How to time the commodities markets
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- Basu, D., Oomen, R. & Stremme, A. J Deriv Hedge Funds (2010) 16: 1. doi:10.1057/jdhf.2010.4
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In this article we construct and investigate the performance of elementary trading strategies that allow an investor to time between equities and commodities. Our strategies appear to capture time-varying risk premiums in the equity and commodity markets, enabling them to successfully time the market, outperforming the benchmark index as well as buy-and-hold and trend-based strategies.
Keywordscommodities dynamic trading strategies market timing asset allocation
TIMING COMMODITY MARKETS USING RISK PREMIUMS
Commodity futures markets have recently come to the attention of financial investors, with the total investments of commodity index funds having grown from US$13 billion to $260 billion in the last 5 years. Much of the attraction comes from the fact that a diversified portfolio of commodities seems to produce equity returns with low or even negative correlation with equities. The study by Gorton and Rouwenhorst1 comes to this conclusion and finds considerable evidence supporting the inclusion of commodities in a portfolio. However, Harvey and Erb2 point out that it is important to avoid naive extrapolation of historical returns and to strike a balance between dependable sources of return and possible sources of return.
Modern finance theory suggests that the most dependable source of return is the risk premium. There are three kinds of risk premiums that exist in the commodity futures markets where most of the institutional investors trade. The first is generated by the risk factors that affect the underlying asset and are transmitted to the futures price via the ‘cash-and-carry’ arbitrage pricing relationship between spot and futures prices. The evidence on this premium is mixed, with Bessembinder3 finding a strong relationship between the risk premiums in spot and futures markets for 22 commodities, whereas Dusak4 finds that the Capital Asset Pricing Model beta for a number of agricultural futures contracts is indistinguishable from zero. The second source of risk premium in futures markets arises from the term structure of futures prices leading to term premiums. These have been studied5,6 more recently by Harvey and Erb2, who suggest that the ‘roll return’ that arises as a result of the shape of the term structure of futures prices explains much of the variation in expected returns across a wide range of commodities. The third source of risk premium is hedging demand by producers, following the hedging pressure hypothesis of Keynes.7 This premium has been empirically investigated in the last few decades.3,8,9 These studies find evidence for a time-varying hedging pressure risk premium particularly in commodity futures markets and also in financial futures markets, although the nature of the risk premium is different across these two sets of markets.
Our study focuses on the hedging pressure risk premium and we endeavor to exploit it to construct long-only timing strategies that time between the commodity market, the S&P500 index and a risk free asset (in this study we use the return on a short-term US Treasury bill). We consider six commodities, crude oil, gold, silver, copper, soybeans and sugar, representing three major commodity sectors: energy, metals and agriculture. All have liquid futures markets. We use the Commitment of Traders (COT) report produced by the Commodity and Futures Trading Commission (CFTC) to construct measures of hedging pressure. ‘Hedging pressure’ is defined as the fraction of traders in each category who are long. The CFTC classifies large traders into ‘commercial traders’ and ‘non-commercial traders’, and we use the hedging pressure of both these categories. The futures positions of commercial traders reflects hedging demand, while that for non-commercial traders should reflect the response of speculators, but perhaps also the actions of momentum traders such as index or hedge funds. Thus, these two measures could provide different information for timing. The Keynesian hedging pressure hypothesis does not apply for the S&P500, and we consider commercial hedging pressure only for the S&P as it reflects the actions of a homogeneous group of traders. The COT report appears to be quite widely used by traders in commodities, equities and foreign exchange, who seem to regard it as a useful intermediate-to-long-term indicator. The importance of the COT report for industry practitioners was highlighted in 2006 when the CFTC announced that they were considering no longer publishing it, and received more than 4500 responses from industry professionals, virtually all of which urged the CFTC to continue publishing the report.
We construct elementary timing strategies based on the information contained in the hedging pressure reports. Specifically, our strategies will take a long position in any given commodity (futures) when commercial hedgers are short or speculators are long, and we go long the S&P whenever commercial hedgers are also long in the S&P. The commodity timing signal is motivated by the hedging pressure hypothesis, whereas the signal for trading the S&P is inspired by the results of Basu and Stremme.10 Our strategies are similar in spirit to ‘trigger’ strategies used by traders who utilize the COT report. We assess the performance of our strategies using various common performance measures, and compare it to the performance of simple trend-following strategies.
DATA AND METHODOLOGY
When a reportable trader, that is, one whose positions are above a minimum threshold level, is identified to the CFTC, the trader is classified as either a ‘commercial’ or ‘non-commercial’ trader. A trader's reported futures position is determined to be commercial if the trader uses futures contracts for the purposes of hedging as defined by CFTC regulations. Specifically, a reportable trader is classified as commercial by filing a statement with the CFTC (using the CFTC Form 40) that he is commercially ‘… engaged in business activities hedged by the use of the futures and option markets’. However, to ensure that traders are classified consistently and with utmost accuracy, CFTC market surveillance staff members in the regional offices check the forms and reclassify the trader if necessary. A reportable participant may be classified by the CFTC as non-commercial in one market and commercial in another market, but cannot be classified as both in the same market. Having said this, a multi-functional organization that has multiple trading entities may have each entity classified independently. The two categories of ‘commercial’ and ‘non-commercial’ comprise between 70 and 90 per cent of open interest in any given futures market (the CFTC's third class of traders, ‘non-reportable’, makes up the remainder of the market interest).
Hedging pressure for any one market and any one group of traders is defined as the number of long contracts held by this group of traders, divided by the total number of contracts in that market. In other words, hedging pressure measures the imbalance in long and short positions between the different groups of traders, relative to the total volume of open interest. Our data are at weekly frequency and covers the period October 1992 (when the CFTC first released the COT report) to the end of 2006. The data are obtained from DataStream.
Our timing strategies are motivated by the hedging pressure hypothesis for commodity producers, which imply that investors should go long when either commercial hedgers are going short or speculators are going long. The investment strategy for the S&P is based on the findings of Basu and Stremme.10 Our strategies are constructed as follows. On Friday of any given week, we invest in a given commodity if the commercial hedging pressure for this commodity and for the S&P500 is below their 52-week averages. Conversely, we invest in the S&P if commercial hedging pressure for both the commodity and the S&P are higher than their 52-week averages. In all other cases we invest in the risk-free asset (in our case the 3-month US Treasury bill). We consider the performance of these real-time strategies over the 2000–2006 period.
As a comparison benchmark for our strategies, we chose trend-based strategies. As there is no commonly accepted theory to select such a strategy (according to the paradigm of finance theory, no such strategy should generate any abnormal return), we sought to find the ‘hardest to beat’, ‘make it as hard as possible’ trend-based strategies. We thus tested a variety of trend-based strategies and selected the best-performing as the benchmark to beat. A ‘trend-reversal’ strategy proved most successful. This strategy invests in a given commodity if the previous week's return on this commodity was below its 52-week average and at the same time last week's return on the S&P500 was above its 52-week average. Conversely, the strategy invests in the S&P500 if its most recent return was below the 52-week average and the most recent return on the commodity was above its average. In all other cases, the strategy remains fully invested in the risk-free asset. This strategy is based on data-mining but is the most challenging benchmark for our risk-premium-based strategy. Of course, it could be argued that the choice of this strategy is based on data-mining, but the idea was to choose the strategy that is the ‘hardest-to-beat’ benchmark for our hedging-pressure-based strategies.
Descriptive statistics of the assets
Strategies based on commercial hedging pressure
Strategies based on commercial hedging pressure
Strategies based on different percentile levels