This study aims to determine and analyze the influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and the exchange rate of rupiah/US dollar towards the transmission on CPO export prices of Indonesia. This study uses quantitative analysis model with the approach of vector autogression model (VAR) which includes three main analysis tools namely Granger causality test, impulse response function (IRF) and forecast error decomposition of variance (FEDV). The variables which are used in this research are world petroleum price, world soybean oil price, CPO price of Rotterdam, CPO export price of Indonesia, fresh fruit bunch price and real exchange rate (real exchange rate). From Granger Causality test result, The price transmission process takes place the plot as follows: world crude oil prices significantly influence the CPO price of world (Rotterdam) which will significantly influence the world soybean oil prices and so on have a significant influence on the value of the real exchange rate which will influence the price of fresh fruit bunches and ultimately have a significant influence on CPO price export of Indonesia. From the estimation result of VAR model, there are significant influences of world crude oil price shocks, world soybean oil prices, world CPO prices, palm oil TBS prices and rupiah/US dollar exchange rates simultaneously to the transmission on CPO export prices of Indonesia. Based on analysis of Impulse response and variance decomposition, in the first period, one hundred percent average variability of CPO export price growth is significantly explained by the average growth of CPO export prices itself. In the subsequent period, the average variability of CPO export price growth is significantly explained by the average growth of CPO export price itself as well as other variables.
The identification of a person through the iris of the eye of the very important issues to prove his identity. It was a preliminary treatment of the samples used in the study program. Then the samples classified into four groups namely (flower iris, jewels iris, shaker iris and stream iris. Have been through the program to find statistical features of each sample from each group and then re-create these features by way wavelet using MATLAB software, and these samples were (1) (15image of the iris of the type flower iris). (2) (15image of the iris of the type jewels iris). (3) (15 image of the iris of the type shaker iris) (4) (15 image of the iris of the type stream iris). When treatment was extracted a number of Mini (mean, std., var., Energy, Homogeneity, and Entropy). Features that represent each iris were used artificial neural network with a reverse spread as a way to distinguish. The four varieties and the number of inputs to the neural network Is six (the number of statistical features used) for all samples were neural network training them and extract precision results to distinguish primary treatment samples. Conversion technology application wavelet using the study samples and extract the same as the previous samples after image processing and conversion wavelets using (wavelet-2D) a reverse spreading neural network as a way to distinguish the four varieties previous input itself For all samples)
This study empirically estimates the behaviour of demand for liquid financial assets, as it is one of the most important recurring issues in theory and application of macroeconomics, and examines the stability of the same in the Sudanese context. The study covered the period 1993 to 2012. The results show that, there is a strong transactions motive for holding liquid financial assets by individuals and banks in Sudan. That happened after the liberalization process and utilization of the credit and debit cards. And also, implementation of Islamic financing techniques; specifically, after the open market policy that allow the functioning of private and Islamic banks along with Khartoum Securities Exchange to join the financial sector. The reliability of the estimation results were questioned due to the shortcomings of traditional techniques. A modern estimation technique was introduced, like cointegration technique. However, findings of cointegration have been interpreted as a sign of constancy of parameter estimates. The empirical analysis shows that the demand for liquid financial assets is a function of national income and negatively behaving with changes in prices and rates of return. ADF test for unit roots results show a non-stationary behavior, and then VAR is applied along with Johansen co-integration method analysis of a multivariate system of equations to test for the existence of a long run relationship between the determinants that shows the existence of a reasonably stable demand for money and other liquid financial assets function in Sudan. Since inflation (continuous prices rising) is exogenous in demand for money and other liquid financial assets function, therefore, the central monetary authority, namely, Central Bank of Sudan and Ministry of Finance are not able to control the price-rises in such open markets