Applications of Quantitative Methods in Finance

Resources for Applications of Quantitative Methods in Finance (AQMF)聽- for more information about the course, please see聽course outlines.

Study skills

You may be interested in the MLC's seminars on聽doing a maths exam听补苍诲听writing and using a cheat sheet.

Assumed knowledge

This course follows on from Introduction to Financial Mathematics I, and it is a good idea to revise the skills learned in that course.

The MLC resources for Introduction to Financial Maths I are on this webpage. They will help you revise the content from the previous course.

Revision seminars in order of time

In most years, the MLC gives a revision seminar for AQMF before the exam. Below are the revision seminars that have been given in the past for this course.

2024

This revision seminar was given for students of AQMF in Semester 2 2024. Nicholas discussed the following things: Bayes' formula (at 2m28s), Multivariable calculus (at 29m23s), Sum notation and upper/lower sums (at 1h9m48s), Techniques of integration (at 1h28m39s).

2023

This revision seminar was given for students of AQMF in Semester 2 2023. Nicholas discussed various problems including Lagrange multipliers, conditional probability, derivatives by first principles, producer/consumer surplus, discrete probability distributions.

2022

This revision seminar was given for students in AQMF in Semester 2 2022. David talked about many things, but only the first 15 minutes of the seminar got recorded, which contains an example of finding critical points of a polynomial function. The document camera notes from all the topics discussed are available though.

2019

This revision seminar was given to students in AQMF in Semester 2 2019. David discussed implicit differentiation (at the beginning), and differential equations (38m30s).

2018

This revision seminar was given to students of AQMF in聽2018. Nicholas covered miscellaneous topics from the course including probability (at the start), markov chains (42m45s), income streams (1h31m8s), tricky derivatives (1h51m58s), integration by parts (2h1m30s), and normal distributions (2h11m20s).

2015

This revision seminar was given to students of the AQMF in 2015. Nicholas gave several examples of upper sums and also the trapezoidal rule.

This revision seminar was given to students of AQMF聽in 2015. Nicholas gave some worked examples of Markov Chain problems.

This revision seminar was given to students of AQMF in 2015. Nicholas answered questions about differential equations, in particular about separable equations and particular vs general solutions.

2014

This revision seminar was given to students of AQMF in 2014. Nicholas talked about the rules for calculating and rearranging with sum notation.

This revision seminar was given to students of AQMF in 2014. Nicholas gave a short revision seminar on just the binomial distribution and the normal approximation to it.

2013

This revision seminar was given to students of AQMF in 2013. David covered the idea of two-variable functions, their derivatives and an example of using Lagrange multipliers.

This revision seminar was given to students of the AQMF聽in 2013. David discussed details of how Markov Chains work including finding steady state vectors, and then summarised the whole topic.

2012

This revision seminar was given to students of AQMF聽in 2012. It covered various integration techniques including the basic formulas, substitution and integration by parts.

This revision seminar was given to students of AQMF in 2012. David discussed implicit differentiation, and differential equations.

This revision seminar was given to students of both Maths 1A and AQMF in 2012. It covers calculating integrals using upper and lower sums.

This revision seminar was given to students of Maths IB and AQMF聽in 2012. It covers domains, ranges, partial derivatives, maxima and minima in multivariable calculus.

This revision seminar was given to students of AQMF in 2012. David covered discrete distributions, the binomial distribution, the normal distribution, expected values and variance.