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.     

Renewable versus nonrenewable resources: an analysis of volatility in futures prices

This study outlines a new approach for differentiating commodity futures based on their exhaustibility. Various aspects of volatility in the futures prices of renewable resources (palm oil, coffee, soya beans, rice, wheat and corn) and nonrenewable resources (zinc, aluminium, natural gas, gold, crude oil and copper) are studied, exploring whether volatility is greater in the former than in the latter. We use a generalised autoregressive conditional heteroskedasticity (GARCH) model to test our main hypothesis that the volatility in futures prices for renewable resources has recently been equal to or greater than the volatility in futures prices for nonrenewable resources. Our key findings suggest that futures prices for some renewable resources have greater variance than those for benchmark crude oil in a simulated GARCH series. We extend our analysis using a nonlinear vector smooth transition autoregressive (VSTAR) model to test for the existence of a shifting‐mean tendency in the commodity series that we researched. We show that transition from a stable to a volatile regime is more abrupt for renewable resources.     

Volatility and Price Jumps in Agricultural Futures Prices—Evidence from Wheat Options

Evidence suggests that agricultural futures price movements have fat-tailed distributions and exhibit sudden and unexpected price jumps. There is also evidence that the volatility of futures prices is time-dependent both as a function of calendar-time (seasonal effect) and time to maturity (maturity effect). This article extends Bates' (1991) jump-diffusion option pricing model by including both seasonal and maturity effects in the volatility specification. Both in-sample and out-of-sample procedures to fit market option prices on wheat futures show that the suggested model outperforms previous published models. A numerical example shows the magnitude of pricing errors for option valuation.     

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。     

Futures markets and price stabilisation: An analysis of soybeans markets in North America

The objective of this paper was to determine whether the futures markets have a stabilising or destabilising impact on soybean's spot prices in North America. Directed acyclic graphs (DAGs) are used to test for causality between futures prices, spot prices and ending stocks, followed by time series econometric analysis. The DAGs point to the two-way causal link between futures and spot prices and a lack of a causal link between inventory/stocks and spot price volatility. Time series results, including cointegration, vector error correction, impulse response and variance decomposition analysis, indicate a large impact from futures markets on the level and volatility of soybean spot prices in both the short and long run. These results have potentially important implications, as the impact of commodity price volatility is typically asymmetric across different actors. Farmers, for example, unlike speculators, utilise price risk management (PRM) instruments such as futures markets to mitigate price risks and appear to suffer from intensified volatility precisely because of their use of these instruments. Therefore, additional policies to cope with commodity price volatility, such as direct price controls or mitigation of consequences, can have critical stabilising functions supporting farmers' welfare and regional (rural) development.     

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.     

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.     

Fractional Integration in Agricultural Futures Price Volatilities

This article tests whether the volatility of agricultural futures prices exhibits fractional integration. Volatility series were constructed for fourteen agricultural futures price series with over 5,300 observations per series. The volatility series exhibit strong long-term dependence, which is an indicator of fractional integration. A fractional integration model, FIGARCH(1,  d , 1), performs significantly better than a traditional volatility model, GARCH(1,1), in modeling agricultural futures price volatility.     

Structural Breaks and the Relationship between Barley and Wheat Futures Prices on the London International Financial Futures Exchange

Co-movement between futures prices can arise when commodities are substitutes. Counterintuitively, Dawson and White fail to find a significant long-run link between feed barley and wheat prices on the London International Financial Futures Exchange. This relationship is re-examined using  Johansen, Mosconi, and Nielsen's co-integration procedure that permits structural breaks. Results show evidence of co-integration and hence price discovery. There is a significant break in October 2000 following Common Agricultural Policy intervention price reductions, the barley–wheat futures market is perfectly integrated, and the barley price Granger-causes the wheat price. Modeling structural breaks in price relationships appears important.     

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.     

SPECTRAL ANALYSIS OF THE THEORY OF ANTICIPATORY PRICES

The paper investigates the intertemporal relationship between cash and futures price changes using the techniques of spectral analysis. Daily data for the wheat, corn and soybean markets are analysed to determine if and how cash and futures prices move together. On a daily basis wheat and corn cash and futures prices move together; soybeans cash and futures prices do not move together on a daily basis.     

Agricultural Producer Price Expectations

Producer price expectations underlie much of agricultural supply analysis. While producer price expectations would ideally be discovered experimentally, this is too costly. Instead, producer price expectations are usually represented in agricultural supply analysis by easily obtained hypothesized expectation formulations. In most cases, the hypothesized expectation formulations are functions of past prices. However, other formulations are sometimes used, such as current cash and futures prices, or initial payments in the case of grains marketed by the Canadian Wheat Board. This paper compares actual producer price expectations with a variety of hypothesized expectation formulations for wheat and canola in Saskatchewan. A test developed by Granger is used to determine the proxy models that are significantly dominant. The model that dominates as a proxy in the case of wheat price expectations is the two-year declining-weight moving average. The two models that dominate as a proxy in the case of canola price expectations are the first-order autoregressive and, as well, the two-year declining-weight moving average. There is no significant difference between the two models. Somewhat surprising is the performance of formulations based on futures prices. These formulations perform very poorly in representing producers' price expectations, even though they are found to be among the most accurate predictors of actual commodity prices. An even more interesting observation is the performance of the futures price model in the canola market. Even though the November contract in January explains very little of the variation in the actual commodity prices for that year, its error in predicting canola prices is not significantly greater than that of the best performing, the four-year declining-weight moving average, based upon the root mean squared error criterion.     

