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Displaying results 1 to 5 of 5.

  1. Asymmetric models for realized covariances
    Author: Bauwens, Luc; Dzuverovic, Emilija; Hafner, Christian M.
    Published: [2024]
    Publisher:  CORE, Louvain-la-Neuve

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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 203
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    No inter-library loan
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 2078.1/292375
    Series: LIDAM discussion paper CORE ; 2024, 24
    Subjects: High frequency data; asymmetric volatility; realized covariance; conditional autoregressive Wishart model
    Scope: 1 Online-Ressource (circa 60 Seiten), Illustrationen
  2. Realized Copula
    Author: Fengler, Matthias R.; Okhrin, Ostap
    Published: 2012
    Publisher:  Humboldt-Universität zu Berlin, Berlin

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    Subjects: Kapitalertrag; Kopula <Mathematik>; Zeitreihenanalyse; Varianzanalyse; Theorie
    Other subjects: (stw)Kapitaleinkommen; (stw)Multivariate Verteilung; (stw)Zeitreihenanalyse; (stw)Varianzanalyse; (stw)Theorie; realized variance; realized covariance; realized copula; multivariate dependence; Arbeitspapier; Graue Literatur
    Scope: Online-Ressource
    Notes:

    In: Sonderforschungsbereich 649: Ökonomisches Risiko, Band 2012, Ausgabe 34, 2012
  3. The impact of jumps and leverage in forecasting co-volatility
    Author: Asai, Manabu; McAleer, Michael
    Published: 2015
    Publisher:  Tinbergen Inst., Rotterdam [u.a.]

    The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the jump-robust two time scale covariance estimator of Boudt and Zhang (2013)such that the estimated matrix is positive definite. Using... more

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 432 (2015,18)
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    The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the jump-robust two time scale covariance estimator of Boudt and Zhang (2013)such that the estimated matrix is positive definite. Using this approach we can disentangle the estimates of the integrated co-volatility matrix and jump variations from the quadratic covariation matrix. Empirical results for three stocks traded on the New York Stock Exchange indicate that the co-jumps of two assets have a significant impact on future co-volatility, but that the impact is negligible for forecasting weekly and monthly horizons.

     
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    Content information
    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/107881
    Series: Array ; 2015-018
    Subjects: co-volatility; forecasting; jump; leverage effects; realized covariance; threshold
    Scope: Online-Ressource (20 S.), graph. Darst.
  4. Estimation and forecasting of large realized covariance matrices and portfolio choice
    Author: Callot, Laurent; Kock, Anders Bredahl; Medeiros, Marcelo C.
    Published: 2014
    Publisher:  Tinbergen Inst., Rotterdam [u.a.]

    In this paper we consider modeling and forecasting of large realized covariance matrices by penalized vector autoregressive models. We propose using Lasso-type estimators to reduce the dimensionality to a manageable one and provide strong theoretical... more

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 432 (2014,147)
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    In this paper we consider modeling and forecasting of large realized covariance matrices by penalized vector autoregressive models. We propose using Lasso-type estimators to reduce the dimensionality to a manageable one and provide strong theoretical performance guarantees on the forecast capability of our procedure. To be precise, we show that we can forecast future realized covariance matrices almost as precisely as if we had known the true driving dynamics of these in advance. We next investigate the sources of these driving dynamics for the realized covariance matrices of the 30 Dow Jones stocks and find that these dynamics are not stable as the data is aggregated from the daily to the weekly and monthly frequency. The theoretical performance guarantees on our forecasts are illustrated on the Dow Jones index. In particular, we can beat our benchmark by a wide margin at the longer forecast horizons. Finally, we investigate the economic value of our forecasts in a portfolio selection exercise and find that in certain cases an investor is willing to pay a considerable amount in order get access to our forecasts.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/107858
    Series: Array ; 2014-147
    Subjects: realized covariance; vector autoregression; shrinkage; Lasso; forecasting; portfolio allocation
    Scope: Online-Ressource (32 S.), graph. Darst.
  5. Forecasting realized (co)variances with a block structure Wishart autoregressive model
    Author: Bonato, Matteo; Caporin, Massimiliano; Ranaldo, Angelo
    Published: 2012
    Publisher:  School of Finance, Univ. of, St. Gallen

    The increased availability of high-frequency data provides new tools for forecasting of variances and covariances between assets. However, recent realized (co)variance models may suffer from a 'curse of dimensionality' problem similar to that of... more

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    Verlag (kostenfrei)
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    Verlag (kostenfrei)

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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Location:
    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 314 (2012,11)
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    The increased availability of high-frequency data provides new tools for forecasting of variances and covariances between assets. However, recent realized (co)variance models may suffer from a 'curse of dimensionality' problem similar to that of multivariate GARCH specifications. As a result, they need strong parameter restrictions, in order to avoid non-interpretability of model coefficients, as in the matrix and log exponential representations. Among the proposed models, the Wishart autoregressive model introduced by Gourieroux et al. (2005) analyzes the realized covariance matrices without any restriction on the parameters while maintaining coefficient interpretability. Indeed, the model, under mild stationarity conditions, provides positive definite forecasts for the realized covariance matrices. Unfortunately, it is still not feasible for large asset cross-section dimensions. In this paper we propose a restricted parametrization of the Wishart Autoregressive model which is feasible even with a large cross-section of assets. In particular, we assume that the asset variances-covariances have no or limited spillover and that their dynamic is sector-specific. In addition, we propose a Wishart-based generalization of the HAR model of Corsi (2004). We present an empirical application based on variance forecasting and risk evaluation of a portfolio of two US treasury bills and two exchange rates. We compare our restricted specifications with the traditional WAR parameterizations. Our results show that the restrictions may be supported by the data and that the risk evaluations of the models are extremely close. This confirms that our model can be safely used in a large cross-sectional dimension given that it provides results similar to fully parametrized specifications

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    Edition: Current Draft: November 2008
    Series: Working papers on finance ; 2012,11
    Subjects: realized covariance; WAR; HAR; multivariate volatility forecasts
    Scope: Online-Ressource (PDF-Datei: 29 S.), graph. Darst.