Semiparametric Portfolios: Improving Portfolio Performance by Exploiting Non-Linearities in Firm Characteristics

46 Pages Posted: 23 Apr 2021 Last revised: 6 Jul 2021

See all articles by João Caldeira

João Caldeira

Universidade Federal de Santa Catarina & CNPq

Andre A. P. Santos

University of Edinburgh - Edinburgh Business School; Universidade Federal de Santa Catarina (UFSC) - Department of Economics

Hudson Torrent

Universidade Federal do Rio Grande do Sul (UFRGS) - Department of Statistics

Date Written: July 3, 2021

Abstract

We present a semiparametric portfolio optimization method in which portfolio weights are parameterized as a non-linear function of firm characteristics. This approach generalizes the linear parametric portfolio policy of Brandt et al. (2009) and can be applied to high-dimensional problems at a relatively low computational cost. An empirical implementation exploiting the size, value, and momentum anomalies in the universe of CRSP stocks reveals that non-linearities as well as interaction effects are both important and complementary for the portfolio construction problem. Moreover, an out-of-sample evaluation indicates that the semiparametric strategies perform well in terms of returns, risk, and risk-adjusted returns both in the absence and in the presence of transaction costs. Our evidence suggests that allowing for a more flexible relation between portfolio weights and firm characteristics can provide a more accurate description of the empirical patterns seen in data.

Keywords: Penalized splines; Portfolio turnover; Risk-adjusted returns; Sharpe ratios.

JEL Classification: B26, C58, G11

Suggested Citation

Caldeira, João and A. P. Santos, Andre and Torrent, Hudson, Semiparametric Portfolios: Improving Portfolio Performance by Exploiting Non-Linearities in Firm Characteristics (July 3, 2021). Available at SSRN: https://ssrn.com/abstract=3830435 or http://dx.doi.org/10.2139/ssrn.3830435

João Caldeira

Universidade Federal de Santa Catarina & CNPq ( email )

R. Eng. Agronômico Andrei Cristian Ferreira, s/n
Florianópolis, SC Rio Grande do Sul 90480-004
Brazil

Andre A. P. Santos (Contact Author)

University of Edinburgh - Edinburgh Business School ( email )

29 Buccleuch Pl
Edinburgh, Scotland EH8 9JS
United Kingdom

Universidade Federal de Santa Catarina (UFSC) - Department of Economics ( email )

PO Box 476
Florianopolis, SC 88010-970
Brazil

HOME PAGE: http://sites.google.com/site/andreportela

Hudson Torrent

Universidade Federal do Rio Grande do Sul (UFRGS) - Department of Statistics ( email )

Instituto de Matemática - UFRGS
Av. Bento Gonçalves, 9500 - Prédio 43-111 - Agrono
Porto Alegre, RS 91509-900
Brazil

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