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  1. Modeling frailty correlated defaults with multivariate latent factors
    Autor*in: Christoffersen, Benjamin; Matin, Rastin
    Erschienen: [2020]
    Verlag:  Danmarks Nationalbank, Copenhagen

    Firm-level default models are important for bottomup modeling of the default risk of corporate debt portfolios. However, models in the literature typically have several strict assumptions which may yield biased results, notably a linear effect of... mehr

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 135
    Fernleihe:
    keine Fernleihe

     

    Firm-level default models are important for bottomup modeling of the default risk of corporate debt portfolios. However, models in the literature typically have several strict assumptions which may yield biased results, notably a linear effect of covariates on the log-hazard scale, no interactions, and the assumption of a single additive latent factor on the log-hazard scale. Using a sample of US corporate firms, we provide evidence that these assumptions are too strict and matter in practice and, most importantly, we provide evidence of a time-varying effect of the relative firm size. We propose a frailty model to account for such effects that can provide forecasts for arbitrary portfolios as well. Our proposed model displays superior out-of-sample ranking of firms by their default risk and forecasts of the industry-wide default rate during the recent global financial crisis.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/227869
    Schriftenreihe: Working paper / Danmarks Nationalbank ; no. 151 (22 January 2020)
    Umfang: 1 Online-Ressource (circa 27 Seiten), Illustrationen
  2. Seeing through the spin
    the effect of news sentiment on firms' stock market performance
    Autor*in: Daetz, Stine Louise; Hvid, Anna Kirstine; Martinello, Alessandro; Matin, Rastin
    Erschienen: [2019]
    Verlag:  Danmarks Nationalbank, Copenhagen

    The sentiment of news predicts the short-term stock market performance of individual companies. We find that this association is solely due to the idiosyncratic informational content of an article. We transparently quantify the association between... mehr

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 135
    Fernleihe:
    keine Fernleihe

     

    The sentiment of news predicts the short-term stock market performance of individual companies. We find that this association is solely due to the idiosyncratic informational content of an article. We transparently quantify the association between news sentiment and stock market performance of S&P 500 companies, using articles written by Reuters between 2000 and 2018. First, we isolate the effect of sentiment independently of idiosyncratic informational content by exploiting a topicbased shift-share instrument. Second, we show that exogenous variation in article sentiment isolated through our topic-based shiftshare instrument, while strongly related to article sentiment, is unrelated to abnormal returns in the stock market.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/227859
    Schriftenreihe: Working paper / Danmarks Nationalbank ; no. 141 (4 October 2019)
    Umfang: 1 Online-Ressource (circa 26 Seiten), Illustrationen
  3. Are climate change risks priced in the U.S. Stock market?
    Autor*in: Faccini, Renato; Matin, Rastin; Skiadopoulos, George
    Erschienen: [2021]
    Verlag:  Danmarks Nationalbank, Copenhagen

    We construct novel proxies of physical and transition climate risks by conducting textual analysis of climate-change news over the period 2000-2018. This analysis uncovers four textual variables related to the topics of U.S. climate policy,... mehr

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 135
    Fernleihe:
    keine Fernleihe

     

    We construct novel proxies of physical and transition climate risks by conducting textual analysis of climate-change news over the period 2000-2018. This analysis uncovers four textual variables related to the topics of U.S. climate policy, international summits, natural disasters, and global warming, respectively. The first two variables proxy transition risks, whereas the last two proxy physical risks. We find that only the climate policy factor is priced in the U.S. stock market with the evidence being more pronounced over 2012-2018. The documented premium is consistent with the idea that investors hedge short-term transition risks. We validate this explanation using a narrative approach to measuring climate news. Our results imply that investors' attention is an important driver of asset returns

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/245990
    Schriftenreihe: Working paper / Danmarks Nationalbank ; nr. 169 (08 February 2021)
    Schlagworte: Climate; Financial Stability; Statistical Method
    Umfang: 1 Online-Ressource (circa 57 Seiten), Illustrationen
  4. Female business owners pay higher interest rates on corporate loans
    Autor*in: Martinello, Alessandro Tang-Andersen; Mønsted, Bjarke; Matin, Rastin; Steffensen, Sigurd Anders Muus; Holm Laursen, Karen
    Erschienen: [2021]
    Verlag:  Danmarks Nationalbank, Copenhagen

