This class was fine. The title is somewhat misleading - you don't really learn a whole lot about "Computational Methods" and there is barely any "Data Analysis". There's a nominal coding component in R, and weekly lab lectures where the TAs teach some stuff about R, but it's very basic stuff, and you can get through all the coding homework parts by following the TA example code. I was somewhat disappointed that with a name like "Computational Finance and Data Analysis for Financial Engineering", there were few useful skills that I learned (ARMA and ARCH models notwithstanding).

Liao isn't the most engaging lecturer, and he can be a little hard to understand at times, but at least his slides were good. The first half of the class is a review of basic concepts in finance and probability. I haven't taken 106F, but some of my classmates said it was all review from that class. The second half covers time series concepts and models, including conditional volatility (ARCH/GARCH), with a final section on portfolio theory which I found interesting. The time series and conditional volatility models are the most useful part of the class for real-world skills, but I took Econ 144 with Rojas in the same quarter, and the time series concepts in this class paled in comparison to the shitshow that was Rojas. The second half of this class would actually be a good preparation for Econ 144.

The tests were much more difficult than the homework (which was not a good preparation). Make sure you have probability and statistics from Econ 41 squarely down, as this class relies on that a lot. Both the midterm and the final allowed "cheat sheets", which were very helpful (if you take the time to prepare them right). Overall, the class wasn't that difficult, and it's a fine choice if you're interested in econometrics electives.

I took this class after Econ 144 with Rojas, and there is a lot of overlap. Professor Liao's class has a more theoretical approach, requiring you to prove certain properties of processes. The R coding is minimal, and most of the code is given to you already. The workload is low, with four lab assignments (very little work) and five homework assignments. The homework is short and the questions follow directly from lecture notes, so they aren't too bad. The grade makeup is 50% Final, 30% Midterm, and 20% Homework. The professor offers two different grading methods to determine your final grade, either based on your raw score (>=85 is an A) or ranking in the class (top 20% is an A). The exams aren't easy, but they are fair and take a few questions directly from the homework. He also allows a double-sided page of notes during the exams. During lectures, he annotates the slides with his iPad, which can cause a lot of clutter. These are usually just further explanations, so remember that the essentials are typed on the original slide. Professor Liao is very nice, and I would take another class with him again.

The first half of this course was really hard looking back. THe first half was basically just focusing on returns and statistics, stuff you would learn in econ 41 and 103 but the midterm really drills you hard on how much you can remember from 41 and 103. You need to be really good at statistics in order to do well but this class is also related to 104 and 144 since the second half gets into the higher level statistical models and their properties. The final wasn't bad, it's what you would see based on your homework and final practice tests he gives as well as stuff from the actual midterm. The homework and lab assignments are doable and are the bulk of your grade. He's very responsive to emails and helpful (I never went to office hours, had a time conflict). The curve is also generous so even if you feel like you're doing bad (like I did cause I thought I bombed my midterm), chances are most people in the class felt that way and the curve does account your performance in comparison to others. So if you want to take this class, you should take it if you want to learn more about econometrics and data science, especially if you want a focus in financial markets

Professor Liao is a good instructor. He explains concepts from the first principles and is very knowledgeable about the material. However, this course is more theoretical than practical, so avoid this course if you want to get hands-on experience in financial engineering.

Grade-wise, Professor Liao is a lenient grader. It is quite easy to get A/A- but requires a lot more work to get an A+.

Overall, a decent quantitative upper elective. Would take it again.

I feel bad saying this, but it was difficult to understand Zhipeng because of his accent. It made going to lecture pointless, so I exclusively used the slides. That being said, the slides are very comprehensive and give you almost everything you need to know for the class. The workload is decent, but is mostly graded on completion. The labs supplied all the code necessary for assignments, so an understanding of R isn't really needed. Overall, a decent class with a high ceiling, if the subject material really speaks to you and you want to learn more.

Taking this class online, his accent made it REALLY REALLY hard for me to get through the lectures. I felt quite lost in this class as the professor focused only on delivering the material and did not really address anything else in the class? Just read the syllabus. Discussion sections are basically office hours with the TA, so you could use that if you're lost at lecture. This class uses R and they go at a pretty decent pace so just make sure to keep up with it each week.