Financialization of Commodities Markets

Dear Colleagues,

Materially, the financialization of commodity markets began almost two centuries ago when the risks of commodity markets were transferred to financial investors through forward and other derivative contracts. However, the term has been more recently coined for when institutional investors, mainly through commodity swaps and derived indexed products, increase exposure to this market segment using modern portfolio theory as a guide. Using swap dealers as the main conduit to established futures markets, the associated institutions have been perceived as having a significant influence on price formation and, in particular, volatility. The term “financialization” is often associated with the claim that commodity price movements are being increasingly driven by financial (portfolio) considerations and less by commodity-specific factors. Some argue that this leads to excessive price volatility and, thus, to higher real costs and potential welfare losses for commercial participants in the commodity sector. These conjectures have triggered a large body of empirical research investigating the price discovery process in commodity and commodity futures markets, paying particular attention to the role of “financial” investors.

We are seeking papers that can be grouped, according to the research questions they address, into three categories: First, papers about the impact of financial investors (sometimes coined as “speculation”) on commodity price level, returns, or risk premiums. Second, papers that examine the impact of speculation on price volatility—either commodity specific or considering the market segment (index) as a whole. This also includes research on the impact of speculation on the price discovery process, i.e., the adjustment of spot vs. futures prices on macroeconomic and financial market disturbances. This leads to the third strand of research, namely the transmission of shocks between (and within) commodity markets. Such research focuses on the lead–lag relations of various market segments in relation to speculative activity (as separate from the correlation effects of financialization and their impact on risk diversification).

With this Special Issue, we seek to provide insight related to the empirical findings on financialization, including assessments of the impact of data quality, specification of variables (e.g., futures prices and returns, speculation proxies), model selection and estimation (including estimation periods), and choice of asset universe. We seek papers that are particularly focused on empirical and methodological questions and provide insight on the sensitivity of empirical findings against sample selection, variable measurement, and model specification.

Although the number of research papers on financialization has sharply increased in the past two decades, the metastudy of Haase, Seiler, and Zimmermann (J Commod Mark, 2016), covering some 100 published papers, indicates that the quality of some published papers is extremely heterogeneous in terms of methodology, data, and empirical measures, such that the results are often not traceable and difficult to compare. This calls for further, careful empirical research utilizing more recent data.

Prof. Dr. Jeffrey H. Harris
Dr. Donato Morea
Prof. Dr. Heinz Zimmermann
Guest Editors

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• commodity index trading
• speculation in commodity markets
• price discovery
• the transmission of shocks between financial markets and commodities

Title: Time-varying deterministic volatility model for options on wheat futures
Authors: Marco Hasse; Jacqueline Henn
Affiliation: Department of Finance, Faculty of Business and Economics, University of Basel, Peter Merian Weg 6, CH-4002 Basel, Switzerland
Abstract: This study introduces a robust model that captures wheat futures volatility dynamics, influenced by seasonality, time to maturity, and storage dynamics, with minimal calibratable parameters. Our approach reduces error-proneness and enhances plausibility checks, offering a reliable alternative to models that are difficult to calibrate. Transferring estimated parameters from liquid to illiquid markets is feasible, which is challenging for models with numerous parameters. This is of practical importance as it improves the modelling of volatility in illiquid markets, where price discovery is less efficient. In liquid markets, on the other hand, where speculative activity is high, we find that implied volatility is usually the best measure. Additionally, the introduced volatility model is suitable for pricing options on wheat futures in a risk-neutral measure.