Winter 2023

Scholarly Research Digest Articles

The paper employs the Nelson-Siegel framework to model the term structure of commodity futures prices.  It then exploits the information embedded in the model’s level, slope and curvature parameters to develop novel investment strategies in commodity markets.  The slope strategy, which assumes the continuation of recent slope movements of futures curves one-day ahead, generates a large out-of-sample Sharpe ratio of 1.41 before trading costs. Its performance survives exposure to traditional commodity risk factors or the consideration of reasonable transaction costs. The slope strategy’s profits increase with sentiment and are in part a compensation for the drawdowns incurred when economic activity slows down.

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The ability of oil investment vehicles to perfectly track spot oil has always been challenging; however, recently many vehicles have underperformed spot oil. The authors study the behavior of oil futures and exchange-traded products that invest in oil futures to document and understand the source of this tracking error. The primary reason why oil investment vehicles have underperformed spot oil is an increase in contango in oil futures markets that the authors find might be related to investment crowding and the financialization of commodity markets. They show that from 2006 to 2017, oil futures investing underperformed spot oil and the market was in contango most of the time. Proxies for crowding, such as the concentration of major oil investors and changes in assets under management and fund flows of major oil exchange-traded products, are associated with contango in the futures markets and the divergence between futures and spot returns. The authors also provide evidence of an impact of the financialization on oil futures prices.

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As an exogenous factor in the investment market, geopolitical risk has significant impacts on economic activities, but short-term economic fluctuations are unlikely to cause or predict it. This paper identifies the existence of a significant geopolitical risk premium, and empirically investigates the features of the premium based on the cross-section of commodity futures.  The paper finds that (i) the risk premium is negative as the commodity futures contracts with higher geopolitical risk exposures have lower risk-adjusted returns; (ii) the risk premium is amplified in high geopolitical risk periods and in years before 2000; and (iii) ex-ante threats, instead of ex-post acts events, largely drive the risk premium.

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During the 2005-2010 period, the nonconvergence of cash prices to the prices of expiring futures contracts for corn, soybean, and winter wheat raised concerns among market participants and regulators.  This paper builds on the minimum variance framework and highlights important hedging characteristics of converging and nonconverging markets.  The article assesses the hedging performance of the futures market for a producer during this nonconvergence episode in the following two dimensions:  minimization of hedging profit variability and maximization of the net selling price.  The article confirms that the hedge in the wheat futures market failed to provide risk reduction to a producer during nonconvergence.  The hedging effectiveness of wheat futures improved post-nonconvergence when the Chicago Mercantile Exchange (CME) Group introduced the variable storage rate mechanism in the year 2010 to correct for convergence failures in the market.

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The authors present a new term-structure model for commodity futures prices based on Trolle and Schwartz (2009), which they extend by incorporating multiple jump processes.  The authors’ work explores the valuation of plain vanilla options on futures prices when (a) the spot price follows a log-normal process, (b) the forward cost of carry curve and the volatility are stochastic variables, and (c) the spot price and the forward cost of carry allow for time-dampening jumps.  The authors obtain an analytical representation of the characteristic function of futures prices and, hence, also for plain vanilla option prices using the fast Fourier transform methodology.  They price options on WTI crude oil futures contracts using the paper’s model and extant models, and they obtain higher accuracy than earlier models and save significantly in computing time.

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This study examines the profitability of a cross-asset time-series momentum strategy (XTSMOM) constructed using past changes in crude oil–implied volatility (OVX) and stock market returns as joint predictors.  The authors show that employing the past changes in OVX in addition to past stock returns helps better predict future stock market returns globally.  The XTSMOM outperforms both the single-asset time-series momentum and buy & hold strategies with higher mean returns, lower standard deviations, and higher Sharpe ratios.  This study contributes to the literature on cross-asset momentum spillovers as well as on the impact of crude oil uncertainty on stock markets.

