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A long-term product?

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If we focus only on returns and covariances over a one-year investment horizon, we might conclude that commodities are not suitable for investment portfolios. However, over longer investment horizons, especially when using expected returns and maintaining historical serial dependencies, the efficiency of commodities increases dramatically.

We explain how allocations to commodities change over an investment horizon, particularly when inflation is taken into account.Our analysis suggests that investment professionals may need to take a more nuanced view of certain investments, particularly real assets like commodities, when constructing their portfolios.

This is the third installment in a series on the CFA Institute Research Foundation. paperFirst, we demonstrated the existence of serial correlation across asset classes historically, and then we discussed how the risk of stocks changes depending on the investment horizon.

Historical inefficiency of goods

Real assets such as commodities are often considered inefficient within a larger opportunity set of choices and therefore are rarely (or never) allocated to in common portfolio optimization routines such as mean-variance optimization (MVO). The historical inefficiency of commodities is documented in Figure 1, which contains historical annual returns for US cash, US bonds, US stocks and commodities from 1870 to 2023. Primary returns for US cash, US bonds and US stocks were taken from the Jordà-Schularick-Taylor (JST) macro-historical database from 1872 (the earliest year for which a complete dataset is available) to 2020 (the latest year available). For returns beyond that, we used the Ibbotson SBBI series.

The commodity return series uses Bank of Canada returns. Commodity Price Index (BCPI) from 1872 to 1969, and S&P GSCI Index From 1970 to 2023. BCPI The GSCI is a chained Fisher Price index of spot or US dollar traded prices of 26 commodities produced in Canada and sold on global markets. The GSCI is the world’s first major investment commodity index, broad-based, production-weighted and represents the beta of global commodity markets.

We chose the GSCI because of its long history, its similar composition to the BCPI, and the availability of several publicly traded products that can loosely track its performance, including the iShares exchange-traded fund (ETF). G.S.G.S.G.was launched on July 10, 2006. The primary reasons for using two commodity index proxies are data availability (e.g., returns going back to 1872) and familiarity. The results of the analysis should be viewed with these limitations in mind.

Figure 1. Historical standard deviation and geometric returns for asset classes: 1872-2023.

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Sources: Jordà-Schularick-Taylor (JST) macro historical database. Bank of Canada. Morningstar Direct. Authors’ calculations.

Commodities appear to be highly inefficient when compared to notes, bonds, and stocks. For example, commodities are less profitable and significantly more risky than notes and bonds. On the other hand, commodities have roughly the same annual standard deviation as stocks, but are about 600 basis points (bps) less profitable. Based on these values ​​alone, most optimization frameworks would allocate less to commodities.

However, this view does not take into account the long-term benefits of holding commodities, especially during periods of high inflation.Exhibit 2 contains information on the average returns on bills, bonds, stocks, and commodities in various inflationary environments.

Figure 2. Average asset class returns in different inflation environments: 1872-2023.

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Source: Jordà-Schularick-Taylor (JST) macro historical database. Bank of Canada. Morningstar Direct. Authors’ calculations. Data as of 12/31/2023..

We see that while commodities have poor returns when inflation is low, they perform significantly better when inflation is high.

As the investment horizon increases, the correlation between commodities and inflation increases noticeably, from about 0.2 over one year to 0.6 over ten years. In contrast, the correlation between stocks and inflation is only about -0.1 over one year and 0.2 over ten years. In other words, focusing on the long-term benefits of owning commodities and explicitly taking inflation into account can dramatically change the perceived efficiency of a portfolio optimization routine.

Listen to my conversation with Mike Wahlberg, CFA:

Allocation to products

Inflation can be explicitly considered in certain types of optimization, such as “surplus” or debt-relative optimization, but one potential problem with these models is that changes in the prices of goods and services do not necessarily move in sync with changes in financial markets. Lagged effects can result. For example, while financial markets can experience sudden value changes, inflation tends to have a more latent effect, meaning changes appear with a lag and can take years to appear. Focusing on the correlation (or covariance) of a particular asset class, such as stocks, with inflation over a period of one year (e.g., a calendar year) can mask potential long-term benefits.

To determine how the optimal product allocation varies with investment horizon, we performed annual portfolio optimization for investment horizons ranging from 1 to 10 years. The optimal allocation was determined using constant relative risk aversion (CRRA), which adjusts the cumulative growth of assets for risk over a given investment horizon.

Based on the target risk aversion level, optimal allocations were determined corresponding to equity allocations in 5% increments from 5% to 100%. Four asset classes were included in the portfolio optimization: bills, bonds, stocks, and commodities. Figure 3 contains the optimal allocation to commodities in each scenario considered.

Figure 3. Optimal commodity allocations by wealth definition, equity risk target, and investment horizon: 1872-2023.

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When wealth was defined in nominal returns, the allocation to commodities remained near zero for almost all equity allocation targets (Panel A). On the other hand, when wealth was defined in real terms (i.e. including inflation), the allocation turned out to be relatively significant over longer investment horizons (Panel B). This is especially true for investors targeting a moderately conservative portfolio (e.g. around 40% equity allocation), where the optimal allocation to commodities is around 20%. In other words, the perceived historical benefits of an allocation to commodities vary significantly depending on the definition of wealth (nominal vs. real) and the assumed investment horizon (e.g. moving from 1 year to 10 years).

Future returns for commodities are less pessimistic than their long-term historical averages. For example, commodities have underperformed equities by about 600 basis points on a risk-adjusted basis, but PGIM Quantitative Solutions’ fourth-quarter 2023 capital market assumptions and Horizon Actuarial Research 42 investment managers (focusing on 10-year returns)

We reran the portfolio optimization using the same historical time series, but centered the historical returns to match the expected returns (3.6%, 5.4%, 8.4%, 6.1%, and 2.5%, respectively) and standard deviations (2.0%, 5.6%, 15.3%, 14.7%, and 2.0%, respectively) of cash, bonds, stocks, commodities, and inflation.As shown in Figure 4, the optimal allocation to commodities increased significantly, regardless of whether wealth was defined in nominal or real values.

Figure 4. Optimal allocation to commodities by asset definition, equity risk objective and investment horizon: expected return.

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When focusing on nominal assets, the optimal allocation to commodities is around 10%, regardless of an investor’s equity risk objective or investment horizon, but when focusing on real assets, it is closer to 20% or more. These results suggest that the potential benefits of an allocation to commodities are significantly higher when comparing expected and historical returns.

Looking beyond one-year returns and covariance

When considering the risk of an asset, it is important to recognize that focusing only on returns and covariance over a one-year investment horizon does not necessarily capture the full potential benefits. Asset classes such as commodities have historically offered significant diversification benefits for long-term investors concerned about inflation. It is essential that investment professionals are aware of these effects and their potential impact on optimal portfolios.

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