ACCOUNTING AND FINANCIAL SCIENCES JOURNAL

The importance of the research lies in the sensitive nature of the risk control process in central banks, which is more important than other financial institutions. The matter does not stop at only protecting the value of investments, but also extends to preserving the reputation of the central bank and enhancing the confidence of the financial markets. Hence, it has become necessary to adopt the value-at-risk (VaR) model to measure and predict the risks of investing in foreign reserves, to enable central banks to reallocate the investment portfolio quickly and easily to avoid capital losses. The Norwegian central bank is considered a successful monetary experiment in managing the risks of its investments within European countries that have not joined the European Monetary Union, as the Norwegian economy is often classified as a distinguished model that combines the efficiency of the free market with strong government intervention.

This study aims to predict the credit risk of the companies under investigation by applying the structural KMV model. The model relies on market data represented by stock prices, the number of shares, and their volatility, in addition to the company’s financial obligations. The model focuses on estimating the market value and volatility of the firm’s assets using Merton’s model equations, which are solved through the Solver algorithm to obtain the best possible estimate of asset value. Subsequently, the Distance to Default (DD) is calculated, and the Expected Default Frequency (EDF) is derived to measure the level of credit risk for each company in a precise quantitative manner. The study adopts the yield on U.S. Treasury bonds as the risk-free rate, selecting maturities consistent with each company’s debt horizon, based on daily yield curve data.
The results reveal noticeable differences in risk levels among the companies. They indicate that an increase in equity value leads to a higher Distance to Default and a lower probability of default, reflecting the inverse relationship between financial strength and credit risk level. The findings confirm the importance of the KMV model as a practical tool for measuring and predicting credit risk based on market data.

This research aims to identify the factors influencing external audit fees and analyze their relative importance from the perspectives of practitioners in Syria and Iraq. Furthermore, the study explores the specific methods employed for fee determination in both countries. To achieve these objectives, a descriptive-analytical approach was adopted, utilizing a structured questionnaire for data collection. The study population consisted of external auditors in both nations, with a random sample of 30 individuals selected from each country. The response rate was 80% for Syrian auditors (n = 24) and 90% for Iraqi auditors (n = 27). The collected data were subjected to rigorous statistical analysis to test the formulated hypotheses and categorize the relative importance of the identified factors Findings..
The results indicate that from the perspective of Syrian external auditors, the primary factors influencing audit fees and, subsequently, audit quality are:
The duration required to complete the audit engagement.
The size of the client’s entity.
The efficiency of the client’s internal audit function. Discrepancies in the profession's regulatory environment.
Wage levels and prevailing working conditions.
Conversely, Iraqi external auditors identified the most significant factors as: The size of the client’s entity.
The integrity and robustness of the client’s internal control system. Market competition within the auditing sector.
The necessity for a standardized regulatory framework for fee-pricing policies.
The study concludes that the fixed-fee method is the most significant from the viewpoint of Iraqi auditors, whereas the variable-fee method is more prominent among Syrian auditors. Finally, the findings demonstrate that audit fee determinants significantly impact audit quality through variables such as the regulatory environment, market competition, wage structures, and the urgent need

This research aimed to explore the impact of digital marketing mix elements on achieving competitive advantage for Palestinian insurance companies amidst rapid digital transformation and increasing reliance on electronic media in service delivery. It examined eight digital marketing mix elements (Product, Price, Promotion, Distribution, Processes, Physical Environment, People, and Performance) and linked them to dimensions of competitive advantage (Cost, Quality, Innovation, Flexibility, and Time). Adopting a descriptive-analytical correlational methodology, data was collected from a sample of 313 employees working in Palestinian insurance companies, using an electronic five-point Likert scale questionnaire. Data were analyzed statistically using SPSS, where the Pearson correlation coefficient was used to test relationships between variables, simple linear regression analysis to measure impacts, and Cronbach's Alpha coefficient to test reliability. The findings revealed a statistically significant impact of the overall digital marketing mix on competitive advantage, and that each of the eight elements has an independent and significant impact on achieving it. The elements of Digital Physical Environment, Digital Processes, and Digital People were found to be the most influential. It also showed that designing attractive and user-friendly digital insurance goods and services enhances customer satisfaction and loyalty, providing companies with a distinct edge in dynamic markets. The research recommended the necessity of developing integrated and seamless digital platforms, investing in advanced data analysis tools to understand customer behavior and customize services, ensuring enhanced competitiveness and market expansion.

