to an option value, CL
2. A "high" volatility estimate, aH, corresponding to an option value, CH
The option market price, Cm , lies between CL and cH . The bisection estimate is given as the linear interpolation between the two estimates:
v(i + 1) = v(L) + (c(m) - c(L)) * (v(H) - v(L)) / (c(H) - c(L))
Replace v(L) with v(i + 1) if c(v(i + 1)) < c(m), or else replace v(H) with v(i + 1) if c(v(i + 1)) > c(m) until |c(m) - c(v(i + 1))| <= E, at which point v(i + 1) is the implied volatility and E is the desired degree of accuracy.
Implied Volatility: Newton-Raphson Method
The Newton-Raphson method is an efficient way to find the implied volatility of an option contract. It is nothing more than a simple iteration technique for solving one-dimensional nonlinear equations (any introductory textbook in calculus will offer an intuitive explanation). The method seldom uses more than two to three iterations before it converges to the implied volatility . Let
v(i + 1) = v(i) + (c(v(i)) - c(m)) / (dc / dv (i))
until |c(m) - c(v(i + 1))| <= E at which point v(i + 1) is the implied volatility , E is the desired degree of accuracy, c(m) is the market price of the option, and dc/ dv (i) is the vega of the option evaluaated at v(i) (the sensitivity of the option value for a small change in volatility ).
Things to know
Only works on the daily timeframe and for the current source price.
You can adjust the text size to fit the screen
Black-Scholes 1973 OPM on Non-Dividend Paying Stocks [Loxx]Black-Scholes 1973 OPM on Non-Dividend Paying Stocks is an adaptation of the Black-Scholes-Merton Option Pricing Model including Analytical Greeks and implied volatility calculations. Making b equal to r yields the BSM model where dividends are not considered. The following information is an excerpt from Espen Gaarder Haug's book "Option Pricing Formulas". The options sensitivities (Greeks) are the partial derivatives of the Black-Scholes-Merton ( BSM ) formula. For our purposes here are, Analytical Greeks are broken down into various categories:
Delta Greeks: Delta, DDeltaDvol, Elasticity
Gamma Greeks: Gamma, GammaP, DGammaDSpot/speed, DGammaDvol/Zomma
Vega Greeks: Vega , DVegaDvol/Vomma, VegaP
Theta Greeks: Theta
Rate/Carry Greeks: Rho
Probability Greeks: StrikeDelta, Risk Neutral Density
(See the code for more details)
Black-Scholes-Merton Option Pricing
The BSM formula and its binomial counterpart may easily be the most used "probability model/tool" in everyday use — even if we con- sider all other scientific disciplines. Literally tens of thousands of people, including traders, market makers, and salespeople, use option formulas several times a day. Hardly any other area has seen such dramatic growth as the options and derivatives businesses. In this chapter we look at the various versions of the basic option formula. In 1997 Myron Scholes and Robert Merton were awarded the Nobel Prize (The Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel). Unfortunately, Fischer Black died of cancer in 1995 before he also would have received the prize.
It is worth mentioning that it was not the option formula itself that Myron Scholes and Robert Merton were awarded the Nobel Prize for, the formula was actually already invented, but rather for the way they derived it — the replicating portfolio argument, continuous- time dynamic delta hedging, as well as making the formula consistent with the capital asset pricing model (CAPM). The continuous dynamic replication argument is unfortunately far from robust. The popularity among traders for using option formulas heavily relies on hedging options with options and on the top of this dynamic delta hedging, see Higgins (1902), Nelson (1904), Mello and Neuhaus (1998), Derman and Taleb (2005), as well as Haug (2006) for more details on this topic. In any case, this book is about option formulas and not so much about how to derive them.
Provided here are the various versions of the Black-Scholes-Merton formula presented in the literature. All formulas in this section are originally derived based on the underlying asset S follows a geometric Brownian motion
dS = mu * S * dt + v * S * dz
where t is the expected instantaneous rate of return on the underlying asset, a is the instantaneous volatility of the rate of return, and dz is a Wiener process.
The formula derived by Black and Scholes (1973) can be used to value a European option on a stock that does not pay dividends before the option's expiration date. Letting c and p denote the price of European call and put options, respectively, the formula states that
c = S * N(d1) - X * e^(-r * T) * N(d2)
p = X * e^(-r * T) * N(d2) - S * N(d1)
where
d1 = (log(S / X) + (r + v^2 / 2) * T) / (v * T^0.5)
d2 = (log(S / X) + (r - v^2 / 2) * T) / (v * T^0.5) = d1 - v * T^0.5
**This version of the Black-Scholes formula can also be used to price American call options on a non-dividend-paying stock, since it will never be optimal to exercise the option before expiration.**
Inputs
S = Stock price.
X = Strike price of option.
T = Time to expiration in years.
r = Risk-free rate
b = Cost of carry
v = Volatility of the underlying asset price
cnd (x) = The cumulative normal distribution function
nd(x) = The standard normal density function
convertingToCCRate(r, cmp ) = Rate compounder
gImpliedVolatilityNR(string CallPutFlag, float S, float x, float T, float r, float b, float cm , float epsilon) = Implied volatility via Newton Raphson
gBlackScholesImpVolBisection(string CallPutFlag, float S, float x, float T, float r, float b, float cm ) = implied volatility via bisection
Implied Volatility: The Bisection Method
The Newton-Raphson method requires knowledge of the partial derivative of the option pricing formula with respect to volatility ( vega ) when searching for the implied volatility . For some options (exotic and American options in particular), vega is not known analytically. The bisection method is an even simpler method to estimate implied volatility when vega is unknown. The bisection method requires two initial volatility estimates (seed values):
1. A "low" estimate of the implied volatility , al, corresponding to an option value, CL
2. A "high" volatility estimate, aH, corresponding to an option value, CH
The option market price, Cm , lies between CL and cH . The bisection estimate is given as the linear interpolation between the two estimates:
v(i + 1) = v(L) + (c(m) - c(L)) * (v(H) - v(L)) / (c(H) - c(L))
Replace v(L) with v(i + 1) if c(v(i + 1)) < c(m), or else replace v(H) with v(i + 1) if c(v(i + 1)) > c(m) until |c(m) - c(v(i + 1))| <= E, at which point v(i + 1) is the implied volatility and E is the desired degree of accuracy.
Implied Volatility: Newton-Raphson Method
The Newton-Raphson method is an efficient way to find the implied volatility of an option contract. It is nothing more than a simple iteration technique for solving one-dimensional nonlinear equations (any introductory textbook in calculus will offer an intuitive explanation). The method seldom uses more than two to three iterations before it converges to the implied volatility . Let
v(i + 1) = v(i) + (c(v(i)) - c(m)) / (dc / dv (i))
until |c(m) - c(v(i + 1))| <= E at which point v(i + 1) is the implied volatility , E is the desired degree of accuracy, c(m) is the market price of the option, and dc/ dv (i) is the vega of the option evaluaated at v(i) (the sensitivity of the option value for a small change in volatility ).
Things to know
Only works on the daily timeframe and for the current source price.
You can adjust the text size to fit the screen
Generalized Black-Scholes-Merton w/ Analytical Greeks [Loxx]Generalized Black-Scholes-Merton w/ Analytical Greeks is an adaptation of the Black-Scholes-Merton Option Pricing Model including Analytical Greeks and implied volatility calculations. The following information is an excerpt from Espen Gaarder Haug's book "Option Pricing Formulas". The options sensitivities (Greeks) are the partial derivatives of the Black-Scholes-Merton (BSM) formula. Analytical Greeks for our purposes here are broken down into various categories:
Delta Greeks: Delta, DDeltaDvol, Elasticity
Gamma Greeks: Gamma, GammaP, DGammaDSpot/speed, DGammaDvol/Zomma
Vega Greeks: Vega, DVegaDvol/Vomma, VegaP
Theta Greeks: Theta
Rate/Carry Greeks: Rho, Rho futures option, Carry Rho, Phi/Rho2
Probability Greeks: StrikeDelta, Risk Neutral Density
(See the code for more details)
Black-Scholes-Merton Option Pricing
The BSM formula and its binomial counterpart may easily be the most used "probability model/tool" in everyday use — even if we con- sider all other scientific disciplines. Literally tens of thousands of people, including traders, market makers, and salespeople, use option formulas several times a day. Hardly any other area has seen such dramatic growth as the options and derivatives businesses. In this chapter we look at the various versions of the basic option formula. In 1997 Myron Scholes and Robert Merton were awarded the Nobel Prize (The Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel). Unfortunately, Fischer Black died of cancer in 1995 before he also would have received the prize.
It is worth mentioning that it was not the option formula itself that Myron Scholes and Robert Merton were awarded the Nobel Prize for, the formula was actually already invented, but rather for the way they derived it — the replicating portfolio argument, continuous- time dynamic delta hedging, as well as making the formula consistent with the capital asset pricing model (CAPM). The continuous dynamic replication argument is unfortunately far from robust. The popularity among traders for using option formulas heavily relies on hedging options with options and on the top of this dynamic delta hedging, see Higgins (1902), Nelson (1904), Mello and Neuhaus (1998), Derman and Taleb (2005), as well as Haug (2006) for more details on this topic. In any case, this book is about option formulas and not so much about how to derive them.
Provided here are the various versions of the Black-Scholes-Merton formula presented in the literature. All formulas in this section are originally derived based on the underlying asset S follows a geometric Brownian motion
dS = mu * S * dt + v * S * dz
where t is the expected instantaneous rate of return on the underlying asset, a is the instantaneous volatility of the rate of return, and dz is a Wiener process.
The formula derived by Black and Scholes (1973) can be used to value a European option on a stock that does not pay dividends before the option's expiration date. Letting c and p denote the price of European call and put options, respectively, the formula states that
c = S * N(d1) - X * e^(-r * T) * N(d2)
p = X * e^(-r * T) * N(d2) - S * N(d1)
where
d1 = (log(S / X) + (r + v^2 / 2) * T) / (v * T^0.5)
d2 = (log(S / X) + (r - v^2 / 2) * T) / (v * T^0.5) = d1 - v * T^0.5
Inputs
S = Stock price.
X = Strike price of option.
T = Time to expiration in years.
r = Risk-free rate
b = Cost of carry
v = Volatility of the underlying asset price
cnd (x) = The cumulative normal distribution function
nd(x) = The standard normal density function
convertingToCCRate(r, cmp ) = Rate compounder
gImpliedVolatilityNR(string CallPutFlag, float S, float x, float T, float r, float b, float cm , float epsilon) = Implied volatility via Newton Raphson
gBlackScholesImpVolBisection(string CallPutFlag, float S, float x, float T, float r, float b, float cm ) = implied volatility via bisection
Implied Volatility: The Bisection Method
The Newton-Raphson method requires knowledge of the partial derivative of the option pricing formula with respect to volatility ( vega ) when searching for the implied volatility . For some options (exotic and American options in particular), vega is not known analytically. The bisection method is an even simpler method to estimate implied volatility when vega is unknown. The bisection method requires two initial volatility estimates (seed values):
1. A "low" estimate of the implied volatility , al, corresponding to an option value, CL
2. A "high" volatility estimate, aH, corresponding to an option value, CH
The option market price, Cm , lies between CL and cH . The bisection estimate is given as the linear interpolation between the two estimates:
v(i + 1) = v(L) + (c(m) - c(L)) * (v(H) - v(L)) / (c(H) - c(L))
Replace v(L) with v(i + 1) if c(v(i + 1)) < c(m), or else replace v(H) with v(i + 1) if c(v(i + 1)) > c(m) until |c(m) - c(v(i + 1))| <= E, at which point v(i + 1) is the implied volatility and E is the desired degree of accuracy.
Implied Volatility: Newton-Raphson Method
The Newton-Raphson method is an efficient way to find the implied volatility of an option contract. It is nothing more than a simple iteration technique for solving one-dimensional nonlinear equations (any introductory textbook in calculus will offer an intuitive explanation). The method seldom uses more than two to three iterations before it converges to the implied volatility . Let
v(i + 1) = v(i) + (c(v(i)) - c(m)) / (dc / dv (i))
until |c(m) - c(v(i + 1))| <= E at which point v(i + 1) is the implied volatility , E is the desired degree of accuracy, c(m) is the market price of the option, and dc/ dv (i) is the vega of the option evaluaated at v(i) (the sensitivity of the option value for a small change in volatility ).
Things to know
Only works on the daily timeframe and for the current source price.
