Welcome to Portfolio Networks, brought to you by Portfolio Selection Systems
18th January 2018

About Us

PSS publishes a state of the art portfolio selection software package PSS Release 2.0: Digital Portfolio Theory. PSS gives the investor the ability to efficiently achieve market timing and optimal diversification by applying digital signal processing to the classical Modern Portfolio Theory portfolio selection problem. The application of the mathematics of digital signal processing to financial network theory has resulted in a revolutionary new approach to risk management and portfolio selection. The addition of a time dimension to risk, allows memory to be included in the investment model. The PSS software package enables the user to find optimal diversified portfolios of investments based on systematic, unsystematic, calendar and non-calendar risk. Not only is PSS the most sophisticated large scale portfolio optimization software but it also performs fundamental analysis as well. The software does not do any form of technical analysis or forecasting. The software package utilizes digital signal processing technology to measure the risk of calendar and long memory effects. Calendar and non-calendar risk are used to solve the Digital Portfolio Theory model. The Digital Portfolio Theory model is presented in the PSS User’s Guide. The PSS Release 2.0 software package makes the benefit of this new theory available to the average investor.

Also available from PSS is the textbook, Portfolio Management, by the same author as the software package. The book gives an in depth treatment of the theoretical model used in the software package. It presents the theoretical transformation of financial theory using signal processing to describe risk. The stochastic generalized portfolio network model derived in the book creates a unified field of financial risk management and portfolio optimization. A complete derivation of Digital Portfolio Theory is available in the book Portfolio Management published by McGraw-Hill in 1992.