Retour à Python and Statistics for Financial Analysis

4.5

332 notes

•

67 avis

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....

Aug 04, 2019

Great course! Very didatic explanations about financial and statistical concepts also with some interesting practical Python for Finance! Looking forward for new courses from same Univ. and prof.!

Jul 05, 2019

The videos in this course are exceptional and very interesting. The Jupyter notebooks provide a good template for applying the methods and techniques.

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par Cheuk W K

•Mar 01, 2019

It is a good course overall, combining the basics of statistics, Python and finance. I've learned a lot from it. I think the students can benefit more if additional suggested reading materials can be provided, so that if one lacks a strong background in a particular discipline, one can find out more outside the course. Also will be helpful if slides can be downloaded.

par Helena K

•Feb 08, 2019

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 car moving man!!

This course is not spoon-feeding like your elementary school teachers!!! Professor taught you something, and you are expected to study further on your own. i am not good at stat, but I know programming reasonably well, I know where i should pick up some statistics to understand the materials.

you will be able to find tons of courses that introduces programming language/statistics, but they never tell you how useful the programming language/statistics is in real life. But this course is so practical that I can pick up the knowledge and use immediately.

Highly appreciate professor xu's effort in creating this valuable course!

par Satish N

•Feb 28, 2019

I had only basic knowledge of python and very basic knowledge of statistic - most of which I had not put to use, since leaving school. This course was a helped me to get more confidence with using python in a practical way. In the process I also brushed up my statistical skills - there is no better way to understand statistics then to apply in real-life scenarios as explained in this course. And python packages makes learning fun, by taking off the difficult computation tasks. Overall I would recommend this course to anyone who has interest in learning how to apply statistics and python to analysing data.

par carlo

•Mar 23, 2019

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par sabarinathan r

•Feb 07, 2019

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 this a wonderful course.

Thanks

Sabarinathan alias Cheryn

par Ezekiel J T

•Feb 05, 2019

The lecture videos were very helpful to my studies. The teacher was able to explain the materials very clearly. However, I this course doesn't fit my expectations. The reason why is because I wanted to learn how to code in Python. This course emphasizes more on the business side and it doesn't provide an opportunity for us to actually learning the basics of coding in Python. I only learned a few useful terms in Python.

par Zeyu H

•Jan 20, 2019

【Now you know Prof. Xuhu Wan, please avoid his course in HKUST】

0. Course Equivalence😐

This course basically covers 50% content of MATH2411 Applied Statistics (I heard there is ISOM2500 that is similar to MATH2411?). Accidentally I took 2411 right before this winter when this course is out, so I found this course quite disappointing because I expect some practical manipulation of Python is covered while it doesn't. More is discussed in #3.

1. Teaching ☹

If you have the experience of recording a video presentation eight hours before the deadline, with scripts written three days before and you hadn't recited or even gone through it in these three days, you will find the professor the same unpassionate. You will find his tone flat enough and gestures unnatural enough as if he is not emphasizing on anything but focusing to recite his scripts. You will find him lag a lot at strange and unnatural spots as if his brain goes blank and he quickly reads the copy of scripts next to the camera.

I thought business people cares a lot about presentation, but I was wrong.

2. Subtitle 😡

There are tons of me steaks in the subtitles, not only tipos but also worlds of cellar pronunciation.

(There are tons of mistakes in the subtitle, not only typos but also words of similar pronunciation.)

I enable subtitle because I sometimes can‘t understand the professor's perfect Mainland accent, but it turns out the subtitle is on his side but not my side.

I thought business people are very strict about the material that comes along with their presentation, that they always carefully spellcheck every sentence. But I was wrong.

3. Content 😐

3.1 Overall:

Please rename this course "Python and applied statistics". The professor spends sooooo much time talking about the statistics concepts and spends soooo little time applying the knowledge to financial analysis. It is not about "Statistics for Financial Analysis". Replace the data he uses for demonstration with GPA of every student and it becomes "Statistics for Being HKUST President" or "Statistics for Anything". I feel I am taking an introduction course to statistics and financial analysis is just an excuse the teacher use to show us the content he teaches is somewhat useful.

3.2 Pace:

You MAY find the pace quite fast because:

The teacher throws many statistics concepts

The teacher cannot fully explain the concepts (or it is not a 4 week course) so he moves on before you ever (perhaps never will) digest the previous concepts

This is extremely annoying in week 4, e.g. Multiple Linear Regression is taught without introducing a single formula, merely Python codes and black boxes behind them. (Actually this is the way I originally expect the professor to do, but it is quite inconsistent with the style in week 1-3)

You MAY find the pace quite slow because:

After all this course introduces formulas and codes and let you to use them without knowing why.

