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ZigzagLibrary "Zigzag" Zigzag related user defined types. Depends on DrawingTypes library for basic types method tostring(this, sortKeys, sortOrder, includeKeys)   Converts ZigzagTypes/Pivot object to string representation   Namespace types: Pivot   Parameters:      this (Pivot) : ZigzagTypes/Pivot      sortKeys (bool) : If set to true, string output is sorted by keys.      sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys      includeKeys (string ) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered   Returns: string representation of ZigzagTypes/Pivot method tostring(this, sortKeys, sortOrder, includeKeys)   Converts Array of Pivot objects to string representation   Namespace types: Pivot   Parameters:      this (Pivot ) : Pivot object array      sortKeys (bool) : If set to true, string output is sorted by keys.      sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys      includeKeys (string ) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered   Returns: string representation of Pivot object array method tostring(this)   Converts ZigzagFlags object to string representation   Namespace types: ZigzagFlags   Parameters:      this (ZigzagFlags) : ZigzagFlags object   Returns: string representation of ZigzagFlags method tostring(this, sortKeys, sortOrder, includeKeys)   Converts ZigzagTypes/Zigzag object to string representation   Namespace types: Zigzag   Parameters:      this (Zigzag) : ZigzagTypes/Zigzagobject      sortKeys (bool) : If set to true, string output is sorted by keys.      sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys      includeKeys (string ) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered   Returns: string representation of ZigzagTypes/Zigzag method calculate(this, ohlc, indicators, indicatorNames)   Calculate zigzag based on input values and indicator values   Namespace types: Zigzag   Parameters:      this (Zigzag) : Zigzag object      ohlc (float ) : Array containing OHLC values. Can also have custom values for which zigzag to be calculated      indicators (matrix) : Array of indicator values      indicatorNames (string ) : Array of indicator names for which values are present. Size of indicators array should be equal to that of indicatorNames   Returns: current Zigzag object method calculate(this)   Calculate zigzag based on properties embedded within Zigzag object   Namespace types: Zigzag   Parameters:      this (Zigzag) : Zigzag object   Returns: current Zigzag object method nextlevel(this)   Calculate Next Level Zigzag based on the current calculated zigzag object   Namespace types: Zigzag   Parameters:      this (Zigzag) : Zigzag object   Returns: Next Level Zigzag object method clear(this)   Clears zigzag drawings array   Namespace types: ZigzagDrawing   Parameters:      this (ZigzagDrawing ) : array   Returns: void method drawplain(this)   draws fresh zigzag based on properties embedded in ZigzagDrawing object without trying to calculate   Namespace types: ZigzagDrawing   Parameters:      this (ZigzagDrawing) : ZigzagDrawing object   Returns: ZigzagDrawing object method drawfresh(this, ohlc, indicators, indicatorNames)   draws fresh zigzag based on properties embedded in ZigzagDrawing object   Namespace types: ZigzagDrawing   Parameters:      this (ZigzagDrawing) : ZigzagDrawing object      ohlc (float ) : values on which the zigzag needs to be calculated and drawn. If not set will use regular OHLC      indicators (matrix) : Array of indicator values      indicatorNames (string ) : Array of indicator names for which values are present. Size of indicators array should be equal to that of indicatorNames   Returns: ZigzagDrawing object method drawcontinuous(this, ohlc, indicators, indicatorNames)   draws zigzag based on the zigzagmatrix input   Namespace types: ZigzagDrawing   Parameters:      this (ZigzagDrawing) : ZigzagDrawing object      ohlc (float ) : values on which the zigzag needs to be calculated and drawn. If not set will use regular OHLC      indicators (matrix) : Array of indicator values      indicatorNames (string ) : Array of indicator names for which values are present. Size of indicators array should be equal to that of indicatorNames   Returns: method getPrices(pivots)   Namespace types: Pivot   Parameters:      pivots (Pivot ) method getBars(pivots)   Namespace types: Pivot   Parameters:      pivots (Pivot ) Indicator   Indicator is collection of indicator values applied on high, low and close   Fields:      indicatorHigh (series float) : Indicator Value applied on High      indicatorLow (series float) : Indicator Value applied on Low PivotCandle   PivotCandle represents data of the candle which forms either pivot High or pivot low or both   Fields:      _high (series float) : High price of candle forming the pivot      _low (series float) : Low price of candle forming the pivot      length (series int) : Pivot length      pHighBar (series int) : represents number of bar back the pivot High occurred.      pLowBar (series int) : represents number of bar back the pivot Low occurred.      pHigh (series float) : Pivot High Price      pLow (series float) : Pivot Low Price      indicators (Indicator ) : Array of Indicators - allows to add multiple Pivot   Pivot refers to zigzag pivot. Each pivot can contain various data   Fields:      point (chart.point) : pivot point coordinates      dir (series int) : direction of the pivot. Valid values are 1, -1, 2, -2      level (series int) : is used for multi level zigzags. For single level, it will always be 0      componentIndex (series int) : is the lower level zigzag array index for given pivot. Used only in multi level Zigzag Pivots      subComponents (series int) : is the number of sub waves per each zigzag wave. Only applicable for multi level zigzags      microComponents (series int) : is the number of base zigzag components in a zigzag wave      ratio (series float) : Price Ratio based on previous two pivots      sizeRatio (series float)      subPivots (Pivot )      indicatorNames (string ) : Names of the indicators applied on zigzag      indicatorValues (float ) : Values of the indicators applied on zigzag      indicatorRatios (float ) : Ratios of the indicators applied on zigzag based on previous 2 pivots ZigzagFlags   Flags required for drawing zigzag. Only used internally in zigzag calculation. Should not set the values explicitly   Fields:      newPivot (series bool) : true if the calculation resulted in new pivot      doublePivot (series bool) : true if the calculation resulted in two pivots on same bar      updateLastPivot (series bool) : true if new pivot calculated replaces the old one. Zigzag   Zigzag object which contains whole zigzag calculation parameters and pivots   Fields:      length (series int) : Zigzag length. Default value is 5      numberOfPivots (series int) : max number of pivots to hold in the calculation. Default value is 20      offset (series int) : Bar offset to be considered for calculation of zigzag. Default is 0 - which means calculation is done based on the latest bar.      level (series int) : Zigzag calculation level - used in multi level recursive zigzags      zigzagPivots (Pivot ) : array which holds the last n pivots calculated.      flags (ZigzagFlags) : ZigzagFlags object which is required for continuous drawing of zigzag lines. ZigzagObject   Zigzag Drawing Object   Fields:      zigzagLine (series line) : Line joining two pivots      zigzagLabel (series label) : Label which can be used for drawing the values, ratios, directions etc. ZigzagProperties   Object which holds properties of zigzag drawing. To be used along with ZigzagDrawing   Fields:      lineColor (series color) : Zigzag line color. Default is color.blue      lineWidth (series int) : Zigzag line width. Default is 1      lineStyle (series string) : Zigzag line style. Default is line.style_solid.      showLabel (series bool) : If set, the drawing will show labels on each pivot. Default is false      textColor (series color) : Text color of the labels. Only applicable if showLabel is set to true.      maxObjects (series int) : Max number of zigzag lines to display. Default is 300      xloc (series string) : Time/Bar reference to be used for zigzag drawing. Default is Time - xloc.bar_time. ZigzagDrawing   Object which holds complete zigzag drawing objects and properties.   Fields:      zigzag (Zigzag) : Zigzag object which holds the calculations.      properties (ZigzagProperties) : ZigzagProperties object which is used for setting the display styles of zigzag      drawings (ZigzagObject ) : array which contains lines and labels of zigzag drawing.
