Destabilizing role of futures markets on North American hard red spring wheat spot prices

The objective of the paper is to determine if the futures prices of hard red spring wheat (HRSW) have stabilizing or destabilizing impact on spot HRSW price in North America. Several important results emerge from thorough empirical analysis. First, both Granger causality tests and directed acyclic graph algorithms (DAGs) point to two-way causality between futures and spot HRSW prices and thus endogeneity in both prices formation. To the contrary, both procedures suggest that ending stocks are exogenous to spot and futures HRSW prices. Both vector error correction model and impulse response functions point to a large and long-lasting impact of a shock to futures price on spot price level. Finally, variance decomposition analysis indicates that futures prices are responsible for the bulk of spot price volatility in both short and long run. Our result is consistent with those of theoretical models suggesting that when production (supply side) is the dominant disturbance, spot price is destabilized in both the short and the long run by futures prices. An important implication of this research is the need for alternative market mechanisms or alternative farm policy measures that would mitigate price risk and ensure sustainable farming of American HRSW farmers.     

Did Futures Markets Stabilise US Grain Prices?

Though economists are divided over whether, in practice, futures markets reduce spot price volatility, observers of nascent nineteenth century US futures markets essentially praised the stabilising effects of this financial innovation. Indeed, such praise is understandable, particularly if, as the Chicago Board of Trade (CBOT) and others assert, “violent” spot price fluctuations were common prior to, but not after, the 1870s; the same decade that grain trade historians typically associate with the birth of the modern futures contract. And whereas these events may be unrelated, the claim is intriguing because it requires that nineteenth century futures prices fulfil their price discovery function, a property that many modern futures markets do not possess. This paper explores what role, if any, the advent of futures trading may have had on spot price volatility. I corroborate the CBOT's assertion regarding diminished spot price volatility around the 1870s and show that early futures prices did indeed fulfil their price discovery function. Moreover, I address two alternative hypotheses that relate the decline in spot price volatility to the Civil War. Ultimately, I maintain that the evolution of futures markets is the principal proximate reason why commodity spot price volatility diminished.     

Information-rich wheat markets in the early days of COVID-19

This paper uses the information implicit in commodity futures and options prices to infer market beliefs about the impact of early-stages COVID-19 on commodity market fundamentals. The particular commodity examined is soft red winter (SRW) wheat, and the timeframe is early February to late March 2020. The analysis highlights various adjustments in the cash and futures price of SRW wheat in light of surging short-run demand from consumer hoarding of staple food products, and a weakening long-run market from growing wheat stocks and an emerging global recession. This split is causing the forward curve to flatten and basis levels to invert. The change over time in the price of options on wheat futures reveals increased price volatility in response to growing uncertainty about the COVID-19 impacts. Similarly, changes in the skewness of the option's volatility smile illustrate a shift in traders’ perception about risk in the right versus left tail of the price distribution.     

Price discovery in a private cash forward market for lumber

Cash forward contracting is a common, and often preferred, means of managing commodity price risk in many industries. Despite this, little is known about the performance of cash forward markets, in particular the role they play in price discovery. The US lumber market provides a unique case for examining this issue. The Bloch Lumber Company maintains an active cash forward market for many lumber products, and publishes benchmark forward prices on their website and disseminates these prices to data vendors. Focusing on 2×4 random lengths lumber and 7/16 oriented strand board, this research examines the lead–lag relationships between the 3-month forward prices published by Bloch Lumber, representative spot prices, and lumber futures prices at the Chicago Mercantile Exchange. Results suggest that at least for 2×4 random lengths lumber, the forward prices published by Block Lumber lead both the spot price and futures price, suggesting that this private cash forward market provides some level of price discovery in the lumber markets.     

Futures markets and real estate public equity: Connectivity of lumber futures and Timber REITs

This paper investigates connectivity between lumber futures contracts, Timberland REITs, the FTSE NAREIT U.S. REIT index, spot prices, and timberland capitalization rates, and contributes to this tranche of research by empirically linking the price discovery process of Timberland Real Estate Investment Trusts to lumber futures. We employ VEC and GARCH models, providing evidence that lumber futures have a positive significant long- and short-run equilibrium relationship with publicly traded Timber REIT prices, connecting a specific futures commodity with its theoretically entwined real estate equity index. As such, exogenous factors that influence Timber REIT prices are documented leading to possible diversification/risk reduction strategies.     

