The olive oil and cotton lint sectors in the European Union

This paper examines and analyses the impacts of the reformed CAP as well as the decisions of the new round of negotiations for the olive oil and cotton sectors in the European Union. The aim of this study is to estimate changes in supply (agricultural supply plus intermediate demand and final production), demand (consumption), price and stock formation (import, export, beginning and ending stocks, national price formation) for both the olive oil and cotton sectors. The model designed for this purpose is partial equilibrium and policy oriented. The objectives of this model are to estimate changes in the production and consumption of the two products concerned, to determine how the reformed CAP and the new round of negotiations of the WTO affect these two sectors to analyse the evolution of export and import volumes, and finally to determine how this evolution will influence the welfare situation of the olive and cotton sectors.

Design and techno-economic evaluation of microbial oil production as a renewable resource for biodiesel and oleochemical production

Experimental results from the open literature have been employed for the design and techno-economic evaluation of four process flowsheets for the production of microbial oil or biodiesel. The fermentation of glucose-based media using the yeast strain Rhodosporidium toruloides has been considered. Biodiesel production was based on the exploitation of either direct transesterification (without extraction of lipids from microbial biomass) or indirect transesterifaction of extracted microbial oil. When glucose-based renewable resources are used as carbon source for an annual production capacity of 10,000 t microbial oil and zero cost of glucose (assuming development of integrated biorefineries in existing industries utilising waste or by-product streams) the estimated unitary cost of purified microbial oil is $3.4/kg. Biodiesel production via indirect transesterification of extracted microbial oil proved more cost-competitive process compared to the direct conversion of dried yeast cells. For a price of glucose of $400/t oil production cost and biodiesel production cost are estimated to be $5.5/kg oil and $5.9/kg biodiesel, correspondingly. Industrial implementation of microbial oil production from oleaginous yeast is strongly dependent on the feedstock used and on the fermentation stage where significantly higher productivities and final microbial oil concentrations should be achieved.

A panel cointegration analysis of the demand for oil in the Middle East

This article applies recently developed panel unit root and panel cointegration techniques to estimate the long-run income and price elasticities for oil in the Middle East. The results for the panel indicate that demand for oil is highly price inelastic and slightly income elastic in the Middle East. There is considerable variation in the results for the income variable across countries, with the coefficient on the income variable statistically insignificant for several countries. The coefficient on the price variable is statistically significant in all cases with the expected sign and the price elasticity is uniformly low. While the results for the income variable differ across countries, the results for the panel as a whole suggest that the demand for oil in the Middle East is being driven largely by strong economic growth, while consumers are largely insensitive to price changes.

Fish oil replacement in finfish nutrition

Unsustainable fishing practices have placed a heavy emphasis on aquaculture to meet the global shortfalls in the supply of fish and seafood, which are commonly accepted as the primary source of health-promoting essential omega-3 (n-3 highly unsaturated fatty acids). However, dietary fish oil is required for the production of omega-3-rich farmed fish and this commodity, in a vicious circle, is at present derived solely from wild fisheries. Decreasing global availability coupled with the highly variable price of this resource has forced the aquaculture industry to investigate the possibilities of alternative dietary lipid sources. This review attempts to compile all principal information available regarding the effects of fish oil replacement for the diets of farmed finfish, analysing the findings using a comparative approach among different cultured fish species. The review initially focuses on the present situation with regard to the production, availability and main nutritional characteristics of fish oil and the principal alternative lipid sources (such as vegetable oils and animal fats). Following this, the effects of fish oil replacement in finfish nutrition on feed quality, fish performance, feed efficiency, fish lipid metabolism, final eating quality and related economic aspects are presented and discussed.

Economic growth with coal, oil and renewable energy consumption in China: prospects for fuel substitution

We examine the relationship between Chinese aggregate production and consumption of three main energy commodities: coal, oil and renewable energy. Both autoregressive distributed lag (ARDL) and vector error correction modeling (VECM) show that Chinese growth is led by all three energy sources. Economic growth also causes coal, oil and renewables consumption, but with negative own-price effects for coal and oil and a strong possibility of fuel substitution through positive cross-price effects. The results further show coal consumption causing pollution, while renewable energy consumption reduces emissions. No significant causation on emissions is found for oil. Hence, making coal both absolutely and relatively expensive compared to oil and renewable energy encourages shifting from coal to oil and renewable energy, thereby improving economic and environmental sustainability.

