Price Volatility, Nonlinearity, and Asymmetric Adjustments in Corn, Soybean, and Cattle Markets: Implications of Ethanol-Driven (Market) Shocks

Grain prices have risen sharply since 2005 and 2006 affecting livestock markets by increasing feed prices and leading to significant volatility shocks. The high price levels and magnitude of sustained high volatilities has raised concerns for many sectors of the economy, in particular those with direct relation to these markets. Policy makers are analyzing the interrelationships among these markets, and the effects of energy market shocks on agricultural markets. This study considers a threshold structure in a multivariate time-series model that evaluates these market linkages, capturing asymmetric correlations between grain and livestock prices, including volatility spillovers. We empirically study the impact of corn usage for ethanol production in the evolution of the above mentioned prices. Results are compared to previous scenarios where corn, soybean and livestock production and consumption did not face the corn demand for ethanol production. We find positive dynamic correlations between corn and soybean and feeder and fed cattle prices, consistent with the literature. And we find an inverse or negative relation between corn and feeder/calf prices for the period post mandated ethanol production, as anticipated by the literature for increased corn prices. Also, we find there are adjustment costs inhibiting price transmission between the crops and the live cattle market, in the form of modifying feeding rations. More relevantly, we identify plausible asymmetric effect on the correlations between the markets, especially when considering the period for the ethanol driven corn consumption versus previous periods of corn consumption. These asymmetric correlations are the result of spillover effects.price volatility, market linkages, thresholds, ethanol-driven shocks, asymmetric correlations, spillovers, Agribusiness, Agricultural and Food Policy, Agricultural Finance, Demand and Price Analysis, Farm Management, Financial Economics, Public Economics, Research Methods/ Statistical Methods,

Multiproduct Optimal Hedging by Time-Varying Correlations in a State Dependent model of Regime-Switching

Replaced with revised version of paper 07/29/10.Agribusiness, Demand and Price Analysis, Risk and Uncertainty,

Carry Trades: Betting Against Safe Haven

We examine contagion and flight-to-quality phenomena implied by carry strategies. More specifically, we analyze correlation dynamics between returns on a global equity index and returns on an investment strategy with a long position in high-yield and a short position in low-yield markets. Modeling information spillovers in a multivariate GARCH framework reveals that correlation increases considerably in response to a negative stock market shock. Moreover, a test for symmetry in exceedance correlation shows that correlation is indeed significantly larger for joint market downturns as opposed to joint market upturns. Our findings suggest that conditional correlation exposes carry traders to a severe diversification meltdown in times of global stock market crises.Carry trades, contagion, multivariate GARCH, exceedance correlation

Financialization, Crisis and Commodity Correlation Dynamics

We study bi-variate conditional volatility and correlation dynamics for individual commodity futures and financial assets from May 1990-July 2009 using DSTCC-GARCH (Silvennoinen and Terasvirta 2009). These models allow correlation to vary smoothly between extreme states via transition functions driven by indicators of market conditions. Expected stock volatility and money manager open interest in futures markets are relevant transition variables. Results point to increasing integration between commodities and financial markets. Higher commodity returns volatility is predicted by lower interest rates and corporate bond spreads, US dollar depreciations, higher expected stock volatility and financial traders open positions. We observe higher and more variable correlations between commodity futures and financial asset returns, particularly from mid-sample, often predicted by higher expected stock volatility. For many pairings, we observe a structural break in the conditional correlation processes from the late 1990s.commodity futures; double smooth transition; conditional correlation; financialization

Modelling Conditional Correlations in the Volatility of Asian Rubber Spot and Futures Returns

Asia is presently the most important market for the production and consumption of natural rubber. World prices of rubber are not only subject to changes in demand, but also to speculation regarding future markets. Japan and Singapore are the major futures markets for rubber, while Thailand is one of the world’s largest producers of rubber. As rubber prices are influenced by external markets, it is important to analyse the relationship between the relevant markets in Thailand, Japan and Singapore. The analysis is conducted using several alternative multivariate GARCH models. The empirical results indicate that the constant conditional correlations arising from the CCC model lie in the low to medium range. The results from the VARMA-GARCH model and the VARMA-AGARCH model suggest the presence of volatility spillovers and asymmetric effects of positive and negative return shocks on conditional volatility. Finally, the DCC model suggests that the conditional correlations can vary dramatically over time. In general, the dynamic conditional correlations in rubber spot and futures returns shocks can be independent or interdependent.Multivariate GARCH; volatility spillovers; conditional correlations; spot returns; futures returns

How Far Do Shocks Move Across Borders? Examining Volatility Transmission in Major Agricultural Futures Markets

This paper examines the level of interdependence and volatility transmission in global agricultural futures markets. We follow a multivariate GARCH approach to explore the dynamics and cross-dynamics of volatility across major exchanges of corn, wheat, and soybeans between the United States, Europe, and Asia. We account for the potential bias that may arise when considering exchanges with different closing times. The results indicate that agricultural markets are highly interrelated and there are both own- and cross- volatility spillovers and dependence among most of the exchanges. The results also show the major role Chicago plays in terms of spillover effects over the other markets, particularly for corn and wheat. Additionally, the level of interdependence between exchanges has only increased in recent years for some of the commodities.Volatility transmission, agricultural commodities, futures markets, Multivariate GARCH.

INVESTIGATING RAPESEED PRICE VOLATILITIES IN THE COURSE OF THE FOOD CRISIS

Multivariate GARCH, MATIF, rapeseed, crude oil, volatilities, food crisis, Demand and Price Analysis, Research Methods/ Statistical Methods, C32, E44, G1, Q11, Q13, Q49,

Export diversification and resource-based industrialization: the case of natural gas

For resource-rich economies, primary commodity specialization has often been considered to be detrimental to growth. Accordingly, export diversification policies centered on resource-based industries have long been advocated as effective ways to moderate the large variability of export revenues. This paper discusses the applicability of a mean-variance portfolio approach to design these strategies and proposes some modifications aimed at capturing the key features of resource processing industries (presence of scale economies and investment lumpiness). These modifications help make the approach more plausible for use in resource-rich countries. An application to the case of natural gas is then discussed using data obtained from Monte Carlo simulations of a calibrated empirical model. Lastly, the proposed framework is put to work to evaluate the performances of the diversification strategies implemented in a set of nine gas-rich economies. These results are then used to formulate some policy recommendations