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Commodity Futures

These entries address investing and trading in commodities and commodity futures as an alternative asset class to equities.

Futures Market Open Interest as Return Predictor

Do changes in the level of futures markets activity predict returns for corresponding asset classes? In their January 2011 paper entitled “What Does Futures Market Interest Tell Us about the Macroeconomy and Asset Prices?”, Harrison Hong and Motohiro Yogo relate futures markets open interest (the number of contracts outstanding) to future asset class returns. They focus on the 12-month change in open interest and 12-month future return. As noted by the authors, simple logic suggests that open interest should be a non-directional because each futures contract involves countering long and short positions. However, changes in the number of futures contracts could indicate changes in anticipated economic risks. Using monthly open interest data for 30 commodity futures, eight currency futures, ten bond futures, 14 stock index futures and corresponding asset class returns for periods from earliest availability of data through 2008, they find that: Keep Reading

Commodities as an Inflation Hedge

If you believe inflation is coming, should you shift assets toward commodities-oriented assets? In their November 2010 paper entitled “Are Commodities a Good Hedge Against Inflation? A Comparative Approach”, Laura Spierdijk and Zaghum Umar compare five measures of inflation hedging capacity as applied to commodities for investment horizons ranging from one month to ten years. They also investigate how these measures of hedging capacity relate. Using the monthly U.S. inflation rate based on the seasonally adjusted all urban Consumer Price Index, monthly returns for the S&P GSCI Total Return Index (proxy for a diversified, unleveraged, long-only commodity futures position) and its components, and the U.S. 3-month Treasury bill (T-bill) yield during January 1982 through August 2010, they find that: Keep Reading

Measuring and Interpreting Market Information Pulse

What is the best way to measure and interpret market reaction to new information? In their October 2010 paper entitled “Measuring Flow Toxicity in a High Frequency World”, David Easley, Marcos López de Prado and Maureen O’Hara introduce a new method to estimate the degree to which trading in financial markets is informed. They name this metric Volume-Synchronized Probability of Informed Trading (VPIN), approximated by the fraction of trading volume that is imbalanced (absolute difference between seller-initiated and buyer-initiated volumes, divided by total volume).  Their approach builds on three beliefs: (1) new orders indicate arrival of new information potentially predictive of subsequent price moves; (2) a specific volume of trades therefore represents a more consistent metric for information arrival than an interval of time; and, (3) a trade imbalance is the hallmark of arrival of important information. In a related November 2010 paper entitled “The Microstructure of the ‘Flash Crash’: Flow Toxicity, Liquidity Crashes and the Probability of Informed Trading”, these same authors focus this method on the May 6, 2010 market crash. Using high-frequency (one-minute intervals) price and volume data for a variety of futures contracts during January 2008 through August 2010 to construct rolling sets of equal-volume increments, they find that: Keep Reading

Secrets of Informed Commodity Futures Traders?

Are there commodity futures traders who consistently outperform? Who are they? What information do they exploit? In the September 2010 version of their paper entitled “Identifying Informed Traders in Futures Markets”, Raymond Fishe and Aaron Smith examine the short-term trading abilities of commodity futures traders by recreating their trading histories. They distinguish between those who trade intraday and those who hold overnight, arguing that the latter are efficient processors of technical trading information, while the former possess the best signals about fundamental short-run price pressures. Using daily positions for 8,921 traders in 12 futures markets over the period January 2000 through May 2009, they find that: Keep Reading

Hedges and Safe Havens Across Asset Classes

How effectively and consistently do equities, bonds, oil, gold and the dollar serve as hedges and safe havens for each other? In their September 2010 paper entitled “Hedges and Safe Havens – An Examination of Stocks, Bonds, Oil, Gold and the Dollar”, Cetin Ciner, Constantin Gurdgiev and Brian Lucey investigate pairwise hedging and safe haven relationships among these five major assets/asset classes. The define an asset as a hedge (safe haven) for another if respective returns are uncorrelated or negatively correlated on average over the long term (during relatively short intervals of stress). They define the long term (relatively short intervals) as their entire sample period (rolling four-month subperiods). They define intervals of stress as returns in the lowest fourth of observations. Using daily levels of the S&P 500 Index, an index of 10-year Treasuries, nearest-month gold and oil futures and the Federal Reserve Nominal Trade Weighted Effective Index for the dollar from January 1985 through October 2009 (nearly 25 years), they find that: Keep Reading

Effects of Creeping Indexation?

