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Abstract

This article provides a new approach to analyze the issue of volatility spillovers. In particular, we investigate relationships and transmissions between implied volatilities in corn and soybean markets – two of the most important agricultural commodity markets in the United States. Using weekly average data from 2001 to 2010, we estimate a VAR model with Fourier seasonal components as exogenous variables. Results from this model indicate that volatility spillovers exist from the corn market to the soybean market, but there is no volatility spillover from the soybean market to the corn market. Impulse response functions from this model show that a standard positive shock in the implied volatility of corn has a positive impact on responses of the implied volatility of soybeans. However, responses of the implied volatility of corn to a shock in the soybean market are not significant. To examine the time invariance property of this model, we conduct three bootstrap versions of Chow tests (sample-split, break-point, and Chow forecast). All of these tests suggest significant structural break points in several time periods. To improve the accuracy of our model, we develop a threshold VAR model with four regimes that depend on previous levels of volatilities. Results from the threshold VAR model indicate that when both volatilities are relatively low, volatility spills over from the corn market to the soybean market, but when the implied volatility of soybeans is relatively high, volatility spillover effects reveal an opposite direction. Finally, using futures prices, we estimate a BEKK-GARCH model, which is commonly used to investigate volatility spillover effects. Results from the BEKK model show that volatility spillovers exist between the two markets, which is different from what we have found using implied volatilities.

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