The Introduction to Portfolio Construction and Analysis with Python course offers a comprehensive understanding of the transformation of investment management through computational methods. This course provides a solid foundation in investment science while emphasizing practical implementation using the Python programming language.
This course, offered by EDHEC Business School, is the first in a four-course specialization in Data Science and Machine Learning in Asset Management but can be taken independently. Throughout the course, you will delve into investment science fundamentals, practical techniques in investment management, and portfolio construction, all while implementing concepts in Python. By the end of this course, you will have both a foundational understanding of modern computational methods in investment management and practical mastery in their implementation.
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The course modules cover a range of topics including analyzing returns, portfolio optimization, diversification, and asset-liability management, providing a comprehensive understanding of modern computational methods in investment management.
The "Analysing returns" module provides a foundational understanding of investment science, covering risk and reward fundamentals, measures of risk and reward, and deviations from normality. Through hands-on lab sessions, you will gain practical experience in implementing these concepts using Python.
The "An Introduction to Portfolio Optimization" module delves into the efficient frontier, Markowitz optimization, and the Capital Market Line. You will learn about the robustness of portfolio optimization methods and gain practical experience in applying these concepts through lab sessions.
The "Beyond Diversification" module explores the limits of diversification, CPPI strategies, Monte Carlo simulations, and portfolio insurance strategies. Through interactive lab sessions, you will analyze and design CPPI strategies, gaining practical insights into portfolio insurance strategies.
The "Introduction to Asset-Liability Management" module covers asset-liability management, liability-driven investing, policy portfolio selection, and dynamic liability-driven investing strategies. You will engage in lab sessions to understand and apply these concepts, including liability-friendly equity portfolios and dynamic risk budgeting.
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