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Deriving estimators from historical data is common practice in applied quantitative finance. The availability of ever larger data sets and easier access to statistical algorithms has also led to an increased usage of historical estimators. In this research note, we illustrate how to assess the...
Persistent link: https://www.econbiz.de/10014236566
This paper proposes a novel regularisation method for the estimation of large covariance matrices, which makes use of …
Persistent link: https://www.econbiz.de/10010361374
This paper proposes a regularisation method for the estimation of large covariance matrices that uses insights from the … it is easy to implement and does not require cross-validation. The MT estimator of the sample correlation matrix is shown …
Persistent link: https://www.econbiz.de/10011405221
into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity …
Persistent link: https://www.econbiz.de/10010411945
into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity …
Persistent link: https://www.econbiz.de/10010412428
Estimating the covariance between assets using high frequency data is challenging due to market microstructure effects and asynchronous trading. In this paper we develop a multivariate realised quasi maximum likelihood (QML) approach, carrying out inference as if the observations arise from an...
Persistent link: https://www.econbiz.de/10013008145
establish matching upper and lower bounds to show that the ARP estimation procedure is optimal. To estimate large integrated …
Persistent link: https://www.econbiz.de/10013236780
novel statistical methods have been introduced to address large volatility matrix estimation problems from a high … Huber loss function with a diverging threshold to develop a robust realized volatility estimation. We show that it has the … the proposed estimation methods …
Persistent link: https://www.econbiz.de/10012941604
exist in similar methods - it doesn’t require neither the estimation of the inverse covariance matrix of ⃗X nor the … estimation of the covariance matrix of ⃗N. -- dimension reduction ; non-Gaussian components ; NGCA …
Persistent link: https://www.econbiz.de/10008663366
distributions. For such cases we calculate general bounds for two association measures, Pearson's correlation coefficient and …
Persistent link: https://www.econbiz.de/10010339585