Applied topics in conic finance and credit risk

The research material available in this practice-oriented PhD thesis delves into two areas of financial mathematics, namely bid-ask pricing and credit risk.
Firstly, we investigate different applications of the conic finance theory, which aims to model the dynamics of financial markets in the presence of frictions and, in particular, of bid-ask spreads. These applications include estimating risk-neutral model parameters (and market data) starting from bid and ask security prices directly, as well as the deployment of machine learning techniques to price in markets with direction-dependent prices.
Secondly, we present applied work pertaining to the area of credit risk. In particular, the research conducted in this respect relates to estimating default probabilities of counterparties in the presence of insufficient, (partly) missing and/or untrustworthy credit default swap market data. For this purpose, the concepts of Wasserstein distance and Wasserstein barycenter play a pivotal role.