JOURNAL OF ADMINISTRATION AND ECONOMICS

Options pricel are generally determined by a tradeoff between risk and return. Options - prices models generally rely on the volatility index in stock market prices, which represents the risk to the buyer or the option seller in the financial market. This has led to the emergence of many models of pricing options that generated different values for one option according to the assumptions, parameters and techniques used in each model , and hers lies the problem of this research, that the application of pricing models that assume volatility instability can produce option's Prices closer to market prices. The aim of this research is to apply one of the models of random volatility in the samples-prile of options, namely Heston Model. To achieve the objective of the research, the historical published prices of the shares of (4) large companies operating in the US technology sector for the period from (29/12/2015) to (19/2/2016) for a sample consisting of (12) options on the shares of those companies. The research had a set of conclusions and recommendations, the most important of which is that the prices of Heston model almost close to its market price, but this model depends on the accuracy of its prices on the change in the value of the parameters it consists of as well as the complexity that accompanies its application.

The purpose of this research is embodied in studying the effect of production capacity utilization on the operating profitability, for the company which does not make use of its available production capacity or that which suffer from a deficiency in its production capacity, its production costs rise due to a decrease in the production levels and consequently to a decline in the profits, which proves that there is an expected relationship between the amount of the production capacity utilization and the operating profitability. A non-random intentional sample has been selected including (16) Iraqi industrial corporations listed in Iraq Stock Exchange for period of (10) consecutive years (2006-2015). The research variables have been measured and analyzed quantitatively and statistically in description and explanation using the method of panel data analysis which combines between cross-sectional data including the corporations and the time-series data represented by years, which works on rising the efficiency of estimating the parameters of the studied model in comparison with the model capabilities in case of using the cross-sectional data or the time-series data alone separately, as well as employing the description instruments and statistical inference. The research problem is explained based on one main hypothesis states that the variance in the levels of production capacity utilization results in a statistically significant opposite variance in the operating profitability. The research reached to many conclusions, perhaps the most important of which is what confirms the validity of the research hypothesis, as it becomes clear that the higher

The paper deals with estimation shape parameter of Burr distribution type X (which also called two parameter exponential Rayleigh).The methods of estimation are Maximum likelihood method and percentiles estimator (PER), as well as Bayesian estimator using Jeffery's prior distribution. The Bayes estimator of shape parameter (θ) is conducted using different loss function, like squared error loss function and also precautionary loss function. The comparison is done using statistical Measures Mean Square error (MSE) take different sample size (n=15,30,50,100) and different set of initial values for (θ,λ) Keywords: Burr type X distribution, Maximum likelihood estimator, Percentiles Estimator, Bayes estimator, Mean squared error.

The purpose of this research is to highlight the importance of
Mahalnobis has statistic (D2) in the discrimination between two groups.
To do that, the researcher formulated a rule of distinction derived from
(D2) and distributed (F) called (RD2 ). Also (D2) has you used to construct
a linear discriminant function (L. D. F) and evaluate its classification of
random sample objects

Logistic regression is an important statistical tool for modeling a set of independent variables that effect in a binary response variable. Most practitioners of statistics have used logistic regression in many scientific areas. Unfortunately, they are not aware that the method of estimation logistic regression breaks down in the presence of outlying data point(s) in the original dataset. The objective of this paper is to bring out the attention of respectful researchers in various scientific areas to single logistic regression diagnostics methods, and the effect of the presence of outliers on logistic regression estimates. Real data are considered in this paper and the results show the high performance of diagnostic methods to detect these observations that are affected on the logistic regression estimates. Some graphs are discussed and supported the results of diagnostic method the influence of outlying data point on the fitted logistic model.

Jordan has adopted various policies to engage foreign direct investment in light of the country's urgent need to increase economic resources, thus providing many investment opportunities for foreign investors. There is no doubt according to most studies the foreign direct investment contributes to increase economic growth rates. This paper focuses on the impact of foreign direct investment on economic growth in Jordan for the period from 2000 to 2017. Using the EViews program, relying on a set of macroeconomic variables, and using the standard analytical approach, the paper aims to identify the impact of foreign direct investment on economic growth. The paper found a positive impact of foreign investment on economic growth. Based on this result, the ultimate goal of the Jordanian government is to seek to attract more foreign direct investment to increase the rate of economic growth. Keywords: Jordan, economic growth, foreign direct investmentJEL Classification: F21, O4

This study aims to use the six sigma in the Faculty of Administration and Economics at the University of Sulaimani, and clarify the importance of its application in the constant improvement of services and educational aspects and to identify the obstacles faced by the college when using this method in the academic year (2015-2016). The main aim is to apply the technique of six sigma on college of Administration and economics at university of Suleimanah and the aim of this research is to determine the range of six sigma for departments and find the value of six sigma according to Gender. The total number of students is (1709) students obtained bachelor’s degree. The most important findings are that the Department of Economics is closer to the six sigma scale followed by the accounting department. The statistics and administration departments have the same result. It is also concluded that the females are closer to six sigma than males. The departments of Administration and Economics have the same range with Six Sigma technique for pre million 3.4 defective (about DPMO and Level of Sigma).

In this research, the researcher has derived different standard Bayes estimators for scale parameter of Exponential distribution by using balanced and unbalanced loss function. This estimation includes two cases availability and lack of primary information (Jeffery and Gamma conjugate priors) about the phenomenon studied. Simulation experiments with different sample sizes and virtual parameters have been built for this purpose, then a comparison is mads between these estimators depend on the Mean Square Error (MSE) criteria. The results have demonstrating the superiority of balanced loss functions in the absence of prior information about the phenomenon studied, while they may not have the same efficiency if availability of prior information about this phenomenon is cannot found.Keywords: Exponential Distribution, Bayes Method, Balanced Loss Functions .