How financial investment distorts food prices: evidence from U.S. grain markets

Convergence between commodity futures prices and the underlying physical assets at each contract's expiration date is a pivotal condition for the market's functioning. Between 2005 and 2010, convergence failed for several U.S. grain markets. This article presents a price pressure‐augmented commodity storage model that links the scale of nonconvergence to financial investment channeled through indices, which are traded in commodity futures markets. The model is empirically tested, using Markov regime‐switching regression analysis. Regression results strongly support the model's predicted link between index investment and the extent of nonconvergence for three grains traded at the Chicago Board of Trade: wheat, corn, and soybeans.     

Futures Markets and Spot Price Volatility: A Case Study

Futures markets, where they exist, can play a crucial role in determining the storage decision in the underlying spot (physical) market. The futures market acts as a conduit for market information and is a gatherer of agents' expectations about the future prospects for the spot market. As such, it is able to provide both price insurance and price discovery roles, the latter of which generates information for spot market traders and allows them to make rational storage decisions. If this were to be the case, then the efficiency of storage is improved which can potentially lead to a reduction in the volatility of spot prices over the marketing season. The existing literature is ambiguous as to whether futures markets can help spot markets price more efficiently. This paper seeks to examine whether this is the case in the British maincrop potato market by evaluating the volatility of spot prices over the period 1969–96 in a “before-after” analysis of the impact of the introduction of futures trading in 1980. The results suggest that the introduction of the futures market has led to a reduction in price volatility, despite some problems in the operation of the futures market itself.     

Evaluating price transmission between global agricultural markets and consumer food price indices in the European Union

This paper uses error correction models to evaluate the extent to and speed at which world agricultural commodity price movements affect consumer food prices in the European Union member states. We consider three types of world commodity price indices, each containing different commodities and weighting criteria. Results reveal a long‐run relationship between world agricultural commodity and consumer food prices in over half of the member states. Consumer prices in different member states and categories of member states respond differently to specific world price indices, suggesting that there are disparities in the structure and the efficiency of their food markets. The eurozone founders generally have lower transmission elasticities. This should be taken into account when predicting the impacts of extreme world price volatility and consumer food price rises, prompting governments to pay attention to the most vulnerable households.     

Bubbles,Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets

The Masters Hypothesis suggests that long‐only index funds were the main cause of a massive increase in commodity prices in 2007–2008 and 2011–2012. Central to the Masters Hypothesis are three basic tenets: (i) long‐only commodity index funds were directly responsible for driving futures prices higher; (ii) the deviations from fundamental value were economically very large; (iii) the impact was pervasive across commodity futures markets. There has been a great deal of empirical research on the Masters Hypothesis and commodity market bubbles. However, surprisingly few studies have found evidence that directly support the main tenets of the Masters Hypothesis. Some have attributed the lack of supporting evidence to the low‐power of time‐series tests, market efficiency issues and a lack of conditioning variables within models. In this paper, we address each of these issues using updated data and new empirical approaches. Still, price behaviour consistent with the Masters Hypothesis is surprisingly difficult to find in the data. This is an important finding given the on‐going policy debate and regulations proposed or being implemented to limit speculative positions in these markets.     

Commodity futures markets: a survey

This review article describes the main contributions in the literature on commodity futures markets. It is argued that modern studies have focused primarily on technical questions, with insufficient economic content. More research needs to be directed towards understanding fundamental economic issues such as why so few farmers hedge, the impacts of government farm programs on commodity futures, and the market impacts of commodity pools. The literature has failed to explain the prevalence of inverted markets in grains and oilseeds, and there is unexplainable price volatility in markets such as hogs and orange juice.     

