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Pricing Catastrophic Risk Bonds With Expectation-Maximization Algorithms

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  • Full or part time
    Dr J Shao
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

This PhD studentship concentrates on seeking methods and financial products to reduce the impacts of natural and man-made disasters. Insurance companies do not have the adequate fund to cover the losses caused by catastrophic events, such as earthquakes, tsunamis, floods, or hurricanes. Catastrophe (CAT) risk bonds are an example of insurance linked securities (ILS) that transfer a specific set of risks from an issuer or sponsor to investors and share the risk to another level – global financial markets.

To-date, the value of CAT risk bonds is produced using approximation methods, e.g. Monte-Carlo simulation which is computationally expensive. Alternative methods, e.g. the Expectation-Maximization (EM) algorithm is used to find maximum likelihood parameters where the equations cannot be solved directly, which can then be applied to catastrophic risks for the first time. This project also investigates empirical asset pricing and sovereign risks on the pricing with the application on the historical data.

Training and Development

The successful candidate will receive comprehensive research training including technical, personal and professional skills.

All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.

Entry criteria for applicants to PhD

• A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average.


• the potential to engage in innovative research and to complete the PhD within a 3.5 years
• a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)

For further details see:

Additional specification

• Subjects include: Statistics, Biostatistics/Bioinformatics, Mathematics, Financial Mathematics, Data Science, Computer Sciences or other closely related fields.
• A strong interest in the finance.
• Strong mathematical and analytical skills, self-discipline, problem-solving capacity, intellectual curiosity, and creativity are essential qualities in order to successfully complete a PhD thesis;
• Skills in programming (in particular R, Matlab or Python), numerical modelling and in knowledge of finance or data science are beneficial but not necessary.

How to apply

To apply on line please visit:

All applications require full supporting documentation, a covering letter, plus a 2000-word supporting statement showing how the applicant’s expertise and interests are relevant to the project.

Duration of study: Full-Time – between three and three and a half years fixed term

Interview dates: Will be confirmed to shortlisted candidates

Funding Notes

Bursary plus tuition fees (UK/EU/International)

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