Operators can improve a reservoir’s value by optimizing it in a more holistic manner, or over its entire life cycle. This thesis developed approaches to life cycle optimization, with emphasis on accessible technical and economic modeling techniques for production. The challenges of life cycle optimization are properly scheduling the times at which the operator should switch from one recovery phase to the next, along with determining other field design parameters such as well spacing and injection pressures for waterflooding and enhanced oil recovery processes. To deliver the most value, the operator needs to produce from a reservoir the greatest quantity of oil, at a relatively low cost, reasonably soon, and ideally at a time when the oil price is high. This is quite a tall order, as these goals are often in conflict. This thesis extended existing research regarding lifecycle optimization, first modeling production from a reservoir using an exponential decline model and assuming the oil price’s behavior can be approximated with mean-reverting processes. Implications of operating and capital costs potentially being correlated with the oil price were also examined. Finally, a mean-reverting price model that forecasts the mean oil price as increasing and described by a logistic model was proposed to accommodate both recent price forecasts and economic reality. As exponential decline models are more appropriate for characterizing existing production history rather than making a priori predictions, a geologic-parameter-based model was developed using a tank model for primary recovery and a model based on Koval theory and parameterizing a reservoir in terms of flow capacity and storage capacity for waterflooding and CO2 flooding. This model was adapted from existing theory to account for situations where a waterflood has incompletely swept a reservoir at the start of CO2 flooding. Analytical expressions were also derived for estimating injection rates into a formation parameterized by flow capacity and storage capacity. The geologic-parameter-based model was combined with economic assumptions and optimized using a genetic algorithm. This optimization suggested an operator should switch from primary recovery to a CO2 flood with a large WAG ratio relatively early in the reservoir’s life. / text

Exchange rate risk, interest rate risk and oil price fluctuations are the most demonstrated risks in the GCC (Gulf Cooperation Council) countries (Arouri and Nguyen, 2010). Research, however, in this area is still underdeveloped. The importance of this study is to contribute to this research gap. This research aims to show how these three risks affect firms' market values by examining 473 listed firms in Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates for the period January 2007 to June 2012. The research further examines the determinants of these risks. The study uses the AR (1) EGARCH-M model. The results indicate that stock returns in GCC countries are influenced by the exchange rate risk, interest rate risk and oil price risk. However, the exposure was highest for exchange rate risk and lowest for interest rate risk. While the effects of these risks were mixed, overall, exchange rate risk and oil price risk showed more positive significance as compared to the interest rate risk that showed more negatively significant effect on firm values. The level of the effect of these risk also differed from country to country. However, firms in United Arab Emirates revealed the highest exposure to all the three risks while those in Saudi Arabia showed the least exposed to the three risks. Oman firms also showed high exposure to exchange rate and interest rate risks. The segregated results overall showed lower exposure of financial firms as compared to non-financial firms. However, the non-financial firms in Bahrain were more exposed to the risks than the financial firms. In Saudi Arabia, the financial firms revealed the least exposure to the risk suggesting effective risk management practices. In addition, foreign operations and firm size had a significant influence on the extent of the firms’ exposure to all the three risks. Leverage also influenced the level of exposure to interest rate risk. Profitability, growth and liquidity did not reveal a significant influence on the level of exposure. Further, increasing the risk does not lead to increased returns in most of the GCC countries. The risk-return parameters were largely negative. However, positive news increases return volatility more than negative news in most countries. Also, the current volatility of most GCC firms’ returns are time varying, are a function or past innovation and past volatility. The volatility of stock returns, which is affected by changes in the risk factors, could demonstrate the non-prioritisation of risk management by firms.

