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.     

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.     

A Price Analysis of U.S. Agricultural Exports in East Asian Markets

This paper examines the price competition between U.S. agricultural exports and that of its competitors in East Asia. The results show weak price competition in Japan's corn and soybean markets, and no price competition in the wheat market. U.S. cotton exports to Japan face strong price competition. In Hong Kong, U.S. market shares are low, while the demand for its rice, corn, soybeans and cotton is elastic. For South Korea and Taiwan, improved political relationships between China, South Korea, and Taiwan have caused the U.S. to lose market shares to China.     

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.     

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。     

How much of commodity price behavior can a rational expectations storage model explain?

A rational expectations competitive storage model was applied to the U.S. corn market, to assess the aptness of this framework in explaining monthly price behavior in an actual commodity market. Relative to previous models, extensive realism was added to the model, in terms of how production activities and storage costs are specified. By modeling convenience yield, “backwardation” in prices between crop years did not depend on the unrealistic assumption of zero ending stocks. Our model generated cash prices that were distributed with positive skewness and kurtosis, and mean and variance that increased over the storage season, comparable to the persistence and the occasional spikes observed in commodity prices. Futures prices were generated as conditional expectations of cash prices at contract maturity, and the variances of futures prices exhibited realistic time–to‐maturity and seasonal patterns. Model realizations of cash and futures prices over many “years” were used to demonstrate the wide variety of price behaviors that could be observed in an efficient market with a similar market structure, implying that economic and policy implications drawn from short, historical samples of prices could be misleading.     

World market integration for export and food crops in developing countries: a case study for Mali and Nicaragua

Using a generalized error correction model, this article measures and compares market integration for export cash crops versus imported food crops for Mali and Nicaragua, and computes transmission elasticities between changes in the goods’ border and domestic prices. Both Mali and Nicaragua obtain the bulk of their export revenue from a particular agricultural commodity—cotton for Mali and coffee for Nicaragua—and both import the same key staple food of rice. To reap the economic gains from this trade specialization, the two countries’ agriculture must be well‐integrated into world markets. The two countries present an important policy contrast that affects their degree of world market integration and price transmission. In Mali, a parastatal enterprise controls its cotton industry, while Nicaragua has less state direction over agriculture. Reflecting this difference, the results show that for both its main export and import commodity, Nicaragua is more integrated into world markets and has higher price transmission than Mali. The results for Nicaragua also show much higher integration and price transmission for its main agricultural export (coffee) than its major import (rice).     

中国水产品市场价格波动特征研究

文章基于2004年10月到2013年12月的月度时间序列数据,运用自回归条件异方差模型具体分析了我国水产品市场的价格波动状况。研究发现:我国水产品市场价格具有比较明显的集簇性;我国水产品市场价格波动受到前期波动的影响更大,外部条件的冲击对我国的水产品市场价格波动影响有限,高风险高回报的特征在我国水产品市场并没有得到具体的体现;但是水产品市场价格的波动率却存在杠杆效应,出现利好消息时,水产品市场价格指数的波动率的波动会减小。     

新一轮国际粮食价格上涨：原因及对中国市场的影响

目的 随着中国粮食进口不断增加,国内外市场联系越来越紧密。2020年下半年以来,国际市场粮食价格快速上涨,对国内粮食市场产生一定影响,分析国际市场价格上涨的原因和影响对确保国内粮食供应稳定、保障国家粮食安全具有重要意义。方法 文章分析了2019年以来小麦、大米、玉米、大豆4种粮食产品的国内外价格走势,从供需状况、贸易政策、气候变化等因素分析国际市场价格波动的原因,并探讨了国际价格对国内价格的影响。结果 当前全球主要粮食品种供应充足,库存仍处于较高水平,此轮国际粮食价格上涨主要是受到美国等发达国家宽松的货币政策以及疫情后全球消费逐步回暖的影响;但国际市场价格上涨对中国市场的影响总体有限,国内小麦、大米、玉米价格上涨的主因是国内消费回暖和生猪产能恢复带动的饲用需求快速增长,油用大豆受国际市场的影响较大。结论 为稳定国内粮食市场,避免国际市场的冲击,中国要进一步提升粮食综合生产能力,强化科技支撑,加强粮食储备管理,健全政策支持体系,并引导居民建立科学的消费观念。     

