Effective Stock Selection and Portfolio Construction Within US, International, and Emerging Markets

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.

Investment Portfolio Management equities applying Markowitz Theory

“…En el modelo clásico de media-varianza (MV), hay dos situaciones principales para la aplicación práctica. El primero es que el MV se basa en el rendimiento esperado y el riesgo de los activos de entrada para producir carteras óptimas para cada nivel de rendimiento esperado y riesgo (Beheshti, 2018). Como DOI: http://dx.doi.org/10.17268/sciendo.2023.030 resultado, al seleccionar buenos activos para poner en el proceso de optimización, el modelo MV puede lograr un mejor rendimiento (Mitra Thakur et al, 2018).…”