Open Research Questions in Commodities and Derivatives

Book: Commodities: Markets, Performance, and Strategies
Editors: H. Kent Baker, Greg Filbeck, Jeffrey H. Harris
Publisher: Oxford University Press, 2018
ISBN: 9780190656010

What We Still Do Not Know

Chapter 27, written by Scott Mixon from the CFTC’s Office of the Chief Economist, is different from the other chapters. Instead of explaining what we know, it focuses on what we do not know. It maps out the open research questions in commodity markets and highlights where academic work could actually help real-world decision-makers.

The central tension is that commodity derivatives directly link the real economy with financial markets. Decades of research have been done, but substantial knowledge gaps remain. And the people who need answers the most (regulators, corporate risk managers, policymakers) often need them on tight timelines.

A Brief History of Commodity Research and Regulation

The chapter starts with useful context. Disagreements over the social benefits of commodity trading have been around since the late 1800s. By the 1920s, the U.S. government was already doing data-intensive investigations. The Grain Futures Administration (a predecessor of the CFTC) required exchanges to publish data on open interest, volume, and prices.

When wheat futures got volatile in 1925, the Senate requested an investigation. Researchers found a positive correlation between speculator position changes and price changes, and recommended position limits. That basic finding and policy response has essentially been repeated in every commodity price spike since.

One key difference from securities markets: the CFTC has comprehensive data on positions held by various types of market participants. This level of detail does not exist in equity markets. The Commitments of Traders (COT) report, published weekly, breaks down positions by producer/merchant/processor, swap dealer, managed money, and other categories.

Core Research Themes

How Do Hedgers Actually Behave?

The standard assumption is that commercial hedgers maintain a passive short position to offset their physical commodity exposure. But the data tells a more complicated story. Cheng and Xiong (2014) found that the volatility of hedger positions is much higher than the volatility of actual output. Hedgers trade far more than a simple passive hedge would require.

Meanwhile, average hedge ratios are surprisingly low. Between 2007 and 2011, hedge ratios were only 17 percent for corn, 28 percent for wheat, 32 percent for soybeans, and 57 percent for cotton. Most theoretical models would predict much higher ratios. Why hedgers trade so much yet hedge so little is an open puzzle.

Rampini, Sufi, and Viswanathan (2014) raised another issue: hedging costs money because it requires collateral. When does hedging become too expensive? How does that interact with a firm’s other financial decisions? The literature has focused mostly on interest rate and foreign exchange hedging because of historical data availability, but commodity hedging questions remain underexplored.

Who Provides Liquidity?

The traditional theory from Keynes (1923) and Hicks (1939) predicts that speculators earn a risk premium for taking positions opposite hedgers. Modern studies support this. Dewally, Ederington, and Fernando (2013) found that mean hedger profits are negative but mean speculator profits are positive. Hedge funds in particular get paid for providing risk-bearing capacity, especially when volatility is high or inventories are low.

But here is an interesting twist. Some research suggests that commercial hedgers also provide short-term liquidity. Kang, Rouwenhorst, and Tang (2017) found that while hedgers want a long-term hedge position, they may vary their positions in the short term if they are paid for the immediacy they provide. This could help explain why hedgers trade so much.

The Rise of Electronic Trading

Trading pits are essentially dead. Electronic order books displaced them rapidly once introduced. Table data from the chapter shows automated trading as a percentage of total volume rising across all product groups between 2012 and 2016. Energy crude oil went from 54 to 63 percent. Agriculture grain and oilseed went from 39 to 49 percent. G10 FX was already at 84 percent.

But electronic trading is not uniform. Electricity trading is still essentially zero percent automated. Thinly traded agricultural products and roll activity still involve more human processing. Understanding how electronic intermediation differs from pit-based intermediation, especially during stressed periods, is an open and important question.

The Financialization Debate

Mixon covers similar ground to Chapter 25 but frames it from a research perspective. He notes that the financialization term is often used in a pejorative sense. Some commentators take strong positions that commodity markets have been “distorted” by financial flows.

The irony is that during the 1970s-1990s, the literature complained that commodity markets were too segmented from financial markets. Then in the early 2000s, the complaint flipped to markets being too integrated with financial markets.

Many academic papers tested the “Masters Hypothesis” that index speculation inflated commodity prices. Most found little support. Brunetti and Reiffen (2014) even found that index investors reduced the cost of hedging and became important suppliers of price risk insurance.

The Swap Market Black Box

A major data gap existed because commodity swap activity was largely opaque before Dodd-Frank. Researchers relied on COT data, which only covers futures positions. This created puzzles. For example, swap dealer positions in crude oil were long from 2006-2010 but short from 2011-2015, which made no sense if swap dealers were just facilitating long index exposure.

Mixon, Onur, and Riggs (2017) introduced new CFTC data on actual swap positions and found that commercial end-users hold even larger positions in swaps than in futures. The swap dealer exposure was driven more by large short swap positions from commercials than by long positions from index investors. Less than a quarter of WTI swap exposure came from index investments.

Practical Regulatory Questions

The second half of the chapter covers questions that regulators actually face. Two examples stand out:

Transparency vs. Hedger Privacy

After Dodd-Frank, swap transactions were publicly reported in near real-time. This was supposed to improve transparency. But it created problems for large hedgers.

Southwest Airlines had a well-known strategy of hedging fuel costs with long-dated oil derivatives. After the reporting rules took effect, dealer counterparties started calling them immediately after seeing their trades on the public ticker. “I see you just did a trade in 2017,” they would say. Dealers widened their spreads and charged more. The CFTC eventually granted Southwest a 15-day delay for public reporting of long-dated crude oil trades.

Mexico faces a similar problem with its massive annual oil hedging program. In 2016, the program covered 250 million barrels at a cost of $1.028 billion in premiums. When the press spotted Mexico’s trades on the public swap ticker, it complicated the entire hedging process. More academic work on the optimal design of transparency rules for commodity markets would be valuable.

The “Wrong Kind of Liquidity”

As post-crisis regulations made commodity trading more capital-intensive for banks, many banks left the business. Morgan Stanley sold its oil division. JPMorgan sold its physical commodities business. Nine of the 10 largest Western banks either left commodity trading or substantially reduced activity.

Trading houses stepped in to fill the gap, but they tend to provide more short-term liquidity and lack the broad relationship services (lines of credit, portfolio margining, investment banking) that banks offered. Whether this shift is good or bad for commercial end-users is still an open question.

My Take

This is one of the most intellectually honest chapters in the book. Mixon admits what researchers do not know, which is refreshing after chapters that present findings as more settled than they really are. The Southwest Airlines and Mexico examples are particularly good because they show how academic questions have direct, practical consequences.

The observation that hedgers trade far more than their output would justify, yet hedge far less than theory predicts, is a genuinely interesting puzzle. Anyone who solves it would make a real contribution.

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