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BarLibrary "Bar" A comprehensive library for creating and managing custom multi-timeframe (MTF) candlestick bars without using request.security calls, providing enhanced visualization and analytical capabilities with improved performance Candle()   Creates a new candle object initialized with current bar's OHLC data   Returns: A new _Candle instance with current market data method body(this)   Calculates the absolute size of the candle body (distance between open and close)   Namespace types: _Candle   Parameters:      this (_Candle)   Returns: The absolute difference between closing and opening prices method topWick(this)   Calculates the length of the upper wick (shadow above the candle body)   Namespace types: _Candle   Parameters:      this (_Candle)   Returns: The distance from the higher of open/close to the high price method bottomWick(this)   Calculates the length of the lower wick (shadow below the candle body)   Namespace types: _Candle   Parameters:      this (_Candle)   Returns: The distance from the low price to the lower of open/close method display(this, bullishColor, bearishColor, transp, borderWidth, lineWidth)   Renders the candle visually on the chart with customizable colors and styling options   Namespace types: _Candle   Parameters:      this (_Candle)      bullishColor (color)      bearishColor (color)      transp (int)      borderWidth (int)      lineWidth (int) candles(tf, autoDisplay)   Creates and manages an array of custom timeframe candles with optional automatic display   Parameters:      tf (string) : Target timeframe string (e.g., "60", "240", "D") for candle aggregation      autoDisplay (bool)   Returns: Array containing all completed candles for the specified timeframe _Candle   Custom candlestick data structure that stores OHLCV data with visual rendering components   Fields:      start (series int) : Opening timestamp of the candle period      end (series int) : Closing timestamp of the candle period      o (series float) : Opening price of the candle      h (series float) : Highest price reached during the candle period      l (series float) : Lowest price reached during the candle period      c (series float) : Closing price of the candle      v (series float) : Volume traded during the candle period      bodyBox (series box)      wickLine (series line) Example Usage // Change version with latest version import EmreKb/Bar/1 as bar // "240" for 4h timeframe // true for auto display candles on chart (default: false) candlesArr = bar.candles("240", true)
Pine Script® library
by EmreKb
zuperviewResourcesLibrary "zuperview" ComputeMAValue(maType, series, period)   ComputeMAValue @description Computes the moving average (MA) value based on the specified MA type.   Parameters:      maType (string) : (string) The type of moving average: "EMA", "SMA", "RMA", "WMA", "HMA", "VWMA", "LinReg".      series (float) : (float) The input price series (typically close).      period (simple int) : (int) The number of periods used for MA calculation.   Returns: (float) The computed MA value or `na` if maType is invalid. ComputeATRValue(period)   ComputeATRValue @description Computes the moving average (ATR) value based on the specified ATR type.   Parameters:      period (int) : (int) The number of periods used for MA calculation.   Returns: (float) The computed ATR value or `na` if maType is invalid. Max(src, period)   Parameters:      src (float)      period (int) Min(src, period)   Parameters:      src (float)      period (int) ComputeRSIValue(src, period, smooth)   ComputeRSIValue @description Computes the moving average (RSI) value based on the specified RSI type.   Parameters:      src (float) : (series) Input series (series float), which can be close (`close`), open (`open`), high (`high`), low (`low`), or any other price-based series.      period (int) : (int) The number of periods used for MA calculation.      smooth (int)   Returns: (float) The computed RSI value or `na` if maType is invalid. ComputeSMMAValue(src, period)   ComputeSMMAValue @description Computes the moving average (SMMA) value based on the specified SMMA type.   Parameters:      src (float) : (series) Input series (series float), which can be close (`close`), open (`open`), high (`high`), low (`low`), or any other price-based series.      period (int) : (int) The number of periods used for MA calculation.   Returns: (float) The computed SMMA value or `na` if maType is invalid. ComputeStochasticValue(src, periodD, periodK, smoothingMethod, smoothingPeriod)   ComputeStochasticValue @description Computes the moving average (SMMA) value based on the specified SMMA type.   Parameters:      src (float) : (series) Input series (series float), which can be close (`close`), open (`open`), high (`high`), low (`low`), or any other price-based series.      periodD (simple int) : (int) The number of periods used for MA calculation.      periodK (int) : (int) The number of periods used for MA calculation.      smoothingMethod (string) : (string) The type of moving average: "EMA", "SMA", "RMA", "WMA", "HMA", "VWMA", "LinReg".      smoothingPeriod (simple int) : (int) The number of periods used for MA calculation.   Returns: (float) The computed Stochastic(K, D) value or `na` if maType is invalid. FindSwingsByNeighborhood(arraySwingTop, arraySwingBottom, neighborhood)   Find Swings By Neighborhood @description Computes the moving average (SMMA) value based on the specified SMMA type.   Parameters:      arraySwingTop (array) : (array): An array to store detected swing highs.      arraySwingBottom (array) : (array): An array to store detected swing lows.      neighborhood (int) : (int): The number of bars to consider when identifying a swing point.   Returns: none FindSwingsByOffset(arraySwingTop, arraySwingBottom, minSwingLength)   Find Swings By Offset @description Identifies swing points based on a minimum swing length criteria.   Parameters:      arraySwingTop (array) : (array): An array to store detected swing highs.      arraySwingBottom (array) : (array): An array to store detected swing lows.      minSwingLength (float) : (float): The minimum price movement required to qualify as a swing point.   Returns: none SwingPoint   Fields:      Key (series int)      IsTop (series bool)      Price (series float)      BarStart (series int)      BarEnd (series int)      TimeStart (series int)      TimeEnd (series int)      Sign (series int)      Label (series label)
Pine Script® library
by ZuperView
BecakFloatingPanelsLibrary "BecakFloatingPanels" Library for creating floating indicator panels with MACD, RSI, and Stochastic indicators calculateMacd(source, fastLength, slowLength, signalLength)   Calculate MACD components   Parameters:      source (float) : Price source for calculation      fastLength (simple int) : Fast EMA period      slowLength (simple int) : Slow EMA period      signalLength (simple int) : Signal line period   Returns: MacdData MACD calculation results calculateRsi(source, length)   Calculate RSI   Parameters:      source (float) : Price source for calculation      length (simple int) : RSI period   Returns: float RSI value calculateStochastic(source, high, low, kLength, kSmoothing, dSmoothing)   Calculate Stochastic components   Parameters:      source (float) : Price source for calculation      high (float) : High prices      low (float) : Low prices      kLength (int) : %K period      kSmoothing (int) : %K smoothing period      dSmoothing (int) : %D smoothing period   Returns: StochData Stochastic calculation results calculateStochSignals(stochK, stochD, overboughtLevel, oversoldLevel)   Calculate Stochastic signals   Parameters:      stochK (float) : Stochastic %K series      stochD (float) : Stochastic %D series      overboughtLevel (float) : Overbought threshold      oversoldLevel (float) : Oversold threshold   Returns: StochSignals Signal flags calculateChartMetrics(high, low, lookbackLength)   Calculate chart range and positioning metrics   Parameters:      high (float) : High prices      low (float) : Low prices      lookbackLength (int) : Lookback period   Returns: ChartMetrics Chart positioning data calculateMacdRange(macdLine, signalLine, histogram, safeLookback)   Calculate MACD range for normalization   Parameters:      macdLine (float) : MACD line series      signalLine (float) : Signal line series      histogram (float) : Histogram series      safeLookback (int) : Lookback period   Returns: MacdRange MACD range metrics initVisualArrays()   Initialize visual arrays   Returns: VisualArrays Container with initialized arrays clearVisuals(visuals)   Clear all visual elements   Parameters:      visuals (VisualArrays) : VisualArrays container   Returns: void calculatePanelPositions(chartMetrics, oscPlacement, panelHeight, panelSpacing, centerOffset)   Calculate panel positions based on placement option   Parameters:      chartMetrics (ChartMetrics) : Chart metrics object      oscPlacement (string) : Panel placement option      panelHeight (float) : Panel height percentage      panelSpacing (float) : Panel spacing percentage      centerOffset (float) : Center offset percentage   Returns: PanelPositions Panel boundary coordinates createPanelBackgrounds(visuals, positions, panelLeft, panelRight, showBackground, transparency)   Create panel backgrounds   Parameters:      visuals (VisualArrays) : VisualArrays container      positions (PanelPositions) : PanelPositions object      panelLeft (int) : Left boundary      panelRight (int) : Right boundary      showBackground (bool) : Show background flag      transparency (int) : Background transparency   Returns: void drawReferenceLines(visuals, positions, chartMetrics, macdRange, dataLeft, dataRight, panelHeight, rsiOverbought, rsiOversold, stochOverbought, stochOversold)   Draw reference lines for all panels   Parameters:      visuals (VisualArrays) : VisualArrays container      positions (PanelPositions) : PanelPositions object      chartMetrics (ChartMetrics) : ChartMetrics object      macdRange (MacdRange) : MacdRange object      dataLeft (int) : Left data boundary      dataRight (int) : Right data boundary      panelHeight (float) : Panel height percentage      rsiOverbought (int) : RSI overbought level      rsiOversold (int) : RSI oversold level      stochOverbought (int) : Stochastic overbought level      stochOversold (int) : Stochastic oversold level   Returns: void drawMacdIndicator(visuals, macdLine, signalLine, histogram, macdRange, positions, chartMetrics, barIndex, nextBarIndex, barIndexOffset, panelHeight)   Draw MACD indicator   Parameters:      visuals (VisualArrays) : VisualArrays container      macdLine (float) : MACD line series      signalLine (float) : Signal line series      histogram (float) : Histogram series      macdRange (MacdRange) : MacdRange object      positions (PanelPositions) : PanelPositions object      chartMetrics (ChartMetrics) : ChartMetrics object      barIndex (int) : Current bar