Comparative Analysis of the Semi-parametric Estimation Methodologies and Copula Estimation in Value at Risk (VaR) in the Colombian Stock Market This research article illustrates different types of statistical methodologies with the objective of making an adequate estimate for value at risk (VaR), implementing the use of semi-parametric methods and a flexible class of copulas named VineCopulas. It was found that it is possible to explain volatility and dynamic market movements in estimation techniques by including the management of complex patterns of non-linear dependence in the modeling of financial assets. The flexibility of the models presented with the use of copulas and semi-parametric methodologies, such as quasi-maximum likelihood estimate (QMLE) and extreme value theory (EVT), allowed the adequate estimation of VaR in the Colombian equity market.