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Gerstein Fisher’s Multi-Factor® Approach to Global Real Estate Investing

Gerstein Fisher offers investors a distinct strategy for obtaining exposure to global real estate. The first globally diversified REIT strategy to use a quantitative, multi-factor-based approach, it provides investors with intelligently constructed access to this fast-growing asset class.

Real estate investing today is more public, more global, more transparent, and more liquid than ever. Global real estate securities – in particular real estate investment trusts (REITs) – have played a key role in this transformation. US REITs and similar structures in other countries have provided a broad range of investors with access to an asset class traditionally known for its illiquidity, opaque and infrequent pricing, and high minimum investment requirement.

While still a relatively new construct in the investment world, REITs have seen significant and rapid growth since they were first created in the United States in 1960. The first European REIT legislation was passed in 1969 in the Netherlands, and today approximately 40 countries in North America, South America, Europe, Asia-Pacific, Africa and the Middle East have REIT legislation in place.

The Gerstein Fisher Multi-Factor® Global Real Estate Securities strategy provides investors with broad global diversification across REITs via a distinct quantitative, multi-factor® investment approach.

Factor-Based Investing and Multi-Factor Models
Factor-based investing involves identifying systematic sources of risk – called factors – that are primarily responsible for the variation in stock returns. The roots of Factor-based investing were laid with the Capital Asset Pricing Model (CAPM) in the early 1960s, which stated that a stock’s performance hinged solely on its beta; i.e. its relationship to the market. Since then, multiple such factors have been uncovered that help better explain the risk and return of securities. Given that we know today that multiple factors contribute to the variation of stock returns, how can we build models to account for this complexity? Instead of using one factor, as in CAPM, multi-factor models (MFMs) incorporate multiple risk factors to explain the performance of a given stock or portfolio.

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