This thesis is based on three papers examining Gulf Cooperation Council (GCC) financial markets. The member countries of the GCC are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates. These countries have transitioned from developing to frontier markets over the past ten years, but there is considerable debate about whether GCC economies are efficient or affected by shocks in oil and other commodity markets. The first paper (chapter 2) considers GCC stock market returns and examines how they are affected by oil price shocks using a bivariate VAR-GARCH(1,1) approach. The conclusion of this essay is that GCC economies are more affected by shocks than are other countries considered for comparison purposes. The second paper (chapter 3) discusses how food prices are affected by oil price shocks, and it examines possible parameter shifts between food and oil that result from four recent events, including renewable fuel policies and the financial crisis. The third paper (chapter 4) uses an empirical approach to compare a least squares model and a non-linear Markov switching model to measure the effect of newspaper sentiment on stock market performance. The results indicate that all information is important to stock market investors and that non-linear models are better predictors of stock market performance then linear models when using data from newspaper articles. Chapter 5 offers some final conclusions and remarks.

The objective of this research concerns identifying whether or not there is a relationship between oil price increases in a given quarter and the likelihood of a recession in the subsequent quarter. The data used is gathered from the St. Louis Fed's Fred II, the National Bureau of Economic Research, and the Energy Information Administration to generate modified variables. These variables are tested using a qualitative dependent variable, recession, in a binary choice model. The findings validated the assumption that oil prices do have a correlation with recessions, and that the relationship is a direct one. Based on the model, an increase in the price of oil will positively affect the likelihood of a "recession" outcome versus the alternative, "no recession". It is anticipated that the results will inspire future research into the causes and effects of oil price surges, as well as the determinants of economic contractions in the future based on policy decisions and economic decision-making practices in the present.

Yes / This is a pioneering effort to test the comparative performance of two competing models for out-of-sample forecasting the term structure of volatility of crude oil price changes employing both symmetric and asymmetric evaluation criteria. Under symmetric error statistics, our empirical model using the estimated growth factor of volatility through time is overall superior, and it beats in most cases the benchmark model of the square-root-of-time for holding periods between one and 250 days. Under asymmetric error statistics, if over-prediction (under-prediction) of volatility is undesirable, the empirical (benchmark) model is consistently superior. Relative performance of the empirical model is much higher for holding periods up to fifty days.

This thesis focuses on the relationship between the Organisation of Petroleum Exporting Countries (OPEC) economies and global climate change mitigation policies with a view to determining the energy exports demand security risks of OPEC member states. The successful implementation of a universally adopted climate regime has been marred with controversies as different interest groups have raised their concerns about all the options presented so far. OPEC as the major crude oil exporting group in the world has been in the forefront of these debates and negotiations. OPEC’s major concern is the envisaged adverse impacts of the industrialised countries carbon reductions on its members' economies. Several studies have shown that when industrialised countries adopt carbon dioxide emissions reduction policies in line with the United Nations Framework Convention on Climate Change, such as carbon taxes and energy efficiency strategies, OPEC’s net price of crude oil decreases at the same time as a reduction in the quantity of crude oil products sold. OPEC believes that such climate change policy-induced fall in crude oil exports revenues would have a significant negative effect on its members' economies. With the limitations related to the assumptions of the existing energy economy models on the impacts of climate change mitigation policies on OPEC’s economies (Barnett et al, 2004), this study opts for a risk based model. This model quantifies the energy exports demand security risks of OPEC members with special interest on crude oil. This study also investigates the effects of carbon reduction policies on crude oil prices vis-à-vis the impacts of crude oil prices on OPEC’s economies. To address these three main issues, this thesis adopts a three-prong approach. The first paper addresses the impacts of climate change mitigation on crude oil prices using a dynamic panel model. Results from the estimated dynamic panel model show that the relationship between crude oil prices and climate change mitigation is positive. The results also indicate that a 1% change in carbon intensity causes a 1.6% and 8.4% changes in crude oil prices in the short run and long run, respectively. The second paper focuses on the impacts of crude oil prices on OPEC economies using a panel vector auto regression (VAR) approach, highlighting the exposure of OPEC members to the volatile crude oil prices. The findings from the panel VAR model show that the relationship between OPEC members’ economic growth and crude oil prices is positive and economic growth in OPEC member states respond positively and significantly to a 10% deviation in crude oil prices by 1.4% in the short run and 1.7% in the long run. The third paper creates an index of the risks OPEC members face when there is a decline in the demand for their crude oil exports. To show these risks, this study develops two indexes to show the country level risks and the contributions to the OPEC-wide risks exposure. The results from the indexes show that OPEC members that are more dependent on crude oil exports are faced with more energy exports demand risks. The findings from this thesis are relevant for the development of a new OPEC energy policy that should accommodate the realities of a sustainable global climate regime. They are also useful to the respective governments of the countries that are members of OPEC and non-OPEC crude oil exporting countries. Finally, the outcomes of this thesis also contribute to the climate change and energy economics literature, especially for academic and subsequent research purposes.

