Regular biography
Blanka Nora Horvath is a Research Fellow in the Department of Mathematical Institute at the University of Oxford. Her research interests include mathematical and computational finance, with a focus on time-series forecasting, non-parametric option surfaces, and financial optimization. She has contributed to recent publications exploring topics such as arbitrage-free models, non-linear filtering, and robust financial strategies. Her work emphasizes the development of advanced methodologies for financial applications, with a particular emphasis on uncertainty-aware approaches and model-agnostic frameworks.
Scholar-generated biography
Blanka Horvath is a researcher in Mathematical Finance, focusing on the application of deep learning and stochastic analysis to financial modeling. Her work explores the pricing and calibration of volatility models, particularly in the context of rough volatility, and develops data-driven methods for market simulation and hedging. She has contributed to the understanding of skew behavior, functional central limit theorems, and the use of kernel mean embeddings for stochastic processes. Her research also addresses robust hedging strategies and the use of signatures in financial markets. Horvath's publications highlight the intersection of mathematical finance, machine learning, and stochastic calculus, with an emphasis on practical applications in financial risk management.