I've been testing out performance of simple Monte Carlo simulation for a call option, basically generating random samples of outcome and taking a mean. I did this with vectorization and also in a loop. What I found is that Julia is *way* slower than Matlab or numpy:
Julia Vectorized: 50.16s Loop: 358.6s Matlab Vactorized: 6.6s Numpy Vectorized: 10.31s The codes are in here: http://pithawat.com/post/monte-carlo-simulation http://pithawat.com/post/first-brush-with-julia Anyone care to explain why?
