Universities / Monash University
Master of Financial Mathematics (MFinMath)
A mathematics-led route into financial modelling, with stochastic calculus and risk management at its centre. Electives cover pricing, numerical finance and statistical learning, while a placement or industry research project applies the methods.
What you’ll study
Core
- Stochastic calculus and mathematical finance
- Quantitative risk management
Electives
- Interest rate modelling
- Computational methods in finance
- Quantitative trading and market microstructure
- Partial differential equations in finance; From qualitative analysis to machine learning
- Quantitative and data analysis in Python
- Financial machine learning
- Advanced financial econometrics
- Statistical learning in finance
Source: handbook.monash.edu ↗
Before you apply
- Background
- Bachelor’s degree or equivalent with strong mathematical content and at least a 65% credit average; advanced entry depends on mathematics qualifications.
- Maths
- multivariable calculus; linear algebra; probability; statistics; differential equations
Source: monash.edu ↗
After graduation
The programme doesn’t publish an employment report.
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Entry points require 48, 72 or 96 credits. Major industry placement/research routes require a 70% average in Part B; a placement is not an employment guarantee.
Checked 6 November 2026 against the sources linked on this page. Fees, units and requirements change each year, so confirm them on the programme’s website before applying.
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