Commodity Futures

Do trend following strategies widely used by managed futures funds break down during financial crises? In the December 2013 version of their paper entitled “Is This Time Different? Trend Following and Financial Crises”, Mark Hutchinson and John O’Brien examine the effectiveness of trend following strategies as applied to futures contract series during and between financial crises. They define a financial crisis interval as the two to four years after the start of the crisis. They consider six global crises: (1) the Great Depression commencing 1929: (2) the 1973 oil crisis; (3) the third world debt crisis of 1981; (4) the crash of October 1987; (5) the bursting of the dot-com bubble in 2000; and, (6) the sub-prime/euro crisis commencing in 2007. They also consider eight regional crises during 1977 through 2000. They calculate momentum returns for each asset class by each month weighting constituent contract series proportionally to their excess return over the past one to 12 months and inversely to an estimate of their volatility based on lagged data. They include estimates of transaction costs proportional to the value traded that vary by asset class and time period. They also incorporate management and incentive fees (based on high water mark) of 2% and 20%, respectively. Using actual and modeled futures prices encompassing 21 equity indexes, 13 government bonds, nine currency exchange rates and 21 commodities (and contemporaneous risk-free rates) during January 1921 through June 2013, they find that: Keep Reading

Is simple momentum the secret sauce of Managed Futures funds? In their 2013 paper entitled “Demystifying Managed Futures”, Brian Hurst, Yao Ooi and Lasse Pedersen examine how well simple trend-following strategies based on time series (intrinsic or absolute) momentum explain the performance of Managed Futures funds. Their simple intrinsic momentum strategy goes long (short) a contract series with a positive (negative) return relative to the risk-free rate over 1-month, 3-month and 12-month look-back intervals. They apply the strategy to a liquid universe of 24 commodity futures, 9 equity futures, 13 government bond futures and 12 currency forwards. They adopt a simple diversification weighting that targets 40% annualized volatility for each position. They rebalance the diversified portfolio weekly at the Friday close based on data from the Thursday close. They ignore rebalancing/roll frictions. Using daily and weekly prices for 58 futures contract and currency forward series during January 1985 through June 2012, they find that: Keep Reading

Have investors overwhelmed commercial traders in commodity futures markets, thereby depressing the value of commodity futures as a diversifier of stocks and bonds? In his November 2013 papers entitled “Implications of Financialization for Commodity Investors: The Case of Roll Yields” and “Implications of Financialization for Strategic Asset Allocation: The Case of Correlations”, Adam Zaremba examines the effects of commodity futures market financialization on the potential diversification benefit of a passive allocation to commodities. He quantifies financialization as the share of open interest in commodity futures contracts held by non-commercial traders per Commitments of Traders reports of the Commodity Futures Trading Commission. He investigates specifically the effects of financialization on: (1) roll return, the return from continually shifting from expiring to longer-term commodity futures contracts to maintain a position; and, (2) the correlations of commodity futures returns with those of stocks and bonds. Then, in a mean-variance optimization framework from the perspective of a U.S. investor, he examines how these effects alter the diversification benefit of adding a commodity futures position to stocks and bonds. Using monthly returns of index proxies for the broad U.S. stock market, U.S. government bonds and a broad set of commodity futures from the end of 1991 through 2012, he finds that: Keep Reading

Are other precious metals more effective than gold as safe havens from turmoil in stock and bond markets? In their September 2013 paper entitled “Time Variation in Precious Metal Safe Haven Status — Evidence from the USA”, Brian Lucey and Sile Li compare and contrast the effectiveness of four precious metals (gold, silver, platinum and palladium) as safe havens from sharp declines in U.S. stocks (the S&P 500 Index) and U.S. bonds (a 10-year U.S. Treasury note index). They define an asset as a safe haven from another if returns of the former exhibit zero or negative correlation with returns of the latter when the latter experiences a sharp drawdown. A safe haven is different from a hedge, which has zero or negative return correlation with another asset or portfolio on average. They calculate returns for precious metals based on a continually rolling position in nearest month futures. They calculate return correlations quarter by quarter and focus on the worst 5% of drawdowns in stocks or bonds. Using daily futures contract prices for gold, silver, platinum and palladium and daily returns for the stock and bond indexes from the first quarter of 1989 through the second quarter of 2013, they find that: Keep Reading

Is platinum as good as gold? In the September 2013 version of their paper entitled “Analysis of the Investment Potential of Platinum Group Metals”, James Ross McCown and Ron Shaw evaluate the investment value of platinum group metals (platinum, palladium, rhodium, iridium, ruthenium and osmium). Using daily spot prices for platinum group metals, gold and crude oil, daily levels of a broad U.S. stock market index, monthly U.S. consumer and producer price indexes and monthly U.S. industrial production levels during July 1992 through December 2011, they find that: Keep Reading

