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# Python and Statistics for Financial Analysis

### Overview

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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.

### 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!

Xuhu Wan

## Reviews

4.4 rating, based on 552 Class Central reviews

4.4 rating at Coursera based on 4058 ratings

Start your review of Python and Statistics for Financial Analysis

• Anonymous
"Python and Statistics for Financial Analysis" is an exceptional course that truly stands out in the realm of finance and data analysis education. As someone who has been navigating the intricate world of finance, I can confidently say that this cou…
• 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…
• 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
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…
• 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.
• 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…
• Anonymous
"I recently completed a comprehensive finance course that covered a wide range of essential topics, crucial for anyone interested in financial analysis and trading strategies. The course adeptly handled key concepts like linear regression, including…
• Anonymous
The lab experience appears to be less hands-on, with students primarily tasked with executing pre-existing practical work rather than actively engaging in the creation or execution of experiments. This structure may limit students' opportunities to…
• Anonymous
The Python and Statistics course on Coursera is an exceptional blend of programming prowess and statistical concepts. This course offers a comprehensive understanding of Python's application in statistical analysis, making it an invaluable resource…
• 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…
• M. Meghdari
I absolutely loved this online course! It exceeded my expectations in every way. The content was incredibly well-structured and easy to follow, and the instructor's expertise really shone through. The interactive elements and quizzes kept me engaged throughout, and the peer discussion forums were a great way to connect with fellow learners. The course material was not only informative but also practical, and I found myself applying what I learned immediately in my work. The support from the course staff was exceptional, with prompt responses to any questions or concerns. I would highly recommend this course to anyone looking to expand their knowledge in this subject. Thank you for a fantastic learning experience!
• Anonymous
The course has its main focus on the statistic side of the stock market analysis, not as I had hoped on Python. It is more a tool to get the empirical data and i missed more details about how to plotting, why using numpy and other librarys, how to use these functions and so on.
It is more a "I have a statistical problem and how can I solve it and because I don't want to calculate those formulas myself I use python" instead of "What possibilities do I have with python to solve statistical problems and here is a generic example".
The speaker is sometimes hard to understand for me as a non-native english speaker
• Anonymous
It’s such an awesome experienceto take this course. The quality of the contents is superb.

Incorporating all I have learned into the diverse circumstances I am facing at the moment will assist me in passing the huge hurdle.

This course has equipped me with lots of tangible and professional tools to leverage on and use in achieving excellent desired results.

Now I feel extraordinary energy to deal with some issues am going through, as a result of the so much value I gained from the course.
• 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…
• Anonymous
I really like how the instructor putting together the real world examples and how we can solve the problems and also precautions with Python. It is better for any student to brush up of the statistics & probability concept / knowledge before taking the course as you would enjoy and understand it more. Just one suggestion that it would be better to have the slide deck or lecture note for download. Thanks a mill for making this good course available for us.
recently completed a statistics and Python course in finance, and I must say it was an incredible learning experience. This course provided a comprehensive overview of how statistical techniques can be applied to financial data analysis, giving me v…
• Anonymous
I work as a Business Analyst and have have always been interesting the analysis using Python. My area of interest is Finance and this course just provided me with all the tools and confidence I need to make a start.

Cannot thank Coursera enough for making this available.

I would however recommend that if you want to really get the most out of this it. Polish up on your statistical concepts and take a python course where you use Anaconda
• 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…
• 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…
• Anonymous
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.

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