Prediction interval estimation for electricity price and demand using support vector machines

Uncertainty is known to be a concomitant factor of almost all the real world commodities such as oil prices, stock prices, sales and demand of products. As a consequence, forecasting problems are becoming more and more challenging and ridden with uncertainty. Such uncertainties are generally quantified by statistical tools such as prediction intervals (Pis). Pis quantify the uncertainty related to forecasts by estimating the ranges of the targeted quantities. Pis generated by traditional neural network based approaches are limited by high computational burden and impractical assumptions about the distribution of the data. A novel technique for constructing high quality Pis using support vector machines (SVMs) is being proposed in this paper. The proposed technique directly estimates the upper and lower bounds of the PI in a short time and without any assumptions about the data distribution. The SVM parameters are tuned using particle swarm optimization technique by minimization of a modified Pi-based objective function. Electricity price and demand data of the Ontario electricity market is used to validate the performance of the proposed technique. Several case studies for different months indicate the superior performance of the proposed method in terms of high quality PI generation and shorter computational times.

Intraday volatility interaction between the crude oil and equity markets

This paper investigates the price volatility interaction between the crude oil and equity markets in the US using 5-min data over the period 2009-2012. Our main findings can be summarised as follows. First, we find strong evidence to demonstrate that the integration of the bid-ask spread and trading volume factors leads to a better performance in predicting price volatility. Second, trading information, such as bid-ask spread, trading volume, and the price volatility from cross-markets, improves the price volatility predictability for both in-sample and out-of-sample analyses. Third, the trading strategy based on the predictive regression model that includes trading information from both markets provides significant utility gains to mean-variance investors.

The fiscal impact of trade liberalization and commodity price fluctuation: the case of Dominican Republic, 1980-1998

Includes bibliography

The fiscal impact of trade liberalization and commodity price fluctuation: the case of Costa Rica, 1980-1998

Includes bibliography

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

Oil, paint and drug reporter.

Vols. include the proceedings (some summarized, some official stenographic reports) of the National Wholesale Druggists' Association (called 18 -1882, Western Wholesale Druggists' Association) and of other similar organizations.

The oil shock of 2005

During the course of 2005, the price of crude oil reached unprecedented high levels, at least in nominal terms. Australian motorists have become used to paying more than a dollar a litre for petrol. Given the past volatility in oil prices, often described in terms of a series of oil ‘shocks’ (the large price increases in 1973, 1979 and 1999), several questions arise. First, will current high prices persist, or will prices decline substantially as occurred after previous oil shocks? Second, is the current shortage of oil a temporary phenomenon, caused by inadequate investment in oil exploration, drilling and refining capacity, or is it a signal that the supply of oil available to the world has peaked? Third, will high oil prices lead to broader economic disruption, as is commonly supposed to have happened after previous shocks? Fourth, how painful will an adjustment to lower use of oil be? Finally, how does all this relate to our efforts to deal with the problem of climate change? This article is an effort to answer some of these questions in the light of the knowledge available to us.

Price transmission in the EU wholesale petroleum markets

This article employs nonlinear smooth transition models to analyze the relationship between upstream and midstream prices of petroleum products. We test for the presence of nonlinearities in price linkages using both weekly series constructed using official EU procedures and also daily industry series applied for the first time. Our results show that the estimated shape of the transition function and equilibrium reversion path depend on the frequency of the price dataset. Our analysis of the crude oil to wholesale price transmission provides evidence of nonlinearities when prices are observed with daily frequency. The nature of the nonlinearities provides evidence in support of the existence of menu costs or, more generally, frictions in the markets rather than supply adjustment costs. This result differs from that found for the U.S. petroleum markets. © 2012 American Statistical Association.

Causality in crude oil prices

Crude oil markets witness growing disparity between the quality of crudes supplied and demanded in the market. The market share of low-quality crudes is increasing due to the depletion of old fields and increasing demand. This is unnerving the practitioners and affecting the relevance of the traditional benchmark crudes due to the lack of lower quality benchmarks (Montepeque, 2005). In this article, we apply Granger causality tests to study the price dependence of 32 crudes in order to establish which crudes drive other prices and which ones simply follow general market trends. Our results indicate that some of the old benchmarks are still relevant while others can be disregarded. Our results also interestingly show that the low-quality Mediterranean Russian Urals crude, introduced in the late 1990s, has emerged recently as a significant driver of global prices. © 2011 Taylor & Francis.

How do Small Players Deduce Beliefs about Uncertainty? A Look at Texas Shale Oil Investments

Thesis (Ph.D.)--University of Washington, 2016-08