Franklin Portfolio Associates, LLC (FPA) believes that employing a disciplined investment strategy, based on fundamental concepts that are quantitatively implemented, provides us with the best opportunity to add consistent value to our clients' portfolios while maintaining an acceptable level of risk.

Our investment process is predicated on the belief that we can consistently differentiate differentiate between undervalued and overvalued securities between undervalued and overvalued securities. As a result, we emphasize stock selection in our process and limit our over- or under-exposure to sectors and other factors. Using over 40 models or factors, we rank stocks in terms of relative attractiveness. The factors can be categorized into one of seven separate themes. Three of the themes are value oriented, three themes are momentum oriented, and the final theme focuses on management signals.

The value themes answer the question of is a particular stock attractively priced relative to its peers. single score of relative attractivenessThe momentum themes focus on the relative health of a particular company, again versus its peers. Health could be described as earnings improvement, long-term growth prospects or price momentum. The aggregate weight of the value factors remains fairly close to the aggregate weight of the momentum factors at all times (+/- 10%) to avoid a style trap within the portfolio. The management signals theme examines indicators such as executive buying and selling as well as corporate buy-back/issuance activity. All of the factors are rolled up into a single score of relative attractiveness for each stock in the investable universe.

To enable us to make meaningful comparisons between stocks that have different industry, style, capitalization, and/or characteristics, Peer Group Relativization we rigorously apply a sophisticated process that we call Peer Group Relativization (PGR). PGR removes certain industry and style effects that can distort a fair comparison across a wide universe of securities. The individual measures are then blended together using a proprietary approach to determine a single score of attractiveness. This proprietary blending gives favorable consideration to measures that have high levels of predictiveness, low levels of variability, and a low degree of correlation with other measures.