Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://doi.org/10.21256/zhaw-21933| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Robust covariance estimators for mean-variance portfolio optimization with transaction lots |
| Autor/-in: | Rosadi, Dedi Setiawan, Ezra Putranda Templ, Matthias Filzmoser, Peter |
| et. al: | No |
| DOI: | 10.1016/j.orp.2020.100154 10.21256/zhaw-21933 |
| Erschienen in: | Operations Research Perspectives |
| Band(Heft): | 7 |
| Heft: | 100154 |
| Erscheinungsdatum: | 2020 |
| Verlag / Hrsg. Institution: | Elsevier |
| ISSN: | 2214-7160 |
| Sprache: | Englisch |
| Schlagwörter: | Finance; Markowitz portfolio; Transaction lot; Robust estimation; Genetic algorithm |
| Fachgebiet (DDC): | 510: Mathematik |
| Zusammenfassung: | This study presents an improvement to the mean-variance portfolio optimization model, by considering both the integer transaction lots and a robust estimator of the covariance matrices. Four robust estimators were tested, namely the Minimum Covariance Determinant, the S, the MM, and the Orthogonalized Gnanadesikan–Kettenring estimator. These integer optimization problems were solved using genetic algorithms. We introduce the lot turnover measure, a modified portfolio turnover, and the Robust Sharpe Ratio as the measure of portfolio performance. Based on the simulation studies and the empirical results, this study shows that the robust estimators outperform the classical MLE when data contain outliers and when the lots have moderate sizes, e.g. 500 shares or less per lot. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/21933 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2020_Rosadi_etal_Robust-covariance-estimators.pdf | 2.95 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Rosadi, D., Setiawan, E. P., Templ, M., & Filzmoser, P. (2020). Robust covariance estimators for mean-variance portfolio optimization with transaction lots. Operations Research Perspectives, 7(100154). https://doi.org/10.1016/j.orp.2020.100154
Rosadi, D. et al. (2020) ‘Robust covariance estimators for mean-variance portfolio optimization with transaction lots’, Operations Research Perspectives, 7(100154). Available at: https://doi.org/10.1016/j.orp.2020.100154.
D. Rosadi, E. P. Setiawan, M. Templ, and P. Filzmoser, “Robust covariance estimators for mean-variance portfolio optimization with transaction lots,” Operations Research Perspectives, vol. 7, no. 100154, 2020, doi: 10.1016/j.orp.2020.100154.
ROSADI, Dedi, Ezra Putranda SETIAWAN, Matthias TEMPL und Peter FILZMOSER, 2020. Robust covariance estimators for mean-variance portfolio optimization with transaction lots. Operations Research Perspectives. 2020. Bd. 7, Nr. 100154. DOI 10.1016/j.orp.2020.100154
Rosadi, Dedi, Ezra Putranda Setiawan, Matthias Templ, and Peter Filzmoser. 2020. “Robust Covariance Estimators for Mean-Variance Portfolio Optimization with Transaction Lots.” Operations Research Perspectives 7 (100154). https://doi.org/10.1016/j.orp.2020.100154.
Rosadi, Dedi, et al. “Robust Covariance Estimators for Mean-Variance Portfolio Optimization with Transaction Lots.” Operations Research Perspectives, vol. 7, no. 100154, 2020, https://doi.org/10.1016/j.orp.2020.100154.
Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.