Studier om oljepriser och finansiella marknader är relativt få i jämförelse med de studier som finns om förhållandet mellan oljepriser och makroekonomiska variabler. Olja betraktas som en av de viktigaste produktionsfaktorerna, vilket innebär att förändringar i oljepriser påverkar företags kostnader och därmed aktiemarknaden. Att studera förhållandet mellan oljepris och aktiemarknader är av vikt för ett flertal intressenter, bland annat investerare, banker ochportföljförvaltare. Investerare får till exempel svårigheter att maximera aktieavkastning om de inte förstår sambandet mellan oljepris och finansiella marknader. I studien analyserades förhållandet mellan oljepris och den svenska aktiemarknaden med koppling till ränta och växelkurs. Studien baserades på en kvantitativ undersökning med deduktiv ansats, utifrån data över tidsperioden 1991 till 2016. De statistiska tester som genomfördes var en korrelationsanalys, en bivariat och en multipel regressionsanalys. Resultaten visade att det finns ett positivt förhållande mellan oljepris och den svenskaaktiemarknaden. Vidare observerades ett negativt förhållande mellan ränta och den svenska aktiemarknaden och ett positivt förhållande mellan växelkurs och den svenska aktiemarknaden. Studiens första hypotes gällande de grundläggande variablerna förkastades eftersom det ursprungliga antagandet var att ett negativt förhållande skulle råda mellan oljepris och aktiemarknaden i Sverige. Däremot visade studien stöd för resterande två hypoteser. Studiens resultat är inte applicerbart på alla aktiemarknader utan kan begränsas tillbörser i oljeimporterande, utvecklade länder med liknande ekonomisk och politisk struktur som i Sverige. Vidare forskning inom området är nödvändig. Framtida studier bör inkludera fler variabler och ha större fokus på de bakomliggande orsakerna till förändringar i oljepris och deras eventuella koppling till aktiemarknader. Det kan även vara av värde att inkluderasocioekonomiska och politiska faktorer och undersöka oljeprisets effekt inom olika branscher och sektorer på aktiemarknaden. / Studies on oil prices and financial markets are relatively few in comparison to the studies on the relationship between oil prices and macroeconomic variables. Oil is considered to be one of the main production factors, which means that changes in oil prices affect corporate costs and thus the stock market. Studies of the relationship between oil price and stock markets areimportant for a number of stakeholders, including investors, banks and portfolio managers. For example, investors get difficulties in maximizing share returns if they do not understand the correlation between oil prices and financial markets.In the study, the relationship between oil prices and the Swedish stock market and its connection with interest rates and exchange rates was analyzed. The study was based on a quantitative survey with a deductive approach, with data over the period 1991 to 2016. The statistical tests conducted were a correlation analysis, a bivariate and a multiple regression analysis. The results showed that there is a positive relationship between oil prices and theSwedish stock market. Furthermore, a negative relationship between interest rates and the Swedish stock market was observed and also a positive relationship between the exchange rate and the Swedish stock market. The study's first hypothesis regarding the basic variables was rejected, since the original assumption was that a negative ratio would prevail between oil prices and the Swedish stock market. On the other hand, the study showed support for the remaining two hypotheses. The study's results are not applicable to all stock markets but can be limited to financial markets in oil importing, developed countries with similar economic and political structure as in Sweden. Further research in the field is necessary. Future studies should include more variables and focus more on the underlying causes of changes in oilprices and their possible links with stock markets. It may also be useful to include socioeconomic and political factors, as well as to investigate the effect of oil prices in different sectors in the stock market.

Despite the extent of a theoretical framework in financial market studies, a vast majority of the traders, investors and computer scientists have relied only on technical and timeseries data for predicting future prices. So far, the forecasting models have rarely incorporated macro-economic and market fundamentals successfully, especially with short-term predictions ranging less than a month. In this investigation on the predictability of certain financial markets, an attempt has been made to incorporate a un-exampled and encompassing set of parameters into an Artificial Neural Network prediction system. Experiments were carried out on three market instruments ??? namely currency exchange rates, share prices and oil prices. The choice of parameters for inclusion or exclusion, and the time frame adopted for the experimental sets were derived from the market literature. Good directional prediction accuracies were achieved for currency exchange rates and share prices with certain parameters as inputs, which consisted of predicting short-term movements based on past movements. These predictions were better than the results produced by a traditional least square prediction method. The trading strategy developed based on the predictions also achieved a higher percentage of winning trades. No significant predictions were observed for oil prices. These results open up questions in the microstructure of the markets and provide an insight into the inputs required for market forecasting in the corresponding time frame, for future investigation. The study concludes by advocating the use of trend based input parameters and suggests ways to improve neural network forecasting models.

