On the robustness of the principal volatility components

Author(s)

Trucios, Carlos ^{[1, 2]} ; Hotta, Luiz K. ^[3] ; Valls Pereira, Pedro L. ^{[1, 2]}

Affiliation

^[1] FGV, Sao Paulo Sch Econ, Rua Itapeva, 474 Bela Vista, BR-01332000 Sao Paulo, SP - Brazil

^[2] FGV, Ctr Quantitat Studies Econ & Finance, Rua Itapeva, 286-10 Andar Bela Vista, BR-01332000 Sao Paulo, SP - Brazil

^[3] Univ Estadual Campinas, Dept Stat, Rua Sergio Buarque de Holanda, BR-13083859 Campinas, SP - Brazil

• Document type: Journal article
• Source: JOURNAL OF EMPIRICAL FINANCE; v. 52, p. 201-219, JUN 2019.
• Web of Science Citations: 1

Abstract

In this paper, we analyse the recent principal volatility components analysis procedure. The procedure overcomes several difficulties in modelling and forecasting the conditional covariance matrix in large dimensions arising from the curse of dimensionality. We show that outliers have a devastating effect on the construction of the principal volatility components and on the forecast of the conditional covariance matrix and consequently in economic and financial applications based on this forecast. We propose a robust procedure and analyse its finite sample properties by means of Monte Carlo experiments and also illustrate it using empirical data. The robust procedure outperforms the classical method in simulated and empirical data. (AU)

• FAPESP's process: 13/22930-0 - Price discovery in high-dimensional arbitrage portfolios
• Grantee: Pedro Luiz Valls Pereira
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 16/18599-4 - Modeling and forecasting volatility of high dimensional financial series
• Grantee: Carlos Cesar Trucios Maza
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 18/03012-3 - Robust dynamic dimension reduction techniques for volatilities
• Grantee: Carlos Cesar Trucios Maza
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor