Commodity Market Interest and Asset Prices∗

Open interest in commodity futures, which signals commodity market activity, contains information about future commodity and bond prices. High open-interest growth predicts high commodity-price inflation, a rising short rate, and low bond returns. Open interest is a more powerful predictor of commodity prices than the short rate, the yield spread, basis, and hedging pressure. While highly correlated with commodityprice inflation and the Chicago Fed national activity index (both oft-used for inflation forecasting), open-interest growth is a better predictor of commodity and bond prices than either of these variables. Somewhat surprisingly, we find an analogous result in currency markets: open interest in currency futures is a better predictor of exchanges rates than the forward discount. We develop a simple model of futures pricing to explain why open interest can be more informative than past prices in forecasting future price movements. ∗This paper subsumes our earlier work titled “Digging into Commodities”. For comments and discussions, we thank Erkko Etula, Hong Liu, David Robinson, Nikolai Roussanov, Allan Timmermann, and seminar participants at Boston College, Centre de Recherche en Economie et Statistique, Columbia University, Dartmouth College, Federal Reserve Bank of Chicago, Fordham University, Imperial College London, International Monetary Fund, London School of Economics, Northwestern University, Ohio State University, PanAgora Asset Management, SAC Capital, Stockholm School of Economics, University of California Los Angeles, University of California San Diego, University of Minnesota, University of Pennsylvania, University of Rochester, University of Southern California, University of Texas at Austin, Washington University in St. Louis, the 2008 Economic Research Initiatives at Duke Conference on Identification Issues in Economics, the 2010 Annual Meeting of the American Finance Association, and the 2010 NBER Summer Institute Working Group on Forecasting and Empirical Methods in Macroeconomics and Finance. We thank Jennifer Kwok, Hui Fang, Yupeng Liu, James Luo, Thien Nguyen, and Elizabeth So for research assistance. Hong acknowledges support from the National Science Foundation (grant SES-0850404). Yogo acknowledges support from the Rodney L. White Center for Financial Research at the University of Pennsylvania. The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System. †Princeton University and NBER (e-mail: [email protected]) ‡Federal Reserve Bank of Minneapolis and NBER (e-mail: [email protected])