[SFdS] Information du groupe BFA
WG Risk - June, 6th 2023 - Prof. Frédéric Vrins

Dear All,

We have the pleasure thanks to the support of the ESSEC IDS dpt, Institut des Actuaires, LabEx MME-DII, the group BFA (SFdS), to invite you to the seminar by:



Prof. Frédéric Vrins
President of the Louvain Finance research center, UCLouvain, Belgium


Date: Tuesday, June 06th at 12:30 pm (Paris) and 6:30 pm (Singapore)

Dual format: ESSEC Paris La Défense (CNIT), Room TBA
and via Zoom, please click here (Password/Code : 202300)


« Optimal Portfolio Diversification via Independent Component Analysis »

A natural approach to enhance portfolio diversification is to rely on factor-risk parity, which yields the portfolio whose risk is equally spread among a set of uncorrelated factors. The standard choice is to take the variance as risk measure, and the principal components (PCs) of asset returns as factors. Although PCs are unique and useful for dimension reduction, they are an arbitrary choice: any rotation of the PCs results in uncorrelated factors. This is problematic because we demonstrate that any portfolio is a factor-variance-parity portfolio for some rotation of the PCs. More importantly, choosing the PCs does not account for the higher moments of asset returns. To overcome these issues, we propose using the independent components (ICs) as factors, which are the rotation of the PCs that are maximally independent, and care about higher moments of asset returns. We demonstrate that using the IC-variance-parity portfolio helps to reduce the return kurtosis. We also show how to exploit the near independence of the ICs to parsimoniously estimate the factor-risk-parity portfolio based on value at risk. Finally, we empirically demonstrate that portfolios based on ICs outperform those based on PCs, and several state-of-the-art benchmarks.


Kind regards,
Jeremy Heng, Olga Klopp, Roberto Reno, and Marie Kratz
https://crear.essec.edu/crear-events/working-group-on-risk
and Riada Djebbar (Singapore Actuarial Society - ERM)

SFdS - Société Française de Statistique
©2024 SFdS