Institute of Risk http://www.liv.ac.uk/risk-and-uncertainty PhD Project ...

statistical approach for extreme flood prediction. Dependencies between the different kinds
of information are analysed in order to identify the most significant statistical mechanisms
and possibly a data transformation scheme. This will allow implementations to exploit
available information to a maximum extent. On the other hand, to not introduce
unwarranted information, indeterminacies and missing information in this analysis are
covered by imprecise mathematical formulations using fuzzy sets, which are then
implemented into the derived probabilistic models and estimates via fuzzy probabilities. In
this manner, the extreme flood estimates will cover the entire range of plausible predictions
using an entire set of plausible probabilistic models. Additional data/information collected
afterwards can be implemented into the new prediction model to naturally decrease the
epistemic uncertainty in the form of imprecision in the estimates with the growing amount
of information. The predictions from this envisaged model will exhibit a significantly better
quality estimate compared to current practice and avoid facing unforeseen scenarios due to
modelling errors.
Name of Project: Robust design of financial market tools
Supervisor(s): Edoardo Patelli (Engineering)
Jan Wenzelburger (Management)
Further co-supervision depending on student’s interest
Outline of Project: The proposed multi-disciplinary research project combines
engineering, financial science and mathematics. The last two decades has seen
a severe increase in natural and technological disasters, the Fukushima incident
being a prominent example. As consequence, insurance and reinsurance
industries are exposed to increasing risks. In this regard, the insurance and reinsurance
industries have been constantly looking for alternative ways to spread the risk, especially for
such large insured losses. A better understanding of how to manage these risk Financially
and how to design robust financial tool is of fundamental importance.
The key stakeholders in the risk management of risk of natural hazards can be described by
a pyramid where at the bottom are the property owners who are the primary victims of
losses caused by hazards. Insurers on the next layer offer coverage to property owners
against losses. However, faced with the possibility of very large claims caused by
catastrophic events, insurers will turn to reinsurers, the next layer of the pyramid, to
transfer some of their risk. Finally, at the top of the pyramid are the capital markets, which
in recent years have provided financial protection to both insurers and reinsurers through
financial instruments, such as Catastrophe (CAT) Bonds.
In general, the magnitude of economic and insured losses from natural disasters raises
various questions. For instance: a) who are the individuals affected by these events? b)
What options are available to them to assess their risks? c) what factors influence their
choices to deal with and actively managing these risks?
The specific objectives of the project comprise the following:
� Develop a reliability framework for modelling and analyse how hazard risks
propagate into the financial market studying the impact of securitized risks on the
prices of financial assets.