Oil Price

Gasoline is the petroleum product whose price is most visible and, therefore, always under public scrutiny. Many claim there is an asymmetric relationship between gasoline and oil prices - specifically, gasoline price changes follow oil price changes more quickly when oil prices are rising than when they are falling. To explore this issue, Nathan Balke, Stephen Brown and Mine Yucel

Climbing oil prices, increasing demand for energy, and energy supply disruptions have -once again -focused the public interest on energy and energy security issues. In this paper we discuss the power of electronics as a means for addressing current challenges in energy production, distribution, and for using energy more efficiently than today. It is argued that the full power of electronic energy management has yet to be exploited. One reason for this lies in a still largely unutilized opportunity for improving the energy efficiency of systems in many application areas. State-of-the-art electronic control systems will play an ever increasing part in managing energy systems. The realization of the enormous potential of this technology will require new forms of collaboration of the energy and information technology sector and an improved shared vision of public policy makers and the industry.

We provide an arbitrage-free valuation of exhaustible resource firms through extending the Gibson and Schwartz (1990) model and also the Jamshidian and Fein (1990) solution to valuing an entire petroleum firm based on quoted oil futures. Our solutions are compared to accounting, traditional finance and to stockmarket valuations on a daily basis. An alternative expression of the valuations relative to stockmarket prices is in terms of the time varying implied ‘market price’ of convenience yield risk. Initial illustrations show that the implied convenience yield risk is not necessarily consistent between stockmarket and derivative market participants. Finally, we calculate the sensitivities of petroleum firm values to changes in oil prices, the convenience yield observable on NYMEX, and oil price volatilities. These partial derivatives show some of the complexities in the dynamic hedging process of using the contingent claims approach to valuing (and hedging) real assets.

This paper analyzes empirically whether the exchange rates and crude oil prices have explanatory power over Indian Stock market prices or not. The data used for this study are daily stock price indexes of BSE Sensex, Crude oil price and exchange rates for the period 2nd January 1991 – 12th ,December 2007. Engel granger and cointegration tests, VECM and variance

Russian monetary policy has failed persistently to achieve sustained low inflation, both in absolute terms and relative to the peer group of countries similarly exiting from Soviet-style central planning. This paper explores the reasons for this state of affairs by analysing the kind of monetary policy that has been pursued by the central bank during the period 1995 to 2009. Our contribution is to search for a possible transmission channel between the real interest rate, inflation rate, exchange rate, output growth and foreign reserve growth, after having controlled for the effect of oil price inflation. Using a vector autoregressive model in error-correction form and using sign restrictions methodology, we show that the monetary authorities' failure to abate double-digit inflation appears to be driven by the policy of exchange rate targeting, as reflected in our identified exchange rate shocks.

During the periods of globalization and deregulation, it is become very common for the equity market of a country to respond to the movement of prices of some internationally traded goods. The effort, trying to achieve in this study, relates to how Indian equity market responds to the movement of Crude Oil Prices. BSE Sensex and S&P CNX Nifty have been taken as the indicator of stock market performance. Daily closing prices of the equity indices and the price of Crude Oil for a period of 11 years starting from July, 2001 to June, 2012 have been used to assess the co-movement of prices among them. The study applies the concept of Unit Root test, Johansen's Cointegration test, Vector Error Correction Model (VECM) and Granger causality test to establish the long-run and short-run causal relationship between them. From the Trace test statistics and Maximum Eigen statistics we conclude that there exists one cointegrating vector for each case i.e., there exist a long term relationship between oil price and stock indices. The coefficient of the cointegrating equation shows that the relationship is positive and statistically significant. The VECM result shows a long-run causality moves from Indian stock market to oil price and the results of the Granger Causality test confirms the same unidirectional movement in short-run also.

This paper analyzes empirically whether the exchange rates and crude oil prices have explanatory power over Indian Stock market prices or not. The data used for this study are daily stock price indexes of BSE Sensex, Crude oil price and exchange rates for the period 2 nd January 1991 – 12th ,December 2007. Engel-Granger and cointegration tests, VECM and variance Decomposition tests were used in the study to explain the long run relations among variables questioned. Obtained results illustrate that stock price indexes are cointegrated with crude oil prices and exchange rates by providing direct long run equilibrium relation. Our results also indicate that the stock market prices are influenced by oil and exchange rate at lag -50 where as stock market prices are influenced by exchange rate only at lag-25. The results also indicates that the average real returns in the era of rupee depreciation are lesser than that of appreciation period.

While the Great Recession and ensuing “Arab Spring” have taken a heavy toll on many nations in North Africa and the Middle East, yielding unprecedented volatility in country risk metrics, GCC member-states, with the exception of Bahrain, seemed relatively immune to economic decline. But the 2014 Saudi-Qatari Rift, which can be interpreted as a fight between the world’s leading oil and natural gas producers, could have deeper and longer lasting consequences than previous crises....

This study aims to forecast oil prices using evolutionary techniques such as gene expression programming (GEP) and artificial neural network (NN) models to predict oil prices over the period from January 2, 1986 to June 12, 2012. Autoregressive integrated moving average (ARIMA) models are employed to benchmark evolutionary models. The results reveal that the GEP technique outperforms traditional statistical techniques in predicting oil prices. Further, the GEP model outperforms the NN and the ARIMA models in terms of the mean squared error, the root mean squared error and the mean absolute error. Finally, the GEP model also has the highest explanatory power as measured by the R-squared statistic. The results of this study have important implications for both theory and practice.

We assess the impact of oil shocks on euro-area macroeconomic variables by estimating a new-Keynesian small open economy model with Bayesian methods. Oil price is determined according to supply and demand conditions in the world oil market. We find that the impact of an increase in the price of oil depends upon the underlying sources of variation: when the driver

This report provides practical guidance to central, regional, and local government agencies on how to manage the transport challenges associated with rising oil prices. The three main sections of the report are: • Modelling Prices for Transport Fuels – several oil price forecasts are combined to develop a view on future oil prices. This shows annual average oil prices staying