You can adjust the text size to fit the screen
StapleIndicatorsLibrary "StapleIndicators"
This Library provides some common indicators commonly referenced from other studies in Pine Script
squeeze(bbSrc, bbPeriod, bbDev, kcSrc, kcPeriod, kcATR, signalPeriod) Volatility Squeeze
Parameters:
bbSrc : (Optional) Bollinger Bands Source. By default close
bbPeriod : (Optional) Bollinger Bands Period. By default 20
bbDev : (Optional) Bollinger Bands Standard Deviation. By default 2.0
kcSrc : (Optional) Keltner Channel Source. By default close
kcPeriod : (Optional) Keltner Channel Period. By default 20
kcATR : (Optional) Keltner Channel ATR Multiplier. By default 1.5
signalPeriod : (Optional) Keltner Channel ATR Multiplier. By default 1.5
Returns:
adx(diPeriod, adxPeriod, signalPeriod, adxTier1, adxTier2, adxTier3) ADX: Average Directional Index
Parameters:
diPeriod : (Optional) Directional Indicator Period. By default 14
adxPeriod : (Optional) ADX Smoothing. By default 14
signalPeriod : (Optional) Signal Period. By default 13
adxTier1 : (Optional) ADX Tier #1 Level. By default 20
adxTier2 : (Optional) ADX Tier #2 Level. By default 15
adxTier3 : (Optional) ADX Tier #3 Level. By default 10
Returns:
smaPreset(srcMa) Delivers a set of frequently used Simple Moving Averages
Parameters:
srcMa : (Optional) MA Source. By default 'close'
Returns:
emaPreset(srcMa) Delivers a set of frequently used Exponential Moving Averages
Parameters:
srcMa : (Optional) MA Source. By default 'close'
Returns:
maSelect(ma, srcMa) Filters and outputs the selected MA
Parameters:
ma : (Optional) MA text. By default 'Ema-21'
srcMa : (Optional) MA Source. By default 'close'
Returns: maSelected
periodAdapt(modeAdaptative, src, maxLen, minLen) Adaptative Period
Parameters:
modeAdaptative : (Optional) Adaptative Mode. By default 'Average'
src : (Optional) Source. By default 'close'
maxLen : (Optional) Max Period. By default '60'
minLen : (Optional) Min Period. By default '4'
Returns: periodAdaptative
azlema(modeAdaptative, srcMa) Azlema: Adaptative Zero-Lag Ema
Parameters:
modeAdaptative : (Optional) Adaptative Mode. By default 'Average'
srcMa : (Optional) MA Source. By default 'close'
Returns: azlema
ssma(lsmaVar, srcMa, periodMa) SSMA: Smooth Simple MA
Parameters:
lsmaVar : Linear Regression Curve.
srcMa : (Optional) MA Source. By default 'close'
periodMa : (Optional) MA Period. By default '13'
Returns: ssma
jvf(srcMa, periodMa) Jurik Volatility Factor
Parameters:
srcMa : (Optional) MA Source. By default 'close'
periodMa : (Optional) MA Period. By default '7'
Returns:
jBands(srcMa, periodMa) Jurik Bands
Parameters:
srcMa : (Optional) MA Source. By default 'close'
periodMa : (Optional) MA Period. By default '7'
Returns:
jma(srcMa, periodMa, phase) Jurik MA (JMA)
Parameters:
srcMa : (Optional) MA Source. By default 'close'
periodMa : (Optional) MA Period. By default '7'
phase : (Optional) Phase. By default '50'
Returns: jma
maCustom(ma, srcMa, periodMa, lrOffset, almaOffset, almaSigma, jmaPhase, azlemaMode) Creates a custom Moving Average
Parameters:
ma : (Optional) MA text. By default 'Ema'
srcMa : (Optional) MA Source. By default 'close'
periodMa : (Optional) MA Period. By default '13'
lrOffset : (Optional) Linear Regression Offset. By default '0'
almaOffset : (Optional) Alma Offset. By default '0.85'
almaSigma : (Optional) Alma Sigma. By default '6'
jmaPhase : (Optional) JMA Phase. By default '50'
azlemaMode : (Optional) Azlema Adaptative Mode. By default 'Average'
Returns: maTF
3B-Play Finder1 - Objective
2 - How to use (Theory)
3 - How to use (Grade System)
4 - Inputs
5 - Extras and Alerts
6 - Notes
Objective
This script aims to mark 3 Bar play patterns (both short and long) by identifying them on the chart, with an arrow pointing up from long and down for short. Aswell, setting alerts based on grade.
Following the base concept, this script comes with a "grade" system (A, B, C), which aims to classify 3B-Play according to input parameters.
2 - How to use (Theory)
The pattern is described by a wide range Ignite bar followed by a narrow resting bar.
Long
Given a 3 Bar play pattern, with a wide range green bar, the entry point should be above the ignite and narrow bar wicks (high) with stop loss set below the resting bar wick low but within ignite wide range bar.
The exit depends on the chart analysis, and there is no set rule for it.
Short
Similar to long but is with a wide range red bar and entry is defined on wick low and stop-loss at wick high.
3 - How to use (Grade System)
Since 3B-play come in all sort of shapes, some are "textbook" perfect, others a bit more "loose". I set a grading system, to differentiate each one.
The way the 3 Bar play quality is determined is based on the percentage size of the resting bar in relation to igniting bar size, starting from de close. An example of how this works is the following. Note: enabling the extra draws lines helps visually to adjust the grades to your preference.
4 - Inputs
3B Quality section
Enable/disable each grade.
CONTROL LONG / SHORT
Set the percentage values for each grade.
Extras
Enable/Disable extra plots.
5 - Extras and Alerts
This script comes with an extra section, enabling it, draws lines on the max and min values, as well, showing the values in text and the set percentage.
Also, you can set alerts based on the grade and short/long, note you should set the alert to bar close to avoid pre-trigger warnings.
6 - Notes
The script can be shorted a lot, by only looking for a single 3 bar play, to less than 30 lines.
Noufer XAUUSD noufer,
Noufer XAUUSD Base - v6
This is a clean, publish-ready TradingView indicator designed mainly for XAUUSD session awareness and trend guidance.
🔹 1. Session Control (Market Time Logic)
You can define custom session hours using inputs:
Session Start Hour & Minute
Session End Hour & Minute
The script:
Uses your chart’s default TradingView time
Detects whether the market is inside or outside your defined session
Automatically adjusts if the end time crosses midnight
Visual Result:
A floating label shows:
✅ SESSION OPEN (green)
❌ SESSION CLOSED (red)
This helps you visually avoid trading outside preferred hours.
🔹 2. Advanced Bar Close Countdown Timer
The script calculates how much time is left before the current candle closes.
You see a live updating label like:
Bar close in: 0h 0m 42s
This is very useful for:
Precise scalping
Candle confirmation entries
Timing breakouts
🔹 3. Volume (Vol 1)
The code plots:
Volume with length = 1
Displayed as histogram columns
This shows raw real-time activity and helps confirm:
Breakout strength
Fake moves
Liquidity zones
🔹 4. Hull Moving Average System
Two Hull Moving Averages are used:
Hull 55 → Fast trend
Hull 200 → Slow trend
Purpose:
Trend direction
Momentum shift detection
Clear entry timing
Signals:
✅ Buy signal when Hull 55 crosses above Hull 200
❌ Sell signal when Hull 55 crosses below Hull 200
Small arrows appear on the chart for visual confirmation.
🔹 5. Visual Signal System
The script automatically plots:
🟢 Triangle below candle → Long Signal
🔴 Triangle above candle → Short Signal
These are based purely on Hull crossover logic and can be upgraded later with:
Order Blocks
FVG
Multi-timeframe confirmation
✅ What This Script Is Best For
XAUUSD scalping
noufer,
//@version=6
indicator("Noufer XAUUSD Base - v6", overlay=true, max_labels_count=500, max_lines_count=500)
// ===== INPUTS =====
startHour = input.int(1, "Session Start Hour")
startMin = input.int(0, "Session Start Minute")
endHour = input.int(23, "Session End Hour")
endMin = input.int(0, "Session End Minute")
volLen = input.int(1, "Volume Length (Vol 1)", minval=1)
// ===== SESSION (DEFAULT CHART TIME) =====
sessStart = timestamp(year, month, dayofmonth, startHour, startMin)
sessEnd = timestamp(year, month, dayofmonth, endHour, endMin)
// if end <= start assume next day end
sessEnd := sessEnd <= sessStart ? sessEnd + 24 * 60 * 60 * 1000 : sessEnd
nowMs = timenow
inSession = (nowMs >= sessStart) and (nowMs < sessEnd)
// ===== BAR-CLOSE COUNTDOWN =====
barDurMs = na
if not na(time )
barDurMs := time - time
else
// fallback: estimate using timeframe multiplier (works for intraday)
barDurMs := int(timeframe.multiplier) * 60 * 1000
secsLeftBar = math.max(0, ((time + barDurMs) - nowMs) / 1000)
hrsB = math.floor(secsLeftBar / 3600)
minsB = math.floor((secsLeftBar % 3600) / 60)
secsB = math.floor(secsLeftBar % 60)
barCountdown = str.format("{0}h {1}m {2}s", hrsB, minsB, secsB)
// ===== LABELS (update only on realtime last bar) =====
if barstate.islast
var label sessLabel = na
sessTxt = inSession ? "SESSION OPEN" : "SESSION CLOSED"
if na(sessLabel)
sessLabel := label.new(bar_index, high * 1.002, sessTxt, xloc.bar_index, yloc.abovebar, style=label.style_label_left, color=inSession ? color.green : color.red, textcolor=color.white, size=size.small)
else
label.set_xy(sessLabel, bar_index, high * 1.002)
label.set_text(sessLabel, sessTxt)
label.set_color(sessLabel, inSession ? color.green : color.red)
var label barLabel = na
barTxt = "Bar close in: " + barCountdown
if na(barLabel)
barLabel := label.new(bar_index, low * 0.998, barTxt, xloc.bar_index, yloc.belowbar, style=label.style_label_right, color=color.new(color.blue, 0), textcolor=color.white, size=size.small)
else
label.set_xy(barLabel, bar_index, low * 0.998)
label.set_text(barLabel, barTxt)
// ===== VOLUME (Vol 1) =====
volPlot = ta.sma(volume, volLen)
plot(volPlot, title="Volume 1 (SMA)", style=plot.style_columns)
// ===== HULL MOVING AVERAGE =====
hull(src, len) =>
wma_half = ta.wma(src, len / 2)
wma_full = ta.wma(src, len)
diff = 2 * wma_half - wma_full
ta.wma(diff, math.round(math.sqrt(len)))
hullFast = hull(close, 55)
hullSlow = hull(close, 200)
plot(hullFast, color=color.orange, linewidth=2, title="Hull 55")
plot(hullSlow, color=color.blue, linewidth=2, title="Hull 200")
// ===== SIMPLE SIGNALS (example) =====
longSignal = ta.crossover(hullSlow, hullFast)
shortSignal = ta.crossunder(hullSlow, hullFast)
plotshape(longSignal, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.tiny, title="Long")
plotshape(shortSignal, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.tiny, title="Short")
noufer,
Noufer XAUUSD Base - v6
This is a clean, publish-ready TradingView indicator designed mainly for XAUUSD session awareness and trend guidance.
🔹 1. Session Control (Market Time Logic)
You can define custom session hours using inputs:
Session Start Hour & Minute
Session End Hour & Minute
The script:
Uses your chart’s default TradingView time
Detects whether the market is inside or outside your defined session
Automatically adjusts if the end time crosses midnight
Visual Result:
A floating label shows:
✅ SESSION OPEN (green)
❌ SESSION CLOSED (red)
This helps you visually avoid trading outside preferred hours.
🔹 2. Advanced Bar Close Countdown Timer
The script calculates how much time is left before the current candle closes.
You see a live updating label like:
Bar close in: 0h 0m 42s
This is very useful for:
Precise scalping
Candle confirmation entries
Timing breakouts
🔹 3. Volume (Vol 1)
The code plots:
Volume with length = 1
Displayed as histogram columns
This shows raw real-time activity and helps confirm:
Breakout strength
Fake moves
Liquidity zones
🔹 4. Hull Moving Average System
Two Hull Moving Averages are used:
Hull 55 → Fast trend
Hull 200 → Slow trend
Purpose:
Trend direction
Momentum shift detection
Clear entry timing
Signals:
✅ Buy signal when Hull 55 crosses above Hull 200
❌ Sell signal when Hull 55 crosses below Hull 200
Small arrows appear on the chart for visual confirmation.