index      nextBarIndex (int) : Next bar index      barIndexOffset (int) : Horizontal offset      panelHeight (float) : Panel height percentage   Returns: void drawRsiIndicator(visuals, rsiValue, positions, chartMetrics, barIndex, nextBarIndex, barIndexOffset, panelHeight)   Draw RSI indicator   Parameters:      visuals (VisualArrays) : VisualArrays container      rsiValue (float) : RSI value      positions (PanelPositions) : PanelPositions object      chartMetrics (ChartMetrics) : ChartMetrics object      barIndex (int) : Current bar index      nextBarIndex (int) : Next bar index      barIndexOffset (int) : Horizontal offset      panelHeight (float) : Panel height percentage   Returns: void drawStochasticIndicator(visuals, stochK, stochD, positions, chartMetrics, barIndex, nextBarIndex, barIndexOffset, panelHeight, stochOverbought, stochOversold)   Draw Stochastic indicator   Parameters:      visuals (VisualArrays) : VisualArrays container      stochK (float) : Stochastic %K series      stochD (float) : Stochastic %D series      positions (PanelPositions) : PanelPositions object      chartMetrics (ChartMetrics) : ChartMetrics object      barIndex (int) : Current bar index      nextBarIndex (int) : Next bar index      barIndexOffset (int) : Horizontal offset      panelHeight (float) : Panel height percentage      stochOverbought (int) : Overbought level      stochOversold (int) : Oversold level   Returns: void addStochasticSignals(visuals, buySignal, sellSignal, positions, chartMetrics, currentBarIndex, barIndexOffset, panelHeight, signalIndex)   Add Stochastic buy/sell signals   Parameters:      visuals (VisualArrays) : VisualArrays container      buySignal (bool) : Buy signal series      sellSignal (bool) : Sell signal series      positions (PanelPositions) : PanelPositions object      chartMetrics (ChartMetrics) : ChartMetrics object      currentBarIndex (int) : Current bar index      barIndexOffset (int) : Horizontal offset      panelHeight (float) : Panel height percentage      signalIndex (int) : Signal index for lookback   Returns: void setPanelLabels(macdLabel, rsiLabel, stochLabel, positions, chartMetrics, labelOffset, panelHeight, barIndexOffset)   Set panel title labels   Parameters:      macdLabel (label) : MACD label reference      rsiLabel (label) : RSI label reference      stochLabel (label) : Stochastic label reference      positions (PanelPositions) : PanelPositions object      chartMetrics (ChartMetrics) : ChartMetrics object      labelOffset (int) : Label horizontal offset      panelHeight (float) : Panel height percentage      barIndexOffset (int) : Horizontal offset   Returns: void showDebugInfo(chartMetrics, debugMode)   Display debug information   Parameters:      chartMetrics (ChartMetrics) : ChartMetrics object      debugMode (bool) : Debug mode flag   Returns: void ChartMetrics   Chart metrics container   Fields:      visibleHigh (series float) : Highest visible price      visibleLow (series float) : Lowest visible price      chartRange (series float) : Price range of chart      chartCenter (series float) : Center point of chart MacdData   MACD calculation results   Fields:      macdLine (series float) : Main MACD line      signalLine (series float) : Signal line      histogram (series float) : MACD histogram MacdRange   MACD range metrics for normalization   Fields:      highest (series float) : Highest MACD value      lowest (series float) : Lowest MACD value      BRange (series float) : Total range StochData   Stochastic calculation results   Fields:      k_smooth (series float) : Smoothed %K line      d (series float) : %D line StochSignals   Stochastic signals   Fields:      buySignal (series bool) : Buy signal flag      sellSignal (series bool) : Sell signal flag PanelPositions   Panel positioning data   Fields:      macdTop (series float) : MACD panel top      macdBottom (series float) : MACD panel bottom      rsiTop (series float) : RSI panel top      rsiBottom (series float) : RSI panel bottom      stochTop (series float) : Stochastic panel top      stochBottom (series float) : Stochastic panel bottom VisualArrays   Visual elements arrays container   Fields:      macdLines (array) : Array of MACD lines      macdHist (array) : Array of MACD histogram boxes      rsiLines (array) : Array of RSI lines      stochLines (array) : Array of Stochastic lines      stochAreas (array) : Array of Stochastic areas      stochSignals (array) : Array of Stochastic signals      panelBackgrounds (array) : Array of panel backgrounds
Pine Script® library
by kromut76
ConcatenatedAlertsHi all! This library is useful if you want to concatenate every tick alert for sending on bar close. The 'alert()' function, provided by Tradingview, with the 'freq' parameter set to 'alert.freq_once_per_bar_close' only fires when the realtime bar closes. So if something has happened intrabar, the alert wont be sent. This library concatenates all alert messages during the bar and sends them on bar close with a header saying how many messages it contains. It's useful in many cases, but here are a few examples: When you want alerts for a zone having a breakout (with a candle close) and another one being entered, like this: When a candle breaks through 2, or more, lines. Like in this example: There are of course more useful use cases, but above is 2 examples. The library uses an own enum saying 'alert.freq_all', 'alert.freq_once_per_bar' and 'alert.freq_once_per_bar_close'. The value of this enumeration represents how often an alert will be sent. 'alert.freq_all' and 'alert.freq_once_per_bar' will behave as the once in the 'alert()' function provided by Tradingview. No concatenatination will take place in this case. However, when 'alert.freq_once_per_bar_close' is set, concatenatination will happen with all alert messages during the bar and sent on bar close. Helper functions can be used for both the string value used by the 'alert()' function by Tradingview and this enum type. Example code is provided in the source code, with the usage of input values for both this string and the enumeration. Hope this is of help! Concatenate(a_lert, message)   Concatenates all alert messages (called on every tick) to fire all of them with 'Alert()'.   Parameters:      a_lert (Alert) : The 'Alert' object to be used for the alert messages concatination.      message (string) : The string message to be added to the bar alert. Alert(a_lert)   When the 'Alert.Frequency' is set to fire on the current tick, this function will concatenate all messages on the current bar and fire an alert. Concatenation will occur if 'alert.freq_once_per_bar_close' is set on 'a_lert.Frequency' separated by new lines and a header saying how many messages the bar contains.   Parameters:      a_lert (Alert) : The 'Alert' object to be used for the alert messages concatination and all its 'Messages' will be alerted. Create(frequency)   Helper function to create an 'Alert' object.   Parameters:      frequency (series Frequency) : The 'Frequency' in the created 'Alert' object.   Returns: The 'Alert' object that can be used for concatination. CreateFromAlertFreq(alertFreq)   Helper function to convert 'alert.freq_all', 'alert.freq_once_per_bar' or 'lert.freq_once_per_bar_close'.   Parameters:      alertFreq (string) : The 'alert.freq_all', 'alert.freq_once_per_bar' or 'lert.freq_once_per_bar_close' to convert to 'Frequency' enum.   Returns: The 'Alert' object that can be used for concatination. Alert   Holds all the values for the 'Alert' to be used.   Fields:      Messages (array) : Holds the alert messages within the current bar that will be sent according to 'Frequency'.      Frequency (series Frequency) : The frequency for the final alert. One of 'alert.freq_all', 'alert.freq_once_per_bar' or 'alert.freq_once_per_bar_close'. If 'alert.freq_all' is set the alert messages will be fired on each tick and no concatination will occure. The same when 'alert.freq_once_per_bar' is set, but the alert will only fire once per bar. If 'alert.freq_once_per_bar_close' is set concatenation will occure before sending an alert (with all concatenated messages) on bar close.      SkipAddition (series bool) : Will skip addition of messages. Used internally if 'Frequency' is 'alert.freq_once_per_bar'.
Pine Script® library
by mickes
MarketStructureLibMarketStructure Library This library extends the "MarketStructure" library by mickes () under the Mozilla Public License 2.0, credited to mickes. It provides functions for detecting and visualizing market structure, including Break of Structure (BOS), Change of Character (CHoCH), Equal High/Low (EQH/EQL), and liquidity zones, with enhancements for improved accuracy and customization. Functionality Market Structure Detection: Identifies internal (orderflow) and swing market structures using pivot points, with support for BOS, CHoCH, and EQH/EQL. Volatility Filter: Only confirms pivots when the ATR exceeds a user-defined threshold, reducing false signals in low-volatility markets. Trend Strength Metric: Calculates a trend strength score based on pivot frequency and volatility, stored in the Structure type for use in scripts. Customizable Visualizations: Allows users to configure line styles and colors for BOS and CHoCH, and label sizes for pivots, BOS, CHoCH, and liquidity. Liquidity Zones: Visualizes liquidity levels with confirmation bars and lookback periods. Methodology Pivot Detection: Uses ta.pivothigh and ta.pivotlow with a volatility filter (ATR multiplier) to confirm significant pivots. Trend Strength: Computes a score as pivotCount / LeftLength * (currentATR / ATR), reflecting trend reliability based on pivot frequency and market volatility. BOS/CHoCH Logic: Detects BOS when price breaks a pivot in the trend direction, and CHoCH when price reverses against the trend, with labels for "MSF" or "MSF+" based on pivot patterns. EQH/EQL Zones: Creates boxes around equal highs/lows within an ATR-based threshold, with optional extension. Visualization: Draws lines and labels for BOS, CHoCH, and liquidity, with user-defined styles, colors, and sizes. Usage Integration: Import into Pine Script indicators (e.g., import Fenomentn/MarketStructure/1) to analyze market structure. Configuration: Set pivot lengths, volatility threshold, label sizes, and visualization styles via script inputs. Alerts: Enable alerts for BOS, CHoCH, and EQH/EQL events, triggered on bar close to avoid repainting. Best Practices: Use on forex or crypto charts (1m to 12h timeframes) for optimal results. Adjust the volatility threshold for different market conditions. Originality This library builds on mickes’ framework by adding: A volatility-based pivot filter to enhance signal accuracy. A trend strength metric for assessing trend reliability. Dynamic label sizing and customizable visualization styles for better usability. No additional open-source code was reused beyond mickes’ library, credited under MPL 2.0. Developed by Fenomentn. Published under Mozilla Public License 2.0.
