Asset allocation models for big tech stocks: The importance of lower partial moments and short length windows

Abstract

The group of companies formed by Meta, Apple, Microsoft, Amazon and Alphabet have become a successful investment alternative in the U.S. stock market. In this context, the aim of this research is to provide investment strategies based on these companies to the challenge of how individual investors should allocate their funds in a portfolio and outperform benchmarks such as the SPY ETF or a naïve portfolio. To this end, we developed a total of 20 asset allocation models and constructed portfolios with different rebalancing periods between April 2014 and June 2022. Our overall results reveal that a combination of a short window length for estimating the parameters of the asset allocation models and a procedure that takes downside risk into account, more precisely the Lower Partial Moment approach, significantly outperforms the alternative of investing in the SPY ETF and also the naïve portfolio.