🔹 5. Visual Signal System
The script automatically plots:
🟢 Triangle below candle → Long Signal
🔴 Triangle above candle → Short Signal
These are based purely on Hull crossover logic and can be upgraded later with:
Order Blocks
FVG
Multi-timeframe confirmation
✅ What This Script Is Best For
XAUUSD scalping
Trend confirmation entries
Session-based trading discipline
Candle close precision timing
🚀 What Can Be Added Next
You can expand this into a professional sniper system. Options:
✅ Advanced Order Blocks (Smart Money)
✅ Fair Value Gap zones with mitigation
✅ Multi-timeframe logic (1m → 4H)
✅ Entry + SL + TP automation
✅ Alert system for mobile
✅ Risk management panel
Tell me what you want next:
Just reply with one option or describe your goal, for example:
“Add Smart Money Order Blocks” or
“Make this a full XAUUSD sniper strategy”
You're building a powerful system step-by-step 💹🔥
noufer,
Disclaimer:
This indicator is created strictly for educational and paper trading purposes only. It is not intended as financial advice or a guaranteed trading system. Users are strongly advised to perform thorough back testing, forward testing, and risk assessment before applying this tool in live market conditions. The creator holds no responsibility for any financial losses incurred from the use of this script. Trade at your own risk.
Turtle System 1 (20/10) + N-Stop + MTF Table V7.2🐢 Description: Turtle System 1 (20/10) IndicatorThis indicator implements the original trading signals of the Turtle Trading System 1 based on the classic Donchian Channels. It incorporates a historically correct, volatility-based Trailing Stop (N-Stop) and a Multi-Timeframe (MTF) status dashboard. The script is written in Pine Script v6, optimized for performance and reliability.📊 Core Logic and ParametersThe system is a pure trend-following model, utilizing the more widely known, conservative parameters of the Turtle System 1:FunctionParameterValueDescriptionEntry$\text{Donchian Breakout}$$\mathbf{20}$Buy/Sell upon breaking the 20-day High/Low.Exit (Turtle)$\text{Donchian Breakout}$$\mathbf{10}$Close the position upon breaking the 10-day Low/High.Volatility$\mathbf{N}$ (ATR Period)$\mathbf{20}$Calculation of market volatility using the Average True Range (ATR).Stop-LossMultiplier$\mathbf{2.0} BER:SETS the initial and Trailing Stop at $\mathbf{2N}$.🛠️ Key Technical Features1. Original Turtle Trailing Stop (Section 4)The stop-loss mechanism is implemented with the historically accurate Turtle Trailing Logic. The stop is not aggressively tied to the current candle's low/high, which often causes premature exits. Instead, the stop only trails in the direction of the trend, maximizing the previous stop price against the new calculated $\text{Close} \pm 2N$:$$\text{New Trailing Stop} = \text{max}(\text{Previous Stop}, \text{Close} \pm (2 \times N))$$2. Reliable Multi-Timeframe (MTF) Status (Section 6)The indicator features a robust MTF status table.Purpose: It calculates and persistently stores the Turtle System 1 status (LONG=1, SHORT=-1, FLAT=0) for various timeframes (1H, 4H, 8H, 1D, and 1W).Method: It uses global var int variables combined with request.security(), ensuring the status is accurately maintained and updated across different bars and timeframes, providing a reliable higher-timeframe context.3. VisualizationsChannels: The 20-period (Entry) and 10-period (Exit) Donchian Channels are plotted.Stop Line: The dynamic $\mathbf{2N}$ Trailing Stop is visible as a distinct line.Signals: plotshape markers indicate Entry and Exit.MTF Table: A clean, color-coded status summary is displayed in the upper right corner.
Turtle System 2 (55/20) + N-Stop + MTF Table V7.2🐢 Description: Turtle System 2 (55/20) IndicatorThis indicator implements the trading signals of the Turtle Trading System 2 based on the classic Donchian Channels, supplemented by a historically correct, volatility-based Trailing Stop (N-Stop) and a Multi-Timeframe (MTF) status overview. The script was developed in Pine Script v6 and is optimized for performance and robustness.📊 Core Logic and ParametersThe indicator is based on the rule-based trend-following system developed by Richard Dennis and William Eckhardt, utilizing the more aggressive Entry/Exit parameters of System 2:FunctionParameterValueDescriptionEntry$\text{Donchian Breakout}$$\mathbf{55}$Buy/Sell upon breaking the 55-day High/Low.Exit (Turtle)$\text{Donchian Breakout}$$\mathbf{20}$Close the position upon breaking the 20-day Low/High.Volatility$\mathbf{N}$ (ATR Period)$\mathbf{20}$Calculation of market volatility using the Average True Range (ATR).Stop-LossMultiplier$\mathbf{2.0} BER:SETS the initial and Trailing Stop at $\mathbf{2N}$.🛠️ Technical Implementation1. Correct Trailing Stop (Section 4)In contrast to many flawed implementations, the Trailing Stop is implemented here according to the Original Turtle Logic. The stop price (current_stop_price) is not aggressively tied to the current low or high. Instead, at the close of each bar, it is only trailed in the direction of the trade (math.max for long positions) based on the formula:$$\text{New Trailing Stop} = \text{max}(\text{Previous Stop}, \text{Close} \pm (2 \times N))$$This ensures the stop is only adjusted upon sustained positive movement and is not prematurely triggered by short-term, deep price shadows.2. Reliable Multi-Timeframe (MTF) Logic (Section 6)The MTF section utilizes global var int variables (mtf_status_1h, mtf_status_D, etc.) in conjunction with the request.security() function.Purpose: Calculates and persistently stores the current Turtle System 2 status (LONG=1, SHORT=-1, FLAT=0) for the timeframes 1H, 4H, 8H, 1D, and 1W.Advantage: By persistently storing the status using the var variables, the critical error of single-update status is eliminated. The states shown in the table are reliable and accurately reflect the Turtle System's position status on the respective timeframes.3. Visual ComponentsDonchian Channels: The entry (55-period) and exit (20-period) channels are drawn with color highlighting.N-Stop Line: The dynamically calculated Trailing Stop ($\mathbf{2N}$) is displayed as a magenta line.Visual Signals: plotshape markers indicate Entry and Exit points.MTF Table: A compact status summary with color coding (Green/Red/Gray) for the higher timeframes is displayed in the upper right corner.
15m ORB + FVG Strategy (ChadAnt)Core Logic
The indicator's logic revolves around three main phases:
1. Defining the 15-Minute Opening Range (ORB)
The script calculates the highest high (rangeHigh) and lowest low (rangeLow) that occurred during the first 15 minutes of the trading day.
This time window is defined by the sessionStr input, which defaults to 0930-0945 (exchange time).
The high and low of this range are plotted as small gray dots once the session ends (rangeSet = true).
2. Identifying a Fair Value Gap (FVG) Setup
After the 15-minute range is set, the indicator waits for a breakout of either the range high or range low.
A "Strict FVG breakout" requires two conditions on the first candle that closes beyond the range:
The candle before the breakout candle ( bars ago) must have been inside the range.
The breakout candle ( bar ago) must have closed outside the range.
A Fair Value Gap (FVG) must form on the most recent three candles (the current bar and the two previous bars).
Bullish FVG (Long Setup): The low of the current bar (low) is greater than the high of the bar two periods prior (high ). This FVG represents a price inefficiency that the trade expects to fill.
Bearish FVG (Short Setup): The high of the current bar (high) is less than the low of the bar two periods prior (low ).
If a valid FVG setup occurs, the indicator marks a pending setup and draws a colored box to highlight the FVG area (Green for Bullish FVG, Red for Bearish FVG).
3. Trade Entry and Management
If a pending setup is identified, the trade is structured as a re-entry trade into the FVG zone:
Entry Price: Set at the outer boundary of the FVG, which is the low of the current bar for a Long setup, or the high of the current bar for a Short setup.
Stop Loss (SL): Set at the opposite boundary of the FVG, which is the low for a Long setup, or the high for a Short setup.
The trade is triggered (tradeActive = true) once the price retraces to the pendingEntry level.
Risk/Reward (RR) Targets: Three Take Profit (TP) levels are calculated based on the distance between the Entry and Stop Loss:
$$\text{Risk} = | \text{Entry} - \text{SL} |$$
$$\text{TP}n = \text{Entry} \pm (\text{Risk} \times \text{RR}n)$$
where $n$ is 1, 2, or 3, corresponding to the input $\text{RR}1$, $\text{RR}2$, and $\text{RR}3$ values (defaults: 1.0, 1.5, and 2.0).
Trade Lines: Upon triggering, lines for the Entry, Stop Loss, and three Take Profit levels are drawn on the chart for a specified length (lineLength).
A crucial feature is the directional lock (highBroken / lowBroken):
If the price breaks a range level (e.g., simpleBrokeHigh) but without a valid FVG setup, the corresponding directional flag (e.g., highBroken) is set to true permanently for the day.
This prevents the indicator from looking for any subsequent trade setups in that direction for the rest of the day, suggesting that the initial move, without an FVG, exhausted the opportunity.
Open-source script
In true TradingView spirit, the creator of this script has made it open-source, so that traders can review and verify its functionality. Kudos to the author! While you can use it for free, remember that republishing the code is subject to our House Rules.
ChadAnt
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied
15m ORB + FVG (ChadAnt)Core Logic
The indicator's logic revolves around three main phases:
1. Defining the 15-Minute Opening Range (ORB)
The script calculates the highest high (rangeHigh) and lowest low (rangeLow) that occurred during the first 15 minutes of the trading day.
This time window is defined by the sessionStr input, which defaults to 0930-0945 (exchange time).
The high and low of this range are plotted as small gray dots once the session ends (rangeSet = true).
2. Identifying a Fair Value Gap (FVG) Setup
After the 15-minute range is set, the indicator waits for a breakout of either the range high or range low.
A "Strict FVG breakout" requires two conditions on the first candle that closes beyond the range:
The candle before the breakout candle ( bars ago) must have been inside the range.
The breakout candle ( bar ago) must have closed outside the range.
A Fair Value Gap (FVG) must form on the most recent three candles (the current bar and the two previous bars).
Bullish FVG (Long Setup): The low of the current bar (low) is greater than the high of the bar two periods prior (high ). This FVG represents a price inefficiency that the trade expects to fill.
Bearish FVG (Short Setup): The high of the current bar (high) is less than the low of the bar two periods prior (low ).
If a valid FVG setup occurs, the indicator marks a pending setup and draws a colored box to highlight the FVG area (Green for Bullish FVG, Red for Bearish FVG).
3. Trade Entry and Management
If a pending setup is identified, the trade is structured as a re-entry trade into the FVG zone:
Entry Price: Set at the outer boundary of the FVG, which is the low of the current bar for a Long setup, or the high of the current bar for a Short setup.
Stop Loss (SL): Set at the opposite boundary of the FVG, which is the low for a Long setup, or the high for a Short setup.
The trade is triggered (tradeActive = true) once the price retraces to the pendingEntry level.
Risk/Reward (RR) Targets: Three Take Profit (TP) levels are calculated based on the distance between the Entry and Stop Loss:
$$\text{Risk} = | \text{Entry} - \text{SL} |$$
$$\text{TP}n = \text{Entry} \pm (\text{Risk} \times \text{RR}n)$$
where $n$ is 1, 2, or 3, corresponding to the input $\text{RR}1$, $\text{RR}2$, and $\text{RR}3$ values (defaults: 1.0, 1.5, and 2.0).
Trade Lines: Upon triggering, lines for the Entry, Stop Loss, and three Take Profit levels are drawn on the chart for a specified length (lineLength).
A crucial feature is the directional lock (highBroken / lowBroken):
If the price breaks a range level (e.g., simpleBrokeHigh) but without a valid FVG setup, the corresponding directional flag (e.g., highBroken) is set to true permanently for the day.
This prevents the indicator from looking for any subsequent trade setups in that direction for the rest of the day, suggesting that the initial move, without an FVG, exhausted the opportunity.
Market Electromagnetic Field [The_lurker]Market Electromagnetic Field
An innovative analytical indicator that presents a completely new model for understanding market dynamics, inspired by the laws of electromagnetic physics — but it's not a rhetorical metaphor, rather a complete mathematical system.
Unlike traditional indicators that focus on price or momentum, this indicator portrays the market as a closed physical system, where:
⚡ Candles = Electric charges (positive at bullish close, negative at bearish)
⚡ Buyers and Sellers = Two opposing poles where pressure accumulates
⚡ Market tension = Voltage difference between the poles
⚡ Price breakout = Electrical discharge after sufficient energy accumulation
█ Core Concept
Markets don't move randomly, but follow a clear physical cycle:
Accumulation → Tension → Discharge → Stabilization → New Accumulation
When charges accumulate (through strong candles with high volume) and exceed a certain "electrical capacitance" threshold, the indicator issues a "⚡ DISCHARGE IMMINENT" alert — meaning a price explosion is imminent, giving the trader an opportunity to enter before the move begins.
