980 resultados para jet fuel price risk


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Tämän kandidaatintutkielman tarkoituksena on tutkia, miten yhdysvaltalaisten lentoyhtiöiden harjoittama rahoituksellinen lentopolttoaineen hintasuojaus on vaikuttanut niiden keskimääräisiin polttoainekustannuksiin 2000-luvun aikana. Lisäksi tavoitteena on kirjallisuuskatsauksen muodossa tarkastella lentopolttoaineen hintariskiä ja siltä suojautumista. Aiheeseen liittyvä aiempi tutkimus on pääasiassa keskittynyt rahoitusasemaan liittyvien vaikutusten tarkasteluun. Tässä tutkielmassa puolestaan tutkitaan suojauksen vaikutusta tarkasteltavien lentoyhtiöiden liiketoiminnan kustannuksiin. Lentopolttoaineen hintasuojauksen kustannusvaikutuksia arvioidaan regressiomallilla, jossa selitettävänä muuttujana on lentoyhtiön keskimääräinen polttoainekustannus. Selittävinä muuttujina puolestaan toimivat seuraavan vuoden arvioiduista polttoainehankinnoista rahoituksellisin keinoin suojattujen hankintojen osuus sekä lentopolttoaineen keskimääräinen markkinahinta kunakin tarkasteluvuonna. Tutkimuksen aineisto koostuu kymmenestä yhdysvaltalaisesta lentoyhtiöstä ja niiden 2000-luvulla vuosikertomuksissaan raportoimista tiedoista liittyen polttoainekustannuksiin ja rahoitukselliseen polttoaineen hintasuojaukseen. Lisäksi lentopolttoaineen keskimääräiset vuotuiset markkinahinnat tarkastelujakson ajalta haetaan Yhdysvaltain energiainformaatiota välittävän viranomaisen verkkotietokannasta. Johtopäätöksenä todetaan yhdysvaltalaisten lentoyhtiöiden rahoituksellisen polttoaineen hintasuojauksen vähentäneen niiden keskimääräisiä polttoainekustannuksia 2000-luvun aikana. Lentopolttoaineen markkinahinnan todetaan vaikuttavan kustannuksiin reilusti lentoyhtiöiden suojaustoimenpiteitä voimakkaammin. Lisäksi aiempiin tutkimuksiin ja toisaalta tässä tutkielmassa estimoitavan mallin autokorreloituvaan luonteeseen nojaten todetaan, että tämän mallin selittävät muuttujat eivät ole ainoat keskimääräisiin polttoainekustannuksiin vaikuttavat tekijät. Yhteenvetona todetaankin tarkempaa lisätutkimusta tarvittavan, jotta tämän tutkielman tulokset voidaan luotettavammin yleistää.

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The present paper is devoted to the results of experimental research undertaken into photocatalytical oxidation (PCO) of aqueous solutions of de-icing agents and aqueous extract of jet fuel. The report consists of introduction, literature review, description of materials and methods, discussion of results and conclusions. TiO2 was selected as a photocatalyst for the experiments with synthetic solutions of ethylene glycol, 2-ethoxyethanol and aqueous extract of jet fuel. To explain the PCO mechanisms affecting certain behaviour of de-icing agent under distinctive conditions, the following factors were studied: the impact of initial concentration of pollutant, the role of pH, the presence of tert-butanol as OH·-radicals scavenger and mineral admixtures. PCO under solar radiation performed in two ways: catalysed by irradiated TiO2 slurry or by TiO2 attached to buoyant hollow glass micro-spheres. Special attention was paid to the energy-saving PCO with reduced intensity mixing of the slurry. The effect of PCO was assessed by determination of residual chemical oxygen demand of solution (COD) and by measuring of concentration of glycols. The PCO process efficiency was assumed to be dependent on the TiO2 suspension fractional composition. Thus, the following effects of solutions’ media were viewed: presence of organic admixtures, pH influence, mixing mode during the PCO. The effects of mineral admixtures - Ca2+, Fe3+/2+, Mn2+, SO42- - that are often present in natural and wastewater systems or produced during the degradation of organic pollutants and which can affect the rate of PCO of de-icing agents, were also investigated.

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The focus of this study has been comovement of stock price risk level between two companies as they form strategic alliance. Thus the main reason has been to shed more light to possible increased risk level that the stockholder confronts when a company he owns forms a strategic alliance with another company. This study has centralized to interfirm cooperation between mobile and internet companies, which have furthered the development of mobile internet. The study has been divided into theoretical and empirical part. In theoretical part the main concepts riskiness of a stock (volatility), comovement and strategic alliance have been run through. In empirical part seven strategic alliances formed by mobile internet companies have been examined. Based on this, strategic alliance seems to increase comovement of stock price risk in some degree. This comovement seems to be stronger when core businesses or operating environments of cooperating companies differ more from each other.