Volatility in Cereal Prices: Intra‐ Versus Inter‐annual Volatility

Intra‐annual (within crop year) price volatility and inter‐annual (between crop years) price volatility are measured for wheat, maize, rice, barley, oats and rye. A set of explanatory variables is used in a pooled regression to explain variations in these price volatilities. With low cereal stocks, supply (yield) shocks (defined here as volatilities, as for the price volatilities) mostly influence inter‐annual volatility while other influential factors are the crude oil price and exchange rate. Cereal demand and interest rate shocks combined with low stocks affect intra‐annual volatility, while other explanatory factors include exchange rate and crude oil price shocks. The derivatives market activity appears to have no significant effect on either intra‐ or inter‐annual volatility. In contrast, large cereal stocks and a well‐functioning international cereal market reduce the effects of shocks in the explanatory variables on both intra‐ and inter‐annual volatilities.     

中国粮食价格支持的政策优化与未来走向——基于美国指控中国粮食价格支持过度的分析

[目的]分析2015年美国DTB联合公司(DTB Associates,LLP)针对中国粮食(仅包括小麦、大米和玉米)的价格支持力度过度的指控是否合理,并明确我国实际的粮食市场价格支持情况。[方法]文章根据市场价格支持水平的基本计算公式以及我国向WTO的通报文件和公开资料,对2013/2014年度我国小麦、大米和玉米的实际市场价格支持水平进行了重新测算,并将测算结果与指控内容进行了对比分析和讨论。[结果]测算结果表明,2013/2014年度,我国对小麦、大米和玉米的实际市场价格支持水平分别为168亿元、-221亿元和36亿元,远远低于DTB联合公司的公布结果。[结论]美国DTB联合公司对我国粮食市场价格支持过度的指控不实,主要是指标选取有误和数据选取不合理导致了其对我国粮食价格支持力度过高的判断。为从容应对以后可能面临的国际指控和调查,我国需要在支持手段、支持领域等方面进一步优化粮食市场价格支持政策。     

Inter‐ and intra‐seasonal crop acreage response to international food prices and implications of volatility

Understanding how producers make decisions to allot acreage among crops and how decisions about land use are affected by changes in prices and their volatility is fundamental for predicting the supply of staple crops and, hence, assessing the global food supply situation. This study makes estimations of monthly (i.e., seasonal) versus annual global acreage response models for the world's principal staple food crops: wheat, corn, soybeans, and rice. Primary emphasis is given to the magnitude and speed of the allocation process. Estimation of intra‐annual acreage elasticity is crucial for expected food supply and for input demand, especially in the light of the recent short‐term volatility in food prices. The econometric results indicate that global crop acreage responds to crop prices and price risks, input costs as well as a time trend. Depending on respective crop, short‐run elasticities are about 0.05 to 0.40; price volatility tends to reduce acreage for some of the crops; comparison of the annual and the monthly acreage response elasticities suggests that acreage adjusts seasonally around the globe to new information and expectations. Given the seasonality of agriculture, time is of an essence for acreage response. The analysis indicates that acreage allocation is more sensitive to prices in the northern hemisphere spring than in winter and the response varies across months.     

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.     

Price volatility and rational expectations in a sectoral framework commodity model: a multivariate GARCH approach

This article explores supply response models in a rational expectations framework with endogenous risk by using a multivariate generalized autoregressive conditional heteroskedasticity model with Cholesky decomposition. This approach allows the incorporation of price volatility as a risk factor into the supply response of a primary commodity sector that is composed of several markets of homogenous products. The model is applied to the Greek meat sector, which is composed of four major meat categories, that is, beef, lamb, pork, and broiler, and thus the model for the entire market includes supply and demand equations for all the four meat markets, which are estimated simultaneously. The empirical results confirm that price volatility is a significant risk factor in Greek meat production and also provide useful implications about the cost factors of production. Furthermore, the empirical findings show that the last reform of the Common Agricultural Policy seems to have had a negative effect on beef and lamb production in Greece.     

