The Shape of the Optimal Hedge Ratio: Modeling Joint Spot-Futures Prices using an Empirical Copula-GARCH Model

Commodity cash and futures prices have been rising steadily since 2006. As evidenced by the April 2008 Commodity Futures Trading Commission Agricultural Forum, there is much concern among traditional futures and options market participants that the usefulness of commodity derivatives has been compromised. When basis risk is particularly high, dynamic hedging methods may be helpful despite their complexity and higher transaction costs. To assess the potential benefits of dynamic hedging in volatile times, this paper proposes a novel, empirical copula-based method to estimate GARCH models and to compute time-varying hedge ratios. This approach allows a nonlinear, asymmetric dependence structure between cash and futures prices. The paper addresses four principal questions: (1) Does the empirical copula-GARCH method overcome traditional limitations of dynamic hedging methods? (2) How does the empirical copula- GARCH hedging approach perform, for storable agricultural commodities, compared with traditional GARCH and Minimum Variance (static) hedging methods? (3) Is dynamic hedging more or less effective in the post-2006 biofuels expansion time period? (4) How sensitive is the ranking of methods to the hedging effectiveness criterion used? Preliminary findings suggest that the empirical copula-GARCH approach leads to superior hedging effectiveness based on some, but not all, risk criteria.Agricultural Finance,

Water calcium concentration modifies whole-body calcium uptake in sea bream larvae during short-term adaptation to altered salinities

Whole-body calcium uptake was studied in gilthead sea bream larvae (9–83·mg) in response to changing environmental salinity and [Ca2+]. Calcium uptake increased with increased fish size and salinity. Fish exposed to calcium-enriched, diluted seawater showed increased calcium uptake compared with fish in diluted seawater alone. Calcium uptake was unchanged in Na+- enriched, diluted seawater. Overall, [Ca2+], and not salinity/osmolarity per se, appears to be the main factor contributing to calcium uptake. By contrast, drinking was reduced by a decrease in salinity/osmolarity but was little affected by external [Ca2+]. Calculations of the maximum contribution from drinking-associated calcium uptake showed that it became almost insignificant (less than 10%) through a strong decrease in drinking rate at low salinities (0–8‰). Diluted seawater enriched in calcium to the concentration present in full-strength seawater (i.e. constant calcium, decreasing salinity) restored intestinal calcium uptake to normal. Extra-intestinal calcium uptake also benefited from calcium addition but to a lesser extent

Impurity segregation in graphene nanoribbons

The electronic properties of low-dimensional materials can be engineered by doping, but in the case of graphene nanoribbons (GNR) the proximity of two symmetry-breaking edges introduces an additional dependence on the location of an impurity across the width of the ribbon. This introduces energetically favorable locations for impurities, leading to a degree of spatial segregation in the impurity concentration. We develop a simple model to calculate the change in energy of a GNR system with an arbitrary impurity as that impurity is moved across the ribbon and validate its findings by comparison with ab initio calculations. Although our results agree with previous works predicting the dominance of edge disorder in GNR, we argue that the distribution of adsorbed impurities across a ribbon may be controllable by external factors, namely an applied electric field. We propose that this control over impurity segregation may allow manipulation and fine-tuning of the magnetic and transport properties of GNRs.Comment: 5 pages, 4 figures, submitte

The phosphorus requirements for silage production on high fertility soils

peer-reviewedThe minimum phosphorus requirement for a mid-season ryegrass was investigated under cutting conditions over a 10-year period at each of three Teagasc sites (Clonroche, Johnstown Castle and Oak Park) in southeast Ireland. Treatments consisted of 0, 20, 30, 40, and 50 kg ha–1 year–1 P applied in autumn. Generally, there were three grass cuts each year and soil samples were taken after the third cut prior to the application of P. Nitrogen and potassium fertiliser was applied to ensure maximum grass yield. There was an emerging treatment effect over time as evidenced by the significance of the treatment × year interaction. The effect of site varied with year reflecting the variability in weather and number of cuts taken at the individual sites. A treatment effect on annual first-cut-silage yield was observed. The largest treatment difference for dry matter (DM) yield of first-cut silage was between the control and the P treated plots (0.32 t/ha). The results show that the draw down of soil-P reserves was adequate to maintain yield for a number of years without additional fertiliser P application. Initial soil tests indicated moderate to high soil test P levels (STP) as measured by the Morgan’s test. Application of P at equivalent to removal rates did not maintain STP. The results suggest that application of a regular small maintenance dressing of P, replacing realistic removals, is the most appropriate fertiliser application strategy.McDonagh/Albatros Fertiliser

