This work addresses the problem of enhanced portfolio replication, proposing a strategy based on the minimization of a novel deviation strategies based on expectiles. This measure allows to account asymmetrically for the differences between the portfolio and the benchmark, favouring positive deviations compared to negative ones. We show that the model nests the minimum TEV replication scheme. The empirical applications focuses on the Standard and Poor’s 100 index, for which we create replicating portfolios with a positive expected excess return. The results show that the replication scheme proposed here allows to overperform the benchmark out-of-sample, and that portfolios with < . allow to reduce the lower tail risk measured in terms of CVAR compared to the minimum TEV portfolio. The resulting portfolios show a sufficient level of diversification, and a controlled turnover.

(2020). Minimum deviation enhanced portfolio replication with expectiles . In MANAGING AND MODELLING OF FINANCIAL RISKS. Retrieved from http://hdl.handle.net/10446/177930

Minimum deviation enhanced portfolio replication with expectiles

Torri, Gabriele
2020

Abstract

This work addresses the problem of enhanced portfolio replication, proposing a strategy based on the minimization of a novel deviation strategies based on expectiles. This measure allows to account asymmetrically for the differences between the portfolio and the benchmark, favouring positive deviations compared to negative ones. We show that the model nests the minimum TEV replication scheme. The empirical applications focuses on the Standard and Poor’s 100 index, for which we create replicating portfolios with a positive expected excess return. The results show that the replication scheme proposed here allows to overperform the benchmark out-of-sample, and that portfolios with < . allow to reduce the lower tail risk measured in terms of CVAR compared to the minimum TEV portfolio. The resulting portfolios show a sufficient level of diversification, and a controlled turnover.
File allegato/i alla scheda:
File Dimensione del file Formato  
proceeding MMFR 2020 Torri.pdf

Solo gestori di archivio

Versione: publisher's version - versione editoriale
Licenza: Licenza default Aisberg
Dimensione del file 2.21 MB
Formato Adobe PDF
2.21 MB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/177930
Citazioni
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact