Multiple factor models for equities : An empirical study of the performance of factor mimicking portfolios

The trade-off between risk and return for equities has long been a challenge for portfolio and risk managers in order to create financial success and stability. This issue has led to several researchers trying to explain equity returns through various factor models. The capital asset-pricing model (CAPM) formulated by Sharpe (1964), Lintner (1965), and Black (1972) was the first model explaining the relation between cross-sectional returns relative the broad market index. Since then, factor models have evolved and fundamental multiple factor models have been found to successfully explain the risk structure of equities, through linear combinations of firm specific data and market data. In this paper, we implement and analyze a fundamental factor model. The objective is to build a dynamic and robust model that provide portfolio and risk managers with insight of what drives returns and risks of equities and portfolios. A key to understand the advantages of factor models lies in the characteristics of factors and the concept of factor mimicking portfolios, whose return perfectly replicates those of factors. These portfolios are derived through cross-sectional regressions of security returns and standardized exposure towards factors, which results in portfolios with a desired exposure. The model implementation is applied and evaluated for both a European and Swedish estimation universe, and the result indicate that some factor mimicking portfolios yield an excess return relative the market during 2015-01-01 to 2017-01-01.