The goal of this master thesis is to analyze impact of shocks in oil prices to automobile industry stock prices and returns. We decompose oil price shocks on oil supply shocks, aggregate demand shocks and oil-specific demand shocks and assess their individual impacts on these stock prices/returns. This is done using the vector autoregression (VAR) methodology which allows us to compute impulse responses, that is the reaction paths on the individual shocks. In addition to linear VARs we also employ threshold VAR models in order to capture nonlinearities in impulse responses and besides the aggregate automobile stock price index we compute these nonlinear impulse responses also for some selected individual car producers. We think that this analysis have two different uses. First, it can be beneficial to stock market investors. Second, it can be used by policymakers in countries such as Slovakia and the Czech Republic, which are relatively heavily dependent on automotive industry. 1

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.

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 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.

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.

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.

The thesis is focused on the changes in the terms of trade in Czech international trade in the term of from 2005 to 2015, as the period after the Czech Republic joined the European Union. The terms of trade are an important indicator of the benefits and loses of international trade. The main aim is to analyze the changes of terms of trade, the causes of their changes, and the impact on the real economy. The direction of the overall terms of trade index was highly unsettled, and did not actually generated additional gains in the economy not over the reporting period. The overall terms of trades were most influenced by the price development of two groups of the Standard International Trade Classification, Crude materials and lubricants, and machinery and transport equipment. The prices of Crude materials and lubricants are determined mainly by changes in the oil prices. These were very volatile in the reporting period, the especially the collapse of the prices in both 2009 and 2014-2015, had a significant impact on the import prices of the Czech economy. The thesis also analyzes the impact of exchange rate on the international trade prices, in the period since November 2013, i.e. after the Czech National Bank has committed to maintain the rate of Czech koruna against the Euro above the level of 27 CZK/EUR, which helped to protect the economy from deflations and enhance the economic growth. The effect of the weak crown, that favored the Czech exporters, however a faded over time.