The volatility of the financial markets and the oil market plays a major role in influencing macroeconomic activity, as well as the high interaction between the both markets and the remarkable sensitivity to their each other fluctuations which cause the undesirable impact on other economic sectors as an expected result due the mentioned interaction.

The study aimed to analyze the relationship between the volatility of the major US market indices represented by the DJIA index, S & P500, due to their comprehensiveness of the financial market, as they summarize the performance of the entire US market which is the largest economy in the world, as well as the difference in the calculation mechanism, and oi

The goal of the study is to discover the best model for forecasting the exchange rate of the US dollar against the Iraqi dinar by analyzing time series using the Box Jenkis approach, which is one of the most significant subjects in the statistical sciences employed in the analysis. The exchange rate of the dollar is considered one of the most important determinants of the relative level of the health of the country's economy. It is considered the most watched, analyzed and manipulated measure by the government. There are factors affecting in determining the exchange rate, the most important of which are the amount of money, interest rate and local inflation global balance of payments. The data for the research that represents the exchange r

This research aims to predict the value of the maximum daily loss that the fixed-return securities portfolio may suffer in Qatar National Bank - Syria, and for this purpose data were collected for risk factors that affect the value of the portfolio represented by the time structure of interest rates in the United States of America over the extended period Between 2017 and 2018, in addition to data related to the composition of the bonds portfolio of Qatar National Bank of Syria in 2017, And then employing Monte Carlo simulation models to predict the maximum loss that may be exposed to this portfolio in the future. The results of the Monte Carlo simulation showed the possibility of decreasing the value at risk in the future due to the dec

Most of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment.  This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020.  The results revealed that positive and negative shocks for both exchange rates have unequal effects on

In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as a mechanism and encompasses

Research aims to identify the immediate impact of the announcement of mergers in the stockholders and the feasibility of gain abnormal return and benefiting from  asymmetric information during the announcement that unite 30 days before the announcement of the merger, and announcement day, and 30 days after the announcement of the merger. It was the largest and most important mergers and acquisitions pick that occurred during the global financial crisis, specifically in health care/pharmaceutical industry, Pfizer and Wyeth merger with Novartis acquisition on Alcon. search has adopted three hypotheses: the first hypothesis that ((achieves the target company's shareholders positive abnormal return (or negative) during and befor

Investments in shares represent an essential component of companies’ assets and a source of profit making resources. These investments are linked to the areas of trading and speculation, which is reflected on their market value, which makes accounting for and evaluating these investments require their own accounting standards, and thus several international standards were issued regarding this as well as a statement of their impact on growth Sustainable, as the research problem is to show the impact of measuring investments in shares according to international accounting and financial reporting standards on the sustainable growth of economic units, the research sample and its reflection on audit procedures. In accordance with i

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev