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#### 100% online

Start instantly and learn at your own schedule.

Reset deadlines in accordance to your schedule.

#### Beginner Level

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

#### Approx. 10 hours to complete

Suggested: 4 weeks of study, 3-4 hours/week...

#### English

Subtitles: English

#### 100% online

Start instantly and learn at your own schedule.

Reset deadlines in accordance to your schedule.

#### Beginner Level

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

#### Approx. 10 hours to complete

Suggested: 4 weeks of study, 3-4 hours/week...

#### English

Subtitles: English

### Syllabus - What you will learn from this course

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!

...
7 videos (Total 30 min), 2 readings, 1 quiz
7 videos
1.0 Module Introduction3m
1.1 Packages for Data Analysis1m
1.2 Importing data2m
1.3 Basics of Dataframe5m
1.4 Generate new variables in Dataframe8m
Getting started with Jupyter Notebook10m
1 practice exercise
Quiz 130m
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.

...
4 videos (Total 19 min), 1 quiz
4 videos
2.1 Outcomes and Random Variables2m
2.2 Frequency and Distributions5m
2.3 Models of Distribution7m
1 practice exercise
Quiz 230m
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.

...
5 videos (Total 32 min), 1 quiz
5 videos
3.1 Population and Sample8m
3.2 Variation of Sample5m
3.3 Confidence Interval4m
3.4 Hypothesis Testing11m
1 practice exercise
Quiz 330m
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!

...
6 videos (Total 46 min), 1 reading, 2 quizzes
6 videos
4.1 Association of random variables5m
4.2 Simple linear regression model13m
4.3 Diagnostic of linear regression model4m
4.4 Multiple linear regression model14m
4.5 Evaluate the strategy5m
Please rate this course!2m
2 practice exercises
Quiz 430m
Post-course survey5m
4.6
40 Reviews

## 50%

started a new career after completing these courses

## 33%

got a tangible career benefit from this course

### Top reviews from Python and Statistics for Financial Analysis

By DAJan 21st 2019

Perfect for the beginning to intermediate python programmer who wants to utilize finance data to make decisions (i.e. trading).

By TGJun 9th 2019

An interactive and succinct course to get an insight into the statistical analysis used in the finance domain on daily basis.

## Instructor

### Xuhu Wan

Associate Professor
Department of Information Systems, Business Statistics and Operations Management

## About The Hong Kong University of Science and Technology

HKUST - A dynamic, international research university, in relentless pursuit of excellence, leading the advance of science and technology, and educating the new generation of front-runners for Asia and the world....

## Frequently Asked Questions

• Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.