Strategic Asset Allocation and the Role of Alternative Investments

• DOI: http://doi.org/10.1111/j.1468-036X.2012.00642.x
• Author: Denis Schweizer,Lars Helge Haß,Douglas Cumming
• Date: 01 June 2014
• Published date: 01 June 2014

European Financial Management, Vol. 20, No. 3, 2014, 521–547

doi: 10.1111/j.1468-036X.2012.00642.x

Strategic Asset Allocation and the Role

of Alternative Investments

Douglas Cumming

YorkUniversity – Schulich School of Business, 4700 Keele Street, Toronto, Ontario M3J 1P3,

Canada

E-mail: dcumming@schulich.yorku.ca.

Lars Helge Haß

Lancaster University Management School, Lancaster University,Lancaster, LA1 4YX, UK

E-mail: l.h.hass@lancaster.ac.uk.

Denis Schweizer

WHU – Otto Beisheim School of Management, Assistant Professor of Alternative Investments,

Burgplatz 2, 56179 Vallendar, Germany

E-mail: Denis.Schweizer@whu.edu.

Abstract

We introduce a framework for strategic asset allocation with alternative invest-

ments. Our framework uses a quantifiable risk preference parameter, λ, instead

of a utility function. We account for higher moments of the return distributions

and approximate best-fit distributions. Thus, we replace the empirical return

distributions with two normal distributions. We then use these in the strategic

asset allocation. Our framework yields better results than Markowitz’s framework.

Furthermore, our framework better manages regime switches that occur during

crises. To test the robustness of our results, we use a battery of robustness checks

and find stable results.

Keywords: alternative investments;higher moments;strategic asset allocation

JEL Classification: G2, G12, G31

We are very grateful to an anonymous referee for many helpful comments and to the editor

John Doukas for very useful suggestions. Moreover,the paper has benef itted from comments

by Greg N. Gregoriou, Dieter G. Kaiser, Harry M. Kat, Lutz Johanning, Christian Koziol,

Rainer Lauterbach, Michael McDonald, Mark Mietzner, Juliane Proelss, and Maximilian

Trossbach as well as the participants of the EFM Alternative Investments Conference

2011 (Toronto), International Business Research Conference (8th Annual Meeting, Dubai),

European Financial Management Association (17th Annual Meeting, Athena), Campus for

Finance 2009 (Vallendar), and Midwest Finance Association (58th Annual Meeting, Chicago)

for helpful comments and suggestions. All remaining errors are our own.

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2012 Blackwell Publishing Ltd

© 2012 John Wiley & Sons Ltd

Douglas Cumming, Lars Helge Haß and Denis Schweizer

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1. Introduction

Alternative investment funds, which exceeded US$9 trillion worldwide in 2009, have

become increasingly important for the portfolios of institutional investors. This paper

proposes a framework for strategic asset allocation that is able to incorporate the special

characteristics of alternative investments.

If investors want to build exposure to alternative investments, they must decide on

their strategic asset allocation. Because strategic asset allocation explains most of a

portfolio’s retur n variability, it is the major determinant of investment performance and

the most critical decision in the investment process (Hoernemann et al., 20051). Use of

an appropriate strategic asset model is even more important when alternativeinvestments

are considered.

Alternative investments typically suffer from data biases due to appraisal smoothing

and stale pricing. Furthermore, return distributions of alternative investments have

significantly higher moments (skewness and kurtosis) which the standard deviation

does not cover. Thus, every standard method for portfolio optimisation employing

alternative investments is likely to be inaccurate (see, e.g., Fung and Hsieh, 1997;

Fung and Hsieh, 2001; Martin, 2001; Brooks and Kat, 2002; Popova et al., 2003;

Agarwal and Naik, 2004; Jondeau and Rockinger, 2006). Furthermore, institutional

investorshave different objective functions than individual investors(Morton et al., 2006;

Cumming and Johan, 2006; Cumming et al., 2011; Groh and von Liechtenstein, 2011;

Nielsen, 2011).

Therefore, our framework corrects for data biases in the return time series of some

alternative investments (private equity and hedge funds). We use a mixture of normal

methods to replace the empirical return distributions, which often exhibit skewness

and positive excess kurtosis, with two normal distributions to approximate a best-fit

distribution. This approach ensures that the best-fit return distributions exhibit higher

moments close to their empirical pendants. We then use the best-fit distributions in the

optimisation procedure. To derivethe strategic asset allocation, we apply a goal function

to examine real investor preferences for risk aversion. Our investors’ objective function

maximises the probability of outperforming some benchmark return while minimising

the probability of underperforming another benchmark.

The previous literature on asset allocation with alternative investments focuses on the

effects of adding one alternative investment class to a traditional mixed-asset portfolio.

It associates the addition of hedge funds with positive effects on portfolio performance

(see, e.g., Amin and Kat, 2002; Lhabitant and Learned, 2002; Amin and Kat, 2003;

Gueyie and Amvella, 2006; Kooli, 2007). In addition, findings assign positive effects

for privateequity (see, e.g., Chen et al ., 2002; Schmidt, 2004; Ennis and Sebastian, 2005).

The literature also finds that real estate investment trusts (REITs) can increase portfolio

performance (see, e.g., National Association of Real Estate Investment Trusts, hereafter

NAREIT, 2002; Hudson-Wilson et al., 2004; Chen et al., 2005; Lee and Stevenson,

2005; Chiang and Ming-Long, 2007).

Huang and Zhong (2011) are a notable exception to this literature. Their work,which is

the most similar to ours, shows that commodities, REITs, and treasury inflation-protected

1The authors present an alternative to the often-cited studies of Brinson et al. (1986, 1991).

They use a slightly different framework and cover a longer time horizon. They also include

alternative assets and use synthetic portfolios.

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© 2012 John Wiley & Sons Ltd