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The objective of the study is to extend the existing hedging literature of the commodity price risks by investigating what kind of hedging strategies can be used in companies using bitumen as raw material in their production. Five different alternative swap hedging strategies in bitumen markets are empirically tested. Strategies tested are full hedge strategy, simple, conservative, and aggressive term structure strategies, and implied volatility strategy. The effectiveness of the alternative strategies is measured by excess returns compared to no hedge strategy. In addition, the downside risk of each strategy is measured with target absolute semi-deviation. Results indicate that any of the tested strategies does not outperform the no hedge strategy in terms of excess returns in all maturities. The best-performing aggressive term structure strategy succeeds to create positive excess returns only in short maturities. However, risk seems to increase hand-in-hand with the excess returns so that the best-performing strategies get the highest risk metrics as well. This implicates that the company willing to gain from favorable price movements must be ready to bear a greater risk. Thus, no superior hedging strategy over the others is found.

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Formal and analytical models that contractors can use to assess and price project risk at the tender stage have proliferated in recent years. However, they are rarely used in practice. Introducing more models would, therefore, not necessarily help. A better understanding is needed of how contractors arrive at a bid price in practice, and how, and in what circumstances, risk apportionment actually influences pricing levels. More than 60 proposed risk models for contractors that are published in journals were examined and classified. Then exploratory interviews with five UK contractors and documentary analyses on how contractors price work generally and risk specifically were carried out to help in comparing the propositions from the literature to what contractors actually do. No comprehensive literature on the real bidding processes used in practice was found, and there is no evidence that pricing is systematic. Hence, systematic risk and pricing models for contractors may have no justifiable basis. Contractors process their bids through certain tendering gateways. They acknowledge the risk that they should price. However, the final settlement depends on a set of complex, micro-economic factors. Hence, risk accountability may be smaller than its true cost to the contractor. Risk apportionment occurs at three stages of the whole bid-pricing process. However, analytical approaches tend not to incorporate this, although they could.

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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.

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Dermal exposure to jet fuel suppresses the immune response. Immune regulatory cytokines, and biological modifiers, including platelet activating factor, prostaglandin E2, and interleukin-10 have all been implicated in the pathway leading to immunosuppression. It is estimated that approximately 260 different hydrocarbons are found in JP-8 (jet propulsion-8) jet fuel, and the identity of the immunotoxic compound is not known. The recent availability of synthetic jet fuel (S-8), which is devoid of aromatic hydrocarbons, made it feasible to design experiments to test the hypothesis that the aromatic hydrocarbons are responsible for jet fuel induced immune suppression. Applying S-8 to the skin of mice does not up-regulate the expression of epidermal cyclooxygenase-2 nor does it induce immune suppression. Adding back a cocktail of 7 of the most prevalent aromatic hydrocarbons found in jet fuel to S-8 up-regulated cyclooxygenase-2 expression and induced immune suppression. Cyclooxygenase-2 induction can be initiated by reactive oxygen species (ROS). JP-8 treated keratinocytes increased ROS production, S-8 did not. Antioxidant pre-treatment blocked jet fuel induced immune suppression and cyclooxygenase-2 up-regulation. Accumulation of reactive oxygen species induces oxidant stress and affects activity of ROS sensitive transcription factors. JP-8 induced activation of NFκB while S-8 did not. Pre-treatment with antioxidants blocked activation of NFκB and parthenolide, an NFκB inhibitor, blocked jet fuel induced immune suppression and cyclooxygenase-2 expression in skin of treated mice. p65 siRNA transfected keratinocytes demonstrated NFκB is critically involved in jet fuel induced COX-2 expression. These findings clearly implicate the aromatic hydrocarbons found in jet fuel as the agents responsible for inducing immune suppression, in part by the production of reaction oxygen species, NFκB dependent up-regulation of cyclooxygenase-2, and the production of immune regulatory factors and cytokines. ^

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Three different oils: babassu, coconut and palm kernel have been transesterified with methanol. The fatty acid methyl esters (FAME) have been subjected to vacuum fractional distillation, and the low boiling point fractions have been blended with fossil kerosene at three different proportions: 5, 10 and 20% vol.

