A0395
Title: Portfolio replication via penalisation with asymmetric deviation measures
Authors: Rosella Giacometti - University of Bergamo (Italy) [presenting]
Gabriele Torri - University of Bergamo (Italy)
Sandra Paterlini - University of Trento (Italy)
Abstract: Passive strategies, such as the ones implemented by ETFs and ETPs, have gained increasing popularity among investors. In this context, smart beta products promise better performance or lower risk by implementing systematically investing strategies while being cheaper than traditional active strategies. Penalized optimization strategies may offer significant advantages to investors, thanks to their ability to control estimation risk and reduce turnover compared to non-penalized optimal portfolio strategies. In the context of index replication, most literature focuses on the minimization of tracking error measures compared to an index, while imposing constraints on the performances or limiting the number of assets included in the portfolios. We propose here some investment strategies that aim to minimize an asymmetric risk measure related to the expectile, while controlling for the portfolio weight distance from a benchmark composition. Empirical analysis on the S&P100 US, FTSE 100 index and the EUROSTOXX 50 allows to critically discuss the pros and cons of the proposed strategies compared to state-of-art benchmarks
