Fixed trading costs, signal processing and stochastic portfolio networks

In this study, we use zero-one variables to control fixed transaction costs independent of trade size in the portfolio selection problem. The optimal solution to the maximum flow, risk constrained stochastic portfolio network is found using Digital Portfolio Theory (DPT). Digital signals describe return processes and power spectral densities describe variances of long and short horizon returns. We find high fixed trading costs reduce size and affect composition of optimal portfolios for small investors or long holding periods. High risk portfolios are more sensitive to trading costs. Optimal portfolios for active traders or large portfolios are largely unaffected by fixed commission costs.