This thesis examines the relationship between food prices, oil prices, carbon emission prices, exchange rates and global risk perception. To obtain the effects of these variables on the food prices, Toda and Yamamoto procedure is employed for 5-day week daily time series covering the period February 27, 2008 and March 21, 2011. The empirical results indicate that only volatility index Granger causes food prices. Furthermore, according to results of generalized impulse response plots food prices respond to all variables in the short run.

This thesis consists of three essays on risk management in crude oil markets. In the first essay, the valuation of an oil sands project is studied using real options approach. Oil sands production consumes substantial amount of natural gas during extracting and upgrading. Natural gas prices are known to be stochastic and highly volatile which introduces a risk factor that needs to be taken into account. The essay studies the impact of this risk factor on the value of an oil sands project and its optimal operation. The essay takes into account the co-movement between crude oil and natural gas markets and, accordingly, proposes two models: one incorporates a long-run link between the two markets while the other has no such link. The valuation problem is solved using the Least Square Monte Carlo (LSMC) method proposed by Longsta ff and Schwartz (2001) for valuing American options. The valuation results show that incorporating a long-run relationship between the two markets is a very crucial decision in the value of the project and in its optimal operation. The essay shows that ignoring this long-run relationship makes the optimal policy sensitive to the dynamics of natural gas prices. On the other hand, incorporating this long-run relationship makes the dynamics of natural gas price process have a very low impact on valuation and the optimal operating policy. In the second essay, the relationship between the slope of the futures term structure, or the forward curve, and volatility in the crude oil market is investigated using a measure of the slope based on principal component analysis (PCA). The essay begins by reviewing the main theories of the relation between spot and futures prices and considering the implication of each theory on the relation between the slope of the forward curve and volatility. The diagonal VECH model of Bollerslev et al. (1988) was used to analyse the relationship between of the forward curve slope and the variances of the spot and futures prices and the covariance between them. The results show that there is a significant quadratic relationship and that exploiting this relation improves the hedging performance using futures contracts. The third essay attempts to model the spot price process of crude oil using the notion of convenience yield in a regime switching framework. Unlike the existing studies, which assume the convenience yield to have either a constant value or to have a stochastic behaviour with mean reversion to one equilibrium level, the model of this essay extends the Brennan and Schwartz (1985) model to allows for regime switching in the convenience yield along with the other parameters. In the essay, a closed form solution for the futures price is derived. The parameters are estimated using an extension to the Kalman filter proposed by Kim (1994). The regime switching one-factor model of this study does a reasonable job and the transitional probabilities play an important role in shaping the futures term structure implied by the model.

In the first part of this thesis the prices of six non-ferrous metals (aluminum, copper, lead, nickel, tin, and zinc) are used to assess the forecasting performance of GARCH models. We find that the forecasting performances of GARCH, EGARCH, and TGARCH models are similar. However, we suggest the use of the GARCH model because it is more parsimonious and has a slightly better statistical performance than the other two. In the second part, the prices of six non-ferrous metals and the price of crude oil are used to examine the dynamic links between oil and metal returns by using the BEKK specification of the multivariate GARCH model and the Granger causality-in-variance tests. Results of our study agree with the previous studies in that the crude oil market volatility leads all non-ferrous metal markets. In order to move as far away from the effects of 9/11, daily data for the period December 12, 2003 &ndash / December 15, 2008 is used for the data analysis part of the thesis.

In this thesis the relationship between Brent oil prices, LME copper prices, Turkish gold and silver spot prices, XU100 index, interest rate and exchange rate is examined. Their long run Granger causality relationship is investigated by looking at Wald statistics. The short run relationship between them is examined by using generalized impulse responses. The data range is from January 2, 2002 to February 24, 2011. Due to the oil crisis in 2008, we divide the data into three periods: January 2, 2002 to December 31 as first period, 2007, from January 1, 2008 to December 31 as second period, 2008 and January 1, 2009 and February 24, 2011 as third period. We conduct each test separately for these periods but in third period we use Toda-Yamamoto procedure since maximum order of integration is 1.