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    Back to Computational Methods in Pricing and Model Calibration

    Learner Reviews & Feedback for Computational Methods in Pricing and Model Calibration by Columbia University

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    4.3
    stars
    40 ratings

    About the Course

    This course focuses on computational methods in option and interest rate, product’s pricing and model calibration. The first module will
    introduce different types of options in the market, followed by an in-depth discussion into numerical techniques helpful in pricing them, e.g.
    Fourier Transform (FT) and Fast Fourier Transform (FFT) methods. We will explain models like Black-Merton-Scholes (BMS), Heston, Variance
    Gamma (VG), which are central to understanding stock price evolution, through case studies and Python codes. The second module introduces
    concepts like bid-ask prices, implied volatility, and option surfaces, followed by a demonstration of model calibration for fittin...
    ...

    Top reviews

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    1 - 11 of 11 Reviews for Computational Methods in Pricing and Model Calibration

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    By skanuri

    •

    Jun 2, 2023

    Watched all lecture videos in Week 1 & 2. Took detailed notes of all derivations. This is unquestionably the BEST course on Coursera I have ever taken! Professor Hirsa was clear and audible in all videos (and that really matters, after I have completed several Coursera courses and the audio in some wasn't good). The material is top notch, the professor's way of explaining the concepts is just phenomenal! So happy to be auditing this course (auditing for now). Dr. Gilbert Strang and Dr. Ali Hirsa stand out for their excellent teaching skills -- thank you!

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    By Alina C

    •

    Apr 8, 2025

    I was impressed by the level of theoretical depth, much more than I expected, and in a very good way. The balance between theory and hands-on, from-scratch implementation was spot on. Solid university-level math knowledge is definitely needed, which I think is a strength of the specialization. Many thanks to the professors and staff for designing such a beautiful and valuable specialization. I can recommend all courses from it.

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    By daniel h

    •

    Oct 5, 2022

    Very practical and useful course, congratulations to the professor, I really enjoyed it!! :)

    pd: I recommend to have a good background in calculus and programing before applying

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    By Hao H

    •

    Jul 3, 2024

    It is great, this is brand new content. I made sure I fully understood all the content to be able to implement the code correctly and pass exams.

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    By Marco P

    •

    Feb 7, 2025

    This course provide many technical and theoretical tools to really understand how to valued finacial instruments

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    By Sheng Z

    •

    Jul 28, 2024

    nice course

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    By Sandra J

    •

    Nov 7, 2024

    excellent

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    By Kostya T

    •

    Sep 19, 2021

    Great course, one of the best in Financial Engineering and Risk Management specialization. Really enjoyed doing quizes and assignments, change from Excel to Python is fantastic. At the time of taking the course is a bit rough around the ages, especially closer to the end, e.g. with one part of a lecture missing and quite a few lectures duplicated. Would have been nice to have more references to literature/papers for further study. Also would be really cool to add DNN pricing from the 2019 paper by the professor.

    All in all a very positive experience, many thanks professor Ali Hirsa!

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    By Murray S

    •

    Oct 19, 2021

    I found that the course relied extensively on the use of Python in order to complete the assignments/quizzes. Not being a Python user, I spent a lot of time understanding notebooks in Python and Python coding conventions, which I would have rather spent on learning the concepts in the course. That said, the course content itself was fine.

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    By Angela T

    •

    Feb 26, 2023

    The course is easy to follow, and I like the laboratory part, where we can apply what we learn using Python. The only four disadvantages of the course are 1.- You cannot download the lessons in pdf and, therefore, it takes more time than expected to complete them (because you need to copy everything by yourself) 2.-There are some .py files that are not available. Supposedly, Coursera is not allowed to share them, so, in the end, you end up with some Python files that you won't be able to reuse (Module 5) 3.- Some Python homework asks for unnecessary tasks (such as in Module 3, and the use of Brute-Force) where you end up stuck. 4.-The help desk is slow; Coursera should improve this.

    Filled StarStarStarStarStar

    By J

    •

    Feb 3, 2022

    I purchased a subscription and started this course just to realize after some time that it is utterly incomplete. Slides of the presentation are missing (why?) and after several months staff confirmed that slides would never be provided, no reasons given (why??) - the situation is so incomprehensible that lead me to cancel my subcription.

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