Economic Uncertainty And Commodity Futures Volatility by OFR
Sumudu W. Watugala
This paper investigates the dynamics of commodity futures volatility. I derive the variance decomposition for the futures basis to show how unexpected excess returns result from new information about expected future interest rates, convenience yields, and risk premia. This motivates my empirical analysis of the volatility impact of economic and inflation regimes and commodity supply-demand shocks. Using data on major commodity futures markets and global bilateral commodity trade, I analyze the extent to which commodity volatility is related to fundamental uncertainty arising from increased emerging market demand and macroeconomic uncertainty, and control for the potential impact of financial frictions introduced by changing market structure and index trading. I find that a higher concentration in the emerging market importers of a commodity is associated with higher futures volatility. Commodity futures volatility is significantly predictable using variables capturing macroeconomic uncertainty. I examine the conditional variation in the asymmetric relationship between returns and volatility, and how this relates to the futures basis and sensitivity to consumer and producer shocks.
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Economic Uncertainty And Commodity Futures Volatility – Introduction
This paper investigates the time-variation in commodity futures volatility and the factors explaining its dynamics. I analyze the impact of concentration and increased emerging market demand on commodity markets. This research builds on Bloom (2014), who presents evidence that emerging markets and recessionary periods are strongly associated with economic uncertainty, and Gabaix (2011), who shows the impact on aggregate volatility from power laws in size distributions. This paper adds to the literature on what explains fluctuations in volatility (see, for example, Roll (1984); Schwert (1989); Engle and Rangel (2008); Gabaix (2011); Bloom (2014)), while also contributing to the current debate on commodity price dynamics and potential distortions arising from market frictions.1 In particular, I examine how supply-demand shocks, macroeconomic uncertainty, and financial frictions are related to realized volatility in commodity futures markets.
Volatility dynamics are a key consideration in strategy formation for hedging, derivatives trading, and portfolio optimization. Moreover, producers and consumers benefit from understanding the factors explaining price fluctuations when evaluating real options embedded in investment choices (Schwartz, 1997). Distortions can lead to under- or over-investment, and even transitory deviations from fundamentals can lead to the long-term misallocation of resources (see, for example, Bernanke (1983); Bloom, Bond, and Reenen (2007)). This is especially important when there are non-convex production functions and large fixed costs to entry and expansion (e.g., a copper producer considering the development of a new mine or a manufacturer considering the opening of a new factory that uses raw commodities as inputs). Uncertainty also increases the difficulty for both producers and consumers when formulating optimal hedging strategies, potentially leading to higher volatility in their cash flows. This can cause higher borrowing costs and lower debt in the presence of non-zero costs to bankruptcy and default, which can in turn lead to lower firm values. Consequently, understanding the relationship between volatility and economic factors is a first-order consideration. For commodities with derivative markets that are illiquid, opaque, or have little market depth or limited expirations, the findings in this paper can provide a useful aid to price discovery, real option evaluation, and risk management for end-users as well as financial investors. A better understanding of these futures return dynamics also enables policy-makers to consider the impact of possible market intervention and evaluate regulatory options aimed at achieving a desired welfare objective.
Using a reduced form model of a commodity market with power-law distributed consumers and producers, I present several hypotheses on how concentration and emerging market demand impacts commodity volatility, and test these in the data. When commodity supply and demand are dominated by a handful of countries, their shocks affect global commodity markets. Even in the case where trading partners face homogeneous shocks, the market concentration itself can have an impact on volatility. Heterogeneous consumers and producers may face supply-demand shocks with different variance. When the larger consumers are also riskier and more volatile (experience higher variance shocks), their impact on market volatility is amplified through concentration. This is important when considering the impact of growing emerging market demand on commodity prices. Many of these markets are volatile, segmented, and pose non-diversifiable risks to hedgers and international investors (Bekaert and Harvey, 1997; Bloom, 2014).
I collate data on 22 major commodity futures markets and the global bilateral trade in the underlying commodities and analyze the extent to which commodity volatility is related to increased emerging market demand and other fundamentals such as inflation uncertainty, while controlling for financial frictions introduced by changing market structure and commodity index trading. A higher concentration in the emerging market importers of a commodity is associated with higher futures volatility. The results imply that a 1:00% gain in market concentration by developing country consumers is associated with a 1:19% increase in commodity futures volatility. I find predictability in commodity futures volatility using variables capturing macroeconomic uncertainty, with adjusted R-squared gains of over 10% over the baseline specification. Moreover, controlling for recession periods further increases the explanatory power of the main predictive regressions by over 13%. These reflect economically significant gains for an investor, particularly those engaged in hedging, in evaluating real options embedded in investment choices, or in trading portfolios of derivatives.
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