macrocephalopod

There's a massive gap between how optimization in finance (particularly portfolio optimizers) are viewed by non-experts, and how they are used by practitioners. That gap is responsible for some false beliefs, along the lines of "optimization never works" or ...

"portfolio optimizers always maximize errors" or "optimizers are for dweebs". Wrong! I'll try to explain why. The non-expert view of portfolio optimizers is something like - you have a vector of alphas (expected returns), a covariance matrix, a vector of costs (e.g. spread and

impact), current position x0, and some constraints, and you run a quadratic optimization to find a vector of positions "x" which maximises alpha * x - x' * covariance * x - spread * abs(x - x0) - slippage If you do this naively you will get bad results!

A better approach, the one I use, is to start with a heuristic solution that you know works (i.e. you would make money with it). Then write down an optimization problem that gives you the same result. You're now in a good place because you have a set of parameters for the