Network Diversification for a Robust Portfolio Allocation

32 Pages Posted: 4 May 2022

See all articles by Markus Jaeger

Markus Jaeger

Munich Reinsurance Company, Financial Solutions

Dimitri Marinelli

Munich Reinsurance Company, Financial Solutions; FinNet

Date Written: March 28, 2022

Abstract

Portfolio allocation strategies often seek risk budgeting and diversification by relying only on correlation matrices to model relationships between assets. Although this approach can capture, in normal times, most of the dependencies between asset prices, it faces several challenges in terms of noise resistance, capturing non-linear relations that can naturally appear in the market and extreme allocations in long-short portfolio strategies.

This paper presents novel network-based strategies that combine equal volatility allocation with network centrality measures to construct efficiently diversified portfolios and deliver stable strategies also suitable for long-short investments.

Networks can encode linear and non-linear relationships between asset prices. To encode several layers of information simultaneously multiplex networks - a particular form of a multilayer network - can be deployed. Associated centrality measures can agnostically account for each asset's (ir)relevance in diversifying the risks of the portfolios.

The results show that network-based portfolios can outperform several competing alternatives, maintaining a favourable risk characteristic.

Keywords: asset allocation, portfolio construction, graph theory, networks, multilayer networks, eigenvector centrality

JEL Classification: C15, G11, G15 ,G17, G0, G1, E44

Suggested Citation

Jaeger, Markus and Marinelli, Dimitri, Network Diversification for a Robust Portfolio Allocation (March 28, 2022). Available at SSRN: https://ssrn.com/abstract=4068889 or http://dx.doi.org/10.2139/ssrn.4068889

Markus Jaeger

Munich Reinsurance Company, Financial Solutions ( email )

Königinstr. 107
Munich, 80802
Germany

Dimitri Marinelli (Contact Author)

Munich Reinsurance Company, Financial Solutions

Königinstr. 107
Munich, 80802
Germany

FinNet ( email )

Frankfurt am Main, DE

HOME PAGE: http://www.financial-networks.eu

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