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Online Course

Python and Statistics for Financial Analysis

All-Time Top 100

The Hong Kong University of Science and Technology via Coursera

513
  • Provider Coursera
  • Cost Free Online Course (Audit)
  • Session In progress
  • Language English
  • Certificate Paid Certificate Available
  • Effort 3-4 hours a week
  • Duration 4 weeks long
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Overview

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.

Syllabus

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!

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.

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.

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!

Taught by

Xuhu Wan

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Reviews for Coursera's Python and Statistics for Financial Analysis Based on 55 reviews

  • 5 stars 62%
  • 4 stars 20%
  • 3 stars 15%
  • 2 stars 4%
  • 1 star 0%

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  • 1
Anonymous
9 months ago
Anonymous is taking this course right now.
this course is very practical! it explains how statistic concepts can be applied into financial-related examples using python.

some argue the course do not cover enough of python nor financial, nor statistics concepts. hey man !!! this course is not a baby intro course!!! it assumes you are either strong in one/some of the aspects (either you are strong in computer, or stats, or finance), and you want to see how the other aspects can be combined to work out something valuable. do you need to learn everything about a car before driving it? you just learn what you need to get the ca…
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Anonymous
7 months ago
Anonymous completed this course.
I feel like I got the overall gist of modelling. However, there were many details in the lectures that were left wanting. For example, the Sharpe Ratio; I still don't understand why this a useful measure in our model - why is this better than using variance and standard deviation between the test and the train data? Also, I found the lectures hard to watch at times. I felt like the professor was very knowledgeable, but he sounded like he was reading pedantically from a teleprompter the whole time. It would be helpful if he paused to ask questions or repeat some important concepts for emph…
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Ariel G
10 months ago
Ariel completed this course, spending 6 hours a week on it and found the course difficulty to be medium.
Its a complete course which gives the fundamentals for programming financial applications into Python. I would suggest to improve in trying to use the code presented in the Jupyter applications, not only for the variable names but for the code consistency. Also, I would suggest that the data files been published for the students which work off-line and try to keep peace; I use Sublime + Python interpreter on my laptop and no Jupyter, for example. I recommend the course for people which takes a very first idea of Phyton, anyways it's no difficult to keep the rhythm.
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Anonymous
4 months ago
Anonymous completed this course.
This course gives great insights into the use of statistics and its implementation in python for financial analysis. The curriculum is well structured which gradually increases in difficulty every week. It gives a healthy introduction to various techniques which can be applied to Finance & will definitely motivate you enough to delve deeper into concepts to explore more. A perfect blend of Statistics, Finance & Computing!
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Anonymous
7 months ago
Anonymous completed this course.
I would expect the course to provide more in-depth and more practical financial models. For me it's more like a revision on statistics and very simple Python coding.

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Anonymous
7 months ago
Anonymous is taking this course right now.
Good start for a beginner, but I would prefer a bit more intermediate stuff. Apart, from that the course is well organised & Systematic making it an interesting one.
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Kurp K
5 months ago
Kurp completed this course, spending 2 hours a week on it and found the course difficulty to be easy.
I have mixed feelings about the course. It shows very practical aspects of building trading stategy in Python, which is still quite unique topic here. It also offers a lot of practice and ready to use and modify solutions delivered as Jupyter notebooks. This course definitely expect you to know a bit about statistics and also to know Python programming, on basic level at least. On the other hand I think the course does not cover the topic deep enough, we've got only some simple linear regression model based on some not-so-creative feature engineering. It does not cover such aspects as HFT vs swing trading strategies, using slipage and transaction costs to evaluate strategy, managing invested capital and many more. I've expected a bit more, to be honest. The course is well done as ready-to-use implementation of very simple concept - but there's nothing more to expect here.
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Sabarinathan C
9 months ago
Sabarinathan completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
This gives a application of all the three famous sectors viz, finance, python and statistics. Actually speaking i am searching for these kind of courses and did not get one. Atlast got this one for my solace. This suited my need. This course cannot be easily designed as other courses . This really needs one time . Thanks to the person who devised the course and also to the instructor Mr. Xuhu Wan for his meticulous time to provide the information in a precise way.

Infact the while explaining errors actually in a very short time he explained the unexplained, explained and total error in a concise and apt way. really its a wonderful course.

Thanks

Sabarinathan alias Cheryn
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Anonymous
4 months ago
Anonymous completed this course.
The course is okay. There is a lot of information and sometimes the lecture material feels very dry lacking detailed explanations of certain concepts, particularly in week 4. Also, there were incorrect answers in some of the weekly quizzes.