Libreria Pine Script®
di Trendoscope
7
ZigzagTypesLibrary "ZigzagTypes" Zigzag related user defined types. Depends on DrawingTypes library for basic types Indicator   Indicator is collection of indicator values applied on high, low and close   Fields:      indicatorHigh : Indicator Value applied on High      indicatorLow : Indicator Value applied on Low PivotCandle   PivotCandle represents data of the candle which forms either pivot High or pivot low or both   Fields:      _high : High price of candle forming the pivot      _low : Low price of candle forming the pivot      length : Pivot length      pHighBar : represents number of bar back the pivot High occurred.      pLowBar : represents number of bar back the pivot Low occurred.      pHigh : Pivot High Price      pLow : Pivot Low Price      indicators : Array of Indicators - allows to add multiple Pivot   Pivot refers to zigzag pivot. Each pivot can contain various data   Fields:      point : pivot point coordinates      dir : direction of the pivot. Valid values are 1, -1, 2, -2      level : is used for multi level zigzags. For single level, it will always be 0      ratio : Price Ratio based on previous two pivots      indicatorNames : Names of the indicators applied on zigzag      indicatorValues : Values of the indicators applied on zigzag      indicatorRatios : Ratios of the indicators applied on zigzag based on previous 2 pivots ZigzagFlags   Flags required for drawing zigzag. Only used internally in zigzag calculation. Should not set the values explicitly   Fields:      newPivot : true if the calculation resulted in new pivot      doublePivot : true if the calculation resulted in two pivots on same bar      updateLastPivot : true if new pivot calculated replaces the old one. Zigzag   Zigzag object which contains whole zigzag calculation parameters and pivots   Fields:      length : Zigzag length. Default value is 5      numberOfPivots : max number of pivots to hold in the calculation. Default value is 20      offset : Bar offset to be considered for calculation of zigzag. Default is 0 - which means calculation is done based on the latest bar.      level : Zigzag calculation level - used in multi level recursive zigzags      zigzagPivots : array which holds the last n pivots calculated.      flags : ZigzagFlags object which is required for continuous drawing of zigzag lines. ZigzagObject   Zigzag Drawing Object   Fields:      zigzagLine : Line joining two pivots      zigzagLabel : Label which can be used for drawing the values, ratios, directions etc. ZigzagProperties   Object which holds properties of zigzag drawing. To be used along with ZigzagDrawing   Fields:      lineColor : Zigzag line color. Default is color.blue      lineWidth : Zigzag line width. Default is 1      lineStyle : Zigzag line style. Default is line.style_solid.      showLabel : If set, the drawing will show labels on each pivot. Default is false      textColor : Text color of the labels. Only applicable if showLabel is set to true.      maxObjects : Max number of zigzag lines to display. Default is 300      xloc : Time/Bar reference to be used for zigzag drawing. Default is Time - xloc.bar_time. ZigzagDrawing   Object which holds complete zigzag drawing objects and properties.   Fields:      properties : ZigzagProperties object which is used for setting the display styles of zigzag      drawings : array which contains lines and labels of zigzag drawing.      zigzag : Zigzag object which holds the calculations.
Libreria Pine Script®
di Trendoscope
7
Chart Info & Signature## Overview Chart Info & Signature displays customizable information tables on your TradingView chart. It consists of two independent tables that can be positioned anywhere on the chart and fully customized to match your branding and preferences. --- ## Table 1: Market Info Table ### What It Displays The Market Info Table shows essential trading information: 1. **Exchange** - The exchange name (e.g., "BINANCE", "NASDAQ") 2. **Trading Pair** - The symbol pair (e.g., "BTC/USD", "EUR/USD") with optional timeframe 3. **Date** - Current date in DD/MM/YYYY format 4. **Signature** (optional) - Custom text that appears below the date ### Positioning - **Vertical Position**: Top, Middle, or Bottom of the chart - **Horizontal Position**: Left, Center, or Right of the chart - **Exchange Position**: Can be placed at the top or bottom of the table ### Customization Options #### Exchange Settings - Show/Hide exchange name - Text size (tiny, small, normal, large, huge, auto) - Text color - Background color - Position (top or bottom of table) #### Pair Settings - Pair delimiter (default: "/") - Text size - Text color - Background color #### Timeframe Settings - Show/Hide timeframe (displays current chart timeframe like "1h", "15m", "1D") #### Date Settings - Show/Hide date - Text size - Text color - Background color #### Signature Settings (Below Date) - Show/Hide signature - Custom text - Text size - Text color - Background color - Spacing before signature (with adjustable size) --- ## Table 2: Signature Table ### What It Displays The Signature Table displays up to 3 customizable text lines, perfect for contact information or any custom text you want to display. ### Positioning - **Vertical Position**: Top, Middle, or Bottom of the chart - **Horizontal Position**: Left, Center, or Right of the chart ### Customization Options #### Line 1 (Top Line) - Show/Hide line - Custom text - Text size - Text color - Background color - Spacing after line (with adjustable size) #### Line 2 (Middle Line) - Show/Hide line - Custom text - Text size - Text color - Background color - Spacing after line (with adjustable size) #### Line 3 (Bottom Line) - Show/Hide line - Custom text - Text size - Text color - Background color ### Smart Positioning The table automatically adjusts the spacing between lines based on which lines are visible, ensuring proper alignment regardless of which lines you choose to display. --- ## Key Features ### ✅ Fully Customizable - Every element can be shown or hidden - Individual text sizes for each element - Custom colors for text and backgrounds - Adjustable spacing between elements ### ✅ Flexible Positioning - Each table can be positioned independently - 9 possible positions per table (3 vertical × 3 horizontal) - Tables can overlap or be placed separately ### ✅ Organized Settings - Settings are organized into logical groups and subgroups - Easy to find and modify specific elements - Clean, intuitive settings panel ### ✅ Dynamic Content - Trading pair automatically updates based on chart symbol - Timeframe automatically matches current chart timeframe - Date updates in real-time - Exchange name pulled from symbol information --- ## Text Size Options All text size settings support the following options: - **tiny** - Smallest fixed size - **small** - Small fixed size - **normal** - Standard fixed size - **large** - Large fixed size - **huge** - Largest fixed size - **auto** - Automatically adjusts based on chart zoom and screen size --- ## Default Configuration - **Market Info Table**: Positioned at top-right, showing exchange, pair with timeframe, and date. Signature row in Market Info Table is hidden by default. - **Signature Table**: Positioned at bottom-right, showing 3 signature lines with added spacing between line 1 and line 2 - All text uses semi-transparent white (#ffffff77) by default - All backgrounds are transparent by default --- ## Tips 1. Use **auto** text size for elements that need to scale with chart zoom 2. Use transparent backgrounds for a clean, minimal look 3. Position tables in corners to avoid interfering with price action 4. Customize colors to match your chart theme 5. Hide elements you don't need to keep the display clean
Indicatore Pine Script®
di trader_KDI