价格支持、政策调整及粮食市场波动

目的 为了估计价格支持政策对不同粮食品种期现货价格波动的直接影响,实证分析和比较了政策及其调整对粮食期现货价格波动实施效果的影响,为深化粮食价格形成机制改革提供一定的理论参考和实证支撑。方法 文章利用稻谷、小麦、玉米和大豆的现货与期货价格日数据,将政策以虚拟变量的形式引入GARCH模型实证分析最低收购价政策、临时收储政策及其调整对平抑粮食期现货市场波动的作用。结果 价格支持政策对粮食价格波动产生了显著影响,最低收购价政策能够明显降低稻谷和小麦现货市场的波动程度,但对期货市场波动的作用则相反;玉米和大豆临时收储政策的取消导致现货市场波动性提高,而对期货市场波动的影响存在差异。结论 价格支持政策具有降低价格波动的作用效果,政策调控效果与实施品种的国内供求及市场形势、国内外市场的联系程度密切相关,政策的完善还需关注对期货市场波动的影响。     

A speculative bubble in commodity futures prices? Cross‐sectional evidence

Recent accusations against speculators in general and long-only commodity index funds in particular include: increasing market volatility, distorting historical price relationships, and fueling a rapid increase and decrease in the level of commodity prices. Some researchers have argued that these market participants—through their impact on market prices—may have inadvertently prevented the efficient distribution of food aid to deserving groups. Certainly, this result—if substantiated—would counter the classical argument that speculators make prices more efficient and thus improve the economic efficiency of the food marketing system. Given the very important policy implications, it is crucial to develop a more thorough understanding of long-only index funds and their potential market impact. Here, we review the criticisms (and rebuttals) levied against (and for) commodity index funds in recent U.S. Congressional testimonies. Then, additional empirical evidence is added regarding cross-sectional market returns and the relative levels of long-only index fund participation in 12 commodity futures markets. The empirical results provide scant evidence that long-only index funds impact returns across commodity futures markets.     

Out‐of‐sample testing price discovery in commodity markets: the case of soybeans

Price discovery, a central function of futures markets, has been usually tested in‐sample by studying the common stochastic trend between spot and futures prices. Instead, to evaluate futures as anticipatory prices, we develop a forecast approach to out‐of‐sample test price discovery in a multivariate framework. We apply it to the soybeans market. Results indicate futures prices as the best available “predictors” of future spot prices, although this finding holds only on average and for certain periods, other models show forecasting gains.     

A simple model of endogenous agricultural commodity price fluctuations with storage

A debate has been raging for centuries regarding the effects of interannual storage on commodity prices. Most analysts consider storage to function as a price stabilizer, while others place it at the core of an explanation of intriguing features of commodity price series, such as skewed distributions. Most studies have been developed in the context of the theory of competitive storage where random shocks affect supply or demand. Recently, the endogenous chaotic behavior of markets has become another possible hypothesis regarding the origin of commodity price fluctuations. We develop a nonlinear cobweb model with intra‐ and interannual storage, risk averse agents, and adaptive expectations. Like the theory of competitive storage, this nonlinear cobweb model with storage can reproduce some of the stylized facts of agricultural commodity prices (autocorrelation of first rank, low kurtosis, and skewness). In addition, the effects of storage on price variation are mixed. In the presence of interannual storage, chaotic price series show less variation compared to a situation without interannual storage but we find that storage contributes to the endogenous volatility of prices by making chaotic dynamics more likely.     

Financial activity in agricultural futures markets: evidence from quantile regressions

This study analyses the relationship between financial activity and price returns in 12 US agricultural futures markets. It contributes to the existing research by exploring the forecasting power of trading activity for returns from the perspective of conditional quantiles. Quantile regressions detect Granger‐causal effects from positions of speculators and index traders to price returns in a wide range of commodity markets such as cocoa, coffee, corn, sugar and SRW wheat.     

