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  • The Rockledge Group is an investment management firm specializing in Alternative Strategies and Sector Investing using “Sector Scoring and Allocation Methodology”. SectorSAM™ is a robust proprietary quantitative sector selection and rotation investment process. We have a demonstrated ability to obtain superior risk-adjusted returns by successfully forecasting the relative strength of sectors within the S&P 500 index.

    Over two decades ago the founding partners pioneered an investment approach based on the philosophy that the bulk of individual stock performance can be attributed to the sector the stock is in. We believe that sector investing provides better risk adjusted returns than investing in individual stocks. Based on this philosophy and using fundamental data, a quantitative analysis to score and rank sectors was developed and successfully tested with substantitative results. Consequently this strategy was used to manage over $9 billion of pension assets for a large insurance company.


    The Rockledge Group was founded in 2004 and in 2005 we launched our first strategy, which was given a name “L2 Market Outperform”. L2 successfully forecasts undervalued sectors and over the last eight years it has significantly outperformed its benchmark S&P 500.

    In 2008 a Long/Short version of this investment philosophy was developed and launched. This strategy, called “SectorAlpha”, is designed to provide stable monthly returns in any market environment over a market cycle.

    Rockledge works in various capacities with investors, for more information visit our Rockledge manages assets for high net worth individuals and institutions in the US and Europe. Our strategies are available on the following platforms: Interactive BrokersPlacemarkCovestorFolioFN.




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    Investment Philosophy

    The Rockledge Group was founded with the intent of applying risk management techniques acquired through years of experience in managing institutional products to the development of new investment strategies capitalizing on the availability and viability of emerging investment vehicles.

    Our initial work has concentrated on the use of ETFs to support a number of investment strategies. The increasing variety and liquidity offered by ETFs is quickly reshaping the investment landscape confronting both retail and institutional investors.

    Of particular interest to us was the development of a strategy that could capitalize on the efficiency with which sector exposure could be captured or eliminated through available ETFs. This efficiency has continued to increase in markets over time allowing ever larger potential portfolios to be considered in making use of these instruments.

    For a universe of stocks (such as the S&P500 Index) that can be completely partitioned into segments with representative ETFs interesting possibilities present themselves. We observe that there can be significant performance dispersion among the constituent index sectors. The ability to consistently identify which sectors will out perform the overall index and which will under perform over a specified time period can lead to considerable cumulative absolute returns.

    Our work here has been centered on the notion that the bulk of investment performance is attributable most consistently to proper sector selection. This is analogous to the conclusion offered by Brinson, Hood and Beebower, further supported by Ibbotson, Kaplan and also by Vardharaj and Fabozzi, that proper asset class selection is responsible for the greater part of overall investment results. Moreover, the use of broadly diversified capitalization weighted market segments leads to a superior risk/return profile.

    To accomplish this we have developed a process that forecasts sector excess returns over a given timeframe. Absolute returns (Long/Short strategy) are captured by going long sectors which we forecast to out perform the market and shorting sectors that are forecast to under perform the market. Market outperform positive returns relative to the S&P500 Index (Long strategy) are achieved by buying sectors with the greatest excess return forecasts.

    We approached our development process from two directions: first, through neural net analysis of over 200 factors influencing stock returns and secondly, through subjective influences gleaned from our experiences as institutional investors developing quantitative equity portfolio strategies. The intersection was further influenced by a desire for parsimony. Factors belong to three broad categories: fundamental, macroeconomic and market technical. Unlike many other quantitative approaches we have developed individual sector forecasts independently and insure that total market weighted sector excess return forecasts equal zero.

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