Michael's Custom Watermark🔷 MICHAEL'S CUSTOM WATERMARK INDICATOR ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 OVERVIEW A comprehensive chart watermark overlay that displays essential fundamental and technical information for stocks in a clean, customizable table format. Perfect for traders who want quick access to key metrics without cluttering their charts. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✨ KEY FEATURES 📊 Fundamental Data Display — Shows Industry, Sector, Market Cap, and P/E Ratio 📅 Earnings Information — Displays next earnings date with countdown timer 📈 ATR Volatility Indicator — 14-day ATR with color-coded visual alerts (🔴🟡🟢) 🎨 Auto Theme Detection — Automatically adjusts text color based on chart background ⚙️ Fully Customizable — Position, colors, size, and displayed metrics all adjustable 🏢 GICS Sector Mapping — Heuristic-based sector classification aligned with industry standards ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 WHAT MAKES THIS INDICATOR UNIQUE? Unlike basic watermarks, this indicator provides: Real-time fundamental data integration Smart theme-aware color adaptation for both light and dark charts Configurable volatility alerts using ATR thresholds Earnings countdown feature to never miss important dates Optimized display that only shows relevant data for the current symbol type ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📖 HOW TO USE 1. BASIC SETUP Add the indicator to your chart. By default, it displays in the top-left corner with all features enabled. 2. POSITIONING Vertical Location: Top, Middle, or Bottom Horizontal Location: Left, Center, or Right Vertical Offset: Fine-tune position with 0-50 pixel offset from top 3. CUSTOMIZATION OPTIONS TEXT APPEARANCE: Auto Text Color — Enable to automatically adapt text color to your chart theme Manual Color — Set a fixed text color if auto-color is disabled Text Size — Choose from Huge, Large, Normal, or Small Theme Colors — Customize text color for light and dark backgrounds separately DATA DISPLAY TOGGLES: Show Industry & Sector — Display heuristic-based GICS-aligned sector and industry classification Show Market Cap — View market capitalization in T/B/M format Show P/E Ratio — Display Price-to-Earnings ratio (stocks only) Show ATR (14-Day) — Display Average True Range with percentage and visual indicator Show Next Earnings — Display upcoming earnings information Show Earnings Countdown — Show days remaining until next earnings (requires earnings display) 4. ATR VOLATILITY ALERTS Configure custom thresholds to monitor volatility: Red Threshold — ATR percentage that triggers red alert 🔴 (default: 6%) Yellow Threshold — ATR percentage that triggers yellow alert 🟡 (default: 3%) Green — Shows automatically when ATR is below yellow threshold 🟢 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📐 UNDERSTANDING THE DISPLAY 🏢 SECTOR & INDUSTRY Shows the GICS sector classification followed by the specific industry. The indicator uses heuristic-based mapping to align TradingView sectors with standard GICS classifications. Note that this mapping is based on keyword detection and industry analysis, so while generally accurate, it may not perfectly match official GICS classifications in all cases. 💰 MARKET CAP Displays market capitalization using standard abbreviations: T = Trillion B = Billion M = Million 📊 P/E RATIO Shows the trailing twelve-month Price-to-Earnings ratio. Only displayed for stocks when enabled. Shows "N/A" if data is unavailable. 📈 ATR (14-DAY) Displays the 14-period Average True Range in both absolute value and percentage terms, with a color-coded indicator: 🔴 Red: High volatility (above red threshold) 🟡 Yellow: Moderate volatility (between yellow and red thresholds) 🟢 Green: Low volatility (below yellow threshold) 📅 EARNINGS Shows earnings information in three formats: "X days remaining" — When countdown is enabled and earnings date is known "Upcoming" — When date is in the future but countdown is disabled "Recently Reported" — When earnings just occurred "N/A" — When no earnings data is available ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ TECHNICAL DETAILS SUPPORTED INSTRUMENTS: Optimized for stocks with full fundamental data Works with other instruments (crypto, forex, futures) but only displays applicable metrics Automatically suppresses irrelevant data (e.g., P/E for non-stocks) PERFORMANCE: Lightweight overlay with minimal resource usage Updates only on last bar for efficiency No historical recalculation needed COMPATIBILITY: Pine Script v6 Works on all timeframes Compatible with all chart types Auto-adapts to theme changes ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 TIPS & BEST PRACTICES Enable Auto Text Color for seamless theme switching between light and dark modes Adjust vertical offset to avoid overlap with price action in high-volatility periods Use ATR thresholds appropriate to your trading style and asset class Disable features you don't use to keep the watermark clean and focused Position in corners to maximize chart viewing space Use smaller text size for multi-panel layouts ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔧 TROUBLESHOOTING "N/A" SHOWING FOR P/E RATIO: This is normal for non-stock instruments May occur for stocks with negative earnings Check if fundamental data is available for the symbol EARNINGS SHOWING "N/A": Earnings data may not be available for all stocks Check TradingView's data coverage for your symbol TEXT COLOR NOT VISIBLE: Enable Auto Text Color feature Manually set text color to contrast with your chart background Adjust custom light/dark text colors in settings ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ DISCLAIMER This indicator is for informational purposes only. The fundamental data displayed is sourced from TradingView's data providers. Always verify critical information before making trading decisions. Past performance is not indicative of future results. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ If you find this indicator helpful, please give it a boost 🚀 and share your feedback in the comments! Version: 1.0 Pine Script Version: v6 Created by: Michael
Indicatore Pine Script®
di ehudm1
Adaptive Volume‐Demand‐Index (AVDI)Demand Index (according to James Sibbet) – Short Description The Demand Index (DI) was developed by James Sibbet to measure real “buying” vs. “selling” strength (Demand vs. Supply) using price and volume data. It is not a standalone trading signal, but rather a filter and trend confirmer that should always be used together with chart structure and additional indicators. --- \ 1. Calculation Basis\ 1. Volume Normalization $$ \text{normVol}_t = \frac{\text{Volume}_t}{\mathrm{EMA}(\text{Volume},\,n_{\text{Vol}})_t} \quad(\text{e.g., }n_{\text{Vol}} = 13) $$ This smooths out extremely high volume spikes and compares them to the average (≈ 1 means “average volume”). 2. Price Factor $$ \text{priceFactor}_t = \frac{\text{Close}_t - \text{Open}_t}{\text{Open}_t}. $$ Positive values for bullish bars, negative for bearish bars. 3. Component per Bar $$ \text{component}_t = \text{normVol}_t \times \text{priceFactor}_t. $$ If volume is above average (> 1) and the price rises slightly, this yields a noticeably positive value; conversely if the price falls. 4. Raw DI (Rolling Sum) Over a window of \$w\$ bars (e.g., 20): $$ \text{RawDI}_t = \sum_{i=0}^{w-1} \text{component}_{\,t-i}. $$ Alternatively, recursively for \$t \ge w\$: $$ \text{RawDI}_t = \text{RawDI}_{t-1} + \text{component}_t - \text{component}_{\,t-w}. $$ 5. Optional EMA Smoothing An EMA over RawDI (e.g., \$n\_{\text{DI}} = 50\$) reduces short-term fluctuations and highlights medium-term trends: $$ \text{EMA\_DI}_t = \mathrm{EMA}(\text{RawDI},\,n_{\text{DI}})_t. $$ 6.Zero Line Handy guideline: RawDI > 0: Accumulated buying power dominates. RawDI < 0: Accumulated selling power dominates. 2. Interpretation & Application Crossing Zero RawDI above zero → Indication of increasing buying pressure (potential long signal). RawDI below zero → Indication of increasing selling pressure (potential short signal).  Not to be used alone for entry—always confirm with price action. RawDI vs. EMA_DI RawDI > EMA\_DI → Acceleration of demand. RawDI < EMA\_DI → Weakening of demand. Divergences Price makes a new high, RawDI does not make a higher high → potential weakness in the uptrend. Price makes a new low, RawDI does not make a lower low → potential exhaustion of the downtrend. 3. Typical Signals (for Beginners) \ 1. Long Setup\ RawDI crosses zero from below, RawDI > EMA\_DI (acceleration), Price closes above a short-term swing high or resistance. Stop-Loss: just below the last swing low, Take-Profit/Trailing: on reversal signals or fixed R\:R. 2. Short Setup RawDI crosses zero from above, RawDI < EMA\_DI (increased selling pressure), Price closes below a short-term swing low or support. Stop-Loss: just above the last swing high. --- 4. Notes and Parameters Recommended Values (Beginners): Volume EMA (n₍Vol₎) = 13 RawDI window (w) = 20 EMA over DI (n₍DI₎) = 50 (medium-term) or 1 (no smoothing) Attention:\ NEVER use in isolation. Always in combination with price action analysis (trendlines, support/resistance, candlestick patterns). Especially during volatile news phases, RawDI can fluctuate strongly → EMA\_DI helps to avoid false signals. --- Conclusion The Demand Index by James Sibbet is a powerful filter to assess price movements by their volume backing. It shows whether a rally is truly driven by demand or merely a short-term volume anomaly. In combination with classic chart analysis and risk management, it helps to identify robust entry points and potential trend reversals earlier.
Indicatore Pine Script®
di TradeQUO
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
Indicatore Pine Script®
di stockmaniac696
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.
Indicatore Pine Script®
di johndee123
1
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
Indicatore Pine Script®
di SYNC-AND-TRADE
3
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
Libreria Pine Script®
di jason5480
3
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.
