Associate Professor Robert Bianchi Griffith University

Associate Professor Robert Bianchi Griffith University

Stream 1: Project #2 Is Infrastructure an Asset Class? An Asset Pricing Approach Robert Bianchi and Michael Drew

Introduction OECD (2007) estimates a global infrastructure gap of U.S.$1,800 billion per year for many years. Infrastructure Australia (2013) estimates a domestic infrastructure gap of A$300 billion. Superannuation funds are developing a growing interest in infrastructure assets. Some academics and industry professionals believe that infrastructure is an asset class while others believe it is a subset of current asset classes that are already available. Research Question: Is Infrastructure an Asset Class?

Research Motivation Q: Is Infrastructure an Asset Class? This has implications for superannuation funds and their asset allocation decisions. Is infrastructure sufficiently different to stocks or bonds? Is infrastructure simply a sub-sector of stocks or bonds?

Related Literature Infrastructure is a logical grouping of assets that share similar characteristics - Idzorek and Armstrong (2009) Infrastructure are low-risk investments due to their regular income stream, high regulatory structure and low levels of market competition Newbery (2002), Rothballer and Kaserer (2012), Regan, Smith and Love (2011) Inderst (2010) takes a taxonomy approach and argues infrastructure is a sub-sector within current asset classes such as stocks, bonds, private equities and real estate.

Related Literature continued... Markowitz (1952, 1959) examines portfolios of securities. There is a paucity of literature which attempts to define an asset class. The alternative investments literature attempts to deal with the defining asset classes in the context of real estate, hedge funds and commodities. Examples are Greer (1997), Oberhofer (2001) and Mongars and Marchal-Dombrat (2006). Let s look at the alternative investment literature on how they define real estate, hedge funds and commodities as asset classes or otherwise.

Greer (1997) An asset class is a set of assets that bear some fundamental economic similarities to each other, and that have characteristics that make them distinct from other assets that are not part of that class. [p.86]. Greer (1997) employs correlation analysis as the primary method of evaluating and differentiating various asset classes.

Oberhofer (2001) Oberhofer (2001) examined whether hedge funds are an asset class or a sub-set of other assets. He concludes that hedge funds are unconventional investment strategies within existing asset classes. Oberhofer (2001) argues that an asset class must exhibit six characteristics: (i) (ii) Securities in the class must be similar. Returns must be highly correlated with each other. (iii) The asset class should represent a material fraction of the investment opportunity set. (iv) Price and composition data should be readily available. (v) It is possible to invest useful amounts in the asset class passively, at the quoted prices. (vi) All defined asset classes should sum to an approximation of the entire investment opportunity set.

Mongars and Marchal-Dombrat (2006) Mongars and Marchal-Dombrat (2006) argue that commodities constitute an asset class because they demonstrate the following three characteristics: (i) The asset exhibits the ability to outperform the risk-free rate. (ii) The asset reports low or negative correlation with other asset classes. (iii) It cannot be replicated with a simple linear combination of assets.

Merton (1973) The traditional academic/scientific approach is known as the Merton (1973) zero-intercept criterion. The zero-intercept criterion of Merton (1973) argues that the systematic risk factors of an asset are captured in a multifactor asset pricing model when two conditions are met: (i) When you identify the statistically significant independent variable(s), and (ii) You achieve an insignificant intercept term.

Asset Pricing Literature Single-factor Capital Asset Pricing Model (CAPM) from Sharpe (1964), Lintner (1965) and Mossi (1966). Market beta, size premium and value premium explain returns in the thee-factor Model from Fama and French (1992, 1993) Carhart (1997) four-factor model introduces momentum to the Fama- French three-factor model. Fama and French (2012) develop a global version of the Carhart (1997) model. Fama and French (1997) and Chou, Ko and Ho (2012) demonstrate that asset pricing models do not capture the variation of industry returns. Bianchi, Bornholt, Drew and Howard (2014) show that U.S. utilities industry returns are efficient at explaining U.S. listed infrastructure.

Methodology Our methodology follows the Merton (1973) zero-intercept criterion approach. Fama and French (2012) global four-factor model (ie international version of Carhart (1997)). R t - R f,t =a + b 1 (R m - R f )+ b 2 (SMB t )+ b 3 (HML t )+ b 4 (WML t )+e t Fama and French (2012) global four-factor model and world utilities orthogonal to other factors. R t - R f,t = a + b 1 (R m - R f )+ b 2 (SMB t )+ b 3 (HML t )+ b 4 (WML t )+...... + b 5 (UTIL t - R f,t )+e t

Data Seven MSCI world and regional infrastructure index returns from January 1999 to October 2014 (190 monthly observations.) We employ world infrastructure index returns to identify the systematic risks of infrastructure. We employ global and regional infrastructure indices because national infrastructure index returns are contaminated with country risk, idiosyncratic risk, low number of constituents in each national index and high asset specificity. We employ global risk factors (the independent variables), namely, World Stocks, SMB, HML, WML, World Utilities and World Bonds.

Table 1 Summary Statistics

Figure 1: Growth of $1,000 Invested in World Stocks and Infrastructure Indices

Preliminary Analysis - Correlations

4 Factor Model MSCI World Infrastructure

5 Factor Model MSCI World Infrastructure

4 Factor Model MSCI Europe Infrastructure

5 Factor Model MSCI Europe Infrastructure

4 Factor Model MSCI Asia-Pac Infrastructure

5 Factor Model MSCI Asia-Pac Infrastructure

5 Factor Model MSCI Australia Infrastructure

Conclusions Despite their unique characteristics, the behaviour of listed infrastructure returns and their excess returns can be explained by exposures to world stocks, world utilities, large-cap returns, growth returns or a combination of these four factors. The five-factor model can readily explain the variation of returns of the MSCI World Infrastructure Index and MSCI Europe Infrastructure Index. The MSCI Asia-Pacific Infrastructure Index exhibits exposure to a nonpriced risk factor that has yet to be identified (ie. it has no excess return). The Merton (1973) zero-intercept criterion suggests that the returns of global and European infrastructure index returns can be replicated with the linear combination of world stocks, world utility industry, large-cap returns and growth related returns. These findings suggest that listed infrastructure cannot be defined as a separate asset class.

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