Pine Script® library
by Fenomentn
TimeSeriesBenchmarkMeasuresLibrary "TimeSeriesBenchmarkMeasures" Time Series Benchmark Metrics. \ Provides a comprehensive set of functions for benchmarking time series data, allowing you to evaluate the accuracy, stability, and risk characteristics of various models or strategies. The functions cover a wide range of statistical measures, including accuracy metrics (MAE, MSE, RMSE, NRMSE, MAPE, SMAPE), autocorrelation analysis (ACF, ADF), and risk measures (Theils Inequality, Sharpness, Resolution, Coverage, and Pinball). ___ Reference: - github.com . - medium.com . - www.salesforce.com . - towardsdatascience.com . - github.com . mae(actual, forecasts)   In statistics, mean absolute error (MAE) is a measure of errors between paired observations expressing the same phenomenon. Examples of Y versus X include comparisons of predicted versus observed, subsequent time versus initial time, and one technique of measurement versus an alternative technique of measurement.   Parameters:      actual (array) : List of actual values.      forecasts (array) : List of forecasts values.   Returns: - Mean Absolute Error (MAE). ___ Reference: - en.wikipedia.org . - The Orange Book of Machine Learning - Carl McBride Ellis . mse(actual, forecasts)   The Mean Squared Error (MSE) is a measure of the quality of an estimator. As it is derived from the square of Euclidean distance, it is always a positive value that decreases as the error approaches zero.   Parameters:      actual (array) : List of actual values.      forecasts (array) : List of forecasts values.   Returns: - Mean Squared Error (MSE). ___ Reference: - en.wikipedia.org . rmse(targets, forecasts, order, offset)   Calculates the Root Mean Squared Error (RMSE) between target observations and forecasts. RMSE is a standard measure of the differences between values predicted by a model and the values actually observed.   Parameters:      targets (array) : List of target observations.      forecasts (array) : List of forecasts.      order (int) : Model order parameter that determines the starting position in the targets array, `default=0`.      offset (int) : Forecast offset related to target, `default=0`.   Returns: - RMSE value. nmrse(targets, forecasts, order, offset)   Normalised Root Mean Squared Error.   Parameters:      targets (array) : List of target observations.      forecasts (array) : List of forecasts.      order (int) : Model order parameter that determines the starting position in the targets array, `default=0`.      offset (int) : Forecast offset related to target, `default=0`.   Returns: - NRMSE value. rmse_interval(targets, forecasts)   Root Mean Squared Error for a set of interval windows. Computes RMSE by converting interval forecasts (with min/max bounds) into point forecasts using the mean of the interval bounds, then compares against actual target values.   Parameters:      targets (array) : List of target observations.      forecasts (matrix) : The forecasted values in matrix format with at least 2 columns (min, max).   Returns: - RMSE value for the combined interval list. mape(targets, forecasts)   Mean Average Percentual Error.   Parameters:      targets (array) : List of target observations.      forecasts (array) : List of forecasts.   Returns: - MAPE value. smape(targets, forecasts, mode)   Symmetric Mean Average Percentual Error. Calculates the Mean Absolute Percentage Error (MAPE) between actual targets and forecasts. MAPE is a common metric for evaluating forecast accuracy, expressed as a percentage, lower values indicate a better forecast accuracy.   Parameters:      targets (array) : List of target observations.      forecasts (array) : List of forecasts.      mode (int) : Type of method: default=0:`sum(abs(Fi-Ti)) / sum(Fi+Ti)` , 1:`mean(abs(Fi-Ti) / ((Fi + Ti) / 2))` , 2:`mean(abs(Fi-Ti) / (abs(Fi) + abs(Ti))) * 100`   Returns: - SMAPE value. mape_interval(targets, forecasts)   Mean Average Percentual Error for a set of interval windows.   Parameters:      targets (array) : List of target observations.      forecasts (matrix) : The forecasted values in matrix format with at least 2 columns (min, max).   Returns: - MAPE value for the combined interval list. acf(data, k)   Autocorrelation Function (ACF) for a time series at a specified lag.   Parameters:      data (array) : Sample data of the observations.      k (int) : The lag period for which to calculate the autocorrelation. Must be a non-negative integer.   Returns: - The autocorrelation value at the specified lag, ranging from -1 to 1. ___ The autocorrelation function measures the linear dependence between observations in a time series at different time lags. It quantifies how well the series correlates with itself at different time intervals, which is useful for identifying patterns, seasonality, and the appropriate lag structure for time series models. ACF values close to 1 indicate strong positive correlation, values close to -1 indicate strong negative correlation, and values near 0 indicate no linear correlation. ___ Reference: - statisticsbyjim.com acf_multiple(data, k)   Autocorrelation function (ACF) for a time series at a set of specified lags.   Parameters:      data (array) : Sample data of the observations.      k (array) : List of lag periods for which to calculate the autocorrelation. Must be a non-negative integer.   Returns: - List of ACF values for provided lags. ___ The autocorrelation function measures the linear dependence between observations in a time series at different time lags. It quantifies how well the series correlates with itself at different time intervals, which is useful for identifying patterns, seasonality, and the appropriate lag structure for time series models. ACF values close to 1 indicate strong positive correlation, values close to -1 indicate strong negative correlation, and values near 0 indicate no linear correlation. ___ Reference: - statisticsbyjim.com adfuller(data, n_lag, conf)   : Augmented Dickey-Fuller test for stationarity.   Parameters:      data (array) : Data series.      n_lag (int) : Maximum lag.      conf (string) : Confidence Probability level used to test for critical value, (`90%`, `95%`, `99%`).   Returns: - `adf` The test statistic. - `crit` Critical value for the test statistic at the 10 % levels. - `nobs` Number of observations used for the ADF regression and calculation of the critical values. ___ The Augmented Dickey-Fuller test is used to determine whether a time series is stationary or contains a unit root (non-stationary). The null hypothesis is that the series has a unit root (is non-stationary), while the alternative hypothesis is that the series is stationary. A stationary time series has statistical properties that do not change over time, making it suitable for many time series forecasting models. If the test statistic is less than the critical value, we reject the null hypothesis and conclude the series is stationary. ___ Reference: - www.jstor.org - en.wikipedia.org theils_inequality(targets, forecasts)   Calculates Theil's Inequality Coefficient, a measure of forecast accuracy that quantifies the relative difference between actual and predicted values.   Parameters:      targets (array) : List of target observations.      forecasts (array) : Matrix with list of forecasts, ordered column wise.   Returns: - Theil's Inequality Coefficient value, value closer to 0 is better. ___ Theil's Inequality Coefficient is calculated as: `sqrt(Sum((y_i - f_i)^2)) / (sqrt(Sum(y_i^2)) + sqrt(Sum(f_i^2)))` where `y_i` represents actual values and `f_i` represents forecast values. This metric ranges from 0 to infinity, with 0 indicating perfect forecast accuracy. ___ Reference: - en.wikipedia.org sharpness(forecasts)   The average width of the forecast intervals across all observations, representing the sharpness or precision of the predictive intervals.   Parameters:      forecasts (matrix) : The forecasted values in matrix format with at least 2 columns (min, max).   Returns: - Sharpness The sharpness level, which is the average width of all prediction intervals across the forecast horizon. ___ Sharpness is an important metric for evaluating forecast quality. It measures how narrow or wide the prediction intervals are. Higher sharpness (narrower intervals) indicates greater precision in the forecast intervals, while lower sharpness (wider intervals) suggests less precision. The sharpness metric is calculated as the mean of the interval widths across all observations, where each interval width is the difference between the upper and lower bounds of the prediction interval. Note: This function assumes that the forecasts matrix has at least 2 columns, with the first column representing the lower bounds and the second column representing the upper bounds of prediction intervals. ___ Reference: - Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts. otexts.com resolution(forecasts)   Calculates the resolution of forecast intervals, measuring the average absolute difference between individual forecast interval widths and the overall sharpness measure.   Parameters:      forecasts (matrix) : The forecasted values in matrix format with at least 2 columns (min, max).   