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State of the Art. Process and Distillation. Fuel Characterization. Fuel Compatibility Tests

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Water is a common impurity of jet fuel, and can exist in three forms: dissolved in the fuel, as a suspension and as a distinct layer at the bottom of the fuel tank. Water cannot practically be eliminated from fuel but must be kept to a minimum as large quantities can cause engine problems, particularly when frozen, and the interface between water and fuel acts as a breeding ground for biological contaminants. The quantities of dissolved or suspended water are quite small, ranging from about 10 ppm to 150 ppm. This makes the measurement task difficult and there is currently a lack of a convenient, electrically passive system for water-in-fuel monitoring; instead the airlines rely on colorimetric spot tests or simply draining liquid from the bottom of fuel tanks. For all these reason, people have explored different ways to detect water in fuel, however all these approaches have problems, e.g. they may not be electrically passive or they may be sensitive to the refractive index of the fuel. In this paper, we present a simple, direct and sensitive approach involving the use of a polymer optical fibre Bragg grating to detect water in fuel. The principle is that poly(methyl methacrylate) (PMMA) can absorb moisture from its surroundings (up to 2% at 23 °C), leading to both a swelling of the material and an increase in refractive index with a consequent increase in the Bragg wavelength of a grating inscribed in the material.

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Water is a common impurity of jet fuel, and can exist in three forms: dissolved in the fuel, as a suspension and as a distinct layer at the bottom of the fuel tank. Water cannot practically be eliminated from fuel but must be kept to a minimum as large quantities can cause engine problems, particularly when frozen, and the interface between water and fuel acts as a breeding ground for biological contaminants. The quantities of dissolved or suspended water are quite small, ranging from about 10 ppm to 150 ppm. This makes the measurement task difficult and there is currently a lack of a convenient, electrically passive system for water-in-fuel monitoring; instead the airlines rely on colorimetric spot tests or simply draining liquid from the bottom of fuel tanks. For all these reason, people have explored different ways to detect water in fuel, however all these approaches have problems, e.g. they may not be electrically passive or they may be sensitive to the refractive index of the fuel. In this paper, we present a simple, direct and sensitive approach involving the use of a polymer optical fibre Bragg grating to detect water in fuel. The principle is that poly(methyl methacrylate) (PMMA) can absorb moisture from its surroundings (up to 2% at 23 °C), leading to both a swelling of the material and an increase in refractive index with a consequent increase in the Bragg wavelength of a grating inscribed in the material.

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The study of price risk management concerning high grade steel alloys and their components was conducted. This study was focused in metal commodities, of which nickel, chrome and molybdenum were in a central role. Also possible hedging instruments and strategies for referred metals were studied. In the literature part main themes are price formation of Ni, Cr and Mo, the functioning of metal exchanges and main hedging instruments for metal commodities. This section also covers how micro and macro variables may affect metal prices from the viewpoint of short as well as longer time period. The experimental part consists of three sections. In the first part, multiple regression model with seven explanatory variables was constructed to describe price behavior of nickel. Results were compared after this with information created with comparable simple regression model. Additionally, long time mean price reversion of nickel was studied. In the second part, theoretical price of CF8M alloy was studied by using nickel, ferro-chrome and ferro-molybdenum as explanatory variables. In the last section, cross hedging possibilities for illiquid FeCr -metal was studied with five LME futures. Also this section covers new information concerning possible forthcoming molybdenum future contracts as well. The results of this study confirm, that linear regression models which are based on the assumption of market rationality, are not able to reliably describe price development of metals at issue. Models fulfilling assumptions for linear regression may though include useful information of statistical significant variables which have effect on metal prices. According to the experimental part, short futures were found to incorporate the most accurate information concerning the price movements in the future. However, not even 3M futures were able to predict turning point in the market before the faced slump. Cross hedging seemed to be very doubtful risk management strategy for illiquid metals, because correlations coefficients were found to be very sensitive for the chosen time span.

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Fluctuating commodity prices, foreign exchange rates and interest rates are causing changes in cash flows, market value and the companies’ profit. Most of the commodities are quoted in US dollar. Companies with non-dollar accounting face a double risk in the form of the commodity price risk and foreign exchange risk. The objective of this Master’s thesis is to find out how companies under commodity should manage foreign exchange exposure. The theoretical literature is based on foreign exchange risk, commodity risk and foreign exchange exposure management. The empirical research is done by using constructive modelling of a case company in the oil industry. The exposure is model with foreign exchange net cash flow and net working capital. First, the factors affecting foreign exchange exposure in case company are analyzed, then a model of foreign exchange exposure is created. Finally, the models are compared and the most suitable method is defined. According to the literature, foreign exchange exposure is the foreign exchange net cash flow. However, the results of the study show that foreign exchange risk can be managed also with net working capital. When the purchases, sales and storage are under foreign exchange risk, the best way to manage foreign exchange exposure is with combined net cash flow and net working capital method. The foreign exchange risk policy of the company defines the appropriate way to manage foreign exchange risk.