Giorgio Consigli (Khalifa university and University of Bergamo)

Coauthors: Lewis Ntaimo (Texas A&M U), Randhy Pratama (Khalifa U) and Xin Yu Zhuang (Texas A&M U)

Increasing exposure to natural risks, from floods, hurricanes, earthquakes, tsunamis and alike is affecting large regions and causing unprecedented human and economic costs globally. The financial resources allocated to mitigate these risks can be local or coming from international and supranational institutions (WB, IMF, EBRD, etc), from developed countries on a bilateral basis, and now increasingly from capital markets thanks to the development of the market of insurance-linked securities (ILS).

Of specific relevance among ILS the Catastrophe (CAT) Bond market that during the first quarter of this century has experienced a remarkable growth, with a nominal amount outstanding at the end of 2025 of around 61.3 billion USD, of which 25.6 bln issued in 2025.

In this research project, taking the perspective of a policy maker, we consider the impact of a CAT bond issuance for natural risk hedging as well as the implications of a 2-stage stochastic programming formulation for an optimal risk capital allocation problem by a central planner with a 1 year horizon.

The natural risk process is modeled as an homogenous marked Poisson process with state distribution modeled by a Generalized Pareto distribution and a Gaussian kernel. For bond pricing purposes a simple one state variable model (Vasicek 1977) is adopted for the yield curve.

A case study is presented for a region in Indonesia historically among the most exposed to earthquakes in the world. A set of evidence is provided to assess the accuracy of the natural and financial risk models, validate the pricing methodology and the optimization problem formulation. The case study helps clarifying the benefits of an optimal risk-based budget allocation and of risk transfer to capital markets for governments from developing countries.