Returns: - The average absolute difference between individual forecast interval widths and the overall sharpness measure, representing the resolution of the forecasts. ___ Resolution is a key metric for evaluating forecast quality that measures the consistency of prediction interval widths. It quantifies how much the individual forecast intervals vary from the average interval width (sharpness). High resolution indicates that the forecast intervals are relatively consistent across observations, while low resolution suggests significant variation in interval widths. The resolution is calculated as the mean absolute deviation of individual interval widths from the overall sharpness value. This provides insight into the uniformity of the forecast uncertainty estimates across the forecast horizon. Note: This function requires the forecasts matrix to have at least 2 columns (min, max) representing the lower and upper bounds of prediction intervals. ___ Reference: - (sites.stat.washington.edu) - (www.jstor.org) coverage(targets, forecasts)   Calculates the coverage probability, which is the percentage of target values that fall within the corresponding forecasted prediction intervals.   Parameters:      targets (array) : List of target values.      forecasts (matrix) : The forecasted values in matrix format with at least 2 columns (min, max).   Returns: - Percent of target values that fall within their corresponding forecast intervals, expressed as a decimal value between 0 and 1 (or 0% and 100%). ___ Coverage probability is a crucial metric for evaluating the reliability of prediction intervals. It measures how well the forecast intervals capture the actual observed values. An ideal forecast should have a coverage probability close to the nominal confidence level (e.g., 90%, 95%, or 99%). For example, if a 95% prediction interval is used, we expect approximately 95% of the actual target values to fall within those intervals. If the coverage is significantly lower than the nominal level, the intervals may be too narrow; if it's significantly higher, the intervals may be too wide. Note: This function requires the targets array and forecasts matrix to have the same number of observations, and the forecasts matrix must have at least 2 columns (min, max) representing the lower and upper bounds of prediction intervals. ___ Reference: - (www.jstor.org) pinball(tau, target, forecast)   Pinball loss function, measures the asymmetric loss for quantile forecasts.   Parameters:      tau (float) : The quantile level (between 0 and 1), where 0.5 represents the median.      target (float) : The actual observed value to compare against.      forecast (float) : The forecasted value.   Returns: - The Pinball loss value, which quantifies the distance between the forecast and target relative to the specified quantile level. ___ The Pinball loss function is specifically designed for evaluating quantile forecasts. It is asymmetric, meaning it penalizes underestimates and overestimates differently depending on the quantile level being evaluated. For a given quantile τ, the loss function is defined as: - If target >= forecast: (target - forecast) * τ - If target < forecast: (forecast - target) * (1 - τ) This loss function is commonly used in quantile regression and probabilistic forecasting to evaluate how well forecasts capture specific quantiles of the target distribution. ___ Reference: - (www.otexts.com) pinball_mean(tau, targets, forecasts)   Calculates the mean pinball loss for quantile regression.   Parameters:      tau (float) : The quantile level (between 0 and 1), where 0.5 represents the median.      targets (array) : The actual observed values to compare against.      forecasts (matrix) : The forecasted values in matrix format with at least 2 columns (min, max).   Returns: - The mean pinball loss value across all observations. ___ The pinball_mean() function computes the average Pinball loss across multiple observations, making it suitable for evaluating overall forecast performance in quantile regression tasks. This function leverages the asymmetric Pinball loss function to evaluate how well forecasts capture specific quantiles of the target distribution. The choice of which column from the forecasts matrix to use depends on the quantile level: - For τ ≤ 0.5: Uses the first column (min) of forecasts - For τ > 0.5: Uses the second column (max) of forecasts This loss function is commonly used in quantile regression and probabilistic forecasting to evaluate how well forecasts capture specific quantiles of the target distribution. ___ Reference: - (www.otexts.com)
Pine Script® library
by RicardoSantos
4
Correlation HeatMap Matrix Data [TradingFinder]🔵 Introduction Correlation is a statistical measure that shows the degree and direction of a linear relationship between two assets. Its value ranges from -1 to +1 : +1 means perfect positive correlation, 0 means no linear relationship, and -1 means perfect negative correlation. In financial markets, correlation is used for portfolio diversification, risk management, pairs trading, intermarket analysis, and identifying divergences. Correlation HeatMap Matrix Data TradingFinder is a Pine Script v6 library that calculates and returns raw correlation matrix data between up to 20 symbols. It only provides the data – it does not draw or render the heatmap – making it ideal for use in other scripts that handle visualization or further analysis. The library uses ta.correlation for fast and accurate calculations. It also includes two helper functions for visual styling : CorrelationColor(corr) : takes the correlation value as input and generates a smooth gradient color, ranging from strong negative to strong positive correlation. CorrelationTextColor(corr) : takes the correlation value as input and returns a text color that ensures optimal contrast over the background color. Library "Correlation_HeatMap_Matrix_Data_TradingFinder" CorrelationColor(corr)   Parameters:      corr (float) CorrelationTextColor(corr)   Parameters:      corr (float) Data_Matrix(Corr_Period, Sym_1, Sym_2, Sym_3, Sym_4, Sym_5, Sym_6, Sym_7, Sym_8, Sym_9, Sym_10, Sym_11, Sym_12, Sym_13, Sym_14, Sym_15, Sym_16, Sym_17, Sym_18, Sym_19, Sym_20)   Parameters:      Corr_Period (int)      Sym_1 (string)      Sym_2 (string)      Sym_3 (string)      Sym_4 (string)      Sym_5 (string)      Sym_6 (string)      Sym_7 (string)      Sym_8 (string)      Sym_9 (string)      Sym_10 (string)      Sym_11 (string)      Sym_12 (string)      Sym_13 (string)      Sym_14 (string)      Sym_15 (string)      Sym_16 (string)      Sym_17 (string)      Sym_18 (string)      Sym_19 (string)      Sym_20 (string) 🔵 How to use Import the library into your Pine Script using the import keyword and its full namespace. Decide how many symbols you want to include in your correlation matrix (up to 20). Each symbol must be provided as a string, for example FX:EURUSD . Choose the correlation period (Corr\_Period) in bars. This is the lookback window used for the calculation, such as 20, 50, or 100 bars. Call Data_Matrix(Corr_Period, Sym_1, ..., Sym_20) with your selected parameters. The function will return an array containing the correlation values for every symbol pair (upper triangle of the matrix plus diagonal). For example : var string Sym_1 = '' , var string Sym_2 = '' , var string Sym_3 = '' , var string Sym_4 = '' , var string Sym_5 = '' , var string Sym_6 = '' , var string Sym_7 = '' , var string Sym_8 = '' , var string Sym_9 = '' , var string Sym_10 = '' var string Sym_11 = '', var string Sym_12 = '', var string Sym_13 = '', var string Sym_14 = '', var string Sym_15 = '', var string Sym_16 = '', var string Sym_17 = '', var string Sym_18 = '', var string Sym_19 = '', var string Sym_20 = '' switch Market 'Forex' => Sym_1 := 'EURUSD' , Sym_2 := 'GBPUSD' , Sym_3 := 'USDJPY' , Sym_4 := 'USDCHF' , Sym_5 := 'USDCAD' , Sym_6 := 'AUDUSD' , Sym_7 := 'NZDUSD' , Sym_8 := 'EURJPY' , Sym_9 := 'EURGBP' , Sym_10 := 'GBPJPY' ,Sym_11 := 'AUDJPY', Sym_12 := 'EURCHF', Sym_13 := 'EURCAD', Sym_14 := 'GBPCAD', Sym_15 := 'CADJPY', Sym_16 := 'CHFJPY', Sym_17 := 'NZDJPY', Sym_18 := 'AUDNZD', Sym_19 := 'USDSEK' , Sym_20 := 'USDNOK' 'Stock' => Sym_1 := 'NVDA' , Sym_2 := 'AAPL' , Sym_3 := 'GOOGL' , Sym_4 := 'GOOG' , Sym_5 := 'META' , Sym_6 := 'MSFT' , Sym_7 := 'AMZN' , Sym_8 := 'AVGO' , Sym_9 := 'TSLA' , Sym_10 := 'BRK.B' ,Sym_11 := 'UNH' , Sym_12 := 'V' , Sym_13 := 'JPM' , Sym_14 := 'WMT' , Sym_15 := 'LLY' , Sym_16 := 'ORCL', Sym_17 := 'HD' , Sym_18 := 'JNJ' , Sym_19 := 'MA' , Sym_20 := 'COST' 'Crypto' => Sym_1 := 'BTCUSD' , Sym_2 := 'ETHUSD' , Sym_3 := 'BNBUSD' , Sym_4 := 'XRPUSD' , Sym_5 := 'SOLUSD' , Sym_6 := 'ADAUSD' , Sym_7 := 'DOGEUSD' , Sym_8 := 'AVAXUSD' , Sym_9 := 'DOTUSD' , Sym_10 := 'TRXUSD' ,Sym_11 := 'LTCUSD' , Sym_12 := 'LINKUSD', Sym_13 := 'UNIUSD', Sym_14 := 'ATOMUSD', Sym_15 := 'ICPUSD', Sym_16 := 'ARBUSD', Sym_17 := 'APTUSD', Sym_18 := 'FILUSD', Sym_19 := 'OPUSD' , Sym_20 := 'USDT.D' 'Custom' => Sym_1 := Sym_1_C , Sym_2 := Sym_2_C , Sym_3 := Sym_3_C , Sym_4 := Sym_4_C , Sym_5 := Sym_5_C , Sym_6 := Sym_6_C , Sym_7 := Sym_7_C , Sym_8 := Sym_8_C , Sym_9 := Sym_9_C , Sym_10 := Sym_10_C ,Sym_11 := Sym_11_C, Sym_12 := Sym_12_C, Sym_13 := Sym_13_C, Sym_14 := Sym_14_C, Sym_15 := Sym_15_C, Sym_16 := Sym_16_C, Sym_17 := Sym_17_C, Sym_18 := Sym_18_C, Sym_19 := Sym_19_C , Sym_20 := Sym_20_C = Corr.Data_Matrix(Corr_period, Sym_1 ,Sym_2 ,Sym_3 ,Sym_4 ,Sym_5 ,Sym_6 ,Sym_7 ,Sym_8 ,Sym_9 ,Sym_10,Sym_11,Sym_12,Sym_13,Sym_14,Sym_15,Sym_16,Sym_17,Sym_18,Sym_19,Sym_20) Loop through or index into this array to retrieve each correlation value for your custom layout or logic. Pass each correlation value to CorrelationColor() to get the corresponding gradient background color, which reflects the correlation’s strength and direction (negative to positive). For example : Corr.CorrelationColor(SYM_3_10) Pass the same correlation value to CorrelationTextColor() to get the correct text color for readability against that background. For example : Corr.CorrelationTextColor(SYM_1_1) Use these colors in a table or label to render your own heatmap or any other visualization you need.