Gill transcriptome response to changes in environmental calcium in the green spotted puffer fish

Abstract Background Calcium ion is tightly regulated in body fluids and for euryhaline fish, which are exposed to rapid changes in environmental [Ca2+], homeostasis is especially challenging. The gill is the main organ of active calcium uptake and therefore plays a crucial role in the maintenance of calcium ion homeostasis. To study the molecular basis of the short-term responses to changing calcium availability, the whole gill transcriptome obtained by Super Serial Analysis of Gene Expression (SuperSAGE) of the euryhaline teleost green spotted puffer fish, Tetraodon nigroviridis, exposed to water with altered [Ca2+] was analysed. Results Transfer of T. nigroviridis from 10 ppt water salinity containing 2.9 mM Ca2+ to high (10 mM Ca2+ ) and low (0.01 mM Ca2+) calcium water of similar salinity for 2-12 h resulted in 1,339 differentially expressed SuperSAGE tags (26-bp transcript identifiers) in gills. Of these 869 tags (65%) were mapped to T. nigroviridis cDNAs or genomic DNA and 497 (57%) were assigned to known proteins. Thirteen percent of the genes matched multiple tags indicating alternative RNA transcripts. The main enriched gene ontology groups belong to Ca2+ signaling/homeostasis but also muscle contraction, cytoskeleton, energy production/homeostasis and tissue remodeling. K-means clustering identified co-expressed transcripts with distinct patterns in response to water [Ca2+] and exposure time. Conclusions The generated transcript expression patterns provide a framework of novel water calcium-responsive genes in the gill during the initial response after transfer to different [Ca2+]. This molecular response entails initial perception of alterations, activation of signaling networks and effectors and suggests active remodeling of cytoskeletal proteins during the initial acclimation process. Genes related to energy production and energy homeostasis are also up-regulated, probably reflecting the increased energetic needs of the acclimation response. This study is the first genome-wide transcriptome analysis of fish gills and is an important resource for future research on the short-term mechanisms involved in the gill acclimation responses to environmental Ca2+ changes and osmoregulation.Peer Reviewe

The Price Shock Transmission during the 2007-2008 Commodity Bull Cycle: A Structural Vector Auto-Regression Approach to the "Chicken-or-Egg" Problem

Commodity and energy prices have exhibited an unprecedented increase between October 2006 and July 2008, only to fall sharply during the last months of 2008. Many explanations have been offered to this phenomenon, including steadily increasing demand from China and India, large mandated increases in ethanol production, droughts in some key agricultural producer countries, production plateaus in some major oil-producing countries, refinery capacity limits, demand pressure from the derivatives market owing to the diversification properties of commodities, etc. Clearly, agricultural input, output, and energy products are closely related economically. In addition to biofuels, the connection points include nitrogen-based solution liquid fertilizers, fossil fuels used in agricultural production, limited acreage available for field crops, etc. While all these price variables are, evidently, closely connected, it is not entirely clear how exogenous price shocks are transmitted through the system, and whether particular commodities drive up the prices of other commodities. The proposed paper attempts to address this "chicken-or-egg" problem by applying the Structural Vector Autoregression (SVAR) framework to the analysis of a wide range of commodity prices. The purpose of this paper is to model and estimate an SVAR model of multiple commodity prices in order to: (i) Investigate the transmission mechanism of the price shocks associated with the commodity boom of 2006-2008 and subsequent bust and identify changes (if any) relative to earlier time periods (e.g. 2004-2006), (ii) Evaluate the possibly asymmetrical relationship between different commodity and energy price variables and (iii) Test hypotheses of causality in a time series definition (Granger and graph-theoretic). The methodology consists of defining and estimating a structural VAR model, studying impulse response functions and the variance decomposition, and testing for the direction of causality. Given that a longstanding problem is the sensitivity of the results to identifying assumptions, graph analysis is used here as it is a promising approach to identify the structure of the variance-covariance matrix and therefore overcome the observational equivalence of various reduced-form models implied by different identification approaches. The main contribution of this paper is to provide a tentative answer to the question of how agricultural input, output and energy product prices are related and whether this relationship has changed in recent years.Commodity prices, commodity bull cycle, energy prices, Granger-causality, graph theory, structural VAR., Agribusiness, Agricultural and Food Policy, Agricultural Finance, Demand and Price Analysis, Financial Economics, Research Methods/ Statistical Methods,

