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Introduction to Portfolio Analysis in Python

AvansatNivel de competențe
Actualizat 04.2026
Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.
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PythonApplied Finance
4 h
15 videoclipuri
52 Exerciții
4,200 XP
20,166
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Descrierea cursului

Have you ever had wondered whether an investment fund is actually a good investment? Or compared two investment options and asked what the difference between the two is? What does the risk indicator of these funds even mean? Or do you frequently work with financial data in your daily job and you want to get an edge? In this course, you’re going to get familiar with the exciting world of investing, by learning about portfolios, risk and return, and how to critically analyze them. By working on actual historical stock data, you’ll learn how to calculate meaningful measures of risk, how to break-down performance, and how to calculate an optimal portfolio for the desired risk and return trade-off. After this course, you’ll be able to make data-driven decisions when it comes to investing and have a better understanding of investment portfolios.

Cerințe prealabile

Manipulating Time Series Data in PythonIntermediate Python for Finance
1

Introduction to Portfolio Analysis

In the first chapter, you’ll learn how a portfolio is build up out of individual assets and corresponding weights. The chapter also covers how to calculate the main characteristics of a portfolio: returns and risk.
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2

Risk and Return

Chapter 2 goes deeper into how to measure returns and risk accurately. The two most important measures of return, annualized returns, and risk-adjusted returns, are covered in the first part of the chapter. In the second part, you’ll learn how to look at risk from different perspectives. This part focuses on skewness and kurtosis of a distribution, as well as downside risk.
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3

Performance Attribution

In chapter 3, you’ll learn about investment factors and how they play a role in driving risk and return. You’ll learn about the Fama French factor model, and use that to break down portfolio returns into explainable, common factors. This chapter also covers how to use Pyfolio, a public portfolio analysis tool.
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4

Portfolio Optimization

In this last chapter, you learn how to create optimal portfolio weights, using Markowitz’ portfolio optimization framework. You’ll learn how to find the optimal weights for the desired level of risk or return. Lastly, you’ll learn alternative ways to calculate expected risk and return, using the most recent data only.
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Introduction to Portfolio Analysis in Python
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