The discussion about the implications of the exchange rate on stock market behavior has become one of the fundamental principles in financial economics. The exchange rate plays an important role in the economic activity of any country and is a factor influencing the financial situation in financial markets. The exchange rate is the linking tool between the local economy and the global economy. This study addressed the impact of exchange rates on the efficiency of the financial market in Iraq. The researcher used the descriptive method to describe the study variables and clarify the theoretical relationship between exchange rates, inflation, and the financial market index. A statistical method was also used to conduct standard modeling using the ARDL methodology which included an empirical study on the effect of the Iraqi dinar exchange rate on the efficiency of the general index of the Iraqi financial market. The study concluded that there is a strong positive relationship between the exchange rate of the Iraqi dinar and the efficiency of the stock market in Iraq, with a correlation coefficient of 0.72. There is a moderate inverse relationship between inflation and the performance of the stock market in Iraq, with a correlation coefficient of -0.64. The stock market is characterized by a rapid recovery ability, with an adjustment speed of 69.88%. Therefore, it is necessary to focus on exchange rate policy and maintain exchange rate stability by the Central Bank of Iraq, to benefit from it in attracting foreign investment, building sufficient reserves of a basket of currencies by the Central Bank of Iraq to face external shocks, and stimulating the productive sector to take advantage of the strengthening of the dinar.

Tracking gold prices is one of the most important topics in the field of financial management, especially since gold is considered one of the most significant investments in financial markets. Accordingly, many approaches have emerged—both traditional methods based on technical and fundamental analysis, and modern methods based on machine learning. In line with technological development, a set of algorithms has been developed through which gold prices can be predicted. These predictions can be further improved by integrating (hybridizing) multiple algorithms, which represents the objective of the present study. This research aims to combine two algorithms to improve the accuracy of gold price forecasting .The study is based on the following research problem: “Can hybrid algorithms improve the forecasting of gold prices?” To achieve the research objective, the study relied on a sample consisting of gold stock prices over the period from 1/1/2000 to 31/8/2025, in addition to generating forecasts for the same period and producing future forecasts up to 31/12/2025. The research used four statistical measures to examine forecasting accuracy: RMSE, MAE, MAPE, and R². The study reached a set of conclusions and recommendations, the most important of which is that “using hybrid algorithms improves the accuracy of gold price forecasting.”

Aim of the study is explored the linkage between the yield volatility for global green bonds and Arab insurance investments around key moments of large geopolitical friction. Moving away from a theory of portfolio diversification as always being the most efficient, the model will explicitly quantify when interdependencies break or when they are restored in times of stress.
Methodology, Design and Approach of the study : In order to avoid the constraints of infrequent issuance of high frequency disclosures in the Arab insurance market, we used a representative portfolio of known ETFs and proxy indices. It guarantees exposure to fixed income, green bonds, equity, and cash markets. The dataset has daily data from January 2020 to December 2024, which includes both times from the dataset.
The study uses the Diebold-Yilmaz index that is included into a Time-Varying VAR (TVP-VAR) model for volatility spillover estimation. We model geopolitical instability by the Caldara-Iacoviello GPR index and its role as both external determinant and a threshold for the potential regime change. The predictive effectiveness of the analysis is then compared to estimates based on GARCH (1,1) and DCC-GARCH, as well as using LSTM networks.
Results of the study It explains (1)The effect of volatility is strong, asymmetric, and time-varying; green bonds behave as net remittances and insurance portfolios as net recipients. (2) The total flow index almost doubles in these scenarios of high geopolitical risk (31.4% → 58.9%), and it indicates that the benefits generated by diversification decay with a rise in systemic stress. (3) LSTM networks reduce RMSE out of sample by 32%, better than GARCH, with a statistically significant improvement (Diebold-Mariano test, p<0.01). (4) Scenario-based forecasts show that insurance portfolio volatility is disproportionately sensitive to negative geopolitical escalations.
Recommended The researchers that academics should be called upon to make efforts to develop systemic risk management tools.