Pine Script® library
by TFlab
Primes_4These libraries (Primes_1 -> Primes_4) contain arrays of reduced Prime Numbers to minimize the amount of tokens, allowing more information to be exported. Values, for example: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 are reduced to: 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 With the restoreValues() function found in this library, the reduced values can be restored back to its original state. 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 is restored back to: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 The libraries contain all Prime Numbers from 2 to 1.340.011 ------------------------------------------------------------ Library "Primes_4" Prime Numbers 1.096.031 - 1.340.011 primes_a()   Prime numbers 1.096.031 - 1.205.999 primes_b()   Prime numbers 1.206.013 - 1.317.989 primes_c()   Prime numbers 1.318.003 - 1.340.011 method restoreValues(iArray, iShow, iFrom, iTo)   restoreValues : Restores reduced prime number values in an array to their original state, for example `7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21` is restored to `7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021`   Namespace types: array   Parameters:      iArray (array)      iShow (bool)      iFrom (int)      iTo (int)   Returns: Initial array with restored prime number values
Pine Script® library
by fikira
Primes_3These libraries (Primes_1 -> Primes_4) contain arrays of reduced Prime Numbers to minimize the amount of tokens, allowing more information to be exported. Values, for example: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 are reduced to: 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 With the restoreValues() function found in the Primes_4 library, the reduced values can be restored back to its original state. 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 is restored back to: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 The libraries contain all Prime Numbers from 2 to 1.340.011 ------------------------------------------------------------ Library "Primes_3" Prime Numbers 713.021 - 1.095.989 primes_a()   Prime numbers 713.021 - 820.997 primes_b()   Prime numbers 821.003 - 928.979 primes_c()   Prime numbers 929.003 - 1.038.953 primes_d()   Prime numbers 1.039.001 - 1.095.989
Pine Script® library
by fikira
Primes_2These libraries (Primes_1 -> Primes_4) contain arrays of reduced Prime Numbers to minimize the amount of tokens, allowing more information to be exported. Values, for example: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 are reduced to: 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 With the restoreValues() function found in the Primes_4 library, the reduced values can be restored back to its original state. 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 is restored back to: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 The libraries contain all Prime Numbers from 2 to 1.340.011 ------------------------------------------------------------ Library "Primes_2" Prime Numbers 340.007 - 712.981 primes_a()   Prime numbers 340.007 - 441.971 primes_b()   Prime numbers 442.003 - 545.959 primes_c()   Prime numbers 546.001 - 650.987 primes_d()   Prime numbers 651.017 - 712.981
Pine Script® library
by fikira
Primes_1These libraries (Primes_1 -> Primes_4) contain arrays of reduced Prime Numbers to minimize the amount of tokens, allowing more information to be exported. Values, for example: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 are reduced to: 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 With the restoreValues() function found in the Primes_4 library, the reduced values can be restored back to its original state. 7001, 13, 19, 27, 39, 43, 57, 69, 79, 7103, 9, 21 is restored back to: 7001, 7013, 7019, 7027, 7039, 7043, 7057, 7069, 7079, 7103, 7109, 7021 The libraries contain all Prime Numbers from 2 to 1.340.011 ------------------------------------------------------------ Library "Primes_1" Prime Numbers 2 - 339.991 primes_a()   Prime numbers 2 - 81.689 primes_b()   Prime numbers 81.701 - 175.897 primes_c()   Prime numbers 175.909 - 273.997 primes_d()   Prime numbers 274.007 - 339.991
Pine Script® library
by fikira
thors_forex_factory_decodingLibrary "forex_factory_decoding" Supporting Utility Library for the Live Economic Calendar by toodegrees Indicator; responsible for formatting and saving Forex Factory News events. isLeapYear()   Finds if it's currently a leap year or not.   Returns: Returns True if the current year is a leap year. daysMonth(M)   Provides the days in a given month of the year, adjusted during leap years.   Parameters:      M (int) : Month in numerical integer format (i.e. Jan=1).   Returns: Days in the provided month. MMM(M)   Converts a month from a numerical integer format to a MMM format (i.e. 'Jan').   Parameters:      M (int) : Month in numerical integer format (i.e. Jan=1).   Returns: Month in MMM format (i.e. 'Jan'). array2string(S, FWD)   Converts a string array to a simple string, concatenating its elements.   Parameters:      S (array) : String array, or string array slice, to turn into a simple string.      FWD (bool) : Boolean defaulted to True. If True the array will be concatenated from head to tail, reversed order if False.   Returns: Returns the simple string equivalent of the provided string array. month2number(M)   Converts a month string in 'MMM' format to its integer equivalent.   Parameters:      M (string) : Month string, in 'MMM' format.   Returns: Returns the integer equivalent of the provided Month string in 'MMM' format. shiftFWD_Days(D)   Shifts forward the current Date by N days.   Parameters:      D (int) : Number of days to forward-shift, default is 7.   Returns: Returns the forward-shifted date in 'MMM %D' format (i.e. Jan 8, Sep 12). ff_dow(D)   Converts a numbered day of the week string in format to 'DDD' format (i.e. "1" = Sun).   Parameters:      D (string) : Numbered day of the week from 1 to 7, starting on Sunday.   Returns: Returns the day of the week in 'DDD' format (i.e. "Fri"). ff_currency(C)   Converts a numbered currency string in format to 'CCC' format (i.e. "1" = AUD).   Parameters:      C (string) : Numbered currency, where "1" = "AUD", "2" = "CAD", "3" = "CHF", "4" = "CNY", "5" = "EUR", "6" = "GBP", "7" = "JPY", "8" = "NZD", "9" = "USD".   Returns: Returns the currency in 'CCC' format (i.e. "USD"). ff_t(T)   Converts a time of the day in 'hhmm' format into an intger.   Parameters:      T (string) : Time of the day string in 'hhmm' format.   Returns: Returns the time of the day integer in 'hhmm' format, or -1 if all day. ff_tod(T)   Converts a time of the day from an integer 'hhmm' format into 'hh:mm' format.   Parameters:      T (int)   Returns: Returns the N Forex Factory News array with time of the day string in 'hh:mm' format, or 'All Day'. ff_impact(I)   Converts a number from 1 to 4 to a relative color based on Forex Factory Impact types.   Parameters:      I (string) : Impact number string from 1 to 4, where "1" = Holiday, "2" = Low Impact, "3" = Medium Impact, "4" = High Impact.   Returns: Returns the color associated to the impact number based on Forex Factory Impact types. ff_tmst(D, T)   Parameters:      D (string)      T (string) decode(ID)   Decodes TOODEGREES_FOREX_FACTORY_SLOT_n Symbols' Pine Seeds data into Forex Factory News Events.   Parameters:      ID (int) : Identifier of the Forex Factory News Event, in "DCHHMMI%T" format (D = day of the week from 1 to 7, C = currency from 1 to 9, HHMM = hour:minute in 24h, I = impact from 1 to 4, %T = event title ID) .   Returns: Returns the Forex Factory News Event. method pullNews(N, n)   Decodes the Forex Factory News Event and adds it to the Forex Factory News array.   Namespace types: array   Parameters:      N (array type from cegb001/forex_factory_utility/1) : Forex Factory News array.      n (float) : imported data from custom feed.   Returns: void method readNews(N, S)   Pulls the individual Forex Factory News Event from the custom data feed format (joint News string), decodes them and adds them to the Forex Factory News array.   Namespace types: array   Parameters:      N (array type from cegb001/forex_factory_utility/1) : Forex Factory News array.      S (string) : joint string of the imported data from custom feed.   Returns: void
Pine Script® library
by cegb001
MSFA_LibraryLibrary "MSFA_library" TODO: add library description here getDecimals()   Calculates how many decimals are on the quote price of the current market   Returns: The current decimal places on the market quote price getPipSize(multiplier)   Calculates the pip size of the current market   Parameters:      multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)   Returns: The pip size for the current market truncate(number, decimalPlaces)   Truncates (cuts) excess decimal places   Parameters:      number (float) : The number to truncate      decimalPlaces (simple float) : (default=2) The number of decimal places to truncate to   Returns: The given number truncated to the given decimalPlaces toWhole(number)   Converts pips into whole numbers   Parameters:      number (float) : The pip number to convert into a whole number   Returns: The converted number toPips(number)   Converts whole numbers back into pips   Parameters:      number (float) : The whole number to convert into pips   Returns: The converted number getPctChange(value1, value2, lookback)   Gets the percentage change between 2 float values over a given lookback period   Parameters:      value1 (float) : The first value to reference      value2 (float) : The second value to reference      lookback (int) : The lookback period to analyze   Returns: The percent change over the two values and lookback period random(minRange, maxRange)   Wichmann–Hill Pseudo-Random Number Generator   Parameters:      minRange (float) : The smallest possible number (default: 0)      maxRange (float) : The largest possible number (default: 1)   Returns: A random number between minRange and maxRange bullFib(priceLow, priceHigh, fibRatio)   Calculates a bullish fibonacci value   Parameters:      priceLow (float) : The lowest price point      priceHigh (float) : The highest price point      fibRatio (float) : The fibonacci % ratio to calculate   Returns: The fibonacci value of the given ratio between the two price points bearFib(priceLow, priceHigh, fibRatio)   Calculates a bearish fibonacci value   Parameters:      priceLow (float) : The lowest price point      priceHigh (float) : The highest price point      fibRatio (float) : The fibonacci % ratio to calculate   Returns: The fibonacci value of the given ratio between the two price points getMA(length, maType)   Gets a Moving Average based on type (! MUST BE CALLED ON EVERY TICK TO BE ACCURATE, don't place in scopes)   Parameters:      length (simple int) : The MA period      maType (string) : The type of MA   Returns: A moving average with the given parameters barsAboveMA(lookback, ma)   Counts how many candles are above the MA   