Comovement of dairy product futures and firm value: returns and volatility

This study investigates the exposure of dairy firm stock prices to the prices of dairy product futures, in terms of returns and volatility, from May 2013 to April 2018. Stock price returns are regressed against an index of the futures price returns to four dairy products – milk, cheese, butter and dry whey – to isolate the effects of the dairy futures price returns. Dairy product futures price returns are found to be significant in the regression in the first three years of the sample period, with a mean coefficient of ?0.024. Using the Diebold‐Yilmaz volatility spillover method of forecast error variance decomposition, we show that the volatility of the four dairy product futures accounted for an average of 5.49 per cent of the volatility of dairy stock prices. These results suggest that the prices of dairy firms have minimal exposure to dairy product futures prices. This has implications for dairy firms and investors, who seek to understand volatility and returns in the dairy products and the stocks they trade in, and for policymakers, who seek to control or mitigate undesirable dairy product price volatility.     

Measuring the functional efficiency of agricultural futures markets

This article presents a method for measuring the functional efficiency of agricultural futures markets in terms of social welfare using a standard futures market structural model. Employing the concept of social surplus, it can be shown that, when futures prices are used to estimate future spot prices, the errors in prediction produce to some degree resource misallocation, which in turn results in welfare losses. Therefore, the social welfare associated with the presence of futures markets can be measured using a Social Loss index. The indicator was calculated for the period 1975–2015 and for several subperiods, which allow us to analyse functional efficiency before and after the 2007–2008 spikes in the prices of agricultural commodities. Futures contracts for 12 products are evaluated. The products are grouped in three different categories: ‘soft products’, ‘livestock’ and ‘grains and oilseeds’. The results indicate that livestock contracts tended to be more efficient than the rest of the contracts during the whole period, but in 2008–2015 their efficiency decreased vis‐á‐vis the rest of the products. Nevertheless, 2008–2015 proved to be the most efficient subperiod, confirming the remarkable development of agricultural futures markets over time.     

FUTURES PRICES AS FORECASTS OF COMMODITY SPOT PRICES: LIVE CATTLE AND WOOL*

In this paper the foundations on which the predictive interpretation of futures prices rests are discussed, and possible reasons for the differential predictive performance of futures prices as between different commodity markets examined. The predictive performances of futures, and spot prices themselves, are tested empirically, using Australian data for wool (a continuous inventory commodity) and finished live beef cattle (virtually a non-storable commodity), by means of instrumental variables estimation.     

Commodity index investment and food prices: does the “Masters Hypothesis” explain recent price spikes?

The “Masters Hypothesis” is the claim that unprecedented buying pressure in recent years from commodity index investors created massive bubbles in food and energy prices. The purpose of this article is to review the evidence from recent studies that investigate the empirical relationship between index investment and price movements in agricultural futures markets. One line of research uses time‐series regression tests, such as Granger causality tests, to investigate the relationship between price movements and index positions. This research provides little evidence in support of the Masters Hypothesis in agricultural futures markets. A second line of research uses cross‐sectional regression tests and studies in this area provide very limited evidence in favor of the Masters Hypothesis for agricultural futures markets. A third line of research investigates whether there is a significant relationship between commodity index trading and the difference, or spread, between futures prices of different contract maturities on the same date. These studies report a range of results depending on the type of test. However, the bulk of the evidence indicates either no relationship or a negative relationship, which is once again inconsistent with the Masters Hypothesis. Overall, this growing body of literature fails to find compelling evidence that buying pressure from commodity index investment in recent years caused a massive bubble in agricultural futures prices. The Masters Hypothesis is simply not a valid characterization of reality.     

Commodity price bubbles and macroeconomics: evidence from the Chinese agricultural markets

This article investigates the links between commodity price bubbles and macroeconomic factors, with an application to the agricultural commodity markets in China from 2006 to 2014. Price bubbles are identified using a newly developed, recursive right‐tailed unit root test. A Zero‐inflated Poisson model is used to analyze the factors contributing to bubbles. Results show that (a) there were speculative bubbles in most Chinese agricultural commodity futures markets during the sample period, though their presence was infrequent; (b) economic growth, money supply, and inflation have positive effects on bubble occurrences, while interest rates have a negative effect; and (c) among all macroeconomic factors considered, economic growth and money supply have the greatest impact in triggering bubbles. Our findings shed new light on the nature and formation of bubbles in the Chinese agricultural commodity markets.