Indicatore Pine Script®
di BooBeeDigital1
8
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)
Libreria Pine Script®
di SamaaraDas
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
Indicatore Pine Script®
di loxx
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
Indicatore Pine Script®
di loxx
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
Indicatore Pine Script®
di loxx
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
Indicatore Pine Script®
di loxx
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
Indicatore Pine Script®
di loxx
1
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
Indicatore Pine Script®
di loxx
1
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
Libreria Pine Script®
di gliderfund
2
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.
Indicatore Pine Script®
di MA_PT
6
Q2A_CandlestickPatterns# Q2A Candlestick Patterns Library A comprehensive Pine Script v6 library for detecting 44 candlestick patterns with trend detection and property calculations. ## 📋 Overview The **Q2A_CandlestickPatterns** library provides a complete toolkit for identifying traditional Japanese candlestick patterns in TradingView. It includes both reversal and continuation patterns, organized by the number of candles required (1, 2, 3, and 5 candles). ### Key Features - ✅ **44 Pattern Detection Functions** - Comprehensive coverage of major candlestick patterns - ✅ **Organized by Candle Count** - Easy navigation (1, 2, 3, and 5 candle patterns) - ✅ **Bullish/Bearish/Neutral Classification** - Clear signal categorization - ✅ **Detailed Pattern Descriptions** - Each pattern returns name, type, and explanation - ✅ **Property Calculation Helper** - Core function for analyzing candle characteristics - ✅ **Clean Q2A Code Style** - Professional, maintainable, and well-documented ## 🚀 Quick Start ### Installation ```pinescript import Quant2Alpha/Q2A_CandlestickPatterns/1 as candlePatterns ``` ### Basic Usage Example ```pinescript //@version=6 indicator("Candlestick Pattern Detector", overlay=true) import Quant2Alpha/Q2A_CandlestickPatterns/1 as cp // Calculate candle properties = cp.calculateCandleProperties(open, close, high, low, ta.ema(close - open, 14), 5.0, 10.0, 10.0) // Define trend upTrend = close > ta.sma(close, 50) downTrend = close < ta.sma(close, 50) // Detect patterns = cp.detectHammerBullish(smallBody, body, bodyLo, hl2, dnShadow, 2.0, hasUpShadow, downTrend) = cp.detectShootingStarBearish(smallBody, body, bodyHi, hl2, upShadow, 2.0, hasDnShadow, upTrend) // Visualize if hammerDetected label.new(bar_index, low, hammerName, style=label.style_label_up, color=color.green, textcolor=color.white, size=size.small, tooltip=hammerDesc) if shootingStarDetected label.new(bar_index, high, shootingStarName, style=label.style_label_down, color=color.red, textcolor=color.white, size=size.small, tooltip=shootingStarDesc) ``` ## 📚 Library Structure ### Core Function #### `calculateCandleProperties()` Calculates essential candlestick properties for pattern detection. **Parameters:** - `p_open`, `p_close`, `p_high`, `p_low` - OHLC prices - `bodyAvg` - Average body size (e.g., EMA of body sizes) - `shadowPercent` - Minimum shadow size as % of body (typically 5.0) - `shadowEqualsPercent` - Tolerance for equal shadows (typically 10.0) - `dojiBodyPercent` - Max body size as % of range for doji (typically 10.0) **Returns:** 17 properties including body dimensions, shadows, and candle characteristics ## 📊 Available Patterns ### Single Candle Patterns (13 patterns) #### Bullish (5) | Pattern | Function | Description | | --------------------- | -------------------------------- | ----------------------------------------------------------- | | **Hammer** | `detectHammerBullish()` | Small body at top, long lower shadow, forms in downtrend | | **Inverted Hammer** | `detectInvertedHammerBullish()` | Small body at bottom, long upper shadow, forms in downtrend | | **Marubozu White** | `detectMarubozuWhiteBullish()` | Long green body with little to no shadows | | **Long Lower Shadow** | `detectLongLowerShadowBullish()` | Lower shadow is 75%+ of total range | | **Dragonfly Doji** | `detectDragonflyDojiBullish()` | Doji with long lower shadow, no upper shadow | #### Bearish (5) | Pattern | Function | Description | | --------------------- | -------------------------------- | --------------------------------------------------------- | | **Hanging Man** | `detectHangingManBearish()` | Small body at top, long lower shadow, forms in uptrend | | **Shooting Star** | `detectShootingStarBearish()` | Small body at bottom, long upper shadow, forms in uptrend | | **Marubozu Black** | `detectMarubozuBlackBearish()` | Long red body with little to no shadows | | **Long Upper Shadow** | `detectLongUpperShadowBearish()` | Upper shadow is 75%+ of total range | | **Gravestone Doji** | `detectGravestoneDojiBearish()` | Doji with long upper shadow, no lower shadow | #### Neutral (3) | Pattern | Function | Description | | ---------------------- | -------------------------- | --------------------------------------------- | | **Doji** | `detectDoji()` | Open equals close, indicates indecision | | **Spinning Top White** | `detectSpinningTopWhite()` | Small green body with long shadows both sides | | **Spinning Top Black** | `detectSpinningTopBlack()` | Small red body with long shadows both sides | ### Two Candle Patterns (15 patterns) #### Bullish (7) | Pattern | Function | Description | | ------------------------ | ------------------------------ | ------------------------------------------------------ | | **Rising Window** | `detectRisingWindowBullish()` | Gap up between two candles in uptrend | | **Tweezer Bottom** | `detectTweezerBottomBullish()` | Two candles with identical lows in downtrend | | **Piercing** | `detectPiercingBullish()` | Green candle closes above midpoint of prior red candle | | **Doji Star Bullish** | `detectDojiStarBullish()` | Doji gaps down after red candle in downtrend | | **Engulfing Bullish** | `detectEngulfingBullish()` | Large green candle engulfs prior small red candle | | **Harami Bullish** | `detectHaramiBullish()` | Small green candle contained in prior large red candle | | **Harami Cross Bullish** | `detectHaramiCrossBullish()` | Doji contained in prior large red candle | #### Bearish (8) | Pattern | Function | Description | | ------------------------ | ------------------------------- | ------------------------------------------------------ | | **On Neck** | `detectOnNeckBearish()` | Small green closes near prior red candle's low | | **Falling Window** | `detectFallingWindowBearish()` | Gap down between two candles in downtrend | | **Tweezer Top** | `detectTweezerTopBearish()` | Two candles with identical highs in uptrend | | **Dark Cloud Cover** | `detectDarkCloudCoverBearish()` | Red candle closes below midpoint of prior green candle | | **Doji Star Bearish** | `detectDojiStarBearish()` | Doji gaps up after green candle in uptrend | | **Engulfing Bearish** | `detectEngulfingBearish()` | Large red candle engulfs prior small green candle | | **Harami Bearish** | `detectHaramiBearish()` | Small red candle contained in prior large green candle | | **Harami Cross Bearish** | `detectHaramiCrossBearish()` | Doji contained in prior large green candle | ### Three Candle Patterns (14 patterns) #### Bullish (7) | Pattern | Function | Description | | -------------------------- | ----------------------------------- | ------------------------------------------------ | | **Upside Tasuki Gap** | `detectUpsideTasukiGapBullish()` | Three