Modern Numerical Techniques and Machine-Learning in Pricing and Risk Management

Dear Colleagues,

In present day financial practice, we need to model and price the impact of a counterparty going bankrupt. In modern risk management, different valuation adjustments, commonly known as “xVA” (where “VA" stands for valuation adjustment and the "x" means “any letter”, where each letter stands for a different VA component), are added to the fair value of a financial derivative. Accurate pricing and hedging of these VAs is of a high importance and requires sophisticated models and numerical techniques.

At the same time, we observe a high interest in financial machine-learning, both at the level of pricing and price prediction, as on the level of risk management (“learning the client, learning the creditworthiness, etc.”).

We would like to connect both of these recent themes in this Special Issue, which will publish high-quality research papers on machine-learning in computational finance, and on advanced risk management. Combinations of these themes are especially interesting.

Prof. Cornelis W. Oosterlee
Dr. Lech A. Grzelak
Guest Editors

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