█ Competitive Advantage
- Predictive forecasting (not confirmatory after the event)
- Smart multi-layer filtering reduces false signals
- Animated 3D visual representation makes reading price conditions instant and intuitive — without need for number analysis
█ Theoretical Physical Foundation
The indicator doesn't use physical terms for decoration, but applies mathematical laws with precise market adjustments:
⚡ Coulomb's Law
Physics: F = k × (q₁ × q₂) / r²
Market: Field Intensity = 4 × norm_positive × norm_negative
Peaks at equilibrium (0.5 × 0.5 × 4 = 1.0), and decreases at dominance — because conflict increases at parity.
⚡ Ohm's Law
Physics: V = I × R
Market: Voltage = norm_positive − norm_negative
Measures balance of power:
- +1 = Absolute buying dominance
- −1 = Absolute selling dominance
- 0 = Balance
⚡ Capacitance
Physics: C = Q / V
Market: Capacitance = |Voltage| × Field Intensity
Represents stored energy ready for discharge — increases with bias combined with high interaction.
⚡ Electrical Discharge
Physics: Occurs when exceeding insulation threshold
Market: Discharge Probability = min(Capacitance / Discharge Threshold, 1.0)
When ≥ 0.9: "⚡ DISCHARGE IMMINENT"
📌 Key Note:
Maximum capacitance doesn't occur at absolute dominance (where field intensity = 0), nor at perfect balance (where voltage = 0), but at moderate bias (±30–50%) with high interaction (field intensity > 25%) — i.e., in moments of "pressure before breakout".
█ Detailed Calculation Mechanism
⚡ Phase 1: Candle Polarity
polarity = (close − open) / (high − low)
- +1.0: Complete bullish candle (Bullish Marubozu)
- −1.0: Complete bearish candle (Bearish Marubozu)
- 0.0: Doji (no decision)
- Intermediate values: Represent the ratio of candle body to its range — reducing the effect of long-shadow candles
⚡ Phase 2: Volume Weight
vol_weight = volume / SMA(volume, lookback)
A candle with 150% of average volume = 1.5x stronger charge
⚡ Phase 3: Adaptive Factor
adaptive_factor = ATR(lookback) / SMA(ATR, lookback × 2)
- In volatile markets: Increases sensitivity
- In quiet markets: Reduces noise
- Always recommended to keep it enabled
⚡ Phase 4–6: Charge Accumulation and Normalization
Charges are summed over lookback candles, then ratios are normalized:
norm_positive = positive_charge / total_charge
norm_negative = negative_charge / total_charge
So that: norm_positive + norm_negative = 1 — for easier comparison
⚡ Phase 7: Field Calculations
voltage = norm_positive − norm_negative
field_intensity = 4 × norm_positive × norm_negative × field_sensitivity
capacitance = |voltage| × field_intensity
discharge_prob = min(capacitance / discharge_threshold, 1.0)
█ Settings
⚡ Electromagnetic Model
Lookback Period
- Default: 20
- Range: 5–100
- Recommendations:
- Scalping: 10–15
- Day Trading: 20
- Swing: 30–50
- Investing: 50–100
Discharge Threshold
- Default: 0.7
- Range: 0.3–0.95
- Recommendations:
- Speed + Noise: 0.5–0.6
- Balance: 0.7
- High Accuracy: 0.8–0.95
Field Sensitivity
- Default: 1.0
- Range: 0.5–2.0
- Recommendations:
- Amplify Conflict: 1.2–1.5
- Natural: 1.0
- Calm: 0.5–0.8
Adaptive Mode
- Default: Enabled
- Always keep it enabled
🔬 Dynamic Filters
All enabled filters must pass for discharge signal to appear.
Volume Filter
- Condition: volume > SMA(volume) × vol_multiplier
- Function: Excludes "weak" candles not supported by volume
- Recommendation: Enabled (especially for stocks and forex)
Volatility Filter
- Condition: STDEV > SMA(STDEV) × 0.5
- Function: Ignores sideways stagnation periods
- Recommendation: Always enabled
Trend Filter
- Condition: Voltage alignment with fast/slow EMA
- Function: Reduces counter-trend signals
- Recommendation: Enabled for swing/investing only
Volume Threshold
- Default: 1.2
- Recommendations:
- 1.0–1.2: High sensitivity
- 1.5–2.0: Exclusive to high volume
🎨 Visual Settings
Settings improve visual reading experience — don't affect calculations.
Scale Factor
- Default: 600
- Higher = Larger scene (200–1200)
Horizontal Shift
- Default: 180
- Horizontal shift to the left — to focus on last candle
Pole Size
- Default: 60
- Base sphere size (30–120)
Field Lines
- Default: 8
- Number of field lines (4–16) — 8 is ideal balance
Colors
- Green/Red/Blue/Orange
- Fully customizable
█ Visual Representation: A Visual Language for Diagnosing Price Conditions
✨ Design Philosophy
The representation isn't "decoration", but a complete cognitive model — each element carries information, and element interaction tells a complete story.
The brain perceives changes in size, color, and movement 60,000 times faster than reading numbers — so you can "sense" the change before your eye finishes scanning.
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🟢 Positive Pole (Green Sphere — Left)
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What does it represent?
Active buying pressure accumulation — not just an uptrend, but real demand force supported by volume and volatility.
● Dynamic Size
Size = pole_size × (0.7 + norm_positive × 0.6)
- 70% of base size = No significant charge
- 130% of base size = Complete dominance
- The larger the sphere: Greater buyer dominance, higher probability of bullish continuation
Size Interpretation:
- Large sphere (>55%): Strong buying pressure — Buyers dominate
- Medium sphere (45–55%): Relative balance with buying bias
- Small sphere (<45%): Weak buying pressure — Sellers dominate
● Lighting and Transparency
- 20% transparency (when Bias = +1): Pole currently active — Bullish direction
- 50% transparency (when Bias ≠ +1): Pole inactive — Not the prevailing direction
Lighting = Current activity, while Size = Historical accumulation
● Pulsing Inner Glow
A smaller sphere pulses automatically when Bias = +1:
inner_pulse = 0.4 + 0.1 × sin(anim_time × 3)
Symbolizes continuity of buy order flow — not static dominance.
● Orbital Rings
Two rings rotating at different speeds and directions:
- Inner: 1.3× sphere size — Direct influence range
- Outer: 1.6× sphere size — Extended influence range
Represent "influence zone" of buyers:
- Continuous rotation = Stability and momentum
- Slowdown = Momentum exhaustion
● Percentage
Displayed below sphere: norm_positive × 100
- >55% = Clear dominance
- 45–55% = Balance
- <45% = Weakness
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🔴 Negative Pole (Red Sphere — Right)
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What does it represent?
Active selling pressure accumulation — whether cumulative selling (smart distribution) or panic selling (position liquidation).
● Visual Dynamics
Same size, lighting, and inner glow mechanism — but in red.
Key Difference:
- Rotation is reversed (counter-clockwise)
- Visually distinguishes "buy flow" from "sell flow"
- Allows reading direction at a glance — even for colorblind users
📌 Pole Reading Summary:
🟢 Large + Bright green sphere = Active buying force
🔴 Large + Bright red sphere = Active selling force
🟢🔴 Both large but dim = Energy accumulation (before discharge)
⚪ Both small = Stagnation / Low liquidity
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🔵 Field Lines (Curved Blue Lines)
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What do they represent?
Energy flow paths between poles — the arena where price battle is fought.
● Number of Lines
4–16 lines (Default: 8)
More lines: Greater sense of "interaction density"
● Arc Height
arc_h = (i − half_lines) × 15 × field_intensity × 2
- High field intensity = Highly elevated lines (like waves)
- Low intensity = Nearly straight lines
● Oscillating Transparency
transp = 30 + phase × 40
where phase = sin(anim_time × 2 + i × 0.5) × 0.5 + 0.5
Creates illusion of "flowing current" — not static lines
● Asymmetric Curvature
- Upper lines curve upward
- Lower lines curve downward
- Adds 3D depth and shows "pressure" direction
⚡ Pro Tip:
When you see lines suddenly "contract" (straighten), while both spheres are large — this is an early indicator of impending discharge, because the interaction is losing its flexibility.
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⚪ Moving Particles
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What do they represent?
Real liquidity flow in the market — who's driving price right now.
● Number and Movement
- 6 particles covering most field lines
- Move sinusoidally along the arc:
t = (sin(phase_val) + 1) / 2
- High speed = High trading activity
- Clustering at a pole = That side's control
● Color Gradient
From green (at positive pole) to red (at negative)
Shows "energy transformation":
- Green particle = Pure buying energy
- Orange particle = Conflict zone
- Red particle = Pure selling energy
📌 How to Read Them?
- Moving left to right (🟢 → 🔴): Buy flow → Bullish push
- Moving right to left (🔴 → 🟢): Sell flow → Bearish push
- Clustered in middle: Balanced conflict — Wait for breakout
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🟠 Discharge Zone (Orange Glow — Center)
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What does it represent?
Point of stored energy accumulation not yet discharged — heart of the early warning system.
● Glow Stages
Initial Warning (discharge_prob > 0.3):
- Dim orange circle (70% transparency)
- Meaning: Watch, don't enter yet
High Tension (discharge_prob ≥ 0.7):
- Stronger glow + "⚠️ HIGH TENSION" text
- Meaning: Prepare — Set pending orders
Imminent Discharge (discharge_prob ≥ 0.9):
- Bright glow + "⚡ DISCHARGE IMMINENT" text
- Meaning: Enter with direction (after candle confirmation)
● Layered Glow Effect (Glow Layering)
3 concentric circles with increasing transparency:
- Inner: 20%
- Middle: 35%
- Outer: 50%
Result: Realistic aura resembling actual electrical discharge.
📌 Why in the Center?
Because discharge always starts from the relative balance zone — where opposing pressures meet.
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📊 Voltage Meter (Bottom of Scene)
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What does it represent?
Simplified numeric indicator of voltage difference — for those who prefer numerical reading.
● Components
- Gray bar: Full range (−100% to +100%)
- Green fill: Positive voltage (extends right)
- Red fill: Negative voltage (extends left)
- Lightning symbol (⚡): Above center — reminder it's an "electrical gauge"
- Text value: Like "+23.4%" — in direction color
● Voltage Reading Interpretation
+50% to +100%:
Overwhelming buying dominance — Beware of saturation, may precede correction
+20% to +50%:
Strong buying dominance — Suitable for buying with trend
+5% to +20%:
Slight bullish bias — Wait for additional confirmation
−5% to +5%:
Balance/Neutral — Avoid entry or wait for breakout
−5% to −20%:
Slight bearish bias — Wait for confirmation
−20% to −50%:
Strong selling dominance — Suitable for selling with trend
−50% to −100%:
Overwhelming selling dominance — Beware of saturation, may precede bounce
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📈 Field Strength Indicator (Top of Scene)
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What it displays: "Field: XX.X%"
Meaning: Strength of conflict between buyers and sellers.
● Reading Interpretation
0–5%:
- Appearance: Nearly straight lines, transparent
- Meaning: Complete control by one side
- Strategy: Trend Following
5–15%:
- Appearance: Slight curvature
- Meaning: Clear direction with light resistance
- Strategy: Enter with trend
15–25%:
- Appearance: Medium curvature, clear lines
- Meaning: Balanced conflict
- Strategy: Range trading or waiting
25–35%:
- Appearance: High curvature, clear density
- Meaning: Strong conflict, high uncertainty
- Strategy: Volatility trading or prepare for discharge
35%+:
- Appearance: Very high lines, strong glow
- Meaning: Peak tension
- Strategy: Best discharge opportunities
📌 Golden Relationship:
Highest discharge probability when:
Field Strength (25–35%) + Voltage (±30–50%) + High Volume
← This is the "red zone" to monitor carefully.
█ Comprehensive Visual Reading
To read market condition at a glance, follow this sequence:
Step 1: Which sphere is larger?
- 🟢 Green larger ← Dominant buying pressure
- 🔴 Red larger ← Dominant selling pressure
- Equal ← Balance/Conflict
Step 2: Which sphere is bright?
- 🟢 Green bright ← Current bullish direction
- 🔴 Red bright ← Current bearish direction
- Both dim ← Neutral/No clear direction
Step 3: Is there orange glow?
- None ← Discharge probability <30%
- 🟠 Dim glow ← Discharge probability 30–70%
- 🟠 Strong glow with text ← Discharge probability >70%
Step 4: What's the voltage meter reading?