candles with gap that fails to close | | **Morning Doji Star** | `detectMorningDojiStarBullish()` | Red, gapped doji, green - stronger morning star | | **Morning Star** | `detectMorningStarBullish()` | Red, small middle, green - classic reversal | | **Three White Soldiers** | `detectThreeWhiteSoldiersBullish()` | Three consecutive long green candles | | **Abandoned Baby Bullish** | `detectAbandonedBabyBullish()` | Doji gaps away from both surrounding candles | | **Tri-Star Bullish** | `detectTriStarBullish()` | Three dojis with gaps between them | | **Kicking Bullish** | `detectKickingBullish()` | Black marubozu followed by gapped white marubozu | #### Bearish (7) | Pattern | Function | Description | | -------------------------- | ---------------------------------- | ------------------------------------------------ | | **Downside Tasuki Gap** | `detectDownsideTasukiGapBearish()` | Three candles with gap that fails to close | | **Evening Doji Star** | `detectEveningDojiStarBearish()` | Green, gapped doji, red - stronger evening star | | **Evening Star** | `detectEveningStarBearish()` | Green, small middle, red - classic reversal | | **Three Black Crows** | `detectThreeBlackCrowsBearish()` | Three consecutive long red candles | | **Abandoned Baby Bearish** | `detectAbandonedBabyBearish()` | Doji gaps away from both surrounding candles | | **Tri-Star Bearish** | `detectTriStarBearish()` | Three dojis with gaps between them | | **Kicking Bearish** | `detectKickingBearish()` | White marubozu followed by gapped black marubozu | ### Five Candle Patterns (2 patterns) #### Bullish (1) | Pattern | Function | Description | | ------------------------ | ----------------------------------- | ----------------------------------------------------- | | **Rising Three Methods** | `detectRisingThreeMethodsBullish()` | Long green, three small reds inside range, long green | #### Bearish (1) | Pattern | Function | Description | | ------------------------- | ------------------------------------ | --------------------------------------------------- | | **Falling Three Methods** | `detectFallingThreeMethodsBearish()` | Long red, three small greens inside range, long red | ## 💡 Advanced Usage Examples ### Multi-Pattern Strategy ```pinescript //@version=6 strategy("Multi-Pattern Strategy", overlay=true) import Quant2Alpha/Q2A_CandlestickPatterns/1 as cp // Setup bodyAvg = ta.ema(math.abs(close - open), 14) = cp.calculateCandleProperties(open, close, high, low, bodyAvg, 5.0, 10.0, 10.0) // Trends sma50 = ta.sma(close, 50) sma200 = ta.sma(close, 200) upTrend = close > sma50 and sma50 > sma200 downTrend = close < sma50 and sma50 < sma200 // Detect bullish patterns = cp.detectHammerBullish(smallBody, body, bodyLo, hl2, dnShadow, 2.0, hasUpShadow, downTrend) = cp.detectEngulfingBullish(downTrend, whiteBody, longBody, blackBody, smallBody, close, open) = cp.detectMorningStarBullish(longBody, smallBody, downTrend, blackBody, whiteBody, bodyHi, bodyLo, bodyMiddle) // Detect bearish patterns = cp.detectShootingStarBearish(smallBody, body, bodyHi, hl2, upShadow, 2.0, hasDnShadow, upTrend) = cp.detectDarkCloudCoverBearish(upTrend, whiteBody, longBody, blackBody, open, high, close, bodyMiddle) = cp.detectEveningStarBearish(longBody, smallBody, upTrend, whiteBody, blackBody, bodyLo, bodyHi, bodyMiddle) // Entry signals bullishSignal = hammer or engulfing or morningStar bearishSignal = shootingStar or darkCloud or eveningStar // Execute trades if bullishSignal and strategy.position_size == 0 strategy.entry("Long", strategy.long) if bearishSignal and strategy.position_size > 0 strategy.close("Long") ``` ### Pattern Scanner Indicator ```pinescript //@version=6 indicator("Pattern Scanner", overlay=true) import Quant2Alpha/Q2A_CandlestickPatterns/1 as cp // Configuration showBullish = input.bool(true, "Show Bullish Patterns") showBearish = input.bool(true, "Show Bearish Patterns") showNeutral = input.bool(false, "Show Neutral Patterns") // Calculate properties bodyAvg = ta.ema(math.abs(close - open), 14) = cp.calculateCandleProperties(open, close, high, low, bodyAvg, 5.0, 10.0, 10.0) // Trends upTrend = close > ta.sma(close, 50) downTrend = close < ta.sma(close, 50) // Scan for all patterns and display // (Add pattern detection and visualization logic here) ``` ## 🔧 Configuration Best Practices ### Recommended Parameter Values | Parameter | Typical Value | Description | | ---------------------- | ----------------------------- | ------------------------------- | | `bodyAvg` | `ta.ema(abs(close-open), 14)` | 14-period EMA of body size | | `shadowPercent` | `5.0` | 5% of body for shadow detection | | `shadowEqualsPercent` | `10.0` | 10% tolerance for equal shadows | | `dojiBodyPercent` | `10.0` | Body ≤10% of range = doji | | `factor` (hammer/star) | `2.0` | Shadow should be 2x body size | ### Trend Definition ```pinescript // Simple SMA crossover upTrend = close > ta.sma(close, 50) downTrend = close < ta.sma(close, 50) // Double SMA confirmation upTrend = close > ta.sma(close, 50) and ta.sma(close, 50) > ta.sma(close, 200) downTrend = close < ta.sma(close, 50) and ta.sma(close, 50) < ta.sma(close, 200) // EMA trend upTrend = close > ta.ema(close, 20) downTrend = close < ta.ema(close, 20) ``` ## 📖 Function Return Format All pattern detection functions return a tuple with 4 elements: ```pinescript ``` - **detected** (bool) - `true` if pattern is found, `false` otherwise - **name** (string) - Pattern name (e.g., "Hammer", "Shooting Star") - **type** (string) - "Bullish", "Bearish", or "Neutral" - **description** (string) - Detailed explanation of the pattern ### Example ```pinescript = cp.detectHammerBullish(...) if isHammer log.info("Pattern: " + patternName) // "Hammer" log.info("Type: " + patternType) // "Bullish" log.info("Info: " + patternInfo) // Full description ``` ## 🎯 Pattern Reliability ### High Reliability (Strong Signals) - Engulfing patterns (Bullish/Bearish) - Morning/Evening Star formations - Three White Soldiers / Three Black Crows - Hammer / Shooting Star (with confirmation) ### Medium Reliability (Use with Confirmation) - Harami patterns - Piercing / Dark Cloud Cover - Tweezer Top/Bottom - Doji Star patterns ### Context-Dependent (Require Trend Analysis) - Window patterns (gaps) - Kicking patterns - Tasuki Gap patterns - Three Methods patterns ## 📝 Notes - **Trend Context is Critical**: Most reversal patterns require proper trend identification for accuracy - **Confirmation Recommended**: Wait for next candle confirmation before taking action - **Volume Matters**: Consider volume alongside patterns (not included in this library) - **Multiple Timeframes**: Check patterns across multiple timeframes for stronger signals - **Risk Management**: Always use stop losses regardless of pattern strength ## 🔗 Integration with Other Indicators This library works well with: - Moving averages (trend confirmation) - RSI/Stochastic (overbought/oversold) - Volume indicators (confirmation) - Support/Resistance levels (context) - ATR (position sizing) ## 📄 License This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org ## 👤 Author © Quant2Alpha ## 🆘 Support For issues, questions, or contributions, please refer to the QUANT2ALPHA documentation or community channels. --- **Version:** 1.0 **Pine Script Version:** 6 **Last Updated:** 2025
Libreria Pine Script®
di Quant2Alpha
