Economics of Commodity Markets
October 27, 2012
James Hamilton, University of California at San Diego and NBER, and Jing Cynthia Wu, University of Chicago
The last decade brought substantial increased participation in commodity markets by index funds that maintain long positions in the near futures contracts. Policymakers and academic studies have reached sharply different conclusions about the effects of these funds on commodity futures prices. Hamilton and Wu propose a unifying framework for examining this question, noting that according to a simple model of futures arbitrage, if index-fund buying influences prices by changing the risk premium, then the notional positions of the index investors should help predict excess returns in these contracts. They find no evidence that the positions of traders in agricultural contracts identified by the CFTC as following an index strategy can help predict returns on the near futures contracts. They review evidence that these positions might help predict changes in oil futures prices, and find that while there is some support for this in the earlier data, it appears to be driven by some of the dramatic features of the 2007-9 recession, with the relation breaking down out of sample.
Brian Henderson, George Washington University, and Neil Pearson and Li Wang, University of Illinois at Urbana-Champaign,
Following the recent, dramatic increase in commodity investments by financial institutions, there has been a heated debate among academics, practitioners, and regulators over whether their trades and holdings have affected commodity prices and return dynamics. Henderson, Pearson, and Wang examine the price impact of commodity investments on the commodities futures markets using a novel dataset of Commodity-Linked Notes (CLNs). CLN issuers hedge their liabilities by taking long positions in the underlying commodity futures on the pricing dates. These hedging trades, which reflect the demands of the CLN investors, are plausibly exogenous to the contemporaneous and subsequent price movements, allowing the researchers to identify the price impact of the hedging trades. The researchers find that the hedging trades cause significant price changes in the underlying futures markets, and therefore provide direct evidence of the impact of financial trades on commodity futures prices.
Michael Sockin, Princeton University, and Wei Xiong
Sockin and Xiong present a model to analyze the feedback effects of commodity futures prices on commodity demand through an information channel. The model builds on two key features: 1) futures prices of key industrial commodities, such as oil and copper, serving as key barometers of global productivity, and 2) complementarity in industrial producers' production decisions as a result of their need to trade produced goods. As a result of information frictions and production complementarity, increases in the futures prices, even if driven by non-fundamental factors, can lead to increased, rather than decreased, commodity demand and thus spot prices. This feedback effect contradicts two widely held arguments that speculators who trade only in futures markets cannot affect spot prices and that commodity price increases driven by non-fundamental reasons must be accompanied by reduced demand.
Suleyman Basak and Anna Pavlova, London Business School
A sharp increase in the popularity of commodity investing in the past decade has triggered an unprecedented inflow of institutional funds into commodity futures markets. Such financialization of commodities coincided with significant booms and busts in commodity markets, raising concerns of policymakers. Basak and Pavlova explore the effects of financialization in a model that features institutional investors alongside traditional futures markets participants. The institutional investors care about their performance relative to a commodity index. The authors find that in the presence of institutions, the prices of all commodity futures go up. The price rise is higher for futures belonging to the index than for non-index ones. If a commodity future is included in the index, then supply and demand shocks specific to that commodity spill over to all other commodity futures markets. In contrast, supply and demand shocks to a non-index commodity affect only that commodity market . In the presence of institutions, the volatilities of both index and non-index futures go up, but those of index futures increase by more. Furthermore, financialization leads to an increase in the correlations amongst commodity futures as well as in equity-commodity correlations. Increases in the correlations between index commodities exceed those for non-index ones. The authors model demand shocks explicitly, which allows them to disentangle the effects of financialization from the effects of rising demand for commodities.
Domenico Ferraro, Duke University; Kenneth Rogoff, Harvard University and NBER; and Barbara Rossi, Duke University
Ferraro, Rogoff, and Rossi investigate whether oil prices have a reliable and stable out-of-sample relationship with the Canadian/U.S dollar nominal exchange rate. Despite state-of-the art methodologies, they find little systematic relation between oil prices and the exchange rate at the monthly and quarterly frequencies. In contrast, their main contribution is to show the existence of a very short-term relationship at the daily frequency, which is rather robust and holds no matter whether they use contemporaneous (realized) or lagged oil prices in our regression. However, in the latter case the predictive ability is ephemeral, mostly appearing after instabilities have been appropriately taken into account.
Amiyatosh Purnanandam and Daniel Weagley, University of Michigan
The payoffs of weather derivative contracts depend on variables such as temperature and snowfall levels in the underlying city during the contract period. The Chicago Mercantile Exchange (CME) has introduced several temperature related contracts on different U.S. cities in a staggered fashion over the past 13 years. Purnanandam and Weagley show that the introduction of these contracts on a city's temperature improves the accuracy of temperature measurement by the dedicated weather station in that city in a causal manner. They argue that the introduction of temperature-based financial markets generates additional scrutiny of the temperature data measured by the National Weather Services (NWS), which in turn produces better outcomes by the government agency. These results have important implications for the role of financial innovation and markets in affecting real outcomes.
Martin Bodenstein and Luca Guerrieri, Federal Reserve Board, and Lutz Kilian, University of Michigan
Bodenstein, Guerrieri, and Kilian provide the first quantitative analysis of how U.S. monetary policy responses should differ depending on the source of the observed oil price fluctuations. They present three main sets of results. First, they propose a novel decomposition of the marginal cost of production that highlights the role of each factor input for the evolution of inflation. Second, conditional on an estimated interest rate policy reaction function, they demonstrate that no two structural shocks induce the same monetary policy response, even after controlling for the impact response of the real price of oil, and we quantify these differences. Third, they show that the policy responses implied by a policy rule, whose coefficients were chosen to maximize U.S. welfare, differ substantially from the policy response implied by the same rule estimated on historical data. Among a wide range of rules, a rule that is easily implementable and that nearly maximizes U.S. welfare involves the Fed putting zero weight on the price of oil and responding to wage inflation without interest rate smoothing.
Hunt Allcott, New York University and NBER, and Daniel Keniston, Yale University
Boyan Jovanovic, New York University and NBER
Jovanovic proposes a test for the presence of a bubble in the price of an exhaustible resource. A bubble is accompanied by a rise in the storage-to-consumption ratio: consumption peters out and a fraction of the original stock is held forever. The test suggests that there is a bubble in the price of oil and in the market for high-end Bordeaux wines, but other explanations are also possible. A bubble reduces welfare regardless of whether there are other stores of value, particularly fiat money.
Eyal Dvir, Boston College, and Kenneth Rogoff
Dvir and Rogoff present evidence showing the existence of stable cointegrating vectors connecting four important variables in the U.S. oil market: U.S. oil production, U.S. stocks of crude oil, the real price of oil, and U.S. industrial production. Their data are monthly, and go back to the 1930s, split into sub-samples which correspond to periods before and after the 1973 crisis. They further show that the cointegrating vectors found in the data accord well with an extended commodity storage model which allows for demand growth dynamics and for supply regimes.
Peter Christoffersen, University of Toronto, and Kris Jacobs and Bingxin Li, University of Houston
Options on crude oil futures are the most actively traded commodity derivatives. Existing pricing models for crude oil derivatives are computationally intensive due to the presence of latent state variables. Christoffersen, Jacobs, and Li adopt a class of computationally efficient discrete-time jump models that allow for closed-form option valuation, and investigate the economic importance of jumps and dynamic jump intensities in the market for crude oil futures and futures options. Including jumps is crucial for modeling crude oil futures and futures options, and they find very strong evidence in favor of time-varying jump intensities. The main role of jumps and jump risk in the crude oil futures and options markets is to capture excess kurtosis in the data. They find that jumps account for a large part of the variation in crude oil futures and options prices, and a substantial part of the risk premium is due to jumps. Futures data indicate the presence of many small jumps, while option data point towards large infrequent jumps.
Steven Baker and Bryan Routledge, Carnegie Mellon University
Baker and Routledge solve a Pareto risk-sharing problem with heterogeneous agents with recursive utility over multiple goods. They use this optimal consumption allocation to derive a pricing kernel and the price of oil and related futures contracts. This gives them insight into the dynamics of risk premiums in commodity markets for oil. As an example, in a calibrated version of this model they show how rising oil prices and falling oil risk premium are an outcome of the dynamic properties of the optimal risk sharing solution. They also compute portfolios that implement the optimal consumption policies and demonstrate that large and variable open interest is a property of optimal risk sharing.