CS16: Recent Advances in Financial and Actuarial Mathematics

Organizer: Zbigniew Palmowski (Wrocław University of Science and Technology)

Valuation of multi-region CoCoCat bonds

Krzysztof Burnecki

We introduce a novel, multidimensional insurance-linked instrument: a contingent convertible bond (CoCoCat bond) whose conversion trigger is activated by predefined natural catastrophes across multiple geographical regions. We develop such a model, explicitly accounting for the complex dependencies between regional catastrophe losses. Specifically, we explore scenarios ranging from complete independence to proportional loss dependencies, both with fixed and random loss amounts. Utilizing change-of-measure techniques, we derive risk-neutral pricing formulas tailored to these varied dependence structures. By fitting our model to real-world natural catastrophe data from Property Claim Services, we demonstrate the significant impact of inter-regional dependencies on the CoCoCat bond’s pricing, highlighting the importance of multidimensional risk assessment for this innovative financial instrument.

Dr

Joanna Janczura

We propose a new method for probabilistic forecasting of electricity prices. It is based on averaging point forecasts from different models combined with expectile regression. We show that deriving the predicted distribution in terms of expectiles, might be in some cases advantageous to the commonly used quantiles. Using expectile predictions as a future risk measure we propose a short-term diversification strategy for an electricity trader. The proposed methods are applied to the day-ahead electricity prices from the German market. The obtained results show that implementation of dynamic strategies based on expectiles improves the outcomes in terms of risk as well as profit.

Bibliography

\([1]\) Joanna Janczura. “Expectile regression averaging method for probabilistic forecasting of electricity prices.” Computational Statistics vol. 40, 2025, pp. 683–700.

\([2]\) Joanna Janczura, Edyta Wójcik. “Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study.” Energy Economics vol. 110, 2022, pp. 106015.