Investors are constantly trying to prepare for the unexpected. Many would trade off the possibility for higher potential returns tomorrow for the certainty of lower returns today (within reason). Given the turbulent macroeconomic environment, investors have perhaps never been more uncertain of how their portfolio stands to perform. This article focuses on how to combat one of the countless uncertainties facing investors: unexpected inflation. While expected inflation is typically accounted for in the pricing of most assets, unexpected inflation by definition cannot be accounted for. Since the depths of the global recession, inflation has been steadily rising around the world. This is in part a result of action taken by policymakers to prevent deflation and stabilise output through quantitative easing and other measures aimed at injecting liquidity into the market. Many fear that these policies could ultimately lead to an inflationary spike. Facing the potential for such a scenario, many investors have sought to insulate their portfolios from the negative effects such an inflationary episode could have on their purchasing power.
Inflation risk stems from the uncertainty of future inflation rates. Unless an investor is stashing cash under their mattress, their purchasing power is generally protected against expected (current) inflation because it is priced into the current values of financial assets. However, terribly few instruments exist to hedge the risk of unexpected inflationary shocks. Historically, investors have allocated portions of their portfolios to real estate, gold, inflation-linked bonds, and commodities in an effort to preserve purchasing power in the event of an inflation shock. Given the empirical evidence available, broad-basket commodity allocations have historically been the most reliable hedge against unexpected inflation.
Unexpected inflation is usually defined in one of two ways: 1) the difference between the risk-free rate (usually the 90 day U.S. Treasury bill) and realised inflation in the same time period, or 2) the difference between realised inflation in one time period and realised inflation in the next period. For the purposes of this article, we use the latter methodology because we think the most recently realised rate of inflation is a purer proxy for inflation expectations in the next time period. Therefore, unexpected inflation is high in absolute terms when the inflation rate varies widely from one time period to the next. Given unexpected inflation, therefore, a good portfolio hedge will exhibit positive correlation with unexpected inflation.
As stated above, a suitable inflation hedging instrument will be positively correlated with unexpected inflation. Positive correlation implies that the hedging instrument and unexpected inflation move together in a linear fashion. Correlation is measured on a scale from -1 to 1 with positive 1 implying perfectly positive correlation. A high positive correlation signifies a strong positive linear relationship and indicates that an increase in unexpected inflation would coincide with an increase in the value of the hedging instrument. Since traditional asset classes, like equities and fixed income, are negatively correlated with unexpected inflation, an increase in unexpected inflation will accompany a decrease in the value of equity and fixed income securities, hence the need for an inflation hedge in a portfolio of stocks and bonds. In testing for correlation between unexpected inflation and the typical hedging instruments, we have chosen two broad commodity indices (S&P GSCI and DJ-UBS Commodity Index), the spot price of gold (London Fix Gold PM), a global REIT index (S&P Global REIT index), and an inflation-linked bond index (BarCap US Treasury TIPS Yld).
As evidenced by the data in the above table the broad-basket commodity indices (S&P GSCI and DJ-UBS Commodity Index) have historically demonstrated the highest positive correlation to unexpected inflation shocks as compared to other commonly cited inflation hedging instruments. The spot price of gold and REITs also had positive--albeit considerably lower--correlations to unexpected inflation.
In addition to examining an asset’s correlation to unexpected inflation, the diversifying investor will want to consider whether the hedging instrument correlates positively or negatively to other pieces of their existing portfolio. Including an instrument with low to negative correlations with traditional asset classes, like equities and fixed income, will tend to increase the risk-adjusted returns of the overall portfolio. To measure how our hedging instruments correlate to stocks and bonds, we chose two equity indices (MSCI World and STOXX Europe 600) and one bond index (BarCap Global Aggregate Bond).
The data in the table above highlight that each of these traditional inflation-hedging instruments demonstrate low to negative correlations with fixed income securities. Depending on the asset, correlations with equities range from negative (bonds) to moderate (S&P Global REIT). Commodities have historically had correlations near zero to equities, but these correlations have risen sharply in recent years. The trailing 12 month correlation between both commodity benchmarks S&P GSCI and DJ-UBSCI and both broad equity benchmarks, MSCI World and STOXX Europe 600, was near zero in July, 2005. However, at the end of July 2011, the trailing 12 month correlation had risen to 0.90 with respect to these benchmarks. While this increase may seem surprising, this phenomenon has actually been demonstrated in other previously difficult-to-reach asset classes, like REITS, and has been labelled trading commonality by James Xiong of Ibbotson Associates. Increased investor interest and capital inflows into historically inaccessible or illiquid markets--such as REITs or commodities--have in part led to these instruments’ progressively higher correlation with equity markets.
