Optimal Granularity for Portfolio Choice

53 Pages Posted: 25 Apr 2016 Last revised: 11 Jan 2019

See all articles by Nicole Branger

Nicole Branger

University of Muenster - Finance Center Muenster

Katarina Lucivjanska

University of Pavol Jozef Šafárik in Kosice

Alex Weissensteiner

Free University of Bolzano Bozen

Date Written: January 9, 2019

Abstract

Many optimization-based portfolio rules fail to beat the simple 1/N rule out-of-sample because of parameter uncertainty. In this paper we suggest a grouping strategy in which we first form groups of equally weighted stocks and then optimize over the resulting groups only. This strategy aims at balancing the trade-off between the benefits from optimization and the losses from estimation risk. We rely on Monte-Carlo simulations to illustrate the performance of the strategy, and we derive the optimal group size for a simplified setup. Furthermore, we show that estimation risk also has an impact via the criterion by which the assets are sorted into groups (like the expected excess returns or betas), but does not negate the grouping approach. We relate our work to linear asset pricing models, and we conduct out of sample back-tests in order to confirm the validity of our grouping strategy empirically.

Keywords: mean-variance optimization, the 1/N rule, parameter uncertainty, optimal portfolio granularity

JEL Classification: G1, G11

Suggested Citation

Branger, Nicole and Lucivjanska, Katarina and Weissensteiner, Alex, Optimal Granularity for Portfolio Choice (January 9, 2019). Available at SSRN: https://ssrn.com/abstract=2769736 or http://dx.doi.org/10.2139/ssrn.2769736

Nicole Branger

University of Muenster - Finance Center Muenster ( email )

Universitatsstr. 14-16
Muenster, 48143
Germany
+49 251 83 29779 (Phone)
+49 251 83 22867 (Fax)

HOME PAGE: http://www.wiwi.uni-muenster.de/fcm/fcm/das-finance-center/details.php?weobjectID=162

Katarina Lucivjanska (Contact Author)

University of Pavol Jozef Šafárik in Kosice ( email )

Šrobárova 2
Košice, 041 32
Slovakia

Alex Weissensteiner

Free University of Bolzano Bozen ( email )

Universitätsplatz 1
Bolzano, 39100
+39 0471 013496 (Phone)

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