BAY_PIVOT S/R(4 Full Lines + ALL Labels)//@version=5 indicator("BAY_PIVOT S/R(4 Full Lines + ALL Labels)", overlay=true, max_labels_count=500, max_lines_count=500) // ────────────────────── TOGGLES ────────────────────── showPivot = input.bool(true, "Show Pivot (Full Line + Label)") showTarget = input.bool(true, "Show Target (Full Line + Label)") showLast = input.bool(true, "Show Last Close (Full Line + Label)") showPrevClose = input.bool(true, "Show Previous Close (Full Line + Label)") useBarchartLast = input.bool(true, "Use Barchart 'Last' (Settlement Price)") showR1R2R3 = input.bool(true, "Show R1 • R2 • R3") showS1S2S3 = input.bool(true, "Show S1 • S2 • S3") showStdDev = input.bool(true, "Show ±1σ ±2σ ±3σ") showFib4W = input.bool(true, "Show 4-Week Fibs") showFib13W = input.bool(true, "Show 13-Week Fibs") showMonthHL = input.bool(true, "Show 1M High / Low") showEntry1 = input.bool(false, "Show Manual Entry 1") showEntry2 = input.bool(false, "Show Manual Entry 2") entry1 = input.float(0.0, "Manual Entry 1", step=0.25) entry2 = input.float(0.0, "Manual Entry 2", step=0.25) stdLen = input.int(20, "StdDev Length", minval=1) fib4wBars = input.int(20, "4W Fib Lookback") fib13wBars = input.int(65, "13W Fib Lookback") // ────────────────────── DAILY CALCULATIONS ────────────────────── high_y = request.security(syminfo.tickerid, "D", high , lookahead=barmerge.lookahead_on) low_y = request.security(syminfo.tickerid, "D", low , lookahead=barmerge.lookahead_on) close_y = request.security(syminfo.tickerid, "D", close , lookahead=barmerge.lookahead_on) pivot = (high_y + low_y + close_y) / 3 r1 = pivot + 0.382 * (high_y - low_y) r2 = pivot + 0.618 * (high_y - low_y) r3 = pivot + (high_y - low_y) s1 = pivot - 0.382 * (high_y - low_y) s2 = pivot - 0.618 * (high_y - low_y) s3 = pivot - (high_y - low_y) prevClose = close_y last = useBarchartLast ? request.security(syminfo.tickerid, "D", close , lookahead=barmerge.lookahead_off) : close target = pivot + (pivot - prevClose) // StdDev + Fibs + Monthly (unchanged) basis = ta.sma(close, stdLen) dev = ta.stdev(close, stdLen) stdRes1 = basis + dev stdRes2 = basis + dev*2 stdRes3 = basis + dev*3 stdSup1 = basis - dev stdSup2 = basis - dev*2 stdSup3 = basis - dev*3 high4w = ta.highest(high, fib4wBars) low4w = ta.lowest(low, fib4wBars) fib382_4w = high4w - (high4w - low4w) * 0.382 fib50_4w = high4w - (high4w - low4w) * 0.500 high13w = ta.highest(high, fib13wBars) low13w = ta.lowest(low, fib13wBars) fib382_13w_high = high13w - (high13w - low13w) * 0.382 fib50_13w = high13w - (high13w - low13w) * 0.500 fib382_13w_low = low13w + (high13w - low13w) * 0.382 monthHigh = ta.highest(high, 30) monthLow = ta.lowest(low, 30) // ────────────────────── COLORS ────────────────────── colRed = color.rgb(255,0,0) colLime = color.rgb(0,255,0) colYellow = color.rgb(255,255,0) colOrange = color.rgb(255,165,0) colWhite = color.rgb(255,255,255) colGray = color.rgb(128,128,128) colMagenta = color.rgb(255,0,255) colPink = color.rgb(233,30,99) colCyan = color.rgb(0,188,212) colBlue = color.rgb(0,122,255) colPurple = color.rgb(128,0,128) colRed50 = color.new(colRed,50) colGreen50 = color.new(colLime,50) // ────────────────────── 4 KEY FULL LINES ────────────────────── plot(showPivot ? pivot : na, title="PIVOT", color=colYellow, linewidth=3, style=plot.style_linebr) plot(showTarget ? target : na, title="TARGET", color=colOrange, linewidth=2, style=plot.style_linebr) plot(showLast ? last : na, title="LAST", color=colWhite, linewidth=2, style=plot.style_linebr) plot(showPrevClose ? prevClose : na, title="PREV CLOSE",color=colGray, linewidth=1, style=plot.style_linebr) // ────────────────────── LABELS FOR ALL 4 KEY LEVELS (SAME STYLE AS OTHERS) ────────────────────── f_label(price, txt, bgColor, txtColor) => if barstate.islast and not na(price) label.new(bar_index, price, txt, style=label.style_label_left, color=bgColor, textcolor=txtColor, size=size.small) if barstate.islast showPivot ? f_label(pivot, "PIVOT\n" + str.tostring(pivot, "#.##"), colYellow, color.black) : na showTarget ? f_label(target, "TARGET\n" + str.tostring(target, "#.##"), colOrange, color.white) : na showLast ? f_label(last, "LAST\n" + str.tostring(last, "#.##"), colWhite, color.black) : na showPrevClose ? f_label(prevClose, "PREV CLOSE\n"+ str.tostring(prevClose, "#.##"), colGray, color.white) : na // ────────────────────── OTHER LEVELS – line stops at label ────────────────────── f_level(p, txt, tc, lc, w=1) => if barstate.islast and not na(p) lbl = label.new(bar_index, p, txt, style=label.style_label_left, color=lc, textcolor=tc, size=size.small) line.new(bar_index-400, p, label.get_x(lbl), p, extend=extend.none, color=lc, width=w) if barstate.islast if showR1R2R3 f_level(r1, "R1\n" + str.tostring(r1, "#.##"), color.white, colRed) f_level(r2, "R2\n" + str.tostring(r2, "#.##"), color.white, colRed) f_level(r3, "R3\n" + str.tostring(r3, "#.##"), color.white, colRed, 2) if showS1S2S3 f_level(s1, "S1\n" + str.tostring(s1, "#.##"), color.black, colLime) f_level(s2, "S2\n" + str.tostring(s2, "#.##"), color.black, colLime) f_level(s3, "S3\n" + str.tostring(s3, "#.##"), color.black, colLime, 2) if showStdDev f_level(stdRes1, "+1σ\n" + str.tostring(stdRes1, "#.##"), color.white, colPink) f_level(stdRes2, "+2σ\n" + str.tostring(stdRes2, "#.##"), color.white, colPink) f_level(stdRes3, "+3σ\n" + str.tostring(stdRes3, "#.##"), color.white, colPink, 2) f_level(stdSup1, "-1σ\n" + str.tostring(stdSup1, "#.##"), color.white, colCyan) f_level(stdSup2, "-2σ\n" + str.tostring(stdSup2, "#.##"), color.white, colCyan) f_level(stdSup3, "-3σ\n" + str.tostring(stdSup3, "#.##"), color.white, colCyan, 2) if showFib4W f_level(fib382_4w, "38.2% 4W\n" + str.tostring(fib382_4w, "#.##"), color.white, colMagenta) f_level(fib50_4w, "50% 4W\n" + str.tostring(fib50_4w, "#.##"), color.white, colMagenta) if showFib13W f_level(fib382_13w_high, "38.2% 13W High\n" + str.tostring(fib382_13w_high, "#.##"), color.white, colMagenta) f_level(fib50_13w, "50% 13W\n" + str.tostring(fib50_13w, "#.##"), color.white, colMagenta) f_level(fib382_13w_low, "38.2% 13W Low\n" + str.tostring(fib382_13w_low, "#.##"), color.white, colMagenta) if showMonthHL f_level(monthHigh, "1M HIGH\n" + str.tostring(monthHigh, "#.##"), color.white, colRed50, 2) f_level(monthLow, "1M LOW\n" + str.tostring(monthLow, "#.##"), color.white, colGreen50, 2) // Manual entries plot(showEntry1 and entry1 > 0 ? entry1 : na, "Entry 1", color=colBlue, linewidth=2, style=plot.style_linebr) plot(showEntry2 and entry2 > 0 ? entry2 : na, "Entry 2", color=colPurple, linewidth=2, style=plot.style_linebr) // Background bgcolor(close > pivot ? color.new(color.blue, 95) : color.new(color.red, 95))
Indicatore Pine Script®
di baymont08980
