مطالب

Predicting stock price fluctuations has always been one of the most important financial challenges due to the complexities of financial data and nonlinear market behavior. This research aimed to analyze and compare the performance of machine learning algorithms in predicting the closing price jump of Iran Khodro Company shares. Two different methods of managing unbalanced data, NearMiss and SMOTE, were used to overcome the challenge of unbalanced data. The results showed that the NearMiss method outperformed SMOTE by balancing precision and recall in machine learning models. The CatBoost model was recognized as the best machine learning model in this study due to its stable performance in NearMiss and SMOTE methods. The CatBoost model showed a perfect balance between evaluation indicators in the NearMiss method, with an accuracy of 91.46% and an F1 score of 91.29%. This model also had high precision (93.18%) and acceptable recall (89.52%), which showed the ability to detect jumps and avoid wrong predictions correctly. On the other hand, in the SMOTE method, the Random Forest model was superior, with an accuracy of 85.08%. These results show that a combination of unbalanced data management methods and advanced machine learning algorithms can significantly improve the accuracy of price volatility prediction. The results of this research can help investors and financial analysts make better decisions in risk management and optimizing investment strategies.

This study investigates the multifaceted challenges of implementing digital transformation within Iranian oil and gas companies, focusing on organizational barriers and managerial solutions. Despite the global momentum toward digitalization, Iran’s oil and gas sector faces unique obstacles, including resistance to change, skill gaps, legacy infrastructure, and insufficient alignment between technology providers and large enterprises. Utilizing a mixed-methods approach, we conducted a survey of 210 managers and IT professionals across upstream and downstream organizations, complemented by in-depth interviews with key stakeholders. Exploratory factor analysis (EFA) and structural equation modeling (SEM) were employed to identify and validate critical barriers and their interrelations. Findings reveal that organizational inertia, lack of digital competencies, and inadequate investment in digital infrastructure are the most significant impediments, while leadership commitment and targeted training programs emerge as effective managerial remedies. The study contributes actionable insights for policymakers and executives by outlining a roadmap for overcoming digital transformation hurdles and achieving sustainable competitive advantage. The results underscore the necessity of a holistic strategy integrating technological, human, and process dimensions to facilitate successful digital transformation in Iran’s oil and gas industry.

The paper is an attempt to analyse Afghanistan's shifting security and economic conditions under Taliban rule using the Regional Security Complex Theory (RSCT). Since the Taliban regained power in 2021, they have faced critical challenges in establishing stable governance, resulting in a severe humanitarian crisis compounded by economic collapse and political isolation. External aid reduction and sanctions have limited Afghanistan’s access to the global financial system, leading to dramatic socio-economic setbacks. Regional actors, including India, Pakistan, China and Iran, interact cautiously with the Taliban administration, aiming to prevent cross-border instability and insurgent threats, while hesitating to grant formal recognition. For South Asia, Afghanistan’s internal upheaval escalates security tensions, particularly between India and Pakistan, and poses broader risks regarding extremism and economic destabilization. This study suggests that collaborative, conditional engagement by regional stakeholders facilitated through SAARC and SCO platforms may provide a viable path toward stability if the Taliban adhere to basic humanitarian and security norms. Such regional engagement is essential for addressing Afghanistan's humanitarian needs and reducing threats to regional security.