But correlation does not imply causation. Beyond examining mere correlation metrics, investors should be concerned with whether or not causal inferences can be made about the relationship between unexpected inflation and the hedging instrument. If a causal inference can be made, the claim that an allocation to that instrument will hedge inflationary shocks will be further substantiated, is not simply coincidence based on backward-looking data, and may have predictive power. We can attempt to determine a causal relationship by regressing the returns of each hedging instrument against current inflation rates and unexpected inflation. The goal of this exercise is to determine whether year over year fluctuations in inflation cause the returns for the hedging instrument to change, and whether this relationship is significant and reliable.
The third table illustrates the relationship between inflation rates and the returns of each of the traditional inflation-hedging vehicles. The coefficients indicate how a change in one of the variables would affect the returns for the associated vehicle. For example, looking at the S&P GSCI index, a 1% increase in unexpected inflation rates would result in a 6.55% increase over the index’s prior period returns. The strength of this relationship is determined by the t-statistic; in general, a t-statistic greater than 2 implies a strong relationship.
Looking at the S&P GSCI results in particular, the regression yields an economically and statistically significant result, namely that unexpected inflation has historically driven a portion of the index’s return. Furthermore, repeating this exercise for other broad-basket commodity indices yields the same result when sufficient data is available. Since the DJ-UBS Commodity index--in its current form--only has data track record going back to 1992, it is difficult to determine whether or not a statistically significant relationship is present. Of the remaining traditional inflation hedges, only gold has a statistically significant relationship (t-statistic greater than 2) with unexpected inflation, but it is not nearly as significant nor is the coefficient as large as it is in the case of the S&P GSCI. Comparatively, inflation-linked bonds have a statistically strong inverse relationship to unexpected inflation, while the performance of REITs exhibits little to no relationship with either inflation or unexpected inflation.
Based on the above data, a causal inference can be made about the relationship between the S&P GSCI and unexpected inflation. But be careful! These results should not be interpreted to mean that unexpected inflation is the sole driver of commodity performance, but rather, that unexpected inflation is one of several factors that contribute positively to the performance of commodity markets. Based on research conducted by Erb and Harvey (2006), changes in the rate of U.S. inflation accounted for roughly 43% of the variance of returns for the S&P GSCI from 1969 to 2003.
Commodities present an attractive option to the investor seeking to hedge against unexpected inflation. On the downside, commodities have become increasingly correlated with equities and, as such, appear to have lost some of their diversification potential. However, on the upside, commodities provide the clearest and most effective hedge against unexpected inflation as compared to other traditional inflation hedging instruments.
Investors have an abundance of choices when it comes to broad-basket commodity futures ETPs (exchange-traded products). The key differentiating factor amongst them will be index construction. Due to differences in index construction, the variety of broad-basket ETPs will not necessarily perform similarly. In considering differences of index construction, an investor will want to focus on these indices' sector exposure and rolling methodology. Historically, more evenly weighted (as measured by sector concentration) indices and those utilising “intelligent” rolling practices have generated superior performance and lower volatility relative to more concentrated indices that use more standard rolling practices.
All this said, here are a few broad basket commodity ETFs that may be worth considering as an inflation hedge:
ComStage ETF Commerzbank Commodity EW (read our analyst report on this fund here) tracks an equally weighted broad-basket commodity index and charges a TER of 0.30%. Due to the equal-weight methodology, the ComStage ETF has experienced significantly lower volatility compared to its peer group and has had higher correlation across a breadth of commodity sectors. Given the levels of correlation, the ComStage ETF probably replicates the experiences of the average consumer better than any of its peers.
db X-trackers DBLCI OY Balanced (read our analyst report on this fund here) has addressed the dynamic nature of the commodity futures curves by employing an optimum yield methodology, which seeks to generate maximum implied roll yield. On a historic basis, the index has outstripped its peer group in terms of absolute performance (~16% annualised since 2001). Surprisingly, the absolute return did not come at the expense of higher volatility in comparison to its peers. Moreover, despite a funded swap structure, db X-trackers’ ETFs are arguably the most insulated from counterparty risk exposure in the broad commodity ETP space. For this ETF, db X-trackers charges a TER of 0.55%, which seems more than reasonable given its solid track record and low counterparty risk exposure.
EasyETF S&P GSCI Capped Commodity 35/20 (read our analyst report on this fund here) uses a rule-based methodology to gain broad exposure to 24 commodities across the energy, agriculture, industrial metals, and precious metals sectors. This ETF tracks a capped version of the S&P GSCI index, which was used in most of the regression analysis of this article. The index constructs its weightings based on perceived economic significance of each commodity. In identifying economic significance, the index draws strictly on production information, which tends to skew towards the energy sector despite the capped methodology. For this ETF, EasyETF charges a comparatively low TER of 0.30%.