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to check   Returns: The bar count of how many recent bars are above the MA barsBelowMA(lookback, ma)   Counts how many candles are below the MA   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to reference   Returns: The bar count of how many recent bars are below the EMA barsCrossedMA(lookback, ma)   Counts how many times the EMA was crossed recently (based on closing prices)   Parameters:      lookback (int) : The lookback period to look back over      ma (float) : The moving average to reference   Returns: The bar count of how many times price recently crossed the EMA (based on closing prices) getPullbackBarCount(lookback, direction)   Counts how many green & red bars have printed recently (ie. pullback count)   Parameters:      lookback (int) : The lookback period to look back over      direction (int) : The color of the bar to count (1 = Green, -1 = Red)   Returns: The bar count of how many candles have retraced over the given lookback & direction getBodySize()   Gets the current candle's body size (in POINTS, divide by 10 to get pips)   Returns: The current candle's body size in POINTS getTopWickSize()   Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)   Returns: The current candle's top wick size in POINTS getBottomWickSize()   Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)   Returns: The current candle's bottom wick size in POINTS getBodyPercent()   Gets the current candle's body size as a percentage of its entire size including its wicks   Returns: The current candle's body size percentage isHammer(fib, colorMatch)   Checks if the current bar is a hammer candle based on the given parameters   Parameters:      fib (float) : (default=0.382) The fib to base candle body on      colorMatch (bool) : (default=false) Does the candle need to be green? (true/false)   Returns: A boolean - true if the current bar matches the requirements of a hammer candle isStar(fib, colorMatch)   Checks if the current bar is a shooting star candle based on the given parameters   Parameters:      fib (float) : (default=0.382) The fib to base candle body on      colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)   Returns: A boolean - true if the current bar matches the requirements of a shooting star candle isDoji(wickSize, bodySize)   Checks if the current bar is a doji candle based on the given parameters   Parameters:      wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)      bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size   Returns: A boolean - true if the current bar matches the requirements of a doji candle isBullishEC(allowance, rejectionWickSize, engulfWick)   Checks if the current bar is a bullish engulfing candle   Parameters:      allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage      engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?   Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle isBearishEC(allowance, rejectionWickSize, engulfWick)   Checks if the current bar is a bearish engulfing candle   Parameters:      allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage      engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?   Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle isInsideBar()   Detects inside bars   Returns: Returns true if the current bar is an inside bar isOutsideBar()   Detects outside bars   Returns: Returns true if the current bar is an outside bar barInSession(sess, useFilter)   Determines if the current price bar falls inside the specified session   Parameters:      sess (simple string) : The session to check      useFilter (bool) : (default=true) Whether or not to actually use this filter   Returns: A boolean - true if the current bar falls within the given time session barOutSession(sess, useFilter)   Determines if the current price bar falls outside the specified session   Parameters:      sess (simple string) : The session to check      useFilter (bool) : (default=true) Whether or not to actually use this filter   Returns: A boolean - true if the current bar falls outside the given time session dateFilter(startTime, endTime)   Determines if this bar's time falls within date filter range   Parameters:      startTime (int) : The UNIX date timestamp to begin searching from      endTime (int) : the UNIX date timestamp to stop searching from   Returns: A boolean - true if the current bar falls within the given dates dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)   Checks if the current bar's day is in the list of given days to analyze   Parameters:      monday (bool) : Should the script analyze this day? (true/false)      tuesday (bool) : Should the script analyze this day? (true/false)      wednesday (bool) : Should the script analyze this day? (true/false)      thursday (bool) : Should the script analyze this day? (true/false)      friday (bool) : Should the script analyze this day? (true/false)      saturday (bool) : Should the script analyze this day? (true/false)      sunday (bool) : Should the script analyze this day? (true/false)   Returns: A boolean - true if the current bar's day is one of the given days atrFilter(atrValue, maxSize)   Parameters:      atrValue (float)      maxSize (float) tradeCount()   Calculate total trade count   Returns: Total closed trade count isLong()   Check if we're currently in a long trade   Returns: True if our position size is positive isShort()   Check if we're currently in a short trade   Returns: True if our position size is negative isFlat()   Check if we're currentlyflat   Returns: True if our position size is zero wonTrade()   Check if this bar falls after a winning trade   Returns: True if we just won a trade lostTrade()   Check if this bar falls after a losing trade   Returns: True if we just lost a trade maxDrawdownRealized()   Gets the max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).   Returns: The max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized). totalPipReturn()   Gets the total amount of pips won/lost (as a whole number)   Returns: Total amount of pips won/lost (as a whole number) longWinCount()   Count how many winning long trades we've had   Returns: Long win count shortWinCount()   Count how many winning short trades we've had   Returns: Short win count longLossCount()   Count how many losing long trades we've had   Returns: Long loss count shortLossCount()   Count how many losing short trades we've had   Returns: Short loss count breakEvenCount(allowanceTicks)   Count how many break-even trades we've had   Parameters:      allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)   Returns: Break-even count longCount()   Count how many long trades we've taken   Returns: Long trade count shortCount()   Count how many short trades we've taken   Returns: Short trade count longWinPercent()   Calculate win rate of long trades   Returns: Long win rate (0-100) shortWinPercent()   Calculate win rate of short trades   Returns: Short win rate (0-100) breakEvenPercent(allowanceTicks)   Calculate break even rate of all trades   Parameters:      allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)   Returns: Break-even win rate (0-100) averageRR()   Calculate average risk:reward   Returns: Average winning trade divided by average losing trade unitsToLots(units)   (Forex) Convert the given unit count to lots (multiples of 100,000)   Parameters:      units (float) : The units to convert into lots   Returns: Units converted to nearest lot size (as float) skipTradeMonteCarlo(chance, debug)   Checks to see if trade should be skipped to emulate rudimentary Monte Carlo simulation   Parameters:      chance (float) : The chance to skip a trade (0-1 or 0-100, function will normalize to 0-1)      debug (bool) : Whether or not to display a label informing of the trade skip   Returns: True if the trade is skipped, false if it's not skipped (idea being to include this function in entry condition validation checks) fillCell(tableID, column, row, title, value, bgcolor, txtcolor, tooltip)   This updates the given table's cell with the given values   Parameters:      tableID (table) : The table ID to update      column (int) : The column to update      row (int) : The row to update      title (string) : The title of this cell      value (string) : The value of this cell      bgcolor (color) : The background color of this cell      txtcolor (color) : The text color of this cell      tooltip (string)   Returns: Nothing.
Pine Script® library
by hphuc0212
thors_forex_factory_utilityLibrary "forex_factory_utility" Supporting Utility Library for the Live Economic Calendar by toodegrees Indicator; responsible for data handling, and plotting news event data. isLeapYear()   Finds if it's currently a leap year or not.   Returns: Returns True if the current year is a leap year. daysMonth(M)   Provides the days in a given month of the year, adjusted during leap years.   Parameters:      M (int) : Month in numerical integer format (i.e. Jan=1).   Returns: Days in the provided month. MMM(M)   Converts a month from a numerical integer format to a MMM format (i.e. 'Jan').   Parameters:      M (int) : Month in numerical integer format (i.e. Jan=1).   Returns: Month in MMM format (i.e. 'Jan'). dow(D)   Converts a numbered day of the week string in format to 'DDD' format (i.e. "1" = Sun).   Parameters:      D (string) : Numbered day of the week from 1 to 7, starting on Sunday.   Returns: Returns the day of the week in 'DDD' format (i.e. "Fri"). size(S, N)   Converts a size string into the corresponding Pine Script v5 format, or N times smaller/bigger.   Parameters:      S (string) : Size string: "Tiny", "Small", "Normal", "Large", or "Huge".      N (int) : Size variation, can be positive (larger than S), or negative (smaller than S).   Returns: Size string in Pine Script v5 format. lineStyle(S)   Converts a line style string into the corresponding Pine Script v5 format.   Parameters:      S (string) : Line style string: "Dashed", "Dotted" or "Solid".   Returns: Line style string in Pine Script v5 format. lineTrnsp(S)   Converts a transparency style string into the corresponding integer value.   Parameters:      S (string) : Line style string: "Light", "Medium" or "Heavy".   Returns: Transparency integer. boxLoc(X, Y)   Converts position strings of X and Y into a table position in Pine Script v5 format.   Parameters:      X (string) : X-axis string: "Left", "Center", or "Right".      Y (string) : Y-axis string: "Top", "Middle", or "Bottom".   Returns: Table location string in Pine Script v5 format. method bubbleSort_NewsTOD(N)   Performs bubble sort on a Forex Factory News array of all news from the same date, ordering them in ascending order based on the time of the day.   Namespace types: array   Parameters:      N (array) : Forex Factory News array.   Returns: void bubbleSort_News(N)   Performs bubble sort on a Forex Factory News array, ordering them in ascending order based on the time of the day, and date.   Parameters:      N (array) : Forex Factory News array.   