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
This tool is a quantitative tip for analysts who study volumes or create volume based trading strategies. Like all our projects, we start with a statistical logic to which we add coding logic. This indicator can save a huge amount of time in calculating the variation of volume between sessions . How it work The indicator calculates the difference between...
Counts days to expected Return Of Investment from any given time. Works only with "1 Day" resolution
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...
A Simple Crypto Dashboard/Screener which indicates the Price and percentage changes for the Given Period of time i.e for 1 Hr ,4 Hrs, 1 Day, 3 Days, 3 Weeks and 3 - 12 Months. By Default it displays #BTC and its Dominance and current trading pair Price and % changes.
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 "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...
Library "FunctionBlackScholes" Some methods for the Black Scholes Options Model, which demonstrates several approaches to the valuation of a European call. // reference: // people.math.sc.edu // people.math.sc.edu asset_path(s0, mu, sigma, t1, n) Simulates the behavior of an asset price over time. Parameters: s0 : float, asset price at...
Library "FunctionMinkowskiDistance" Method for Minkowski Distance, The Minkowski distance or Minkowski metric is a metric in a normed vector space which can be considered as a generalization of both the Euclidean distance and the Manhattan distance. It is named after the German mathematician Hermann Minkowski. reference: en.wikipedia.org double(point_ax,...
Library "regress" produces the slope (beta), y-intercept (alpha) and coefficient of determination for a linear regression regress(x, y, len) regress: computes alpha, beta, and r^2 for a linear regression of y on x Parameters: x : the explaining (independent) variable y : the dependent variable len : use the most recent "len" values of x and...
Library "FunctionNNLayer" Generalized Neural Network Layer method. function(inputs, weights, n_nodes, activation_function, bias, alpha, scale) Generalized Layer. Parameters: inputs : float array, input values. weights : float array, weight values. n_nodes : int, number of nodes in layer. activation_function : string, default='sigmoid',...
Library "FunctionNNPerceptron" Perceptron Function for Neural networks. function(inputs, weights, bias, activation_function, alpha, scale) generalized perceptron node for Neural Networks. Parameters: inputs : float array, the inputs of the perceptron. weights : float array, the weights for inputs. bias : float, default=1.0, the default bias...
Library "MLLossFunctions" Methods for Loss functions. mse(expects, predicts) Mean Squared Error (MSE) " MSE = 1/N * sum ((y - y')^2) ". Parameters: expects : float array, expected values. predicts : float array, prediction values. Returns: float binary_cross_entropy(expects, predicts) Binary Cross-Entropy Loss (log). Parameters: ...
Library "FunctionPeakDetection" Method used for peak detection, similar to MATLAB peakdet method function(sample_x, sample_y, delta) Method for detecting peaks. Parameters: sample_x : float array, sample with indices. sample_y : float array, sample with data. delta : float, positive threshold value for detecting a peak. Returns: tuple with...
Library "cache" A simple cache library to store key value pairs. Fed up of injecting and returning so many values all the time? Want to separate your code and keep it clean? Need to make an expensive calculation and use the results in numerous places? Want to throttle calculations or persist random values across bars or ticks? Then you've come to...