Agree mostly, caveat though that some pricing models indeed are better than others at capturing the true distributional properties. The French quant derivatives guilt has carved itself out a nice edge by running their own customized pricing models that I firmly believe capture risk (the first derivatives and higher order ones) better than classic pricing models. I have seen it way too much over the many years to resort the out performance to mere chance.
Financial markets can be modeled under any number random variable models and their assumed distributions (ie normal, lognormal, pareto etc.) The problem is that none of these models explains reality significantly better than any of the others. The reason is that the underlying processes are more complex than the statistical models can capture. Gee, there's a revelation, human behavior is complex and highly unpredictable.
So the real answer is yes and no. The task is to discern when it is and when it isn't, and have the proper trading plan in place to deal with regime change from random to non-random.