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Introduction to Portfolio Analysis in Python

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Have you ever wondered if an investment funds was a good investment choice? Do you know any other investment options? What is the risk indicator of these funds? Are you a financial professional who wants to be an expert in your field? This course will take you into the exciting world of investing. This course will teach you about portfolios, risk and return, as well as how to analyze them. To calculate risk and breakdown performance, you will be able use historical stock data. This will help you create the best portfolio possible to achieve the right risk/return trade-off. You will be able to make better investment decisions by using data to guide you.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Python for Finance

Manipulating Time Series Data in Python

What You Will Learn

In the first chapter, you’ll learn how a portfolio is build up out of individual assets and corresponding weights

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

You’ll learn about the Fama French factor model, and use that to break down portfolio returns into explainable, common factors

You’ll learn how to find the optimal weights for the desired level of risk or return

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

Course Instructors

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Charlotte Werger

Director of Advanced Analytics at Nike

Dr. Charlotte Werger currently works at Nike as a Director of Advanced Analytics. Charlotte is a data scientist with a background in econometrics and finance. She loves applying Machine Learning to a...
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