Weather derivatives: Concept and application for their use in South Africa

Recent innovations in energy markets suggest the possibility of addressing agricultural risk factors by issuing derivatives on weather elements. Such instruments appear particularly attractive, as asymmetric information and loss adjustment issues do not affect them. This article first describes the concept, functioning and application of weather derivatives. It then examines the feasibility of rainfall derivatives to manage agricultural production risk in South Africa by evaluating the merits of rainfall options, and suggesting an option strategy, as a yield risk management tool. The use of rainfall derivatives in South Africa is likely to increase in future as capital markets, financial institutions, insurance companies, crop insurance companies and hedge funds collectively organize themselves to share and distribute weather risks.Risk and Uncertainty,

Cash flow risk ratio: An aid to marketing decisions

In the past, the fully regulated marketing environment allowed producers to neglect or ignore the marketing side of their business. Now, with an open marketing system and increased volatility in the commodity markets, producers will have the right and the responsibility to determine their own financial security. One of the most difficult questions for producers to answer, is how much of his/her crop must be pre-harvest marketed. Knowing his/her production costs (both variable and fixed) and range of acceptable production, price, and financial risks are the key to determining his/her price objective. Producers can determine their degree of marketing flexibility by using the cash flow risk ratio. This ratio predicts what percentage of the projected crop must be marketed at the expected season average price to meet cash obligations. In this uncertain and risky future, failing to plan may be the same as planning to fail.Agricultural Finance, Marketing,

Analysis of CO₂ leakage through "low-permeability" faults from natural reservoirs in the Colorado Plateau, southern Utah

The numerous CO2 reservoirs in the Colorado Plateau region of the United States are natural analogues for potential geologic CO2 sequestration repositories. To better understand the risk of leakage from reservoirs used for long-term underground CO2 storage, we examine evidence for CO2 migration along two normal faults from a reservoir in east-central Utah. CO2 -charged springs, geysers, and a hydrocarbon seep are localised along these faults. These include natural springs that have been active for long periods of time, and springs that were induced by recent drilling. The CO2 -charged spring waters have deposited travertine mounds and carbonate veins. The faults cut siltstones, shales, and sandstones and the fault rocks are fine-grained, clay-rich gouge, generally thought to be barriers to fluid flow. The geologic and geochemical data are consistent with these faults being conduits for CO2 to the surface. Consequently, the injection of CO2 into faulted geologic reservoirs, including faults with clay gouge, must be carefully designed and monitored to avoid slow seepage or fast rupture to the biosphere

THE IMPACT OF INFLATION ON STOCK PRICES IN TWO SADC COUNTRIES

Demand and Price Analysis,

EMMIXcskew: an R Package for the Fitting of a Mixture of Canonical Fundamental Skew t-Distributions

This paper presents an R package EMMIXcskew for the fitting of the canonical fundamental skew t-distribution (CFUST) and finite mixtures of this distribution (FM-CFUST) via maximum likelihood (ML). The CFUST distribution provides a flexible family of models to handle non-normal data, with parameters for capturing skewness and heavy-tails in the data. It formally encompasses the normal, t, and skew-normal distributions as special and/or limiting cases. A few other versions of the skew t-distributions are also nested within the CFUST distribution. In this paper, an Expectation-Maximization (EM) algorithm is described for computing the ML estimates of the parameters of the FM-CFUST model, and different strategies for initializing the algorithm are discussed and illustrated. The methodology is implemented in the EMMIXcskew package, and examples are presented using two real datasets. The EMMIXcskew package contains functions to fit the FM-CFUST model, including procedures for generating different initial values. Additional features include random sample generation and contour visualization in 2D and 3D

Nonparametric regression analysis

textNonparametric regression uses nonparametric and flexible methods in analyzing complex data with unknown regression relationships by imposing minimum assumptions on the regression function. The theory and applications of nonparametric regression methods with an emphasis on kernel regression, smoothing spines and Gaussian process regression are reviewed in this report. Two datasets are analyzed to demonstrate and compare the three nonparametric regression models in R.Statistic