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The Hong Kong University of Science and Technology

Python and Statistics for Financial Analysis

The Hong Kong University of Science and Technology via Coursera


Course Overview:

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.


  • 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


4.4 rating, based on 505 Class Central reviews

4.4 rating at Coursera based on 3885 ratings

Start your review of Python and Statistics for Financial Analysis

  • The Python and Statistics for Financial Analysis course offered by The Hong Kong University of Science and Technology via Coursera is an outstanding learning experience. The content was well-structured, and the instructors explained complex concepts in a clear and concise manner. It greatly enhanced my understanding of financial analysis using Python and statistical techniques. Highly recommended.
  • Profile image for Abdelaziz Elhelaly
    Abdelaziz Elhelaly
    I recently completed a course on Python and Statistics for Financial Analysis, and I must say that it was a valuable experience. The course delved into the intersection of Python programming and statistical concepts, particularly focusing on their a…
  • Ronny De Winter completed this course, spending 2 hours a week on it and found the course difficulty to be medium.

    This is a compact course on statistical analysis using python on downloaded historical stock prices. You learn how to calculate moving averages (MA), buy signals based on MA, strategy profits, stock return frequency distributions, Value at Risk (VaR…
  • Anonymous

    Anonymous completed this course.

    Executive summary: Recommend, but i personally did not like it and could spend my time better on harder and more useful courses. Complete review: The course is well arranged in terms of what contents they show in each module and it is quite practic…
  • Anonymous
    I recently completed the "Python and Statistics for Financial Analysis" course offered by The Hong Kong University of Science and Technology via Coursera, and I cannot recommend it enough. This course provided a comprehensive and engaging introducti…
  • Anonymous
    This course is very much useful. I enjoyed the course and learned a lot from it. The content is well organised and focused on practical situations. The course is well arranged in terms of what contents they show in each module and it is quite practi…
  • Profile image for Ericlim Pallepogu
    Ericlim Pallepogu
    I recently had the privilege of taking a course, and I wanted to take a moment to express my gratitude and share my thoughts on this incredible learning journey. From the very first class, it was evident that the instructor possesses a deep passion…
  • Profile image for Arnab Sarkar
    Arnab Sarkar
    I recently completed the "Python and Statistics for Financial Analysis" course on Coursera, and I must say that I found it to be an excellent resource for anyone interested in using Python for financial analysis. The course was well-structured and e…
  • Profile image for Xiaoxia
    I have completed this course, spending 1 hour daily on it and found the course really helpful. Thanks to Professor WAN and all the coursera team who participated in providing this course. I found this course very concise and practical, combining thr…
  • Anonymous
    The course on linear regression was a well-designed and interesting learning experience. Python and statistical concepts were effectively integrated to enhance understanding. The hands-on approach, using Python libraries like scikit-learn and stats models, allowed for the practical implementation of regression models. The course covered essential topics such as model fitting, interpretation of coefficients, and model evaluation using metrics like R-squared and p-values. The instructor's clear explanations and real-world examples helped solidify the concepts. Overall, the course provided a comprehensive foundation in linear regression using Python and statistics, equipping learners with valuable skills for data analysis and modeling.
  • Anonymous
    Taking the Python and Statistics for Financial Analysis course was a game-changer for me. The course material was well-organized and presented in a manner that was easy to follow. The step-by-step approach allowed me to grasp the concepts and apply them in practical scenarios. The instructors were knowledgeable and responsive, providing guidance whenever needed. I particularly appreciated the emphasis on real-world applications and the opportunity to work on actual financial datasets. This course has empowered me with the skills and confidence to excel in financial analysis using Python and statistical techniques. I highly recommend it to anyone in the finance field.
  • Profile image for Vitaly Kogtev
    Vitaly Kogtev
    It is the interesting course, because:
    explains many important terms about statistics and testing models
    describes step-by-step testing model sequence
    gives you all necessary Python examples
    finance markets - is very interesting subject area to have any practice

    Thank you for this course,
    Vitaly Kogtev.
  • Profile image for Richard Johnson Taiwo
    Richard Johnson Taiwo
    It enables me to understand the dealings in stocks. It thought me how to use a statistical model to speculate the stock market; hence, I could be a bear or a bull. It also enables me to learn new terms that could be used to test trading strategies such as maximum drawdown. The only pitfall is the Jupyter Book complexity; it should be made easy and simple for the codes to be run by learners. for instance, the moderator should direct learners on how to upload a file from a location, etc. This will make the learners follow through and be motivated as well.
  • Anonymous
    Python and Statistics for Financial Analysis is a comprehensive and well-structured guide that empowers individuals to leverage Python and statistical techniques for financial analysis. Whether you're a finance professional looking to enhance your analytical skills or a data scientist aiming to specialize in finance, this book is an invaluable resource that deserves a place on your bookshelf. The clear explanations, practical examples, and real-world case studies make it a five-star choice for anyone interested in financial analysis using Python.
  • Dharmik Vaghasiya
    this is amazing and very informative course for finance professinoal who can not devote their time for full time trading, they can do the use of the python and make strtegy and can trade if has not time to do the trading. this course help me to connect the field of finance and it. which can help me further to make more depth analysis of the data and can make quite accurate decisions in the upcoming position of the finance field. this can help me reachout my CV to heavy and this will help me to further in our next designated job or institution for MBA.
  • Anonymous
    I have a Bachelor's degree in Statistics and a Master's degree in Economics, with certifications in Finance and Accounting, Financial Marketing, and Corporate Finance. I enrolled in this course to advance my career and adapt to my current needs. This course combines both Python coding and statistical concepts and applies them to the analysis of financial data such as stock data. In my opinion, the course I took provided me with the rudimentary skills needed to make data-driven financial decisions in Python.

  • Anonymous
    have a great lot of experience, which is something I didn't think I needed until it was too late to obtain, but I'm glad I have it now because I can put it to good use. I didn't think I needed it until it was too late to get it. As a consequence of this, not only do I have a more in-depth understanding of Python, but also of stocks and a wide range of other topics. I am at a loss for words to adequately express how much I value the assistance that you have provided, and I cannot thank you enough for it.
  • Anonymous
    For me I am a beginner with basic python and statistical analyses skills for finance. But the teaching was very insightful provided with simple python code, which was easy to understand and learn by doing my self. . However the course s challenging to understand given the complexity of the topic for someone who considers himself beginner at statistics. I really recommend that there is more homework to do with different kind of data set to apply these skills and tested by peers.
  • Berbelek 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 notebo…
  • Profile image for Chengkai Zhang
    Chengkai Zhang
    I personally feel that the course content is very full, but the problem is that there is no padding to quickly enter the explanation, should be more hints about the pre-course, can also explain more about how to use the functions in the package, no explanation directly to use.

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