均线变色K线系统 with 转折箭头//@version=6 indicator("均线变色K线系统 with 转折箭头", overlay=true, max_lines_count=500, max_labels_count=200) // 输入参数 ma_length = input.int(20, title="均线周期", minval=1) atr_filter = input.bool(true, title="启用ATR波动过滤") atr_length = input.int(14, title="ATR周期", minval=1) atr_multiplier = input.float(1.5, title="ATR波动阈值", minval=0.1, step=0.1) show_arrows = input.bool(true, title="显示转折箭头") candle_coloring = input.bool(true, title="启用K线变色") // 计算均线和ATR ma = ta.sma(close, ma_length) atr_value = ta.atr(atr_length) avg_atr = ta.sma(atr_value, atr_length) // 判断均线方向和趋势转折点 ma_rising = ta.rising(ma, 1) ma_falling = ta.falling(ma, 1) // 使用更严格的趋势转折检测（避免repainting） ma_rising_prev = ta.rising(ma, 2) ma_falling_prev = ta.falling(ma, 2) // 检测趋势转折点（确保只在K线收盘确认时检测） trend_change_up = ma_rising and not ma_rising_prev and (not atr_filter or atr_value >= avg_atr * atr_multiplier) trend_change_down = ma_falling and not ma_falling_prev and (not atr_filter or atr_value >= avg_atr * atr_multiplier) // 设置颜色 ma_color = ma_rising ? color.rgb(255, 0, 0) : color.rgb(0, 0, 255) // 红/蓝 candle_color = ma_rising ? color.rgb(255, 0, 0) : color.rgb(0, 0, 255) border_color = ma_rising ? color.rgb(255, 0, 0) : color.rgb(0, 0, 255) wick_color = ma_rising ? color.rgb(255, 0, 0) : color.rgb(0, 0, 255) // 绘制彩色均线 plot(ma, color=ma_color, linewidth=2, title="变色均线") // 使用plotcandle绘制彩色K线 plotcandle(candle_coloring ? open : na, candle_coloring ? high : na, candle_coloring ? low : na, candle_coloring ? close : na, title="变色K线", color = candle_color, wickcolor = wick_color, bordercolor = border_color, editable = true) // 绘制趋势转折箭头（只在K线确认时显示） if show_arrows and barstate.isconfirmed if trend_change_up label.new(bar_index, low * 0.998, "▲", color=color.rgb(0, 255, 0), textcolor=color.white, style=label.style_label_up, yloc=yloc.price, size=size.normal) else if trend_change_down label.new(bar_index, high * 1.002, "▼", color=color.rgb(255, 0, 0), textcolor=color.white, style=label.style_label_down, yloc=yloc.price, size=size.normal) // 背景色轻微提示（可选） bgcolor(ma_rising ? color.new(color.red, 95) : color.new(color.blue, 95), title="趋势背景提示")
Indicatore Pine Script®
di damonle
Morning ORB FVG Trigger✅ Overview Morning ORB FVG Trigger is a complete intraday trading framework built around: A Morning Opening Range Breakout (ORB) The first Fair Value Gap (FVG) after that breakout Strict risk management and position sizing Optional HTF trend filter (Daily / Weekly / Monthly) Optional Daily ATR filter to avoid extreme days The script is designed for futures / indices / FX on intraday charts up to 15 minutes and for traders who want a clean, mechanical entry framework with clear risk. 🧠 Core idea Define a morning opening range (e.g. 09:30–09:45). Wait for a clean breakout above/below that range. After the breakout, wait for the first FVG in breakout direction, confirmed by the next candle (no immediate full reclaim). Use a chosen stop logic + R:R factor to build risk/reward boxes. Calculate position size based on your account risk. (Optional) Only take trades: In the direction of the HTF EMA trend (D/W/M). On days where the morning range is within a band of the Daily ATR. You can also disable all signals/boxes and use the script just as a visual ORB tool. ⏰ 1. ORB / Morning Range Inputs (Main section) Morning Range Session Time window of the opening range in exchange time Example: 09:30–09:45 for a 15-minute ORB. You can type custom ranges (e.g. 09:30–09:35 for a 5-minute ORB). Risk/Reward (TP factor) Multiplier for the take-profit distance relative to the stop. 2.0 = TP is 2× the stop distance 1.5 = TP is 1.5× the stop distance Show ORB range If enabled, draws: ORB high/low lines ORB labels (e.g. 15min ORB high / low) Optional midline Extend ORB lines to the right (bars) How many bars to extend the ORB high/low horizontally beyond the ORB itself. Trade box width (bars) Horizontal width (in bars) of: Red risk box (entry–stop) Green reward box (entry–TP) Implementation details The ORB is always calculated on 1-minute data internally, so it stays precise even on 5m/15m charts. The script only works on intraday timeframes up to 15 minutes. 📦 2. FVG Block Group: “FVG” Threshold % Minimum size of an FVG in % of price. 0 = every FVG Higher values = only larger gaps Auto threshold (from volatility) If enabled, the minimum FVG size is derived from historical volatility instead of a fixed percentage. Allow breakout FVG partly inside ORB Off (default): the FVG must lie fully outside the ORB. On: the breakout FVG itself may still overlap the ORB a bit, as long as it is the first one attached to the breakout move. Enable FVG entry signals, boxes & alerts On: full system – FVG detection, entry labels, risk/TP boxes, alerts. Off: no entries, no risk/TP boxes, no alerts. You only get the ORB and (optionally) the HTF dashboard, so you can trade your own setups. Entry mode Entry mode (Mid / Edge / NextOpen) Mid – Entry at the midpoint of the FVG. Edge – Long at the upper FVG edge, short at the lower FVG edge. NextOpen – No limit order in the gap. Entry is placed at the next bar open after FVG confirmation. Edge offset (ticks) Additional offset for Edge entries: Long: +ticks = a bit above the FVG (more conservative) -ticks = deeper into the FVG (more aggressive) Short: +ticks = a bit below the FVG -ticks = deeper into the FVG FVG detection logic Uses a LuxAlgo-style 3-candle FVG pattern (gap between candle 1 and 3). Only one FVG is taken: the first valid FVG after the ORB breakout in breakup direction. The FVG candle is the middle bar; the script: Detects the FVG on the previous bar. Waits for the current bar to confirm it: Bullish: current low must stay above the lower FVG boundary Bearish: current high must stay below the upper FVG boundary Only then an entry signal is generated. 🛑 3. Stop Logic Group: “Stop Logic” Stop mode (PrevBar / Pivot / FVG Candle) PrevBar – Stop at the low/high of the candle before the FVG (tight/aggressive). FVG Candle – Stop at the low/high of the FVG candle itself (medium). Pivot – Stop at the most recent swing high/low using pivotLeft / pivotRight pivots (more conservative). Ticks (stop buffer) Offset (in ticks) from the selected stop level. > 0 = further away (more room, more risk) < 0 = closer (tighter stop) Pivot left / Pivot right Number of candles left/right to define a swing high/low when using Pivot stop mode. Typical intraday values: 2–3. The script also sanity-checks the stop: if the calculated stop would be invalid (e.g. above entry in a long), it moves it by a minimal distance (2 ticks) to keep a valid risk. 📈 4. HTF Trend Filter (Daily / Weekly / Monthly) Group: “HTF Trend Filter” Enable HTF trend filter If enabled, trades are only allowed: Long when at least 2 of D/W/M closes are above their EMA Short when at least 2 of D/W/M closes are below their EMA EMA length (D/W/M) EMA length for all three higher timeframes (Daily, Weekly, Monthly). This helps focus entries in the direction of the dominant higher-timeframe trend. 📊 5. ATR Filter (Daily) Group: “ATR Filter (Daily)” Use daily ATR filter If enabled, the height of the ORB (ORB high – ORB low) must be within a band of the Daily ATR to allow any signals. Daily ATR length ATR period on the Daily timeframe. Min ORB size vs ATR Lower bound: Example: 0.3 → ORB must be at least 0.3 × Daily ATR 0.0 = no minimum. Max ORB size vs ATR Upper bound: Example: 1.5 → ORB must be ≤ 1.5 × Daily ATR 0.0 = no maximum. If the ORB is too small (choppy) or too large (exhausted move), no breakout or FVG signal will be generated on that day. 🧭 6. HTF Dashboard & Signal Labels Group: “HTF Trend Dashboard” Show HTF dashboard Draws a small label at the top of the chart showing: HTF Trend (EMA X) D: UP/FLAT/DOWN W: UP/FLAT/DOWN M: UP/FLAT/DOWN Dashboard position Top Right, Top Center, Top Left – places the dashboard at the top. Over Risk Info – no top dashboard; instead, the HTF trend info is shown as a label near the risk box when a new signal appears. Lookback (bars) for top anchor How many bars to use to determine the top price level for dashboard placement. Show HTF trend above risk box on signal Only relevant if Dashboard position = Over Risk Info. When enabled, a small HTF label appears near the risk box for each new trade. Signal label vertical offset (ticks) Vertical spacing between risk info label and HTF label. Minimum spacing HTF/Risk (ticks) Ensures a minimum vertical distance so the two labels don’t overlap. HTF signal label X offset (bars) Horizontal offset (left/right) relative to the risk info label. ⏳ 7. ORB–FVG Filters (Session & Time Window) Group: “ORB FVG Filter” Only same session day If enabled, FVG entries are only allowed on the same calendar day as the ORB. When the date changes, all state & drawings are reset. Limit hours after ORB Enables a time window after the ORB end. Trading window after ORB (hours) Length of that window in hours. Example: 2.0 → FVG signals only in the first 2 hours after ORB end. 