بازده بلند مدت زیرساخت های ایالات متحده و انتخاب پرتفولیو

Our understanding of the long-term return behavior and portfolio characteristics of public infrastructure investments is limited by a relatively short history of empirical data. We re-construct U.S. listed infrastructure index returns by mapping their monthly performance to received systematic and industry risk factors from 1927 through 2010. Our findings reveal that the infrastructure returns in recent years may understate the tail-risk that investors could experience over the long-term, however, this tail-risk is commensurate with holding a broad portfolio of U.S. stocks. For mean-variance and mean-CVaR investors, we report the benefits of holding public infrastructure assets in investment portfolios.

The OECD (2007) has reported a U.S.$1.8 trillion per annum projected requirement for global infrastructure spending through to 2030, yet there is a paucity of research on the portfolio benefits of these types of investments. From a United States perspective, the Department of the U.S. Treasury (2012) is allocating $476 billion in the coming years towards the development of new infrastructure initiatives which require both public and private investment. To better understand the characteristics of infrastructure, it is imperative that investors (such as pension funds) understand the long-term reward/risk behavior of infrastructure and its portfolio diversification characteristics. Furthermore, pension plan sponsors have a fiduciary duty to understand the role of infrastructure investment in a portfolio context. For most investments, this is achieved by evaluating the indexes that track the performance of a particular asset class. The challenge with infrastructure is the limited number of indexes (and associated history) with which to evaluate this asset class over the long-term. The challenge becomes more formidable in an asset allocation framework, as portfolio selection models require a large number of data observations that are simply not available for infrastructure investments. Our study addresses these empirical challenges by investigating five U.S. listed infrastructure indexes. This research employs the methodology that follows Agarwal and Naik (2004) by utilizing the Fama and French (1993)/Carhart (1997) asset pricing models as the foundations to construct monthly returns for these U.S. listed infrastructure indexes over the long-term. By mapping U.S. infrastructure returns onto the Fama and French (1993)/Carhart (1997) risk factors and industry returns, we reconstruct U.S. listed infrastructure index monthly returns from 1927 to 2010. We acknowledge that any approach to the backfilling of data has limitations. This study takes the approach of Agarwal and Naik (2004), a methodology that allows researchers to construct historical infrastructure index returns based on the assumption that short-term empirical returns modeled on systematic risk factors and industry returns are a good proxy of their behavior over the long-term. From an asset pricing perspective, this study shows that a significant proportion of the variation of U.S. listed infrastructure index returns can be explained by systematic risk factors and industry returns. We use a five-factor asset pricing model which shows that approximately half of the total variation of returns can be explained by the four Carhart (1997) risk factors while the remaining variation of returns can be explained by the U.S. utilities industry returns orthogonalized to the Fama and French (1993)/Carhart (1997) factors. The asset pricing analysis in this study suggests that U.S. listed infrastructure index returns do not exhibit statistically significant excess returns. We model these indexes from 1927 through 2010 and find that, in general, U.S. listed infrastructure exhibit similar mean returns, correlations and tail-risks as U.S. stocks. Furthermore, we show that the empirical tail-risks from recent empirical infrastructure returns understate their VaR and CVaR estimates over the long-term, however, their levels of tail-risk is commensurate with the systematic risk from U.S. stocks. This commonality between listed infrastructure and broad U.S. stocks is an interesting finding given that infrastructure indexes are heavily concentrated in sufficiently different industries including oil/gas storage and transportation, electricity and other broad based utilities. The risk estimates calculated in this study perhaps challenge the perception of infrastructure as a low-risk and steady-return investment. Our findings support the notion that U.S. listed infrastructure is perhaps not a separate asset class, but rather, a sub-set of the wider universe of U.S. stocks. From an investors’ perspective, we employ these long-term U.S. infrastructure returns to the problem of portfolio selection. We are motivated here to evaluate the long-term portfolio diversification benefits of publicly listed infrastructure. In a post Global Financial Crisis (GFC) world, tail-risk analysis is important within the Markowitz, 1952 and Markowitz, 1959 Mean-Variance framework. The estimation of tail-risk motivates us to examine these investments in the Mean-Variance (MV) and Mean-Conditional-Value-at-Risk (M-CVaR) portfolio selection settings. In general, we find that most infrastructure indexes exhibit characteristics that can improve the risk/reward profile of an investment portfolio. While the various infrastructure indexes exhibit common risk factors, their desirability in a portfolio context is a function of the mean returns, volatilities, correlations and tail-risks of each index. This study is structured as follows. Section 2 reviews the relevant literature, Section 3 describes the data, and Section 4 outlines the methodology employed to evaluate listed infrastructure returns over the long-term. Section 5 presents the empirical analysis and Section 6 offers concluding remarks.

This research addresses the paucity of knowledge relating to U.S. listed infrastructure index returns, asset pricing and optimal portfolio choice. This study employed the procedure from Agarwal and Naik (2004) to model infrastructure returns over the long-term. A five-factor asset pricing model was employed to construct long-term returns from 1927 to 2010. Asset pricing theory informs us that the Fama and French (1993)/Carhart (1997) four-factor model may explain asset returns and this study revealed that this framework with the inclusion of the U.S. Utilities industry returns can generally explain the variation of U.S. listed infrastructure returns over the long-term. With this new information, this study estimated higher levels of risk in infrastructure index investments over the long-term than those experienced in the recent past. The contribution of this study shows that U.S. listed infrastructure index returns exhibit the characteristics of low/moderate market beta and a strong positive relationship with the U.S. utilities industry even though each index possesses differences in design methodology and industry sector concentration. Another major finding of this study is that U.S. listed infrastructure is simply a sub-sector of U.S. stocks. This finding stems from the evidence which demonstrates that the mean returns, correlations and tail-risks of U.S. listed infrastructure indexes and broad U.S. stocks are sufficiently similar, therefore, these investments cannot be considered as a separate asset class. MPT informs us that an asset with a high return, combined with a low standard deviation and a correlation of less than one is desirable in a mean-variance analysis. This study found that the correlation coefficients between all risky assets were positive. Unique to this study, mean-variance portfolios were constructed by employing both long-term and short-term U.S. listed infrastructure index returns. It was established that most infrastructure indexes dominate MV due to the marginally higher return and lower risk than broad U.S. stocks. Furthermore, M-CVaR (99%) portfolios preferred listed infrastructure over U.S. stocks due to their relatively marginally smaller tail-risk. Whilst these infrastructure index returns report common risk factors, they exhibit sufficient differences in mean returns and tail-risks to cause differences in optimal portfolio choice. Pension funds must recognize that the optimal asset allocation to U.S. listed infrastructure index returns is not readily transferable from one index to another due to the similarities in their common risk factors, but rather, their differences in expected return and tail-risk remain the variables that ultimately drive optimal portfolio decision making.