Pubblicazioni

High-dimensional Realized Covariance Estimation: a Parametric Approach  (2022)

Autori:
Buccheri, Giuseppe; Mboussa Anga, Gael
Titolo:
High-dimensional Realized Covariance Estimation: a Parametric Approach
Anno:
2022
Tipologia prodotto:
Articolo in Rivista
Tipologia ANVUR:
Articolo su rivista
Lingua:
Inglese
Referee:
No
Nome rivista:
QUANTITATIVE FINANCE
ISSN Rivista:
1469-7688
Intervallo pagine:
1-16
Parole chiave:
Realized covariance; Risk management; High-dimensions; Epps effect
Breve descrizione dei contenuti:
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.
Id prodotto:
129337
Handle IRIS:
11562/1053251
ultima modifica:
9 novembre 2024
Citazione bibliografica:
Buccheri, Giuseppe; Mboussa Anga, Gael, High-dimensional Realized Covariance Estimation: a Parametric Approach «QUANTITATIVE FINANCE»2022pp. 1-16

Consulta la scheda completa presente nel repository istituzionale della Ricerca di Ateneo IRIS

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