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.     

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.     

Using a functional approach to test trending volatility in the price of Mexican and international agricultural products

In this article, we extend the traditional GARCH(1,1) model by including a functional trend term in the conditional volatility of a time series. We derive the main properties of the model and apply it to all agricultural commodities in the Mexican CPI basket, as well as to the international prices of maize, wheat, swine, poultry, and beef products for three different time periods that implied changes in price regulations and behavior: before the North American Free Trade Agreement (NAFTA; 1987–1993), post‐NAFTA (1994–2005), and commodity supercycle (2006–2014). The proposed model seems to adequately fit the volatility process and, according to heteroscedasticity tests, also outperforms the ARCH(1) and GARCH(1,1) models, some of the most popular approaches used in the literature to analyze price volatility. Our results show that, consistent with anecdotal evidence, price volatility trends increased from the period 1987–1993 to 1994–2005. From 1994–2005 to 2006–2014, trends decreased but the persistence of volatility increased for most products, especially for international commodities. In addition, we identify some agricultural products such as avocado, beans, and chicken that, due to their increasing price volatility trends in the 2006–2014 period, may present a risk for food inflation in the short run.     

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.     

Measuring the Volatility of Wheat Futures Prices on the LIFFE

Agricultural prices rose dramatically in 2007 and have subsequently fluctuated at high levels. This paper estimates the volatility of daily wheat futures prices on the Euronext/London International Financial Futures and Options Exchange for 1996–2012 using an exponential generalised autoregressive conditional heteroscedasticity model with a constant (price) elasticity of variance (CEV) and a broken trend. Results show that volatility is highly persistent; there is a structural break in volatility in June 2007 when volatility rose by 10%; subsequently, the wheat futures price has become more volatile; and the CEV is 0.04.     

“保险+期货”服务地方优势特色农产品价格风险管理——运行机制、突出问题与政策融合空间

本文在对"保险+期货"服务地方特色农产品价格风险管理的运行机制进行理论论证的基础上,总结了现阶段影响"保险+期货"模式的六大突出问题——产品标准化、倒向型定价、对冲磨损、资金来源、基差风险和规模效应。进一步地,以白糖(糖料蔗)价格指数保险试点为案例,剖析了"保险+期货"与政策性农险相融合的发展空间,阐释了"保险+期货"项目在提升边际报酬和资金利用效率方面的改进方式和途径。基于此,本文总结并提出以"强化微观主体基础、扩大财政空间增量、健全配套期货工具、营造宏观制度环境和完善效应评价体系"为重点的"保险+期货"发展方向和建议。     

“保险+期货”服务地方优势特色农产品价格风险管理——运行机制、突出问题与政策融合空间

本文在对"保险+期货"服务地方特色农产品价格风险管理的运行机制进行理论论证的基础上,总结了现阶段影响"保险+期货"模式的六大突出问题——产品标准化、倒向型定价、对冲磨损、资金来源、基差风险和规模效应。进一步地,以白糖(糖料蔗)价格指数保险试点为案例,剖析了"保险+期货"与政策性农险相融合的发展空间,阐释了"保险+期货"项目在提升边际报酬和资金利用效率方面的改进方式和途径。基于此,本文总结并提出以"强化微观主体基础、扩大财政空间增量、健全配套期货工具、营造宏观制度环境和完善效应评价体系"为重点的"保险+期货"发展方向和建议。     

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.     

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。     

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。     

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.     

Cotton market integration and the impact of China's new exchange rate regime

This article studies the integration of China's cotton market with the international market, especially the U.S. market. Investigating the futures prices from the Intercontinental Exchange (ICE) in the U.S. and the Zhengzhou Commodity Exchange (ZCE) in China with several time series models, we find that a long‐run cointegration relationship exists between these two series. The two markets share price transmissions, and based on results from an Autoregressive Conditional Heteroskedasticity (ARCH) model, we find their price volatilities are similar. We argue that China's recent exchange rate reform and its gradual liberalization in bilateral cotton trade since it joined World Trade Organization have had important impacts on these futures markets. Based on these findings, several important economic and policy implications are derived.     

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.     

Market interdependence and volatility transmission among major crops

This article provides a comprehensive analysis of the dynamics of volatility across major agricultural commodities in the United States. Volatility interactions across markets may lower the effectiveness of diversification strategies to mitigate price risks and should be taken into account when analyzing the pricing behavior of different agricultural commodities. We follow a multivariate GARCH approach to evaluate the time evolution of conditional correlations and volatility transmission across corn, wheat, and soybeans price returns on a daily, weekly, and monthly basis. The period of analysis is from 1998 to 2012. The estimation results indicate a lack of lead‐lag relationships between corn, wheat, and soybeans price returns at the mean level. We find, however, important volatility spillovers across commodities, particularly at the weekly and monthly level. Wheat and corn seem to play a major role in terms of volatility transmission. Despite the supposed higher financial market integration of agricultural commodities, we do not observe that agricultural markets have become more interdependent in recent years.     

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.     

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.     

Hedging Opportunities for Canadian

The unprecedented commodity price volatility in the last decade has resulted in a growing interest in futures trading by farmers. One of the major reasons often provided for the usefulness of commodity futures markets is that they provide a mechanism whereby producers can shift the risk of price change onto others. Interestingly, little research has been conducted on the effectiveness of the WCE as a hedging tool for farmers.
The objective of this paper was to investigate the extent to which the futures contracts for rapeseed, barley and flaxseed can be used by farmers in order to reduce price risk (measured by volatility). Drawing on earlier literature, the theory of hedging was reviewed and formulae for estimating the optimal hedge and the effectiveness of hedging were presented. An empirical analysis determined that the Winnipeg rapeseed, barley and flaxseed futures contracts are very useful in terms of allowing a producer the opportunity to reduce exposure to price risk.     

Are commodity prices chaotic?

We conduct tests for the presence of low‐dimensional chaotic structure in the futures prices of four important agricultural commodities. Though there is strong evidence of non‐linear dependence, the evidence suggests that there is no long‐lasting chaotic structure. The dimension estimates for the commodity futures series are generally much higher than would be for low dimension chaotic series. Our test results indicate that autoregressive conditional heteroskedasticity (ARCH)‐type processes, with controls for seasonality and contract‐maturity effects, explain much of the non‐linearity in the data. We make a case that employing seasonally adjusted price series is important in obtaining robust results via some of the existing tests for chaotic structure. Finally, maximum likelihood methodologies, that are robust to the non‐linear dynamics, lend strong support to the Samuelson hypothesis of maturity effects in futures price changes.     

Modeling regime‐dependent agricultural commodity price volatilities

In stark contrast to financial markets, relatively little attention has been given to modeling agricultural commodity price volatility. In recent years, numerous methodologies with various strengths have been proposed for modeling price volatility in financial markets. We propose using a mixture of normals with unique GARCH processes in each component for modeling agricultural commodity prices. While a normal mixture model is quite flexible and allows for time varying skewness and kurtosis, its biggest strength is that each component can be viewed as a different market regime and thus estimated parameters are more readily interpreted. We apply the proposed model to ten different agricultural commodity weekly cash prices. Both in‐sample fit and out‐of‐sample forecasting tests confirm that the two‐state NM‐GARCH approach performs better than the traditional normal GARCH model. A significant and state‐dependent inverse leverage effect is detected only for pork in the regime where the price is expected to drop, indicating the volatility in this regime tends to increase more following a realized price rise than a realized price drop.     

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.