This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities
This dissertation contains four essays that all share a common purpose: developing new methodologies...
The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due...
The increasing availability of high-quality transaction data across many financial assets, allow the...
This paper analyses multivariate high frequency financial data using realized covari-ation. We provi...
This paper analyses multivariate high frequency financial data using realised covariation. We provid...
This paper analyses multivariate high frequency financial data using realised covariation. We provid...
This article proposes a consistent and efficient estimator of the high-frequency covariance (quadrat...
The availability of financial data recorded on high-frequency level has inspired a research area whi...
In this paper we introduce a new method of forecasting covariance matrices of large dimensions by ex...
In this paper we introduce a new method of forecasting covariance matrices of large dimensions by ex...
In this paper we introduce a new method of forecasting covariance matrices of large dimensions by ex...
The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due...
The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due...
This dissertation contains four essays that all share a common purpose: developing new methodologies...
This paper proposes a new method for forecasting covariance matrices of financial returns. the model...
This dissertation contains four essays that all share a common purpose: developing new methodologies...
The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due...
The increasing availability of high-quality transaction data across many financial assets, allow the...
This paper analyses multivariate high frequency financial data using realized covari-ation. We provi...
This paper analyses multivariate high frequency financial data using realised covariation. We provid...
This paper analyses multivariate high frequency financial data using realised covariation. We provid...
This article proposes a consistent and efficient estimator of the high-frequency covariance (quadrat...
The availability of financial data recorded on high-frequency level has inspired a research area whi...
In this paper we introduce a new method of forecasting covariance matrices of large dimensions by ex...
In this paper we introduce a new method of forecasting covariance matrices of large dimensions by ex...
In this paper we introduce a new method of forecasting covariance matrices of large dimensions by ex...
The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due...
The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due...
This dissertation contains four essays that all share a common purpose: developing new methodologies...
This paper proposes a new method for forecasting covariance matrices of financial returns. the model...
This dissertation contains four essays that all share a common purpose: developing new methodologies...
The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due...
The increasing availability of high-quality transaction data across many financial assets, allow the...