- Strong positive ← Confirms buying dominance
- Strong negative ← Confirms selling dominance
- Near zero ← No clear direction
█ Practical Visual Reading Examples
Example 1: Ideal Buy Opportunity ⚡🟢
- Green sphere: Large and bright with inner pulse
- Red sphere: Small and dim
- Orange glow: Strong with "DISCHARGE IMMINENT" text
- Voltage meter: +45%
- Field strength: 28%
Interpretation: Strong accumulated buying pressure, bullish explosion imminent
Example 2: Ideal Sell Opportunity ⚡🔴
- Green sphere: Small and dim
- Red sphere: Large and bright with inner pulse
- Orange glow: Strong with "DISCHARGE IMMINENT" text
- Voltage meter: −52%
- Field strength: 31%
Interpretation: Strong accumulated selling pressure, bearish explosion imminent
Example 3: Balance/Wait ⚖️
- Both spheres: Approximately equal in size
- Lighting: Both dim
- Orange glow: Strong
- Voltage meter: +3%
- Field strength: 24%
Interpretation: Strong conflict without clear winner, wait for breakout
Example 4: Clear Uptrend (No Discharge) 📈
- Green sphere: Large and bright
- Red sphere: Very small and dim
- Orange glow: None
- Voltage meter: +68%
- Field strength: 8%
Interpretation: Clear buying control, limited conflict, suitable for following bullish trend
Example 5: Potential Buying Saturation ⚠️
- Green sphere: Very large and bright
- Red sphere: Very small
- Orange glow: Dim
- Voltage meter: +88%
- Field strength: 4%
Interpretation: Absolute buying dominance, may precede bearish correction
█ Trading Signals
⚡ DISCHARGE IMMINENT
Appearance Conditions:
- discharge_prob ≥ 0.9
- All enabled filters passed
- Confirmed (after candle close)
Interpretation:
- Very large energy accumulation
- Pressure reached critical level
- Price explosion expected within 1–3 candles
How to Trade:
1. Determine voltage direction:
• Positive = Expect rise
• Negative = Expect fall
2. Wait for confirmation candle:
• For rise: Bullish candle closing above its open
• For fall: Bearish candle closing below its open
3. Entry: With next candle's open
4. Stop Loss: Behind last local low/high
5. Target: Risk/Reward ratio of at least 1:2
✅ Pro Tips:
- Best results when combined with support/resistance levels
- Avoid entry if voltage is near zero (±5%)
- Increase position size when field strength > 30%
⚠️ HIGH TENSION
Appearance Conditions:
- 0.7 ≤ discharge_prob < 0.9
Interpretation:
- Market in energy accumulation state
- Likely strong move soon, but not immediate
- Accumulation may continue or discharge may occur
How to Benefit:
- Prepare: Set pending orders at potential breakouts
- Monitor: Watch following candles for momentum candle
- Select: Don't enter every signal — choose those aligned with overall trend
█ Trading Strategies
📈 Strategy 1: Discharge Trading (Basic)
Principle: Enter at "DISCHARGE IMMINENT" in voltage direction
Steps:
1. Wait for "⚡ DISCHARGE IMMINENT"
2. Check voltage direction (+/−)
3. Wait for confirmation candle in voltage direction
4. Enter with next candle's open
5. Stop loss behind last low/high
6. Target: 1:2 or 1:3 ratio
Very high success rate when following confirmation conditions.
📈 Strategy 2: Dominance Following
Principle: Trade with dominant pole (largest and brightest sphere)
Steps:
1. Identify dominant pole (largest and brightest)
2. Trade in its direction
3. Beware when sizes converge (conflict)
Suitable for higher timeframes (H1+).
📈 Strategy 3: Reversal Hunting
Principle: Counter-trend entry under certain conditions
Conditions:
- High field strength (>30%)
- Extreme voltage (>±40%)
- Divergence with price (e.g., new price high with declining voltage)
⚠️ High risk — Use small position size.
📈 Strategy 4: Integration with Technical Analysis
Strong Confirmation Examples:
- Resistance breakout + Bullish discharge = Excellent buy signal
- Support break + Bearish discharge = Excellent sell signal
- Head & Shoulders pattern + Increasing negative voltage = Pattern confirmation
- RSI divergence + High field strength = Potential reversal
█ Ready Alerts
Bullish Discharge
- Condition: discharge_prob ≥ 0.9 + Positive voltage + All filters
- Message: "⚡ Bullish discharge"
- Use: High probability buy opportunity
Bearish Discharge
- Condition: discharge_prob ≥ 0.9 + Negative voltage + All filters
- Message: "⚡ Bearish discharge"
- Use: High probability sell opportunity
✅ Tip: Use these alerts with "Once Per Bar" setting to avoid repetition.
█ Data Window Outputs
Bias
- Values: −1 / 0 / +1
- Interpretation: −1 = Bearish, 0 = Neutral, +1 = Bullish
- Use: For integration in automated strategies
Discharge %
- Range: 0–100%
- Interpretation: Discharge probability
- Use: Monitor tension progression (e.g., from 40% to 85% in 5 candles)
Field Strength
- Range: 0–100%
- Interpretation: Conflict intensity
- Use: Identify "opportunity window" (25–35% ideal for discharge)
Voltage
- Range: −100% to +100%
- Interpretation: Balance of power
- Use: Monitor extremes (potential buying/selling saturation)
█ Optimal Settings by Trading Style
Scalping
- Timeframe: 1M–5M
- Lookback: 10–15
- Threshold: 0.5–0.6
- Sensitivity: 1.2–1.5
- Filters: Volume + Volatility
Day Trading
- Timeframe: 15M–1H
- Lookback: 20
- Threshold: 0.7
- Sensitivity: 1.0
- Filters: Volume + Volatility
Swing Trading
- Timeframe: 4H–D1
- Lookback: 30–50
- Threshold: 0.8
- Sensitivity: 0.8
- Filters: Volatility + Trend
Position Trading
- Timeframe: D1–W1
- Lookback: 50–100
- Threshold: 0.85–0.95
- Sensitivity: 0.5–0.8
- Filters: All filters
█ Tips for Optimal Use
1. Start with Default Settings
Try it first as is, then adjust to your style.
2. Watch for Element Alignment
Best signals when:
- Clear voltage (>│20%│)
- Moderate–high field strength (15–35%)
- High discharge probability (>70%)
3. Use Multiple Timeframes
- Higher timeframe: Determine overall trend
- Lower timeframe: Time entry
- Ensure signal alignment between frames
4. Integrate with Other Tools
- Support/Resistance levels
- Trend lines
- Candle patterns
- Volume indicators
5. Respect Risk Management
- Don't risk more than 1–2% of account
- Always use stop loss
- Don't enter every signal — choose the best
█ Important Warnings
⚠️ Not for Standalone Use
The indicator is an analytical support tool — don't use it isolated from technical or fundamental analysis.
⚠️ Doesn't Predict the Future
Calculations are based on historical data — Results are not guaranteed.
⚠️ Markets Differ
You may need to adjust settings for each market:
- Forex: Focus on Volume Filter
- Stocks: Add Trend Filter
- Crypto: Lower Threshold slightly (more volatile)
⚠️ News and Events
The indicator doesn't account for sudden news — Avoid trading before/during major news.
█ Unique Features
✅ First Application of Electromagnetism to Markets
Innovative mathematical model — Not just an ordinary indicator
✅ Predictive Detection of Price Explosions
Alerts before the move happens — Not after
✅ Multi-Layer Filtering
4 smart filters reduce false signals to minimum
✅ Smart Volatility Adaptation
Automatically adjusts sensitivity based on market conditions
✅ Animated 3D Visual Representation
Makes reading instant — Even for beginners
✅ High Flexibility
Works on all assets: Stocks, Forex, Crypto, Commodities
✅ Built-in Ready Alerts
No complex setup needed — Ready for immediate use
█ Conclusion: When Art Meets Science
Market Electromagnetic Field is not just an indicator — but a new analytical philosophy.
It's the bridge between:
- Physics precision in describing dynamic systems
- Market intelligence in generating trading opportunities
- Visual psychology in facilitating instant reading
The result: A tool that isn't read — but watched, felt, and sensed.
When you see the green sphere expanding, the glow intensifying, and particles rushing rightward — you're not seeing numbers, you're seeing market energy breathing.
⚠️ Disclaimer:
This indicator is for educational and analytical purposes only. It does not constitute financial, investment, or trading advice. Use it in conjunction with your own strategy and risk management. Neither TradingView nor the developer is liable for any financial decisions or losses.
المجال الكهرومغناطيسي للسوق - Market Electromagnetic Field
مؤشر تحليلي مبتكر يقدّم نموذجًا جديدًا كليًّا لفهم ديناميكيات السوق، مستوحى من قوانين الفيزياء الكهرومغناطيسية — لكنه ليس استعارة بلاغية، بل نظام رياضي متكامل.
على عكس المؤشرات التقليدية التي تُركّز على السعر أو الزخم، يُصوّر هذا المؤشر السوق كـنظام فيزيائي مغلق، حيث:
⚡ الشموع = شحنات كهربائية (موجبة عند الإغلاق الصاعد، سالبة عند الهابط)
⚡ المشتريون والبائعون = قطبان متعاكسان يتراكم فيهما الضغط
⚡ التوتر السوقي = فرق جهد بين القطبين
⚡ الاختراق السعري = تفريغ كهربائي بعد تراكم طاقة كافية
█ الفكرة الجوهرية
الأسواق لا تتحرك عشوائيًّا، بل تخضع لدورة فيزيائية واضحة:
تراكم → توتر → تفريغ → استقرار → تراكم جديد
عندما تتراكم الشحنات (من خلال شموع قوية بحجم مرتفع) وتتجاوز "السعة الكهربائية" عتبة معيّنة، يُصدر المؤشر تنبيه "⚡ DISCHARGE IMMINENT" — أي أن انفجارًا سعريًّا وشيكًا، مما يمنح المتداول فرصة الدخول قبل بدء الحركة.
█ الميزة التنافسية
- تنبؤ استباقي (ليس تأكيديًّا بعد الحدث)
- فلترة ذكية متعددة الطبقات تقلل الإشارات الكاذبة
- تمثيل بصري ثلاثي الأبعاد متحرك يجعل قراءة الحالة السعرية فورية وبديهية — دون حاجة لتحليل أرقام
█ الأساس النظري الفيزيائي
المؤشر لا يستخدم مصطلحات فيزيائية للزينة، بل يُطبّق القوانين الرياضية مع تعديلات سوقيّة دقيقة:
⚡ قانون كولوم (Coulomb's Law)
الفيزياء: F = k × (q₁ × q₂) / r²
السوق: شدة الحقل = 4 × norm_positive × norm_negative
تصل لذروتها عند التوازن (0.5 × 0.5 × 4 = 1.0)، وتنخفض عند الهيمنة — لأن الصراع يزداد عند التكافؤ.
⚡ قانون أوم (Ohm's Law)
الفيزياء: V = I × R
السوق: الجهد = norm_positive − norm_negative
يقيس ميزان القوى:
- +1 = هيمنة شرائية مطلقة
- −1 = هيمنة بيعية مطلقة
- 0 = توازن
⚡ السعة الكهربائية (Capacitance)
الفيزياء: C = Q / V
السوق: السعة = |الجهد| × شدة الحقل
تمثّل الطاقة المخزّنة القابلة للتفريغ — تزداد عند وجود تحيّز مع تفاعل عالي.
⚡ التفريغ الكهربائي (Discharge)
الفيزياء: يحدث عند تجاوز عتبة العزل
السوق: احتمال التفريغ = min(السعة / عتبة التفريغ, 1.0)
عندما ≥ 0.9: "⚡ DISCHARGE IMMINENT"
📌 ملاحظة جوهرية:
أقصى سعة لا تحدث عند الهيمنة المطلقة (حيث شدة الحقل = 0)، ولا عند التوازن التام (حيث الجهد = 0)، بل عند انحياز متوسط (±30–50%) مع تفاعل عالي (شدة حقل > 25%) — أي في لحظات "الضغط قبل الاختراق".
█ آلية الحساب التفصيلية
⚡ المرحلة 1: قطبية الشمعة
polarity = (close − open) / (high − low)
- +1.0: شمعة صاعدة كاملة (ماروبوزو صاعد)
- −1.0: شمعة هابطة كاملة (ماروبوزو هابط)
- 0.0: دوجي (لا قرار)
- القيم الوسيطة: تمثّل نسبة جسم الشمعة إلى مداها — مما يقلّل تأثير الشموع ذات الظلال الطويلة
⚡ المرحلة 2: وزن الحجم
vol_weight = volume / SMA(volume, lookback)
شمعة بحجم 150% من المتوسط = شحنة أقوى بـ 1.5 مرة
⚡ المرحلة 3: معامل التكيف (Adaptive Factor)
adaptive_factor = ATR(lookback) / SMA(ATR, lookback × 2)
- في الأسواق المتقلبة: يزيد الحساسية
- في الأسواق الهادئة: يقلل الضوضاء
- يوصى دائمًا بتركه مفعّلًا
⚡ المرحلة 4–6: تراكم وتوحيد الشحنات
تُجمّع الشحنات على lookback شمعة، ثم تُوحّد النسب:
norm_positive = positive_charge / total_charge
norm_negative = negative_charge / total_charge
بحيث: norm_positive + norm_negative = 1 — لتسهيل المقارنة
⚡ المرحلة 7: حسابات الحقل
voltage = norm_positive − norm_negative
field_intensity = 4 × norm_positive × norm_negative × field_sensitivity
capacitance = |voltage| × field_intensity
discharge_prob = min(capacitance / discharge_threshold, 1.0)
█ الإعدادات
⚡ Electromagnetic Model
Lookback Period
- الافتراضي: 20
- النطاق: 5–100
- التوصيات:
- المضاربة: 10–15
- اليومي: 20
- السوينغ: 30–50
- الاستثمار: 50–100
Discharge Threshold
- الافتراضي: 0.7
- النطاق: 0.3–0.95
- التوصيات:
- سرعة + ضوضاء: 0.5–0.6
- توازن: 0.7
- دقة عالية: 0.8–0.95
Field Sensitivity
- الافتراضي: 1.0
- النطاق: 0.5–2.0
- التوصيات:
- تضخيم الصراع: 1.2–1.5
- طبيعي: 1.0
- تهدئة: 0.5–0.8
Adaptive Mode
- الافتراضي: مفعّل
- أبقِه دائمًا مفعّلًا
🔬 Dynamic Filters
يجب اجتياز جميع الفلاتر المفعّلة لظهور إشارة التفريغ.
Volume Filter
- الشرط: volume > SMA(volume) × vol_multiplier
- الوظيفة: يستبعد الشموع "الضعيفة" غير المدعومة بحجم
- التوصية: مفعّل (خاصة للأسهم والعملات)
Volatility Filter
- الشرط: STDEV > SMA(STDEV) × 0.5
- الوظيفة: يتجاهل فترات الركود الجانبي
- التوصية: مفعّل دائمًا
Trend Filter
- الشرط: توافق الجهد مع EMA سريع/بطيء
- الوظيفة: يقلل الإشارات المعاكسة للاتجاه العام
- التوصية: مفعّل للسوينغ/الاستثمار فقط
Volume Threshold
- الافتراضي: 1.2
- التوصيات:
- 1.0–1.2: حساسية عالية
- 1.5–2.0: حصرية للحجم العالي
🎨 Visual Settings
الإعدادات تُحسّن تجربة القراءة البصرية — لا تؤثر على الحسابات.
Scale Factor
- الافتراضي: 600
- كلما زاد: المشهد أكبر (200–1200)
Horizontal Shift
- الافتراضي: 180
- إزاحة أفقيّة لليسار — ليركّز على آخر شمعة
Pole Size
- الافتراضي: 60
- حجم الكرات الأساسية (30–120)
Field Lines
- الافتراضي: 8
- عدد خطوط الحقل (4–16) — 8 توازن مثالي
الألوان
- أخضر/أحمر/أزرق/برتقالي
- قابلة للتخصيص بالكامل
█ التمثيل البصري: لغة بصرية لتشخيص الحالة السعرية
✨ الفلسفة التصميمية
التمثيل ليس "زينة"، بل نموذج معرفي متكامل — كل عنصر يحمل معلومة، وتفاعل العناصر يروي قصة كاملة.
العقل يدرك التغيير في الحجم، اللون، والحركة أسرع بـ 60,000 مرة من قراءة الأرقام — لذا يمكنك "الإحساس" بالتغير قبل أن تُنهي العين المسح.
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🟢 القطب الموجب (الكرة الخضراء — يسار)
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ماذا يمثّل؟
تراكم ضغط الشراء النشط — ليس مجرد اتجاه صاعد، بل قوة طلب حقيقية مدعومة بحجم وتقلّب.
● الحجم المتغير
حجم = pole_size × (0.7 + norm_positive × 0.6)
- 70% من الحجم الأساسي = لا شحنة تُذكر
- 130% من الحجم الأساسي = هيمنة تامة
- كلما كبرت الكرة: زاد تفوّق المشترين، وارتفع احتمال الاستمرار الصعودي
تفسير الحجم:
- كرة كبيرة (>55%): ضغط شراء قوي — المشترون يسيطرون
- كرة متوسطة (45–55%): توازن نسبي مع ميل للشراء
- كرة صغيرة (<45%): ضعف ضغط الشراء — البائعون يسيطرون
● الإضاءة والشفافية
- شفافية 20% (عند Bias = +1): القطب نشط حالياً — الاتجاه صعودي
- شفافية 50% (عند Bias ≠ +1): القطب غير نشط — ليس الاتجاه السائد
الإضاءة = النشاط الحالي، بينما الحجم = التراكم التاريخي
● التوهج الداخلي النابض
كرة أصغر تنبض تلقائيًّا عند Bias = +1:
inner_pulse = 0.4 + 0.1 × sin(anim_time × 3)
يرمز إلى استمرارية تدفق أوامر الشراء — وليس هيمنة جامدة.
● الحلقات المدارية
حلقتان تدوران بسرعات واتجاهات مختلفة:
- الداخلية: 1.3× حجم الكرة — نطاق التأثير المباشر
- الخارجية: 1.6× حجم الكرة — نطاق التأثير الممتد
تمثّل "نطاق تأثير" المشترين:
- الدوران المستمر = استقرار وزخم
- التباطؤ = نفاد الزخم
● النسبة المئوية
تظهر تحت الكرة: norm_positive × 100
- >55% = هيمنة واضحة
- 45–55% = توازن
- <45% = ضعف
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🔴 القطب السالب (الكرة الحمراء — يمين)
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ماذا يمثّل؟
تراكم ضغط البيع النشط — سواء كان بيعًا تراكميًّا (التوزيع الذكي) أو بيعًا هستيريًّا (تصفية مراكز).
● الديناميكيات البصرية
نفس آلية الحجم والإضاءة والتوهج الداخلي — لكن باللون الأحمر.
الفرق الجوهري:
- الدوران معكوس (عكس اتجاه عقارب الساعة)
- يُميّز بصريًّا بين "تدفق الشراء" و"تدفق البيع"
- يسمح بقراءة الاتجاه بنظرة واحدة — حتى للمصابين بعَمَى الألوان
📌 ملخص قراءة القطبين:
🟢 كرة خضراء كبيرة + مضيئة = قوة شرائية نشطة
🔴 كرة حمراء كبيرة + مضيئة = قوة بيعية نشطة
🟢🔴 كرتان كبيرتان لكن خافتتان = تراكم طاقة (قبل التفريغ)
⚪ كرتان صغيرتان = ركود / سيولة منخفضة
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🔵 خطوط الحقل (الخطوط الزرقاء المنحنية)
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ماذا تمثّل؟
مسارات تدفق الطاقة بين القطبين — أي الساحة التي تُدار فيها المعركة السعرية.
● عدد الخطوط
4–16 خط (الافتراضي: 8)
كلما زاد العدد: زاد إحساس "كثافة التفاعل"
● ارتفاع القوس
arc_h = (i − half_lines) × 15 × field_intensity × 2
- شدة حقل عالية = خطوط شديدة الارتفاع (مثل موجة)
- شدة منخفضة = خطوط شبه مستقيمة
● الشفافية المتذبذبة
transp = 30 + phase × 40
حيث phase = sin(anim_time × 2 + i × 0.5) × 0.5 + 0.5
تخلق وهم "تيّار متدفّق" — وليس خطوطًا ثابتة
● الانحناء غير المتناظر
- الخطوط العلوية تنحني لأعلى
- الخطوط السفلية تنحني لأسفل
- يُضفي عمقًا ثلاثي الأبعاد ويُظهر اتجاه "الضغط"
⚡ تلميح احترافي:
عندما ترى الخطوط "تتقلّص" فجأة (تستقيم)، بينما الكرتان كبيرتان — فهذا مؤشر مبكر على قرب التفريغ، لأن التفاعل بدأ يفقد مرونته.
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⚪ الجزيئات المتحركة
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ماذا تمثّل؟
تدفق السيولة الحقيقية في السوق — أي من يدفع السعر الآن.
● العدد والحركة
- 6 جزيئات تغطي معظم خطوط الحقل
- تتحرك جيبيًّا على طول القوس:
t = (sin(phase_val) + 1) / 2
- سرعة عالية = نشاط تداول عالي
- تجمّع عند قطب = سيطرة هذا الطرف
● تدرج اللون
من أخضر (عند القطب الموجب) إلى أحمر (عند السالب)
يُظهر "تحوّل الطاقة":
- جزيء أخضر = طاقة شرائية نقية
- جزيء برتقالي = منطقة صراع
- جزيء أحمر = طاقة بيعية نقية
📌 كيف تقرأها؟
- تحركت من اليسار لليمين (🟢 → 🔴): تدفق شرائي → دفع صعودي
- تحركت من اليمين لليسار (🔴 → 🟢): تدفق بيعي → دفع هبوطي
- تجمّعت في المنتصف: صراع متكافئ — انتظر اختراقًا
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🟠 منطقة التفريغ (التوهج البرتقالي — المركز)
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ماذا تمثّل؟
نقطة تراكم الطاقة المخزّنة التي لم تُفرّغ بعد — قلب نظام الإنذار المبكر.
● مراحل التوهج
إنذار أولي (discharge_prob > 0.3):
- دائرة برتقالية خافتة (شفافية 70%)
- المعنى: راقب، لا تدخل بعد
توتر عالي (discharge_prob ≥ 0.7):
- توهج أقوى + نص "⚠️ HIGH TENSION"
- المعنى: استعد — ضع أوامر معلقة
تفريغ وشيك (discharge_prob ≥ 0.9):
- توهج ساطع + نص "⚡ DISCHARGE IMMINENT"
- المعنى: ادخل مع الاتجاه (بعد تأكيد شمعة)
● تأثير التوهج الطبقي (Glow Layering)
3 دوائر متحدة المركز بشفافية متزايدة:
- داخلي: 20%
- وسط: 35%
- خارجي: 50%
النتيجة: هالة (Aura) واقعية تشبه التفريغ الكهربائي الحقيقي.
📌 لماذا في المركز؟
لأن التفريغ يبدأ دائمًا من منطقة التوازن النسبي — حيث يلتقي الضغطان المتعاكسان.
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📊 مقياس الجهد (أسفل المشهد)
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ماذا يمثّل؟
مؤشر رقمي مبسّط لفرق الجهد — لمن يفضّل القراءة العددية.
● المكونات
- الشريط الرمادي: النطاق الكامل (−100% إلى +100%)
- التعبئة الخضراء: جهد موجب (تمتد لليمين)
- التعبئة الحمراء: جهد سالب (تمتد لليسار)
- رمز البرق (⚡): فوق المركز — تذكير بأنه "مقياس كهربائي"
- القيمة النصية: مثل "+23.4%" — بلون الاتجاه
● تفسير قراءات الجهد
+50% إلى +100%:
هيمنة شرائية ساحقة — احذر التشبع، قد يسبق تصحيح
+20% إلى +50%:
هيمنة شرائية قوية — مناسب للشراء مع الاتجاه
+5% إلى +20%:
ميل صعودي خفيف — انتظر تأكيدًا إضافيًّا
−5% إلى +5%:
توازن/حياد — تجنّب الدخول أو انتظر اختراقًا
−5% إلى −20%:
ميل هبوطي خفيف — انتظر تأكيدًا
−20% إلى −50%:
هيمنة بيعية قوية — مناسب للبيع مع الاتجاه
−50% إلى −100%:
هيمنة بيعية ساحقة — احذر التشبع، قد يسبق ارتداد
═════════════════════════════════════════════════════════════
📈 مؤشر شدة الحقل (أعلى المشهد)
═════════════════════════════════════════════════════════════
ما يعرضه: "Field: XX.X%"
الدلالة: قوة الصراع بين المشترين والبائعين.
