Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
6 documents
This tutorial develops bivariate copulas as a way to describe dependence separately from the marginal distributions of two variables. It defines tail dependence and the Fréchet–Hoeffding bounds, then explains how an empirical copula can be estimated from…
This module implements the bivariate Nelsen 13 copula, a tool for modeling dependence between two uniform variables. It provides the copula cumulative distribution and density, a conditional distribution, random pair generation, and a parameter estimator…
This class template describes a bivariate mixed copula as a weighted combination of component copulas. It calculates the mixture density, joint cumulative probability, and conditional probability by evaluating each component and summing according to its…
This technical reference implements the bivariate Joe copula, a dependence model with a parameter theta in the range from 1 upward. It provides formulas for the copula cumulative distribution, density, and conditional probability, along with a sampling…
This module supports copula analysis by mapping observations to marginal empirical cumulative probabilities, with optional linear interpolation and probability bounds. It provides a multivariate row-wise transform, fits a supplied copula to two series after…
This document defines a common interface for calculating trade amount and account equity, then supplies formulas for linear and inverse assets. For a linear contract, amount scales with contract size, execution price, and quantity; equity adds the marked…