PhD in Efficient Computational Methods for xVA and Financial Risk Management

The aim of this fully funded PhD position is to develop innovative methods for efficiently computing Valuation Adjustments, known as xVAs, along with associated sensitivities and risk measures, that effectively balance accuracy, cost, and interpretability. The new algorithms will be predominantly based on adaptive/hierarchical sampling, variance reduction, path signatures, and machine learning ideas. This project will span theory, algorithm development, and numerical analysis.

Your job
Financial institutions are required to adopt and report various Valuation Adjustments, known as xVA, for over-the-counter derivatives, while also managing associated risks. The primary goal of xVA is to integrate various risk categories and external factors —such as Counterparty Credit Risk— into the pricing of derivative contracts. Efficient computation of xVA metrics, along with their associated risk measures and sensitivities to underlying factors, is crucial for effective portfolio risk management. However, despite existing methods proposed in the literature, these calculations continue to be computationally intensive due to the complex and high-dimensional nature of the problems. Challenges include numerous risk factors and counterparties, large portfolios with path-dependent derivatives, and complex models governing the dynamics of risk factors and defaults.

You will work within the Computational and Modeling Finance group at the Mathematical Institute at Utrecht University, under the guidance of Dr. Chiheb Ben Hammouda. This position offers a unique opportunity to contribute to both practical and scientific advancements in the field. You will be part of a vibrant research group, regularly exchanging expertise with members of the group and leveraging connections with industrial partners, and external international collaborators. This environment will foster both practical and scientific growth, with anticipated contributions relevant to practical applications and other scientific computing fields.

In this PhD position you will:

• conduct research in quantitative finance and numerical analysis;
• publish research findings in scientific (mathematical and finance) journals;
• get the opportunity to attend scientific meetings, conferences and workshops locally and abroad;
• communicate the findings with the finance group members;
• undertake some teaching activities at the Mathematical Institute at Utrecht giving you the opportunity to gain teaching and student supervision experience.

This project may be the right fit for you, if you have:

• a strong background in mathematics, probability/stochastics, (stochastic) differential equations, and numerical analysis;
• a Master’s degree in mathematics or a related discipline, or currently in the process of completing such a degree;
• experience with quantitative finance, numerical methods and/or machine learning (this is advantageous);
• strong familiarity with at least one programming language;
• demonstrable analytical and problem-solving skills;
• strong oral and written communication skills in English;
• ability to work both independently and as part of a team.

We offer:

• a position for four years;
• a working week of 38 hours and a gross monthly salary between €2,770 and €3,539 in the case of full-time employment (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU));
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University has a number of schemes and facilities of its own for employees. This includes schemes facilitating professional development, leave schemes and schemes for sports and cultural activities, as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest in their growth. For more information, please visit Working at Utrecht University.

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The Mathematical Institute in the Department of Mathematics is internationally recognised for its research in both pure and applied mathematics. It houses the Utrecht Centre for Mathematical Modelling and maintains a long-standing tradition of transdisciplinary collaboration with other scientific fields including, among others, mathematical finance, applied data science, computational life sciences, and theoretical physics.

The Mathematical Institute has close ties with several departments, including Economics, Physics, Information and Computing Sciences, Biology, and CWI (the National Research Institute for Mathematics and Computer science). We participate in university focus areas in Complex Systems and Applied Data Science. The institute organises and teaches the Bachelor's curricula in Mathematics as well as the (English-taught) Master's programme. The institute currently comprises about 40 faculty members, 11 Postdocs, and 29 PhD candidates, and teaches 500 students.