Direkt zur Hauptnavigation springen Direkt zum Inhalt springen
info(at)avldigital.remove-this.de
Deutsch English
Letzte Suchanfragen

Ergebnisse für *

Zeige Ergebnisse 1 bis 5 von 5.

  1. Entropy-driven portfolio selection
    a downside and upside risk framework
    Autor*in: Rödder, Wilhelm; Gartner, Ivan Ricardo; Rudolph, Sandra
    Erschienen: 2009
    Verlag:  Fernuniv., Fak. Wirtschaftswiss., Hagen

    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Druck
    RVK Klassifikation: QB 910 ; QB 910
    Schriftenreihe: Diskussionsbeitrag / FernUniversität in Hagen ; Nr. 437
    Schlagworte: Portfolio Selection; Risikoverhalten; Entropie; Künstliche Intelligenz; Expertensystem; Theorie
    Weitere Schlagworte: (stw)Portfolio-Management; (stw)Risikopräferenz; (stw)Entropie; (stw)Künstliche Intelligenz; (stw)Expertensystem; (stw)Theorie; (stw)Deutschland; Finance; Artificial intelligence; Expert systems; Portfolio selection; Arbeitspapier; Graue Literatur; Buch
    Umfang: 27 S., graph. Darst., 30 cm
  2. Efficient mean-variance portfolio selection by double regularization
    Autor*in: Koné, N'Golo
    Erschienen: 2-2021
    Verlag:  Department of Economics, Queen's University, Kingston, Ontario, Canada

    This paper addresses the estimation issue that exists when estimating the traditional mean-variance portfolio. More precisely, the efficient mean-variance is estimated by a double regularization. These regularization techniques namely the ridge, the... mehr

    Zugang:
    Verlag (kostenfrei)
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 216
    Fernleihe:
    keine Fernleihe

     

    This paper addresses the estimation issue that exists when estimating the traditional mean-variance portfolio. More precisely, the efficient mean-variance is estimated by a double regularization. These regularization techniques namely the ridge, the spectral cut-off, and Landweber-Fridman involve a regularization parameter or penalty term whose optimal value needs to be selected efficiently. A data-driven method has been proposed to select the tuning parameter. We show that the double regularized portfolio guarantees to investors the maximum expected return with the lowest risk. In empirical and Monte Carlo experiments, our double regularized rules are compared to several strategies, such as the traditional regularized portfolios, the new Lasso strategy of Ao, Yingying, and Zheng (2019), and the naive 1/N strategy in terms of in-sample and out-of-sample Sharpe ratio performance, and it is shown that our method yields significant Sharpe ratio improvements and a reduction in the expected utility loss.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/230605
    Schriftenreihe: Queen's Economics Department working paper ; no. 1453
    Schlagworte: Portfolio selection; efficient mean-variance analysis; double regularization
    Umfang: 1 Online-Ressource (circa 42 Seiten)
  3. Portfolio performance of linear SDF models
    an out-of-sample assessment
    Autor*in: Guidolin, Massimo; Hansen, Erwin; Lozano-Banda, Martín
    Erschienen: [2018]
    Verlag:  IGIER, Università Bocconi, Milano, Italy

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Fernleihe:
    keine Fernleihe
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Volltext (kostenfrei)
    Volltext (kostenfrei)
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Auflage/Ausgabe: This version: February, 2018
    Schriftenreihe: Working paper series / IGIER ; n. 627
    Schlagworte: Linear asset pricing models; Stochastic discount factor; Portfolio selection; Out-of-sample performance
    Umfang: 1 Online-Ressource (circa 37 Seiten), Illustrationen
    Bemerkung(en):

    Richtiger Name des 3. Verfassers: Martín Lozano-Banda
  4. Test for trading costs effect in a portfolio selection problem with recursive utility
    Autor*in: Carrasco, Marine; Koné, N’Golo
    Erschienen: [2023]
    Verlag:  CIRANO, [Montréal]

    Zugang:
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)
    Verlag (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Fernleihe:
    keine Fernleihe
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    Schriftenreihe: Working paper / CIRANO ; 2023s, 03
    Schlagworte: Portfolio selection; transaction costs; testing overidentifying restrictions; recursive utility
    Umfang: 1 Online-Ressource (circa 60 Seiten)
  5. Regularized maximum diversification investment strategy
    Autor*in: Koné, N'Golo
    Erschienen: 1-2021
    Verlag:  Department of Economics, Queen's University, Kingston, Ontario, Canada

    The maximum diversification portfolio as defined by Choueifaty (2011) depends on the vector of asset volatilities and the inverse of the covariance matrix of the asset return. In practice, these two quantities need to be replaced by their sample... mehr

    Zugang:
    Verlag (kostenfrei)
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 216
    Fernleihe:
    keine Fernleihe

     

    The maximum diversification portfolio as defined by Choueifaty (2011) depends on the vector of asset volatilities and the inverse of the covariance matrix of the asset return. In practice, these two quantities need to be replaced by their sample statistics. The estimation error associated with the use of these sample statistics may be amplified due to (near) singularity of the covariance matrix, in financial markets with many assets. This in turn may lead to the selection of portfolios that are far from the optimal regarding standard portfolio performance measures of the financial market. To address this problem, we investigate three regularization techniques, including the ridge, the spectral cut-off, and the Landweber-Fridman approaches in order to stabilize the inverse of the covariance matrix. These regularization schemes involve a tuning parameter that needs to be chosen. In light of this fact, we propose a data-driven method for selecting the tuning parameter. We show that the selected portfolio by regularization is asymptotically efficient with respect to the diversification ratio. In empirical and Monte Carlo experiments, the resulting regularized rules are compared to several strategies, such as the most diversified portfolio, the target portfolio, the global minimum variance portfolio, and the naive 1/N strategy in terms of in-sample and out-of-sample Sharpe ratio performance, and it is shown that our method yields significant Sharpe ratio improvements.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/230602
    Schriftenreihe: Queen's Economics Department working paper ; no. 1450
    Schlagworte: Portfolio selection; Maximum diversification; Regularization
    Umfang: 1 Online-Ressource (circa 34 Seiten), Illustrationen