**Subject Code/Name:** MATH3311/MATH5335 - Mathematical Computing for Finance/Computational Methods for Finance **Contact Hours:** 2 x 1.5 hour lecture per week. 1 x 1.5 hour tutorial per week.

**Assumed Knowledge:** (MATH2121 or MATH2221 or MATH2111) and (MATH2501 or MATH2601) and (MATH2801 or MATH2901 or MATH2871). Be very comfortable with all of these. I'd go as far as to say take all of the core second-year math subjects before taking this (yes, even complex analysis).

Also, take 2301. I found it helpful to have some decent background knowledge in Matlab, although there's no need to already know Matlab. There are free and accessible resources to help you learn, and it's quite simple to pick up if you're already decently versed in another programming language, or if you're learning from scratch!

**Assessment:** 4x5% Assignments. These weren't too difficult for the most part, mainly being able to translate mathematical logic into Matlab efficiently. There are a few times where you'll want to bang your head into a desk, but as long as you know a couple of tricks (such as not always needing to store an entire matrix, but just one vector that you can play around with for some recursive fun), you shouldn't have too much trouble with it.

20% Matlab Test. This was a bit scary in the leadup, but as long as you just grind out the lab work and past papers you'll smash this.

60% Final exam. Very little preparatory material for this, only past papers. There's no 30-page problem set for this course (unlike every other math course I've taken). The only stuff you're given are weekly self-study questions taken from past papers, so what'll happen is that you finish up the term and realise that there are no new problems for you to study. This made me feel very underprepared going into the final, and I had gotten near full marks on the assignments and problem sets. The final for MATH3311 is shared for MATH5335, so there may be some scaling up for 3311 students.

EDIT: I just finished the exam. What a shocking paper. There were large parts of that paper that we never once covered in lectures, never touched on in labs, and never appeared in past papers, and it certainly didn't come from the textbook or any of the prerequisite courses. I can only pray that we're scaled like hell, because I was only able to answer 25% of that exam with some confidence.

**Lecture Recordings?** Pre-recorded lectures, accessible from the start of the course. They go in-depth with all the topics, and even into some non-assessable topics if you're super keen.

**Notes/Materials Available**: Full slides. As I said above, there are no problem sets for you throughout this course, so you're basically relying on remembering everything you learnt in second year. Some extra resources (even just some refresher questions) would've been helpful.

**Lecturers: ** Professor Josef Dick, 3.5/5. He was alright, explained things well, managed to keep my attention.

Dr Leung Chan, 3/5. A bit difficult to understand at times, but alright for labs.

**Year & Trimester of completion:** 2021/T2

**Difficulty:** 4/5.

**Overall Rating:** 2/5.

**Your Mark/Grade:** 67 CR (seems like the final exam was heavily scaled)

**Comments: ** For a course called Mathematical Computing for Finance, I expected a lot more of the finance side to come into play. It wasn't until week 7 that we first talked about Black Scholes, and that was only in the context of non-linear equations. The course isn't super focused on finance, nor solving problems related to finance.

The first half of the course is your typical "here's Matlab, here's what you can do, here's why it's a terrible idea to use Matlab". The second half covers numerical integration, random numbers, simulations, and PDE's, with a few equations used in finance dotted throughout. I would've much preferred that the course have a focus on financial applications from the start, or at least have problems that help you to see the connection between what you're learning and what is used by financial analysts. Because of this I never felt that the course went below a superficial skim of financial computing. I still learned a lot about Matlab from this course, and if it weren't for catfishing us by calling it computing for finance I'd easily give it a 3.5 or a 4. It just feels like what I learned wasn't quite what I signed up for, which is a shame.

That's a wrap on my math degree though! What a journey! From failing extension math in year 11 and being told that a degree involving lots of maths wouldn't be a good idea, to ticking off all the requirements for a mathematics degree! Excited to finish up my economics courses next term, and then (hopefully) start my economics honours next year!