Returns: Sorted Forex Factory News array. weekNews(N, C, I)   Creates a Forex Factory News array containing the current week's Forex Factory News.   Parameters:      N (array) : Forex Factory News array containing this week's unfiltered Forex Factory News.      C (array) : Currency filter array (string array).      I (array) : Impact filter array (color array).   Returns: Forex Factory News array containing the current week's Forex Factory News. todayNews(W, D, M)   Creates a Forex Factory News array containing the current day's Forex Factory News.   Parameters:      W (array) : Forex Factory News array containing this week's Forex Factory News.      D (array) : Forex Factory News array for the current day's Forex Factory News.      M (bool) : Boolean that marks whether the current chart has a Day candle-switch at Midnight New York Time.   Returns: Forex Factory News array containing the current day's Forex Factory News. adjustTimezone(N, TZH, TZM)   Transposes the Time of the Day, and Date, in the Forex Factory News Table to a custom Timezone.   Parameters:      N (array) : Forex Factory News array.      TZH (int) : Custom Timezone hour.      TZM (int) : Custom Timezone minute.   Returns: Reformatted Forex Factory News array. NewsAMPM_TOD(N)   Reformats the Time of the Day in the Forex Factory News Table to AM/PM format.   Parameters:      N (array) : Forex Factory News array.   Returns: Reformatted Forex Factory News array. impFilter(X, L, M, H)   Creates a filter array from the User's desired Forex Facory News to be shown based on Impact.   Parameters:      X (bool) : Boolean - if True Holidays listed on Forex Factory will be shown.      L (bool) : Boolean - if True Low Impact listed on Forex Factory News will be shown.      M (bool) : Boolean - if True Medium Impact listed on Forex Factory News will be shown.      H (bool) : Boolean - if True High Impact listed on Forex Factory News will be shown.   Returns: Color array with the colors corresponding to the Forex Factory News to be shown. curFilter(A, C1, C2, C3, C4, C5, C6, C7, C8, C9)   Creates a filter array from the User's desired Forex Facory News to be shown based on Currency.   Parameters:      A (bool) : Boolean - if True News related to the current Chart's symbol listed on Forex Factory will be shown.      C1 (bool) : Boolean - if True News related to the Australian Dollar listed on Forex Factory will be shown.      C2 (bool) : Boolean - if True News related to the Canadian Dollar listed on Forex Factory will be shown.      C3 (bool) : Boolean - if True News related to the Swiss Franc listed on Forex Factory will be shown.      C4 (bool) : Boolean - if True News related to the Chinese Yuan listed on Forex Factory will be shown.      C5 (bool) : Boolean - if True News related to the Euro listed on Forex Factory will be shown.      C6 (bool) : Boolean - if True News related to the British Pound listed on Forex Factory will be shown.      C7 (bool) : Boolean - if True News related to the Japanese Yen listed on Forex Factory will be shown.      C8 (bool) : Boolean - if True News related to the New Zealand Dollar listed on Forex Factory will be shown.      C9 (bool) : Boolean - if True News related to the US Dollar listed on Forex Factory will be shown.   Returns: String array with the currencies corresponding to the Forex Factory News to be shown. FF_OnChartLine(N, T, S)   Plots vertical lines where a Forex Factory News event will occur, or has already occurred.   Parameters:      N (array) : News-type array containing all the Forex Factory News.      T (int) : Transparency integer value (0-100) for the lines.      S (string) : Line style in Pine Script v5 format.   Returns: void method updateStringMatrix(M, P, V)   Updates a string Matrix containing the tooltips for Forex Factory News Event information for a given candle.   Namespace types: matrix   Parameters:      M (matrix) : String matrix.      P (int) : Position (row) of the Matrix to update based on the impact.      V (string) : information to push to the Matrix.   Returns: void FF_OnChartLabel(N, Y, S, O)   Plots labels where a Forex Factory News has already occurred based on its/their impact.   Parameters:      N (array) : News-type array containing all the Forex Factory News.      Y (string) : String that gives direction on where to plot the label (options= "Above", "Below", "Auto").      S (string) : Label size in Pine Script v5 format.      O (bool) : Show outline of labels?   Returns: void historical(T, D, W, X)   Deletes Forex Factory News drawings which are ourside a specific Time window.   Parameters:      T (int) : Number of days input used for Forex Factory News drawings' history.      D (bool) : Boolean that when true will only display Forex Factory News drawings of the current day.      W (bool) : Boolean that when true will only display Forex Factory News drawings of the current week.      X (string) : String that gives direction on what lines to plot based on Time (options= "Future", "Both").   Returns: void newTable(P, B)   Creates a new Table object with parameters tailored to the Forex Factory News Table.   Parameters:      P (string) : Position string for the Table, in Pine Script v5 format.      B (color) : Border and frame color for the News Table.   Returns: Empty Forex Factory News Table. resetTable(P, S, headTextC, headBgC, B)   Resets a Table object with parameters and headers tailored to the Forex Factory News Table.   Parameters:      P (string) : Position string for the Table, in Pine Script v5 format.      S (string) : Size string for the Table's text, in Pine Script v5 format.      headTextC (color)      headBgC (color)      B (color) : Border and frame color for the News Table.   Returns: Empty Forex Factory News Table. logNews(N, TBL, R, S, rowTextC, rowBgC)   Adds an event to the Forex Factory News Table.   Parameters:      N (News) : News-type object.      TBL (table) : Forex Factory News Table object to add the News to.      R (int) : Row to add the event to in the Forex Factory News Table.      S (string) : Size string for the event's text, in Pine Script v5 format.      rowTextC (color)      rowBgC (color)   Returns: void FF_Table(N, P, S, headTextC, headBgC, rowTextC, rowBgC, B)   Creates the Forex Factory News Table.   Parameters:      N (array) : News-type array containing all the Forex Factory News.      P (string) : Position string for the Table, in Pine Script v5 format.      S (string) : Size string for the Table's text, in Pine Script v5 format.      headTextC (color)      headBgC (color)      rowTextC (color)      rowBgC (color)      B (color) : Border and frame color for the News Table.   Returns: Forex Factory News Table. timeline(N, T, F, TZH, TZM, D)   Shades Forex Factory News events in the Forex Factory News Table after they occur.   Parameters:      N (array) : News-type array containing all the Forex Factory News.      T (table) : Forex Facory News table object.      F (color) : Color used as shading once the Forex Factory News has occurred.      TZH (int) : Custom Timezone hour, if any.      TZM (int) : Custom Timezone minute, if any.      D (bool) : Daily Forex Factory News flag.   Returns: Forex Factory News Table. News   Custom News type which contains informatino about a Forex Factory News Event.   Fields:      dow (series string) : Day of the week, in DDD format (i.e. 'Mon').      dat (series string) : Date, in MMM D format (i.e. 'Jan 1').      _t (series int)      tod (series string) : Time of the day, in hh:mm 24-Hour format (i.e 17:10).      cur (series string) : Currency, in CCC format (i.e. "USD").      imp (series color) : Impact, the respective impact color for Forex Factory News Events.      ttl (series string) : Title, encoded in a custom number mapping (see the toodegrees/toodegrees_forex_factory library to learn more).      tmst (series int)      ln (series line)
Pine Script® library
by cegb001
CoreJuice001Library "CoreJuice001" DrawingData   Fields:      kzone1Boxes (array)      kzone2Boxes (array)      kzone3Boxes (array)      kzone4Boxes (array)      kzone5Boxes (array)      kzone6Boxes (array)      kzone1Labels (array)      kzone2Labels (array)      kzone3Labels (array)      kzone4Labels (array)      kzone5Labels (array)      kzone6Labels (array)      kzone1TrendLines (array)      kzone2TrendLines (array)      kzone3TrendLines (array)      kzone4TrendLines (array)      kzone5TrendLines (array)      kzone6TrendLines (array)      kzone1PriceLabels (array)      kzone2PriceLabels (array)      kzone3PriceLabels (array)      kzone4PriceLabels (array)      kzone5PriceLabels (array)      kzone6PriceLabels (array)
Pine Script® library
by nuburo
AuthLibLibrary "AuthLib" DrawingData   Fields:      kzone1Boxes (array)      kzone2Boxes (array)      kzone3Boxes (array)      kzone4Boxes (array)      kzone5Boxes (array)      kzone6Boxes (array)      kzone1Labels (array)      kzone2Labels (array)      kzone3Labels (array)      kzone4Labels (array)      kzone5Labels (array)      kzone6Labels (array)      kzone1TrendLines (array)      kzone2TrendLines (array)      kzone3TrendLines (array)      kzone4TrendLines (array)      kzone5TrendLines (array)      kzone6TrendLines (array)      kzone1PriceLabels (array)      kzone2PriceLabels (array)      kzone3PriceLabels (array)      kzone4PriceLabels (array)      kzone5PriceLabels (array)      kzone6PriceLabels (array)
Pine Script® library
by nuburo
Helper Lib by tristanlee85Library "helpers" This library offers various functions and types based on the algorithmic concepts as authored by ICT. kv(key, value)   Returns a string of the key/value set, suitable for debug logging   Parameters:      key (string)      value (string)   Returns: A string formatted as "{key}: {value}" kv(key, value)   Parameters:      key (string)      value (int) kv(key, value)   Parameters:      key (string)      value (float) kv(key, value)   Parameters:      key (string)      value (bool) method enable(this, enable)   Enable/Disable debug logging   Namespace types: Debugger   Parameters:      this (Debugger)      enable (bool) : Set to `true` by default. method group(this, label)   Creates a group label for nested debug() invocations   Namespace types: Debugger   Parameters:      this (Debugger)      label (string) method groupEnd(this, label)   Ends the specified debug group   Namespace types: Debugger   Parameters:      this (Debugger)      label (string) method log(this, s, arg1, arg2, arg3, arg4, arg5)   Logs the param values if debug mode is enabled   Namespace types: Debugger   Parameters:      this (Debugger)      s (string) : Title of the log message      arg1 (string)      arg2 (string)      arg3 (string)      arg4 (string)      arg5 (string) method logIf(this, expr, s, arg1, arg2, arg3, arg4, arg5)   Same behavior as debug() except will only log if the passed expression is true   Namespace types: Debugger   Parameters:      this (Debugger)      expr (bool) : Boolean expression to determine if debug logs should be logged      s (string) : Title of the log message      arg1 (string)      arg2 (string)      