Do the relationships among returns for stocks and the most heavily traded commodities (gold and crude oil) consistently offer risk diversification? In their July 2013 paper entitled “Gold, Oil, and Stocks”, Jozef Baruník, Evzen Kocenda and Lukas Vacha analyze the return relationships among stocks ( the S&P 500 Index), gold and oil (light crude) over the past 26 years. Specifically, they test the degrees to which their prices: (1) co-move; (2) reliably lead one another; and, share any long-term relationships (such as ratios to which they revert). They seek robustness of findings by employing a variety of methods, data sampling frequencies and investment horizons. Using intraday and daily prices of the most active rolling futures contracts for the S&P 500 Index, gold and light crude oil during 1987 through 2012, they find that: Keep Reading

What do records of actual positions suggest about commodity futures trading success? In the June 2013 version of their paper entitled “Determinants of Trader Profits in Commodity Futures Markets”, Michaël Dewally, Louis Ederington and Chitru Fernando examine actual daily closing positions of energy futures traders to determine how profitability relates to differences in risk taking, trading strategy and information/skill. They assign each trader in their sample to one of eleven categories: refiners, independent producers, pipelines and marketers, large energy consumers, commercial banks, energy traders, hedge funds, households, investment banks and dealers, market makers and others. Using end-of-day open interest for 382 traders reporting positions in NYMEX crude oil, heating oil and gasoline futures markets via the CFTC’s Large Trader Reporting System during June 1993 through March 1997, they find that: Keep Reading

Has crude oil turned into paper from an investment perspective? In their May 2013 paper entitled “Oil Prices, Exchange Rates and Asset Prices”, Marcel Fratzscher, Daniel Schneider and Ine Van Robays examine relationships between crude oil price and behaviors of other asset classes. Specifically, they relate spot West Texas Intermediate (WTI) crude oil price to: the U.S. dollar exchange rate versus a basket of developed market currencies; Dow Jones Industrial Average (DJIA) return; U.S. short-term interest rate; the S&P 500 options-implied volatility index (VIX); and, open interest in the NYMEX crude oil futures (as an indication of financialization of the oil market). They also test the response of crude oil price to economic news. Using daily data for these financial series during January 2001 through mid-October 2012, and contemporaneous U.S. economic news and associated expectations, they find that: Keep Reading

Can commodities still be useful for portfolio diversification, despite their recent poor aggregate return, high volatility and elevated return correlations with other asset classes? In the May 2013 version of their paper entitled “Strategic Allocation to Commodity Factor Premiums”, David Blitz and Wilma de Groot examine the performance and diversification power of the commodity market portfolio and of alternative commodity momentum, carry and low-risk (low-volatility) portfolios. They define the commodity market portfolio as the S&P GSCI (production-weighted aggregation of six energy, seven metal and 11 agricultural commodities). The commodity long-only (long-short) momentum portfolio is each month long the equally weighted 30% of commodities with the highest returns over the past 12 months (and short the 30% of commodities with the lowest returns). The commodity long-only (long-short) carry portfolio is each month long the equally weighted 30% of commodities with the highest annualized ratios of nearest to next-nearest futures contract price (and short the 30% of commodities with the lowest ratios). The commodity long-only (long-short) low-risk portfolio is each month long the equally weighted 30% of commodities with the lowest daily volatilities over the past three years (and short the 30% of commodities with the highest volatilities). They also consider a combination that equally weights the commodity momentum, carry and low-risk portfolios. For comparison to U.S. stocks, they use returns of long-only, equally weighted “big-momentum” and “big-value” (comparable to commodity carry) stock portfolios from Kenneth French, and a similarly constructed “big-low-risk” stock portfolio. For comparison with bonds, they use the total return of the JP Morgan U.S. government bond index. For all return series and allocation strategies, they ignore trading frictions. Using daily and monthly futures index levels and contract prices for the 24 commodities in the S&P GSCI as available during January 1979 through June 2012, along with contemporaneous returns for a broad sample of U.S. stocks, they find that: Keep Reading

It is plausible that crude oil as a dominant energy commodity has return characteristics substantially different from those of other commodities and asset classes, and therefore represents a good diversification opportunity. To check, we add the United States Oil Fund (USO) to the following mix of asset class proxies (the same used in “Simple Asset Class ETF Momentum Strategy”):

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for USO and the average pairwise correlation of USO monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without USO. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for USO and the above nine asset class proxies as available from May 2006 (first return available for USO) through April 2013 (84 monthly returns), we find that: Keep Reading