Volatility Spillovers in Agricultural Commodity Markets: An Application Involving Implied Volatilities from Options Markets

Replaced with revised version of paper 07/22/11 and 2/14/2012.Volatility Spillovers, Implied Volatility, Structural Change, Risk and Uncertainty,

Crustal Azimuthal Anisotropy Beneath the Central North China Craton Revealed by Receiver Functions

To characterize crustal anisotropy beneath the central North China Craton (CNCC), we apply a recently developed deconvolution approach to effectively remove near-surface reverberations in the receiver functions recorded at 200 broadband seismic stations and subsequently determine the fast orientation and the magnitude of crustal azimuthal anisotropy by fitting the sinusoidal moveout of the P to S converted phases from the Moho and intracrustal discontinuities. The magnitude of crustal anisotropy is found to range from 0.06 s to 0.54Â s, with an average of 0.25 ± 0.08Â s. Fault-parallel anisotropy in the seismically active Zhangjiakou-Penglai Fault Zone is significant and could be related to fluid-filled fractures. Historical strong earthquakes mainly occurred in the fault zone segments with significant crustal anisotropy, suggesting that the measured crustal anisotropy is closely related to the degree of crustal deformation. The observed spatial distribution of crustal anisotropy suggests that the northwestern terminus of the fault zone probably ends at about 114°E. Also observed is a sharp contrast in the fast orientations between the western and eastern Yanshan Uplifts separated by the North-South Gravity Lineament. The NW-SE trending anisotropy in the western Yanshan Uplift is attributable to fossil crustal anisotropy due to lithospheric extension of the CNCC, while extensional fluid-saturated microcracks induced by regional compressive stress are responsible for the observed ENE-WSW trending anisotropy in the eastern Yanshan Uplift. Comparison of crustal anisotropy measurements and previously determined upper mantle anisotropy implies that the degree of crust-mantle coupling in the CNCC varies spatially

Dynamic Cross-Hedge Ratios: An Application of Copula Models

In this study, we propose a new approach to estimating optimal dynamic cross-hedge ratios. In particular, we apply copula models to discuss the use of corn futures contracts to cross hedge grain sorghum, and the use of Kansas wheat futures contracts to cross hedge barley. Hedge (or cross-hedge) ratios are generally estimated by using the variances of cash and futures returns and the correlation between these returns. We compute the time-varying variances of cash and futures returns by applying the Error Correction Model (ECM) with GARCH error terms. The time-varying correlation term in the dynamic cross-hedge ratio is obtained from eight copula models – two elliptical copulas (Gaussian and Student’s-t) and six Archimedean copulas (Clayton, rotated Clayton, Gumbel, rotated Gumbel, Frank, and Plackett). We use maximum likelihood estimation techniques to estimate the copula models and compare the performance of these copula models by their maximum likelihood values. Results confirm the significant linkages between these markets and demonstrate the effectiveness of cross-hedging as a mechanism for managing price risks

Mixed-Copula Based Extreme Dependence Analysis: A Case Study of Food and Energy Price Comovements

Rich empirical literature has investigated the price transmission among spatially separated and vertically linked markets. In this study, we fill a gap in the price transmission literature by investigating extreme dependence that allows varying general dependence structure between extreme and non-extreme market conditions (through mixed copula functions), and changing degree of co-movements (through time-varying dependence parameters for any given copula functions). Our work is a combination and generalization of time-varying attributes with the mixture model idea. The data used for the analysis are weekly prices for US crude oil, ethanol, and corn from Jan 2000 through December 2013. Our results demonstrate that time-varying attributes in extreme price co-movements can result from many reasons such as government interventions, financial contagion, disease outbreaks, and altering consumer tastes. It is thus a useful extension and generalization of existing approaches for modeling price transmission that has appeared in the literature

Volatility Spillovers in Agricultural Commodity Markets: An Application Involving Implied Volatilities from Options Markets

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

A New Approach to Investigate Market Integration: a Markov-Switching Autoregressive Model with Time-Varying Transition Probabilities

In this study, we develop a new approach to investigate spatial market integration. In particular, it is a Markov-Switching autoregressive (MSAR) model with time-varying state transition probabilities. Studying market integration is an effective way to test whether the law of one price holds across geographically separated markets, in other words, to test whether these markets perform efficiently or not. In this model, we assume that the parameters depend on a state variable which describes two unobservable states of markets – non-arbitrage and arbitrage – and is governed by a time-varying transition probability matrix. The main advantage of this model is that it allows transition probabilities to be time-varying. The probability of being in one state at time t depends on the previous state and the previous levels of market prices. An EM (Expectation-Maximization) algorithm is applied in the estimation of this model. For the empirical application, we examine market integration among four regional corn (Statesville, Candor, Cofield, Roaring River) and three regional soybean markets (Fayetteville, Cofield, and Creswell) in North Carolina. The prices of these markets are quoted daily from 3/1/2005 to 6/30/2010. Six pairwise spatial price relationships for the corn markets, and three pairwise spatial price relationships for the soybean markets are examined. Our results demonstrate that significant regime switching relationships characterize these markets. This has important implications for more conventional models of spatial price relationships and market integration. Our results are consistent with efficient arbitrage subject to transactions costs

Effect of pH on the structure and morphology of W18O49 nanowires and their electrochromic properties

In wet-chemistry processes, pH value is an important parameter that can be used to control the microstructures of the as-grown nanostructures. In this work, W18O49 nanowires with crystalline@amorphous core-shell structures were synthesized by controlling the pH of the precursor solutions in a hydrothermal reaction. Due to surface functionalization by ethylene glycol (EG) groups, the hydrothermally grown W18O49 nanowires could be easily dispersed in aqueous environment, thus enabling the fabrication of electrochromic thin films of W18O49 nanowires by a simple spray-drying process. The optimized W18O49 nanowire films showed a large optical modulation (AT) of 81.1% at 633 nm, short response time (coloring/bleaching time rc/rb = 7.9 s/3.9 s), good cycle stability (AT retention was 84.5% after 1000 cycles), and the excellent memory effect (the color withstood for 36000s after turning off the voltage). Furthermore, the electrochromic device (ECD) (4 x 4 cm2) based on the W18O49 nanowires exhibits a large optical modulation of 56.6%, short response time (rc = 7.6 s, rb = 2.7 s), and superior coloration efficiency (CE) of 64 cm2 C-1. Finally, by simply amplifying the developed processes, a large-area electrochromic device (10 x 10 cm2) was successfully prepared, which implies the possibility of large-area spraying process for practical applications