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.     

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。     

A Heteroskedastic Multivariate Tobit Analysis of Price Dynamics in the Presence of Price Floors

This article presents an econometric analysis of the effects of price floors on price dynamics and price volatility in a multimarket context. We investigate the implications of a government price-support program providing a censoring mechanism to the price determination process. The analysis uses a dynamic multivariate Tobit model under time-varying volatility. The model is applied to the U.S. dairy markets with a special focus on the effects of government price-support programs in a period of market liberalization. The econometric analysis provides useful information on the multimarket effects of price supports on price dynamics and price volatility.     

中国碳排放权交易市场收益率波动性特征研究

以北京、上海、广东、湖北和重庆碳排放权交易市场为研究对象,运用GARCH族模型研究中国碳排放权交易市场收益率波动性特征。结果表明,5个碳排放权交易市场收益率的波动聚集性、持续性表现不完全一致;北京、上海和重庆存在负向的杠杆效应,广东和湖北不存在杠杆效应;从波动溢出效应关系看,5个碳排放权交易市场间的整体联动性不强;运用方差比率检验法得出,5个碳排放权交易市场均未达到弱势有效市场。这些特征反映出中国碳排放权交易市场的运行机制仍然存在缺陷,建议加强顶层设计,完善碳排放权交易体系。     

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.     

Food–oil volatility spillovers and the impact of distinct biofuel policies on price uncertainties on feedstock markets

Over recent decades, the link between crude oil and agricultural markets has been reinforced following the introduction of biofuels. We use timely measures of (co)variation spillovers to analyze the role of crude oil in shaping price uncertainties of agricultural commodities, which are largely used as biofuel feedstocks. Our sectoral- and market-specific measures distinguish tranquil (1995–2005) and crisis episodes (2006–2015), as well as periods during which either consumption mandates or tax credits were enacted to spur biofuels. During the crisis period, crude oil volatility transmissions account for 16% (20%) of price uncertainties in ethanol (biodiesel) feedstock markets on average. Moreover, we find evidence of enhanced volatility transmissions under tax credit regimes compared with consumption mandates. The results from pooled regressions confirm stronger volatility transmissions by about 12% under the enactment of tax credits.     

Why does on-farm storage fail to mitigate price volatility?

We analyze the role of farm stock management on price volatility under liquidity constraints and heterogeneous price expectations. In commodity markets, speculative behaviors by stockholders tend to reduce price volatility, but this is not the case in certain agricultural markets, where speculation by farmers regarding decisions to sell or store grain is subject to liquidity constraints and heterogeneous price expectations. Like stockholders, most farmers sell grain if they expect a price drop in the near future, but unlike stockholders, they are not necessarily able to purchase grain if they expect a price increase in the next period. Heterogeneous price expectations can also lead to suboptimal storage decisions, further increasing price volatility. For these reasons, the storage management behavior of farmers often fails to mitigate price drops in the way that speculation by stockholders does. We merge historical data on maize prices and household storage collected in Burkina Faso in order to build a dynamic panel over the 2005–2012 period. We show that carryover from one season to the next is associated with unexpected price drops during the preceding lean season and that carryover is associated with more frequent unexpected price drops following the subsequent post‐harvest season.     

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.     

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.     

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.     

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.     

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。     

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.     

产业链视角下乳制品价格溢出效应研究——基于VAR-BEKK-GARCH(1,1)模型

奶业产业链是乳制品价格形成的基础,从产业链着手有助于发现乳制品价格溢出效应的本质特征。本文选取牛奶、酸奶、婴幼儿奶粉、老年奶粉作为乳制品的代表,基于2010年5月至2018年5月乳制品产业链月度价格数据,使用VAR-BEKK-GARCH(1,1)模型分析乳制品产业链各环节间的价格溢出效应。研究发现:婴幼儿奶粉产业链上、中、下游价格间存在显著的单向均值溢出效应,而牛奶、酸奶、老年奶粉产业链的中游对上游、下游对中游价格存在显著的单向均值溢出效应;牛奶、酸奶、婴幼儿奶粉、老年奶粉产业链各环节价格在自身和彼此间具有显著双向波动溢出效应,但从显著性水平来看,牛奶产业链和婴幼儿奶粉产业链各环节间的双向波动溢出效应最为明显。     

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.     

Extent and possible causes of intrayear agricultural commodity price volatility

Wheat, corn, rice, soybeans, and cotton experienced higher volatility in the second half of the 2000s. For the sample at hand, the unit root tests only validate a new period of high volatility for wheat and cotton. If in the next couple of years however, corn, rice and soybeans maintain their higher volatility, a new period of high volatility may also be validated statistically. Regarding the factors driving the intrayear volatility GMM estimates show that “commodity market fundamentals” i.e., the stock‐to‐use ratio and to a lesser extent the degree of internationalization, are the most systematically statistically significant coefficients among commodities. Over time, consecutive low stock‐to‐use ratios and a thin international market provoke typically high volatility. Speculative activity and liquidity in the agricultural derivative market have a stabilizing effect on the spot price, if any. Finally, “common macro” factors significantly impact volatility, especially the volatility of petrol and of exchange rates; their dispersion importance over the sample is quite sizeable. However, it is difficult to establish a link between, on the one hand, loose monetary policy, business cycle and inflation, and, on the other hand, commodity price volatility, as the sign of the estimated coefficient changes depending on the commodity and the estimated elasticities are quite low.     

Price and Volatility Transmission and Market Power in the German Fresh Pork Supply Chain

We investigate the relationship between the transmission of price volatility and market power in the German fresh pork supply chain. We use a theoretical model underpinning this relationship followed by an empirical application that uses monthly farm, slaughterhouse and retail pork price data for the period 2000–2011. We examine both the relationships of market power with price level transmission and price volatility transmission in the chain. We use a vector error correction model and least squares regressions to analyse price transmission and price volatility transmissions, respectively. Results show that retail market power limited both types of transmissions. Competition inducing policy measures coupled with measures that support price risk management initiatives of chain actors are suggested.     

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.     

What drives stock market integration? An analysis using agribusiness stocks

This article explores the drivers of regional stock market integration with a focus on the agribusiness sector across relevant regional trade blocs around the world. We implement panel cointegration models to analyze the stock indices of agribusiness firms in the Southern Common Market (MERCOSUR), European Union (EU), Asia‐Pacific Economic Cooperation (APEC), and North American Free Trade Agreement (NAFTA). Based on the literature on market integration and stock return pricing, we identify nine possible determinants of stock market integration, which we separate into three categories: individual market performance, macroeconomic conditions, and agricultural trade. In our analysis, we account for agriculture‐specific factors to control for possible structural shifts in financial markets regimes by including the two main commodity price bubbles during last 20 years. Our results show that most of the variables included in our categories have been important factors in promoting regional stock market integration. Moreover, integration among regional stock markets was strengthened by the implementation of trade agreements. This effect is stronger in trade blocs with fewer members, such as NAFTA and MERCOSUR, compared with larger and more heterogeneous blocs, such as the EU and APEC.