ETC3460: Financial Econometrics

Assignment 1 & 2 - 15% each (30%) - These were done in groups that were allocated randomly based on your tutorial, with 4-5 students in each group. Both assignments consisted of short-answer questions related to the material that had been taught. Assignment 1 was mainly focused on theory behind the CAPM + some interpretation work from EViews, whilst assignment 2 was solely interpretation and graph plotting in EViews. As long as you've done ETC2410 recently, then you should be fine with the EViews work as all steps to carry out analysis in EViews is covered in the course, with the exceptions of news impact curve plotting, which could be done in whatever program you wanted. Most students did well in these assignments as the questions weren't too tricky, with only the odd curveball question here and there.

Group Project (10%)

This was the most tricky task to do for the semester. In the same groups as the assignments, you were to pick up to 10 stocks from the Australian Stock Exchange (ASX), and track your performance in their returns over the semester. Then, starting from mid-way through the semester, you were to forecast tomorrow's returns, using past returns and the methods taught in class. Gradually over the semester the forecasting power got better and better, as there were more models available to help predict your returns. These returns + forecasting methods were then to be written into an investment report, which was to be marketed as a tool for potential investors to invest in the stocks that you had chosen. This was quite tricky for me and my group to plan and write, as it was the first time that we had ever written something in this domain. After the report was submitted, the top 20 groups (out of 64 for the cohort) were chosen and had to present a 5 min report to the class in the week 12 lectures, summarising their report. The top 5 groups out of those 20 received full marks, with the remainder receiving 90%. I found the marking to be very generous for this, resulting in high marks overall, which justified the effort put into the work at hand. My tip for this would be to start as early as possible with forecasting methods, and ideas on how to write up your report, as this will take a ton of time to put together, and will subtract time from everything else that you would like to do on the side.

Exam (60%)

The exam consisted of 4 questions in the following form.

Q1 GARCH Modeling: 20 points
Q2 CAPM Analysis: 30 points
Q3 Time Series Analysis: 20 points
Q4 Volatility Analysis: 30 points

70% of the exam was very similar to the 2018 exam so was not that tricky. The remainder though comprised unseen material, particularly question 4 in relation to using the normal distribution and proving its probabilities. This tripped up a lot of people, including myself, as this was something that had never been fully explained in class as a potential exam question. Despite this, the exam was not overly difficult and was a fair exam that was able to be completed within the 2hr duration. This was reflected by the mean of the exam marks being around 64%, such that it was very fairly written overall. To prepare for this, go through all the tutorial questions again and again, particularly the two revision tutes in weeks 11 and 12, and then attempt the 2018 exam to the best of your ability. The trouble was, I seemed to find the 2018 exam easier than the 2019 exam, as the degree of difficulty seems to have been increased in the 2019 exam to compensate for high in-semester marks.

Thoroughly enjoyed this subject. David is a gun at explaining financial econometrics, and has done a great job of piecing this unit together into one build-up of knowledge. The lecture slides are of outstanding quality, so definitely use those as a revision tool for the exam, even with the odd typo here and there.

The only issue I found was with EViews work. Some commands had to be manually written in the command window in EViews, which was a bit clunky as I was learning code on the go whilst trying to get the graph that I desired. For example, the recode function for EViews was only taught in the week 10 tute, and was necessary for assignment 2 to plot news impact curves in EViews. This is being fixed in the future though as the unit is switching to R and RStudio from next year to do all graphical outputs, due to the majority of students having the background in R and RStudio to be able to use it confidently in the subject.

The content started with a review of statistics needed in the unit, particularly the law of iterated expectations and law of total variance which are examined upon heavily in the exam. Then basic financial modelling such as the CAPM, AR, MA and ARMA process are examined as well as the theory behind finance, returns and financial products. After this, volatility modelling is covered through ARCH, GARCH, T-GARCH & EGARCH processes. Then multivariate volatility is touched upon, in the form of the BEKK and DCC models but this was not covered in the exam.

Tutorials were pretty standard, but were done in the Learning and Teaching Building (LTB) using EViews via MoVE on your personal computer, instead of the computer labs in the Menzies building due to booking constraints. This made the work a little annoying to do due to computers constantly rebooting or being unable to connect to EViews via MoVE and Citrix Receiver. The tutorial class sizes were also large, with around 50 students in each of the 5 tutorial sessions. I had Nathaniel and Shuofan as my tutors, both of whom knew the content extremely well and provided great explanations to each tutorial question. Make sure you go to each tute as stated above, due to detailed tutorial solutions not being provided unless you attend the tutorial or a consultation session for either David or one of the tutors.
Overall, highly enjoyed this unit, as it combined my financial and econometric approaches together. I would strongly recommend this unit for anyone with an econometric / stats / mathematical background if you did ETC2410 and enjoyed it, as it goes deeper into modelling financial products and is a really enjoyable subject due to David providing such a succinct course structure.

David Frazier - Also CE & unit coordinator for the subject. David is incredibly passionate about financial econometrics, so his lectures were very engaging and worthwhile to attend. He knew the content extremely well, only referring to the slides to provide tips on the key material via his laser pointer, or indicating at graphs on the slides. What is key to know is that David does use a laser pointer each lecture to provide further emphasis on the material, and this does not appear in the recordings, so try and get to the lectures otherwise you miss that additional detail.

Yes, the 2018 exam was given along with indicative solutions provided in SWOTVAC.

4.5 out of 5

Yes, with screen capture

No textbooks are needed for this subject, as the slides + Kevin Sheppard's notes provided on Moodle are sufficient to understand the content

2 x 1hr lectures per week
1 x 1.5hr tutorial per week - Attend these each week, as the content is gone over in far more detail + no solutions are given for tutorial questions except in the tutes themselves.

Semester 1, 2019

81 HD