I have a lot (>50) of back tested (and naively "validated") trading strategies. They trade different ETFs, mostly equities, but also others (like GLD, USO, ...). These are all strategies developed on daily time frame (daily bars) with entries/exit on open on next trading day. Mostly duration of the trades is a couple of days (mean reversion strategies). They vary in trading frequency. Some trade 30 times per year, some only 5 times per year (so return vector of a strategy is "sparse").
Their combined equity curve and statistics with 1/N allocation is impressive (I have hard time to believe this naive "diversification" of far from perfect trading strategies works so well).
The problem I have is that I would like to use capital more efficiently by having different allocation between strategies than 1/N. I know how to do portfolio optimization and treat each strategy as a return vector and combine them under different objectives (mean variance, max de-correlation, min concentration, max Sharpe, min draw down, ...) and constraints. But I am not sure the "profile" of these strategies lends themselves to this brute force optimization.
What approach would you recommend for combining these kind of strategies in a somewhat "optimal" portfolio? Is there an optimization approach that makes sense here? I would be grateful to be pointed to resources that deal with this kind of strategy portfolio construction.