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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 567 Class Central reviews

4.4 rating at Coursera based on 4183 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
i was just exploring some courses related to data science on coursera and i finded this course for free .I started to follow the course content and i have tell that the overall course is awesome ,professor have explained very well all the concept a…
• 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
This course is excellent for beginner programmers. The lectures are on point, offering clear and concise explanations that are easy to follow. The instructor's insights are both relatable and insightful, making complex topics accessible and engaging. Each lesson builds on the previous one, ensuring a solid foundation is laid before moving on to more advanced concepts. The practical examples and hands-on exercises reinforce learning, helping students apply what they've learned in real-world scenarios. Overall, this course provides a comprehensive introduction to programming, making it a valuable resource for anyone looking to start their coding journey.
• 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…
• 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…
• 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.
• Anonymous
"I recently completed the 'Python and Statistics for Financial Analysis' course on Coursera offered by The Hong Kong University of Science and Technology, and I must say it exceeded my expectations. The course provides a comprehensive introduction to using Python for financial analysis, coupled with statistical techniques that are crucial in the field.

Thank You, Coursera for giving me this opportunity
• Anonymous
It's good, although there is a big jump in the difficulty from week 3 onwards. Additionally, some of the links in week 4 are outdated, thus making it a little difficult to navigate. Finally, it would have been a lot more helpful if the answers could be provided after successful passing of the quizzes, as there were some questions where I felt the answers were really difficult to understand.
• Anonymous
It's a very good course that provides a quick introduction to the field of finance with Python. The explanation of mathematics and statistics is concise and understandable. It's advisable to have some basic knowledge of Python to be able to follow it without much trouble. Some methods are outdated (which is noted in the classes), but they are still used in the Jupyter labs.
• 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
"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…
• I found this course on Coursera while searching for a good course on Python programming and data analytics. It was a very good course that applied the concepts of statistics I had learned in the past to Python with financial knowledge. I learned a lot and was able to put it into practice immediately.
• Anonymous
The content is ok for someone who has good statistical knowledge. It would have been appreciated if there was more financial explanation.
Unfortunately, it was so hard to follow without reading the subtitles, and all the links in the quizzes were broken.

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