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Pandemic Bond Pricing: Extending the Hull-White & Stochastic Logistic Growth model with Wang Transform - Insights from Germany Data and Trigger Activation Probability Sensitivity
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Orientador(es)
Resumo(s)
As pandemics show an increasing frequency, research on effective pandemic risk management strategies plays a crucial role in strengthening financial markets and insurance industry resilience to such events. This study proposes an extension for Manathunga and Deng’s (2023) pandemic bond pricing framework by integrating the impact of a pandemic inception date relative to the bonds term and adjusting trigger activation probabilities using the Wang transform. As a first approach to pandemic bond pricing using German COVID-19 data, different growth rate scenarios are employed. The following scenarios offer insights into the proposed pandemic bond’s price sensitivity relative to possible pandemic start dates and trigger activation probability scenarios. The Wang transform is used to reflect investors aversion or optimism towards pandemic risk from issuance to bonds maturity. This research hopes to contribute to the emerging field of pandemic bond pricing, providing guidance for investors and policymakers navigating pandemic risk in financial markets.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
Palavras-chave
Pandemic bonds Bond valuation Hull-White model Stochastic Logistic growth model Wang transformation Triggering conditions Pandemic inception date Sensitivity analysis COVID-19