I heard about "Walk Forward Analysis", to me it's just like a dynamic rolling-window out-of-sample test coupled with optimization. The result of this "Walk Forward Analysis" is a set of "optimized" parameters that are suitable for all history(it's robust, but kind of conservative). Am I right? Any good ways of avoiding over-fitting or over-optimization? Thanks!