تحسين أداء المحافظ المالية باستخدام طريقة التباين المتوسط

Résumé: With the continuous advancements in the fields of Big Data, Artificial Intelligence, Blockchain, and Deep Learning, the financial industry has witnessed significant progress, where these technologies have played a pivotal role in enhancing digital finance. These developments contribute to processing the massive amount of financial data while addressing the complexity arising from the inherent laws and random fluctuations in financial models. This has complicated financial characteristics and increased the difficulty of effectively handling financial data, emphasizing the growing need to adapt to resolutions and studies based on data processing technologies. In the context of financial data, such as high-frequency intraday trading data, stock prices, and trading volumes, the Python programming language has proven to offer numerous features that cater to the needs of practitioners in the financial sector, particularly in the field of market finance. Python is characterized by its high computational speed, open-source nature, and excellent data visualization capabilities. This study focuses on analyzing financial data using the Python platform, selecting six stocks representing different industries from the Saudi stock market. These stocks include Saudi Basic Industries Corporation (SABIC), Saudi Arabian Fertilizer Company (SAFCO), Marafiq (The Power and Water Utility Company for Jubail and Yanbu), Saudi Aramco, Luberef (Saudi Aramco Base Oil Company), and Saudi Telecom Company (STC). The study aims to obtain the optimal portfolio using two approaches: the first based on the portfolio with the highest Sharpe Ratio and the second focused on the portfolio with the lowest experimental variance. Python implements Monte Carlo simulations to optimize both approaches. The analyses involve comparing expected returns, standard deviations, and Sharpe Ratios and evaluating the effective results by defining the efficient frontier of optimal portfolios. The empirical analysis clearly highlights the strategic importance of Markowitz's Portfolio Theory in enhancing financial risk management in this research.

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