What are the implications for investors of a trend toward strategic and tactical allocation to index proxies (exchange-traded funds and derivatives) rather than individual securities? The July 2010 paper entitled “On the Economic Consequences of Index-Linked Investing” by Jeffrey Wurgler provides an overview of the effects of index-linked investing on stock prices, risk-return trade-offs, investor portfolio allocation decisions and fund manager skill assessments. The September 2010 paper entitled “Index Investment and Financialization of Commodities” by Ke Tang and Wei Xiong investigates the effects of increased investing during the last decade in commodity indexes. The October 2010 paper entitled “The Financialization of Commodity Futures Markets or: How I Learned to Stop Worrying and Love the Index Funds” by Scott Irwin and Dwight Sanders surveys research on the impact of commodity index fund growth on commodity price behavior. Using results of prior research and recent data on indexation investment levels, index returns and component asset returns, these papers find that: Keep Reading

Exploiting Commodity “Yield Curves”

Is there information useful to investors in the “yield curves” of commodity futures? In their December 2009 paper entitled “Structural Properties of Commodity Futures Term Structures and Their Implications for Basic Trading Strategies”, Rolf Duerr and Matthias Voegeli investigate the informativeness of price progressions across commodity futures contracts with different maturities (term structures or yield curves) over rolling 12-month windows. Specifically, they focus on trading commodity futures contracts based on the current slopes of these curves and on the stabilities of the shapes of the curves over time (slope and curvature). Using weekly closing settlement prices for 23 energy, metals, agriculture and livestock commodities spanning January 1998 through July 2009, they find that: Keep Reading

Analysis of Managed Futures?

A reader suggested: “CXOadvisory.com has a few articles on managed futures, but not a full analysis of claims such as those in the CME Group brochure “Managed Futures: Portfolio Diversification Opportunities”, which states that managed futures provide gains in all environments and with smaller drawdowns.” Keep Reading

Unfooled by Randomness?

Can people reliably distinguish between actual financial markets time series and randomized data? In the February 2010 draft of their paper entitled “Is It Real, or Is It Randomized?: A Financial Turing Test”, Jasmina Hasanhodzic, Andrew Lo and Emanuele Viola report the results of a web-based experiment designed to test the ability of people to distinguish between time series of returns for eight commonly traded financial assets (including stock indexes, a bond index, currencies and commodities, all given names of animals) and randomized data. Using a sample of 8015 guesses from 78 participants over eight contests conducted during 2009, they conclude that: Keep Reading

Success Factors for Futures Traders

Does the profitability of futures traders depend on risk-taking, private information or luck? In the January 2010 revision of their paper entitled “Determinants of Trading Profits of Individual Traders: Risk Premia or Information”, Michaël Dewally, Louis Ederington and Chitru Fernando investigate success factors for traders in the crude oil, gasoline and heating oil futures markets. They exploit detailed daily open interest data for specific large and mid-size traders (from the Commodity Futures Trading Commission, as augmented by the Department of Energy) accounting for about 70% to 80% of these three futures markets. This detailed data enables analytical segmentation of traders into eleven types, consolidated into four categories: (1) hedgers, (2) speculators, (3) market makers and (4) others. Using detailed data for a final sample of 382 traders over the period June 1993 through March 1997 (46 months), they conclude that: Keep Reading

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