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. Do IMF reports affect market expectations ?
    a sentiment analysis approach
    Author: Bennani, Hamza; Couharde, Cécile; Wallois, Yoan
    Published: [2021]
    Publisher:  EconomiX - UMR7235, Université Paris Nanterre, Nanterre

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 334
    Inter-library loan:
    No inter-library loan
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Working paper / EconomiX ; 2021, 6
    Subjects: Financial markets; High frequency; IMF; Sentiment index; Text analysis
    Scope: 1 Online-Ressource (circa 38 Seiten), Illustrationen
  2. Nowcasting euro area GDP with news sentiment
    a tale of two crises
    Author: Ashwin, Julian; Kalamara, Eleni; Saiz, Lorena
    Published: [2021]
    Publisher:  European Central Bank, Frankfurt am Main, Germany

    This paper shows that newspaper articles contain timely economic signals that can materially improve nowcasts of real GDP growth for the euro area. Our text data is drawn from fifteen popular European newspapers, that collectively represent the four... more

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

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 534
    Inter-library loan:
    No inter-library loan

     

    This paper shows that newspaper articles contain timely economic signals that can materially improve nowcasts of real GDP growth for the euro area. Our text data is drawn from fifteen popular European newspapers, that collectively represent the four largest Euro area economies, and are machine translated into English. Daily sentiment metrics are created from these news articles and we assess their value for nowcasting. By comparing to competitive and rigorous benchmarks, we find that newspaper text is helpful in nowcasting GDP growth especially in the first half of the quarter when other lower-frequency soft indicators are not available. The choice of the sentiment measure matters when tracking economic shocks such as the Great Recession and the Great Lockdown. Non-linear machine learning models can help capture extreme movements in growth, but require sufficient training data in order to be effective so become more useful later in our sample.

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9789289948692
    Other identifier:
    hdl: 10419/249889
    Series: Working paper series / European Central Bank ; no 2616 (November 2021)
    Subjects: Text analysis; Forecasting; Machine learning; Business cycles; COVID-19
    Scope: 1 Online-Ressource (circa 52 Seiten), Illustrationen
  3. Carbon boards and transition risk: explicit and implicit exposure implications for total stock returns and dividend payouts
    Author: Mazzarano, Matteo; Guastella, Gianni; Pareglio, Stefano; Xepapadeas, Anastasios
    Published: November 2021
    Publisher:  Fondazione Eni Enrico Mattei, Milano, Italia

    The Security and Exchange Commission (SEC) has considered climate change as a risk issue since 2010. Several emission disclosure initiatives exist aimed at informing investors about the financial risks associated with a zero or low carbon transition.... more

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

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 125
    Inter-library loan:
    No inter-library loan

     

    The Security and Exchange Commission (SEC) has considered climate change as a risk issue since 2010. Several emission disclosure initiatives exist aimed at informing investors about the financial risks associated with a zero or low carbon transition. Stricter regulations, particularly in a few sectors, could affect operations costs, ultimately impacting companies financial performances, especially of listed companies. There are two ways these companies can disclose their transition risk exposure and are not alternatives. One is the explicit declaration of exposure to transition risk in the legally binding documents that listed companies must provide authorities. The other is the disclosure of GHG equivalent emissions, which is implicitly associated with transition risk exposure. This paper empirically analyses to what extent US companies stock returns incorporate information about transition risk by using explicit and implicit risk measures and comparing them. In addition, multiple total stock return measures distinguishing dividend payouts from simple stock returns. Results suggest that both explicit and implicit risks are positively related to dividend payouts and not to stock returns, while the overall effect on total stock returns is negative. Evidence supports the view that market operators price negatively the transition risk exposure and, probably as a consequence, boards in carbon intensive companies use dividend policies to attract investment in risky companies.

     
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/249964
    Series: Working paper / Fondazione Eni Enrico Mattei ; 2021, 029
    Subjects: Climate risk; Transition Risk; SEC-10K; Mandatory Disclosure; Text analysis; CAPM
    Scope: 1 Online-Ressource (circa 28 Seiten), Illustrationen
  4. New indicator of science and technology inter-relationship by using text information of research articles and patents in Japan
    Author: Motohashi, Kazuyuki; Koshiba, Hitoshi; Ikeuchi, Kenta
    Published: [2021]
    Publisher:  RIETI, [Tokyo, Japan]

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    Keine Rechte
    Inter-library loan:
    No inter-library loan
    Export to reference management software   RIS file
      BibTeX file
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Edition: Revised version August 2021
    Series: RIETI discussion paper series ; 21-E, 025
    Subjects: Text analysis; patent information; research paper; science and technology linkage
    Scope: 1 Online-Ressource (circa 19 Seiten), Illustrationen