Asset Pricing with Observable Stochastic Discount Factors.

The stochastic discount factor model provides a general framework for pricing assets. By specifying the discount factor suitably it encompasses most of the theories currently in use, including CAPM and consumption CAPM. The SDF model has been based on the use of single and multiple factors, and on latent and observed factors. In most situations, and especially for the term structure, single factor models are inappropriate, whilst latent variables require the somewhat arbitrary specification of generating processes and are difficult to interpret. In this paper we survey the principal different implementations of the SDF model for FOREX, equity and bonds and we propose a new approach. This is based on the use of multiple factors that are observable and modelling the joint distribution of excess returns and the factors using a multi-variate GARCH-in-mean process. We argue that in general single equation and VAR models, although widely used in empirical finance, are inappropriate as they do not satisfy the no-arbitrage condition. Since risk premia arise from conditional covariation between returns and the factors, both a multi-variate context and having conditional covariances in the conditional mean process, is essential. We explain how apparent exceptions, such as the CIR and Vasicek models, in fact meet this requirement - but at a price. We explain our new approach, discuss how it might be implemented and present some empirical evidence, mainly from our own researches. Partly, to enable comparisons to be made, the survey also includes evidence from recent empirical work using more traditional approaches.Asset Pricing; Stochastic Discount Factors; Forex; Equity Term Structure; Affine Factor Models; Consumption CAPM; Financial Econometrics; GARCH

The Development of a Lutetium Recovery Plant

This research project focused on the scale-up of an industrial facility for the continuous counter-current solvent extraction (CCCSX) separation of lutetium. CCCSX involves a multistage apparatus for the mixing in each stage of two immiscible liquid phases to transfer an analyte from one phase to the other. The two phases continuously flow in opposite directions in a CCCSX system. In this research, aqueous lutetium solutions, obtained from the acid leaching of lutetium oxyorthosilicate, were mixed with kerosene solutions of phosphorus based metal extractants (e.g. mono-2-ethylhexyl-(2- ethylhexyl) phosphonic acid, MEHEHP). This system extracted the lutetium from the aqueous phase, transferring the lutetium to the organic phase. The lutetium was stripped from the organic phase by mixing this phase with an aqueous solution of highly concentrated acid. The subsequent aqueous lutetium solution was processed to produce lutetium oxide. Scale-up is a process which begins with bench-scale experiments and proceeds through pilot-scale experiments to the design of an industrial facility. Bench-scale experiments were performed to investigate the extraction characteristics of lutetium in a variety of systems. The information obtained from the bench-scale experiments was utilized in pilot-scale experiments. The pilot plant used for this research consisted of 15 interconnected mixer-settler units. This pilot plant was operated as a CCCSX system. The results of the pilot-scale experiments were used in the design of an industrial CCCSX facility with the capacity to produce 106 kg of 99.999% pure Lu203 from 127 kg of lutetium oxyorthosilicate per day. Research was also conducted on the industrialization of a technique known as precipitation stripping. Precipitation stripping involves the removal of a metal from a metal-loaded organic phase as a solid metal compound by mixing the organic phase with an aqueous solution of an appropriate precipitating agent. Precipitation stripping was applied to the lutetium CCCSX system to determine the effect of this technique of an industrial facility. It was determined that precipitation stripping can potentially reduce the volume of aqueous effluent generated by an industrial CCCSX facility by a considerable amount

Consumption, Size and Book-to-Market Ratio in Equity Returns

This study extends the standard consumption-based capital asset pricing model (C-CAPM) to include two additional factors related to firm size (SMB) and book-to-market value ratio (HML). The inclusion of HML improves mainly the fit of the low book-to-market portfolios, SMB, and HML that are not correctly priced in the standard C-CAPM. Consumption premium varies across size and coincides with the size effect. The effect of a HML premium is to reduce the amount of consumption premium, implying that low book-to-market ratio and, to a lesser degree, small portfolios are not as risky as consumption predicts. The HML premium across size is contradictory to the size effect as small firms have a larger negative HML premium.Risk Premium; Equity Return; Stochastic Discount Factor; Consumption

A Cross Section of Equity Returns: The No-Arbitrage Test

We propose a new test based on the no-arbitrage condition that compares cross-sectional variation in equity returns to the cross-sectional variation in their conditional covariance with the discount factors. Using the multivariate generalized heteroskedasticity in mean model (MGM) to estimate the 25 portfolios formed on size and book-to-market ratio, together with each with its own arbitrage condition, we find that the no-arbitrage test rejects the consumption-based capital asset pricing model (C-CAPM). Although the conditional covariances of returns with consumption exhibit negative variation across size, they do not vary across the book-to-market ratio. Thus, the C-CAPM can capture size effect, but not value effect. Allowing the coefficients on the consumption covariances to be different largely improves the fit of the C-CAPM, however. The value effect appears to be associated with book-to-market ratio as well as size. Book-to-market ratio separately does not generate information about average returns that cannot be explained by the C-CAPM.Risk Premium; Equity Return; Stochastic Discount Factor; No-arbitrage Condition

Playing a Double Game: Authorial Reading and the Ethics of Interpretation

Students in English education typically have to live in (at least) two worlds: departments of English in which they receive their disciplinary training, and departments or schools or programs of education in which they work to develop the pedagogical content knowledge they need to teach in that discipline. Often those worlds are far apart. In this article, Michael Smith and Peter Rabinowitz, describe their own collaborative efforts as fruitful, mainly because of their differences. Smith is a Professor of Literacy Education, while Rabinowitz is a Professor of Comparative Literature. They share that they have always been able to work through their differences because they share a theory of literacy reading despite their different disciplinary norms. They write here that their work developing this theory has been important to both of them for it has allowed them to benefit from (rather than dismiss) each other\u27s perspectives as their exploration of two important ethical issues in the reading and teaching of literature moves forward. The authors conclude by saying their differences mirror the larger disciplinary differences that students in English education often experience. They wish to encourage classroom discussions of literature that are informed both by the head and the heart, discussions that see seemingly polar positions complementing each other in meaningful ways

Virus Amplification

Sorghum is the fifth most produced cereal in the world and a source of nutrients for humans, feeding more than 500 million people in Africa and Asia [1]. It is grown commercially for food, animal feed, fiber and fuel in roughly 100 countries including U.S. [2]. Worldwide, feeding by 150 insect species causes substantial economic damage to sorghum [3]. Besides feeding damage, aphids such as the Corn Leaf Aphid vector Sugarcane mosaic virus (SCMV), Sorghum mosaic virus (SRMV), Maize mosaic virus (MDMV) and Johnson grass mosaic virus (JGMV) [4]. These are Potyviruses, the largest group of the Potyviridae family with 176 members [5] and cause substantial yield losses to sorghum, sugarcane, and maize. SCMV, SRMV, and MDMV are closely related whereas JGMV is more distantly related to them [6]. All have an average 9.7 kb positive-sense single-stranded RNA genome encoding 10 mature proteins in a single large ORF [7]