A Generalised RBF Finite Difference Approach to Solve Nonlinear Heat Conduction Problems on Unstructured Datasets

Radial Basis Functions have traditionally been used to provide a continuous interpolation of scattered data sets. However, this interpolation also allows for the reconstruction of partial derivatives throughout the solution field, which can then be used to drive the solution of a partial differential equation. Since the interpolation takes place on a scattered dataset with no local connectivity, the solution is essentially meshless. RBF-based methods have been successfully used to solve a wide variety of PDEs in this fashion. Such full-domain RBF methods are highly flexible and can exhibit spectral convergence rates Madych & Nelson (1990). However, in their traditional implementation the fully-populated matrix systems which are produced lead to computational complexities of at least order-N2 with datasets of size N. In addition, they suffer fromincreasingly poor numerical conditioning as the size of the dataset grows, and also with increasingly flat interpolating functions. This is a consequence of ill-conditioning in the determination of RBF weighting coefficients (as demonstrated in Driscoll & Fornberg (2002)), and is described by Robert Schaback Schaback (1995) as the uncertainty relation; better conditioning is associated with worse accuracy, and worse conditioning is associated with improved accuracy. Many techniques have been developed to reduce the effect of the uncertainty relation in the traditional RBF formulation, such as RBF-specific preconditioners Baxter (2002); Beatson et al. (1999); Brown (2005); Ling & Kansa (2005), or adaptive selection of data centres Ling et al. (2006); Ling & Schaback (2004). However, at present the only reliable methods of controlling numerical ill-conditioning and computational cost as problem size increases are domain decomposition Hernandez Rosales & Power (2007); Wong et al. (1999); Zhang (2007); Zhou et al. (2003), or the use of locally supported basis functions Fasshauer (1999); Schaback (1997); Wendland (1995); Wu (1995). In this work the domain decomposition principle is applied, forming a large number of heavily overlapping systems that cover the solution domain. A small RBF collocation system is formed around each global data centre, with each collocation system used to approximate the governing PDE at its centrepoint, in terms of the solution value at surrounding collocation points. This leads to a sparse global linear system which may be solved using a variety of standard solvers. In this way, the proposed formulation emulates a finite difference method, with the RBF collocation systems replacing the polynomial interpolation functions used in traditional finite difference methods. However, unlike such polynomial functions RBF collocation is well suited to scattered data, and the method may be applied to both structured and unstructured datasets without modification. The method is applied here to solve the nonlinear heat conduction equation. In order to reduce the nonlinearity in the governing equation the Kirchhoff integral transformation is applied, and the transformed equation is solved using a Picard iterative process. The application of the Kirchhoff transform necessitates that the thermal property functions be transformed to Kirchhoff space also. If the thermal properties are a known and integrable function of temperature then the transformation may be performed analytically. Otherwise, an integration-interpolation procedure can be performed using 1D radial basis functions, as described in Stevens & Power (2010). In recent years a number of local RBF collocation techniques have been proposed, and applied a wide variety of problems (for example; Divo & Kassab (2007); Lee et al. (2003); Sarler & Vertnik (2006); Wright & Fornberg (2006)). A more comprehensive review of such methods is given in Stevens et al. (2009). Unlike most local RBF collocation methods that are used in the literature, the technique described here utilises the Hermitian RBF collocation formulation (see section 2 for more details), and allows both the PDE-boundary and PDE-governing operators to be included within in the local collocation systems. This inclusion of the governing PDE within the basis functions is shown in Stevens et al. (2009) to significantly improve the accuracy and stability of solutions obtained for linear transport problems. Additionally, the incorporation of information about the convective velocity field into the basis functionswas shown to have a stabilising effect, similar to traditional upwinding methods but without the requirement to alter the stencil configuration based on the local convective field. The standard approach to the solution of linear and nonlinear heat conduction problems is the use of finite difference and finite volume methods with simple polynomial interpolants Bejan (1993); Holman (2002); Kreith & Bohn (2000). Due to the dominance of diffusion in most cases, central differencing techniques are commonly used to compute the heat fluxes. However, limiter methods (such as the unconditionally stable TVD schemes) may be used for nonlinear heat conduction problems where the effective convection term, which results from the non-zero variation of thermal conductivity with temperature, can be expected to approach the magnitude of the diffusive term (see, for example, Shen & Han (2002)). Full-domain RBF methods have also been examined for use with nonlinear heat conduction problems (see Chantasiriwan (2007)), however such methods are restricted to small dataset sizes, due to the computational cost and numerical conditioning experienced by full-domain RBF techniques on large datasets. The present work demonstrates how local RBF collocation may be used as an alternative to traditional finite difference and finite volume methods, for nonlinear heat conduction problems. The described method retains freedom from a volumetric mesh, while allowing solution over unstructured datasets. A central stencil configuration is used in each case, and the solution is stabilised via the inclusion of the governing and boundary PDEs within the local collocation systems (\u201cimplicit upwinding\u201d), rather than by adjusting the stencil configuration based on the local solution field (\u201ctraditional upwinding\u201d). The method is validated using a transient numerical example with a known analytical solution (see section 4), and the ability of the formulation to handle strongly nonlinear problems is demonstrated in the solution of a food freezing problem (see section 5)