For example they give you a link where it displays the table of information you need to answer the question but lets say the value you see from that table is 0.782. The actual options for answers on the quiz doesn't have 0.782. Instead they might have an option that says 0.740. If you pick the closest option to 0.782 then you should get the mark. I don't like this as it doesn't test the students knowledge if the correct option isn't available.
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Anonymous
9 months ago
Anonymous completed this course.
The course covers basic Python to build and evaluate financial models. The course is easy to learn because the length of every video is on average 10 minutes. Although I did not put a lot of time practicing the exercises, I managed to pass the quiz at the end of every Week. Coursera will automatically set deadlines for you, so you should be motivated to finish the course on time. The professor's pace is a bit fast, perhaps this is an online course. This shouldn't be a problem because you can always replay the video again until you understand the concepts.
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Anonymous
7 months ago
Anonymous completed this course.
Course covers basic Python to build and evaluate financial models. The course help my so much to understand finance. Although I did not put a lot of time practicing the exercises, I managed to pass every questions i one week which is fast maybe but I could not wait finish,I was very excaited . Coursera will automatically set deadlines for you, so you should be motivated to finish the course on time. This shouldn't be a problem because you can always replay the video again until you understand the concepts of learning.Great course.
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Anonymous
3 months ago
Anonymous completed this course.
Best course to quickly know financial modeling application, required underlying statistics and Python. Prof Wan has assembled the perfect trifecta in this introductory course.

Some have suggested in their comments that it doesn't cover certain things in detail. However, that is not the intent of this course. It is the perfectly assembled course to introduce the required concepts and provide just enough clarification to understand the trifecta in data science. Details can be found in other textbooks or Google search, etc.
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Anonymous
9 months ago
Anonymous completed this course.
The lecture videos were very helpful to my studies. The teacher was able to convey the course materials in a clear and concise way. However, the course materials didn't fit my expectations. I wanted to learn how to code in Python. Instead, this course focuses more on the business side. I only learned a few useful terms in Python. The course didn't really provide a platform for us student to learn how to code since the basics were not fully covered. Despite that, the materials were very useful and insightful.
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Anonymous
3 months ago
Anonymous completed this course.
One of the finest course in this field. I have already done 2 courses on Python and Statistics for Finance and this was the third one. Amongst the three this is easily the easiest to understand and best course for sure. I will look forward to course from this professor or university in the future. Week 3 and Week 4 from the course are like a gold mine for any learner. And the jupyter notebook exercises give just the required practice immediately after the concept is learned.
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Anonymous
10 months ago
Anonymous completed this course.
It is a very good course to learn the basics in python to analyze financial stock market data. However, if you don't have prior knowledge to statistics and financial data (variance, histograms, regressions, value at risk, hypothesis testing, ...), the course might be to fast to understand the background, because you cannot explain all these things properly in 2-3 hours of video. But I guess most people who want to analyze stock data in python have this knowledge.
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Anonymous
2 weeks ago
Anonymous completed this course.
As a person who knows nothing about Python, it is a bit hard for me to understand the logic of the coding and as a person who know very little about economist, it is confusing for me when terms pop up. But I have to say that, the course is very logical and detailed, I will come back to this course again, after I have a better understanding about both subjects.
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Anonymous
10 months ago
Anonymous completed this course.
There are some mistakes in both Juypter Notebook and Quizs and I think this course is not so practicle. I would recommend this course to add more practice part in coding for students. Cuz so far, I think I just got some proper nouns for python and financial analyse and have no idea of making analysis of stock prices indipendently.
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Anonymous
2 weeks ago
Anonymous completed this course.
Xuhu made a commendable effort in the early part of the class in teaching the basics of this course. Over the last 2 weeks of content however, significant external reading is required for students to do independently from the course content (not a bad thing) but know that extra effort is required to pass the later stages.
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Anonymous
9 months ago
Anonymous completed this course.
Practical and very relevant for finance. Great tools that can be applied for some basic trading techniques. Can always expand more by introducing rolling techniques and more out of sample testing. Overall, one of the best courses on python for finance out there. Many thanks for putting it together.
Was this review helpful to you? Yes
Anonymous
4 months ago
Anonymous completed this course.
The course content and workbook exercises are good. The instructor is very knowledgeable. However the instructor's accent made it a bit difficult to understand, as I found myself scrolling down to look for script below the video and up again to follow the video and repeat many times.
Was this review helpful to you? Yes
  • 1

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