    We analyze micro-level data from the Danish credit register and find that female business owners pay higher interest rates on corporate loans than male owners. The gender gap is partly explained by differences in firm and loan characteristics.... mehr

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 135
    Fernleihe:
    keine Fernleihe

     

    We analyze micro-level data from the Danish credit register and find that female business owners pay higher interest rates on corporate loans than male owners. The gender gap is partly explained by differences in firm and loan characteristics. However, an economically and statistically significant gap persists even after flexible machine learning techniques are applied to the data. While the gender gap most likely arises during the negotiation process, we do not find that it depends on market power or the extent to which banks use data-driven approaches to determine interest rates.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/246000
    Schriftenreihe: Working paper / Danmarks Nationalbank ; nr. 179 (25 June 2021)
    Schlagworte: Financial sector; changes in interest rates; credit risk; statistical methods
    Umfang: 1 Online-Ressource (circa 41 Seiten), Illustrationen
  5. Can machine learning models capture correlations in corporate distresses?
    Autor*in: Christoffersen, Benjamin; Matin, Rastin; Mølgaard, Pia
    Erschienen: 26 October 2018
    Verlag:  Danmarks Nationalbank, Copenhagen

    Accurate probability-of-distress models are central to regulators, firms, and individuals who need to evaluate the default risk of a loan portfolio. A number of papers document that recent machine learning models outperform traditional corporate... mehr

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 135 (128)
    Fernleihe:
    keine Fernleihe

     

    Accurate probability-of-distress models are central to regulators, firms, and individuals who need to evaluate the default risk of a loan portfolio. A number of papers document that recent machine learning models outperform traditional corporate distress models in terms of accurately ranking firms by their riskiness. However, it remains unanswered whether advanced machine learning models can capture correlation in distresses, which traditional distress models struggle to do. We implement a regularly top-performing machine learning model and find that prediction accuracy of individual distress probabilities improves while there is almost no difference in the predicted aggregate distress rate relative to traditional distress models. Thus, our findings suggest that complex machine learning models do not eliminate the need for a latent variable that captures correlations in distresses. Instead, we propose a frailty model, which allows for correlations in distresses, augmented with regression splines. This model demonstrates competitive performance in terms of ranking firms by their riskiness, while providing accurate risk measures.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/202868
    Schriftenreihe: Working paper / Danmarks Nationalbank ; no. 128
    Umfang: 1 Online-Ressource (circa 37 Seiten), Illustrationen
  6. Predicting distresses using deep learning of text segments in annual reports
    Autor*in: Hansen, Caspar; Hansen, Christian; Matin, Rastin; Mølgaard, Pia
    Erschienen: 15 November 2018
    Verlag:  Danmarks Nationalbank, Copenhagen

    Corporate distress models typically only employ the numerical financial variables in the firms' annual reports. We develop a model that employs the unstructured textual data in the reports as well, namely the auditors' reports and managements'... mehr

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 135 (130)
    Fernleihe:
    keine Fernleihe

     

    Corporate distress models typically only employ the numerical financial variables in the firms' annual reports. We develop a model that employs the unstructured textual data in the reports as well, namely the auditors' reports and managements' statements. Our model consists of a convolutional recurrent neural network which, when concatenated with the numerical financial variables, learns a descriptive representation of the text that is suited for corporate distress prediction. We find that the unstructured data provides a statistically significant enhancement of the distress prediction performance, in particular for large firms where accurate predictions are of the utmost importance. Furthermore, we find that auditors' reports are more informative than managements' statements and that a joint model including both managements' statements and auditors' reports displays no enhancement relative to a model including only auditors' reports. Our model demonstrates a direct improvement over existing state-of-the-art models.

     
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    Volltext (kostenfrei)
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    Volltext (kostenfrei)
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/202870
    Schriftenreihe: Working paper / Danmarks Nationalbank ; no. 130
    Umfang: 1 Online-Ressource (circa 25 Seiten), Illustrationen