Equity & fixed income investment strategies for institutional investors.

Asset Management

Overview

GFA Asset Management is the culmination of decades of valuation, risk management and optimization excellence. Powered by the same technology used by leading institutions and government agencies, we combine 45+ years of valuation and risk analysis expertise with cutting edge research and practical implementation, to provide an unparalleled foundation for asset management success.

Strategic Opportunity Portfolio

GFA Strategic Opportunity Portfolio (SOP)

The GFA Strategic Opportunity Portfolio (SOP) is based on a quantitatively driven, highly risk controlled approach designed to achieve incremental return over and above a specified benchmark. This strategy includes state-of-the-art investment technology for portfolio structuring.

An important driver of the GFA Asset Management investment process is the analysis of the yield spread of securities in the benchmark universe. GFA has the capability of quantifying the actual or implied spread (the difference in the yield between the issuer and the Treasury curve). Changes in the spread is a basis for anticipating the financial well being or distress of the company. It is this “early warning” mechanism which provides insights to the expected performance of both individual securities as well as sectors.

The risk analysis is based on a multi-factor approach where the total risk is decomposed into risk exposures at the individual security level. These individual security risk factors are combined by an optimizer to achieve the optimal return and risk profile for the portfolio.

Decision Process

Decision Process

The GFA SOP decision process starts with the trading of universe of the Russell 1000 Index. The universe is analyzed by a portfolio optimization system, which takes into account a securities’ relative yield, expected price appreciation and risk characteristics.

The portfolio optimization step is part of an iterative process where the resulting optimized portfolio may be re-optimized a number of times to achieve an acceptable risk/return trade-off.

The optimization objective is to maximize the portfolio return subject to desired constraints and a risk target.