Arbeitspapier
Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns
We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance matrix dynamics are formulated as a numerically efficient matrix recursion that ensures positive definiteness under simple parameter constraints. Using intraday stock data over the period 2001-2012, we construct realized covariance kernels and show that the new fractionally integrated model statistically and economically outperforms recent alternatives such as the Multivariate HEAVY model and the 2006 “long-memory” version of the Riskmetrics model.
- Language
-
Englisch
- Bibliographic citation
-
Series: Tinbergen Institute Discussion Paper ; No. 16-069/IV
- Classification
-
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Financial Econometrics
- Subject
-
multivariate volatility
fractional integration
realized covariance matrices
heavy tails
matrix-F distribution
score dynamics
- Event
-
Geistige Schöpfung
- (who)
-
Lucas, André
Opschoor, Anne
- Event
-
Veröffentlichung
- (who)
-
Tinbergen Institute
- (where)
-
Amsterdam and Rotterdam
- (when)
-
2016
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Lucas, André
- Opschoor, Anne
- Tinbergen Institute
Time of origin
- 2016
Other Objects (12)
New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels
Time-varying tail behavior for realized kernels
Modelling and Forecasting of Realized Covariance Matrices
Reflection Negative Kernels and Fractional Brownian Motion
Singular conditional autoregressive Wishart model for realized covariance matrices
A blocking and regularization approach to high dimensional realized covariance estimation
A blocking and regularization approach to high dimensional realized covariance estimation
Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice
A blocking and regularization approach to high dimensional realized covariance estimation
A blocking and regularization approach to high dimensional realized covariance estimation
Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors
The contribution of realized covariance models to the economic value of volatility timing
New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels
Time-varying tail behavior for realized kernels
Modelling and Forecasting of Realized Covariance Matrices
Reflection Negative Kernels and Fractional Brownian Motion
Singular conditional autoregressive Wishart model for realized covariance matrices
A blocking and regularization approach to high dimensional realized covariance estimation
A blocking and regularization approach to high dimensional realized covariance estimation
Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice
A blocking and regularization approach to high dimensional realized covariance estimation
A blocking and regularization approach to high dimensional realized covariance estimation
Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors
The contribution of realized covariance models to the economic value of volatility timing
New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels
Time-varying tail behavior for realized kernels
Modelling and Forecasting of Realized Covariance Matrices
Reflection Negative Kernels and Fractional Brownian Motion
Singular conditional autoregressive Wishart model for realized covariance matrices
A blocking and regularization approach to high dimensional realized covariance estimation
A blocking and regularization approach to high dimensional realized covariance estimation
Estimation and Forecasting of Large Realized Covariance Matrices and Portfolio Choice
A blocking and regularization approach to high dimensional realized covariance estimation
A blocking and regularization approach to high dimensional realized covariance estimation
Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors