simulation - Is there a python function similar to np.random.multivariate_normal that generates NON-NORMAL distribution?

Question

Python function np.random.multivariate_normal(mean, cov, n) generates NORMAL random series with given covariance and mean. I would like to generate random series with given covariance and mean, but NOT NORMAL. Is there such a funcion IN PYTHON?

In my case I have time series for 10 stock returns. Those returns are not normal-distributed. I want to simulate 5000 returns for each stock, in such a way that they have same mean and covariance as my original stocks returns. I don't want those simulated returns to be normal-distributed, but rather to have a distribution similar to the original stocks.

Answer 1

You can reach a random distribution you'd like by mapping a uniform distribution to an inverse CDF function (edit: if it has a closed form CDF, like @pjs mention below) of your distribution.

here is a good SO resource. and here is a good explanation how to do it