我国粮食市场风险的度量与评估  ———基于风险价值法的实证分析

该文利用风险价值法,以我国小麦、玉米、粳稻、早籼稻、晚籼稻、大豆的市场价格为研究对象,度量了我国粮食市场的风险大小,评估了我国粮食市场风险的发生程度。结果表明:我国粮食市场是一个风险发生频率较高的市场,并且还是一个高风险市场;不同品种粮食市场风险的发生大小有所不同,其中大豆的市场风险值最大,其次为玉米、粳稻、早籼稻、晚籼稻,小麦的市场风险值最小;粮食市场价格下跌风险与市场价格上涨风险的发生频率基本相当,两者同等重要,在重点关注粮食价格上涨风险的同时,更应重视粮食价格下跌所产生的风险。     

Rural credit and agricultural supply in Brazil

The objective of this study is to determine the financing impact of total expenditure on the use of agriculture inputs (fertilizers, labor, and pesticides), and the output of cotton, rice, beans, corn, soybean, and wheat in Brazil. We study the period 1976–2005. The analysis is based on duality applied to the production theory. The output supplies and conditioned input demands are estimated from a translog multi‐output, multi‐input restricted profit function, where the total production credit is used as proxy of the total expenditure. Farmer expectations with respect to crop prices are incorporated to the estimation based on the quasi‐rational expectation model. The output and input responses to the total expenditure are positive and statistically significant except for cotton, wheat, fertilizer, and pesticides. The short‐run output supply response to own prices is inelastic, except for wheat, which presents elastic response to its price. Acreage has a positive impact on the output supply and it is influenced by land productivity. The main conclusion is that farmers face budget restrictions to purchase inputs, and a government credit program might increase the agricultural supply.     

Assessing the Vulnerability to Price Spikes in Agricultural Commodity Markets

We examine empirically the predictability of conditions associated with a higher probability of a price spike in agricultural commodity markets. We find that the forward spread is the most significant indicator of probable price jumps in maize, wheat and soybeans futures markets, a result which is in line with the ‘Theory of Storage’. We additionally show that some option-implied variables add significant predictive power when added to the more standard information variable set. Overall, the estimated probabilities of large price increases from our probit models exhibit significant correlations with historical sudden market upheavals in agricultural markets.     

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.     

A quantile autoregression analysis of price volatility in agricultural markets

This paper investigates the dynamics of agricultural price volatility based on a quantile autoregression (QAR) model. The QAR model provides a flexible representation of the distribution of price and its dynamics. The approach is applied to U.S. wheat and corn markets over the period of 1980–2017. This period is of significant interest as it covers important changes in agricultural policy and increased reliance on markets. The price analysis is conducted conditional on stocks held in the previous period. We show how increasing previous stocks shift the price distribution to the left and decreases the odds of facing price spikes (by shifting down the upper tail of the price distribution). Our analysis also examines the effects of changing public stocks on prices. For both wheat and corn, this reflects changing agricultural policy, contrasting the 1980s (when public stocks were relatively high) with the post-2005 period (when public stocks became zero). We document how higher public stock ratio during the previous period did not lower the odds of facing price spikes. Applied to the wheat and corn markets, we also uncover evidence of local dynamic instability in the upper tail of the price distribution, suggesting that price instability becomes more pronounced when previous stocks are low.     

Impacts of Market Reform on Spatial Volatility of Maize Prices in Tanzania

Maize is one of the major staples and cash crops for many Tanzanians. Excessive volatility of maize prices destabilises farm income in maize‐growing regions and is likely to jeopardise nutrition and investment in many poor rural communities. This study investigates whether market reform policies in Tanzania have increased the volatility of maize prices, and identifies regional characteristics that can be attributed to the spatial price volatility. To achieve the objectives, an autoregressive conditional heteroskedasticity in mean (ARCH‐M) model is developed and estimated in this study. Results show that the reforms have increased farm‐gate prices and overall price volatility. Maize prices are lower in surplus and less developed regions than those in deficit and developed regions. Results also show that the developed and maize‐deficit regions, and regions bordering other countries have experienced less volatile prices than less developed, maize‐surplus and non‐bordering regions. Our findings indicate that investments in communication and transportation infrastructures from government and donor countries are likely to increase inter‐regional and international trade, thereby reducing the spatial price volatility in Tanzanian maize prices in the long run.