Arbeitspapier

Singular conditional autoregressive Wishart model for realized covariance matrices

Realized covariance matrices are often constructed under the assumption that richness of intra-day return data is greater than the portfolio size, resulting in non-singular matrix measures. However, when for example the portfolio size is large, assets suffer from illiquidity issues, or market microstructure noise deters sampling on very high frequencies, this relation is not guaranteed. Under these common conditions, realized covariance matrices may obtain as singular by construction. Motivated by this situation, we introduce the Singular Conditional Autoregressive Wishart (SCAW) model to capture the temporal dynamics of time series of singular realized covariance matrices, extending the rich literature on econometric Wishart time series models to the singular case. This model is furthermore developed by covariance targeting adapted to matrices and a sectorwise BEKK-specification, allowing excellent scalability to large and extremely large portfolio sizes. Finally, the model is estimated to a 20 year long time series containing 50 stocks, and evaluated using out-ofsample forecast accuracy. It outperforms the benchmark Multivariate GARCH model with high statistical significance, and the sectorwise specification outperforms the baseline model, while using much fewer parameters.

Sprache
Englisch

Erschienen in
Series: Working Paper ; No. 1/2021

Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Large Data Sets: Modeling and Analysis
Financial Econometrics
Financial Forecasting and Simulation
Thema
Covariance targeting
High-dimensional data
Realized covariance matrix
Stock co-volatility
Time series matrix-variate model

Ereignis
Geistige Schöpfung
(wer)
Alfelt, Gustav
Bodnar, Taras
Javed, Farrukh
Tyrcha, Joanna
Ereignis
Veröffentlichung
(wer)
Örebro University School of Business
(wo)
Örebro
(wann)
2020

Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Alfelt, Gustav
  • Bodnar, Taras
  • Javed, Farrukh
  • Tyrcha, Joanna
  • Örebro University School of Business

Entstanden

  • 2020

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