● تفسير القراءات
0–5%:
- المظهر: خطوط مستقيمة تقريبًا، شفافة
- المعنى: سيطرة تامة لأحد الطرفين
- الاستراتيجية: تتبع الترند (Trend Following)
5–15%:
- المظهر: انحناء خفيف
- المعنى: اتجاه واضح مع مقاومة خفيفة
- الاستراتيجية: الدخول مع الاتجاه
15–25%:
- المظهر: انحناء متوسط، خطوط واضحة
- المعنى: صراع متوازن
- الاستراتيجية: تداول النطاق أو الانتظار
25–35%:
- المظهر: انحناء عالي، كثافة واضحة
- المعنى: صراع قوي، عدم يقين عالي
- الاستراتيجية: تداول التقلّب أو الاستعداد للتفريغ
35%+:
- المظهر: خطوط عالية جدًّا، توهج قوي
- المعنى: ذروة التوتر
- الاستراتيجية: أفضل فرص التفريغ
📌 العلاقة الذهبية:
أعلى احتمال تفريغ عندما:
شدة الحقل (25–35%) + جهد (±30–50%) + حجم مرتفع
← هذه هي "المنطقة الحمراء" التي يجب مراقبتها بدقة.
█ قراءة التمثيل البصري الشاملة
لقراءة حالة السوق بنظرة واحدة، اتبع هذا التسلسل:
الخطوة 1: أي كرة أكبر؟
- 🟢 الخضراء أكبر ← ضغط شراء مهيمن
- 🔴 الحمراء أكبر ← ضغط بيع مهيمن
- متساويتان ← توازن/صراع
الخطوة 2: أي كرة مضيئة؟
- 🟢 الخضراء مضيئة ← اتجاه صعودي حالي
- 🔴 الحمراء مضيئة ← اتجاه هبوطي حالي
- كلاهما خافت ← حياد/لا اتجاه واضح
الخطوة 3: هل يوجد توهج برتقالي؟
- لا يوجد ← احتمال تفريغ <30%
- 🟠 توهج خافت ← احتمال تفريغ 30–70%
- 🟠 توهج قوي مع نص ← احتمال تفريغ >70%
الخطوة 4: ما قراءة مقياس الجهد؟
- موجب قوي ← تأكيد الهيمنة الشرائية
- سالب قوي ← تأكيد الهيمنة البيعية
- قريب من الصفر ← لا اتجاه واضح
█ أمثلة عملية للقراءة البصرية
المثال 1: فرصة شراء مثالية ⚡🟢
- الكرة الخضراء: كبيرة ومضيئة مع نبض داخلي
- الكرة الحمراء: صغيرة وخافتة
- التوهج البرتقالي: قوي مع نص "DISCHARGE IMMINENT"
- مقياس الجهد: +45%
- شدة الحقل: 28%
التفسير: ضغط شراء قوي متراكم، انفجار صعودي وشيك
المثال 2: فرصة بيع مثالية ⚡🔴
- الكرة الخضراء: صغيرة وخافتة
- الكرة الحمراء: كبيرة ومضيئة مع نبض داخلي
- التوهج البرتقالي: قوي مع نص "DISCHARGE IMMINENT"
- مقياس الجهد: −52%
- شدة الحقل: 31%
التفسير: ضغط بيع قوي متراكم، انفجار هبوطي وشيك
المثال 3: توازن/انتظار ⚖️
- الكرتان: متساويتان تقريباً في الحجم
- الإضاءة: كلاهما خافت
- التوهج البرتقالي: قوي
- مقياس الجهد: +3%
- شدة الحقل: 24%
التفسير: صراع قوي بدون فائز واضح، انتظر اختراقًا
المثال 4: اتجاه صعودي واضح (لا تفريغ) 📈
- الكرة الخضراء: كبيرة ومضيئة
- الكرة الحمراء: صغيرة جداً وخافتة
- التوهج البرتقالي: لا يوجد
- مقياس الجهد: +68%
- شدة الحقل: 8%
التفسير: سيطرة شرائية واضحة، صراع محدود، مناسب لتتبع الترند الصعودي
المثال 5: تشبع شرائي محتمل ⚠️
- الكرة الخضراء: كبيرة جداً ومضيئة
- الكرة الحمراء: صغيرة جداً
- التوهج البرتقالي: خافت
- مقياس الجهد: +88%
- شدة الحقل: 4%
التفسير: هيمنة شرائية مطلقة، قد يسبق تصحيحاً هبوطياً
█ إشارات التداول
⚡ DISCHARGE IMMINENT (التفريغ الوشيك)
شروط الظهور:
- discharge_prob ≥ 0.9
- اجتياز جميع الفلاتر المفعّلة
- Confirmed (بعد إغلاق الشمعة)
التفسير:
- تراكم طاقة كبير جدًّا
- الضغط وصل لمستوى حرج
- انفجار سعري متوقع خلال 1–3 شموع
كيفية التداول:
1. حدد اتجاه الجهد:
• موجب = توقع صعود
• سالب = توقع هبوط
2. انتظر شمعة تأكيدية:
• للصعود: شمعة صاعدة تغلق فوق افتتاحها
• للهبوط: شمعة هابطة تغلق تحت افتتاحها
3. الدخول: مع افتتاح الشمعة التالية
4. وقف الخسارة: وراء آخر قاع/قمة محلية
5. الهدف: نسبة مخاطرة/عائد 1:2 على الأقل
✅ نصائح احترافية:
- أفضل النتائج عند دمجها مع مستويات الدعم/المقاومة
- تجنّب الدخول إذا كان الجهد قريبًا من الصفر (±5%)
- زِد حجم المركز عند شدة حقل > 30%
⚠️ HIGH TENSION (التوتر العالي)
شروط الظهور:
- 0.7 ≤ discharge_prob < 0.9
التفسير:
- السوق في حالة تراكم طاقة
- احتمال حركة قوية قريبة، لكن ليست فورية
- قد يستمر التراكم أو يحدث تفريغ
كيفية الاستفادة:
- الاستعداد: حضّر أوامر معلقة عند الاختراقات المحتملة
- المراقبة: راقب الشموع التالية بحثًا عن شمعة دافعة
- الانتقاء: لا تدخل كل إشارة — اختر تلك التي تتوافق مع الاتجاه العام
█ استراتيجيات التداول
📈 استراتيجية 1: تداول التفريغ (الأساسية)
المبدأ: الدخول عند "DISCHARGE IMMINENT" في اتجاه الجهد
الخطوات:
1. انتظر ظهور "⚡ DISCHARGE IMMINENT"
2. تحقق من اتجاه الجهد (+/−)
3. انتظر شمعة تأكيدية في اتجاه الجهد
4. ادخل مع افتتاح الشمعة التالية
5. وقف الخسارة وراء آخر قاع/قمة
6. الهدف: نسبة 1:2 أو 1:3
نسبة نجاح عالية جدًّا عند الالتزام بشروط التأكيد.
📈 استراتيجية 2: تتبع الهيمنة
المبدأ: التداول مع القطب المهيمن (الكرة الأكبر والأكثر إضاءة)
الخطوات:
1. حدد القطب المهيمن (الأكبر حجماً والأكثر إضاءة)
2. تداول في اتجاهه
3. احذر عند تقارب الأحجام (صراع)
مناسبة للإطارات الزمنية الأعلى (H1+).
📈 استراتيجية 3: صيد الانعكاس
المبدأ: الدخول عكس الاتجاه عند ظروف معينة
الشروط:
- شدة حقل عالية (>30%)
- جهد متطرف (>±40%)
- تباعد مع السعر (مثل: قمة سعرية جديدة مع تراجع الجهد)
⚠️ عالية المخاطرة — استخدم حجم مركز صغير.
📈 استراتيجية 4: الدمج مع التحليل الفني
أمثلة تأكيد قوي:
- اختراق مقاومة + تفريغ صعودي = إشارة شراء ممتازة
- كسر دعم + تفريغ هبوطي = إشارة بيع ممتازة
- نموذج Head & Shoulders + جهد سالب متزايد = تأكيد النموذج
- تباعد RSI + شدة حقل عالية = انعكاس محتمل
█ التنبيهات الجاهزة
Bullish Discharge
- الشرط: discharge_prob ≥ 0.9 + جهد موجب + جميع الفلاتر
- الرسالة: "⚡ Bullish discharge"
- الاستخدام: فرصة شراء عالية الاحتمالية
Bearish Discharge
- الشرط: discharge_prob ≥ 0.9 + جهد سالب + جميع الفلاتر
- الرسالة: "⚡ Bearish discharge"
- الاستخدام: فرصة بيع عالية الاحتمالية
✅ نصيحة: استخدم هذه التنبيهات مع إعداد "Once Per Bar" لتجنب التكرار.
█ المخرجات في نافذة البيانات
Bias
- القيم: −1 / 0 / +1
- التفسير: −1 = هبوطي، 0 = حياد، +1 = صعودي
- الاستخدام: لدمجها في استراتيجيات آلية
Discharge %
- النطاق: 0–100%
- التفسير: احتمال التفريغ
- الاستخدام: مراقبة تدرّج التوتر (مثال: من 40% إلى 85% في 5 شموع)
Field Strength
- النطاق: 0–100%
- التفسير: شدة الصراع
- الاستخدام: تحديد "نافذة الفرص" (25–35% مثالية للتفريغ)
Voltage
- النطاق: −100% إلى +100%
- التفسير: ميزان القوى
- الاستخدام: مراقبة التطرف (تشبع شرائي/بيعي محتمل)
█ الإعدادات المثلى حسب أسلوب التداول
المضاربة (Scalping)
- الإطار: 1M–5M
- Lookback: 10–15
- Threshold: 0.5–0.6
- Sensitivity: 1.2–1.5
- الفلاتر: Volume + Volatility
التداول اليومي (Day Trading)
- الإطار: 15M–1H
- Lookback: 20
- Threshold: 0.7
- Sensitivity: 1.0
- الفلاتر: Volume + Volatility
السوينغ (Swing Trading)
- الإطار: 4H–D1
- Lookback: 30–50
- Threshold: 0.8
- Sensitivity: 0.8
- الفلاتر: Volatility + Trend
الاستثمار (Position Trading)
- الإطار: D1–W1
- Lookback: 50–100
- Threshold: 0.85–0.95
- Sensitivity: 0.5–0.8
- الفلاتر: جميع الفلاتر
█ نصائح للاستخدام الأمثل
1. ابدأ بالإعدادات الافتراضية
جرّبه أولًا كما هو، ثم عدّل حسب أسلوبك.
2. راقب التوافق بين العناصر
أفضل الإشارات عندما:
- الجهد واضح (>│20%│)
- شدة الحقل معتدلة–عالية (15–35%)
- احتمال التفريغ مرتفع (>70%)
3. استخدم أطر زمنية متعددة
- الإطار الأعلى: تحديد الاتجاه العام
- الإطار الأدنى: توقيت الدخول
- تأكد من توافق الإشارات بين الأطر
4. دمج مع أدوات أخرى
- مستويات الدعم/المقاومة
- خطوط الاتجاه
- أنماط الشموع
- مؤشرات الحجم
5. احترم إدارة المخاطرة
- لا تخاطر بأكثر من 1–2% من الحساب
- استخدم دائمًا وقف الخسارة
- لا تدخل كل الإشارات — اختر الأفضل
█ تحذيرات مهمة
⚠️ ليس للاستخدام المنفرد
المؤشر أداة تحليل مساعِدة — لا تستخدمه بمعزل عن التحليل الفني أو الأساسي.
⚠️ لا يتنبأ بالمستقبل
الحسابات مبنية على البيانات التاريخية — النتائج ليست مضمونة.
⚠️ الأسواق تختلف
قد تحتاج لضبط الإعدادات لكل سوق:
- العملات: تركّز على Volume Filter
- الأسهم: أضف Trend Filter
- الكريبتو: خفّض Threshold قليلًا (أكثر تقلّبًا)
⚠️ الأخبار والأحداث
المؤشر لا يأخذ في الاعتبار الأخبار المفاجئة — تجنّب التداول قبل/أثناء الأخبار الرئيسية.
█ الميزات الفريدة
✅ أول تطبيق للكهرومغناطيسية على الأسواق
نموذج رياضي مبتكر — ليس مجرد مؤشر عادي
✅ كشف استباقي للانفجارات السعرية
يُنبّه قبل حدوث الحركة — وليس بعدها
✅ تصفية متعددة الطبقات
4 فلاتر ذكية تقلل الإشارات الكاذبة إلى الحد الأدنى
✅ تكيف ذكي مع التقلب
يضبط حساسيته تلقائيًّا حسب ظروف السوق
✅ تمثيل بصري ثلاثي الأبعاد متحرك
يجعل القراءة فورية — حتى للمبتدئين
✅ مرونة عالية
يعمل على جميع الأصول: أسهم، عملات، كريبتو، سلع
✅ تنبيهات مدمجة جاهزة
لا حاجة لإعدادات معقدة — جاهز للاستخدام الفوري
█ خاتمة: عندما يلتقي الفن بالعلم
Market Electromagnetic Field ليس مجرد مؤشر — بل فلسفة تحليلية جديدة.
