Munir Hiabu

I studied Mathematics at Heidelberg University and I obtained a PhD in Actuarial Science from Cass Business School.

In my research I work on non-parametric survival analysis. My prime focus is hereby in-sample forecasting.

Recently I also started working on the design of novel pension products.

For more information visit my personal website: https://sites.google.com/site/munirhiabu/

Qualifications

PhD Actuarial Science, Cass Business School, City, University of London, UK MSc Mathematics, Heidelberg University, Germany BSc Mathematics, Heidelberg University, Germany

Awards

• Dimitris N. Chorafas Foundation (2016) Dimitris N. Chorafas Foundation Award Awarded in he last year of the PhD for outstanding work in selected fields in the engineering sciences, medicine and the natural sciences.
• Cass Business School (2015) Best Presentation Award Awarded by Cass Business School for the best talk given during the PhD Research day of the Actuarial Science and Insurance Faculty.

Languages

English and German.

Expertise

Primary Topics

• Actuarial Statistics
• Pensions
• Probability Theory
• Statistics

Title of Thesis: Estimating operational time in a survival analysis setting and application in actuarial reserving

Sep 2016

Summary of Research

The aim of my research is to add operational time, i.e., a certain dependence stucture, to the continuous chain ladder model. There is empirical evidence that such a generalisation of the continuous chain ladder model is appropriate and that independence should not be assumed. The goal is to derive full asymptotics for our new estimators and to compare it with another already existing one. Besides, we are interested in the results on small datasets as they can be found in practice. Furthermore, I examine and compare the performance of simpler, multiplicative models for small samples sizes in simulations and on a datase.

External Supervisor

Mammen, E. Heidelberg.

Featured Publication

• Hiabu, M. (2017). On the relationship between classical chain ladder and granular reserving. Scandinavian Actuarial Journal, 2017(8), pp. 708–729. doi:10.1080/03461238.2016.1240709.
• Hiabu, M., Mammen, E., Martìnez-Miranda, M.D. and Nielsen, J.P. (2016). In-sample forecasting with local linear survival densities. Biometrika, 103(4), pp. 843–859. doi:10.1093/biomet/asw038.

Journal Articles (6)

• Hiabu, M. (2017). On the relationship between classical chain ladder and granular reserving. Scandinavian Actuarial Journal, 2017(8), pp. 708–729. doi:10.1080/03461238.2016.1240709.
• Hiabu, M., Mammen, E., Martìnez-Miranda, M.D. and Nielsen, J.P. (2016). In-sample forecasting with local linear survival densities. Biometrika, 103(4), pp. 843–859. doi:10.1093/biomet/asw038.
• Hiabu, M., Margraf, C., Martínez-Miranda, M.D. and Nielsen, J.P. (2016). Cash flow generalisations of non-life insurance expert systems estimating outstanding liabilities. Expert Systems with Applications, 45, pp. 400–409. doi:10.1016/j.eswa.2015.09.021.
• Hiabu, M., Margraf, C., Martínez-Miranda, M.D. and Nielsen, J.P. (2016). The link between classical reserving and granular reserving through double chain ladder and its extensions. British Actuarial Journal, 21(01), pp. 97–116. doi:10.1017/S1357321715000288.
• Hiabu, M., Martínez-Miranda, M.D., Nielsen, J.P., Spreeuw, J., Tanggaard, C. and Villegas, A.M. (2015). Global polynomial kernel hazard estimation. Revista Colombiana de Estadistica, 38(2), pp. 399–411. doi:10.15446/rce.v38n2.51668.
• Nielsen, J.P., Verrall, R., Miranda, M.D.M., Hiabu, M. and Agbeko, T. (2014). Validating the Double Chain Ladder Stochastic Claims Reserving Model. Variance: advancing the science of risk, 8(2), pp. 138–160.