Mass of Clusters in Simulations

We show that dark matter haloes, in n--body simulations, have a boundary layer (BL) with precise features. In particular, it encloses all dynamically stable mass while, outside it, dynamical stability is lost soon. Particles can pass through such BL, which however acts as a confinement barrier for dynamical properties. BL is set by evaluating kinetic and potential energies (T(r) and W(r)) and calculating R=-2T/W. Then, on BL, R has a minimum which closely approaches a maximum of w= -dlog W/dlog r. Such $Rw$ ``requirement'' is consistent with virial equilibrium, but implies further regularities. We test the presence of a BL around haloes in spatially flat CDM simulations, with or without cosmological constant. We find that the mass M_c, enclosed within the radius r_c, where the $Rw$ requirement is fulfilled, closely approaches the mass M_{dyn}, evaluated from the velocities of all particles within r_c, according to the virial theorem. Using r_c we can then determine an individual density contrast Delta_c for each virialized halo, which can be compared with the "virial" density contrast $\Delta_v ~178 \Omega_m^{0.45}$ (Omega_m: matter density parameter) obtained assuming a spherically symmetric and unperturbed fluctuation growth. The spread in Delta_c is wide, and cannot be neglected when global physical quantities related to the clusters are calculated, while the average Delta_c is ~25 % smaller than the corresponding Delta_v; moreover if $M_{dyn}$ is defined from the radius linked to Delta_v, we have a much worse fit with particle mass then starting from {\it Rw} requirement.Comment: 4 pages, 5 figures, contribution to the XXXVIIth Rencontres de Moriond, The Cosmological Model, Les Arc March 16-23 2002, to appear in the proceeding