Library "AutoFiboRetrace" TODO: add library description here fun(x) TODO: add function description here Parameters: x : TODO: add parameter x description here Returns: TODO: add what function returns
Library "MonthlyReturnsVsMarket" is a repackaging of the script here Credits to @QuantNomad for orginal script Now you can avoid to pollute your own strategy's code with the monthly returns table code and just import the library and call displayMonthlyPnL(int precision) function To be used in strategy scripts.
Library "Canvas" A library implementing a kind of "canvas" using a table where each pixel is represented by a table cell and the pixel color by the background color of each cell. To use the library, you need to create a color matrix (represented as an array) and a canvas table. The canvas table is the container of the canvas, and the color matrix determines...
Library "OrdinaryLeastSquares" One of the most common ways to estimate the coefficients for a linear regression is to use the Ordinary Least Squares (OLS) method. This library implements OLS in pine. This implementation can be used to fit a linear regression of multiple independent variables onto one dependent variable, as long as the assumptions behind OLS...
Library "FunctionPolynomialFit" Performs Polynomial Regression fit to data. In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modelled as an nth degree polynomial in x. reference: en.wikipedia.org www.bragitoff.com gauss_elimination(A, m, n) ...
Library "divergence" divergence: divergence algorithm with top and bottom kline tolerance regular_bull(series, series, simple, simple, simple, simple, simple) regular_bull: regular bull divergence, lower low src but higher low osc Parameters: series : float src: the source series series : float osc: the oscillator index simple : int lbL:...
Library "least_squares_regression" least_squares_regression: Least squares regression algorithm to find the optimal price interval for a given time period basic_lsr(series, series, series) basic_lsr: Basic least squares regression algorithm Parameters: series : int t: time scale value array corresponding to price series : float p: price scale...
Library "simple_squares_regression" simple_squares_regression: simple squares regression algorithm to find the optimal price interval for a given time period basic_ssr(series, series, series) basic_ssr: Basic simple squares regression algorithm Parameters: series : float src: the regression source such as close series : int region_forward: number...
Library "on_balance_volume" on_balance_volume: custom on balance volume obv_diff(string, simple) obv_diff: custom on balance volume diff version Parameters: string : type: the moving average type of on balance volume simple : int len: the moving average length of on balance volume Returns: obv_diff: custom on balance volume diff value ...
Library "moving_average" moving_average: moving average variants variant(string, series, simple) variant: moving average variants Parameters: string : type: type in series : float src: the source series of moving average simple : int len: the length of moving average Returns: float: the moving average variant value
Library "MathProbabilityDistribution" Probability Distribution Functions. name(idx) Indexed names helper function. Parameters: idx : int, position in the range (0, 6). Returns: string, distribution name. usage: .name(1) Notes: (0) => 'StdNormal' (1) => 'Normal' (2) => 'Skew Normal' (3) => 'Student T' (4) => 'Skew Student T' (5)...
Library "MovingAverages" Contains utilities for generating moving average values including getting a moving average by name and a function for generating a Volume-Adjusted WMA. sma(_D, _len) Simple Moving Avereage Parameters: _D : The series to measure from. _len : The number of bars to measure with. ema(_D, _len) Exponential Moving...
Library "eStrategy" Library contains methods which can help build custom strategy for continuous investment plans and also compare it with systematic buy and hold. sip(startYear, initialDeposit, depositFrequency, recurringDeposit, buyPrice) Depicts systematic buy and hold over period of time Parameters: startYear : Year on which SIP is started ...
Library "JohnEhlersFourierTransform" Fourier Transform for Traders By John Ehlers, slightly modified to allow to inspect other than the 8-50 frequency spectrum. reference: www.mesasoftware.com high_pass_filter(source) Detrended version of the data by High Pass Filtering with a 40 Period cutoff Parameters: source : float, data source. Returns:...
Library "FunctionCosineSimilarity" Cosine Similarity method. function(sample_a, sample_b) Measure the similarity of 2 vectors. Parameters: sample_a : float array, values. sample_b : float array, values. Returns: float. diss(cosim) Dissimilarity helper function. Parameters: cosim : float, cosine similarity value (0 > 1) Returns: float
Library "historicalrange" Library provices a method to calculate historical percentile range of series. hpercentrank(source) calculates historical percentrank of the source Parameters: source : Source for which historical percentrank needs to be calculated. Source should be ranging between 0-100. If using a source which can beyond 0-100, use short...
Library "WIPNNetwork" this is a work in progress (WIP) and prone to have some errors, so use at your own risk... let me know if you find any issues.. Method for a generalized Neural Network. network(x) Generalized Neural Network Method. Parameters: x : TODO: add parameter x description here Returns: TODO: add what function returns
Library "FunctionPatternDecomposition" Methods for decomposing price into common grid/matrix patterns. series_to_array(source, length) Helper for converting series to array. Parameters: source : float, data series. length : int, size. Returns: float array. smooth_data_2d(data, rate) Smooth data sample into 2d points. Parameters: data...