Tailor-made strategies through different weight simulation of factor-based investing

Abstract This study explores the implementation and factor integration of diverse factor-based investment strategies in the European market. Specifically, we investigate a contrarian strategy, two value strategies, and a momentum strategy from 2015 to June 2024. Utilising the Python framework Qrumble for efficient experimentation, we integrate evaluation metrics and we consider beyond the commonly used portfolios, equally weighted and value-weighted, two theoretically efficient portfolios - minimum variance and market portfolio. While certain strategies yielded outcomes not entirely in line with state-of-the-art standards, both value strategies showed promising returns with manageable risk. Notably, the combination of factors in a multi-type strategy, named Magical Bambu, demonstrated interesting results, suggesting the potential for effective collaboration between different investment methodologies. This study underscores the nuanced outcomes within theoretically efficient portfolios under specific conditions, prompting further exploration.