About this Course

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Course Overview: https://youtu.be/JgFV5qzAYno
Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry.  The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.

By the end of the course, you can achieve the following using python:

- Import, pre-process, save and visualize financial data into pandas Dataframe

- Manipulate the existing financial data by generating new variables using multiple columns

- Recall and apply the important statistical concepts (random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. ) into financial contexts

- Build a trading model using multiple linear regression model 

- Evaluate the performance of the trading model using different investment indicators

Jupyter Notebook environment is configured in the course platform for practicing python coding without installing any client applications.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Intermediate Level

You will get the most out of the course if you have basic knowledge in probability.

Approx. 12 hours to complete

English

Skills you will gain

Statistical Analysis
Financial Analysis
Financial Data Analysis
Python Programming
Data Visualization (DataViz)

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Intermediate Level

You will get the most out of the course if you have basic knowledge in probability.

Approx. 12 hours to complete

English

Instructor

Instructor rating

4.33/5 (925 Ratings)

Xuhu Wan

Associate Professor

Department of Information Systems, Business Statistics and Operations Management

175,058 Learners

1 Course

Syllabus - What you will learn from this course

Content Rating96%(10,247 ratings)

Week1

Week 1

3 hours to complete

Visualizing and Munging Stock Data

Why do investment banks and consumer banks use Python to build quantitative models to predict returns and evaluate risks? What makes Python one of the most popular tools for financial analysis? You are going to learn basic python to import, manipulate and visualize stock data in this module. As Python is highly readable and simple enough, you can build one of the most popular trading models - Trend following strategy by the end of this module!

3 hours to complete

7 videos (Total 30 min), 3 readings, 1 quiz

Week2

Week 2

2 hours to complete

Random variables and distribution

In the previous module, we built a simple trading strategy base on Moving Average 10 and 50, which are "random variables" in statistics. In this module, we are going to explore basic concepts of random variables. By understanding the frequency and distribution of random variables, we extend further to the discussion of probability. In the later part of the module, we apply the probability concept in measuring the risk of investing a stock by looking at the distribution of log daily return using python. Learners are expected to have basic knowledge of probability before taking this module.

2 hours to complete

4 videos (Total 19 min)

Week3

Week 3

3 hours to complete

Sampling and Inference

In financial analysis, we always infer the real mean return of stocks, or equity funds, based on the historical data of a couple years. This situation is in line with a core part of statistics - Statistical Inference - which we also base on sample data to infer the population of a target variable.In this module, you are going to understand the basic concept of statistical inference such as population, samples and random sampling. In the second part of the module, we shall estimate the range of mean return of a stock using a concept called confidence interval, after we understand the distribution of sample mean.We will also testify the claim of investment return using another statistical concept - hypothesis testing.

3 hours to complete

5 videos (Total 32 min), 1 reading, 1 quiz

Week4

Week 4

4 hours to complete

Linear Regression Models for Financial Analysis

In this module, we will explore the most often used prediction method - linear regression. From learning the association of random variables to simple and multiple linear regression model, we finally come to the most interesting part of this course: we will build a model using multiple indices from the global markets and predict the price change of an ETF of S&P500. In addition to building a stock trading model, it is also great fun to test the performance of your own models, which I will also show you how to evaluate them!

4 hours to complete

6 videos (Total 46 min), 1 reading, 2 quizzes

Reviews

4.4

826 reviews

5 stars
57.75%
4 stars
30.22%
3 stars
8.36%
2 stars
2.04%
1 star
1.60%

TOP REVIEWS FROM PYTHON AND STATISTICS FOR FINANCIAL ANALYSIS

by MKOct 18, 2020

Tricky accent at time but great content and absolutely super Jupyter notebooks. The presentation looks cheap but this is one of the best finance/python starter courses on coursera.

by KXAug 1, 2020

The linear regression part is useful and the trading strategy is also very helpful and inspiring. But statistics knowledge is definitely required to gain a thorough understanding of the topics.

by LHMar 23, 2020

A very good introduction course to python programming and it has a perfect combination with statistics, which makes financial analysis more interesting and refresh my mind on it, thanks.

by GRMar 28, 2022

Very useful introductury course into both python and statistic analysis wich allows you to create a simple trading strategy. It serves as a great first step but there is a long way to go still.

View all reviews

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Python and Statistics for Financial Analysis