Lower funding ratios driven by lower interest rates and increasing life expectancy have forced pension funds and life insurance companies globally to re-think the asset liability management of their pension portfolios and follow a de-risking strategy. The hedging of longevity risk through longevity swaps is a key part of that strategy. In addition to traditional longevity swaps there are instruments which are linked to a mortality index (such as the mortality coefficients for the Dutch population published by the Central Bureau of Statistics). These have the potential for standardization and create a deep and liquid market for longevity risk. A drawback of these instruments is the basis risk between the mortality index and the actual portfolio to be hedged.
The aim of this internship is to extend the work of Cairns and El Boukfaoui (2017) and internal research on basis risk to include commutation risk, replicating portfolio risk and model risk. We start by implementing a stochastic 2-population mortality model that allows to evaluate the basis risk of an index hedge. We then extend existing models for basis risk to include new risk types. Eventually, after understanding all types of basis risk, changes to the index hedge.
Next to a personalized internship in an extremely relevant topic in the pension fund and life insurance industry, the VB risk advisory team prepares you for a career in the financial industry. This internship will help you acquire financial risk management skills, programming skills and provide you the flexibility in terms of working hours. Your hard work will be recognized and rewarded both financially and through development opportunities. We are preferably looking for an intern with the optionality to write his or her thesis in four to six months.
Functional work area: Quantitative Modelling / Finance / Data Science / Research & Development
Hours per week: 36 - 40
Quantitative academic education (MSc Student) in a relevant field, like econometrics, mathematics, actuarial science or physics is a must. The preferred candidate is flexible, proactive and has a positive attitude. Furthermore, accuracy, problem solving skills, decision making skills and ability to work independently with tight deadlines is required as well. Strong affinity with Quantitative Models, Finance, Risk and Data.
Experience in advanced programming language (e.g., MATLAB, R or Python) and interested to work with large datasets.
Required language skills
Well versed in both Dutch and English.
Interested and ready for a challenging and promising graduation period? Send your Curriculum Vitae to us! In case of any questions with regard to this graduate internship do not hesitate to contact Guillamo Bonapart (firstname.lastname@example.org) or send your contact person information and motivation letter to us via the apply button.