Commodity Futures

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

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

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

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

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

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

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

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

Is the aggregate sentiment of futures traders predictive for asset returns? In the June 2008 update of their paper entitled “How to Time the Commodity Market”, Devraj Basu, Roel Oomen and Alexander Stremme investigate whether information in the weekly Commodity Futures Trading Commission’s Commitments of Traders (COT) reports enable successful timing of U.S. equities and commodities markets. These reports aggregate the size and direction of the positions taken by different categories of futures traders in different assets. “Commercial” traders use futures contracts for hedging, “non-commercial” traders use them for other types of speculation and “non-reportable” traders operate below the reporting threshold. The study seeks to exploit “hedging pressure” (the fraction of positions that are long) for each of six liquid commodities (crude oil, gold, silver, copper, soybeans and sugar) and for the S&P 500 Index. Each Friday, the six trading strategies studied: (1) take a long position in a commodity if hedging pressure for both the commodity and the S&P 500 Index are below their 52-week averages; or, (2) take a long position in the S&P 500 Index if hedging pressure for both the commodity and the S&P 500 Index are above their 52-week averages; or, (3) hold 3-month U.S. Treasury bills. Using COT reports and associated weekly futures prices for October 1992 through December 2006, they conclude that: Keep Reading

How can long-term investors best hedge against inflation’s erosion of purchasing power? In their April 2009 paper entitled “Inflation Hedging for Long-Term Investors”, Alexander Attie and Shaun Roache assess the inflation hedging properties of traditional asset classes over different investment horizons. Using total return indexes for several asset classes from initial data availability (January 1927 at the earliest) through November 2008, they conclude that: Keep Reading