The use of organized commodity markets to manage food import price instability and risk

The article explores the possibility of insuring the price risks of wheat and maize imports of low‐income food‐deficit countries (LIFDCs). Optimal strategies for an importing agent, who hedges with futures and options are derived, based on the objective of minimizing the unpredictability of import bills. Ex post simulations for a set of LIFDCs are run on wheat and maize imports hedged with futures and options in the Chicago Board of Trade, to explore the extent to which hedging reduces the unpredictability in import bills. Simulations encompass both periods of normal price behavior, as well as the period of global upheaval that occurred in 2007 and 2008. Results show that hedging with futures alone affords agents considerable opportunities for reducing import cost unpredictability, and the same holds with options, albeit, to a lesser extent. However, during the recent price spike of 2007–2008, hedging with options would have increased the unpredictability of some countries’ maize import bills, due to the combination of erratic import patterns and pronounced market uncertainty.     

A roller coaster ride: an empirical investigation of the main drivers of the international wheat price

Over the last decade, commodity prices have registered substantial booms and busts marked by extreme volatility. Wheat in particular, one of the main nonoil commodities, has registered a roller coaster in price levels which seems to be inconsistent with supply and demand fundamentals. To acutely investigate the drivers of wheat prices and quantify their impact, a vector error correction model (VECM) has been used. The exogenous variables have been distinguished into four groups: market‐specific factors, broad macroeconomic determinants, speculative components, and weather variables. The quadriangulation of the determinants will enable us to better understand the movements in wheat price and identify the specific role of each component. The results show that a mix of factors are contributing to wheat price movements, including speculation, global demand, and real effective exchange rate.     

Food Price Pass‐Through and the Role of Domestic Margin Services

The recent volatility in international agricultural markets has drawn attention to the impact of rising international agricultural prices and the induced price‐insulating measures on consumer food prices. Analyses based on simulation models on this topic typically ignore the role of domestic margin services. We extend the standard Global Trade Analysis Project (GTAP) model to allow for variations in the share of domestic margin services in consumed food across countries. This approach enables us to differentiate consumer prices from producer prices. Following the extension, the results show that domestic margin services reduce the consumer food price volatility for all countries, especially in high‐income countries, where the share of domestic margin services in final food consumption is higher. The effect of price‐insulating border policies is also reduced in the extended model. We find that our extension of the GTAP model greatly improves simulations of the 2007 surge in international agricultural prices. We validate our extension of the GTAP model by showing that the econometrically estimated food price pass‐through is decreasing with income and thus, is smaller in high‐income countries.     

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.     

Risk Management for Grain Processors and “Copulas”

The importance of calibrating hedging strategies for processors has escalated primarily due to the sharply increased volatility of futures, product, and by‐product prices. The purpose of this paper is to analyze price risk‐management strategies for wheat flour milling using copula distributions. While the application is for flour milling, it has similarities with other processing industries which confront one or more ingredients, one or more outputs, and futures for one of the commodities and/or products. The paper develops utility maximizing models encompassing expected return and risk. Alternative scenarios are evaluated. First, the models were used to derive optimal hedge ratios, as well as various measures of risk and return under alternative scenarios, and hedge durations. The results indicated hedge ratios are typically less than 1. The hedge ratios for the Mean‐value‐at‐risk (M‐VaR)‐Copula model increased with greater durations. Second, the VaR for the M‐VaR‐Copula was in most cases less than the noncopula specifications. Thus, noncopula models may over state risk as represented by VaR.     

中加菜籽油期货市场波动溢出实证研究

利用误差修正模型、BEKK-GARCH模型和格兰杰因果关系实证研究了加拿大和中国菜籽油期货市场之间的信息传导、波动溢出和价格引导关系。实证结果显示：这两个市场之间存在一定的信息传导关系;加拿大菜籽油期货市场对中国菜籽油期货市场存在显著的波动溢出效应,而中国菜籽油期货市场对加拿大菜籽油期货市场的波动溢出不显著;短期内加拿大菜籽油期货市场对中国菜籽油期货市场的价格引导作用更强些,这与加拿大菜籽油期货市场是全球菜籽油定价中心的实际相吻合,而中国菜籽油期货市场的竞争力有待进一步提升。     

Volatility Effects of Index Trading and Spillovers on US Agricultural Futures Markets: A Multivariate GARCH Approach

We examine the effects of speculation in the form of index trading on contemporaneous returns and volatility on corn, soybeans and wheat futures markets on the Chicago Board of Trade using multivariate generalised autoregressive conditional heteroscedasticity models and weekly data for 2006–2014. We also assess spillovers. Results are threefold. First, contemporaneous effects of index trading on own returns are positive and inelastic, and they are partially mitigated in the following week. Second, volatility depends positively on own past volatility, and volatility spillovers are limited. Third, index trading reduces own volatility.