Introduction to Computational Finance and Financial Econometrics

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9/10 stars
based on  8 reviews
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Cost FREE
Start Date TBA
Introduction to Computational Finance and Financial Econometrics

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Course Details

Cost

FREE

Upcoming Schedule

  • TBA

Course Provider

Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4724 reviews

Course Description

Learn mathematical and statistical tools and techniques used in quantitative and computational finance. Use the open source R statistical programming language to analyze financial data, estimate statistical models, and construct optimized portfolios. Analyze real world data and solve real world problems.
Reviews 9/10 stars
8 Reviews for Introduction to Computational Finance and Financial Econometrics

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Sai profile image
Sai profile image
7/10 starsCompleted
  • 14 reviews
  • 13 completed
6 years, 11 months ago
The course starts with simple returns and continuously compounded returns, present values, then autoregressive (AR) and moving average (MA) models, and finally covers portfolio theory and capital asset pricing model (CAPM). Basic probability theory and matrix algebra are also covered on the way but it seemed too lengthy to me (spending almost 2 weeks). There are plain quizzes, quizzes that require some R (or Excel) programming, midterm, and final. Even if you don't know much about R, you can still do the programming assignments in R because sample source files, which are almost giving away the solution, are provided. Some of the R techniques I learned from this course-- bootstrapping and hypothesis testing--seem useful for general data analysis projects as well. Prof. Zivot is (was?) also a practitioner of computational finance and I liked the occasional anecdotes he shared with us. As is often the case with UW courses, there will be... The course starts with simple returns and continuously compounded returns, present values, then autoregressive (AR) and moving average (MA) models, and finally covers portfolio theory and capital asset pricing model (CAPM). Basic probability theory and matrix algebra are also covered on the way but it seemed too lengthy to me (spending almost 2 weeks). There are plain quizzes, quizzes that require some R (or Excel) programming, midterm, and final. Even if you don't know much about R, you can still do the programming assignments in R because sample source files, which are almost giving away the solution, are provided. Some of the R techniques I learned from this course-- bootstrapping and hypothesis testing--seem useful for general data analysis projects as well. Prof. Zivot is (was?) also a practitioner of computational finance and I liked the occasional anecdotes he shared with us. As is often the case with UW courses, there will be no certificate; instead they invite you to enroll in UW's own online course, which you can safely ignore if you are not interested. If you decided to take this course, make sure to read "Viewing the Video Lectures" on the course page.
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10/10 starsCompleted
  • 4 reviews
  • 4 completed
4 years, 5 months ago
I started this course out of curiosity and it got me: Loved the math and statistics and the way it made me feel on top of the subject. I learned to use tools/methods I didn't dare to dream of before: matrix algebra, bootstrapping, portfolio theory. In the midterm exam I encountered a technical problem and it looked like I wouln't be able to complete the course with success. After emailing the Coursera helpdesk, the problem was solved very professionally and I was able to complete the course.
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Student profile image

Student

10/10 starsTaking Now
5 years, 1 month ago
Some times difficult to navigate between, Labs, Assignments,lecture Notes, slides.
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Erick Hernandez profile image
Erick Hernandez profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 5 months ago
This is an amazing course, I've had probability and statistics theory before, and I can say professor Zivot is extremely adept at clearly explaining complex concepts in simple english. I do not have a big interest in finance (my area of work is supply chain) but I found the concepts he explains to be widely applicable outside of the use case he focuses on (investment return models). Definitely recommended if you want a refresher/introduction to econometrics.
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Dan profile image
Dan profile image
10/10 starsCompleted
  • 9 reviews
  • 9 completed
5 years, 10 months ago
Most of the class is spent in a detailed review of basic statistics, with an eye to applying it to financial data series. I really needed that, plus we were taught how to do all computations in R, with useful examples. Great treatment of confidence and the bootstrap methods. Final weeks were about basics of portfolio theory (efficient frontier, etc.) again enabling us to do all computations. I also appreciated the teacher mentioning that the theory's value decreases when the market is unstable (as correlation increases) and showing how wildly the theoretic results can vary depending on when the data is collected. Overall I now feel confident with basic statistics (also beyond financial applications) and have continued to use R for statistics and data analysis since this class.
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David Keck profile image
David Keck profile image
4/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 2 months ago
I had prior exeperience Worse than others Extraordinary length of weekly lectures. BUT there's not only no certificate, but no record of having completed the course on your 'course records page'
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L Figueroa profile image
L Figueroa profile image
10/10 starsCompleted
  • 14 reviews
  • 13 completed
6 years, 5 months ago
This was a exciting and detailed class on the subject of computional finance and includes a valuable introduction to the mechanics of using both R and Excel for solving financial problems such as portfolio optimization, Value at Risk and a wide variety of statistical type calculations, including the ability to download financial data from sites such as Yahoo Finance. Professor Zivot does an admirable job in presenting the material in a useful manner for the student. One small downside, is when I took the course last year, no certificates were awarded for those students who successfully passed the course.
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Equanimous Creativity profile image
Equanimous Creativity profile image
8/10 starsCompleted
  • 33 reviews
  • 32 completed
6 years, 7 months ago
Nice course if you have or want a stock portfolio. Teach you the fundamentals on how to wight return and risk. If you know about probability and matrix calculations the 3 first weeks is very boring but it get much better.
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