Issues

In this paper, the authors develop a framework to quantify the convenience yield risk (CYR) inherent to each commodity futures market.  Implementing the paper’s approach, the authors document that their novel CYR measure is informative about future commodity returns.  In panel regressions, the CYR predicts future returns with a positive sign.  Economically, a strategy that opens long positions in commodity markets with a higher than median CYR signal and sells the remaining commodities yields an average return of 6.93% per year.  The performance of the CYR strategy cannot be explained by exposure to existing commodity strategies or other variables that capture changes in the investment opportunity set.

This paper explores how the 2016 U.S. Prime Money Market Funds (PMMFs) regulation affected the crude oil market.  This reform led to an increase in short-term dollar borrowing costs and the oil sector became particularly susceptible to disruptions in the global funding market due to a post-financial crisis debt expansion which far outpaced other commodity industries.  Building on the global crude oil market structural vector autoregression (SVAR) model pioneered by Kilian and Murphy (2014), the authors find that tighter PMMFs funding conditions have a lagged negative effect on the real price of crude oil and a lagged positive effect on oil production.  The authors show that these responses are driven primarily by a fall in certificates of deposits issued by global banks.  Lastly, the authors evidence that the U.S. nominal effective exchange rate acts as a transmission channel for the negative funding shock to the real price of oil.

In August 1988, the Hunt Brothers were found guilty by a jury of conspiracy, manipulation, monopolization, racketeering and fraud.  Using a behavioral model, the authors aim to quantify the extent of manipulation in the silver market during the 1970s and the 1980s, with a specific focus on the period leading up to the Silver Crisis.  The authors’ behavioral model takes account of the role of fundamentals, manipulation and speculation.  The authors’ results indicate very little evidence of manipulation in the silver market in the run up to the Silver Crisis.  Both fundamentals and speculation dominate the silver market during our sample, with speculation particularly important in the latter half of the 1970s.

This paper examines the effects of financialization on commodity markets in terms of pricing.  It investigates whether commodity index traders affect weekly returns and turnover during roll periods and the effect of commodity index traders’ market share on returns.  Risk adjustments are tested to see if they alter liquidity and insurance premiums and how financialization affects liquidity and insurance premiums.  Finally, an alternative method is used to test how liquidity and insurance premiums determine commodity returns.

The quantitative contribution of speculative storage to commodity price dynamics remains an open question.  This research provides an answer by developing a rich model of competitive storage and a new structural estimation approach exploiting the joint dynamics of prices and quantities, and carries it on global grain market data.  The results show that the extended storage model explains most of the moments in the data, including the high price autocorrelation, and that, although supply shocks are the main driver of grain market dynamics, demand shocks are important with a standard deviation of more than three-fifth of that of total supply shocks.

This paper uses machine learning tools to study the lead-lag relations in commodity futures returns.  The authors use LASSO (Least Absolute Shrinkage and Selection Operator) to select the predictors because the number of predictors is large relative to the number of observations.  They find significant full-sample and out-of-sample predictability.  The out-of-sample forecasts based on LASSO generate statistically and economically large gains.  When the authors use more complex machine learning models such as regression trees and neural networks to forecast commodity futures returns, the out-of-sample performance is worse than LASSO portfolios, suggesting that nonlinearities and interactions do not appear substantial in the data.  Finally, the authors find that index trading due to financialization has been associated with excess comovement among commodity futures.

