Introduction to Portfolio Management with Python

Introduction to Portfolio Management with Python

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1. Portfolio Analysis Basics

To start, we'll explore some fundamental financial concepts that will be essential for the rest of the course. These include investing, diversification, portfolio, return and risk. We'll also learn how to use Python to work with them.

What You Will Learn

Investing Basics

What is Portfolio?

Portfolio Returns

Measuring Risk of Portfolio

Annualized Return

Annualized Risk

2. Portfolio Optimization Basics

Now that we've covered the basics of portfolio analysis, it's time to explore methods for choosing optimal weights for our portfolio. Specifically, we'll discuss fundamental concepts in portfolio optimization, including Modern Portfolio Theory and its key component - the Efficient Frontier. Additionally, we'll learn how to balance high returns with low risk, and how to determine the weights for a portfolios that achieves the best possible return-risk trade-off or the lowest risk, all using Python.

Risk Adjusted Return

Overview of Modern Portfolio Theory

Markowitz Portfolios

Challenge: Computing GMV Portfolio

Challenge: Computing MSR Portfolio

3. Factor Investing

Finally, after covering the fundamentals of portfolio analysis and optimization, we’re ready to dive into predicting our portfolio's behavior and understanding the impact of various factors on it. Practically, we'll explore the basics of Factor Analysis, including different types of factors and several models built around them.

Introduction to Factor Analysis

The Capital Asset Pricing Model

The Fama-French Factor Model

The 5-factor Model

Course Content

Introduction to Portfolio Management with Python

Introduction to Portfolio Management with Python

1. Portfolio Analysis Basics

What You Will Learn Investing Basics What is Portfolio?Portfolio Returns Measuring Risk of Portfolio Annualized Return Annualized Risk

2. Portfolio Optimization Basics

Risk Adjusted Return Overview of Modern Portfolio Theory Markowitz Portfolios Challenge: Computing GMV Portfolio Challenge: Computing MSR Portfolio

3. Factor Investing

Introduction to Factor Analysis The Capital Asset Pricing Model The Fama-French Factor Model The 5-factor Model

Challenge: Computing GMV Portfolio

In the previous chapter, we've discovered, how to compute portfolios with minimal risk and with the best ratio of expected return and corresponding risk.

Now, you are going to compute them on your own.

First of all, in this chapter, you are going to compute GMV portfolio, which provides the lowest risk.

Task

Swipe to show code editor

In this task you need to:

Choose right shape for array of weights.
Find index of necessary weights in the right way.
Choose optimal weights and corresponding volatility.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

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Thanks for your feedback!

Section 2. Chapter 4

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Challenge: Computing GMV Portfolio

In the previous chapter, we've discovered, how to compute portfolios with minimal risk and with the best ratio of expected return and corresponding risk.

Now, you are going to compute them on your own.

First of all, in this chapter, you are going to compute GMV portfolio, which provides the lowest risk.

Task

Swipe to show code editor

In this task you need to:

Choose right shape for array of weights.
Find index of necessary weights in the right way.
Choose optimal weights and corresponding volatility.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 4

Switch to desktop for real-world practiceContinue from where you are using one of the options below

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