هو الجسر بين:
- دقة الفيزياء في وصف الأنظمة الديناميكية
- ذكاء السوق في توليد فرص التداول
- علم النفس البصري في تسهيل القراءة الفورية
النتيجة: أداة لا تُقرأ — بل تُشاهد، تُشعر، وتُستشعر.
عندما ترى الكرة الخضراء تتوسع، والتوهج يصفرّ، والجزيئات تندفع لليمين — فأنت لا ترى أرقامًا، بل ترى طاقة السوق تتنفّس.
⚠️ إخلاء مسؤولية:
هذا المؤشر لأغراض تعليمية وتحليلية فقط. لا يُمثل نصيحة مالية أو استثمارية أو تداولية. استخدمه بالتزامن مع استراتيجيتك الخاصة وإدارة المخاطر. لا يتحمل TradingView ولا المطور مسؤولية أي قرارات مالية أو خسائر.
XAUUSD Sniper Setup (Pre-Arrows + SL/TP)//@version=5
indicator("XAUUSD Sniper Setup (Pre-Arrows + SL/TP)", overlay=true)
// === Inputs ===
rangePeriod = input.int(20, "Lookback Bars for Zone", minval=5)
maxRangePercent = input.float(0.08, "Max Range % for Consolidation", step=0.01)
tpMultiplier = input.float(1.5, "TP Multiplier")
slMultiplier = input.float(1.0, "SL Multiplier")
// === Consolidation Detection ===
highestPrice = ta.highest(high, rangePeriod)
lowestPrice = ta.lowest(low, rangePeriod)
priceRange = highestPrice - lowestPrice
percentRange = (priceRange / close) * 100
isConsolidation = percentRange < maxRangePercent
// === Zones ===
demandZone = lowestPrice
supplyZone = highestPrice
// === Plot Consolidation Zone Background ===
bgcolor(isConsolidation ? color.new(color.gray, 85) : na)
// === Plot Potential Buy/Sell Levels ===
plot(isConsolidation ? demandZone : na, color=color.green, title="Potential Buy Level", linewidth=2)
plot(isConsolidation ? supplyZone : na, color=color.red, title="Potential Sell Level", linewidth=2)
// === Liquidity Sweep ===
liquidityTakenBelow = low < demandZone
liquidityTakenAbove = high > supplyZone
// === Engulfing Candles ===
bullishEngulfing = close > open and close < open and close > open
bearishEngulfing = close < open and close > open and close < open
// === Break of Structure ===
bosUp = high > ta.highest(high , 5)
bosDown = low < ta.lowest(low , 5)
// === Sniper Entry Conditions ===
buySignal = isConsolidation and liquidityTakenBelow and bullishEngulfing and bosUp
sellSignal = isConsolidation and liquidityTakenAbove and bearishEngulfing and bosDown
// === SL & TP Levels ===
slBuy = demandZone - (priceRange * slMultiplier)
tpBuy = close + (priceRange * tpMultiplier)
slSell = supplyZone + (priceRange * slMultiplier)
tpSell = close - (priceRange * tpMultiplier)
// === PRE-ARROWS (Show Before Breakout) ===
preBuyArrow = isConsolidation ? 1 : na
preSellArrow = isConsolidation ? -1 : na
plotarrow(preBuyArrow, colorup=color.new(color.green, 50), maxheight=20, minheight=20, title="Pre-Buy Arrow")
plotarrow(preSellArrow, colordown=color.new(color.red, 50), maxheight=20, minheight=20, title="Pre-Sell Arrow")
// === SNIPER CONFIRMATION ARROWS ===
buyArrow = buySignal ? 1 : na
sellArrow = sellSignal ? -1 : na
plotarrow(buyArrow, colorup=color.green, maxheight=60, minheight=60, title="Sniper BUY Arrow")
plotarrow(sellArrow, colordown=color.red, maxheight=60, minheight=60, title="Sniper SELL Arrow")
// === BUY SIGNAL ===
if buySignal
label.new(bar_index, low, "BUY\nSL/TP Added", style=label.style_label_up, color=color.green, textcolor=color.white)
line.new(bar_index, slBuy, bar_index + 5, slBuy, color=color.red, style=line.style_dotted)
line.new(bar_index, tpBuy, bar_index + 5, tpBuy, color=color.green, style=line.style_dotted)
label.new(bar_index, slBuy, "SL", color=color.red, style=label.style_label_down)
label.new(bar_index, tpBuy, "TP", color=color.green, style=label.style_label_up)
// === SELL SIGNAL ===
if sellSignal
label.new(bar_index, high, "SELL\nSL/TP Added", style=label.style_label_down, color=color.red, textcolor=color.white)
line.new(bar_index, slSell, bar_index + 5, slSell, color=color.red, style=line.style_dotted)
line.new(bar_index, tpSell, bar_index + 5, tpSell, color=color.green, style=line.style_dotted)
label.new(bar_index, slSell, "SL", color=color.red, style=label.style_label_up)
label.new(bar_index, tpSell, "TP", color=color.green, style=label.style_label_down)
// === Alerts ===
alertcondition(buySignal, title="Sniper BUY", message="Sniper BUY setup on XAUUSD")
alertcondition(sellSignal, title="Sniper SELL", message="Sniper SELL setup on XAUUSD")
OANDA:XAUUSD
Trading Sessions [QuantAlgo]🟢 Overview
The Trading Sessions indicator tracks and displays the four major global trading sessions: Sydney, Tokyo, London, and New York. It provides session-based background highlighting, real-time price change tracking from session open, and a data table with session status. The script works across all markets (forex, equities, commodities, crypto) and helps traders identify when specific geographic markets are active, which directly correlates with changes in liquidity and volatility patterns. Default session times are set to major financial center hours in UTC but are fully adjustable to match your trading methodology.
🟢 Key Features
→ Session Background Color Coding
Each trading session gets a distinct background color on your chart:
1. Sydney Session - Default orange, 22:00-07:00 UTC
2. Tokyo Session - Default red, 00:00-09:00 UTC
3. London Session - Default green, 08:00-16:00 UTC
4. New York Session - Default blue, 13:00-22:00 UTC
When sessions overlap, the color priority is New York > London > Tokyo > Sydney. This means if London and New York are both active, the background shows New York's color. The priority matches typical liquidity and volatility patterns where later sessions generally show higher volume.
→ Color Customization
All session colors are configurable in the Color Settings panel:
1. Click any session color input to open the color picker
2. Select your preferred color for that session
3. Use the "Background Transparency" slider (0-100) to adjust opacity. Lower values = more visible, higher values = more subtle
4. Enable "Color Price Bars" to color candlesticks themselves according to the active session instead of just the background
The Color column in the info table shows a block (█) in each session's assigned color, matching what you see on the chart background.
→ Information Table Breakdown
→ Timeframe Warning
If you're viewing a timeframe of 12 hours or higher, a red warning label appears center-screen. Session boundaries don't render accurately on high timeframes because the time() function in Pine Script can't detect intra-bar session changes when each bar spans multiple sessions. The warning tells you to switch to sub-12H timeframes (e.g., 4H, 1H, 30m, 15m, etc.) for proper session detection. You can disable this warning in Color Settings if needed, but session highlighting can be unreliable on 12H+ charts regardless.
→ Time Range Configuration
Every session's time range is editable in Session Settings:
1. Click the time input field next to each session
2. Enter time as HHMM-HHMM in 24-hour format
3. All times are interpreted as UTC
4. Modify these to account for daylight saving shifts or to define custom session periods based on your backtested optimal trading windows
For example, if your strategy performs best during London/NY overlap specifically, you could set London to 08:00-17:00 and New York to 13:00-22:00 to ensure you see the full overlap highlighted.
→ Weekdays Filter
The "Weekdays Only (Mon-Fri)" toggle controls whether sessions display on weekends:
Enabled: Sessions only show Monday-Friday and hide on Saturday-Sunday. Use this for markets that close on weekends (most equities, forex).
Disabled: Sessions display 24/7 including weekends. Use this for markets that trade continuously (crypto).
→ Table Display Options
The info table has several configuration options in Table Settings:
Visibility: Toggle "Show Info Table" on/off to display or hide the entire table.
Position: Nine position options (Top/Middle/Bottom + Left/Center/Right) let you place the table wherever it doesn't block your price action or other indicators.
Text Size: Four size options (Tiny, Small, Normal, Large) to match your screen resolution and visual preferences.
→ Color Schemes:
Mono: Black background, gray header, white text
Light: White background, light gray header, black text
Blue: Dark blue background, medium blue header, white text
Custom: Manual selection of all five color components (table background, header background, header text, data text, borders)
→ Alert Functionality
The indicator includes ten alert conditions you can access via TradingView's alert system:
Session Opens:
1. Sydney Session Started
2. Tokyo Session Started
3. London Session Started
4. New York Session Started
5. Any Session Started
Session Closes:
6. Sydney Session Ended
7. Tokyo Session Ended
8. London Session Ended
9. New York Session Ended
10. Any Session Ended
These alerts fire when sessions transition based on your configured time ranges, letting you automate monitoring of session changes without watching the chart continuously. Useful for strategies that trade specific session opens/closes or need to adjust position sizing when volatility regime shifts between sessions.
Custom Checklist# Custom Checklist - Trading Preparation & Reminders
A fully customizable checklist overlay indicator for TradingView that helps traders maintain discipline and follow their trading routine systematically.
## 🎯 Purpose
This indicator serves as a visual reminder system on your charts to ensure you complete all necessary analysis steps before entering a trade. Perfect for traders who want to maintain consistency and avoid emotional or rushed trading decisions.
## ✨ Key Features
- **20 Customizable Lines**: Create your own checklist items with any text you need
- **Flexible Display Options**:
- Show/hide title header
- Toggle entire checklist on/off
- Position anywhere on chart (9 positions available)
- Adjustable text size (tiny to huge)
- **Symbol Filtering**: Option to show checklist only on specific symbols (BTC/USD, GOLD, SPX500, USOIL)
- **Customizable Appearance**:
- Background color
- Text color
- Border color
- Transparency controls
- **Clean Interface**: Empty by default - add only the items you need
## 📋 Use Cases
- **Morning Routine**: Daily market preparation checklist
- **Trade Entry Rules**: Verify all setup conditions are met
- **Risk Management**: Confirm stop-loss, position size, and exit strategy
- **Multi-Timeframe Analysis**: Ensure you checked all required timeframes
- **Technical Analysis**: Track which indicators and patterns you've reviewed
- **News & Events**: Remember to check economic calendar and news
- **Personal Rules**: Your custom trading rules and reminders
## 🎨 Customization
Every aspect is customizable:
- All 20 lines can be edited to your needs
- Only non-empty lines are displayed
- Table position adjustable to any corner or middle position
- Color scheme fully customizable to match your chart theme
- Text size scalable for different screen sizes
## 💡 How to Use
1. Add indicator to your chart
2. Open Settings > Checklist Items
3. Fill in your checklist items (Line 1, Line 2, etc.)
4. Customize colors and position in Display Settings
5. Optional: Enable "Show Only on Specific Symbols" to show on select instruments
## 🔧 Display Settings
- **Checklist Title**: Custom header for your checklist
- **Show Title Header**: Toggle title display
- **Show Checklist**: Master on/off switch
- **Symbol Filter**: Restrict display to specific trading instruments
- **Position**: 9 placement options (corners and middle positions)
- **Text Size**: 5 size options (tiny, small, normal, large, huge)
- **Colors**: Background, text, and border fully customizable
## 📝 Example Checklist Ideas
**Swing Trading:**
- Support/Resistance levels identified
- Trend direction confirmed
- Volume analysis completed
- RSI/MACD signals checked
- Risk/Reward ratio calculated
**Day Trading:**
- Pre-market review done
- Key levels marked
- Economic calendar checked
- Trading plan written
- Position size calculated
**Technical Analysis:**
- Multiple timeframe alignment
- Chart patterns identified
- Moving averages reviewed
- Fibonacci levels drawn
- Volume profile analyzed
## ⚙️ Technical Details
- Pine Script v6
- Overlay indicator (displays on main chart)
- Lightweight - no complex calculations
- No repainting
- Works on all timeframes and instruments
## 🎓 Perfect For
- Beginner traders learning systematic analysis
- Experienced traders maintaining discipline
- Anyone who wants visual trading reminders
- Traders following multi-step strategies
- Those prone to FOMO or emotional trading
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**Note**: This is a visual tool only. It does not generate trading signals or perform analysis. It serves as a reminder checklist to help you follow your own trading process consistently.