arg3 (string)      arg4 (string)      arg5 (string) style_getLineStyleFromType(opt)   Returns the corresponding line style constant for the given LineStyleType   Parameters:      opt (series LineStyleType) : The selected line style type   Returns: The Pine Script line style constant style_getTextSizeFromType(opt)   Returns the corresponding text size constant for the given TextSizeType   Parameters:      opt (series TextSizeType) : The selected text size type   Returns: The Pine Script text size constant style_getTextHAlignFromType(t)   Returns the corresponding horizontal text align constant for the given HAlignType   Parameters:      t (series HAlignType) : The selected text align type   Returns: The Pine Script text align constant style_getTextVAlignFromType(t)   Returns the corresponding vertical text align constant for the given VAlignType   Parameters:      t (series VAlignType) : The selected text align type   Returns: The Pine Script text align constant format_sentimentType(sentiment, pd)   Used to produce a string with the sentiment and PD array type (e.g., "+FVG")   Parameters:      sentiment (series SentimentType) : The sentiment value (e.g., SentimentType.BULLISH)      pd (series PDArrayType) : The price data array (e.g., PDArrayType.FVG)   Returns: A formatted string with the sentiment and PD array (e.g., "+FVG") format_timeToString(timestamp)   Formats a UNIX timestamp into a date and time string based on predefined formats   Parameters:      timestamp (int) : The UNIX timestamp to format   Returns: A formatted string as "MM-dd (E) - HH:mm" method init(this)   Initializes the session and validates the configuration. This MUST be called immediately after creating a new instance.   Namespace types: Session   Parameters:      this (Session) : The Session object reference   Returns: The Session object (chainable) or throws a runtime error if invalid method isActive(this, _time)   Determines if the session is active based on the current bar time   Namespace types: Session   Parameters:      this (Session) : The Session object reference      _time (int)   Returns: `true` if the session is currently active; `false` otherwise method draw(this)   Draws the line and optional label   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference   Returns: The LineLabel object (chainable) method extend(this, x)   Extends the line and label right to the specified bar index   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference      x (int) : The bar index to extend to   Returns: The LineLabel object (chainable) method destroy(this)   Removes the line and label from the chart   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference isFVG(includeVI, barIdx)   Checks if the previous bars form a Fair Value Gap (FVG)   Parameters:      includeVI (bool) : If true, includes Volume Imbalance in the FVG calculation      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if a FVG is detected; otherwise, `na` isVolumeImbalance(barIdx)   Checks if the previous bars form a Volume Imbalance (VI)   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if a VI is detected; otherwise, `na` isLiquidityVoid(barIdx)   Checks if the previous bars form a Liquidity Void (LV)   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if an LV is detected; otherwise, `na` isSwingPoint(barIdx)   Checks if the previous bars form a swing point   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A SwingPoint object if a swing point is detected; otherwise, `na` Debugger   A debug logging utility with group support   Fields:      enabled (series bool)      _debugGroupStack (array) Session   Defines a trading session with a name and time range. When creating a new instance of this type, you MUST call init() immediately.   Fields:      name (series string) : A display-friendly name (e.g., "NY AM")      session (series string) : A string defining the session time range (e.g., "1300-1400")      enabled (series bool) : Optional flag for custom logic; defaults to false      start (series int) : UNIX time representing the session start (set via isActive())      end (series int) : UNIX time representing the session end (set via isActive())      _t (series int)      _start_HH (series float)      _start_mm (series float)      _end_HH (series float)      _end_mm (series float) Gap   Represents a price inefficiency (gap) with details on sentiment and price levels   Fields:      type (series SentimentType) : The sentiment of the gap (e.g., SentimentType.BULLISH)      name (series string) : A display-friendly name (e.g., "+FVG")      startTime (series int) : UNIX time value for the gap's start      endTime (series int) : UNIX time value for the gap's end      startIndex (series int) : Bar index where the gap starts      endIndex (series int) : Bar index where the gap ends      gapLow (series float) : The lowest price level of the gap      gapHigh (series float) : The highest price level of the gap      ce (series float) : The consequent encroachment level of the gap SwingPoint   Represents a swing point with details on type and price level   Fields:      type (series SwingPointType) : The type of swing point (e.g., SwingPointType.HIGH)      time (series int) : UNIX time value for the swing point      barIdx (series int) : Bar index where the swing point occurs      price (series float) : The price level of the swing point which is either the high or low of the middle bar LineLabel   Combines a line and box type to produce a line with a label that is properly aligned   Fields:      x (series int) : The X-axis starting point as a bar index      y (series float) : The Y-axis starting point as the price level      color (series color) : Both the line and text color      width (series int) : Thickness of the line      label (series string) : Text to display      showLabel (series bool) : Boolean to conditionally show/hide the label (default is false)      lineStyle (series LineStyleType) : The style of the line      textSize (series TextSizeType)      _b (series box)      _l (series line)
Pine Script® library
by tristanlee85
SMC_CommonLibrary "SMC_Common" Common types and utilities for Smart Money Concepts indicators get_future_time(bars_ahead)   Parameters:      bars_ahead (int) get_time_at_offset(offset)   Parameters:      offset (int) get_mid_time(time1, time2)   Parameters:      time1 (int)      time2 (int) timeframe_to_string(tf)   Parameters:      tf (string) is_psychological_level(price)   Parameters:      price (float) detect_swing_high(src_high, lookback)   Parameters:      src_high (float)      lookback (int) detect_swing_low(src_low, lookback)   Parameters:      src_low (float)      lookback (int) detect_fvg(h, l, min_size)   Parameters:      h (float)      l (float)      min_size (float) analyze_volume(vol, volume_ma)   Parameters:      vol (float)      volume_ma (float) create_label(x, y, label_text, bg_color, label_size, use_time)   Parameters:      x (int)      y (float)      label_text (string)      bg_color (color)      label_size (string)      use_time (bool) SwingPoint   Fields:      price (series float)      bar_index (series int)      bar_time (series int)      swing_type (series string)      strength (series int)      is_major (series bool)      timeframe (series string) LiquidityLevel   Fields:      price (series float)      bar_index (series int)      bar_time (series int)      liq_type (series string)      touch_count (series int)      is_swept (series bool)      quality_score (series float)      level_type (series string) OrderBlock   Fields:      start_bar (series int)      end_bar (series int)      start_time (series int)      end_time (series int)      top (series float)      bottom (series float)      ob_type (series string)      has_liquidity_sweep (series bool)      has_fvg (series bool)      is_mitigated (series bool)      is_breaker (series bool)      timeframe (series string)      mitigation_level (series float) StructureBreak   Fields:      level (series float)      break_bar (series int)      break_time (series int)      break_type (series string)      direction (series string)      is_confirmed (series bool)      source_swing_bar (series int)      source_time (series int) SignalData   Fields:      signal_type (series string)      entry_price (series float)      stop_loss (series float)      take_profit (series float)      risk_reward_ratio (series float)      confluence_count (series int)      confidence_score (series float)      strength (series string)
Pine Script® library
by M3ns4h
SITFX_FuturesSpec_v17SITFX_FuturesSpec_v17 – Universal Futures Contract Library Full-scale futures contract specification library for Pine Script v6. Covers CME, CBOT, NYMEX, COMEX, CFE, Eurex, ICE, and more – including minis, micros, metals, energies, FX, and bonds. Key Features: ✅ Instrument‑agnostic: ES/MES, NQ/MNQ, YM/MYM, RTY/M2K, metals, energies, FX, bonds ✅ Full contract data: Tick size, tick value, point value, margins ✅ Continuation‑safe: Single‑line logic, no arrays or continuation errors ✅ Foundation for SITFX tools: Gann, Fibs, structure, and risk modules Usage example: import SITFX_FuturesSpec_v17/1 as fs spec = fs.get(syminfo.root) label.new(bar_index, high, str.format("{0}: Tick={1}, Value=${2}", spec.name, spec.tickSize, spec.tickValue))
Pine Script® library
by Solvere
BestTimeFrameFinderLibrary "BestTimeFrameFinder" adx(len)   Parameters:      len (simple int) atrPercent(len)   Parameters:      len (simple int) scaleFromTf(tf, atrWeight)   Parameters:      tf (string)      atrWeight (simple float) scoreLocal(adxLen, atrLen, scale)   Parameters:      adxLen (simple int)      atrLen (simple int)      scale (simple float) maxInArray(arr)   Parameters:      arr (array)
Pine Script® library
by rahnlev
TFPS_EngineLibrary "TFPS_Engine" f_calculate_lead_lag(series1, series2, length, max_lag)   Parameters:      series1 (float)      series2 (float)      length (int)      max_lag (int) f_calculate_pressure_score(spx_ticker, vix_ticker, dxy_ticker, us10y_ticker, benchmark_source, trend_lookback, score_smoothing, use_dynamic_weights, corr_lookback, w_spx, w_vix, w_dxy, w_us10y, zscore_lookback, max_lag)   Parameters:      spx_ticker (string)      vix_ticker (string)      dxy_ticker (string)      us10y_ticker (string)      benchmark_source (float)      trend_lookback (int)      score_smoothing (simple int)      use_dynamic_weights (bool)      corr_lookback (int)      w_spx (float)      w_vix (float)      w_dxy (float)      w_us10y (float)      zscore_lookback (int)      max_lag (int) LeadLagOutput   Fields:      best_lag (series int)      max_corr (series float) TFPS_Output   Fields:      historical_score (series float)      smoothed_score (series float)      z_score (series float)      regime_signal (series int)      lead_lag_bars (series int)      lead_lag_corr (series float)      weight_spx (series float)      weight_vix (series float)      weight_dxy (series float)      weight_us10y (series float)
Pine Script® library
by ayana-ailab
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