Magister Economicae - MEcon / Numerous studies have investigated the impact of oil price shocks on the exchange rates in developed economies. However, fewer studies have examined the effect of oil price shocks in developing economies. One study by Turhan, Hacihasanoglu and Soytas in 2012 examines the dynamic effect of oil price movements in thirteen developing markets, including South Africa. Another study by Kin and Courage (2014) investigate the effect of crude oil prices on the South African exchange rate, but their modelling, time period and variables differs. The intention of the current mini-thesis, however, is investigate the effect of crude oil prices on the exchange rate of South Africa from January 1980 to December 2014. The aim of this mini-thesis is to explore the impact of crude oil price movements on the volatility of the exchange rate on the South African market. Currently emerging economies are consuming an increasing share of the world’s oil and they have therefore become larger players in the global financial markets. Basher and Sadorsky (2006:224-227) state that as countries modernise and urbanise, their demand for crude oil and its related products tends to increase. The rising economic importance of the BRICS (Brazil, Russia, India, China and South Africa) economies implies that the possibility of the consumption of oil in the developing economies could surpass the global oil consumption of developed economies. It is important to note that future oil demand cannot be predicted, but oil demand growth is highly correlated with the growth in the industrial production of a country. The use of oil for energy consumption and the use of oil trading on the stock markets and the financial markets are all linked on the path of a country’s economic growth. In order to evaluate the link between the four variables of oil prices, exchange rates, manufacturing production index and the prime rate, qualitative research methods will be used. The methods which will be applied are the vector autoregressive model and the vector error correction mechanism. This study reveals that the movement in Brent oil prices has a relatively insignificant impact on the movement of the South African rand on a monthly basis.

We estimate the macroeconomic performance in terms of inflation and GDP growth of Sweden in relations to oil price shocks, focusing on the differences across two periods, pre and post 2008. By using a Vector Error Correction model and linear hypothesis testing we can see short term and long term correlations between the nominal oil price and three dependent variables, GDP, CPI and GDP deflator. Our hypothesis is that the effects of oil price shocks are indifferent across our estimation period and this would be in line with previous literature.  We find that the macroeconomic factors of GDP and inflation responds differently post 2008 and by using impulse response functions (IRFs) we can see how the dependent variables responds to an oil price shock. They show that oil shocks have permanent effects in GDP and GDP deflator but transitory effects in CPI, we found short run causality for GDP and CPI but not for GDP deflator.

Crude oil prices impact the world economy and are thus of interest to economic experts and politicians. Oil price’s volatile behaviour, which has moulded today’s world economy, society and politics, has motivated and continues to excite researchers for further study. This volatile behaviour is predicted to prompt more new and interesting research challenges. In the present research, machine learning and computational intelligence utilising historical quantitative data, with the linguistic element of online news services, are used to predict crude oil prices via five different models: (1) the Hierarchical Conceptual (HC) model; (2) the Artificial Neural Network-Quantitative (ANN-Q) model; (3) the Linguistic model; (4) the Rule-based Expert model; and, finally, (5) the Hybridisation of Linguistic and Quantitative (LQ) model. First, to understand the behaviour of the crude oil price market, the HC model functions as a platform to retrieve information that explains the behaviour of the market. This is retrieved from Google News articles using the keyword “Crude oil price”. Through a systematic approach, price data are classified into categories that explain the crude oil price’s level of impact on the market. The price data classification distinguishes crucial behaviour information contained in the articles. These distinguished data features ranked hierarchically according to the level of impact and used as reference to discover the numeric data implemented in model (2). Model (2) is developed to validate the features retrieved in model (1). It introduces the Back Propagation Neural Network (BPNN) technique as an alternative to conventional techniques used for forecasting the crude oil market. The BPNN technique is proven in model (2) to have produced more accurate and competitive results. Likewise, the features retrieved from model (1) are also validated and proven to cause market volatility. In model (3), a more systematic approach is introduced to extract the features from the news corpus. This approach applies a content utilisation technique to news articles and mines news sentiments by applying a fuzzy grammar fragment extraction. To extract the features from the news articles systematically, a domain-customised ‘dictionary’ containing grammar definitions is built beforehand. These retrieved features are used as the linguistic data to predict the market’s behaviour with crude oil price. A decision tree is also produced from this model which hierarchically delineates the events (i.e., the market’s rules) that made the market volatile, and later resulted in the production of model (4). Then, model (5) is built to complement the linguistic character performed in model (3) from the numeric prediction model made in model (2). To conclude, the hybridisation of these two models and the integration of models (1) to (5) in this research imitates the execution of crude oil market’s regulators in calculating their risk of actions before executing a price hedge in the market, wherein risk calculation is based on the ‘facts’ (quantitative data) and ‘rumours’ (linguistic data) collected. The hybridisation of quantitative and linguistic data in this study has shown promising accuracy outcomes, evidenced by the optimum value of directional accuracy and the minimum value of errors obtained.

Master of Arts / Department of Economics / Lance J. Bachmeier / The traditional view of oil price movements is that they represent exogenous changes in the supply of oil. In that case, oil price increases will hurt output. Recently, some have questioned whether oil price increases are actually due to higher demand for oil, in which case higher oil prices will be followed by higher output. This thesis develops a model that allows changes in the price of oil to have different effects depending on whether the price of oil and output growth are moving in the same direction (so that the increase in the price of oil was primarily due to an increase in the demand for oil) or in the opposite direction (so that the increase in the price of oil was primarily due to an oil supply shock). The paper presents three sets of results. First, we present the model results for the 1965-2008 time period. Then we look at the 1986-2008 period separately. Finally, we construct a forecasting model for the U.S. industrial production index. The model developed does not require making identifying assumptions and can be used with the data that is available on the internet, and is well understood. Maximum likelihood estimation, which is commonly used for non-linear estimation, is used to estimate the model. We find in-sample evidence in favor of our new model for the 1986-2008 subsample. The new model is unable to provide better out-of-sample forecasts for the 1986-2008 time period.

This dissertation spans topics related to global trade, oil prices, optimum currency areas, the eurozone, monetary independence, capital controls and the international monetary policy trilemma. It consists of four chapters and three essays. Chapter one provides a brief summary of all three essays. Chapter two investigates the impact of oil prices on global trade. It is concluded that when oil prices increase, countries start trading relatively more with their neighbors. As an application this chapter provides a new estimate of the eurozone effect on trade. Chapter three continues to study the eurozone and asks whether it is an optimum currency area using the member countries’ desired monetary policies. It is concluded that Greece, Spain, and Ireland have desired policies that are the least compatible with the common euro policy and are therefore the least likely to have formed an optimum currency area with the euro. Chapter four provides a new methodology in testing the international trilemma hypothesis. It is concluded that the trilemma holds in the context of the Asian countries.