💰 8. Risk Management & Position Sizing Group: “Risk Management” Calculate position size If enabled, the script computes suggested mini and micro contract size for you. Account size Your trading account size (in account currency). Risk mode Percent – risk is a % of account size (Account risk %). Fixed amount – risk is a fixed dollar amount (Fixed risk ($)). Account risk % Risk per trade as a percentage of account size (e.g. 1.0 for 1%). Fixed risk ($) Fixed risk per trade in dollars when using Fixed amount mode. Micro factor (vs mini) How much a micro contract is worth relative to a mini. Example: 0.1 → one micro moves 1/10 of one mini. Risk Info label For each new trade, a label is shown above the boxes with: Stop distance in price and $ risk per mini Max risk allowed for the trade Suggested mini and micro size Text like: Suggested: 2 mini Suggested: 5 micro or Suggested: no trade This makes the script especially useful for prop-firm rules or strict risk discipline. 🎨 9. Visual Style (Boxes, Labels, ORB Lines) Group: “Box & Label Style (Trade)” Label font size (Very small, Small, Normal, Large) Entry label BG / text color Stop label BG / text color TP label BG / text color Risk info BG / text color Risk box color (entry–stop zone) Reward box color (entry–TP zone) Group: “ORB Style” ORB high line color ORB low line color ORB line width ORB label font size ORB label background color ORB label text color Show ORB midline ORB midline color / width / style (Solid / Dashed / Dotted) ⚠️ 10. Alerts Group: “Alerts” The script defines three alert conditions: Long entry FVG breakout Triggered when a new long signal appears. Short entry FVG breakout Triggered when a new short signal appears. FVG entry (long/short) Generic alert for any new signal (long or short). To use them: Add the indicator to the chart. Open the Alerts dialog → “Condition”. Select this script and one of the alert conditions. Set your preferred expiration and notification settings. Alerts only fire when Enable FVG entry signals, boxes & alerts is on. 🧩 11. How the trading logic flows (summary) Build ORB on 1-minute data during the selected session. Optionally reject the day if ORB is outside the ATR bounds. Wait for a breakout (close above high or below low), respecting HTF trend filter. After breakout, look for the first valid FVG in that direction: Outside the ORB (unless breakout FVG allowed inside) Confirmed by the next candle (no full reclaim) Once confirmed: Compute entry, stop, target. Draw risk/reward boxes and all labels. Optionally show HTF signal label over the risk info. Trigger alerts if enabled. If you disable FVG signals, only steps 1–3 (plus dashboard) are effectively active. ⚠️ 12. Notes & Disclaimer Script is intended for intraday trading up to 15-minute timeframes. All signals are mechanical and do not guarantee profitability. Always backtest and forward-test on your own data before risking real money. This script is for educational purposes only and is not financial advice. 🚀 Quick-start guide Add the script to your chart Use an intraday timeframe ≤ 15 minutes (1m, 3m, 5m, 15m). Works best on liquid indices, futures, FX and large-cap stocks. Set the Morning Range In “Morning Range Session” choose the exchange’s opening window. Examples US index futures (CME): 08:30–08:45 or 08:30–08:35 US stocks (NYSE/Nasdaq): 09:30–09:45 or 09:30–09:35 The ORB is always calculated on 1-minute data internally, so the range stays accurate on higher intraday charts. Keep the default filters at first HTF Trend Filter: ON EMA length = 20 This will only allow trades in the direction of the dominant D/W/M trend. ATR Filter: OFF (optional; you can enable later once you’re comfortable). Use the full trade system In the FVG group leave “Enable FVG entry signals, boxes & alerts” = ON Entry mode: Mid Stop mode: FVG Candle or PrevBar Risk/Reward: 2.0 as a starting point. Set your risk Turn on “Calculate position size”. Enter your Account size and choose either: Risk mode = Percent (e.g. 1.0 = 1% per trade), or Risk mode = Fixed amount (e.g. $250 per trade). The risk info label will show: Stop distance in price and $/contract Max allowed risk Suggested mini and micro contract size. Enable alerts (optional) Open the Alerts dialog → Condition: this script. Choose one of: Long entry FVG breakout Short entry FVG breakout FVG entry (long/short) Choose “Once per bar” or “Once per bar close”, and your preferred notification type. Replay & journal Use the TradingView bar replay tool to step through past days. Focus on: How the ORB defines the structure. How the first confirmed FVG outside the ORB behaves. Whether the risk/TP levels fit your own style and product. 🎛 Recommended settings & profiles These are starting points, not rules. Always adapt to the instrument and your own risk tolerance. 1. Conservative / Trend-following Timeframe: 5m or 15m Morning Range Session: 15-minute ORB around the cash or futures open FVG Threshold %: 0.05–0.1 (filter out very small gaps) Auto threshold: OFF (keep it simple) Allow breakout FVG partly inside ORB: OFF Enable FVG entry signals/boxes/alerts: ON Entry mode: Mid Stop Logic Stop mode: Pivot Pivot left/right: 2–3 Stop buffer: +1–2 ticks HTF Trend Filter Enabled: ON EMA length: 20 ATR Filter Enabled: ON Daily ATR length: 14 Min ORB vs ATR: 0.3–0.4 Max ORB vs ATR: 1.2–1.5 Risk Management Risk mode: Percent Account risk: 0.5–1.0% Idea: Only trade when the higher-timeframe trend supports the move and the opening range is of a “normal” size for the current volatility. 2. Balanced / Intraday directional Timeframe: 3m or 5m FVG Threshold %: 0.02–0.05 Auto threshold: ON (lets the script adapt to volatility) Allow breakout FVG partly inside ORB: ON (first breakout FVG may partly sit inside the ORB) Entry mode: Edge Edge offset (ticks): 0 or +1 Stop Logic Stop mode: FVG Candle Stop buffer: 0–1 ticks HTF Trend Filter Enabled: ON ATR Filter Enabled: OFF (optional) Risk Management Risk mode: Percent Account risk: 1.0–1.5% (if this fits your plan) Idea: Slightly more aggressive entries at the gap edge, still aligned with HTF trend, but with more flexibility on ATR. 3. Aggressive / Scalping around the ORB Timeframe: 1m or 3m FVG Threshold %: 0.0–0.02 Auto threshold: ON Allow breakout FVG partly inside ORB: ON Entry mode: NextOpen or Edge with a negative offset (deeper into the gap) Stop Logic Stop mode: PrevBar Stop buffer: 0 or -1 tick HTF Trend Filter Enabled: OFF (or ON but treat as soft guidance) ATR Filter Enabled: OFF Risk Management Risk mode: Percent Account risk: lower, e.g. 0.25–0.5% per trade Idea: More trades and tighter stops. Best for experienced traders who understand the limitations of scalping and whipsaw risk. Final reminder All of these are templates, not guarantees: Always check how the system behaves on your market and session. Start on replay and demo before trading real money. Adjust filters (HTF, ATR, thresholds) until the signals fit your personal approach.
Indicatore Pine Script®
di SebastianMaywald
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