Skip to main navigation Skip to main content
info(at)avldigital.remove-this.de
Deutsch English
Last searches

Results for *

Displaying results 1 to 4 of 4.

  1. Structural dynamic analysis of systematic risk
    Author: Calvet, Laurent E.; Czellar, Veronika; Gouriéroux, Christian
    Published: [2016]
    Publisher:  Centre de recherche en economie et statistique, [Palaiseau]

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Inter-library loan:
    No inter-library loan
    Export to reference management software   RIS file
      BibTeX file
    Content information
    Volltext (kostenfrei)
    Volltext (kostenfrei)
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Série des documents de travail / Centre de recherche en economie et statistique ; no. 2016, 19
    Subjects: Systemically Important Financial Institutions (SIFI); Merton’smodel; Value of the Firm; indirect inference; rating; ABC filtering and smoothing
    Scope: 1 Online-Ressource (circa 64 Seiten), Illustrationen
  2. When and why do buyers rate in online markets?
    Author: Hui, Xiang; Klein, Tobias J.; Stahl, Konrad
    Published: February 2022
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    Online ratings play an important role in many markets. We study the often disputed information content of these ratings, by proposing a reduced-form Bayesian model of the typical buyer's rating decision. Our empirical evidence based on eBay raw data... more

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

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 63
    Inter-library loan:
    No inter-library loan

     

    Online ratings play an important role in many markets. We study the often disputed information content of these ratings, by proposing a reduced-form Bayesian model of the typical buyer's rating decision. Our empirical evidence based on eBay raw data is in line with even intricate predictions from it. We thus have good reasons to calibrate the model to moments of the data. Our simulations suggest that the rating record reveals the seller’s type after about 100 transactions, or 65-70 ratings.

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/252079
    Series: CESifo working paper ; no. 9562 (2022)
    Subjects: online markets; rating; reputation
    Scope: 1 Online-Ressource (circa 60 Seiten), Illustrationen
  3. Learning from online ratings
    Author: Hui, Xiang; Klein, Tobias J.; Stahl, Konrad
    Published: June 2024
    Publisher:  CESifo, Munich, Germany

    Online ratings play an important role in many markets. However, how fast they can reveal seller types remains unclear. To study this question, we propose a new model in which a buyer learns about the seller’s type from previous ratings and her own... more

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

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 63
    Inter-library loan:
    No inter-library loan

     

    Online ratings play an important role in many markets. However, how fast they can reveal seller types remains unclear. To study this question, we propose a new model in which a buyer learns about the seller’s type from previous ratings and her own experience and rates the seller if she learns enough. We derive two testable implications and verify them using administrative data from eBay. We also show that alternative explanations are unlikely to explain the observed patterns. After having validated the model in that way, we calibrate it to eBay data to quantify the speed of learning. We find that ratings can be very informative. After 25 transactions, the likelihood of correctly predicting the seller type is above 95 percent.

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/301297
    Series: CESifo working papers ; 11171 (2024)
    Subjects: online markets; rating; reputation; Bayesian learning
    Scope: 1 Online-Ressource (circa 83 Seiten), Illustrationen
  4. ESG as protection against downside risk
    Author: Kräussl, Roman; Oladiran, Tobi; Stefanova, Denitsa
    Published: [2023]
    Publisher:  Center for Financial Studies, Goethe University, Frankfurt am Main, Germany

    We examine whether the uncertainty related to environmental, social, and governance (ESG) regulation developments is reflected in asset prices. We proxy the sensitivity of firms to ESG regulation uncertainty by the disparity across the components of... more

    Access:
    Resolving-System (kostenfrei)

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 108
    Inter-library loan:
    No inter-library loan

     

    We examine whether the uncertainty related to environmental, social, and governance (ESG) regulation developments is reflected in asset prices. We proxy the sensitivity of firms to ESG regulation uncertainty by the disparity across the components of their ESG ratings. Firms with high ESG disparity have a higher option-implied cost of protection against downside tail risk. The impact of the misalignment across the different dimensions of the ESG score is distinct from that of ESG score level itself. Aggregate downside risk bears a negative price for firms with low ESG disparity.

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/285370
    Series: CFS working paper series ; no. 708
    Subjects: ESG; rating; downside risk; options; regulation; risk premium
    Scope: 1 Online-Ressource (circa 56 Seiten), Illustrationen