Corvinus University of Budapest

What you'll study

The programme combines advanced courses in real and functional analysis with probability, statistics and computational techniques tailored to economic and financial applications. Core topics typically include measure-theoretic probability, stochastic processes, stochastic calculus, partial differential equations arising in pricing and optimisation, convex and variational analysis, numerical methods for PDEs and SDEs, and mathematical statistics.

• Mathematical foundations: real analysis, functional analysis, measure theory and optimisation theory.
• Stochastic and probabilistic methods: stochastic processes, martingale theory, stochastic calculus and limit theorems.
• Financial and economic modelling: continuous-time models, derivative pricing PDEs, risk measures, portfolio optimisation and equilibrium models.
• Statistics and econometrics: mathematical statistics, time series analysis and inference techniques used for model calibration and validation.
• Computational skills: numerical methods for differential equations and stochastic simulation, plus programming for data analysis and modelling (commonly using languages and tools such as Python, R, MATLAB or C++).
• Research and applied work: seminars, project courses and an individual master’s thesis that emphasise rigorous problem formulation, mathematical proof and numerical implementation.

Entry requirements

Applicants are normally expected to hold a relevant Bachelor’s degree in mathematics, statistics, economics with strong quantitative training, physics, computer science or engineering. Successful candidates typically have completed courses in calculus, linear algebra, real analysis, probability and statistics. Admissions will consider academic transcripts, a CV, a statement of purpose outlining mathematical interests, and at least one academic reference.

Where applicable, applicants whose first language is not English may need to provide evidence of language proficiency. Some applicants may be asked to attend an interview or to demonstrate their mathematical background through additional written tests or sample work.

Career prospects

Graduates are prepared for a range of quantitative careers in finance, industry and academia. Typical roles include:

• Quantitative analyst / model developer in banking, asset management or hedge funds
• Risk modeller and risk manager in financial institutions or insurance
• Data scientist and algorithmic trader roles that require strong stochastic and numerical skills
• Analyst positions in central banks, regulatory bodies or economic research institutes
• Entry to doctoral programmes in mathematical finance, econometrics or applied mathematics

Why study at Corvinus University of Budapest

Corvinus has a strong tradition in economics and finance and offers an interdisciplinary environment where rigorous mathematics meets applied economic research. Students benefit from close links between theoretical courses and applied seminars, access to faculty active in both academic research and industry consultancy, and opportunities to collaborate with research groups focused on finance, risk and econometrics.

The university’s central European location and connections with financial institutions and multinational firms in Budapest also support internship and employment opportunities, while workshops, guest lectures and seminar series regularly bring practitioners and academics together to discuss current problems at the interface of mathematics, economics and finance.