Akcijų rinkos yra viena svarbiausių ekonomikos sudedamųjų dalių, be jos nebūtų įmanoma įsivaizduoti nei vienos išsivysčiusios pasaulio šalies. Bendrą akcijų rinkos vertę galima laikyti, pasaulio ar konkrečios šalies, regiono ekonominiu įvertinimu. Ji pastoviai yra veikiama įvairiausių veiksnių, tokių kaip infliacija, nedarbo lygis, vartojimo lygis, palūkanų normos, fiskalinės ir monetarinės politikos, bei naftos kainų. Šis veiksnys, kaip sudedamasis akcijų rinkos vienetas yra nagrinėjamas šiame darbe. Pasak Basher ir Sadorsky (2006) naftos kainos yra modernios ekonomikos kraujas. Nors nėra lengva prognozuoti kokia bus naftos paklausa ateityje, tačiau yra aišku kad naftos paklausa yra labai stipriai koreliuota su industriniu šalies išsivystymu. Ekonomikai stiprėjant energijos paklausa (ypatingai naftos) taip pat kyla. Labai svarbu išsiaiškinti, kas šiuos kainos pokyčius lemia, ar tai ilgalaikis reiškinys bei kokius pokyčius tai gali iššaukti ateityje. Tuo pačiu labai svarbu suprasti kokią įtaką ekonomikai turi naftos kaina. Tam kad tinkamai suprasti šį poveikį reikia ištirti ar yra ryšys tarp žaliavinės naftos ir vertybinių popierių. Šiam ryšiui egzistuojant, būtina nustatyti koks jis yra. Šiame darbe nagrinėjama kaip naftos kainos įtakoja akcijų rinkas. Taip pat tiriama kokius investicinius sprendimus galima priimti atsižvelgiant į naftos kainą, ir jos pokyčius. Tyrimo objektas – Naftos kainos įtaka akcijų rinkai. Šio darbo tikslas – Nustatyti kaip naftos kainos įtakoja... [toliau žr. visą tekstą] / Stock market is one of the main parts of economy, without it it is impossible to imagine any modern country. The total value of the stock market can be taken as the whole world’s or a certain country’s, region’s economical evaluation. It is always impacted with various economical factors like inflation, unemployment rate, consumption rate, interest rates, fiscal and monetary policies and oil prices. This factor, as one of the factors to stock market, is studied in this work. According to Basher and Sadorsky (2006) oil prices is a modern economies blood. Thought it is not easy to forecast what the demand of oil will be in the coming years, but it is totally clear that demand is very strongly correlated with industrial evolution. While the economy is getting stronger the demand for energy (especially oil) is rising too. It is very important to know what is causing these variations, is it a long-term phenomenon and what changes it can make in the future. It is also very important to know what impact oil price has on economy. To properly understand this we need to analyze is there a relation between oil price and stock market. If this relation exists we need to measure it. In this work we analyze how oil prices impacts the stock market. Also we analyze what investment decisions you can make, according to oil prices and it changes. Research object – oil price impact to stock market. This works goal – to measure, how oil prices affect the stock market, and to give recommendations... [to full text]

The airline industry is a major user of jet fuel and this constitutes a large component of the operating costs and is a risk coefficient for airlines. Several studies have been conducted on how oil price volatility affect stock prices and cash flows as well as how, in general, firms that uses derivatives experience lower stock returns volatility and stock s .The impact of oil price volatility on airline stock s and the impact of hedging on airline stock s have not been adequately examined, this paper fills this gap. By gathering daily frequency of oil spot prices to access the quarterly oil price volatility and stock s from 16 European airlines, we correlate quarterly oil price volatility to quarterly airline stock s as well as stock s and hedging percentages between 2010-2015, we reject the hypothesis that oil price volatility has an impact on airline stock s and that hedging reduces stock s. These findings therefore suggest that oil price volatility do not have a large impact on systematic risks or that hedging offset systematic risks. The findings are of interest to investors who want to make well informed investment decisions based on non-diversifiable equity risk since it has become popular for management recently to implement hedging policies to signal competency in risk management in order to attract investments.

Olja har under det förgångna seklet varit en av industrialiseringens stöttepelare. Idag, med omfattande satsningar inom hållbar utveckling så är inverkan av oljan högt aktuellt och inom en snar framtid kan den se en påtaglig nedbringa även om det har visats att dess relevans kommer kvarstå åtminstone fram till 2040. Tidigare forskning har påvisat att fluktuationer i oljepriset är en bidragsgivare till de systematiska risker företag ställs inför dagligen. Denna studie utvidgade analysområdet genom att välja ut länder med en netto-import av olja och sortera de på den andel relativa oljetillförsel som nationen erhållit gentemot nivån av systematisk risk från oljeprisfluktuationer som företagen ställs inför. Analysen utfördes över 120 Finansiella företag i 12 europeiska länder. Det anträffades utpräglade mönster i studiens resultat som kan antyda en koppling mellan dessa variabler, men resultaten återfinns i majoritet till att inte uppnå statistisk signifikans. Vidare kan studiens modell utgöra en bas för vidare forskning inom området.