Abstract
In this paper, we explore the ex-post attributes of 120 simulated portfolios across the U.S., International, and Emerging Markets. We estimate expected returns using a given global stock selection model employing Global Equity Rating (GLER) and Consensus Temporary Earnings Forecasting (CTEF) signals. Our portfolios are constructed under the Markowitz optimization framework and constrained at various tracking error levels. Further, an alpha alignment factor is applied to aid in portfolio construction. As a result of our research, we present the reader with three key findings. First, GLER and CTEF signals employed as the primary inputs to security selection result in portfolios with superior risk adjusted returns relative to the Russell 3000, MSCI AC World ex. US, and MSCI Emerging Markets benchmarks which they are measured against. Second, expanding the investment universe outside the U.S. increases the opportunity set yielding higher risk adjusted performance. Third, the incorporation of an alpha alignment factor within the portfolio construction process improves risk forecasts resulting in ex-post tracking error aligning more closely to ex-ante, and ultimately improving information ratios.
Highlights
There are generally multiple layers of investment research that are conducted in order to arrive at a final portfolio
We focus our research on the Global Equity Ratings (GLER) database in Guerard et al [1] and the consensus earnings forecasting efficiency variable, Consensus Temporary Earnings Forecasting (CTEF), developed in Guerard [2]
Excess return increases as tracking error goes up, information ratio is highest at lower tracking error levels, and Sharpe ratio remains consistent across most risk thresholds
Summary
There are generally multiple layers of investment research that are conducted in order to arrive at a final portfolio. We focus our research on the Global Equity Ratings (GLER) database in Guerard et al [1] and the consensus earnings forecasting efficiency variable, CTEF, developed in Guerard [2]. These variables are designed using FactSet and Thomson Financial global security databases. A detailed decomposition of our chosen signals can be found in section Stock Selection Models. After verifying the efficacy of the chosen stock selection model, the step is to transfer our given signal into an investable portfolio.
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