This study examines the relationship dynamic between currency and commodity returns around the Russian invasion of Ukraine in February 2022.  In regular times, in line with previous research, there is a positive relationship between currency and commodity returns; that is, an increase in commodity prices is associated with an increase in foreign currency values relative to the U.S. dollar.  However, this positive relationship reverses and becomes negative during the period when the invasion of Ukraine was highly probable (from January 20, 2022) and remains negative during the outset of the war (February 24 – March 11, 2022).  The results suggest that the war’s anticipation and subsequent start changed the sign of the relationship between commodity and currency prices.  In other words, during this period of heightened geopolitical risks, the observed increase in commodity prices was associated with a decrease in the value of foreign currencies relative to the U.S. dollar.  This study also examines whether the exposure to geopolitical risk around the invasion of Ukraine affects currency returns.  The study reports that geographic distance to the war significantly affects currency returns during the period of anticipation and the outset of the war; that is, the further away the country is from the war, the higher the country’s currency return.  Overall, the results indicate that a war between two major commodity-exporting countries significantly affects global currency pricing.

Tokens in the recent phenomenon of the staking economy offer transaction convenience in digital networks and are frequently staked for base-layer consensus generation or incentivizing platform development (consequently earning staking rewards), thereby generating both currency-like and commodity-like properties as hybrid assets.  This paper builds a theoretical model where heterogeneous agents dynamically allocate their wealth over staking, on-chain transaction, and off-chain consumption.  Model implications and empirical findings from stakable tokens corroborate the predictions: (i) the staking ratio positively correlates with reward rates; (ii) higher staking ratios predict greater excess returns; and (iii) uncovered interest-rate parity is violated, generating significant crypto carry premia.

In their research, the authors use the crude oil market in a case study that introduces a method of assessing whether there is meaningful price-risk asymmetry reflected in options pricing.  Specifically, they use CVOL, an implied volatility calculation from the CME Group, to look into whether there are important differences between the upside price risk reflected in out-of-the-money call options compared to the downside price risk reflected in out-of-the-money put options.  The authors pay particular attention to how risk-management approaches might need to be adjusted when price-risk sentiment is significantly asymmetric.

The authors note that as the potential U.S. regulatory framework begins to take shape, participants in the space should prepare for significant change.  To understand what may come next, these market participants can look to rules and regulations put in place by the U.S. Commodity Futures Trading Commission (CFTC) for participants in the swaps, options, and futures marketplaces.  However, even if the CFTC does gain regulatory jurisdiction over digital assets through legislation, token issuers should be aware that the U.S. Securities and Exchange Commission will retain some authority due to case law and the Howey Test for investment contracts.

The U.S. Strategic Petroleum Reserve (SPR), “the world’s largest supply of emergency crude oil was established primarily to reduce the impact of disruptions in supplies of petroleum products and to carry out obligations of the United States under the international energy program,” notes the U.S. Department of Energy.  Dr. Ilia Bouchouev is an expert on the U.S. SPR, and as such provided testimony on March 8, 2023, regarding this topic to a subcommittee of the U.S. House Committee on Oversight and Accountability, specifically the U.S. House Subcommittee on Economic Growth, Energy Policy, and Regulatory Affairs.  With permission from Dr. Bouchouev, the Summer 2023 issue of the CID is republishing his well-thought-out testimony.

The rise of carbon markets and the increased cost of compliance is forcing commodity markets to respond.  The carbon risk facing commodity markets is acute, including (a) the emissions associated with the extraction, refining and combustion of fossil fuels, (b) the energy required to dig and process ore into metal, and (c) the risk of deforestation and high emissions associated with carbon intensive agriculture.  In addition to the increased regulatory burden, companies are having to face up to much greater scrutiny as to the provenance and the emissions associated with their products.  But as this CID article also demonstrates, the commodity industry is not sitting idly by.  Companies across various commodity industries have a rich capacity to innovate in the face of these new and emerging pressures.

We are delighted to interview Julie Lerner, Founder and CEO of U.S.-based PanXchange, a web-based trading and price-discovery platform for physical commodities.  Lerner is a regular contributor to media outlets such as the Wall Street Journal, the Financial Times and Bloomberg TV.  She has also been endorsed as a Futures Industry Association Innovator.  In addition, she has been recognized both in the Forbes 50>50 in Finance and in the Denver Business Journal’s most admired CEO’s.  In this interview we learn how her career evolved, and how PanXchange was founded.