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Journal of the Association of Arab Universities for Research in Higher Education (مجلة اتحاد الجامعات العربية (للبحوث في التعليم العالي

Journal of the Association of Arab Universities for Research in Higher Education (مجلة اتحاد الجامعات العربية (للبحوث في التعليم العالي

Abstract

One of the problems considered in financial mathematics is finding portfolios of given financial assets that minimize risk for targeted returns. The set of such portfolios is called the envelope of the assets. Traditionally, this problem is solved as a calculus minimization problem involving partial derivatives and Lagrange multipliers. The mean-variance framework is the preferred method for picking investments for many retail and institutional investors. Meanwhile, big data and the real-time economy have created new asset allocation challenges and opportunities. These changes have been thoroughly recorded, and portfolio management firms constantly incorporate the data into complex models. In this study, we tackle this issue by engineering practical tools for asset allocation and implementing them in the Python programming language. With its clear syntax, efficient development, and usability, Python programming provides an ideal framework for this research study. We turn to convex optimization to formulate specific portfolio optimization problems and incorporate different investment constraints. We give code samples from the associated procedures and

useful graphics that illustrate the input data and the produced results. We discover that most optimization issues can be written in convex form and hence quickly implemented and solved using Python modules to generate portfolios from real-world data. In this research work, we presented the results of three case studies that we have carried out on Moroccan Assets and multinational companies. We used and analyzed data from Yahoo Finance and Investing.com for the period that covers ten years, between 2012 and 2022. For our third case, we have used the Pandas-Datareader library in Python, and we have computed all the parameters for portfolio optimization, and we discussed the outcome profitability

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