So I would say this is a 4-day course if you can spare 1 hour each day. After all you are not asked "why" but only "how". If you haven't taken MATH2411 or ISOM, you can spend more time on week 2 & 3 to understand the underlying knowledge. Week 1 is simple and week 4 is needless to comprehend.

4. Jupyter Notebook (JN for short) 😡

4.1 Poor Exercise

Almost useless. Just a copy of the codes appeared in the video, with some variables assigned None instead of the correct expression. Your job is to change the lines of variable assignment (usually one or two lines), and the rest is done for you. Some notebooks are even 100% done for you, and all you need to do is look at it and appreciate. Even if you are fiddling with provided exercises, you don't know how to use JN, because...

4.2 Irresponsible adoption of JN

If you want to do some real exercise, you may want to append empty cells below the given content and type codes from scratch. But oh, this course does not teach you how to use JN! It just throw you a tutorial link of how to INSTALL JN ON YOUR COMPUTER{https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook}. What a shame!

Quickly gone through the linked tutorial, it assumes you have installed multiple instance of Python on your desktop, and know basics of pip, conda, docker, and virtual env, and teaches you how to install and configure JN in various dev. environments. But you just mentioned we can use Coursera's pre-installed JN out-of-the-box, why you want us to learn that huh? And to create cells, run cells, run several cells in order, run all, and other basic operations, is hidden in the last seconds of GIFs, not explicitly explained.

I guess the professor is TOO UNRESPONSIBLE to not only teach students how to use JN himself, but also SPEND AT LEAST SOME TIME to check if the external tutorial really "explains how to use Jupyter Notebooks". Please, not every one taking this course is CS student like me, SBM students they may not know how to use Python stuff.

5. Coursera Technical 😐

Quizzes do not provide correct answer. So it is not that helpful. But getting 80% is not that hard either. But given the assumption that you can't use JN (explained in #4.), you lose at least 10% in Quiz 3 and 20% in Quiz 4. Oh that hurts! (Since Notebook 4.4 is done for you, another 20% in Quiz 4 related to JN is okay.)

par Tobias T

•Jan 22, 2019

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.

par Shuhong L

•Feb 07, 2019

this is a wonderful course with well-prepared videos to illustrate and well-organised Notebook for practice. the final score you will get is only depended on four quizzes, but it is always useful for you to watch videos carefully and try very best to type codes on Notebook provided for you, which can also benefit your quizzes. you can some basic sentence structure of Python and grasp the practical tool to build a model to make financial inference. with light workload, you can get a lot.

par Adrian B W

•Feb 19, 2019

Great course by a great instructor.

par RS

•Feb 24, 2019

Hard subject to grasp for a novice, but material and professor was superb!

par SHIVAM B

•Feb 24, 2019

Great course that makes your basics very clear. to top it all the course is taught by an excellent tutor.

par Feiting X

•Feb 27, 2019

Nice Introduction!

par Wang H

•Mar 30, 2019

This is my first time to study on Coursera. This course is fairly useful to me. Thanks, Prof. Wan.

par ducvannguyen

•Apr 01, 2019

Thank you very much for this useful course. I hope to join many course from you

par Ruikun D

•Jan 29, 2019

very

useful

par Giancarlo G

•Jan 27, 2019

Overall, the course was good, but I felt that the course was a bit abrupt in its ending, as I would have wanted to learn about nonlinear regression models, making more trading strategies, and automatic the process using Python.

par Yaron K

•Jan 26, 2019

A short course that shows how to handle time series data, run a multiple linear regression on it, and evaluate the results. This is only an introductory course, and as such it is clear and concise and thus deserving of 5 stars. However it only touches the surface of Python, statistics or trading. As for trading - before risking Real Money - it is strongly advised to learn much more on the subject of stock markets.

par Egor S

•Jan 28, 2019

Good and very practical course! Looking forward to next parts considering more complex models.

par Santiago L C

•Jan 30, 2019

I enjoy very much

par Ren J

•Apr 11, 2019

Clear explanation of the statistics and python, well-prepared exercise in notebook and basic bags in python are recommended to use in data processing.

par Yau T H

•Jan 08, 2019

I great and easy-to-understand course to learn python for basic statistics!

par Donovan A

•Jan 21, 2019

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

par DING G

•Feb 13, 2019

friendly to beginners

par Gary C

•Mar 11, 2019

great instructions using real life data and examples. Useful for stock financial analysis based on the indicator.

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