This research aims to utilize data governance requirements as a methodological foundation to support internal auditors in designing highly effective audit procedures and building a procedural framework for implementing audit programs within a digital transformation environment. The focus is on highlighting the applications of the data governance concept to enhance the efficiency of internal audit procedure design in assessing compliance with these requirements, identifying priority audit areas, and developing appropriate audit evidence. This leads to the development of a practical methodology that helps internal auditors perform their tasks effectively in digital business environments.
Based on the applied aspect of the research, the researcher adopted an analytical and descriptive approach through a case study of an Iraqi bank. This case study analyzed the policies and technical procedures issued by the Central Bank and their impact on banking data governance. It also analyzed financial reports for the period (2020–2024) and published reports on bank governance to diagnose and analyze the governance requirements actually implemented. Based on the results from this analysis, a checklist was developed comprising seven key requirements to measure the level of implementation, define the scope of the audit, document supporting evidence for internal audit procedures, and demonstrate their relationship to digital transformation pathways in the banking sector.
The results of the implementation level assessment revealed a weakness in the separation of responsibilities and roles between the board of directors and executive management regarding data governance, leading to deficiencies in policies and control procedures. The results also indicated insufficient attention to developing data management and its policies, and inadequate compliance with legal requirements and data integrity assurance.

The research aims to evaluate the performance of the optimal investment portfolios that were selected and to build the portfolio based on the principle of diversification according to the additional return to beta and the risk-free interest rate, using entropy risk value models and modern tail measures of various types (Var, Cvar, Evar) at different confidence levels and using historical and parametric methods. To achieve the objectives and preferences of investors and portfolio managers, there is a real need for more accurate and efficient measures of risk for financial instruments. To achieve the objective of this research, we relied on companies listed on the Iraq Stock Exchange General Index. For the separate years of the portfolios (2022) and (2023), we used the monthly closing prices of the shares. The results show the effectiveness and superiority of entropy risk measures (Evar) and the success of the measure in dealing with and hedging against random fluctuations and extreme risks, as the portfolio for the year (2023) provided higher protection for investors than traditional measures. It is a measure that provides strong statistical evidence that systematic and unsystematic risks have been managed very efficiently. This makes it the best choice for investors, achieving returns while ensuring the highest possible degree of conservatism and security.

This research aims to study the role of integrating IAS 36 and IVS 300 in assessing and reporting the impairment of non-current assets, and to demonstrate its impact on the quality of accounting information. This is achieved by applying the requirements of both standards to the financial statements of Baghdad Soft Drinks Company. The study also examines the impact of this application on the quality of accounting information through financial analysis, which provides quantitative and objective measures of changes in the financial statements. This analysis relies on comparing financial indicators before and after applying the requirements of the two standards to the company's statements. The researchers concluded that the integration of IAS 36 and IVS 300 plays a clear role in enhancing the quality of accounting information by standardizing measurement methods, increasing comparability between financial periods, and revealing the true value of non-current assets in the company under study. The researchers presented a set of recommendations, most importantly: They recommended that Iraqi industrial companies, and in particular the company under study, adopt International Accounting Standard IAS 36 and International Valuation Standard IVS 300, given their fundamental role in assessing the fair value of non-current assets and reporting their impairment. These standards accurately reflect the true value of assets and benefit companies by reducing income tax and providing more reliable accounting information.

This research aims to test the impact of earnings management using the discretionary component of loan loss provisions on the efficiency of stock pricing in Jordanian banks during the period (2012–2021), based on the problem of the unclear effect of banking earnings management practices on the market pricing efficiency of stocks, with the hypothesis that there is a significant impact of these practices on pricing efficiency. The study relied on data from 12 banks and used two models to measure stock pricing efficiency: the price model and the return model. The results showed no significant impact of earnings management when measuring efficiency by stock price, whereas a high negative significant impact was observed when measuring it by stock returns, reflecting investors' response to earnings management practices when evaluating investment performance. There were also no significant differences based on the size or characteristics of the bank. The study recommends increasing transparency in the disclosure of provisions and enhancing oversight of earnings management practices. It also suggests applying the model in similar Arab financial markets, particularly the Iraqi market, to test the consistency of the relationship in closely related banking environments.