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The margin between the price of crude oil and one or more of its refined products, known as the crack spread, is a key risk measure in the energy trading industry.  Effective forecasts of crack spread returns require modelling the co-movements of crude oil and refined product prices.  To this end, in this paper the authors re-examine the relationship between parameter instability in energy commodity returns correlations and macroeconomic fundamentals using a new correlation component model dubbed the Regime Switching DCC-MIDAS, which distinguishes regime switches in the short and long-run correlations. Breaks in the secular component are associated with low-frequency macroeconomic fundamentals, while short-run correlations are characterized by abrupt breaks linked to market constraints. The results reveal the benefits of the specification for Value-at-Risk and portfolio optimization in terms of forecasting performance at medium and long horizons and in times of intense market instability, such as the recent pandemic crisis.

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The transition from high- to low-carbon production systems increasingly creates regulatory and market risks for high-emitting firms. The authors analyze to what extent financial investors demand a premium to compensate for such risks and thus might raise firms’ cost of equity capital. They find that there is a distinct and robust positive impact of carbon intensity (carbon emissions per unit of output) on this cost of equity capital. This suggests carbon emissions demand a significant risk premium indeed. The effect results from systematic risk factors: high-emitting assets are significantly more sensitive to economy-wide fluctuations than low-emitting ones. The impact of carbon intensity on the cost of equity capital is more pronounced in high-emitting sectors, EU countries, and firms subject to carbon pricing regulation. These results suggest that carbon emission reduction is a valuable risk mitigation strategy as it reduces the costs of equity.

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Practitioner Insights

The U.S. corn market responds in powerful ways to shifts in crude oil prices and potential droughts, yet not in consistent patterns.  In this research, the authors use a time-varying parameter regression methodology to highlight how the corn market’s reaction to oil and drought has changed over time.  They use this methodology more specifically to highlight the characteristics of the interaction between corn prices, oil prices, and drought indicators that seem to be more significant than just tracking typical price momentum and volatility metrics and assuming persistent and consistent patterns.

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The green energy transition requires the expansion of electric vehicle battery metals supply, particularly in the production of nickel.  Indonesia, the leading global nickel producer, emerges as the most promising candidate to bridge this supply gap and foster downstream investment through an ambitious industrial strategy.  This article analyzes Indonesia’s strategic decision to become a class 1 nickel hub, despite historically mining low-grade nickel. Recent data suggests that High-Pressure Acid Leaching (HPAL) technology, previously scrutinized for cost overruns and energy intensity, is not the primary bottleneck. Rather the article posits that the technology’s high environmental footprint creates unaccounted-for profitability and policy risks, with the potential to impact global markets.

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This article notes that Artificial Intelligence (AI) is a tool, not a replacement.  However, as it evolves, it will redefine our roles.  Efficiency gaps will widen, the nature of work will change and standards of professionalism will rise.  AI literacy is the way forward.

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Book Review

The recently released book, Back to the Futures, was written by Scott H. Irwin, a prominent agricultural economist and professor at the University of Illinois, and Doug Peterson, a writer of 79 books including seven historical novels and over 40 children’s books.  The authors discuss several commodity-related topics and their origins, delve into the mechanics of the commodity futures markets, and walk the reader through several market examples to explain the mechanics of the futures markets, as well as some of the issues related to Congress and the regulators.  The book is written in a very easy-to-comprehend format for both the commodity market novice as well as the seasoned professional.

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Interviews

In this interview, Professor Craig Pirrong discusses how he originally became involved in commodities and how his career has evolved.  As an academic expert on commodity-market debacles, Pirrong also comments on the coverage of the FTX scandal.  In addition, he provides his thoughts on how the liquefied natural gas (LNG) export market from the U.S. will evolve.  He concludes with advice to current students and young professionals in the commodities markets.

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Victor Liu, Ph.D., is a Managing Director at Hemado Green Energy with more than 15 years of global energy-market experience.  He was previously Director of Consulting at Wood Mackenzie and Head of Transaction Services at Infield Systems in London.  Dr. Liu has extensive experience in both renewable energy and in digitalization.  He is also a regular speaker at global energy conferences and has published his findings in academic and industry journals. In addition, Dr. Liu is a founding member of the Editorial Board of Bayes Business School’s Commodity Insights Digest (CID).

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Bayes Equation

Bayes Business School’s name is inspired by Bayes’ theorem of conditional probability, which states that beliefs should be updated in proportion to the weight of relevant new evidence.

Commodity Insights Digest