Publications

Authors:

Buccheri, Giuseppe; Mboussa Anga, Gael

Title:

High-dimensional Realized Covariance Estimation: a Parametric Approach

Year:

2022

Type of item:

Articolo in Rivista

Tipologia ANVUR:

Articolo su rivista

Language:

Inglese

Referee:

No

Name of journal:

QUANTITATIVE FINANCE

ISSN of journal:

1469-7688

Page numbers:

1-16

Keyword:

Realized covariance; Risk management; High-dimensions; Epps effect

Short description of contents:

We introduce a parametric dynamic factor specification for high-frequency financial data that simplifies considerably the estimation of the realized covariance matrix in high dimensions. The estimation method is tested in an empirical setting that emphasizes the effect of the curse of dimensionality. Compared to standard parametric approaches, our factor specification is computationally less demanding and provides statistically indistinguishable performances in standard risk management applications. The method is also assessed on Monte-Carlo simulations under several forms of misspecification.

Product ID:

129337

Handle IRIS:

11562/1053251

Last Modified:

November 9, 2024

Bibliographic citation:

Buccheri, Giuseppe; Mboussa Anga, Gael, High-dimensional Realized Covariance Estimation: a Parametric Approach «QUANTITATIVE FINANCE» , 2022 , pp. 1-16

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