Factor-Based Commodity Investing
Commodities represent a small but significant part of alternative assets in institutional investor portfolios. Commodity investors stress the low correlation between commodities and traditional investments (like equities and bonds) as well as the diversification benefits of including commodities in portfolios. They also view commodities as one of the few assets offering protection against rising inflation. The fall in commodity prices since the financial crisis of 2008 and the sharp fall of S&P GSCI, the benchmark used by most institutional investors to evaluate commodity investments, raised questions about the long-term return potential of commodities and the role of commodities in strategic asset allocation.
We adopt a factor-based investment approach to create a diversified portfolio of commodity factors and examine the efficiency gains achieved compared to widely used commodity benchmarks. Our research strongly suggests that factor-based commodity portfolios generate significantly better returns than the widely used benchmark of the S&P GSCI or an equally-weighted portfolio of commodity futures. Commodity portfolios exposed to commodity factors earn significant risk premia, in addition to the premium offered by a broadly diversified commodity index. Assuming that commodity risk premia are time varying, we also explore the possible benefits of dynamic strategies that rotate between commodity factors based on commodity variance-timing and commodity return-forecasting models.
There is growing evidence that commodity prices can be explained by a small number of priced commodity factors. Academic research shows that commodity investment strategies based on exposures to commodity fundamental characteristics such as the basis, momentum, inflation, liquidity, skewness, open interest and value outperform commercially available commodity indices such as the S&P GSCI or a passive equally-weighted index of all commodities. Asset pricing tests narrow down the number of commodity factors that are priced among commodity-sorted portfolios. The empirical evidence supports the pricing in the cross-section of commodity returns of the basis, the average commodity factor, momentum and basis-momentum. The risk premium associated with the basis factor is compensation for the low returns of the factor during periods of high global equity volatility. The momentum factor on the other hand tends to do well when aggregate speculative activity increases. The basis-momentum factor premium cannot be explained by the classical theories of storage, backwardation or hedging pressure but could represent a factor risk premium to compensate investors for exposure to commodity volatility risk.
While capturing commodity risk premia requires the construction of passive portfolios with the desired exposure to commodity factors, timing commodity returns presupposes the ability to predict commodity returns and risk and calls for the design of dynamic trading strategies that rotate between the factors. Evidence on the predictability of commodity returns are as controversial as the evidence on the predictability of equity returns. There is currently little research on the profitability of variance-timing commodity strategies.
Our research accomplishes four tasks. First, we create a well-diversified portfolio of commodity factors. To address the issue of estimation risk, we use alternative portfolio construction methodologies in the factor combination. We create portfolios without short positions in individual commodities but we also consider long-short versions that allow for short positions, especially since shorting is inexpensive and straightforward in the commodities futures market. Second, we test which of the proposed commodity factors are priced and non-redundant. We use recently developed statistical methodologies to choose the appropriate factors to be included in the portfolio and avoid the risk of data dredging. We limit the number of factors and models and consider factors for which there is theoretical justifications and evidence of cross-sectional pricing. Third, we compare the performance of the multi-factor commodity portfolio to existing commodity benchmarks and in particular the S&P GSCI which represents the leading fully collateralised investable index and is the preferred benchmark for the majority of professionally managed portfolios. Fourth, we provide evidence on the predictability of commodity factor-based portfolios. To assess the economic benefits of risk and returns predictability we create dynamic investment strategies based on risk or return prediction signals and measure the improvement in performance compared to passive investment strategies.
Our study supports the following conclusions. First, we identify the equally-weighted portfolio of all commodities, and portfolios based on the basis, momentum and basis-momentum as risk factors for the commodities market. Second, an equally-weighted commodity factor portfolio combining the low basis, high momentum and the high basis-momentum factor portfolios, achieves over the period 1975-2015 a Sharpe ratio of 0.68 that represents a major improvement compared with the return-to-risk offered by the S&P GSCI (0.03) and the equally-weighted portfolio of all commodities (0.28). The improvement in return-to-risk is significantly better when short positions are allowed in the construction of the commodity factor portfolios (Sharpe ratio of 1.02). Using mean-variance, minimum variance, maximum diversification or risk parity weights to create the multi-factor commodity portfolio makes little differences in performance compared to equal weights.
Third, the factor-based portfolio represents a dramatic improvement compared with the S&P GSCI, the benchmark used by most institutional investors, ETFs, ETNs and mutual funds. In particular, over the 1975-2015 period the S&P GSCI achieved an annual excess return of 0.63% compared with an annual excess return of 11.28% of an equally-weighted long-only commodity factor portfolio. The significant outperformance has been achieved with much lower volatility (16.63% vs. 19.48%) and is robust across sub-periods, the business cycle and volatility states. The evidence suggests that the S&P GSCI is unlikely to be on the mean-variance efficient frontier and that switching to the factor-based commodity benchmark increases the return-to-risk from investing in commodities significantly.
Finally, we build dynamic factor portfolio-timing strategies based on predictions of factor returns and volatility. Variance-timing is profitable, producing statistically significant alphas for the average commodity portfolio and the long-only versions of the momentum, basis and basis-momentum factor portfolios. We find strong evidence suggesting that variance-timing works out-of-sample for the long-short commodity momentum premium but adds little value to passive investments in the long-short basis or basis-momentum factor premia. Models predicting commodity factor returns do not add value once variance-timing has been implemented.
Our findings have important implications for commodity portfolio management. Commodity factor portfolios based on momentum, the basis and basis-momentum and a multi-factor combination perform significantly better than the widely used S&P GSCI benchmark. The commodity factor portfolios outperform the S&P GSCI consistently across sub-periods, the business cycle and volatility regimes. Since the financial crisis of 2008, the multi-factor commodity portfolio gained 58% compared with the 65% loss experienced by the S&P GSCI. Investors should consider replacing the S&P GSCI commodity benchmark with the better-diversified and performing portfolio of commodity factors.
Our results also have implications for the controversial question on the value added of commodities in the traditional stock/bond asset mix. The role of commodities in asset allocation should be re-evaluated in light of the evidence presented in this paper suggesting that a passive multi-factor portfolio is significantly better than the S&P GSCI or the average commodity portfolio of individual commodities used in previous studies to assess the role of commodities in asset allocation.
Call for sponsorship for research chairs:
EDHEC-Risk Institute aspires to associate its research efforts on factor investing in commodity markets with a major name from the industry and welcomes sponsorship to conduct a research chair. Research chair involves a close partnership with the financial sponsor and a commitment from EDHEC-Risk to publishing related articles in international academic journals as well as to releasing the research results to the investment management profession through wide distribution of practitioner-oriented publications and presentations at industry conferences.
An EDHEC-Risk Institute research chair therefore enables its sponsor to support high quality, independent research that will be made public; this is an ideal way to demonstrate your organisation’s interest and commitment to the field of factor investing in commodity markets.
If you are interested in discussing further research chair opportunities, please contact: Maud Gauchon on +33 (0)4 93 18 78 87 or at firstname.lastname@example.org