Macro Factor Mimicking Portfolios

34 Pages Posted: 2 May 2019

Date Written: January 31, 2019

Abstract

The estimation of risk factors and their replication through mimicking portfolios are of critical importance for academics and practitioners in finance. We propose a general optimization framework to construct macro factor mimicking portfolios that encompasses existing portfolio mimicking approaches such as two-pass cross-sectional regression models (Fama and MacBeth, 1973) and maximal correlation approaches (Huberman et al., 1987, Lamont, 2001). We also incorporate potential empirical estimation improvements through machine learning methodologies. We provide an application to the construction of tradable portfolios mimicking three global macro factors such as growth, inflation surprises, and financial stress indicators.

Keywords: factor investing, mimicking portfolios, portfolio optimization, macro risk management, machine learning

JEL Classification: G11, D81, C60

Suggested Citation

Jurczenko, Emmanuel and Teiletche, Jerome, Macro Factor Mimicking Portfolios (January 31, 2019). Available at SSRN: https://ssrn.com/abstract=3363598 or http://dx.doi.org/10.2139/ssrn.3363598

Emmanuel Jurczenko

Glion Institute of Higher Education ( email )

Route de Glion 111
Montreux, 1823
Switzerland

Jerome Teiletche (Contact Author)

Unigestion ( email )

8c, avenue de Champel CP 387
CP 387
Genève 12, CH 1211
Switzerland

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